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An Efficient Impersonation Attack Detection Method in Fog Computing

computers, Materials & Continua 2021年第7期68卷 267-281页

作者： Jialin Wan Muhammad Waqas Shanshan Tu Syed Mudassir Hussain Ahsan Shah Sadaqat Ur Rehman Muhammad Hanif Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information TechnologyBeijing University of TechnologyBeijing100124China Faculty of Computer Science and Engineering Ghulam Ishaq Khan Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Electronics Engineering FICTBalochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Department of Computer Science Namal InstituteMianwali42200Pakistan

Fog computing paradigm extends computing,communication,storage,and network resources to the network’s *** the fog layer is located between cloud and end-users,it can provide more convenience and timely services to ***,in fog computing(FC),attackers can behave as real fog nodes or end-users to provide malicious services in the *** attacker acts as an impersonator to impersonate other legitimate ***,in this work,we present a detection technique to secure the FC ***,we model a physical layer key generation based on wireless channel *** generate the secret keys between the legitimate users and avoid impersonators,we then consider a Double Sarsa technique to identify the impersonators at the receiver *** compare our proposed Double Sarsa technique with the other two methods to validate our work,i.e.,Sarsa and *** simulation results demonstrate that the method based on Double Sarsa outperforms Sarsa and Q-learning approaches in terms of false alarm rate(FAR),miss detection rate(MDR),and average error rate(AER).

关键词： Fog computing double Sarsa attack detection physical layer key security

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Study on material removal mechanism for Cu-CMP on a patterned silicon wafer 10

Study on material removal mechanism for Cu-CMP on a patterne...

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10th International Conference on Leading Edge Manufacturing Technologies in 21st Century, LEM 2021

作者： Bakier, Mohammed A.Y.A. Matsumoto, Ryuunosuke Fuchiwaki, Masaki Khajornrungruang, Panart Suzuki, Keisuke Department of Mechanical Information Science and Technology Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology 820-8502 Japan Department of Mathematics Faculty of Science Assiut University Egypt

Pattern effect as dishing and erosion on Cu-CMP process become a serious problem to fabricate multilevel interconnect in advanced ULSI devices. In the current study, planarization models using patterned wafer and ANSYS software are suggested to make precise predictions of the post-CMP surface height to support optimize the layout design. The slurry flow effect on the copper body has been investigated and the removed mass character is monitored through the stress distribution at the solid domain. By determination of the removal regions by the calculation, we can avoid the dishing and erosion areas in the patterned area from the post-CMP process. © 2021 The Japan Society of Mechanical Engineers.

关键词： Silicon wafers

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Domain Adaptation in Color-Shifted Datasets Through Adversarial Learning Balancing

Domain Adaptation in Color-Shifted Datasets Through Adversar...

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International Conference on Artificial Intelligence and Data sciences (AiDAS)

作者： Hidayaturrahman Agung Trisetyarso Iman Herwidiana Kartowisastro Widodo Budiharto Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusatara University Jakarta Indonesia Mathematics Department School of Computer Science Bina Nusatara University Jakarta Indonesia Computer Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

Due to the disparity in the levels of difficulty presented by the several tasks, doing domain adaptation in an adversarial way may result in an imbalanced learning process. In the MNIST dataset, this phenomenon also manifests itself in the form of domain adaptation for color-shifted distribution. In this particular situation, the domain classifier has a higher tendency to fit more quickly, but the category classifier fits quite poorly in the learning process. In order to address this problem, a new hyper-parameter has been added to the loss function in order to strike a compromise between the learning speed of the domain and the categorical classifier. By using this technique, the categorical classifier may better match the data while still maintaining the same level of performance as the domain classifier. In order to determine whether or not making use of this hyper-parameter is useful, the phenomena in question is examined using three distinct color-shifted settings. Following the evaluations, it was discovered that the newly introduced hyper-parameter is capable of coping with imbalanced learning while simultaneously engaging in domain adaptation.

