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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Hermanus, Davy Ronald Sasmoko Indrianti, Yasinta Research Interest Group in Educational Technology Bina Nusantara University Computer Science Department Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Research Interest Group in Educational Technology Bina Nusantara University Faculty of Humanities Primary Teacher Education Department Jakarta Indonesia Universitas Agung Podomoro Entrepreneurship Department Jakarta Indonesia

ISBN: (纸本)9798350389654

This paper examines the incorporation of DNA testing into intelligent education systems to develop customized learning plans that respond to the specific needs of each student. Through the examination of distinct genetic indicators associated with personality traits, talent, and inborn abilities, educators can formulate approaches that optimize academic achievement and boost the overall welfare of students. This approach not only enhances learning outcomes but also promotes a supportive and inclusive educational environment. The study critically examines the present state of literature regarding the correlation between genetics and learning. It digs into the ethical implications surrounding this topic and shows case studies that provide evidence of the effectiveness of teaching methods informed by DNA analysis. The results underscore the capacity of DNA testing to transform education by enhancing its adaptability and responsiveness to the distinct genetic composition of individual students. This underscores the need for additional research and ethical guidelines to guarantee responsible integration in educational environments. © 2024 IEEE.

关键词： Federated learning

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Lattice Parameters of B2 and B19′ Phases in Ti–Ni Alloys Near Transformation Temperatures: Effects of Ni Concentration and Temperature

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Shape Memory and Superelasticity 2025年 1-14页

作者： Hikosaka, Gen Shinohara, Yuri Matsumura, Ryutaro Nishida, Minoru Inamura, Tomonari School of Materials and Chemical Technology Institute of Science Tokyo Yokohama Japan Graduate School of Informatics and Engineering The University of Electro-Communications Chofu Japan Materials and Structures Laboratory Institute of Integrated Research Institute of Science Tokyo Yokohama Japan Laboratory for Future Interdisciplinary Research of Science and Technology Institute of Integrated Research Institute of Science Tokyo Yokohama Japan Department of Advanced Materials Science and Engineering Faculty of Engineering Sciences Kyushu University Kasuga Japan

The Ni concentration and temperature dependence of the lattice parameters of the B2 and B19′ phases in binary Ti–Ni alloys was systematically clarified near the martensitic transformation temperatures, using samples with finely varied Ni concentrations ranging from 50.00 to 51.00 at.%. The differences between the present data and previously reported values were quantitatively explained and reinterpreted in terms of uncertainties in Ni concentration, measurement conditions, thermal history, and extrapolation methods. Furthermore, based on the lattice parameters obtained in this study, the effect of Ni concentration on the suppression of transformation-induced dislocations and the stabilization of thermal cycling behavior was discussed in terms of geometrical incompatibility. From the perspectives of composition increment, temperature steps, consistency in thermal history, and transparency of extrapolation procedure, the present dataset is considered to be among the most accurate, precise, and consistent lattice parameter datasets currently available. This dataset provides a highly reliable basis for evaluating the variation in lattice parameters among literature and serves as a foundation for future investigations into phase transformation behavior in Ti–Ni alloys.

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Blockchain-based Security Framework for Metaverse: A Decentralized Approach 15

Blockchain-based Security Framework for Metaverse: A Decentr...

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15th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2023

作者： Rajawat, Anand Singh Goyal, S.B. Solanki, RamKumar Raboaca, Maria Simona Mihaltan, Traian Candin Illes, Zoltan Verma, Chaman School of Computer Science & Engineering Sandip University Nashik India City University Faculty of Information Technology Petaling Jaya Malaysia Research and Development Institute for Cryogenics and Isotopic Technologies Ramnicu Icsi Energy Department National Valcea Romania Technical University of Cluj-Napoca Faculty of Building Services Cluj-Napoca40033 Romania Eötvös Loránd University Faculty of Informatics Department of Media and Educational Informatics Budapest Hungary

ISBN: (纸本)9798350321388

People can act out fake social exchanges in the Metaverse, which is an online community. Security has become a problem in the Metaverse because there are so many online transactions and digital assets. In this thesis, a Blockchain-based security system for the Metaverse is proposed. This would be a decentralised way to keep the virtual world safe. Our system uses Blockchain's autonomous structure to make sure that all financial transactions in the Metaverse are safe, anonymous, and true. We suggest a new consensus process that combines Proof of Stake (PoS) and Proof of Authority (PoA) to make networks safer and allow them to grow. We also have a user-focused, decentralised identity management system that keeps their information safe. We also suggest a way to process Metaverse transactions safely that is based on smart contracts. Our method makes sure that transactional proof, recording, and validation are done in a safe and reliable way. We also show a reputation system that benefits people who follow the law and punishes people who break the law. Lastly, we test how well our suggested structure works with simulations and real-world tests. The results show that our way works to reduce possible security risks in the Metaverse and create a safe, scalable environment for online business. Overall, our Blockchain-based Security Framework for Metaverse: A Decentralised Approach is a good way to keep the security and privacy of digital activities in Metaverse. © 2023 IEEE.

