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IEEE International Conference on Software engineering and Service Sciences (ICSESS)

作者： Sakorn Mekruksavanich Wikanda Phaphan Phaisarn Jeefoo Anuchit Jitpattanakul Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao Thailand Research Group in Statistical Learning and Inference Department of Applied Statistics Faculty of Applied Science King Mongkut's University of Technology North Bangkok Bangkok Thailand Geographic Information System School of Information and Communication Technology University of Phayao Phayao Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Faculty of Applied Science King Mongkut's University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798350389166

ISBN: (纸本)9798350389173

Detecting chewing is vital to tracking eating habits, which is necessary to preserve good well-being and health. Advancements in wearable sensors have recently enabled cap-turing a wide range of sensor data, including signals from inertial measurement units (IMUs) and photoplethysmography (PPG). This research presents a new deep-learning design that efficiently detects chewing occurrences employing IMU and PPG sensor data acquired from an early instrument. The design includes convolutional neural networks (CNN) and bidirectional long short-term memory (LSTM). The CNN-BiLSTM network presented in this study combines the advantages of both CNN and BiLSTM to capture spatial and temporal characteristics from the sensor data effectively. The CNN layers extract localized patterns and characteristics from the IMU and PPG data, whereas the BiLSTM layers represent the extended relationships and time-based changes in chewing behavior. By integrating these two formidable designs, our network attains a high level of resilience and precision in detecting chewing. We assess the efficacy of the CNN-BiLSTM network using a standardized dataset obtained from several individuals wearing wearable devices while engaging in eating events. The dataset comprises IMU and PPG sensor data that have been annotated with associated chewing sessions. The experimental findings clearly show that the suggested network outperforms the current leading approaches, obtaining an accu-racy of 98.18 % and an F1-score of 98.29 %, the highest recorded. The CNN-BiLSTM network performs better than baseline models such as CNN, LSTM, BiLSTM, GRU, and BiGRU, emphasizing the efficacy of integrating spatial and temporal modeling for chewing identification.

关键词： Performance evaluation Recurrent neural networks Measurement units Photoplethysmography Convolutional neural networks Wearable devices Long short term memory Wearable sensors Software engineering Resilience

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LeNet enabled intrusion detection system for iot- networks

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AIP Conference Proceedings 2024年第1期3072卷

作者： Muhammad Allah Rakha Inam Ullah Khan Salma El Hajjami Abdelkarim El Hajjami Farhood Nishat Keshav Kaushik Department of Computer Science FAST National University of Computer and Emerging Sciences Peshawar 25000 Pakistan Department of Electronic Engineering School of Engineering and Applied Sciences (SEAS) Isra University Islamabad 76000 Pakistan LabSIV Department of Computer Science Faculty of Science Ibn Zohr University Agadir 80060 Morocco Department of Computer Science and Telecommunications INP-ENSEEIHT University of Toulouse Toulouse 31000 France Department of Information Security Institute of System Engineering Riphah University Islamabad 45320 Pakistan School of Computer Sciences University of Petroleum and Energy Studies Dehradun 248007 India

Now a day’s Internet of Thing’s (IoT’s) is considered growing technology. Ever increasing demand of IoT devices must have reliable channels for communication therefore, security needs to be ensured. Wireless enabled IoT use to have many real-time applications which include smart education, intelligent transportation, smart home, smart grid, health care and farming etc. Data collection can be made possible with the help of massive IoT devices. Intruder directly sends illegal data packets which lead to hijack overall network. IoT-networks have improved human experience in many real-time applications. Cyber-security threats usually limit computational resources. Therefore, detection of cyber-threats is the main problem for IoT-networks. This paper presents a novel concept of leNet model-based IDS to detect cyber- attacks. Although, two benchmark datasets such as IoTID20 and CICIDS2017 are utilized for simulation. LeNet model is compared with other traditional techniques like linear discriminant analysis, quadratic discriminant analysis, support vector machine and multi-layer perceptron. Accordingly, metrics like accuracy, precision, recall, F1-score, confusion matrix and correlation matrix are used for performance evaluation. Extensive analysis is performed which indicates that with IoTIDS20 dataset, LeNet achieves recall-99.91%, precision-99.74%, F1-score-99.83% and accuracy-99.68%. While, using CICIDS2017 dataset, LeNet presents optimal results in terms of recall-97.96%, precision-96.41%, F1-score- 97.18% and accuracy-98.87%. Proposed LeNet model is light weighted and adaptable.