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Analysis of the Expected Possession Value in RoboCupSoccer Simulation 2D

Analysis of the Expected Possession Value in RoboCupSoccer S...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Masaki Ban Takumi Amano Keisuke Ando Takeshi Uchitane Kazunori Iwata Nobuhiro Ito Graduate School of Business Administration and Computer Science Aichi Institute of Technology Toyota Japan Faculty of Information Science Aichi Institute of Technology Toyota Japan Faculty of Business Administration Aichi University Nagoya Japan

RoboCupSoccer Simulation 2D(RSS2D) simulates a soccer match between two teams of 11 autonomous mobile robots each on a virtual two-dimensional plane. In soccer, the ball and players are always on the move, leading to a constantly changing game situation. RSS2D agents thus need to constantly analyze the match situation and predict the actions of enemy agents in determining their actions. However, it is not easy to analyze a player’s actions, because it is necessary to combine specialized knowledge with consideration of the intentions of all players’ actions. In human soccer, an analysis method using the expected possession value (EPV) has been proposed to solve this problem. The EPV is a measure of the probability that a team will score or concede a goal according to the game conditions and player actions. In this study, we apply the EPV to RSS2D to analyze match situations and agent actions. We also examine whether EPV-based analysis is effective in an RSS2D environment. We create a dataset by extracting agent actions and ball position information from RSS2D log files. Next, using the dataset as input, we train several estimation models using a convolutional neural network. Then, by combining the multiple estimation models, we create an estimation model for the EPV of passing. The effectiveness of the estimation model for the EPV of passing is confirmed by analyzing game conditions and agent actions.

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Research and Application of Machine Learning in Automatic program Generation

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Chinese Journal of Electronics 2020年第6期29卷 1001-1015页

作者： ZHANG Xiaojiang JIANG Ying Yunnan Key Laboratory of Computer Technology Application Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming University of Science and Technology

With the development of artificial intelligence,machine learning has been applied in more and more *** order to improve the quality and efficiency of software,automatic program generation is becoming a research *** recent years,machine learning has also been gradually applied in automatic program *** trees,language models,and cyclic neural networks have been applied in code generation,code completion and code knowledge *** efficiency of software development has been improved to a certain extent using machine *** at the automatic program generation,this paper analyzes and summarizes the models of machine learning,the modifications involved in the models and the application *** research direction is discussed from the aspects of programmer behavior and automatic program generation of machine learning.

关键词： code generation Combinatorial mathematics neural nets decision trees machine learning code completion automatic programming language models Data handling techniques data mining cyclic neural networks programming support software engineering automatic program generation Software engineering techniques programmer behavior code knowledge mining Neural computing techniques learning (artificial intelligence) Knowledge engineering techniques

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Identifying english proficiency by frontal theta activity during english learning

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Discover Education 2025年第1期4卷 1-7页

作者： Emsawas, Taweesak Kimura, Tsukasa Ogura, Shintaro Morita, Hironori Abdullajon, Ergashov Grundlehner, Bernard Ogura, Mototsugu Numao, Masayuki Graduate School of Information Science and Technology Osaka University Osaka Japan SANKEN (The Institute of Scientific and Industrial Research) Osaka University Osaka Japan Graduate School of Human Sciences Osaka University Osaka Japan Shinhodo Inc Tokyo Japan imec the Netherlands/Holst Centre Eindhoven Netherlands Faculty of Engineering Department of Information and Computer Science Kyoto Tachibana University Kyoto Japan

