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SSRN 2024年

作者： Wei, Jinlian Oyunbaatar, Nomin-Erdene Jeong, Yun-Jin Park, Jongsung Kim, Su-Hwan Kwon, Kyeongha Lee, Heonzoo Won, Yonggwan Kim, Dong-Su Lee, Dong-Weon School of Mechanical Engineering Chonnam National University Gwangju61186 Korea Republic of Department of Automatic System Chosun College of Science & Technology Gwangju61453 Korea Republic of Department of Precision Mechanical Engineering Kyungpook National University Gyeongsangbuk-do Sangju37224 Korea Republic of School of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of Department of Intelligent Electronics and Computer Engineering Chonnam National University Gwangju61186 Korea Republic of Gwangju61012 Korea Republic of

With the growing use of stent implantations, the risk of in-stent restenosis represents a major concern for cardiovascular patients. Herein, we propose a hybrid bioresorbable vascular scaffold (H-BVS) integrated with a wireless sensor that could enable significant advances in cardiovascular therapeutics. The H-BVS was manufactured using a state-of-the-art customized 3D printer equipped with dual nozzles to ensure a synergistic combination of polycaprolactone and polylactic acid. Moreover, the H-BVS was integrated with a wireless, battery-less LC-type pressure sensor for real-time monitoring of in-stent restenosis. This wireless sensor was meticulously connected with the H-BVS framework through engineered microstructures, which not only ensured a robust bond but also significantly enhanced the overall integrity and functionality of the device. Furthermore, the combination of the H-BVS and sensor was optimized to exhibit superior bending flexibility and radial strength, which are key factors in ensuring effectiveness and patient safety. The feasibility of the smart H-BVS (SH-BVS) was verified through comprehensive testing within a phantom system designed to simulate real blood flow conditions. We believe that the potential of the SH-BVS system to revolutionize patient monitoring and treatment strategies in the cardiovascular healthcare domain cannot be overstated. © 2024, The Authors. All rights reserved.

关键词： Biodegradable polymers

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Region-based Flash Caching with Joint Latency and Lifetime Optimization in Hybrid SMR Storage systems

Region-based Flash Caching with Joint Latency and Lifetime O...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Zhengang Chen Guohui Wang Zhiping Shi Yong Guan Tianyu Wang College of Information Engineering Capital Normal University Beijing China Beijing Key Laboratory of Electronic System Reliability Technology Capital Normal University Beijing China International Science and Technology Cooperation Base of Electronic System Reliability and Mathematical Interdisciplinary Capital Normal University Beijing China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong China

The frequent Read-Modify-Write operations (RMWs) in Shingled Magnetic Recording (SMR) disks severely degrade the random write performance of the system. Although the adoption of persistent cache (PC) and built-in NAND flash cache alleviates some of the RMWs, when the cache is full, the triggered write-back operations still prolong I/O response time and the erasure of NAND flash also sacrifices its lifetime. In this paper, we propose a Region-based Co-optimized strategy named Multi-Regional Collaborative Management (MCM) to optimize the average response time by separately managing sequential/random and hot/cold data and extend the NAND flash lifetime by a region-aware wear-leveling strategy. The experimental results show that our MCM reduces 71 % of the average response time and 96% of RMWs on average compared with the Skylight (baseline). For the comparison with the state-of-art flash-based cache (FC) approach, we can still save the average response time and flash erase operations by 17.2 % and 33.32 %, respectively.

