89,894 results on '"Hakan, As"'
Search Results
2. Transient studies using a TCAD and Allpix Squared combination approach
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Viera, Manuel A. Del Rio, Buschmann, Eric, Chauhan, Ankur, Dannheim, Dominik, Dort, Katharina, Eckstein, Doris, Feindt, Finn, Gregor, Ingrid-Maria, Hansen, Karsten, He, Yajun, Huth, Lennart, Mendes, Larissa, Mulyanto, Budi, Rastorguev, Daniil, Reckleben, Christian, Daza, Sara Ruiz, Schlaadt, Judith, Schütze, Paul, Simancas, Adriana, Snoeys, Walter, Spannagel, Simon, Stanitzki, Marcel, Velyka, Anastasiia, Vignola, Gianpiero, and Wennlöf, Håkan more...
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Physics - Instrumentation and Detectors - Abstract
The goal of the TANGERINE project is to develop the next generation of monolithic silicon pixel detectors using a 65 nm CMOS imaging process, which offers a higher logic density and overall lower power consumption compared to previously used processes. A combination of Technology Computer-Aided Design (TCAD) and Monte Carlo (MC) simulations is used to understand the physical processes within the sensing element and thus the overall performance of the pixel detector. The response of the sensors can then be tested in laboratory and test beam facilities and compared to simulation results. Transient simulations allow for studying the response of the sensor as a function of time, such as the signal produced after a charged particle passes through the sensor. The study of these signals is important to understand the magnitude and timing of the response from the sensors and improve upon them. While TCAD simulations are accurate, the time required to produce a single pulse is large compared to a combination of MC and TCAD simulations. In this work, a validation of the transient simulation approach and studies on charge collection are presented., Comment: TIPP 2023 Proceedings more...
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- 2025
Catalog
3. The H2M Monolithic Active Pixel Sensor - characterizing non-uniform in-pixel response in a 65 nm CMOS imaging technology
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Daza, Sara Ruiz, Ballabriga, Rafael, Buschmann, Eric, Campbell, Michael, Mohr, Raimon Casanova, Dannheim, Dominik, Dilg, Jona, Dorda, Ana, King, Finn, Feyens, Ono, Gadow, Philipp, Gregor, Ingrid-Maria, Hansen, Karsten, He, Yajun, Huth, Lennart, Kremastiotis, Iraklis, Lemoine, Corentin, Maffessanti, Stefano, Mendes, Larissa, Otarid, Younes, Reckleben, Christian, Rettie, Sébastien, Viera, Manuel Alejandro del Rio, Schlaadt, Judith, Simancas, Adriana, Snoeys, Walter, Spannagel, Simon, Vanat, Tomas, Velyka, Anastasiia, Vignola, Gianpiero, and Wennlöf, Håkan more...
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Physics - Instrumentation and Detectors - Abstract
The high energy physics community recently gained access to the TPSCo 65 nm ISC (Image Sensor CMOS), which enables a higher in-pixel logic density in monolithic active pixel sensors (MAPS) compared to processes with larger feature sizes. To explore this novel technology, the Hybrid-to-Monolithic (H2M) test chip has been designed and manufactured. The design followed a digital-on-top design workflow and ports a hybrid pixel-detector architecture, with digital pulse processing in each pixel, into a monolithic chip. The chip matrix consists of 64$\times$16 square pixels with a size of 35$\times$35 um2, and a total active area of approximately 1.25 um2. The chip has been successfully integrated into the Caribou DAQ system. It is fully functional, and the measured threshold dispersion and noise agree with the expectation from front-end simulations. However, a non-uniform in-pixel response related to the size and location of the n-wells in the analog circuitry has been observed in test beam measurements and will be discussed in this contribution. This asymmetry in the pixel response, enhanced by the 35 um pixel pitch - larger than in other prototypes - and certain features of the readout circuit, has not been observed in prototypes with smaller pixel pitches in this technology. more...
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- 2025
4. Multiple Instance Learning with Coarse-to-Fine Self-Distillation
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Wu, Shuyang, Qiu, Yifu, Nearchou, Ines P., Prost, Sandrine, Fallowfield, Jonathan A., Bilen, Hakan, and Kendall, Timothy J.
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Multiple Instance Learning (MIL) for whole slide image (WSI) analysis in computational pathology often neglects instance-level learning as supervision is typically provided only at the bag level. In this work, we present PathMIL, a framework designed to improve MIL through two perspectives: (1) employing instance-level supervision and (2) learning inter-instance contextual information on bag level. Firstly, we propose a novel Coarse-to-Fine Self-Distillation (CFSD) paradigm, to probe and distil a classifier trained with bag-level information to obtain instance-level labels which could effectively provide the supervision for the same classifier in a finer way. Secondly, to capture inter-instance contextual information in WSI, we propose Two-Dimensional Positional Encoding (2DPE), which encodes the spatial appearance of instances within a bag. We also theoretically and empirically prove the instance-level learnability of CFSD. PathMIL is evaluated on multiple benchmarking tasks, including subtype classification (TCGA-NSCLC), tumour classification (CAMELYON16), and an internal benchmark for breast cancer receptor status classification. Our method achieves state-of-the-art performance, with AUC scores of 0.9152 and 0.8524 for estrogen and progesterone receptor status classification, respectively, an AUC of 0.9618 for subtype classification, and 0.8634 for tumour classification, surpassing existing methods. more...
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- 2025
5. SQUASH: Serverless and Distributed Quantization-based Attributed Vector Similarity Search
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Oakley, Joe and Ferhatosmanoglu, Hakan
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Computer Science - Distributed, Parallel, and Cluster Computing ,Computer Science - Databases - Abstract
Vector similarity search presents significant challenges in terms of scalability for large and high-dimensional datasets, as well as in providing native support for hybrid queries. Serverless computing and cloud functions offer attractive benefits such as elasticity and cost-effectiveness, but are difficult to apply to data-intensive workloads. Jointly addressing these two main challenges, we present SQUASH, the first fully serverless vector search solution with rich support for hybrid queries. It features OSQ, an optimized and highly parallelizable quantization-based approach for vectors and attributes. Its segment-based storage mechanism enables significant compression in resource-constrained settings and offers efficient dimensional extraction operations. SQUASH performs a single distributed pass to guarantee the return of sufficiently many vectors satisfying the filter predicate, achieving high accuracy and avoiding redundant computation for vectors which fail the predicate. A multi-level search workflow is introduced to prune most vectors early to minimize the load on Function-as-a-Service (FaaS) instances. SQUASH is designed to identify and utilize retention of relevant data in re-used runtime containers, which eliminates redundant I/O and reduces costs. Finally, we demonstrate a new tree-based method for rapid FaaS invocation, enabling the bi-directional flow of data via request/response payloads. Experiments comparing SQUASH with state-of-the-art serverless vector search solutions and server-based baselines on vector search benchmarks confirm significant performance improvements at a lower cost. more...
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- 2025
6. The New Science of Unidentified Aerospace-Undersea Phenomena (UAP)
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Knuth, Kevin H., Ailleris, Philippe, Agrama, Hussein Ali, Ansbro, Eamonn, Cai, Tejin, Canuti, Thibaut, Cifone, Michael C., Cornet Jr., Walter Bruce, Courtade, Frédéric, Dolan, Richard, Domine, Laura, Dini, Luc, Friscourt, Baptiste, Graves, Ryan, Haines, Richard F., Hoffman, Richard, Kayal, Hakan, Little, Sarah, Nolan, Garry P., Powell, Robert, Rodeghier, Mark, Russo, Edoardo, Skafish, Peter, Strand, Erling, Swords, Michael, Szydagis, Matthew, Tedesco, Gerald T., Tedesco, John J., Teodorani, Massimo, Vallée, Jacques, Vaillant, Michaël, Villarroel, Beatriz, and Watters, Wesley A. more...
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Astrophysics - Instrumentation and Methods for Astrophysics ,Physics - Popular Physics - Abstract
After decades of dismissal and secrecy, it has become clear that a significant number of the world's governments take Unidentified Aerospace-Undersea Phenomena (UAP), formerly known as Unidentified Flying Objects (UFOs), seriously -- yet still seem to know little about them. As a result, these phenomena are increasingly attracting the attention of scientists around the world, some of whom have recently formed research efforts to monitor and scientifically study UAP. In this paper, we review and summarize approximately 20 historical government studies dating from 1933 to the present (in Scandinavia, WWII, US, Canada, France, Russia, China), several historical private research studies (France, UK, US), and both recent and current scientific research efforts (Ireland, Germany, Norway, Sweden, US). In doing so, our objective is to clarify the existing global and historical scientific narrative around UAP. Studies range from field station development and deployment to the collection and analysis of witness reports from around the world. We dispel the common misconception that UAPs are an American phenomenon and show that UAP can be, and have been, scientifically investigated. Our aim here is to enable future studies to draw on the great depth of prior documented experience., Comment: 164 pages, 7 figures more...
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- 2025
7. A sandbox study proposal for private and distributed health data analysis
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Brännvall, Rickard, Svensson, Hanna, Kaliyaperumal, Kannaki, Burden, Håkan, and Stenberg, Susanne
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Computer Science - Cryptography and Security ,Computer Science - Computers and Society ,Computer Science - Distributed, Parallel, and Cluster Computing ,68M14 (Primary) 92C60, 68P25, 68P20 (Secondary) ,K.4.1 ,J.3.2 ,H.2.8 ,D.4.6 - Abstract
This paper presents a sandbox study proposal focused on the distributed processing of personal health data within the Vinnova-funded SARDIN project. The project aims to develop the Health Data Bank (H\"alsodatabanken in Swedish), a secure platform for research and innovation that complies with the European Health Data Space (EHDS) legislation. By minimizing the sharing and storage of personal data, the platform sends analysis tasks directly to the original data locations, avoiding centralization. This approach raises questions about data controller responsibilities in distributed environments and the anonymization status of aggregated statistical results. The study explores federated analysis, secure multi-party aggregation, and differential privacy techniques, informed by real-world examples from clinical research on Parkinson's disease, stroke rehabilitation, and wound analysis. To validate the proposed study, numerical experiments were conducted using four open-source datasets to assess the feasibility and effectiveness of the proposed methods. The results support the methods for the proposed sandbox study by demonstrating that differential privacy in combination with secure aggregation techniques significantly improves the privacy-utility trade-off., Comment: 20 pages, 5 figures, 4 tables more...
