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Click-through-rate (CTR) prediction plays an important role in online advertising and ad recommender systems. In the past decade, maximizing CTR has been the main focus of model development and solution creation. Therefore, researchers and practitioners have proposed various models and solutions to enhance the effectiveness of CTR prediction. Most of the existing literature focuses on capturing either implicit or explicit feature interactions. Although implicit interactions are successfully captured in some studies, explicit interactions present a challenge for achieving high CTR by extracting both low-order and high-order feature interactions. Unnecessary and irrelevant features may cause high computational time and low prediction performance. Furthermore, certain features may perform well with specific predictive models while underperforming with others. Also, feature distribution may fluctuate due to traffic variations. Most importantly, in live production environments, resources are limited, and the time for inference is just as crucial as training time. Because of all these reasons, feature selection is one of the most important factors in enhancing CTR prediction model performance. Simple filter-based feature selection algorithms do not perform well and they are not sufficient. An effective and efficient feature selection algorithm is needed to consistently filter the most useful features during live CTR prediction process. In this paper, we propose a heuristic algorithm named Neighborhood Search with Heuristic-based Feature Selection (NeSHFS) to enhance CTR prediction performance while reducing dimensionality and training time costs. We conduct comprehensive experiments on three public datasets to validate the efficiency and effectiveness of our proposed solution.

GSM-R (GSM for Railways) is a 2G-based standardized ground-to-train communications system that enabled interoperability across different countries. However, as a 2G-based system, it is nearing its lifetime and therefore, it will be replaced with 5G-based Future Railway Mobile Communications System (FRMCS). FRMCS is expected to bring in new use cases that demand low latency and high reliability. However, from a mobility perspective, it is not clear how the low latency and high reliability will be achieved. This paper investigates the effect of handover procedure on latency and reliability and analyzes which use cases of FRMCS can be satisfied using baseline handover. We also sweep through different handover parameter configurations and analyze their effect on mobility performance. Then, we analyze the effect of mobility performance on packet latency and reliability. Our results show that, with baseline handover, Standard Data Communications Scenario is met and optimizing for baseline handover performance can reduce latency by up to 18.5%, indicating that optimizing for mobility performance is crucial in FRMCS., Comment: 6 pages, 8 figures, submitted to the 20th International Conference on Wireless and Mobile Computing, Networking and Communications, 2024

Users' desire for enhanced performance drive the inevitable technological progress on vertical applications in wireless communication systems. To meet these demands, researchers vigorously investigate potential 6G and beyond technologies and solutions. Reconfigurable intelligent surfaces (RISs) have risen in popularity and attracted the attention of academia as well as industry and seem to be a promising candidate for 6G technology. RISs are reflective metamaterials with many configurable elements consisting of pin diodes that have the ability to manipulate the impinging signals' properties, hence, enabling some sort of virtual control over the wireless channel. In this paper, we propose a novel over-the-air index modulation (IM) scheme through the use of a hybrid RIS with active and passive partitions to convey additional IM bits over-the-air. In addition we propose another modified scheme that allows the transmission for even more IM bits but at the expense of certain trade-offs. First, we present the system model for both of the proposed schemes. Furthermore, comprehensive computer simulation results are provided and discussed presenting the superior bit error rate (BER) performance and additional benefits of the proposed systems compared to similar benchmarks., Comment: ICCSPA 2024, 6 pages, 6 figures

The advent of the sixth generation (6G) wireless networks heralds a transformative era for mobile communication, where the integration of cutting-edge technologies like Reconfigurable Intelligent Surfaces (RISs) is paramount in addressing the burgeoning demands for energy efficiency, high data rates, reliable connectivity, and enhanced coverage in densely populated areas. RISs have attracted the attention of academia as well as the industry and emerged as a beacon of innovation, offering a novel paradigm to reconfigure the wireless propagation environment beneficially, thereby enhancing the overall network performance. It is envisioned that the deployment of numerous RISs in a mobile network will serve user equipments (UEs) to boost various key performance indicators (KPIs), with lower energy consumption compared to alternative solutions (e.g., relays, and network-controlled repeaters). However, the knowledge of whether or not a UE is being served through an RIS and if so, which RIS it is being served by is crucial and beneficial for various network planning and operational reasons. In this paper, we address the importance and the benefits of RIS identification in a mobile network. Additionally, we guide the readers and researchers by introducing alternative methods to enable RIS identification. Through the lens of this research, we unveil and shed light to various benefits, the challenges, and future opportunities in the identification of RISs serving mobile users in complex network environments, highlighting the necessity for advanced identification strategies to fully harness the potential of RIS technology in next-generation wireless systems., Comment: 7 pages, 5 figures, 13 references, magazine

