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2023 IEEE INFOCOM Conference on Computer Communications Workshops, INFOCOM WKSHPS 2023

作者： Hamdan, Mosab Eldhai, Arwa M. Abdelsalam, Samah Ullah, Kifayat Bashir, Ali Kashif Marsono, M.N. Kon, Fabio Batista, Daniel Macêdo Department of Computer Science Brazil University of Science and Technology Faculty of Engineering Sudan Khartoum University Faculty of Mathematical Sciences and Informatics Sudan Manchester Metropolitan University Department of Computing and Mathematics United Kingdom Universiti Teknologi Malaysia Faculty of Electrical Engineering Malaysia

ISBN: (纸本)9781665494274

The Internet of Things (IoT), like other network infrastructures, requires Intrusion Detection Systems (IDSs) to be protected against attacks. When deploying an IDS in IoT-based smart city environments, the balance between latency and node capacity must be considered, which justifies a distributed IDS with specific classifiers based on the location of the system processing nodes. This paper proposes a two-level classification technique for collaborative anomaly-based IDSs deployed on fog and edge nodes. A Gradient Boosting Classifier (GBC) is used in the lower layer classifier at the edge, while a Convolutional Neural Network (CNN) is used in the upper layer classifier at the fog. Experimentation has demonstrated that the suggested IDS architecture outperforms previous solutions. For instance, in some scenarios, when comparing our proposal with Random Forest, the former obtained an accuracy equal to 99.1%, while the latter obtained 95.3%. Furthermore, our proposal can better select the most important network traffic features, reducing 76% of the data to be analyzed and improving privacy. © 2023 IEEE.

关键词： Internet of things

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Neuro-Fuzzy Employee Ranking System in the Public Sector 8

Neuro-Fuzzy Employee Ranking System in the Public Sector

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8th International Conference on Fuzzy Systems and Data Mining, FSDM 2022

作者： Michalopoulos, Dimitrios Karras, Aristeidis Karras, Christos Sioutas, Spyros Giotopoulos, Konstantinos C. Department of Management Science and Technology University of Patras Patras Greece Department of Computer Engineering and Informatics University of Patras Patras Greece

ISBN: (纸本)9781643683461

One of the biggest problems the public sector faces is the proper utilization of human resources. Within a particular combination of practices, dynamic resource allocation management aims to increase employee productivity. The question that arises is how to match the abilities of employees on a measurable scale through their connection with the logic of neuro-fuzzy systems. Productivity and efficiency are two sides of the same coin and are directly related to the deployment of tasks. In this context, the new era of digital transformation along with the automation of processes allows the direct measurement of the workload status at any time. After the deployment of numerous experiments we verify that skill management is linked to performance measurement. Hard skills are selected since there is no direction of how to quantify soft skills and especially when applied to employees of a public body. ANFIS neuro-fuzzy system was selected since it uses the learning algorithm derived from neural network theory along with human criteria. Therefore the proposed system is based on two distinct factors, Skill management and Neuro-Fuzzy Inference System. The model initialization is system-data driven, which enhances the accuracy compared to traditional HR systems and secures a non-subjective procedure on employee management applied to the public sector. © 2022 The authors and IOS Press.

关键词： Efficiency

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Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains

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Computational and Structural Biotechnology Journal 2024年 23卷 1864-1876页

作者： Do, Duyen Thi Yang, Ming-Ren Vo, Tran Nam Son Le, Nguyen Quoc Khanh Wu, Yu-Wei Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Business Administration College of Management Lunghwa University of Science and Technology Taoyuan City Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan TMU Research Center for Digestive Medicine Taipei Medical University Taipei Taiwan

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR. © 2024 The Authors

关键词： Genes

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An Explainable Artificial Intelligence model in the assessment of Brain MRI Lesions in Multiple Sclerosis using Amplitude Modulation - Frequency Modulation multi-scale feature sets 24

An Explainable Artificial Intelligence model in the assessme...