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- 2025
8. Full Proportional Justified Representation
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Kalayci, Yusuf Hakan, Liu, Jiasen, and Kempe, David
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Computer Science - Computer Science and Game Theory ,Computer Science - Artificial Intelligence - Abstract
In multiwinner approval voting, forming a committee that proportionally represents voters' approval ballots is an essential task. The notion of justified representation (JR) demands that any large "cohesive" group of voters should be proportionally "represented". The "cohesiveness" is defined in different ways; two common ways are the following: (C1) demands that the group unanimously approves a set of candidates proportional to its size, while (C2) requires each member to approve at least a fixed fraction of such a set. Similarly, "representation" have been considered in different ways: (R1) the coalition's collective utility from the winning set exceeds that of any proportionally sized alternative, and (R2) for any proportionally sized alternative, at least one member of the coalition derives less utility from it than from the winning set. Three of the four possible combinations have been extensively studied: (C1)-(R1) defines Proportional Justified Representation (PJR), (C1)-(R2) defines Extended Justified Representation (EJR), (C2)-(R2) defines Full Justified Representation (FJR). All three have merits, but also drawbacks. PJR is the weakest notion, and perhaps not sufficiently demanding; EJR may not be compatible with perfect representation; and it is open whether a committee satisfying FJR can be found efficiently. We study the combination (C2)-(R1), which we call Full Proportional Justified Representation (FPJR). We investigate FPJR's properties and find that it shares PJR's advantages over EJR: several proportionality axioms (e.g. priceability, perfect representation) imply FPJR and PJR but not EJR. We also find that efficient rules like the greedy Monroe rule and the method of equal shares satisfy FPJR, matching a key advantage of EJR over FJR. However, the Proportional Approval Voting (PAV) rule may violate FPJR, so neither of EJR and FPJR implies the other., Comment: 18 pages, Accepted to AAMAS 25 more...
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- 2025
9. LegalGuardian: A Privacy-Preserving Framework for Secure Integration of Large Language Models in Legal Practice
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Demir, M. Mikail, Otal, Hakan T., and Canbaz, M. Abdullah
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Computer Science - Computation and Language ,Computer Science - Cryptography and Security ,Computer Science - Information Retrieval ,68T50, 68U35 ,I.2.7 ,K.5.0 ,I.7.0 - Abstract
Large Language Models (LLMs) hold promise for advancing legal practice by automating complex tasks and improving access to justice. However, their adoption is limited by concerns over client confidentiality, especially when lawyers include sensitive Personally Identifiable Information (PII) in prompts, risking unauthorized data exposure. To mitigate this, we introduce LegalGuardian, a lightweight, privacy-preserving framework tailored for lawyers using LLM-based tools. LegalGuardian employs Named Entity Recognition (NER) techniques and local LLMs to mask and unmask confidential PII within prompts, safeguarding sensitive data before any external interaction. We detail its development and assess its effectiveness using a synthetic prompt library in immigration law scenarios. Comparing traditional NER models with one-shot prompted local LLM, we find that LegalGuardian achieves a F1-score of 93% with GLiNER and 97% with Qwen2.5-14B in PII detection. Semantic similarity analysis confirms that the framework maintains high fidelity in outputs, ensuring robust utility of LLM-based tools. Our findings indicate that legal professionals can harness advanced AI technologies without compromising client confidentiality or the quality of legal documents., Comment: 10 pages, 3 figures more...
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- 2025
10. Finite Sample Analysis of Subspace Identification Methods
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He, Jiabao, Ziemann, Ingvar, Rojas, Cristian R., Qin, S. Joe, and Hjalmarsson, Håkan
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Electrical Engineering and Systems Science - Systems and Control - Abstract
As one of the mainstream approaches in system identification, subspace identification methods (SIMs) are known for their simple parameterization for MIMO systems and robust numerical properties. However, a comprehensive statistical analysis of SIMs remains an open problem. Amid renewed focus on identifying state-space models in the non-asymptotic regime, this work presents a finite sample analysis for a large class of open-loop SIMs. It establishes high-probability upper bounds for system matrices obtained via SIMs, and reveals that convergence rates for estimating Markov parameters and system matrices are $\mathcal{O}(1/\sqrt{N})$ up to logarithmic terms, in line with classical asymptotic results. Following the key steps of SIMs, we arrive at the above results by a three-step procedure. In Step 1, we begin with a parsimonious SIM (PARSIM) that uses least-squares regression to estimate multiple high-order ARX models in parallel. Leveraging a recent analysis of an individual ARX model, we obtain a union error bound for a bank of ARX models. Step 2 involves model reduction via weighted singular value decomposition (SVD), where we consider different data-dependent weighting matrices and use robustness results for SVD to obtain error bounds on extended controllability and observability matrices, respectively. The final Step 3 focuses on deriving error bounds for system matrices, where two different realization algorithms, the MOESP type and the Larimore type, are considered. Although our study initially focuses on PARSIM, the methodologies apply broadly across many variants of SIMs. more...
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- 2025
11. Low-Complexity Frequency-Dependent Linearizers Based on Parallel Bias-Modulus and Bias-ReLU Operations
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Linares, Deijany Rodriguez and Johansson, Håkan
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Electrical Engineering and Systems Science - Signal Processing - Abstract
This paper introduces low-complexity frequency-dependent (memory) linearizers designed to suppress nonlinear distortion in analog-to-digital interfaces. Two different linearizers are considered, based on nonlinearity models which correspond to sampling before and after the nonlinearity operations, respectively. The proposed linearizers are inspired by convolutional neural networks but have an order-of-magnitude lower implementation complexity compared to existing neural-network-based linearizer schemes. The proposed linearizers can also outperform the traditional parallel Hammerstein (as well as Wiener) linearizers even when the nonlinearities have been generated through a Hammerstein model. Further, a design procedure is proposed in which the linearizer parameters are obtained through matrix inversion. This eliminates the need for costly and time-consuming iterative nonconvex optimization which is traditionally associated with neural network training. The design effectively handles a wide range of wideband multi-tone signals and filtered white noise. Examples demonstrate significant signal-to-noise-and-distortion ratio (SNDR) improvements of some $20$--$30$ dB, as well as a lower implementation complexity than the Hammerstein linearizers. more...
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- 2024
12. Spatially-Adaptive Hash Encodings For Neural Surface Reconstruction
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Walker, Thomas, Mariotti, Octave, Vaxman, Amir, and Bilen, Hakan
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Positional encodings are a common component of neural scene reconstruction methods, and provide a way to bias the learning of neural fields towards coarser or finer representations. Current neural surface reconstruction methods use a "one-size-fits-all" approach to encoding, choosing a fixed set of encoding functions, and therefore bias, across all scenes. Current state-of-the-art surface reconstruction approaches leverage grid-based multi-resolution hash encoding in order to recover high-detail geometry. We propose a learned approach which allows the network to choose its encoding basis as a function of space, by masking the contribution of features stored at separate grid resolutions. The resulting spatially adaptive approach allows the network to fit a wider range of frequencies without introducing noise. We test our approach on standard benchmark surface reconstruction datasets and achieve state-of-the-art performance on two benchmark datasets. more...
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- 2024
13. Steady states of the spherically symmetric Vlasov-Poisson system as fixed points of a mass-preserving algorithm
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Andréasson, Håkan, Kunze, Markus, and Rein, Gerhard
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Mathematics - Analysis of PDEs ,General Relativity and Quantum Cosmology ,Mathematical Physics - Abstract
We give a new proof for the existence of spherically symmetric steady states to the Vlasov-Poisson system, following a strategy that has been used successfully to approximate axially symmetric solutions numerically, both to the Vlasov-Poisson system and to the Einstein-Vlasov system. There are several reasons why a mathematical analysis of this numerical scheme is important. A generalization of the present result to the case of flat axially symmetric solutions would prove that the steady states obtained numerically in \cite{AR3} do exist. Moreover, in the relativistic case the question whether a steady state can be obtained by this scheme seems to be related to its dynamical stability. This motivates the desire for a deeper understanding of this strategy., Comment: 11 pages more...
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- 2024
14. Optimal Transmission Switching and Busbar Splitting in Hybrid AC/DC Grids
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Bastianel, Giacomo, Vanin, Marta, Van Hertem, Dirk, and Ergun, Hakan
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Electrical Engineering and Systems Science - Systems and Control - Abstract
Driven by global climate goals, an increasing amount of Renewable Energy Sources (RES) is currently being installed worldwide. Especially in the context of offshore wind integration, hybrid AC/DC grids are considered to be the most effective technology to transmit this RES power over long distances. As hybrid AC/DC systems develop, they are expected to become increasingly complex and meshed as the current AC system. Nevertheless, there is still limited literature on how to optimize hybrid AC/DC topologies while minimizing the total power generation cost. For this reason, this paper proposes a methodology to optimize the steady-state switching states of transmission lines and busbar configurations in hybrid AC/DC grids. The proposed optimization model includes optimal transmission switching (OTS) and busbar splitting (BS), which can be applied to both AC and DC parts of hybrid AC/DC grids. To solve the problem, a scalable and exact nonlinear, non-convex model using a big M approach is formulated. In addition, convex relaxations and linear approximations of the model are tested, and their accuracy, feasibility, and optimality are analyzed. The numerical experiments show that a solution to the combined OTS/BS problem can be found in acceptable computation time and that the investigated relaxations and linearisations provide AC feasible results. more...