Reconfigurable intelligent surfaces (RISs) bring great potential to the advancement of 6G and beyond wireless communication technologies. RISs introduce a great degree of flexibility, allowing some sort of virtual control over the wireless channel. Exploiting the flexibility introduced by RISs, we propose a novel RIS-enabled downlink (DL) non-orthogonal multiple access (NOMA) scheme where NOMA is enabled over-the-air rather than at the base station (BS) or the receiver (Rx). Here, the RIS is partitioned into distinctive groups where each part of the RIS serves a different user equipment (UE) to perform multiple accessing. The BS transmits an unmodulated signal to the RIS, and each partition modulates the impinging signal over-the-air by introducing a phase shift according to the incoming information bits to serve the corresponding UE. First, the end-to-end system model for the proposed system is presented. Furthermore, outage probability calculations, theoretical error probability analysis, and bit error rate (BER) derivations are discussed and reinforced with comprehensive computer simulation results., Comment: 11 pages, 13 figures, transaction journal

Citation recommendation is the task of finding appropriate citations based on a given piece of text. The proposed datasets for this task consist mainly of several scientific fields, lacking some core ones, such as law. Furthermore, citation recommendation is used within the legal domain to identify supporting arguments, utilizing non-scholarly legal articles. In order to alleviate the limitations of existing studies, we gather the first scholarly legal dataset for the task of citation recommendation. Also, we conduct experiments with state-of-the-art models and compare their performance on this dataset. The study suggests that, while BM25 is a strong benchmark for the legal citation recommendation task, the most effective method involves implementing a two-step process that entails pre-fetching with BM25+, followed by re-ranking with SciNCL, which enhances the performance of the baseline from 0.26 to 0.30 MAP@10. Moreover, fine-tuning leads to considerable performance increases in pre-trained models, which shows the importance of including legal articles in the training data of these models., Comment: Seventeenth International Workshop on Juris-informatics (JURISIN 2023)

Online innovation communities are an important source of innovation for many organizations. While contributions to such communities are typically made without financial compensation, these contributions are often governed by licenses such as Creative Commons that may prevent others from building upon and commercializing them. While this can diminish the usefulness of contributions, there is limited work analyzing what leads individuals to impose restrictions on the use of their work. In this paper, we examine innovators imposing restrictive licenses within the 3D-printable design community Thingiverse. Our analyses suggest that innovators are more likely to restrict commercialization of their contributions as their reputation increases and when reusing contributions created by others. These findings contribute to innovation communities and the growing literature on property rights in digital markets.

Magnetic recording devices are still competitive in the storage density race thanks to new technologies such as two-dimensional magnetic recording (TDMR). Error-prone patterns where a bit is surrounded by complementary bits at the four positions with Manhattan distance $1$ on the TDMR grid are called plus isolation (PIS) patterns. Recently, we introduced optimal plus LOCO (OP-LOCO) codes that prevent these patterns from being written. However, as the device ages, error-prone patterns where a bit is surrounded by complementary bits at only three positions with Manhattan distance $1$ emerge, and we call these incomplete PIS (IPIS) patterns. In this paper, we present capacity-achieving codes that forbid both PIS and IPIS patterns in TDMR systems with wide read heads. We collectively call these patterns rotated T isolation (RTIS) patterns, and we call the new codes optimal T LOCO (OT-LOCO) codes. We analyze OT-LOCO codes and derive their encoding-decoding rule. Simulation results demonstrate that OT-LOCO codes entirely eliminate media noise at practical TD densities. We suggest using OP-LOCO codes early in the device lifetime, then reconfiguring to OT-LOCO codes later on. Moreover, we introduce another coding scheme to remove RTIS patterns which offers lower complexity, lower error propagation, and track separation., Comment: 27 pages (single column), 12 figures, submitted to the IEEE Transactions on Information Theory (TIT)

Supervised training of deep neural networks on pairs of clean image and noisy measurement achieves state-of-the-art performance for many image reconstruction tasks, but such training pairs are difficult to collect. Self-supervised methods enable training based on noisy measurements only, without clean images. In this work, we investigate the cost of self-supervised training in terms of sample complexity for a class of self-supervised methods that enable the computation of unbiased estimates of gradients of the supervised loss, including noise2noise methods. We analytically show that a model trained with such self-supervised training is as good as the same model trained in a supervised fashion, but self-supervised training requires more examples than supervised training. We then study self-supervised denoising and accelerated MRI empirically and characterize the cost of self-supervised training in terms of the number of additional samples required, and find that the performance gap between self-supervised and supervised training vanishes as a function of the training examples, at a problem-dependent rate, as predicted by our theory.