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24th International Conference on Digital Signal Processing, DSP 2023

作者： Nicolaou, Andria Kakas, Antonis Pattichis, Constantinos S. Pattichis, Marios S. Fotso, Kevin Loizou, Christos P. Pantzaris, Marios Department of Computer Science University of Cyprus Nicosia Cyprus Department of Electrical Engineering and Computer Engineering University of New Mexico United States Department of Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Cyprus Institute of Neurology and Genetics Nicosia Cyprus

ISBN: (纸本)9798350339598

The objective of this study was to implement an explainable artificial intelligence (AI) model with embedded rules to assess Multiple Sclerosis (MS) disease evolution based on brain Magnetic Resonance Imaging (MRI) multi-scale lesion evaluation. Amplitude Modulation-Frequency Modulation (AM-FM) features were extracted from manually segmented brain MS lesions obtained using MRI and were labeled with the Expanded Disability Status Scale (EDSS). Machine learning models were used to classify the MS subjects with a benign course of the disease and subjects with advanced accumulating disability. Rules were extracted from the selected model with high accuracy and then were modified to perform argumentation-based reasoning. It is demonstrated that the proposed explainable AI modeling can distinguish MS subjects and give meaningful information to track the progression of the disease. Future research will examine more subjects and add new feature sets and models. © 2023 IEEE.

关键词： Frequency modulation

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Comparison Between Bi-Directional LSTM And Transfer Learning in Correcting Typing Errors on Twitter Social Media Posts 11

Comparison Between Bi-Directional LSTM And Transfer Learning...

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11th International Conference on Cyber and IT Service Management, CITSM 2023

作者： Lubis, Arif Ridho Prayudani, Santi Hamzah, Muhammad Luthfi Politeknik Negeri Medan Department of Computer Engineering and Informatics Medan Indonesia Universitas Islam Negeri Sultan Syarif Kasim Riau Faculty of Science and Technology Pekanbaru Indonesia

ISBN: (纸本)9798350305968

Typing errors are a behavior that often occurs in communication via short messages or posts on social media platforms. In communicating on social media, many individuals without realizing it often make typing errors that can affect the meaning of sentences. This research will apply a model that can check typing errors using Bi-Directional LSTM and transfer learning which results in the Bi-Directional LSTM model achieving an accuracy of 78% after being trained for 20 epochs with a batch size of 64. On the other hand, the transfer learning model achieves an accuracy of 80% with the same epoch and batch size settings. Furthermore, when the Bi-Directional LSTM model was set with 20 epochs and batch size 64, the accuracy increased to 83%, while the transfer learning model achieved 87% accuracy. Finally, with 20 epochs and a batch size of 64, the Bi-Directional LSTM model achieved 87% accuracy, while the transfer learning model achieved an impressive accuracy of 93%. © 2023 IEEE.

关键词： Social networking (online)

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Development and Evaluation Experiment of a Classroom Support System for Programming Education Using Tangibles Educational Materials 12

Development and Evaluation Experiment of a Classroom Support...

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12th International Conference on Information and Education technology, ICIET 2024

作者： Oda, Koji Kato, Toshiyasu Kambayashi, Yasushi Saitama Prefectural Kawaguchi Technical High School Department Of Information And Telecommunication Kawaguchi Japan Nippon Institute Of Technology Department Of Information And Media Engineering Minamisaitama Japan Sanyo-Onoda City University Department Of Informatics And Data Science Sanyo-Onoda Japan

ISBN: (纸本)9798350371772

In recent years, the utilization of tangible educational materials has attracted attention on educational settings. Because they provide hands-on learning experiences for beginners. This trend is also notable in the field of programming education. Such educational materials are employed in educational institutions worldwide. They liberate programming languages from small computer screen. On the other hand, classroom time is limited. When instructing more than 30 learners, it is hard for the instructor to provide adequate guidance for everyone. Consequently, they have to work extended hours, e.g., after-school hours. To address this problem, we have developed a classroom support system for programming education that complements the use of tangible educational materials. With this system, instructors can monitor the real-time progress of each learner during the class and analyze which parts of the program many learners find challenging. Based on these analytical results, instructors can provide appropriate instructions for individual learners and effectively conduct the class. © 2024 IEEE.

