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61,142 results on '"Ho A"'

1. VAE-Based 3D Image Restoration Method for PCB Profilometry

Author

Min-Ho Ha, Saba Arshad, Tae-Jung Kim, and Tae-Hyoung Park

Subjects
3D restoration, deep learning, moiré pattern profilometry (MPP), printed circuit board (PCB), variational auto encoder (VAE), Applied optics. Photonics, TA1501-1820, Optics. Light, QC350-467
Abstract

This paper focuses on three-dimensional measurement system of printed circuit board components. Most automated optical inspections suffer from shadows and reflections obscured by the components. We propose a new method to restore shadow and reflection regions of components for accurate shape measurements, which defines shadow and reflection regions for restoration. The region is restored with a variational auto encoder-based restoration network. It is efficient to input information about both shadow and reflection region to restore the region. Additionally, long skip connection is added to VAE for improved accuracy. We confirmed its superiority through experiments by comparing its performance with other restoration networks such as cycle generative adversarial networks and coherent semantic attention inpainting.

Published
2024
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2. Advancements in Cerebellar Modeling and Its Practical Applications: A Comprehensive Review

Author

Shaojia Huang, Tao Xu, Jiaqing Chen, Jiajia Huang, Zhikun Wang, Ya Ke, and Wing Ho Yung

Subjects
Cerebellar modeling, motor learning, synaptic plasticity, robotic control, artificial intelligence, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

The cerebellum plays a crucial role in motor learning and memory, and recent studies have proposed various cerebellar models to investigate these functions. This review examines the literature on different levels of cerebellar modeling, including animal models, neuronal and synaptic plasticity models, relevant artificial intelligence (AI) paradigms, and real-time applications. The development of cerebellar models is discussed, from simple to complex and from theory to application. Optimization methods used in AI for optimizing cerebellar neuronal electrophysiology parameters are also highlighted, allowing for the prediction of difficult-to-observe neuronal features. Combining neuroscience and computer science-oriented neural networks, such as the spiking neural network (SNN) and the artificial neural network (ANN), can enable the cerebellar model to adapt to various applications, including robotic control, neurological disease simulation, and drug delivery simulation. This review provides a useful guide for future research on cerebellar modeling.

Published
2024
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3. Double Critics and Double Actors Deep Deterministic Policy Gradient for Mobile Robot Navigation Using Adaptive Parameter Space Noise and Parallel Experience Replay

Author

Wenjie Hu, Ye Zhou, Hann Woei Ho, and Chun Zhang

Subjects
Deep reinforcement learning, deep deterministic policy gradient, adaptive parameter space noise, double critics and double actors, mobile robot navigation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

In recent years, mobile robots have been increasingly used in a variety of industries, such as manufacturing, logistics, health care, and security services. Effective autonomous navigation preventing collisions for mobile robots has become crucial for efficiently performing tasks in these diverse applications. Deep reinforcement learning (DRL) is promising for path planning and autonomous navigation, but Deep Q-Network is limited to discrete actions. To extend to continuous action space, the deep deterministic policy gradient (DDPG) algorithm was developed. However, it suffers from insufficient exploration and overestimation. To solve these challenges, this paper proposes the adaptive parameter space noise with parallel experience replay, double critics and double actors DDPG (AP-D4PG) algorithm, an enhanced variant of DDPG. It incorporates adaptive parameter space noise in actor networks for better exploration, double critics and double actors to mitigate overestimation and improve the estimate accuracy of target Q value, and parallel experience replay to make a better balance between exploration and exploitation, thereby significantly improving the performance of autonomous navigation for mobile robots. Furthermore, a novel and powerful target-oriented reward function is employed to boost learning efficiency. Additionally, to further bolster the stability and robustness, useful improvements including gradient clipping mechanism and Xavier initialization are employed. Subsequently, the efficacy of the proposed model is assessed through numerical experiments with the robot operating system (ROS) and Gazebo. The experimental findings demonstrate that the AP-D4PG algorithm achieves faster convergence and enhanced robustness, with a 3.83% and 7.78% increase in navigation accuracy, and a 61.14% and 48.93% higher average score in static and dynamic scenarios, respectively, compared to traditional DDPG. These improvements and the robustness of the AP-D4PG algorithm in both static and dynamic environments indicate that refining network architectures, exploration strategies, and reward mechanisms can enhance the performance of DRL algorithms. This opens up new possibilities for improving the efficiency and effectiveness of other DRL methods.