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PAM-4 Optical Transmission Beyond 224 Gbps Based on an Ultrahigh-Bandwidth Slow-light Silicon Modulator

PAM-4 Optical Transmission Beyond 224 Gbps Based on an Ultra...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Changhao Han Jun Qin Qipeng Yang Zhao Zheng Haowen Shu Yunhao Zhang Yichen Wu Yu Sun Junde Lu Yan Zhou Zhangfeng Ge Lei Wang Zhixue He Shaohua Yu Weiwei Hu Chao Peng John E. Bowers Xingjun Wang State Key Laboratory of Advanced Optical Communications System and Networks School of Electronics Peking University Beijing China Department of Electrical and Computer Engineering University of California Santa Barbara CA US Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Frontiers Science Center for Nano-optoelectronics Peking University Beijing China Peng Cheng Laboratory Shenzhen China Peking University Yangtze Delta Institute of Optoelectronics Nantong China

We experimentally demonstrate PAM-4 optical transmission beyond 224 Gbps based on an ultrahigh-bandwidth slow-light silicon modulator in C-band with the combination of the artificial neural network equalizers.

ISBN: (纸本)9798350369311

关键词： Equalizers C-band Optical computing Artificial neural networks Electro-optic modulators Optical fiber networks Silicon photonics Ultrafast optics Optical modulation Passband

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Meta-Chain: User-Aware Cross-Layer Space Allocation Strategy for Blockchain Storage systems: Work-in-Progress

Meta-Chain: User-Aware Cross-Layer Space Allocation Strategy...

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International Conference on Hardware/Software Codesign and system Synthesis (CODES)

作者： Jing Liao Zhengda Li Yi Wang College of Computer Science and Software Engineering The National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China

ISBN: (数字)9781728191980

ISBN: (纸本)9781728191997

Current LSM-Tree-based blockchain storage system will assign the data from multiple system users to the same disk drive. This will lead to the inefficient usage of physical spaces in disk and cause extra compaction operations for LSM - Tree. This paper presents Meta-Chain , a user-aware cross-layer space allocation strategy for blockchain storage systems. As a cross-layer design, Meta-Chain redesigns the organization of LSM - Tree and utilizes the rich functionalities provided by open-channel SSD. Experimental results show that Meta-Chain can effectively reduce write amplification and extend the lifetime of SSD in comparison with representative schemes.

关键词： Disk drives Blockchain Organizations Compaction Resource management

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Hydrogen iodide (HI) neutral beam etching characteristics of InGaN and GaN for micro-LED fabrication

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Nanotechnology 2023年第36期34卷 365302-365302页

作者： Ohori, Daisuke Ishihara, Takahiro Wang, Xuelun Endo, Kazuhiko Hsieh, Tsou-Hwa Li, Yiming Natori, Nobuhiro Matsui, Kazuma Samukawa, Seiji Institute of Fluid Science Tohoku University 2-1-1 Katahira Aoba-ku Sendai980-8577 Japan Furo-cho Chikusa-ku Nagoya464-8601 Japan Institute of Materials and Systems for Sustainability Nagoya University Furo-cho Chikusa-ku Nagoya464-8601 Japan Institute of Communications Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Center for mmWave Smart Radar System and Technologies National Chiao Tung University Hsinchu300 Taiwan Advanced Institute for Materials Research Tohoku University 2-1-1 Katahira Aoba-ku Sendai980-8577 Japan Resonac Corporation 5-1 Ohgimachi Kawasaki-ku Kanagawa Kawasaki210-0867 Japan

We investigated the etching characteristics of hydrogen iodide (HI) neutral beam etching (NBE) of GaN and InGaN and compared with Cl2 NBE. We showed the advantages of HI NBE versus Cl2 NBE, namely: higher InGaN etch rate, better surface smoothness, and significantly reduced etching residues. Moreover, HI NBE was suppressed of yellow luminescence compared with Cl2 plasma. InCl x is a product of Cl2 NBE. It does not evaporate and remains on the surface as a residue, resulting in a low InGaN etching rate. We found that HI NBE has a higher reactivity with In resulting in InGaN etch rates up to 6.3 nm min−1, and low activation energy for InGaN of approximately 0.015 eV, and a thinner reaction layer than Cl2 NBE due to high volatility of In-I compounds. HI NBE resulted in smoother etching surface with a root mean square average (rms) of 2.9 nm of HI NBE than Cl2 NBE (rms: 4.3 nm) with controlled etching residue. Moreover, the defect generation was suppressed in HI NBE compared to Cl2 plasma, as indicated by lower yellow luminescence intensity increase after etching. Therefore, HI NBE is potentially useful for high throughput fabrication of μLEDs. © 2023 The Author(s). Published by IOP Publishing Ltd.