关键词： Blockchain

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An Enhanced Residual Networks Based Framework for Early Alzheimer’s Disease Classification and Diagnosis 6th

An Enhanced Residual Networks Based Framework for Early Alzh...

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6th International Conference on Communication, Devices and Networking, ICCDN 2022

作者： Awotunde, Joseph Bamidele Sur, Nath Samarendra Imoize, Agbotiname Lucky Misra, Sanjay Gaber, Tarek Department of Computer Science Faculty of Information and Communication Sciences University of Ilorin Kwara State Ilorin240003 Nigeria Department of Electronics and Communication Engineering Sikkim Manipal Institute of Technology Sikkim Manipal University East Sikkim Rangpo Majitar737136 India Department of Electrical and Electronics Engineering Faculty of Engineering University of Lagos Akoka Lagos100213 Nigeria Department of Electrical Engineering and Information Technology Institute of Digital Communication Ruhr University Bochum44801 Germany Department of Applied Data Science Institute of Energy Technology Halden Norway Faculty of Computers and Informatics Suez Canal University Ismailia41522 Egypt School of Science Engineering and Environment University of Salford ManchesterM5 4WT United Kingdom

ISBN: (纸本)9789819919826

Alzheimer's disease (AD) is a long-lasting, degenerative brain illness for which there is now no successful treatment. However, there are medications that can delay its growth and stop its tracks. Therefore, stopping and regulating the progression of AD depends greatly on its early diagnosis. Computer-aided diagnosis (CAD) in health care has become more and more dependent on deep learning technologies. This has help in early diagnosis and detection of various disease in health care. New techniques for the early diagnosis of neurocognitive abnormalities are now possible thanks to advancements in medical imaging and computational capacity in an effort to stop or slow down cognitive aging. Therefore, this study proposes a residual network (ResNet) type 50 for early diagnosis of AD. Convolutional neural networks (CNNs) are first used in the study for features extraction and then make the ultimate diagnosis using the ResNet-50. To create a better architecture, the problem of AD diagnosis will be addressed by utilizing and incorporating ResNet-50, which improves the current categorization problem's accuracy to its maximum. With a 98.8% accuracy rate, the proposed model using ResNet-50 produces encouraging findings for AD prediction. The study reveals that the model can effectively circumvent CNNs for the diagnostic issue with AD. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computer aided diagnosis

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IoT-Based Autonomous Baby Monitoring System Using Mobile App Control 1

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8th International Conference on Computational science and technology, ICCST 2021

作者： Chung, Gwo Chin Teong, Khan Vun Tan, Soo Fun Sundarajoo, Ruven A/L Faculty of Engineering Multimedia University Cyberjaya63100 Malaysia Faculty of Computing and Informatics Universiti Malaysia Sabah Kota Kinabalu88400 Malaysia Preparatory Centre for Science and Technology Universiti Malaysia Sabah Kota Kinabalu88400 Malaysia

ISBN: (数字)9789811685156

ISBN: (纸本)9789811685149

In this modern world, almost 80% of parents have to work in order to balance their financial demands. The probability of providing better childcare, especially for babies is reducing. Although hiring a guardian or sending babies to daycare centers can temporarily solve the issue, it does not reduce the anxiety and stress of the parents due to more and more child abuses being reported every year. During this Covid19 pandemic, the need for an alternative better solution is urgent when some parents are forced to undergo quarantine for at least a few weeks. In this paper, we propose to develop a long-ranged baby monitoring and controlling system. The system consists of hardware architecture that is inter-connected with an IoT network to monitor the real-time condition of the baby such as crying, awakening and cleanliness, and its surrounding environment such as temperature, humidity and motion. In the proposal, the overall system operation involves four different phases: data collection, information sharing and processing, output display and notification, and user control. At the end of the project, a prototype has been successfully constructed to collect the monitoring data, and then share and display them to the users accurately via mobile app. In addition, users can also remotely perform basic control over any components or devices that are connected to the system. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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Weapons Detection for Security and Video Surveillance Using CNN and YOLO-V5s

