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IEEE International Symposium on Embedded Multicore Socs (MCSoC)

作者： Jiahua Xu Ningyi Xie Xinwei Lee Yoshiyuki Saito Nobuyoshi Asai Dongsheng Cai Graduate School of Science and Technology University of Tsukuba Japan School of Computing and Information Systems Singapore Management University Singapore Graduate School of Computer Science and Engineering University of Aizu Japan School of Computer Science and Engineering University of Aizu Japan Faculty of Engineering Information and Systems University of Tsukuba Japan

ISBN: (数字)9798331530471

ISBN: (纸本)9798331530488

The research on Variational Quantum Algorithms (VQAs) has gained significant momentum because of their promising practicality in the noisy intermediate-scale quantum (NISQ) era. Recent studies highlight the potential of VQAs in reinforcement learning (RL) by replacing classical components with parameterized quantum circuits (PQCs). Building on this, we propose a quantum Q-learning model for the Capacitated Vehicle Routing Problem (CVRP), combining a PQC with an RL training process. We present a PQC for embedding both static and dynamic states in RL environments. The proposed PQC approximates the Q-value function by using the expectation values of different observables. Experimental results demonstrate that the proposed PQC outperforms the existing PQC for the CVRP with fewer quantum resources. Furthermore, our method shows competitive performance compared to the classical counterpart.

关键词： Training Q-learning Quantum algorithm Multicore processing Vehicle routing Buildings Noise measurement Integrated circuit modeling Vehicle dynamics Quantum circuit

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PPM-HC: A method for helping project portfolio management based on topic hierarchy learnings

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International Journal of Business Intelligence and Data Mining 2021年第3期18卷 364-382页

作者： Pinto, Ricardo A.M. Bernardini, Flavia Marcacini, Ricardo M. Graduate Program in Industrial Engineering and Computing Systems Fluminense Federal University Jardim Bela Vista Rio das OstrasRJ Brazil Computing Institute Fluminense Federal University São Domingos NiteróiRJ Brazil Information Systems Federal University of Mato Grosso do Sul P.O. Box 210 Três LagoasMS Brazil

The projects categorisation is a crucial step in the project portfolio management (PPM). Categorising projects allows the organisation to identify categories with a lack or excess of projects, according to its strategic objectives. In this work, we present a new method for project portfolio management based on hierarchical clustering (PPM-HC) to organise the projects at several levels of abstraction. In the PPM-HC, similar projects are allocated to the same clusters and subclusters. PPM-HC automatically learns an understandable topic hierarchy from the project portfolio dataset, thereby facilitating the (human) task of exploring, analysing and prioritising the projects of the organisation. We also proposed a card sorting-based technique which allows the evaluation of the projects categorisation using an intuitive visual map. We carried out an experimental evaluation based on a benchmark dataset and we also presented a real-world case study. The results show that the proposed PPM-HC method is promising. © 2021 Inderscience Enterprises Ltd.

关键词： Investments

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Multiobjective Evolutionary Component Effect on Algorithm Behaviour

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ACM Transactions on Evolutionary Learning and Optimization 2024年第2期4卷 1-24页

作者： Lavinas, Yuri Ladeira, Marcelo Ochoa, Gabriela Aranha, Claus University of Toulouse 2 avenue Hubert Curien Toulouse31037 France University of Brasilia CIC building Est-CIC campus Darcy Ribeiro Asa Norte - DF Brasília70910-900 Brazil Computing Science and Mathematics School of Natural Sciences University of Stirling StirlingFK9 4LA United Kingdom The University of Tsukuba Graduate School of Systems and Information Engineering Tennodai 1-1-1 Ibaraki Tsukuba City305-8573 Japan