关键词： Learning systems

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Flexible yet impermeable composites with wrinkle structured BNNSs assembling for high-performance thermal management

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npj Flexible Electronics 2024年第1期8卷 568-576页

作者： Guilei Guo Yijie Liu Yafei Ding Wenjie Liu Guimei Zhu Xiaoli Hao Xingyi Huang Jianfei Xia Baowen Li Tong-Yi Zhang Bin Sun College of Electronics and Information Qingdao University266071 QingdaoPR China Department of Polymer Science and Engineering Shanghai Key Laboratory of Electrical Insulation and Thermal AgingShanghai Jiao Tong University200240 ShanghaiPR China School of Electrical Engineering Southwest Jiaotong University611756 ChengduChina Department of Materials Science and Engineering Southern University of Science and Technology518055 ShenzhenPR China School of Microelectronics Southern University of Science and Technology518055 ShenzhenPR China College of Chemistry and Chemical Engineering Shandong Sino-Japanese Center for Collaborative Research of Carbon NanomaterialsInstrumental Analysis Center of Qingdao UniversityQingdao University266071 QingdaoPR China Department of Physics Southern University of Science and Technology518055 ShenzhenPR China Guangzhou Municipal Key Laboratory of Materials Informatics Sustainable Energy and Environment ThrustAdvanced Materials ThrustHong Kong University of Science and Technology(Guangzhou)511400 GuangzhouPR China Weihai Innovation Research Institute of Qingdao University 264200 WeihaiPR China

Efficient thermal management has becomeone of the most critical issues of electronics because of the high heat flux generated from highly integrated,miniaturized,and increased *** we report highly flexible composites with aligned and overlapping interconnected boron nitride nanosheets(BNNSs)assembled in wrinkle *** high in-plane thermal conductivity of more than 26.58Wm^(−1) K^(−1),such structure rendered enhanced through-plane conduction along with increasing *** thermal interface materials(TIMs)of both rigid and flexible devices,the composites revealed an outstanding thermal cooling capability outperforming some commercial *** a record-long bending process of more than 3000 cycles,the maximum temperature fluctuation of the flexible device with 100%-prestrained composite was only within 0.9℃,less than one-third of that with commercial thermal ***,the composite revealed a superior impermeability for flexible *** results illustrate that the composites could be an ideal candidate for the thermal management of emerging flexible electronics.

关键词： composites composite thermal

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DUCK: A Drone-Urban Cyber-Defense Framework Based on Pareto-Optimal Deontic Logic Agents 37

DUCK: A Drone-Urban Cyber-Defense Framework Based on Pareto-...

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37th AAAI Conference on Artificial Intelligence, AAAI 2023

作者： Deb, Tonmoay Dix, Jürgen Jeong, Mingi Molinaro, Cristian Pugliese, Andrea Li, Alberto Quattrini Santos, Eugene Subrahmanian, V.S. Yang, Shanchieh Zhang, Youzhi Department of Computer Science Northwestern University EvanstonIL United States Department of Computer Science Dartmouth College HanoverNH United States Department of Informatics Modeling Electronics and System Engineering University of Calabria Rende Italy Department of Informatics Technical University of Clausthal Clausthal Germany Department of Computer Engineering Rochester Institute of Technology RochesterNY United States CAIR Hong Kong Institute of Science and Innovation Hong Kong

ISBN: (纸本)9781577358800

Drone based terrorist attacks are increasing daily. It is not expected to be long before drones are used to carry out terror attacks in urban areas. We have developed the DUCK multiagent testbed that security agencies can use to simulate drone-based attacks by diverse actors and develop a combination of surveillance camera, drone, and cyber defenses against them. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Terrorism

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Comparison of *** and Spring Boot in Web Development 15