Published
2024
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4. Experimental Investigation of Free Space Optical Channel Performance in the Arctic Weather

Author

Sahil Nazir Pottoo, Pal Gunnar Ellingsen, and Tu Dac Ho

Subjects
Free space optical communication, optical attenuation, Arctic broadband, atmospheric measurements, channel modeling, unmanned aerial vehicles, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

This paper investigates the technical aspects of the 1550 nm free space optical (FSO) link in extreme Arctic weather, specifically in falling snow, which is currently understudied. We measured the time variation of the received optical power in many snowfall events and derived attenuation statistics. Continuous measurements allowed us to estimate attenuation under varying temperatures and humidity to examine the after-snow channel impairments. Our results show several shortcomings in the International Telecommunication Union-Radio Communication (ITU-R) snow attenuation model and verify that a correlation exists between snow features, snowfall rate, temperature, and humidity in determining the total snow attenuation. We demonstrated the relationship between snow properties, temperature, humidity, and attenuation under both in-snow and post-snow environments. Furthermore, based on the experimental results, we recommend several mitigation techniques to realize FSO communication during challenging Arctic weather conditions. Lastly, we present a feasibility study of FSO in Svalbard at 78°N latitude.

Published
2024
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5. Application of Plasma Information-Based Virtual Metrology (PI-VM) for Etching in C₄F₈/Ar/O₂ Plasma.

Author

Kim, Gwanjoong, Kwon, Ji-Won, Lee, Ingyu, Seo, Hwiwon, Park, Jong-Bae, Shin, Jong-Hyeon, and Kim, Gon-Ho

Abstract

This study developed Plasma Information-based Virtual Metrology (PI-VM) to predict etching process results and analyze process phenomena. Using a dual-frequency capacitively coupled plasma (CCP) etcher with C4F8/Ar/O2 plasma, we etched low aspect ratio (AR) trench patterns in amorphous carbon layer (ACL) hard masks and $\rm SiO_{2}$ molds, and developed the PI-VM statistically by integrating plasma information (PI) variables that reflect domain knowledge. The passivation effect of fluorocarbon plasma was analyzed by varying the gas ratios and the effect of ion energy was analyzed by changing the low frequency (LF) power. In the PI-VM results, the density ratios of the passivation precursor $\rm CF_{2}$ to the etchant F and O were selected as key factors for predicting the process. The selection of radical density ratios as features confirmed the dominance of plasma chemistry in low AR etching. Demonstrating high predictive accuracy with minimal data, PI-VM offers significant potential to enhance the development of semiconductor process recipes. [ABSTRACT FROM AUTHOR]

Published
2024
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8. A Novel Program-verify Free and Low Drift Multilevel Operation on Cross-point OTS-PCM for In-Memory Computing Application

Author

Chien, W. C., primary, Sung, C. L., additional, Bruce, R. L., additional, Yeh, C. W., additional, Cheng, H. Y., additional, Liu, Z. L., additional, Lai, E. K., additional, Cheng, C. W., additional, Zheng, J. X., additional, Grun, A., additional, Ray, A., additional, Daudelin, D., additional, Ho, H. Y., additional, BrightSky, M., additional, and Lung, H. L., additional

Published
2024
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44. 13.3 A 280-Layer 1Tb 4b/cell 3D-NAND Flash Memory with a 28.5Gb/mm2 Areal Density and a 3.2GB/s High-Speed IO Rate

Author

Jung, Wontaeck, primary, Kim, Hyunggon, additional, Kim, Do-Bin, additional, Kim, Tae-Hyun, additional, Lee, Namhee, additional, Shin, Dongjin, additional, Kim, Minyoung, additional, Rho, Youngsik, additional, Lee, Hun-Jong, additional, Hyun, Yujin, additional, Park, Jaeyoung, additional, Kim, Taekyung, additional, Kim, Hwiwon, additional, Lee, Gyeongwon, additional, Lee, Jisang, additional, Jang, Joonsuc, additional, Park, Jungmin, additional, Kim, Sion, additional, Jeon, Su Chang, additional, Kim, Suyong, additional, Song, Jung-Ho, additional, Kim, Min-Seok, additional, Lee, Taesung, additional, Chun, Byung-Kwan, additional, Kim, Tongsung, additional, Lee, Young Gyu, additional, Lee, Hokil, additional, Lee, Soowoong, additional, Lee, Hwaseok, additional, Cho, Dooho, additional, Nam, Sang-Wan, additional, Kim, Yeomyung, additional, Yoon, Kunyong, additional, Lee, Yoonjae, additional, Kim, Sunghoon, additional, Hwang, Jungseok, additional, Song, Raehyun, additional, Jang, Hyunsik, additional, Son, Jaeick, additional, Jeon, Hongsoo, additional, Lee, Myunghun, additional, Lee, Mookyung, additional, Kim, Kisung, additional, Lee, Eungsuk, additional, Lee, Myeongwoo, additional, Jo, Sungkyu, additional, Kim, Chan Ho, additional, Park, Jong Chul, additional, Yun, Kyunghwa, additional, Seol, Soonock, additional, Cho, Ji-Ho, additional, Lee, Seungjae, additional, Lee, Jin-Yub, additional, and Hur, Sung-Hoi, additional