The performance of multiobjective evolutionary algorithms (MOEAs) varies across problems, making it hard to develop new algorithms or apply existing ones to new problems. To simplify the development and application of new multiobjective algorithms, there has been an increasing interest in their automatic design from their components. These automatically designed metaheuristics can outperform their human-developed counterparts. However, it is still unknown what are the most influential components that lead to performance improvements. This study specifies a new methodology to investigate the effects of the final configuration of an automatically designed algorithm. We apply this methodology to a tuned Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D) designed by the iterated racing (irace) configuration package on constrained problems of 3 groups: (1) analytical real-world problems, (2) analytical artificial problems and (3) simulated real-world. We then compare the impact of the algorithm components in terms of their Search Trajectory Networks (STNs), the diversity of the population, and the anytime hypervolume values. Looking at the objective space behavior, the MOEAs studied converged before half of the search to generally good HV values in the analytical artificial problems and the analytical real-world problems. For the simulated problems, the HV values are still improving at the end of the run. In terms of decision space behavior, we see a diverse set of the trajectories of the STNs in the analytical artificial problems. These trajectories are more similar and frequently reach optimal solutions in the other problems. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Multiobjective optimization

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Multiomics Reveals Induction of Neuroblastoma SK-N-BE(2)C Cell Death by Mitochondrial Division Inhibitor 1 through Multiple Effects

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Journal of Proteome Research 2024年第1期23卷 301-315页

作者： Wang, Wei-Hsuan Kao, Yi-Chun Hsieh, Chiao-Hui Tsai, Shin-Yu Cheung, Chantal Hoi Yin Huang, Hsuan-Cheng Juan, Hsueh-Fen Genome and Systems Biology Degree Program Academia Sinica and National Taiwan University Taipei 106 Taiwan Department of Life Science National Taiwan University Taipei 106 Taiwan Center for Computational and Systems Biology National Taiwan University Taipei 106 Taiwan Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei 112 Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei 106 Taiwan Center for Advanced Computing and Imaging in Biomedicine National Taiwan University Taipei 106 Taiwan

Mitochondrial division inhibitor 1 (Mdivi-1) is a well-known synthetic compound aimed at inhibiting dynamin-related protein 1 (Drp1) to suppress mitochondrial fission, making it a valuable tool for studying mitochondrial dynamics. However, its specific effects beyond Drp1 inhibition remain to be confirmed. In this study, we employed integrative proteomics and phosphoproteomics to delve into the molecular responses induced by Mdivi-1 in SK-N-BE(2)C cells. A total of 3070 proteins and 1945 phosphorylation sites were identified, with 880 of them represented as phosphoproteins. Among these, 266 proteins and 97 phosphorylation sites were found to be sensitive to the Mdivi-1 treatment. Functional enrichment analysis unveiled their involvement in serine biosynthesis and extrinsic apoptotic signaling pathways. Through targeted metabolomics, we observed that Mdivi-1 enhanced intracellular serine biosynthesis while reducing the production of C24:1-ceramide. Within these regulated phosphoproteins, dynamic dephosphorylation of proteasome subunit alpha type 3 serine 250 (PSMA3-S250) occurred after Mdivi-1 treatment. Further site-directed mutagenesis experiments revealed that the dephosphorylation-deficient mutant PSMA3-S250A exhibited a decreased cell survival. This research confirms that Mdivi-1’s inhibition of mitochondrial division leads to various side effects, ultimately influencing cell survival, rather than solely targeting Drp1 inhibition. © 2023 American Chemical Society.

关键词： Mdivi-1 multiomics neuroblastoma phosphoproteome proteome targeted metabolome

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Experimental Evaluation of a Checklist-Based Inspection Technique to Verify the Compliance of Software systems with the Brazilian General Data Protection Law

arXiv

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arXiv 2023年

作者： Cerqueira, Diego André de Mello, Rafael Maiani Travassos, Guilherme Horta Systems Engineering and Computer Science Graduate Program Federal University of Rio de Janeiro Brazil Computing Institute Federal University of Rio de Janeiro Brazil

