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arXiv 2023年

作者： Yu, Xinchun Wei, Shuangqing Huang, Shao-Lun Zhang, Xiao-Ping The Institute of information and Data Science Tsinghua Shenzhen International Graduate School Shenzhen China The Division of Electrical and Computer Engineering School of Electrical Engineering and Computer Science Louisiana State University Baton RougeLA70803 United States

This paper investigates the asymptotics of the maximal throughput of communication over AWGN channels by n channel uses under a covert constraint in terms of an upper bound δ of Kullback-Leibler divergence (KL divergence). It is shown that the first and second order asymptotics of the maximal throughput are √nδ log e and (2)1/2(nδ)1/4(log e)3/4 · Q−1(ϵ), respectively. The technique we use in the achievability is quasiΕ-neighborhood notion from information geometry. For finite blocklength n, the generating distributions are chosen to be a family of truncated Gaussian distributions with decreasing variances. The law of decreasing is carefully designed so that it maximizes the throughput at the main channel in the asymptotic sense under the condition that the output distributions satisfy the covert constraint. For the converse, the optimality of Gaussian distribution for minimizing KL divergence under the second order moment constraint is extended from dimension 1 to dimension n. Based on that, we establish an upper bound on the average power of the code to satisfy the covert constraint, which further leads to the direct converse bound in terms of covert metric. © 2023, CC BY-NC-ND.

关键词： Gaussian distribution

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Percolation Nature of Threshold Switching: an Experimental Verification

Percolation Nature of Threshold Switching: an Experimental V...

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IEEE Conference on Nanotechnology

作者： Suman Devkota Brendan M Kuzior Victor G. Karpov Daniel G. Georgiev Frank Li Vamsi Borra Electrical and Computer Engineering program Youngstown State University Youngstown OH OH USA Department of Physics and Astronomy and Department of Electrical Engineering and Computer Science respectively University of Toledo Toledo OH USA

This paper details a process used to create an interconnect in a conducting systems, such as amorphous or polycrystalline semiconductors. An experimental verification on the plasticity that supports the percolation conduction mechanism is provided. The plasticity observed in the sample could be harnessed in the development of new electronic devices that require flexibility and adaptability, such as wearable electronics and bendable screens. Overall, TEM characterization, in combination with SAED analysis, revealed a highly oriented crystalline structure in the sample. In addition, the results of this study have implications for the design of new memory devices that are based on a percolation conduction mechanism, which could potentially lead to the development of more efficient and reliable non-volatile storage technologies.

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Testing Facility Location with Constrained Queue Time Problem: A Case Study in Florida, USA 24

Testing Facility Location with Constrained Queue Time Proble...

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Proceedings of the Winter Simulation Conference

作者： Almir Antonio Monteiro Junior Rafael Schneider Vanessa de Almeida Guimarães Pedro Henrique González System Engineering and Computer Science Program Federal University of Rio de Janeiro BRAZIL COPPEAD Graduate School of Business Federal University of Rio de Janeiro BRAZIL

ISBN: (纸本)9798331534202

This study addresses the Testing Facility Location with Constrained Queue Time Problem. This optimization problem focuses on determining the best places to deploy testing sites and their available testers for infectious diseases, while constraining the maximum time in the queue with a given probability. An integer programming model is introduced and applied to the three biggest counties, in terms of population, of Florida, United States. Moreover, the Monte Carlo method is used to evaluate the model's output, aiming to check if the queueing time constraint is being satisfied. Through the experiments, a testing facility deployment plan can be determined for each county and further validated by the simulation. The results show that the solutions returned by the model behaved successfully when submitted to the Monte Carlo method, not exceeding the time in the queue in more than the predefined probability.

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Accessing Gender Bias in Speech Processing Using Machine Learning and Deep Learning with Gender Balanced Audio Deepfake Dataset

Accessing Gender Bias in Speech Processing Using Machine Lea...

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International Conference on Informatics and Computing (ICIC)

作者： Tricia Estella Amalia Zahra Wai-Keung Fung Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia Department of Engineering Cardiff School of Technologies EUREKA Robotics Centre Cardiff Metropolitan University United Kingdom

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

The rapid advancement of AI has led to the rise of Audio Deepfakes (AD), which pose serious ethical and security concerns by accurately mimicking human speech. This research addresses the urgent need for effective AD detection, with a focus on gender bias that can reduce the effectiveness of detection models. We examined how gender affects the performance of both Machine Learning (Support Vector Machine, Random Forest, Logistic Regression, XGBoost) and Deep Learning (Deep Neural Networks, Convolutional Neural Networks) models using the GBAD dataset. Our findings show that models trained on female audio outperform those trained on male audio, likely due to the expressive nature of female voice features and high-pitched artifacts in FAKE audio. This highlights the need for more robust, gender-sensitive detection systems. Future work should focus on developing adaptive models to reduce gender bias, improving security, and creating lightweight models for wider public use.