关键词： Etching

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An Integrated Sensing Chip for Detecting the Products of Loop-Mediated Isothermal Amplification Using a Non-Colorimetric Probe-Free Method

SSRN

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SSRN 2022年

作者： Mao, Subin Zhao, Jinping Ding, Xiaoke Vuong, Van Anh Song, Junqi Que, Long Electrical and Computer Engineering Department Iowa State University Ames50011 United States Texas A&M AgriLife Research Center at Dallas Texas A&M University System DallasTX75252 United States Department of Plant Pathology & Microbiology Texas A&M University College Station77843 United States

Loop-mediated isothermal amplification (LAMP) is a nucleic acid amplification technique and has been widely used for detection of pathogens in many organisms. Current LAMP-based sensors usually require the LAMP products to be labeled in order for them to be detected. Here, we present a novel label-free LAMP chip, which consists of a nanopore thin-film sensor embedded inside a LAMP reaction chamber. A fraction of LAMP primers is immobilized on the sensor surface, allowing the LAMP products to be synthesized and attached to the sensor surface via immobilized primers. After the LAMP reaction components are rinsed out of the reaction chamber, the amplified LAMP products attached to the sensor surface, which give rise to significantly increased transducing signals, can be measured by a portable optical spectrometer through an optical fiber probe. As a demonstration, we used the LAMP chip to detect the causal agent of late blight, Phytophthora infestans, which is one of the most devastating plant pathogens and poses a major threat to sustainable crop production worldwide. It has been found this chip can detect trace levels of pathogen DNA as low as 1 fg/µl in 30 min, which is at least 10 times more sensitive than the currently available methods to detect LAMP products. This label-free sensing technology holds great promise to open up a new avenue for ultra-sensitive, highly specific, rapid, and cost-effective pathogen detection suitable for the point-of-care testing. The integrated LAMP chip can be broadly applied for on-site diagnostics of plant, animal, human, and foodborne pathogens. © 2022, The Authors. All rights reserved.

关键词： Pathogens

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Semi-automatic segmentation of knee cartilage in longitudinal MR images by seed transfer 2

Semi-automatic segmentation of knee cartilage in longitudina...

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2nd International Conference on Electrical, Communication and computer engineering, ICECCE 2020

作者： Kim, Myoung Jin Park, Taewoo Lee, Soochahn Jung, Ho Yup Yun, Il Dong Hankuk University of Foreign Studies Dept. Computer and Electronic System Yongin Korea Republic of Geumgang University Division of Public Policy Nonsan Korea Republic of School of Electrical Engineering Kookmin University Seoul Korea Republic of Chosun Niveristy Dept. Compter Engineering Gwangju Korea Republic of

ISBN: (数字)9781728171166

ISBN: (纸本)9781728171166

In this paper, we propose an efficient and effective semi-automatic segmentation framework for knee cartilage in longitudinal MR images. The proposed method provides a seamless and efficient combination of initial automatic segmentation and interactive segmentation. The main idea is to generate and transfer the seeds, rather than the labels, of the manual segmentation results of the initial image, to segment sequential images. Here, segmentation seeds are defined as sample voxels that are highly likely to be either the organ of interest or background. Similar to user annotations by scribbles, seeds can be used to determine labels for remaining voxels. Compared to methods that transfer segmentation labels, the proposed method is able to reduce the amount of required user annotations, since it does not require the user to identify and correct erroneous regions in the transferred segmentation labels, while still providing a robust initial segmentation based on transferred initial seeds. We evaluate the effectiveness of the proposed framework by measuring the interaction time of the user to segment the cartilage within the images. We compare the results with previous methods and show that the proposed method reduces the required interaction time. © 2020 IEEE.