Background/Context: Recent laws to ensure the security and protection of personal data establish new software requirements. Consequently, new technologies are needed to guarantee software quality under the perception of privacy and protection of personal data. Therefore, we created a checklist-based inspection technique (LGPDCheck) to support the identification of defects in software artifacts based on the principles established by the Brazilian General Data Protection Law (LGPD). Objective/Aim: To evaluate the effectiveness and efficiency of LGPDCheck for verifying privacy and data protection (PDP) in software artifacts compared to ad-hoc techniques. Method: To assess LGPDCheck and ad-hoc techniques experimentally through a quasi-experiment (two factors, five treatments). The data will be collected from IoT-based health software systems built by software engineering students from the Federal University of Rio de Janeiro. The data analyses will compare results from ad-hoc and LGPDCheck inspections, the participant's effectiveness and efficiency in each trial, defects' variance and standard deviation, and time spent with the reviews. The data will be screened for outliers, and normality and homoscedasticity will be verified using the Shapiro-Wilk and Levene tests. Nonparametric or parametric tests, such as the Wilcoxon or Student's t-tests, will be applied as appropriate. © 2023, CC BY-NC-ND.

关键词： Data privacy

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A Highly Secure and Accurate System for COVID-19 Diagnosis from Chest X-Ray Images

A Highly Secure and Accurate System for COVID-19 Diagnosis f...

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： Tuy Tan Nguyen Tianyi Chen Ian Philippi Quoc Bao Phan Shunri Kudo Samsul Huda Yasuyuki Nogami School of Informatics Computing and Cyber Systems Northern Arizona University USA Graduate School of Environmental Life Natural Science and Technology Okayama University Japan Green Innovation Center Okayama University Japan

ISBN: (数字)9798350387179

ISBN: (纸本)9798350387186

Global healthcare systems face growing pressure as populations rise. This can lead to longer wait times and an increased risk of treatment delays or misdiagnosis. Artificial intelligence (AI) diagnostic systems are being developed to address these challenges, but concerns exist about their accuracy and data security. This study introduces a robust AI telehealth system that offers a two-pronged approach. It utilizes a cutting-edge image analysis method, vision transformer, to enhance diagnostic accuracy, while also incorporating post-quantum cryptography algorithm, Kyber, to ensure patient privacy. Furthermore, an interactive visualization tool aids in interpreting the diagnostic results, providing valuable insights into the model's decisionmaking process. This translates to faster diagnoses and potentially shorter wait times for patients. Extensive testing with various datasets has demonstrated the system's effectiveness. The optimized model achieves a remarkable 95.79% accuracy rate in diagnosing COVID-19 from chest X-rays, with the entire process completed in under five seconds.

关键词： COVID-19 Computer vision Accuracy Data visualization Medical services Transformers Artificial intelligence

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Securing Data Transmission in Noisy Channels: A Synergistic Approach using Kyber and BCH Codes

Securing Data Transmission in Noisy Channels: A Synergistic ...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Linh Nguyen Andri Santoso Samsul Huda Yasuyuki Nogami Tuy Tan Nguyen School of Informatics Computing and Cyber Systems Northern Arizona University USA Graduate School of Environmental Life Natural Science and Technology Okayama University Japan Green Innovation Center Okayama University Japan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

The proliferation of the Internet of Things leads to the sharing of more data among diverse stakeholders, ranging from individual users to large enterprises. However, ensuring the security of this data exchange while simultaneously minimizing errors during transmission presents a complex challenge. Due to the involvement of numerous devices and users capable of data sharing, the dynamic and heterogeneous nature of the environment leads to constant changes. In this paper, we integrate the Kyber algorithm for post-quantum security with Bose-Chaudhuri-Hocquenghem (BCH) codes for error correction. We validate our approach by transmitting images from the widely- used CIFAR-10 dataset in encrypted mode over noisy communication channels. The system demonstrates effective image encryption and robust error correction capabilities.

关键词： Heuristic algorithms Real-time systems Encoding Error correction codes Error correction Encryption Noise measurement

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SnapSafe: Enabling Selective Image Privacy Through YOLO and AES-Protected Facial Encryption with QR Code

SnapSafe: Enabling Selective Image Privacy Through YOLO and ...