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- 2024
15. DepthCues: Evaluating Monocular Depth Perception in Large Vision Models
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Danier, Duolikun, Aygün, Mehmet, Li, Changjian, Bilen, Hakan, and Mac Aodha, Oisin
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Large-scale pre-trained vision models are becoming increasingly prevalent, offering expressive and generalizable visual representations that benefit various downstream tasks. Recent studies on the emergent properties of these models have revealed their high-level geometric understanding, in particular in the context of depth perception. However, it remains unclear how depth perception arises in these models without explicit depth supervision provided during pre-training. To investigate this, we examine whether the monocular depth cues, similar to those used by the human visual system, emerge in these models. We introduce a new benchmark, DepthCues, designed to evaluate depth cue understanding, and present findings across 20 diverse and representative pre-trained vision models. Our analysis shows that human-like depth cues emerge in more recent larger models. We also explore enhancing depth perception in large vision models by fine-tuning on DepthCues, and find that even without dense depth supervision, this improves depth estimation. To support further research, our benchmark and evaluation code will be made publicly available for studying depth perception in vision models., Comment: Website: https://danier97.github.io/depthcues/ more...
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- 2024
16. TabDeco: A Comprehensive Contrastive Framework for Decoupled Representations in Tabular Data
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Chen, Suiyao, Wu, Jing, Wang, Yunxiao, Ji, Cheng, Xie, Tianpei, Cociorva, Daniel, Sharps, Michael, Levasseur, Cecile, and Brunzell, Hakan
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
Representation learning is a fundamental aspect of modern artificial intelligence, driving substantial improvements across diverse applications. While selfsupervised contrastive learning has led to significant advancements in fields like computer vision and natural language processing, its adaptation to tabular data presents unique challenges. Traditional approaches often prioritize optimizing model architecture and loss functions but may overlook the crucial task of constructing meaningful positive and negative sample pairs from various perspectives like feature interactions, instance-level patterns and batch-specific contexts. To address these challenges, we introduce TabDeco, a novel method that leverages attention-based encoding strategies across both rows and columns and employs contrastive learning framework to effectively disentangle feature representations at multiple levels, including features, instances and data batches. With the innovative feature decoupling hierarchies, TabDeco consistently surpasses existing deep learning methods and leading gradient boosting algorithms, including XG-Boost, CatBoost, and LightGBM, across various benchmark tasks, underscoring its effectiveness in advancing tabular data representation learning. more...
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- 2024
17. Real almost reducibility of differentiable real quasi-periodic cocycles
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Chatal, Maxime, Chavaudret, Claire, and Eliasson, L. Hakan
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Mathematics - Dynamical Systems - Abstract
We prove that infinitely differentiable almost reducible quasi-periodic cocycles, under a Diophantine condition on the frequency vector, are almost reducible to a sequence of real constant cocycles with a sequence of real conjugations, up to a period doubling. more...
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- 2024
18. Protected chaos in a topological lattice
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Sahin, Haydar, Akgün, Hakan, Siu, Zhuo Bin, Rafi-Ul-Islam, S. M., Kong, Jian Feng, Jalil, Mansoor B. A., and Lee, Ching Hua
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Condensed Matter - Mesoscale and Nanoscale Physics ,Condensed Matter - Other Condensed Matter ,Nonlinear Sciences - Chaotic Dynamics - Abstract
The erratic nature of chaotic behavior is thought to erode the stability of periodic behavior, including topological oscillations. However, we discover that in the presence of chaos, non-trivial topology not only endures but also provides robust protection to chaotic dynamics within a topological lattice hosting non-linear oscillators. Despite the difficulty in defining topological invariants in non-linear settings, non-trivial topological robustness still persists in the parametric state of chaotic boundary oscillations. We demonstrate this interplay between chaos and topology by incorporating chaotic Chua's circuits into a topological Su-Schrieffer-Heeger (SSH) circuit. By extrapolating from the linear limit to deep into the non-linear regime, we find that distinctive correlations in the bulk and edge scroll dynamics effectively capture the topological origin of the protected chaos. Our findings suggest that topologically protected chaos can be robustly achieved across a broad spectrum of periodically-driven systems, thereby offering new avenues for the design of resilient and adaptable non-linear networks., Comment: 13 figures, 23 pages more...
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- 2024
19. Deterministic criticality & cluster dynamics hidden in the Game of Life
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Akgün, Hakan, Yan, Xianquan, Taşkıran, Tamer, Ibrahimi, Muhamet, Mobaraki, Arash, Lee, Ching Hua, and Jahangirov, Seymur
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Condensed Matter - Statistical Mechanics ,Physics - Data Analysis, Statistics and Probability ,82B43, 82B27, 37B15 - Abstract
Conway's Game of Life (GOL) is an epitome showing how complex dynamical behavior emerges from simple local interactions. Although it has often been found that GOL dynamics lies close to critical behavior, this system has never been studied in the context of a deterministic phase transitions and cluster dynamics. In this work, we study the deterministic critical behavior that emerges in the \textit{logistic} GOL: an extension of Conway's GOL with a parameter that alters the dynamics by expanding the binary state space into a Cantor set, but while maintaining the deterministic nature of the system. Upon tuning the parameter, we find that the logistic GOL comprises at least three types of asymptotic behavior, i.e phases, that are separated by two critical points. One critical point defines the boundary between a sparse-static and a sparse-dynamic asymptotic phase, whereas the other point marks a deterministic percolation transition between the sparse-dynamic and a third, dense-dynamic asymptotic phase. Moreover, we identify distinct power-law distributions of cluster sizes near the critical points, and discuss the underlying mechanisms that give rise to such critical behavior. Overall, our work highlights that scale invariance can emerge even when clusters in a system are generated by a purely deterministic process., Comment: 20 pages,16 figures more...
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- 2024
20. Mesoscopic theory of the Josephson junction
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Maldonado, Thomas J., Türeci, Hakan E., and Rodriguez, Alejandro W.
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Quantum Physics - Abstract
We derive a mesoscopic theory of the Josephson junction from non-relativistic scalar electrodynamics. Our theory reproduces the Josephson relations with the canonical current phase relation acquiring a weak second harmonic term, and it improves the standard lumped-element descriptions employed in circuit quantum electrodynamics by providing spatial resolution of the superconducting order parameter and electromagnetic field. By providing an ab initio derivation of the charge qubit Hamiltonian that relates traditionally free qubit parameters to geometric and material properties, we progress toward the quantum engineering of superconducting circuits at the subnanometer scale. more...
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- 2024
21. Weighted Null Space Fitting (WNSF): A Link between The Prediction Error Method and Subspace Identification
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He, Jiabao and Hjalmarsson, Håkan
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Electrical Engineering and Systems Science - Systems and Control - Abstract
Subspace identification method (SIM) has been proven to be very useful and numerically robust for estimating state-space models. However, it is in general not believed to be as accurate as the prediction error method (PEM). Conversely, PEM, although more accurate, comes with non-convex optimization problems and requires local non-linear optimization algorithms and good initialization points. This contribution proposes a weighted null space fitting (WNSF) method to identify a state-space model, combining some advantages of the two mainstream approaches aforementioned. It starts with the estimate of a non-parametric model using least-squares, and then the reduction to a state-space model in the observer canonical form is a multi-step least-squares procedure where each step consists of the solution of a quadratic optimization problem. Unlike SIM, which focuses on the range space of the extended observability matrix, WNSF estimates its null space, avoiding the need for singular value decomposition. Moreover, the statistically optimal weighting for the null space fitting problem is derived. It is conjectured that WNSF is asymptotically efficient, which is supported by a simulation study. more...
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- 2024
22. Model Order Reduction for Open Quantum Systems Based on Measurement-adapted Time-coarse Graining
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Fan, Wentao and Türeci, Hakan E.
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Quantum Physics - Abstract
Model order reduction encompasses mathematical techniques aimed at reducing the complexity of mathematical models in simulations while retaining the essential characteristics and behaviors of the original model. This is particularly useful in the context of large-scale dynamical systems, which can be computationally expensive to analyze and simulate. Here, we present a model order reduction technique to reduce the time complexity of open quantum systems, grounded in the principle of measurement-adapted coarse-graining. This method, governed by a coarse-graining time scale $\tau$ and the spectral band center $\omega_0$, organizes corrections to the lowest-order model which aligns with the RWA Hamiltonian in certain limits, and rigorously justifies the resulting effective quantum master equation (EQME). The focus on calculating to a high degree of accuracy only what can be resolved by the measurement introduces a principled regularization procedure to address singularities and generates low-stiffness models suitable for efficient long-time integration. Furthermore, the availability of the analytical form of the EQME parameters significantly boosts the interpretive capabilities of the method. As a demonstration, we derive the fourth-order EQME for a challenging problem related to the dynamics of a superconducting qubit under high-power dispersive readout in the presence of a continuum of dissipative waveguide modes. This derivation shows that the lowest-order terms align with previous results, while higher-order corrections suggest new phenomena. more...
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- 2024
23. FilMBot: A High-Speed Soft Parallel Robotic Micromanipulator
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Yu, Jiangkun, Bettahar, Houari, Kandemir, Hakan, and Zhou, Quan
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Computer Science - Robotics - Abstract
Soft robotic manipulators are generally slow despite their great adaptability, resilience, and compliance. This limitation also extends to current soft robotic micromanipulators. Here, we introduce FilMBot, a 3-DOF film-based, electromagnetically actuated, soft kinematic robotic micromanipulator achieving speeds up to 2117 $\deg$/s and 2456 $\deg$/s in $\alpha$ and $\beta$ angular motions, with corresponding linear velocities of 1.61 m/s and 1.92 m/s using a 4-cm needle end-effector, and 1.57 m/s along the Z axis. The robot can reach ~1.50 m/s in path-following tasks, operates at frequencies up to 30 Hz, and remains functional up to 50 Hz. It demonstrates high precision (~6.3 $\mu$m, or ~0.05% of its workspace) in small path-following tasks. The novel combination of the low-stiffness soft kinematic film structure and strong electromagnetic actuation in FilMBot opens new avenues for soft robotics. Furthermore, its simple construction and inexpensive, readily accessible components could broaden the application of micromanipulators beyond current academic and professional users., Comment: 12 pages, 15 figures more...