Comparison of *** and Spring Boot in Web Development

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

作者： Novac, Ovidiu Constantin Ghiurau, David Novac, Mihaela Cornelia Gordan, Cornelia Emilia Oproescu, Mihai Bujdoso, Gyongyi Mihalca, Vlad Ovidiu University of Oradea Electrical Engineering and Information Technology Faculty Department of Computers and Information Technology Oradea Romania University of Oradea Management in Information Technology Electrical Engineering and Information Technology Faculty Oradea Romania University of Oradea Electrical Engineering and Information Technology Faculty Department of Electrical Engineering Oradea Romania University of Oradea Electrical Engineering and Information Technology Faculty Department of Electronics and Telecommunications Oradea Romania University of Pitesti Faculty of Electronics Communication and Computer Science Department of Electronics Computers and Electrical Engineering Pitesti Romania University of Debrecen Faculty of Informatics Department of Computer Science and Library and Information Science Debrecen Hungary School of Engineering Sciences University of Oradea Electrical Engineering and Information Technology Faculty Oradea Romania

ISBN: (纸本)9798350321388

In this paper we present two types of server implementation, we will look at the advantages and disadvantages of each technology. *** server application, built with ***, a single threaded server which will treat the requests in an asynchronous manner, with a non-blocking principle, whilst Spring Boot is a more robust and more common approach of a server technology with the benefits of having a strongly typed architecture and multiple threads available. These types of application will behave the same, making almost impossible to tell the difference between a *** and a Spring Boot web server. © 2023 IEEE.

关键词： Node.Js non-blocking single-multi threaded Spring Boot web server

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Enhanced Magnetic Interaction between Ga and Fe in Two-Dimensional van der Waals Ferromagnetic Crystal Fe_(3)GaTe_(2)

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Chinese Physics Letters 2023年第8期40卷 108-112页

作者：查鹤鸣李炜张高节刘文晶邓力玮姜琦叶茂武浩常海欣乔山 State Key Laboratory of Functional Materials for Informatics Center for Excellence in Superconducting ElectronicsShanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Department of Physics and State Key Laboratory of Surfac Physics Fudan UniversityShanghai 200433China State Key Laboratory of Material Processing and Die&Mold Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China Wuhan National High Magnetic Field Center and Institute for Quantum Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China Center for Transformative Science ShanghaiTech UniversityShanghai 201210China Shanghai Synchrotron Radiation Facility Shanghai Advanced Research InstituteChinese Academy of SciencesShanghai 201210China Shenzhen R&D Center of Huazhong University of Science and Technology Shenzhen 518000China School of Physical Science and Technology ShanghaiTech UniversityShanghai 201210China

Fe_(3)GaTe_(2),a recently discovered van der Waals ferromagnetic crystal with the highest Curie temperature and strong perpendicular magnetic anisotropy among two-dimensional(2D)magnetic materials,has attracted significant attention and makes it a promising candidate for next-generation spintronic *** with Fe_(3)GeTe_(2),which has the similar crystal structure,the mechanism of the enhanced ferromagnetic properties in Fe_(3)GaTe_(2)is still unclear and needs to be ***,by using x-ray magnetic circular dichroism measurements,we find that both Ga and Te atoms contribute to the total magnetic moment of the system with antiferromagnetic coupling to Fe *** first-principles calculations reveal that Fe_(3)GaTe_(2)has van Hove singularities at the Fermi level in nonmagnetic state,resulting in the magnetic instability of the system and susceptibility to magnetic phase *** addition,the calculation results about the density of states in ferromagnetic states of two materials suggest that the exchange interaction between Fe atoms is strengthened by replacing Ge atoms with Ga *** findings indicate the increase of both the itinerate and local moments in Fe_(3)GaTe_(2)in view of Stoner and exchange interaction models,which results in the enhancement of the overall magnetism and a higher Curie *** work provides insight into the underlying mechanism of Fe_(3)GaTe_(2)’s remarkable magnetic properties and has important implications for searching 2D materials with expected magnetic properties in the future.

关键词： magnetic ferromagnetic mechanism

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