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International Technical Conference o Circuits/systems, Computers and Communications (ITC-CSCC)

作者： Andri Santoso Samsul Huda Tuy Tan Nguyen Yuta Kodera Yasuyuki Nogami Graduate School of Environmental Life Natural Science and Technology Okayama University Japan School of Informatics Computing and Cyber Systems Northern Arizona University USA Green Innovation Center Okayama University Japan

ISBN: (数字)9798350379051

ISBN: (纸本)9798350379068

In the digital age, organizations commonly use photos to share their activities for brand visibility. However, it is crucial to safeguard the facial information of individuals depicted in these photos to prevent potential misuse. In this paper, we propose a single-party security system for enabling selective image privacy with a focus on facial regions, called SnapSafe. It adopts the YOLOv8 deep learning model for face detection, AES encryption for security, and QR technology to store the encrypted face region coordinates. Our evaluation assesses the effectiveness of the system through the usability of its face locking and unlocking processes, alongside an analysis of its running time. The results demonstrate the system's proficiency in executing face protection tasks with high accuracy and minimal time overhead, thus indicating its suitability for real-time applications.

关键词： Deep learning Data privacy Accuracy Real-time systems Encryption Face detection Usability

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Mobile Application for Elderly Care 2

Mobile Application for Elderly Care

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Jose, Fernando Livaldo Mahardhika, Mozan Hafiz Sukiman, Nathanael Adolf Warnars, Harco Leslie Hendric Spits Ramadhan, Arief Utomo, Wiranto Herry Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara Univerisity Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia President University Faculty of Computing Department of Magister Science of Information Technology West Java17530 Indonesia

ISBN: (纸本)9781665400527

This paper discusses the design and implementation process of mobile applications used by nurses to communicate with the elderly or with people appointed to represent the elderly in using this mobile application. This mobile application is expected to help caregivers or nurses monitor the health condition of the elderly, and this mobile application has several functions that make it complete. These functions include submitting weekly reports, communicating with others via forums, and providing relevant information about the elderly and how to deal with them, including news and government regulations on elderly care. This mobile application uses case diagrams to describe business processes and class diagrams to illustrate database design. As for the implementation, android studio and MySQL database are used for database storage. This paper is limited to 9 references for literature review previous similar research by searching for publication titles with the sentences 'mobile application'+elderly+care using quotation marks and without quotation marks for the words elderly and care for all years of publication. © 2022 IEEE.

关键词： Mobile computing

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On Efficient Processing of Queries for Live Multi-Streaming Soiree Organization

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IEEE Transactions on Services computing 2023年第4期16卷 2812-2826页

作者： Kankeu Fotsing, C.P. Shen, Chih-Ya Huang, Liang-Hao Chen, Yi-Shin Lee, Wang-Chien Yang, De-Nian International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei115 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu300 Taiwan National Tsing Hua University Department of Computer Science Hsinchu300 Taiwan Academia Sinica Institute of Information Science Taipei115 Taiwan Pennsylvania State University Department of Computer Science and Engineering State CollegePA16801 United States

Real-time social interactions and multi-streaming are two critical features of live streaming services. In this paper, we formulate a new fundamental service query, Social-aware Diverse and Preferred Organization Query (SDSQ), that jointly selects a set of diverse and preferred live streaming channels and a group of socially tight viewers for organization of a live multi-streaming soiree. We prove that SDSQ is NP-hard and inapproximable within any factor, and design SDSSel, a 2-approximation algorithm with a guaranteed error bound. Moreover, we study SDSQ-T, a special case of SDSQ, where the social graph is a threshold graph, and propose TDSSel, a 2-approximation algorithm without any error to SDSQ-T. We propose two pruning strategies, PCP and CDP to boost SDSSel and TDSSel. We further propose a more challenging but practical service query, Generalized Social-aware Maximum Preferred and Diverse Query (GSPQ), a generalization of SDSQ. We design GPDSel, a 4-approximation algorithm for GSPQ with a guaranteed error bound. We propose a strategy to improve the approximation ratios of the proposed algorithms. A user study on Twitch validates SDSQ, and the large-scale experiments on real datasets demonstrate the superiority of the proposed algorithms over several baselines for live-streaming services. © 2008-2012 IEEE.

关键词： Approximation algorithms

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