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- 2024
24. VQ-CNMP: Neuro-Symbolic Skill Learning for Bi-Level Planning
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Aktas, Hakan and Ugur, Emre
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Computer Science - Robotics ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
This paper proposes a novel neural network model capable of discovering high-level skill representations from unlabeled demonstration data. We also propose a bi-level planning pipeline that utilizes our model using a gradient-based planning approach. While extracting high-level representations, our model also preserves the low-level information, which can be used for low-level action planning. In the experiments, we tested the skill discovery performance of our model under different conditions, tested whether Multi-Modal LLMs can be utilized to label the learned high-level skill representations, and finally tested the high-level and low-level planning performance of our pipeline., Comment: 12 pages, 6 figures, Submitted to Conference on Robot Learning LEAP Workshop 2024 more...
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- 2024
25. Oppenheimer-Snyder type collapse for a collisionless gas
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Andréasson, Håkan and Rein, Gerhard
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General Relativity and Quantum Cosmology ,Mathematical Physics ,Mathematics - Analysis of PDEs - Abstract
In 1939, Oppenheimer and Snyder showed that the continued gravitational collapse of a self-gravitating matter distribution can result in the formation of a black hole, cf.~ \cite{OS}. In this paper, which has greatly influenced the evolution of ideas around the concept of a black hole, matter was modeled as dust, a fluid with pressure equal to zero. We prove that when the corresponding initial data are suitably approximated by data for a collisionless gas as modeled by the Vlasov equation, then a trapped surface forms before the corresponding solution to the Einstein-Vlasov system can develop a singularity and again a black hole arises. As opposed to the dust case the pressure does not vanish for such solutions. As a necessary starting point for the analysis, which is carried out in Painlev\'{e}-Gullstrand coordinates, we prove a local existence and uniqueness theorem for regular solutions together with a corresponding extension criterion. The latter result will also become useful when one perturbs dust solutions containing naked singularities in the Vlasov framework., Comment: 74 pages more...
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- 2024
26. A Fourth Planet in the Kepler-51 System Revealed by Transit Timing Variations
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Masuda, Kento, Libby-Roberts, Jessica E., Livingston, John H., Stevenson, Kevin B., Gao, Peter, Vissapragada, Shreyas, Fu, Guangwei, Han, Te, Greklek-McKeon, Michael, Mahadevan, Suvrath, Agol, Eric, Bello-Arufe, Aaron, Berta-Thompson, Zachory, Canas, Caleb I., Chachan, Yayaati, Hebb, Leslie, Hu, Renyu, Kawashima, Yui, Knutson, Heather A., Morley, Caroline V., Murray, Catriona A., Ohno, Kazumasa, Tokadjian, Armen, Zhang, Xi, Welbanks, Luis, Nixon, Matthew C., Freedman, Richard, Narita, Norio, Fukui, Akihiko, de Leon, Jerome P., Mori, Mayuko, Palle, Enric, Murgas, Felipe, Parviainen, Hannu, Esparza-Borges, Emma, Jontof-Hutter, Daniel, Collins, Karen A., Benni, Paul, Barkaoui, Khalid, Pozuelos, Francisco J., Gillon, Michael, Jehin, Emmanuel, Benkhaldoun, Zouhair, Hawley, Suzanne, Lin, Andrea S. J., Stefansson, Gudmundur, Bieryla, Allyson, Yilmaz, Mesut, Senavci, Hakan Volkan, Girardin, Eric, Marino, Giuseppe, and Wang, Gavin more...
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Astrophysics - Earth and Planetary Astrophysics - Abstract
Kepler-51 is a $\lesssim 1\,\mathrm{Gyr}$-old Sun-like star hosting three transiting planets with radii $\approx 6$-$9\,R_\oplus$ and orbital periods $\approx 45$-$130\,\mathrm{days}$. Transit timing variations (TTVs) measured with past Kepler and Hubble Space Telescope (HST) observations have been successfully modeled by considering gravitational interactions between the three transiting planets, yielding low masses and low mean densities ($\lesssim 0.1\,\mathrm{g/cm^3}$) for all three planets. However, the transit time of the outermost transiting planet Kepler-51d recently measured by the James Webb Space Telescope (JWST) 10 years after the Kepler observations is significantly discrepant from the prediction made by the three-planet TTV model, which we confirmed with ground-based and follow-up HST observations. We show that the departure from the three-planet model is explained by including a fourth outer planet, Kepler-51e, in the TTV model. A wide range of masses ($\lesssim M_\mathrm{Jup}$) and orbital periods ($\lesssim 10\,\mathrm{yr}$) are possible for Kepler-51e. Nevertheless, all the coplanar solutions found from our brute-force search imply masses $\lesssim 10\,M_\oplus$ for the inner transiting planets. Thus their densities remain low, though with larger uncertainties than previously estimated. Unlike other possible solutions, the one in which Kepler-51e is around the $2:1$ mean motion resonance with Kepler-51d implies low orbital eccentricities ($\lesssim 0.05$) and comparable masses ($\sim 5\,M_\oplus$) for all four planets, as is seen in other compact multi-planet systems. This work demonstrates the importance of long-term follow-up of TTV systems for probing longer period planets in a system., Comment: 48 pages, 26 figures, accepted for publication in AJ more...
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- 2024
27. electronCT -- An Imaging Technique Using Very-high Energy Electrons
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Schütze, Paul, Abel, Aenne, Burkart, Florian, de Silva, L. Malinda S., Dinter, Hannes, Dojan, Kevin, Herkert, Adrian, Jaster-Merz, Sonja, Kellermeier, Max Joseph, Kuropka, Willi, Mayet, Frank, Daza, Sara Ruiz, Spannagel, Simon, Vinatier, Thomas, and Wennlöf, Håkan more...
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Physics - Instrumentation and Detectors ,Physics - Accelerator Physics ,Physics - Medical Physics - Abstract
The electronCT technique is an imaging method based on the multiple Coulomb scattering of relativistic electrons and has potential applications in medical and industrial imaging. It utilizes a pencil beam of electrons in the very high energy electron (VHEE, 50-250 MeV) range and a single detection layer for the determination of the beam profile. The technique constitutes a projectional, two-dimensional imaging method and thus also qualifies for the tomographic reconstruction of samples. Given the simplicity of the technical setup and its location behind the sample, the electronCT technique has potential synergies with VHEE radiotherapy, making use of the same electron source for both treatment and diagnostics and thus being a candidate for in-situ imaging and patient localization. At the same time, several technical challenges arise from the measurement technique when applied for the imaging of living beings. Measurements performed at the ARES linear particle accelerator at an electron energy of 155 MeV using a mouse phantom and a Timepix3 silicon pixel detector assembly demonstrate the feasibility of this technique. Both projectional and tomographic reconstructions are presented and the potential and limits of the technology are discussed., Comment: 19 pages, 11 figures more...
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- 2024
28. AC-DC Power Systems Optimization with Droop Control Smooth Approximation
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Mohy-ud-din, Ghulam, Heidari, Rahmat, Geth, Frederik, Ergun, Hakan, and Uddin, S M Muslem
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Mathematics - Optimization and Control - Abstract
This paper addresses the challenges of embedding common droop control characteristics in ac-dc power system steady-state simulation and optimization problems. We propose a smooth approximation methodology to construct differentiable functions that encode the attributes of piecewise linear droop control with saturation. We transform the nonsmooth droop curves into smooth nonlinear equality constraints, solvable with Newton methods and interior point solvers. These constraints are then added to power flow, optimal power flow, and security-constrained optimal power flow problems in ac-dc power systems. The results demonstrate significant improvements in accuracy in terms of power sharing response, voltage regulation, and system efficiency, while outperforming existing mixed-integer formulations in computational efficiency., Comment: 6 pages, 8 figures, 2024 IEEE PES Australasian Universities Power Engineering Conference more...
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- 2024
29. Foundation and challenges in modelling Dilute Active Suspensions
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Fung, Lloyd, Caldag, Hakan O., and Bees, Martin A.
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Condensed Matter - Soft Condensed Matter ,Condensed Matter - Statistical Mechanics ,Physics - Biological Physics ,Physics - Fluid Dynamics - Abstract
Active suspensions, which consist of suspended self-propelling particles such as swimming microorganisms, often exhibit non-trivial transport properties. Continuum models are frequently employed to elucidate phenomena in active suspensions, such as shear trapping of bacteria, bacterial turbulence, and bioconvection patterns in suspensions of algae. Yet, these models are often empirically derived and may not always agree with the individual-based description of active particles. Here we establish a more rigorous foundation to fully develop a continuum model based on the respective microscopic dynamics through coarse-graining. All the assumptions needed to reach popular continuum models from a multi-particle Fokker-Planck equation, which governs the probability of the full configuration space, are explicitly presented. In the dilute limit, this approach leads to the mean-field model (a.k.a. Doi-Saintillan-Shelley model), which can be further reduced to a continuum equation for particle density. Moreover, we review the limitations and highlight the challenges related to continuum descriptions, including significant issues in implementing physical boundary conditions and the possible emergence of singular solutions., Comment: 14 pages more...
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- 2024
30. Analysis of Gene Regulatory Networks from Gene Expression Using Graph Neural Networks
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Otal, Hakan T., Subasi, Abdulhamit, Kurt, Furkan, Canbaz, M. Abdullah, and Uzun, Yasin
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Computer Science - Machine Learning ,Computer Science - Computational Engineering, Finance, and Science ,Computer Science - Social and Information Networks ,68T07, 05C90, 92C37, 62P10 ,I.2.1 ,I.2.4 ,J.3 - Abstract
Unraveling the complexities of Gene Regulatory Networks (GRNs) is crucial for understanding cellular processes and disease mechanisms. Traditional computational methods often struggle with the dynamic nature of these networks. This study explores the use of Graph Neural Networks (GNNs), a powerful approach for modeling graph-structured data like GRNs. Utilizing a Graph Attention Network v2 (GATv2), our study presents a novel approach to the construction and interrogation of GRNs, informed by gene expression data and Boolean models derived from literature. The model's adeptness in accurately predicting regulatory interactions and pinpointing key regulators is attributed to advanced attention mechanisms, a hallmark of the GNN framework. These insights suggest that GNNs are primed to revolutionize GRN analysis, addressing traditional limitations and offering richer biological insights. The success of GNNs, as highlighted by our model's reliance on high-quality data, calls for enhanced data collection methods to sustain progress. The integration of GNNs in GRN research is set to pioneer developments in personalized medicine, drug discovery, and our grasp of biological systems, bolstered by the structural analysis of networks for improved node and edge prediction., Comment: 24 Pages, 6 Figures more...