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Microcomb-driven photonic convolutional engine

Microcomb-driven photonic convolutional engine

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Bai, Bowen Yang, Qipeng Shu, Haowen Chang, Lin Wu, Yichen Yang, Fenghe Shen, Bitao Tao, Zihan Xie, Weiqiang Hu, Weiwei Bowers, John E. Wang, Xingjun State Key Laboratory of Advanced Optical Communications System and Networks School of Electronics Peking University Beijing100871 China Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States Frontiers Science Center for Nano-optoelectronics Peking University Beijing100871 China Zhangjiang Laboratory Shanghai201210 China Peking University Yangtze Delta Institute of Optoelectronics Nantong226010 China

We demonstrate a microcomb-driven chip-based photonic convolutional engine utilizing time-wavelength plane stretching approach. A preeminent photonic-core compute density of 1.04 TOPS/mm2 and a record high weight cont... 详细信息

ISBN: (纸本)9781957171258

关键词： Convolution

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Current Trends in Online Programming Languages Learning Tools: A systematic Literature Review

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Journal of Software engineering and Applications 2021年第7期14卷 277-297页

作者： Ahmad Alaqsam Fahad Ghabban Omair Ameerbakhsh Ibrahim Alfadli Amer Fayez Department of Information System Faculty of Computing The University of Tabuk Tabuk Saudi Arabia Information System Department Faculty of Computer Science and Engineering Taibah University Madinah Saudi Arabia

Students face difficulties in programming languages learning (PLL) which encourages many scholars to investigate the factors behind that. Although there a number of positive and negative factors found to be effective in PLL procedure, utilising online tools in PLL were recognized as a positive recommended means. This motivates many researchers to provide solutions and proposals which result in a number of choices and options. However, categorising those efforts and showing what has been done, would provide a better and clear image for future studies. Therefore, this paper aims to conduct a systematic literature review to show what studies have been done and then categorise them based on the type of online tools and the aims of the research. The study follows Kitchenham and Charters guidelines for writing SLR (Systematic Literature Review). The search result reached 1390 publications between 2013-09/2018. After the filtration which has been done through selected criteria, 160 publications were found to be adequate to answer the review questions. The main results of this systematic review are categorizing the aims of the studies in online PLL tools, classifying the tools and finding the current trends of the online PLL tools.

关键词： Online Programming Languages Online Learning Use of Information Technology Online Platforms Online Courses MOOC

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Machine Learning Classifiers for Network Intrusion Detection system: Comparative Study

Machine Learning Classifiers for Network Intrusion Detection...

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2021 International Conference on Information Technology, ICIT 2021

作者： Almomani, Omar Almaiah, Mohammed Amin Alsaaidah, Adeeb Smadi, Sami Mohammad, Adel Hamdan Althunibat, Ahmad The World Islamic Sciences and Education University Department of Information System and Networks Jordan College of Computer Science and Information Technology King Faisal University Al-Ahsa31982 Saudi Arabia The World Islamic Sciences and Education University Department of Computer Science Amman Jordan Al-Zaytoonah University of Jordan Department of Software Engineering Amman11733 Jordan

ISBN: (纸本)9781665428705

Network security risks are increasing at an exponential rate as Internet technology advances. Keeping the network protected is one of the most challenging of network security. Many security mechanisms were implemented to detect and identify any malicious activity on the network. Intrusion Detection system (IDS) one of the most used mechanisms to reduce the effects of these risks. Machine Learning (ML) classifiers are widely begin used to classify the network traffic as normal or abnormal. In this paper a comparative evaluation of the following ML classifiers: LogisticRegression, Multinomial Naive Bayesian, Gaussian Naive Bayesian, Bernoulli Naive Bayesian, k-Nearest Neighbors, Decision Tree, Adaptive Boosting, Random Forest, Multilayer Perceptron, and GradientBoosting is performed to specify the best classifier in identifying intrusion detection. The used evaluation metrics are accuracy, precision, and F-measure. The UNSW-NB15 dataset is used to assess ML classifiers. The experimental results show that the RandomForest classifier outperforms the other classifiers in terms of accuracy at 87%, precision 98%, and F-measure 84%. © 2021 IEEE.