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Computers, Materials & Continua 2022年第2期70卷 2761-2775页

作者： Abdul Hanan Ashraf Muhammad Imran Abdulrahman M.Qahtani Abdulmajeed Alsufyani Omar Almutiry Awais Mahmood Muhammad Attique Mohamed Habib Department of Computer Science Shaheed Zulfikar Ali Bhutto Institute of Science and TechnologyIslamabad44000Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia College of Applied Computer Science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Department of Computer Science HITEC UniversityTaxila47080Pakistan College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Faculty of Engineering Port Said UniversityPort Fuad CityEgypt

In recent years,the number of Gun-related incidents has crossed over 250,000 per year and over 85%of the existing 1 billion firearms are in civilian hands,manual monitoring has not proven effective in detecting *** is why an automated weapon detection system is *** automated convolutional neural networks(CNN)weapon detection systems have been proposed in the past to generate good ***,These techniques have high computation overhead and are slow to provide real-time detection which is essential for the weapon detection *** models have a high rate of false negatives because they often fail to detect the guns due to the low quality and visibility issues of surveillance *** research work aims to minimize the rate of false negatives and false positives in weapon detection while keeping the speed of detection as a key *** proposed framework is based on You Only Look Once(YOLO)and Area of Interest(AOI).Initially,themodels take pre-processed frames where the background is removed by the use of the Gaussian blur *** proposed architecture will be assessed through various performance parameters such as False Negative,False Positive,precision,recall rate,and F1 *** results of this research work make it clear that due to YOLO-v5s high recall rate and speed of detection are *** reached 0.010 s per frame compared to the 0.17 s of the Faster *** is promising to be used in the field of security and weapon detection.

关键词： Video surveillance weapon detection you only look once convolutional neural networks

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Nice Cross-gramian, the Generalized Symmetry and Determination of Controller Structure for Multivariable Switched Systems

Nice Cross-gramian, the Generalized Symmetry and Determinati...

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2022 International Conference on Electrical, Computer, Communications and Mechatronics engineering, ICECCME 2022

作者： Tahavori, Maryamsadat Shaker, Hamid Reza Dashti, Rahman Technical University of Denmark DTU Engineering Technology Ballerup Denmark Center for Energy Informatics University of Southern Denmark Odense Denmark Persian Gulf University Faculty of Intelligent Systems Engineering & Data Science Bushehr*** Iran

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

In this paper, the determination of a control struc-ture for discrete-time MIMO switched systems is addressed. In the first step, for discrete-time switched systems, the concept of nice cross-gramians is proposed and investigation is done on whether the suggested nice cross-gramian exists. It has been demonstrated that the nice cross-gramian can be achieved as a solution to a specific algebraic matrix equation, if it exists. While the proposed cross-gramian has a wide range of uses, including model reduction, in this paper, it has been utilized to form the Nice Hankel Interaction Index Array (NHIIA) for control structure selection. The control structure determination strategy which is proposed is one of the few that supports switched systems, takes advantage of gramian-based techniques, and is computationally more effective than its only counterpart. © 2022 IEEE.

关键词： Matrix algebra

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A Physically Unclonable Function Using Time-to-Digital Converter with Linearity Self-Calibration and its FPGA Implementation

A Physically Unclonable Function Using Time-to-Digital Conve...

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International Test Conference in Asia (ITC-Asia)

作者： Kentaroh Katoh Shuhei Yamamoto Zheming Zhao Yujie Zhao Shogo Katayama Anna Kuwana Takayuki Nakatani Kazumi Hatayama Haruo Kobayashi Keno Sato Takashi Ishida Toshiyuki Okamoto Tamotsu Ichikawa Dept. of Electronics Engineering and Computer Science Faculty of Engineering Fukuoka University Fukuoka Japan Faculty of Science of technology Division of Electronics and Informatics Gunma University ROHM Semiconductor Yokohama Japan

This paper presents a physically unclonable function (PUF) using flash time-to-digital converter (TDC) with linearity self-calibration. The proposed PUF utilizes that the variation of delay of delay elements of TDC is unique to the device and unclonable. The proposed PUF is constructed using the flash TDC with linearity self-calibration using histogram method. With the linearity self-calibration operation, variation of delay elements is estimated. The response output of the PUF is calculated using the estimated variation and the challenge inputs. The proposed PUF is a simple digital circuit consisting of basic digital elements. It is easy to design and implement to both SoC and FPGA. It can be used as not only strong PUF but also as a TDC with fine linearity. The experimental results with Artix7 FPGA show that the intra-chip variation is 8.9 % and the inter-chip variation is 46.9 %. The probability of the correct identification is 99.8 %. Extra resources to construct the proposed PUF are 33.7 % of the resources of the TDC with linearity self-calibration.