Published
2024
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48. AnchorLoc: Large-Scale, Real-Time Visual Localisation Through Anchor Extraction and Detection

Author

Park, Chun Ho, Alhilal, Ahmad, Braud, Tristan Camille, Hui, Pan, Park, Chun Ho, Alhilal, Ahmad, Braud, Tristan Camille, and Hui, Pan

Abstract

Pervasive Augmented Reality (AR) requires accurate pose registration of the device in real-time at a neighbourhood-to-city scale. At such a scale, most pose registration techniques suffer from exponential computational and storage costs and a significant data collection burden. This paper introduces AnchorLoc, a framework that relies on visual anchors (stable and highly recognisable visual elements in a scene) to perform fast and accurate pose registration. Anchorloc automatically identifies these anchors from large image sequences to optimise the search space in later image retrieval and pose registration. As such, it significantly improves the computational efficiency of existing hierarchical localisation pipelines without compromising accuracy. We collect a large-scale localisation dataset consisting of image sequences and 3D reconstruction of a university campus. AnchorLoc reduces localisation runtime by 83% on our campus dataset and 69% on the Cambridge Landmarks dataset without significantly increasing mean pose estimation errors. It is also more accurate and faster than SLD, a localisation algorithm that takes a comparable approach at the keypoint level. This work informs the development of more efficient pervasive AR applications that rely on both absolute and relative camera pose tracking on image sequences. © 2024 IEEE.

Published
2024

49. Generalization of Minimum Storage Regenerating Codes for Heterogeneous Distributed Storage Systems

Author

Li, Zhengrui, Mow, Wai Ho, Han, Yunghsiang, Wu, Ting-Yi, Li, Zhengrui, Mow, Wai Ho, Han, Yunghsiang, and Wu, Ting-Yi

Abstract

Real-world distributed storage systems (DSSs) are heterogeneous because storage nodes may have unequal per-symbol storage costs, and network links may have unequal per-symbol transmission costs. For some general classes of heterogeneous DSSs, the optimal tradeoff between storage and repair costs achievable by functional repair codes is known (at least numerically). However, it is unclear whether exact-repair codes can achieve any point of such an optimal storage-repair tradeoff curve, especially at the point of the minimum storage cost. In this paper, we provide an affirmative answer to the question by constructing the so-called heterogeneous minimum storage repair (HMSR) codes for both the average and worst-case repair costs. To optimize storage and repair costs, a heterogeneous DSS may need to adopt irregular array codes and repair a node by downloading unequal numbers of symbols from helper nodes. However, our results show that for almost all heterogeneous DSSs, exact-repair HMSR codes are regular array codes covering an adequately chosen set of nodes. Specifically, exact-repair HMSR codes are designed by stacking conventional MSR codes and applying different repair schemes to different layers. Still, this does not work for every heterogeneous DSS. It is proven that using regular or linear irregular array codes for constructing exact-repair HMSR codes is insufficient in some cases.

Published
2024

50. A 92% Complexity Reduction of Low-Latency Multi-Group Precoding Scheme based on Björck Sequences

Author

Wang, Geyang, Chan, W. U. David, Tsang, Hong Ki, Mow, Wai Ho, Chen, Lian-Kuan, Wang, Geyang, Chan, W. U. David, Tsang, Hong Ki, Mow, Wai Ho, and Chen, Lian-Kuan

Abstract

We present a multi-group precoding scheme based on Björck sequences, achieving a tradeoff between complexity and BER performance. Experiments at ∼200 Gb/s demonstrate that the proposed approach outperforms OCT while reducing complexity by 92%. © 2024 OSA.

Published
2024

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