关键词： Decision trees

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An Intelligent system for Cucumber Leaf Disease Diagnosis Based on the Tuned Convolutional Neural Network Algorithm

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Mobile Information systems 2022年第1期2022卷

作者： Omer, Saman M. Ghafoor, Kayhan Z. Askar, Shavan K. Department of Technical Information System Engineering Erbil Technical Engineering College Erbil Polytechnic University Kurdistan Region Erbil Iraq Department of Computer Science College of Basic Education University of Raparin Kurdistan Region Ranya Iraq Department of Computer Science Knowledge University Kurdistan Region Erbil44001 Iraq Department of Software and Informatics Engineering Salahaddin University-Erbil Kurdistan Region Erbil44001 Iraq

In agriculture farming, pests and other plant diseases are the most imperative factor that causes significant hindrance to cucumber production and its quality. Farmers around the globe are currently facing difficulty in recognizing various cucumber leaf diseases, which is imperative to preventing leaf diseases effectively. Manual techniques to diagnose cucumber diseases are often time-consuming, subjective, and laborious. To address this issue, this paper proposes a tuned convolutional neural network (CNN) algorithm to recognise five cucumber diseases and healthy leaves that comprises image enhancement, feature extraction, and classification. Data augmentation methods were utilized as a preprocessing step to enlarge the datasets, and it was also to decrease the chance of overfitting. Automatically features are extracted by using CNN layers. Finally, five cucumber leaf diseases and one healthy leaf are classified. Furthermore, to overcome the lack of a public dataset, a new dataset of cucumber leaf diseases has been constructed that includes spider, leaf miner, downy mildew, powdery mildew, one viral disease, and healthy class leaves. The dataset has a total of 4868 cucumber leaf images. In order to prove the authenticity of the proposed CNN, comparative experiments were conducted using pretrained models (AlexNet, Inception-V3, and ResNet-50). The proposed CNN achieves a recognition accuracy of 98.19% with the augmented dataset and 100% with the publicly plant disease dataset. The experimental results confirm that the proposed CNN algorithm was efficient for recognizing the cucumber leaf diseases compared with other algorithms. © 2022 Saman M. Omer et al.

关键词： Image enhancement

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Neural Topic Modeling with Deep Mutual Information Estimation

arXiv

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arXiv 2022年

作者： Xu, Kang Lu, Xiaoqiu Li, Yuan-Fang Wu, Tongtong Qi, Guilin Ye, Ning Wang, Dong Zhou, Zheng School of Computer Science Nanjing University of Posts and Telecommunications China School of Computer Science and Engineering Southeast University China Faculty of Information Technology Monash University Australia Department of Earth System Science Tsinghua University Beijing100084 China

The emerging neural topic models make topic modeling more easily adaptable and extendable in unsupervised text mining. However, the existing neural topic models is difficult to retain representative information of the documents within the learnt topic representation. In this paper, we propose a neural topic model which incorporates deep mutual information estimation, i.e., Neural Topic Modeling with Deep Mutual Information Estimation(NTM-DMIE). NTM-DMIE is a neural network method for topic learning which maximizes the mutual information between the input documents and their latent topic representation. To learn robust topic representation, we incorporate the discriminator to discriminate negative examples and positive examples via adversarial learning. Moreover, we use both global and local mutual information to preserve the rich information of the input documents in the topic representation. We evaluate NTM-DMIE on several metrics, including accuracy of text clustering, with topic representation, topic uniqueness and topic coherence. Compared to the existing methods, the experimental results show that NTM-DMIE can outperform in all the metrics on the four datasets. © 2022, CC BY.

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CHARLIE: A Chatbot That Recommends Daily Fitness and Diet Plans

CHARLIE: A Chatbot That Recommends Daily Fitness and Diet Pl...