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- 2024
31. A New Perspective on ADHD Research: Knowledge Graph Construction with LLMs and Network Based Insights
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Otal, Hakan T., Faraone, Stephen V., and Canbaz, M. Abdullah
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Computer Science - Social and Information Networks ,Computer Science - Computation and Language ,68T30, 68T50, 92C30 ,I.2.4 ,I.2.7 ,J.3 - Abstract
Attention-Deficit/Hyperactivity Disorder (ADHD) is a challenging disorder to study due to its complex symptomatology and diverse contributing factors. To explore how we can gain deeper insights on this topic, we performed a network analysis on a comprehensive knowledge graph (KG) of ADHD, constructed by integrating scientific literature and clinical data with the help of cutting-edge large language models. The analysis, including k-core techniques, identified critical nodes and relationships that are central to understanding the disorder. Building on these findings, we curated a knowledge graph that is usable in a context-aware chatbot (Graph-RAG) with Large Language Models (LLMs), enabling accurate and informed interactions. Our knowledge graph not only advances the understanding of ADHD but also provides a powerful tool for research and clinical applications., Comment: 12 pages, 2 figures more...
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- 2024
32. Federated Learning in Adversarial Environments: Testbed Design and Poisoning Resilience in Cybersecurity
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Huang, Hao Jian, Iskandarov, Bekzod, Rahman, Mizanur, Otal, Hakan T., and Canbaz, M. Abdullah
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Computer Science - Cryptography and Security ,Computer Science - Distributed, Parallel, and Cluster Computing ,Computer Science - Machine Learning ,68T05, 68M14, 68M15 ,I.2.11 ,I.2.6 ,C.2.4 ,K.6.5 - Abstract
This paper presents the design and implementation of a Federated Learning (FL) testbed, focusing on its application in cybersecurity and evaluating its resilience against poisoning attacks. Federated Learning allows multiple clients to collaboratively train a global model while keeping their data decentralized, addressing critical needs for data privacy and security, particularly in sensitive fields like cybersecurity. Our testbed, built using the Flower framework, facilitates experimentation with various FL frameworks, assessing their performance, scalability, and ease of integration. Through a case study on federated intrusion detection systems, we demonstrate the testbed's capabilities in detecting anomalies and securing critical infrastructure without exposing sensitive network data. Comprehensive poisoning tests, targeting both model and data integrity, evaluate the system's robustness under adversarial conditions. Our results show that while federated learning enhances data privacy and distributed learning, it remains vulnerable to poisoning attacks, which must be mitigated to ensure its reliability in real-world applications., Comment: 7 pages, 4 figures more...
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- 2024
33. X-ray Fluoroscopy Guided Localization and Steering of Medical Microrobots through Virtual Enhancement
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Alabay, Husnu Halid, Le, Tuan-Anh, and Ceylan, Hakan
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Computer Science - Robotics - Abstract
In developing medical interventions using untethered milli- and microrobots, ensuring safety and effectiveness relies on robust methods for detection, real-time tracking, and precise localization within the body. However, the inherent non-transparency of the human body poses a significant obstacle, limiting robot detection primarily to specialized imaging systems such as X-ray fluoroscopy, which often lack crucial anatomical details. Consequently, the robot operator (human or machine) would encounter severe challenges in accurately determining the location of the robot and steering its motion. This study explores the feasibility of circumventing this challenge by creating a simulation environment that contains the precise digital replica (virtual twin) of a model microrobot operational workspace. Synchronizing coordinate systems between the virtual and real worlds and continuously integrating microrobot position data from the image stream into the virtual twin allows the microrobot operator to control navigation in the virtual world. We validate this concept by demonstrating the tracking and steering of a mobile magnetic robot in confined phantoms with high temporal resolution (< 100 ms, with an average of ~20 ms) visual feedback. Additionally, our object detection-based localization approach offers the potential to reduce overall patient exposure to X-ray doses during continuous microrobot tracking without compromising tracking accuracy. Ultimately, we address a critical gap in developing image-guided remote interventions with untethered medical microrobots, particularly for near-future applications in animal models and human patients. more...
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- 2024
34. LLM Honeypot: Leveraging Large Language Models as Advanced Interactive Honeypot Systems
- Author
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Otal, Hakan T. and Canbaz, M. Abdullah
- Subjects
Computer Science - Cryptography and Security ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language ,Computer Science - Machine Learning ,Computer Science - Networking and Internet Architecture ,68T50, 68M10 ,I.2.7 ,D.4.6 ,K.6.5 - Abstract
The rapid evolution of cyber threats necessitates innovative solutions for detecting and analyzing malicious activity. Honeypots, which are decoy systems designed to lure and interact with attackers, have emerged as a critical component in cybersecurity. In this paper, we present a novel approach to creating realistic and interactive honeypot systems using Large Language Models (LLMs). By fine-tuning a pre-trained open-source language model on a diverse dataset of attacker-generated commands and responses, we developed a honeypot capable of sophisticated engagement with attackers. Our methodology involved several key steps: data collection and processing, prompt engineering, model selection, and supervised fine-tuning to optimize the model's performance. Evaluation through similarity metrics and live deployment demonstrated that our approach effectively generates accurate and informative responses. The results highlight the potential of LLMs to revolutionize honeypot technology, providing cybersecurity professionals with a powerful tool to detect and analyze malicious activity, thereby enhancing overall security infrastructure., Comment: 6 pages, 5 figures more...
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- 2024
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35. D3-GNN: Dynamic Distributed Dataflow for Streaming Graph Neural Networks
- Author
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Guliyev, Rustam, Haldar, Aparajita, and Ferhatosmanoglu, Hakan
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Computer Science - Distributed, Parallel, and Cluster Computing ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
Graph Neural Network (GNN) models on streaming graphs entail algorithmic challenges to continuously capture its dynamic state, as well as systems challenges to optimize latency, memory, and throughput during both inference and training. We present D3-GNN, the first distributed, hybrid-parallel, streaming GNN system designed to handle real-time graph updates under online query setting. Our system addresses data management, algorithmic, and systems challenges, enabling continuous capturing of the dynamic state of the graph and updating node representations with fault-tolerance and optimal latency, load-balance, and throughput. D3-GNN utilizes streaming GNN aggregators and an unrolled, distributed computation graph architecture to handle cascading graph updates. To counteract data skew and neighborhood explosion issues, we introduce inter-layer and intra-layer windowed forward pass solutions. Experiments on large-scale graph streams demonstrate that D3-GNN achieves high efficiency and scalability. Compared to DGL, D3-GNN achieves a significant throughput improvement of about 76x for streaming workloads. The windowed enhancement further reduces running times by around 10x and message volumes by up to 15x at higher parallelism., Comment: 14 pages, 7 figures, published at VLDB'24 more...
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- 2024
- Full Text
- View/download PDF
36. Data-informativity conditions for structured linear systems with implications for dynamic networks
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Hof, Paul M. J. Van den, Shi, Shengling, Fonken, Stefanie J. M., Ramaswamy, Karthik R., Hjalmarsson, Håkan, and Dankers, Arne G.
- Subjects
Electrical Engineering and Systems Science - Systems and Control - Abstract
When estimating models of a multivariable dynamic system, a typical condition for consistency is to require the input signals to be persistently exciting, which is guaranteed if the input spectrum is positive definite for a sufficient number of frequencies. In this paper it is investigated how such a condition can be relaxed by exploiting prior structural information on the multivariable system, such as structural zero elements in the transfer matrix or entries that are a priori known and therefore not parametrized. It is shown that in particular situations the data-informativity condition can be decomposed into different MISO (multiple input single output) situations, leading to relaxed conditions for the MIMO (multiple input multiple output) model. When estimating a single module in a linear dynamic network, the data-informativity conditions can generically be formulated as path-based conditions on the graph of the network. The new relaxed conditions for data-informativity will then also lead to relaxed path-based conditions on the network graph. Additionally the new expressions are shown to be closely related to earlier derived conditions for (generic) single module identifiability., Comment: 16 pages, 4 figures more...
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- 2024
37. A neural processing approach to quantum state discrimination
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Khan, Saeed A., Hu, Fangjun, Angelatos, Gerasimos, Hatridge, Michael, and Türeci, Hakan E.
- Subjects
Quantum Physics - Abstract
Although linear quantum amplification has proven essential to the processing of weak quantum signals, extracting higher-order quantum features such as correlations in principle demands nonlinear operations. However, nonlinear processing of quantum signals is often associated with non-idealities and excess noise, and absent a general framework to harness nonlinearity, such regimes are typically avoided. Here we present a framework to uncover general quantum signal processing principles of a broad class of bosonic quantum nonlinear processors (QNPs), inspired by a remarkably analogous paradigm in nature: the processing of environmental stimuli by nonlinear, noisy neural ensembles, to enable perception. Using a quantum-coherent description of a QNP monitoring a quantum signal source, we show that quantum nonlinearity can be harnessed to calculate higher-order features of an incident quantum signal, concentrating them into linearly-measurable observables, a transduction not possible using linear amplifiers. Secondly, QNPs provide coherent nonlinear control over quantum fluctuations including their own added noise, enabling noise suppression in an observable without suppressing transduced information, a paradigm that bears striking similarities to optimal neural codings that allow perception even under highly stochastic neural dynamics. Unlike the neural case, we show that QNP-engineered noise distributions can exhibit non-classical correlations, providing a new means to harness resources such as entanglement. Finally, we show that even simple QNPs in realistic measurement chains can provide enhancements of signal-to-noise ratio for practical tasks such as quantum state discrimination. Our work provides pathways to utilize nonlinear quantum systems as general computation devices, and enables a new paradigm for nonlinear quantum information processing., Comment: 25+39 pages, 10+7 figures, and 97 references more...