关键词： Deep learning Support vector machines Deepfakes Adaptation models Logistic regression Computational modeling Security Speech processing Informatics Random forests

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3D Image Generation from X-Ray Projections Using Generative Adversarial Networks

3D Image Generation from X-Ray Projections Using Generative ...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Mohammad AlShurbaji Salam Dhou Biomedical Engineering Graduate Program American University of Sharjah Sharjah UAE Department of Computer Science and Engineering American University of Sharjah Sharjah UAE

The human brain can effortlessly imagine a 3D image from only 2D images with a little expertise and imagination, but for machines, this is not a trivial task. Because of this, reconstructing 3D images from 2D ones is a hot topic and has many applications. In this paper, we propose a Generative Adversarial Network (GAN)-based approach that generates CT-like images using pairs of orthogonal X-ray projections taken from different angles. In this work, a variety of orthogonal pairs from different angles, ranging from 0°&90° to 60°&150°, were considered as input to the 3D image generation model. The effectiveness of the proposed method was assessed by measuring the Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR), which resulted in values of 0.641 and 29.21, respectively. Furthermore, the model's ability to capture the respiratory motion in the input projections and reflect it in the generated images was also assessed. This work demonstrated the feasibility of generating CT-like images from X-ray projections captured from different orthogonal angles taking into consideration the respiratory motion exhibited in these projections.

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Understanding the stability of advanced inorganic-organic hybrid thin films for advanced resist applications 41

Understanding the stability of advanced inorganic-organic hy...

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Advances in Patterning Materials and Processes XLI 2024

作者： Le, Dan N. Chu, Thi Thu Huong Kim, Jin-Hyun Veyan, Jean-Francois Lee, Won-Il Tiwale, Nikhil Lee, Minjong Choi, Seungsoo Woo, Jihoon Nam, Chang-Yong Choi, Rino Kim, Jiyoung Department of Materials Science and Engineering University of Texas at Dallas RichardsonTX75080 United States Department of Materials Science and Chemical Engineering Stony Brook University Stony BrookNY11794 United States Center for Functional Nanomaterials Brookhaven National Laboratory UptonNY11973 United States Department of Electrical and Computer Engineering University of Texas at Dallas RichardsonTX75080 United States Program in Enviromental and Polymer Engineering Inha University Incheon22212 Korea Republic of Department of Materials Science and Engineering Inha University Incheon22212 Korea Republic of

ISBN: (纸本)9781510672208

In this study, we focus on examining the stability of Al-based inorganic-organic hybrid thin films deposited through the molecular atomic layer deposition (MALD) process in ambient environment. Our observations reveal an initial reduction in material thickness within the first 3 days, followed by a period of stability. XPS analysis is employed to further investigate the chemical alternations in the aged Al-based hybrid thin films, revealing an increase in C=O species as well as overall oxygen content in the material. We also evaluate the effects of atmospheric exposure on the sensitivity of the Al-based hybrid thin films using electron flood exposure. This study aims to enhance the understanding of the stability of a vapor-phase synthesized hybrid thin film system for advanced resist applications. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Atomic layer deposition

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Mini-InternVL:a flexible-transfer pocket multi-modal model with 5%parameters and 90%performance

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Visual Intelligence 2024年第1期2卷 392-408页

作者： Zhangwei Gao Zhe Chen Erfei Cui Yiming Ren Weiyun Wang Jinguo Zhu Hao Tian Shenglong Ye Junjun He Xizhou Zhu Lewei Lu Tong Lu Yu Qiao Jifeng Dai Wenhai Wang Shanghai AI Laboratory Shanghai200232China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai200240China School of Computer Science Nanjing UniversityNanjing210023China Tsinghua Shenzhen International Graduate School Tsinghua UniversityShenzhen518055China School of Computer Science Fudan UniversityShanghai200433China SenseTime Research Shanghai200233China Department of Electronic Engineering Tsinghua UniversityBeijing100084China Beijing National Research Center for Information Science and Technology Department of AutomationTsinghua UniversityBeijing100084China Department of Information Engineering The Chinese University of Hong KongHong Kong999077China

Multi-modal large language models(MLLMs)have demonstrated impressive performance in vision-language tasks across a wide range of ***,the large model scale and associated high computational cost pose significant challenges for training and deploying MLLMs on consumer-grade GPUs or edge devices,thereby hindering their widespread *** this work,we introduce Mini-InternVL,a series of MLLMs with parameters ranging from 1 billion to 4 billion,which achieves 90% of the performance with only 5% of the *** significant improvement in efficiency and effectiveness makes our models more accessible and applicable in various real-world *** further promote the adoption of our models,we are developing a unified adaptation framework for Mini-InternVL,which enables our models to transfer and outperform specialized models in downstream tasks,including autonomous driving,medical image processing,and remote *** believe that our models can provide valuable insights and resources to advance the development of efficient and effective MLLMs.