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Independent Set Reconfiguration on Directed Graphs 47

Independent Set Reconfiguration on Directed Graphs

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47th International Symposium on Mathematical Foundations of Computer science, MFCS 2022

作者： Ito, Takehiro Iwamasa, Yuni Kobayashi, Yasuaki Nakahata, Yu Otachi, Yota Takahashi, Masahiro Wasa, Kunihiro Graduate School of Information Sciences Tohoku University Sendai Japan Graduate School of Informatics Kyoto University Kyoto Japan Graduate School of Information Science and Technology Hokkaido University Sapporo Japan Division of Information Science Nara Institute of Science and Technology Ikoma Japan Graduate School of Informatics Nagoya University Nagoya Japan Faculty of Science and Engineering Hosei University Tokyo Japan

ISBN: (纸本)9783959772563

Directed Token Sliding asks, given a directed graph and two sets of pairwise nonadjacent vertices, whether one can reach from one set to the other by repeatedly applying a local operation that exchanges a vertex in the current set with one of its out-neighbors, while keeping the nonadjacency. It can be seen as a reconfiguration process where a token is placed on each vertex in the current set, and the local operation slides a token along an arc respecting its direction. Previously, such a problem was extensively studied on undirected graphs, where the edges have no directions and thus the local operation is symmetric. Directed Token Sliding is a generalization of its undirected variant since an undirected edge can be simulated by two arcs of opposite directions. In this paper, we initiate the algorithmic study of Directed Token Sliding. We first observe that the problem is PSPACE-complete even if we forbid parallel arcs in opposite directions and that the problem on directed acyclic graphs is NP-complete and W[1]-hard parameterized by the size of the sets in consideration. We then show our main result: a linear-time algorithm for the problem on directed graphs whose underlying undirected graphs are trees, which are called polytrees. Such a result is also known for the undirected variant of the problem on trees [Demaine et al. TCS 2015], but the techniques used here are quite different because of the asymmetric nature of the directed problem. We present a characterization of yes-instances based on the existence of a certain set of directed paths, and then derive simple equivalent conditions from it by some observations, which yield an efficient algorithm. For the polytree case, we also present a quadratic-time algorithm that outputs, if the input is a yes-instance, one of the shortest reconfiguration sequences. © 2022 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved.

关键词： Directed graphs

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RerrFact: Reduced Evidence Retrieval Representations for Scientific Claim Verification

RerrFact: Reduced Evidence Retrieval Representations for Sci...

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2022 Workshop on Scientific Document Understanding, SDU 2022

作者： Rana, Ashish Khanna, Deepanshu Ghosal, Tirthankar Singh, Muskaan Singh, Harpreet Rana, Prashant Singh School of Business Informatics and Mathematics University of Mannheim Germany Department of Electronics & Communication Engineering Thapar Institute of Engineering & Technology India Institute of Formal and Applied Linguistics Faculty of Mathematics and Physics Charles University Czech Republic Department of Computer Science & Engineering Thapar Institute of Engineering & Technology India

Exponential growth in digital information outlets and the race to publish has made scientific misinformation more prevalent than ever. However, the task to fact-verify a given scientific claim is not straightforward even for researchers. Scientific claim verification requires in-depth knowledge and great labor from domain experts to substantiate supporting and refuting evidence from credible scientific sources. The SciFact dataset and corresponding task provide a benchmarking leaderboard to the community to develop automatic scientific claim verification systems via extracting and assimilating relevant evidence rationales from source abstracts. In this work, we propose a modular approach that sequentially carries out binary classification for every prediction subtask as in the SciFact leaderboard. Our simple classifier-based approach uses reduced abstract representations to retrieve relevant abstracts. These are further used to train the relevant rationale-selection model. Finally, we carry out two-step stance predictions that first differentiate non-relevant rationales and then identify supporting or refuting rationales for a given claim. Experimentally, our system RerrFact with no fine-tuning, simple design, and a fraction of model parameters fairs competitively on the leaderboard against large-scale, modular, and joint modeling approaches. © 2022 Copyright for this paper by its authors.

关键词： Abstracting

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