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- 2024
38. Investigating the Effect of Internet-Based Applications on Secondary School Students' Academic Achievement in Science, Motivation and Awareness of Web 2.0 Tools
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Merve Güder, Hakan Akçay, and Tufan Inaltekin
- Abstract
In this study, the effect of internet-based applications on the academic achievement, motivation, and awareness of Web 2.0 tools of 6th grade middle school students on "Matter and Heat" was examined. The study group consisted of 73 (experimental: 50, control: 23) 6th grade students from a public school in Istanbul, Turkey. The study was conducted with an experimental design with pretest-posttest control group among quantitative research models. In the experimental group, science lessons were taught with the support of web 2.0 tools such as Nearpod, Canva and Quizizz, while in the control group, no additional application was made and the lessons were taught as specified in the curriculum. The data of the study were collected with the "Motivation Scale in Science Education", "Matter and Heat Achievement Test" and "Awareness Scale for Web 2.0 Tools". T-test and one-way factor analysis (ANCOVA) test were used to analyze the data. The results of this study showed that the academic achievement test scores of the experimental group students were higher than the control group and there was a significant difference between the academic achievement test scores of the experimental and control groups. The results showed that the science motivation scores showed a significant difference in favor of the experimental group and the science motivation scores of the experimental group students who were supported with web-based applications were higher than the control group. In addition, according to the results of the one-way analysis of covariance regarding the awareness of web 2.0 tools, there was a significant difference between the experimental group and the control group in favor of the experimental group in the post-test scores. In this study, the importance of planning and implementing science lessons supported by internet-based applications at the secondary school level was revealed. more...
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- 2024
39. Intrinsic Motivation of Distance Learners in Higher Education Institutions
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Hakan Kilinc and Nil Goksel
- Abstract
As information and communication technologies and learner characteristics in higher education develop, so do distance education methods, which are implemented at various levels by higher education institutions. The involvement of students in the learning process is one of the most crucial factors to consider throughout the distance education application transformation, which might change depending on the conditions. At this point, it can be stated that the intrinsic motivation levels of learners involved in distance learning play a decisive role in participating in learning processes. Therefore, examining the intrinsic motivation levels of distance learners is seen as an element that needs to be emphasized. This justifies the study's goal, which is to analyze the intrinsic motivation levels of students who get distance education from higher education institutions concerning factors including age, gender, employment, and educational status. The relational survey model, one of the general survey models, was utilized in this study, which included 327 distance learners. In terms of distance education applications, the findings of the study have a guiding nature for the administrators working in higher education institutions. The analyses carried out revealed that there were no significant differences in the intrinsic motivation levels of distance learners according to their gender, employment situation, or level of education. Furthermore, it has been found that as people get older, their intrinsic incentive for learning grows. A list of recommendations based on the data gathered within this study is provided at the end. more...
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- 2024
40. Education of Refugee Children within the Intref Project Framework
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Maja Kerneža, Dejan Zemljak, Metka Kordigel Aberšek, Boris Aberšek, Polona Legvart, Helena Konšak, Hakan Sari, Ildiko Hanuliakova, Loreta Huber, Inga Laurusone, Kübra Terzioglu, and Metin Kilic
- Abstract
Amidst growing migratory movements and hurdles of assimilation, the INTREF initiative strives to craft a comprehensive strategy for the schooling of refugee children, melding e-learning, emotional and social support, along with adaptable teaching methods. This endeavor learns on principles like linguistic diversity, cross-cultural skills, and customizing the educational journey, crucial for assimilation and triumph within academic settings. Studies indicate the indispensability of bespoke linguistic assistance, cognizance of cultural variances, and personalized educational tactics for the seamless school transition and societal assimilation of children in refuge. The project devised a survey instrument aimed at evaluating the baseline educational scenario in the participating nations and formulating education plans tailored to specific needs. This survey zeroes on four pivotal areas: linguistic proficiency, cross-cultural consciousness, embracing diversity, and pedagogical customization. Feedback from 31 students, 30 teachers and 28 parents revealed a pressing need for augmented linguistic aid in Slovenia, heightened cross-cultural understanding, and classroom method modification to enrich the academic experiences of culturally diverse children. The findings also underscore a discernible discrepancy between the perspectives of educators versus those of parents and children. The insights from this survey lay the groundwork for creating innovative instructional units and resources, finely adapted to the needs of children in refuge. By forging links between theoretical insights and practical application, as well as among various educational stakeholders, INTREF is ready to enrich the discourse and practices surrounding inclusivity, and endeavor made increasingly pertinent by the recent global disruptions, including the migratory dilemma and the COVID-19 outbreak. more...
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- 2024
41. Investigating the Effects of Different Model Based Inquiries on Students' Science Achievement, Scientific Process Skills and Motivation
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Tugba Geçgil and Hakan Akçay
- Abstract
In this research, the effects of using Model-Based and Argumentation-Supported Model-Based Inquiry methods on 6th-grade middle school students' knowledge, scientific process skills, and motivation regarding the subject of sound and its properties were examined according to the current curriculum. A total of 77 students attending a state school participated in the study that employed a mixed research design. In the semi-experimental study, two experimental groups and one control group were used. Lessons were taught according to the model-based inquiry method supported by argumentation in the first experimental group, according to the model-based inquiry method in the second experimental group, and according to the current curriculum in the control group. In the research, achievement tests, scientific process skills tests, and motivation scales were administered as pre-tests and post-tests for data collection. The obtained data were analyzed using One-Way Analysis of Covariance (ANCOVA). According to the obtained results, it has been determined that the Model-Based and Argumentation-Supported Model-Based Inquiry methods significantly differ from the current curriculum in terms of student achievement and motivation. Furthermore, it has been observed that the Argumentation-Supported Model-Based Inquiry method is more effective than the Model-Based Inquiry method in enhancing students' development of scientific process skills. more...
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- 2024
42. An Analysis of the Effect of Using Collaborative Story Maps on Story Writing Skills
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I?lhan Polat and Hakan Dedeoglu
- Abstract
The aim of the study is to investigate the effect of story writing on the story writing skills of primary school students with the collaborative story map method. This quantitative study has a quasi-experimental design with a pretest-posttest comparison group. The study group consists of 131 primary school 2nd-grade students, 60 boys and 71 girls. There are two experimental groups and one control group in the study. The study lasted 12 weeks and 2 class hours per week. In the collaborative story map writing group, story writing was practiced with a collaborative story map. In the individual story map writing group, story writing work according to the individual story map. In the control group, a free story writing activity was conducted. The data were collected through the Story Grammar Elements Rating Scale. T-Test and ANOVA were used to analyze the data. In conclusion, writing stories with primary school students in the method of collaborative mapping and individual story mapping improves students' story writing skills. However, there is no difference between preparing a story map collaboratively or individually in terms of story writing skills. more...
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- 2024
43. The Impact of Using Educational and Digital Games on Middle School Students Science Achievement
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Asli Bahar Ivgin and Hakan Akcay
- Abstract
Game-based learning has attracted great interest in science education as an effective way to increase student achievement. Most studies in this field have focused on digital or non-digital games. In the literature, some studies generally compare educational games with traditional teaching methods. More studies need to be conducted to compare the effects of digital and non-digital games on achievement. For this reason, the study's primary purpose is to examine the impact of different types of games, namely educational and digital games, and their combinations on students' academic achievement and views on the learning process. In this context, the researcher used three different methods to be applied to three experimental groups and one control group. The research was carried out on 77 5th-grade students studying in a public school in Turkey. Both quantitative and qualitative research methods were used in the quasi-experimental design. Data were obtained through the 'Human and Environment Unit Achievement Test' and semi-structured interviews. The results showed that students in the educational and digital games sections were significantly better at science achievement than students in the textbook-oriented section. No significant difference was found between the digital game-based and educational game-based students in terms of achievement. The academic achievement of the group in which these two game types were used together was higher than the others. In addition, most students were satisfied with the using educational and digital games in science lessons and found the games fun and motivating. more...
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- 2024
44. English Language Learners' Experiences of Using Interactive Videos in EFL Listening
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Arif Bakla and Hakan Demiröz
- Abstract
As blended and online courses are becoming more prevalent, there is need for research into how digital tools might help teachers increase learner motivation and engagement in online learning. This qualitative case study explores learners' perceptions of interactive videos, with a particular focus on perceived levels of learner motivation and engagement, along with the apparent value of the interactive elements in providing feedback and improving listening comprehension. The participants were 37 freshmen English as a Foreign Language (EFL) learners, majoring in English language teaching. The data were collected through semi-structured interviews with six participants and the learning analytics module of the interactive video software. The six interview participants, along with 31 others, also responded to reflective journal prompts. The participants reported that interactive videos provided them with meaningful input and timely feedback, and the perceived improvement in their listening skills motivated them. Most of the participants reported that they preferred interactive components for promoting higher engagement, but they also highlighted that having frequent interactive elements distracted them from the content. more...
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- 2024
45. An Investigation into the Effect of Different Missing Data Imputation Methods on IRT-Based Differential Item Functioning
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Fatma Ünal and Hakan Kogar
- Abstract
The purpose of this study is to examine the effect of missing data imputation methods, namely regression imputation (RI), multiple imputation (MI) and k-nearest neighbor (kNN) on differential item functioning (DIF). In this regard, the datasets used in the research were created by deleting some of the data via the missing completely at random mechanism from the complete datasets obtained from 600 students in Türkiye, the United Kingdom, the USA, New Zealand and Australia, who answered booklets 14 and 15 from the PISA 2018 science literacy test. Data imputation was applied to the datasets through missing data using RI, MI and kNN methods and DIF analysis was performed on all datasets in terms of language and gender variables via Lord's X[superscript 2] method, Raju's area measurement method and item response theory likelihood ratio method. DIF results from the complete datasets were taken as a reference and they were compared with the results from other datasets. As a result of the research, values close to 10% of accurate imputation were achieved in the RI method depending on language and gender variables. In MI and kNN methods, results closest to the complete datasets were obtained at a rate of 5% depending on the language variable. In the MI method, inaccurate results were obtained in all proportions in terms of the gender variable. For the gender variable, the kNN method gave accurate results at rates of 5% and 10%. [The page range (445-462) listed on the PDF is incorrect. The correct page range is 445-463.] more...