关键词： Lightweight multi-modal large language model Vision-language model Knowledge distillation Visual instruction tuning

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NMPC Strategy for Safe Robot Navigation in Unknown Environments Using Polynomial Zonotopes

NMPC Strategy for Safe Robot Navigation in Unknown Environme...

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IEEE Conference on Decision and Control

作者： Iuro B. P. Nascimento Brenner S. Rego Luciano C. A. Pimenta Guilherme V. Raffo Graduate Program in Electrical engineering Federal University of Minas Gerais Brazil Department of Electrical and Computer Engineering University of São Paulo Brazil Department of Electronic Engineering Federal University of Minas Gerais Brazil

This work proposes a nonlinear model predictive control (NMPC) strategy for robot navigation in cluttered unknown environments using polynomial zonotopes. The information provided by a laser sensor is used in the computation of the collision-free area. The procedure splits the area into convex subregions which are converted into polynomial zonotopes (PZs) to generate constraints for the NMPC optimal control problem. The PZ is a set representation that can describe polytopes using fewer constraints than conventional half-space representations, thus being more efficient while maintaining the accuracy equivalent to the polytopic case. Numerical experiments demonstrate the advantages of the proposed strategy.

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High-Performance Asynchronous CNN Accelerator with Early Termination 15

High-Performance Asynchronous CNN Accelerator with Early Ter...

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15th IEEE International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2022

作者： Loo, Tan Rong Teo, T. Hui Tiruye, Mulat Ayinet Wey, I-Chyn Singapore University of Technology and Design Engineering Product Development Singapore Singapore University of Technology and Design Engineering Product Development Science Mathematics and Technology Singapore Artificial Intelligence Research Center School of Electrical and Computer Engineering College of Engineering Graduate Institute of Electrical Engineering Chang Gung University Chang Gung University Taiwan

ISBN: (纸本)9781665464994

Convolutional Neural Network (CNN), especially very deep networks, are highly computation intensive, resulting in long delays and high-power consumption. The dynamically varying environmental conditions in real world inference can result in highly complex problems, and hence the need for these inefficient deep networks to guarantee satisfactory accuracy all the time. Several studies employ approximation techniques to execute partial computation of the network, in attempt to reduce the amount of computation were unnecessary. However, such approaches are still highly sequential in nature, since they still need to run the whole network. This paper proposes an early termination architecture on an already-trained CNN to allow for testing the partial results midway through the network, reducing computations by terminating the main network when it is sufficient as the inference results. The first proposal is implemented in synchronous circuit, however, due to its nature all memory elements are required to capture even when no new data is generated. The second proposal employs the use of asynchronous circuit to significantly reducing power consumption and further sped up the architecture since an operation need not wait the slowest critical path in the circuit. The proposed circuits were designed on FPGA platform. The results of the asynchronous circuit show a nearly 20% increment in speed with about 12% reduction in power consumption in comparison with a synchronous circuit. © 2022 IEEE.

关键词： Electric power utilization

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Black Soldier Fly Bioconversion System: A Digital Twin Approach 32

Black Soldier Fly Bioconversion System: A Digital Twin Appro...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Yu, Guangtao Nishi, Hiroaki Pang, Cheng Gu, Qingqing Lin, Yonghao Liang, Jinxian Dai, Wenbin Vyatkin, Valeriy INSPRO Science Ltd. Shenzhen China Keio University Graduate School of Science and Technology Japan Changsha Robox Institue Co. Ltd. Changsha China Shenzhen Cynovan Technologies Co. Ltd. Shenzhen China Shanghai Jiao Tong University Department of Automation Shanghai China Luleå University of Technology Department of Computer Science Electrical and Space Engineering Luleå Sweden Aalto University Department of Electrical Engineering and Automation Finland

ISBN: (纸本)9798350399714

Insect-based bioconversion is an emerging and economically viable approach that could simultaneously solve the global issues on food waste treatment and protein shortage. An essence of insect-based bioconversion is to feed insects on food wastes and then harvest and refine the developed insects into value-added commodities. This is a circular bioeconomic approach that can efficiently upcycle the nutrients and energy in food waste streams back into agricultural supply chains, but the difficulty is how to realize mass production of insects. This paper reports a commercial-scale insect-based bioconversion system using black soldier flies, whose design and development follow a digital twin paradigm. In particular, an industrialized rearing environment has been established, where the larvae growth can be systematically monitored, controlled, and managed to evaluate the overall bioconversion process efficacy. The system has been deployed in a pilot plant, whose Phase I is capable of handling 20 tons of food waste feedstocks per day and has been consecutively operating to date. © 2023 IEEE.

关键词： Supply chains

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