The personal (or active) electronic dosimeters (PEDs) are devices used to determine the individual exposure to ionizing radiations and they are employed in hospitals, research laboratories and nuclear power plants. The PDOZ project is a personal electronic dosimeter able to detect, discriminate and measure the delivered dose by beta particles and gamma rays. In this paper, several Monte Carlo simulations are described. The first one is regarding the ICRU sphere implemented to evaluate the ambient dose equivalent, H*(10), and the fluence-to-dose equivalent conversion coefficients for gamma rays and beta particles. The second simulation is carried out to study the prototype dosimeter response to gamma rays and beta particles and, also thanks to previous one, to obtain the conversion curve necessary to calculate the ambient dose equivalent from the silicon photomultipliers counts. In the last one, instead, the performance of a prototype dosimeter, composed by a small plastic scintillator coupled to two SiPMs, is evaluated and a simulation with different radioactive sources is made whose results are compared with the experimental measurements. All simulations are carried out by Geant4 including the optical photon transport. All simulations are carried out by Geant4 including the optical photon transport.

In this study, Higgs production processes, Higgsstrahlung and vector boson (W and Z) fusion processes, were investigated for four different future lepton colliders (CEPC, ILC, CLIC, and FCC-ee). The cross sections for each production process and corresponding backgrounds were calculated considering the ISR and beamstrahlung effects. Various cuts and the b-tagging method were used to reduce the background. Finally, the number of events for each collider was determined, and significance calculations were performed. In our calculations, high event numbers were obtained for all four colliders for the Higgsstrahlung, W, and Z fusion process. This shows that electron-positron colliders will play an important role in future Higgs physics research., Comment: 10 pages, 8 figures

Innovative reconfigurable intelligent surface (RIS) technologies are rising and recognized as promising candidates to enhance 6G and beyond wireless communication systems. RISs acquire the ability to manipulate electromagnetic signals, thus, offering a degree of control over the wireless channel and the potential for many more benefits. Furthermore, active RIS designs have recently been introduced to combat the critical double fading problem and other impairments passive RIS designs may possess. In this paper, the potential and flexibility of active RIS technology are exploited for uplink systems to achieve virtual non-orthogonal multiple access (NOMA) through power disparity over-the-air rather than controlling transmit powers at the user side. Specifically, users with identical transmit power, path loss, and distance can communicate with a base station sharing time and frequency resources in a NOMA fashion with the aid of the proposed hybrid RIS system. Here, the RIS is partitioned into active and passive parts and the distinctive partitions serve different users aligning their phases accordingly while introducing a power difference to the users' signals to enable NOMA. First, the end-to-end system model is presented considering two users. Furthermore, outage probability calculations and theoretical error probability analysis are discussed and reinforced with computer simulation results.

In this paper, a combat Unmanned Air Vehicle (UAV) is modeled in the simulation environment. The rotary wing UAV is successfully performed various tasks such as locking on the targets, tracking, and sharing the relevant data with surrounding vehicles. Different software technologies such as API communication, ground control station configuration, autonomous movement algorithms, computer vision, and deep learning are employed.

Deep learning (DL) has proven its unprecedented success in diverse fields such as computer vision, natural language processing, and speech recognition by its strong representation ability and ease of computation. As we move forward to a thoroughly intelligent society with 6G wireless networks, new applications and use-cases have been emerging with stringent requirements for next-generation wireless communications. Therefore, recent studies have focused on the potential of DL approaches in satisfying these rigorous needs and overcoming the deficiencies of existing model-based techniques. The main objective of this article is to unveil the state-of-the-art advancements in the field of DL-based physical layer (PHY) methods to pave the way for fascinating applications of 6G. In particular, we have focused our attention on four promising PHY concepts foreseen to dominate next-generation communications, namely massive multiple-input multiple-output (MIMO) systems, sophisticated multi-carrier (MC) waveform designs, reconfigurable intelligent surface (RIS)-empowered communications, and PHY security. We examine up-to-date developments in DL-based techniques, provide comparisons with state-of-the-art methods, and introduce a comprehensive guide for future directions. We also present an overview of the underlying concepts of DL, along with the theoretical background of well-known DL techniques. Furthermore, this article provides programming examples for a number of DL techniques and the implementation of a DL-based MIMO by sharing user-friendly code snippets, which might be useful for interested readers., Comment: Published in IEEE OJ-COMS