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- 2024
46. The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset.
- Author
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Rudie, Jeffrey, Lin, Hui-Ming, Ball, Robyn, Jalal, Sabeena, Prevedello, Luciano, Nicolaou, Savvas, Marinelli, Brett, Flanders, Adam, Magudia, Kirti, Shih, George, Davis, Melissa, Mongan, John, Chang, Peter, Berger, Ferco, Hermans, Sebastiaan, Law, Meng, Richards, Tyler, Grunz, Jan-Peter, Kunz, Andreas, Mathur, Shobhit, Galea-Soler, Sandro, Chung, Andrew, Afat, Saif, Kuo, Chin-Chi, Aweidah, Layal, Villanueva Campos, Ana, Somasundaram, Arjuna, Sanchez Tijmes, Felipe, Jantarangkoon, Attaporn, Kayat Bittencourt, Leonardo, Brassil, Michael, El Hajjami, Ayoub, Dogan, Hakan, Becircic, Muris, Bharatkumar, Agrahara, Júdice de Mattos Farina, Eduardo, and Colak, Errol more...
- Subjects
CT ,Kidney ,Large Bowel ,Liver ,Small Bowel ,Spleen ,Trauma ,Humans ,Abdominal Injuries ,Tomography ,X-Ray Computed ,Male ,Female ,Adult - Abstract
Supplemental material is available for this article.
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- 2024
47. InstanSeg: an embedding-based instance segmentation algorithm optimized for accurate, efficient and portable cell segmentation
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Goldsborough, Thibaut, Philps, Ben, O'Callaghan, Alan, Inglis, Fiona, Leplat, Leo, Filby, Andrew, Bilen, Hakan, and Bankhead, Peter
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Cell and nucleus segmentation are fundamental tasks for quantitative bioimage analysis. Despite progress in recent years, biologists and other domain experts still require novel algorithms to handle increasingly large and complex real-world datasets. These algorithms must not only achieve state-of-the-art accuracy, but also be optimized for efficiency, portability and user-friendliness. Here, we introduce InstanSeg: a novel embedding-based instance segmentation pipeline designed to identify cells and nuclei in microscopy images. Using six public cell segmentation datasets, we demonstrate that InstanSeg can significantly improve accuracy when compared to the most widely used alternative methods, while reducing the processing time by at least 60%. Furthermore, InstanSeg is designed to be fully serializable as TorchScript and supports GPU acceleration on a range of hardware. We provide an open-source implementation of InstanSeg in Python, in addition to a user-friendly, interactive QuPath extension for inference written in Java. Our code and pre-trained models are available at https://github.com/instanseg/instanseg ., Comment: 12 pages,6 figures more...
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- 2024
48. A Multi-Frequency Iterative Method for Reconstruction of Rough Surfaces Separating Two Penetrable Media
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Sefer, Ahmet, Yapar, Ali, and Bagci, Hakan
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Mathematics - Numerical Analysis ,45Q05, 47A52, 47J06, 65R30, 78A46 - Abstract
A numerical scheme that uses multi-frequency Newton iterations to reconstruct a rough surface profile between two dielectric media is proposed. At each frequency sample, the scheme employs Newton iterations to solve the nonlinear inverse scattering problem. At every iteration, the Newton step is computed by solving a linear system that involves the Frechet derivative of the integral operator, which represents the scattered fields, and the difference between these fields and the measurements. This linear system is regularized using the Tikhonov method. The multi-frequency data is accounted for in a recursive manner. More specifically, the profile reconstructed at a given frequency is used as an initial guess for the iterations at the next frequency. The effectiveness of the proposed method is validated through numerical examples, which demonstrate its ability to accurately reconstruct surface profiles even in the presence of measurement noise. The results also show the superiority of the multi-frequency approach over single-frequency reconstructions, particularly in terms of handling surfaces with sharp variations., Comment: 33 Pages, 11 figures more...
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- 2024
49. Simulating Monolithic Active Pixel Sensors: A Technology-Independent Approach Using Generic Doping Profiles
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Wennlöf, Håkan, Dannheim, Dominik, Viera, Manuel Del Rio, Dort, Katharina, Eckstein, Doris, Feindt, Finn, Gregor, Ingrid-Maria, Huth, Lennart, Lachnit, Stephan, Mendes, Larissa, Rastorguev, Daniil, Daza, Sara Ruiz, Schütze, Paul, Simancas, Adriana, Snoeys, Walter, Spannagel, Simon, Stanitzki, Marcel, Tomal, Alessandra, Velyka, Anastasiia, and Vignola, Gianpiero more...
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Physics - Instrumentation and Detectors - Abstract
The optimisation of the sensitive region of CMOS sensors with complex non-uniform electric fields requires precise simulations, and this can be achieved by a combination of electrostatic field simulations and Monte Carlo methods. This paper presents the guiding principles of such simulations, using a CMOS pixel sensor with a small collection electrode and a high-resistivity epitaxial layer as an example. The full simulation workflow is described, along with possible pitfalls and how to avoid them. For commercial CMOS processes, detailed doping profiles are confidential, but the presented method provides an optimisation tool that is sufficiently accurate to investigate sensor behaviour and trade-offs of different sensor designs without knowledge of proprietary information. The workflow starts with detailed electric field finite element method simulations in TCAD, using generic doping profiles. Examples of the effect of varying different parameters of the simulated sensor are shown, as well as the creation of weighting fields, and transient pulse simulations. The fields resulting from TCAD simulations can be imported into the Allpix Squared Monte Carlo simulation framework, which enables high-statistics simulations, including modelling of stochastic fluctuations from the underlying physics processes of particle interaction. Example Monte Carlo simulation setups are presented and the different parts of a simulation chain are described. Simulation studies from small collection electrode CMOS sensors are presented, and example results are shown for both single sensors and multiple sensors in a test beam telescope configuration. The studies shown are those typically performed on sensor prototypes in test beam campaigns, and a comparison is made to test beam data, showing a maximum deviation of 4% and demonstrating that the approach is viable for generating realistic results., Comment: 22 pages, 25 figures, submitted to Nuclear Instruments and Methods in Physics Research, Section A more...
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- 2024
- Full Text
- View/download PDF
50. The Llama 3 Herd of Models