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IEEE Annual Conference on Pervasive Computing and Communications Workshops (PerCom)

作者： Deepanjali Chowdhury Ahana Roy Sreenivasan Ramasamy Ramamurthy Nirmalya Roy Department of Electrical and Computer Engineering Texas A&M University College Station United States Howard County Public School System Maryland United States Department of Computer Science Bowie State University Bowie United States Department of Information Systems University of Maryland Baltimore County Baltimore United States

Managing a work-life balance has always been challenging, especially after the recent trend of working from home, which has made maintaining one's fitness and diet regime strenuous. Failing to adhere to a fitness and diet plan has been shown to cause long-term effects on a person's health including obesity and shortened lifespans. Currently, people plan their fitness and diet plans around their schedule, but these tasks are challenging to maintain. Users tend to give up these plans due to a lack of time and planning. To help with better planning for a fitness and diet regime, we propose, CHARLIE, a chatbot that works around a user's schedule to intelligently recommend diets and fitness goals based on their calendar. CHARLIE is a recommendation system that suggests the users' a certain meal and fitness activities based on the amount of time they have left in their day and the number of calories they lose.

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Quantum reversible circuits for multiplicative inverse

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EPJ Quantum Technology 2022年第1期9卷 1-17页

作者： Luo, Qing-bin Yang, Guo-wu Li, Xiao-yu Li, Qiang Department of Computer Science and Technology School of Information Engineering Hubei Minzu University Enshi China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Big data research Center & School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu University of Information Technology Chengdu China

The synthesis of quantum circuits for multiplicative inverse over $\operatorname{GF}(2^{8})$ are discussed in this paper. We first convert the multiplicative inverse operation in $\operatorname{GF}(2^{8})$ to arithmetic operations in the composite field $\operatorname{GF}((2^{4})^{2})$ , and then discuss the expressions of the square calculation, the inversion calculation and the multiplication calculation separately in the finite field $\operatorname{GF}(2^{4})$ , where the expressions of multiplication calculation in $\operatorname{GF}(2^{4})$ are given directly in $\operatorname{GF}(2^{4})$ and given through being transformed into the composite field $\operatorname{GF}((2^{2})^{2})$ . Then the quantum circuits of these calculations are realized one by one. Finally, two quantum circuits for multiplicative inverse over $\operatorname{GF}(2^{8})$ are synthesized. They both use 21 qubits, the first quantum circuit uses 55 Toffoli gates and 107 CNOT gates and the second one uses 37 Toffoli gates and 209 CNOT gates. As an example of the application of multiplication inverse, we apply these quantum circuits to the implementations of the S-box quantum circuit of the AES cryptographic algorithm. Two quantum circuits for implementing the S-box of the AES cryptographic algorithm are presented. The first quantum circuit uses 21 qubits, 55 Toffoli gates, 131 CNOT gates and 4 NOT gates and the second one uses 21 qubits, 37 Toffoli gates, 233 CNOT gates and 4 NOT gates. Through the evaluation of quantum cost, the two quantum circuits of the S-box of AES cryptographic algorithm use less quantum resources than the existing schemes.

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Economic and environmental analysis of a solar-powered ev charging system in india—a case study 2nd

Economic and environmental analysis of a solar-powered ev ch...

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2nd International Conference on Electrical and Electronics engineering, ICEEE 2021

作者： Shrivastava, Prashant Soon, Teykok Mekhilef, Saad Ahmad, Furkan Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia Power Electronics and Renewable Energy Laboratory Department of Electrical Engineering Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia School of Software and Engineering Faculty of Science Engineering and Technology Swinburne University of Technology MelbourneVIC3122 Australia Indian Institute of Technology New Delhi Delhi110016 India

ISBN: (纸本)9789811607486

With the growing environmental concern, the demand for electric vehicle is increasing in India. However, the limited existing charging facilities slow down the rate of adoption in the market. Presently, the solar-based charging system is gaining popularity, due to its low greenhouse gas emission. In this study, a case study for different solar charging systems suited in Delhi is presented. The economic and environmental analysis of different solar-based EV charging systems utilized for charging three types of commercial EVs such as 2, 3, and 4-W is explained. The cost of energy required for 100 km drive is lower with vehicle integrating PV charging system;however, it can act as a supportive system for driving range improvement. The analysis shows that the economically solar rooftop charging system is suitable for all types of EVs. The CO2 emission produced by all types of solar-based EV charging systems is lower than coal-based charging systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Solar energy

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