关键词： Cartilage

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Structural Robustness of Complex Networks: A Survey of A Posteriori Measures

arXiv

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arXiv 2023年

作者： Lou, Yang Wang, Lin Chen, Guanrong The Graduate School of Information Science and Technology Osaka University Osaka Suita565-0871 Japan The Department of Computer Science National Yang Ming Chiao Tung University Hsinchu300 Taiwan The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China The Department of Electrical Engineering City University of Hong Kong Hong Kong

Network robustness is critical for various industrial and social networks against malicious attacks, which has various meanings in different research contexts and here it refers to the ability of a network to sustain its functionality when a fraction of the network fail to work due to attacks. The rapid development of complex networks research indicates special interest and great concern about the network robustness, which is essential for further analyzing and optimizing network structures towards engineering applications. This comprehensive survey distills the important findings and developments of network robustness research, focusing on the a posteriori structural robustness measures for single-layer static networks. Specifically, the a posteriori robustness measures are reviewed from four perspectives: 1) network functionality, including connectivity, controllability and communication ability, as well as their extensions;2) malicious attacks, including conventional and computation-based attack strategies;3) robustness estimation methods using either analytical approximation or machine learning-based prediction;4) network robustness optimization. Based on the existing measures, a practical threshold of network destruction is introduced, with the suggestion that network robustness should be measured only before reaching the threshold of destruction. Then, a posteriori and a priori measures are compared experimentally, revealing the advantages of the a posteriori measures. Finally, prospective research directions with respect to a posteriori robustness measures are recommended. © 2023, CC BY.

关键词： Complex networks

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Advancements in Superconducting Microwave Cavities and Qubits for Quantum Information systems

arXiv

引用

arXiv 2023年

作者： Krasnok, Alex Dhakal, Pashupati Fedorov, Arkady Frigola, Pedro Kelly, Michael Kutsaev, Sergey Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Thomas Jefferson National Accelerator Facility Newport NewsVA23606 United States ARC Centre for Engineered Quantum System School of Mathematics and Physics University of Queensland BrisbaneQLD4072 Australia RadiaBeam LLC Santa MonicaCA90403 United States Argonne National Laboratory LemontIL60439 United States

Superconducting microwave cavities with ultra-high Q-factors are revolutionizing the field of quantum computing, offering long coherence times exceeding 1 ms, which is critical for realizing scalable multi-qubit quantum systems with low error rates. In this work, we provide an in-depth analysis of recent advances in ultra-high Q-factor cavities, integration of Josephson junction-based qubits, and bosonic-encoded qubits in 3D cavities. We carefully examine the sources of quantum state dephasing caused by damping and noise mechanisms in cavities and qubits, highlighting the critical challenges that need to be addressed to achieve even higher coherence times. We critically survey the latest progress made in implementing single 3D qubits using superconducting materials, normal metals, and multi-qubit and multi-state quantum systems. Our work sheds light on the promising future of this research area, including novel materials for cavities and qubits, modes with nontrivial topological properties, error correction techniques for bosonic qubits, and new light-matter interaction effects. Copyright © 2023, The Authors. All rights reserved.

关键词： Qubits

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Hierarchical Nb2o5@Zno Hetero-Branched Nanorods for Enhanced H2s Gas Sensing

SSRN

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SSRN 2022年

作者： Wu, Tao Tao Zhu, Liyuan Wu, Xue-Yan Miao, Xiao-Yong Mao, Li-Wen Jin, Xuan-Hong Lu, Hong-Liang State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics & Systems School of Microelectronics Fudan University Shanghai 200433 China School of Optical-Electrical & Computer Engineering University of Shanghai for Science and Technology Shanghai 200093 China Yiwu Research Institute of Fudan University Chengbei Road Zhejiang Yiwu City322000 China

Hierarchical Nb 2 O 5 @ZnO hetero-branched nanorods used for highly responsive, selective, and stable hydrogen sulfide (H 2 S) sensors were synthesized through a sequential process combining a hydrothermal method, atomic-layer-deposition processing, and modified hydrothermal processing for branching ZnO nanowires. The Nb 2 O 5 @ZnO hetero-branched nanorod sensors exhibited a great response (R a /R g ) of 6.10 towards 20 ppm H 2 S at an optimal working temperature of 400 o C, whose resistance changing rate (~5.10) was 39.2- and 1.9-fold those of Nb 2 O 5 (~0.13) and Nb 2 O 5 @ZnO core-shell nanorod (~2.74) sensors, respectively. The heterojunction formed at the Nb 2 O 5 @ZnO interface and the characteristic reaction between ZnO and H 2 S effectively improved H 2 S sensing performance. Moreover, the branching of ZnO nanowires introduced abundant homojunctions and prominently enlarged the specific surface area, further increasing the response of hetero-branched sensors. Meanwhile, the Nb 2 O 5 @ZnO hetero-branched sensors maintained steady performance over a month, indicating good stability and repeatability. In a word, such hierarchical Nb 2 O 5 @ZnO hetero-branched nanorod gas sensors are promising for the development of sensitive and selective H 2 S detection. © 2022, The Authors. All rights reserved.

关键词： Zinc oxide

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