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Grattafiori, Aaron, Dubey, Abhimanyu, Jauhri, Abhinav, Pandey, Abhinav, Kadian, Abhishek, Al-Dahle, Ahmad, Letman, Aiesha, Mathur, Akhil, Schelten, Alan, Vaughan, Alex, Yang, Amy, Fan, Angela, Goyal, Anirudh, Hartshorn, Anthony, Yang, Aobo, Mitra, Archi, Sravankumar, Archie, Korenev, Artem, Hinsvark, Arthur, Rao, Arun, Zhang, Aston, Rodriguez, Aurelien, Gregerson, Austen, Spataru, Ava, Roziere, Baptiste, Biron, Bethany, Tang, Binh, Chern, Bobbie, Caucheteux, Charlotte, Nayak, Chaya, Bi, Chloe, Marra, Chris, McConnell, Chris, Keller, Christian, Touret, Christophe, Wu, Chunyang, Wong, Corinne, Ferrer, Cristian Canton, Nikolaidis, Cyrus, Allonsius, Damien, Song, Daniel, Pintz, Danielle, Livshits, Danny, Wyatt, Danny, Esiobu, David, Choudhary, Dhruv, Mahajan, Dhruv, Garcia-Olano, Diego, Perino, Diego, Hupkes, Dieuwke, Lakomkin, Egor, AlBadawy, Ehab, Lobanova, Elina, Dinan, Emily, Smith, Eric Michael, Radenovic, Filip, Guzmán, Francisco, Zhang, Frank, Synnaeve, Gabriel, Lee, Gabrielle, Anderson, Georgia Lewis, Thattai, Govind, Nail, Graeme, Mialon, Gregoire, Pang, Guan, Cucurell, Guillem, Nguyen, Hailey, Korevaar, Hannah, Xu, Hu, Touvron, Hugo, Zarov, Iliyan, Ibarra, Imanol Arrieta, Kloumann, Isabel, Misra, Ishan, Evtimov, Ivan, Zhang, Jack, Copet, Jade, Lee, Jaewon, Geffert, Jan, Vranes, Jana, Park, Jason, Mahadeokar, Jay, Shah, Jeet, van der Linde, Jelmer, Billock, Jennifer, Hong, Jenny, Lee, Jenya, Fu, Jeremy, Chi, Jianfeng, Huang, Jianyu, Liu, Jiawen, Wang, Jie, Yu, Jiecao, Bitton, Joanna, Spisak, Joe, Park, Jongsoo, Rocca, Joseph, Johnstun, Joshua, Saxe, Joshua, Jia, Junteng, Alwala, Kalyan Vasuden, Prasad, Karthik, Upasani, Kartikeya, Plawiak, Kate, Li, Ke, Heafield, Kenneth, Stone, Kevin, El-Arini, Khalid, Iyer, Krithika, Malik, Kshitiz, Chiu, Kuenley, Bhalla, Kunal, Lakhotia, Kushal, Rantala-Yeary, Lauren, van der Maaten, Laurens, Chen, Lawrence, Tan, Liang, Jenkins, Liz, Martin, Louis, Madaan, Lovish, Malo, Lubo, Blecher, Lukas, Landzaat, Lukas, de Oliveira, Luke, Muzzi, Madeline, Pasupuleti, Mahesh, Singh, Mannat, Paluri, Manohar, Kardas, Marcin, Tsimpoukelli, Maria, Oldham, Mathew, Rita, Mathieu, Pavlova, Maya, Kambadur, Melanie, Lewis, Mike, Si, Min, Singh, Mitesh Kumar, Hassan, Mona, Goyal, Naman, Torabi, Narjes, Bashlykov, Nikolay, Bogoychev, Nikolay, Chatterji, Niladri, Zhang, Ning, Duchenne, Olivier, Çelebi, Onur, Alrassy, Patrick, Zhang, Pengchuan, Li, Pengwei, Vasic, Petar, Weng, Peter, Bhargava, Prajjwal, Dubal, Pratik, Krishnan, Praveen, Koura, Punit Singh, Xu, Puxin, He, Qing, Dong, Qingxiao, Srinivasan, Ragavan, Ganapathy, Raj, Calderer, Ramon, Cabral, Ricardo Silveira, Stojnic, Robert, Raileanu, Roberta, Maheswari, Rohan, Girdhar, Rohit, Patel, Rohit, Sauvestre, Romain, Polidoro, Ronnie, Sumbaly, Roshan, Taylor, Ross, Silva, Ruan, Hou, Rui, Wang, Rui, Hosseini, Saghar, Chennabasappa, Sahana, Singh, Sanjay, Bell, Sean, Kim, Seohyun Sonia, Edunov, Sergey, Nie, Shaoliang, Narang, Sharan, Raparthy, Sharath, Shen, Sheng, Wan, Shengye, Bhosale, Shruti, Zhang, Shun, Vandenhende, Simon, Batra, Soumya, Whitman, Spencer, Sootla, Sten, Collot, Stephane, Gururangan, Suchin, Borodinsky, Sydney, Herman, Tamar, Fowler, Tara, Sheasha, Tarek, Georgiou, Thomas, Scialom, Thomas, Speckbacher, Tobias, Mihaylov, Todor, Xiao, Tong, Karn, Ujjwal, Goswami, Vedanuj, Gupta, Vibhor, Ramanathan, Vignesh, Kerkez, Viktor, Gonguet, Vincent, Do, Virginie, Vogeti, Vish, Albiero, Vítor, Petrovic, Vladan, Chu, Weiwei, Xiong, Wenhan, Fu, Wenyin, Meers, Whitney, Martinet, Xavier, Wang, Xiaodong, Wang, Xiaofang, Tan, Xiaoqing Ellen, Xia, Xide, Xie, Xinfeng, Jia, Xuchao, Wang, Xuewei, Goldschlag, Yaelle, Gaur, Yashesh, Babaei, Yasmine, Wen, Yi, Song, Yiwen, Zhang, Yuchen, Li, Yue, Mao, Yuning, Coudert, Zacharie Delpierre, Yan, Zheng, Chen, Zhengxing, Papakipos, Zoe, Singh, Aaditya, Srivastava, Aayushi, Jain, Abha, Kelsey, Adam, Shajnfeld, Adam, Gangidi, Adithya, Victoria, Adolfo, Goldstand, Ahuva, Menon, Ajay, Sharma, Ajay, Boesenberg, Alex, Baevski, Alexei, Feinstein, Allie, Kallet, Amanda, Sangani, Amit, Teo, Amos, Yunus, Anam, Lupu, Andrei, Alvarado, Andres, Caples, Andrew, Gu, Andrew, Ho, Andrew, Poulton, Andrew, Ryan, Andrew, Ramchandani, Ankit, Dong, Annie, Franco, Annie, Goyal, Anuj, Saraf, Aparajita, Chowdhury, Arkabandhu, Gabriel, Ashley, Bharambe, Ashwin, Eisenman, Assaf, Yazdan, Azadeh, James, Beau, Maurer, Ben, Leonhardi, Benjamin, Huang, Bernie, Loyd, Beth, De Paola, Beto, Paranjape, Bhargavi, Liu, Bing, Wu, Bo, Ni, Boyu, Hancock, Braden, Wasti, Bram, Spence, Brandon, Stojkovic, Brani, Gamido, Brian, Montalvo, Britt, Parker, Carl, Burton, Carly, Mejia, Catalina, Liu, Ce, Wang, Changhan, Kim, Changkyu, Zhou, Chao, Hu, Chester, Chu, Ching-Hsiang, Cai, Chris, Tindal, Chris, Feichtenhofer, Christoph, Gao, Cynthia, Civin, Damon, Beaty, Dana, Kreymer, Daniel, Li, Daniel, Adkins, David, Xu, David, Testuggine, Davide, David, Delia, Parikh, Devi, Liskovich, Diana, Foss, Didem, Wang, Dingkang, Le, Duc, Holland, Dustin, Dowling, Edward, Jamil, Eissa, Montgomery, Elaine, Presani, Eleonora, Hahn, Emily, Wood, Emily, Le, Eric-Tuan, Brinkman, Erik, Arcaute, Esteban, Dunbar, Evan, Smothers, Evan, Sun, Fei, Kreuk, Felix, Tian, Feng, Kokkinos, Filippos, Ozgenel, Firat, Caggioni, Francesco, Kanayet, Frank, Seide, Frank, Florez, Gabriela Medina, Schwarz, Gabriella, Badeer, Gada, Swee, Georgia, Halpern, Gil, Herman, Grant, Sizov, Grigory, Guangyi, Zhang, Lakshminarayanan, Guna, Inan, Hakan, Shojanazeri, Hamid, Zou, Han, Wang, Hannah, Zha, Hanwen, Habeeb, Haroun, Rudolph, Harrison, Suk, Helen, Aspegren, Henry, Goldman, Hunter, Zhan, Hongyuan, Damlaj, Ibrahim, Molybog, Igor, Tufanov, Igor, Leontiadis, Ilias, Veliche, Irina-Elena, Gat, Itai, Weissman, Jake, Geboski, James, Kohli, James, Lam, Janice, Asher, Japhet, Gaya, Jean-Baptiste, Marcus, Jeff, Tang, Jeff, Chan, Jennifer, Zhen, Jenny, Reizenstein, Jeremy, Teboul, Jeremy, Zhong, Jessica, Jin, Jian, Yang, Jingyi, Cummings, Joe, Carvill, Jon, Shepard, Jon, McPhie, Jonathan, Torres, Jonathan, Ginsburg, Josh, Wang, Junjie, Wu, Kai, U, Kam Hou, Saxena, Karan, Khandelwal, Kartikay, Zand, Katayoun, Matosich, Kathy, Veeraraghavan, Kaushik, Michelena, Kelly, Li, Keqian, Jagadeesh, Kiran, Huang, Kun, Chawla, Kunal, Huang, Kyle, Chen, Lailin, Garg, Lakshya, A, Lavender, Silva, Leandro, Bell, Lee, Zhang, Lei, Guo, Liangpeng, Yu, Licheng, Moshkovich, Liron, Wehrstedt, Luca, Khabsa, Madian, Avalani, Manav, Bhatt, Manish, Mankus, Martynas, Hasson, Matan, Lennie, Matthew, Reso, Matthias, Groshev, Maxim, Naumov, Maxim, Lathi, Maya, Keneally, Meghan, Liu, Miao, Seltzer, Michael L., Valko, Michal, Restrepo, Michelle, Patel, Mihir, Vyatskov, Mik, Samvelyan, Mikayel, Clark, Mike, Macey, Mike, Wang, Mike, Hermoso, Miquel Jubert, Metanat, Mo, Rastegari, Mohammad, Bansal, Munish, Santhanam, Nandhini, Parks, Natascha, White, Natasha, Bawa, Navyata, Singhal, Nayan, Egebo, Nick, Usunier, Nicolas, Mehta, Nikhil, Laptev, Nikolay Pavlovich, Dong, Ning, Cheng, Norman, Chernoguz, Oleg, Hart, Olivia, Salpekar, Omkar, Kalinli, Ozlem, Kent, Parkin, Parekh, Parth, Saab, Paul, Balaji, Pavan, Rittner, Pedro, Bontrager, Philip, Roux, Pierre, Dollar, Piotr, Zvyagina, Polina, Ratanchandani, Prashant, Yuvraj, Pritish, Liang, Qian, Alao, Rachad, Rodriguez, Rachel, Ayub, Rafi, Murthy, Raghotham, Nayani, Raghu, Mitra, Rahul, Parthasarathy, Rangaprabhu, Li, Raymond, Hogan, Rebekkah, Battey, Robin, Wang, Rocky, Howes, Russ, Rinott, Ruty, Mehta, Sachin, Siby, Sachin, Bondu, Sai Jayesh, Datta, Samyak, Chugh, Sara, Hunt, Sara, Dhillon, Sargun, Sidorov, Sasha, Pan, Satadru, Mahajan, Saurabh, Verma, Saurabh, Yamamoto, Seiji, Ramaswamy, Sharadh, Lindsay, Shaun, Feng, Sheng, Lin, Shenghao, Zha, Shengxin Cindy, Patil, Shishir, Shankar, Shiva, Zhang, Shuqiang, Wang, Sinong, Agarwal, Sneha, Sajuyigbe, Soji, Chintala, Soumith, Max, Stephanie, Chen, Stephen, Kehoe, Steve, Satterfield, Steve, Govindaprasad, Sudarshan, Gupta, Sumit, Deng, Summer, Cho, Sungmin, Virk, Sunny, Subramanian, Suraj, Choudhury, Sy, Goldman, Sydney, Remez, Tal, Glaser, Tamar, Best, Tamara, Koehler, Thilo, Robinson, Thomas, Li, Tianhe, Zhang, Tianjun, Matthews, Tim, Chou, Timothy, Shaked, Tzook, Vontimitta, Varun, Ajayi, Victoria, Montanez, Victoria, Mohan, Vijai, Kumar, Vinay Satish, Mangla, Vishal, Ionescu, Vlad, Poenaru, Vlad, Mihailescu, Vlad Tiberiu, Ivanov, Vladimir, Li, Wei, Wang, Wenchen, Jiang, Wenwen, Bouaziz, Wes, Constable, Will, Tang, Xiaocheng, Wu, Xiaojian, Wang, Xiaolan, Wu, Xilun, Gao, Xinbo, Kleinman, Yaniv, Chen, Yanjun, Hu, Ye, Jia, Ye, Qi, Ye, Li, Yenda, Zhang, Yilin, Zhang, Ying, Adi, Yossi, Nam, Youngjin, Yu, Wang, Zhao, Yu, Hao, Yuchen, Qian, Yundi, Li, Yunlu, He, Yuzi, Rait, Zach, DeVito, Zachary, Rosnbrick, Zef, Wen, Zhaoduo, Yang, Zhenyu, Zhao, Zhiwei, and Ma, Zhiyu more...
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Computer Science - Artificial Intelligence ,Computer Science - Computation and Language ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development. more...
- Published
- 2024
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