Second-language (L2) knowledge of English is an essential communication tool in the contemporary era of globalization in many research and business fields. Among the important tasks in English education is the measurement of student proficiency. While various tests purport to measure proficiency in learning English, repeated preparation and implementation of tests remain major costs in providing English education. We propose that measurement with an electroencephalogram (EEG) might be used for measuring proficiency in L2 learning of English without the repeated preparation and implementation of English tests. In this study, we proposed the use of an EEG as an index of the frontal theta band activity involved in concentration with the use of English materials without the need for the repeated preparation and implementation of English tests. Our experiments recorded the EEG signals of 52 participants, divided into two groups of those with beginner and advanced knowledge of English. All participants were asked to attend three sessions: before, during, and after the English lesson and the frontal theta band activities were analyzed as index of concentration for these lessons. The results showed that the frontal theta band activity for advanced students during the English lesson was larger than that for beginner students. Frontal brain activity reflects a common computation recognizing the need for cognitive control, such as concentration on L2 learning. Without dependence on existing tests, this study proposes a method to measure L2 proficiency more quickly than the methods used in previous neuroscience studies. © The Author(s) 2025.

关键词： Concentration Electroencephalogram (EEG) Second-language acquisition Second-language education Time-frequency analysis

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Multi-Satellite Beam Hopping and Frequency Allocation for Satellite-Terrestrial Communications

Multi-Satellite Beam Hopping and Frequency Allocation for Sa...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Wang, Guanhua Yang, Fang Song, Jian Han, Zhu Tsinghua University Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Beijing100084 China Tsinghua University Shenzhen International Graduate School Shenzhen518055 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States

ISBN: (纸本)9798350351255

In this paper, a multi-satellite cooperation architecture for satellite-terrestrial communications is studied with the dense constellation of low Earth orbit (LEO) satellites. Moreover, beam hopping (BH) and frequency allocation enable a flexible solution for the non-uniform geographical distribution of communications, which are optimized to improve the performance and avoid interference in satellite-terrestrial communications. The total problem for maximizing the networking throughput and ensuring the delay fairness is decomposed into two sub-problems, in which the deep reinforcement learning is utilized to determine the BH pattern, and the frequency allocation among beams is implemented by the majorization-minimization algorithm. Simulation results demonstrate that the proposed method obtains a 13.0% improvement in throughput compared with the original benchmark, while the delay fairness can be ensured by the iterative solution of the two sub-problems. © 2024 IEEE.

关键词： Orbits

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Design of Task Assignments based on Ordering and Time Window Constraints for RoboCupRescue Agents

Design of Task Assignments based on Ordering and Time Window...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Itsuki Matsunaga Haruki Uehara Ryoya Maeda Joe Fujisawa Hiroya Suzuki Keisuke Ando Takeshi Uchitane Kazunori Iwata Nobuhiro Ito Graduate School of Business Administration and Computer Science Aichi Institute of Technology Toyota Japan Faculty of Information Science Aichi Institute of Technology Toyota Japan Faculty of Business Administration Aichi University Nagoya Japan

The RoboCupRescue Simulation (RRS) is a project that uses multi-agent systems to address real-world problems. RRS needs to perform an optimal task assignment for various disaster relief teams (agents) to minimize the damage caused by disasters. In previous studies, the RRS task assignment problem was modeled as a distributed constraint optimization problem (DCOP) and its effectiveness was confirmed. The DCOP can handle cooperative actions by one type of agent, but it cannot handle cooperative actions by multiple types of agents. To achieve this cooperative behavior, task assignment must take into account the order constraints of multiple types of tasks. It is also difficult for the DCOP to consider the dynamic environment. RRS should consider the dynamic environment because disaster conditions change over time. To consider the dynamic environment, task assignment must take into account the time window constraints of the task. Therefore, the objective of this study is to realize a disaster relief agent that performs task assignment considering the task order and time window constraints for RRS. First, the task assignment problem of RRS was modeled as a layered DCOP (L-DCOP) and L-DCOP was applied to RRS. Next, the rescue abilities and behavior of the L-DCOP agent applying the L-DCOP were compared with those of the DCOP agent applying the DCOP. The results confirmed the effectiveness of the L-DCOP agent and its ability to perform given the constraints of the task.

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Movement Impacts on Eyeblink Detection Using FMCW Radar

Movement Impacts on Eyeblink Detection Using FMCW Radar

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Smart World Congress (SWC), IEEE

作者： Xinze Zhang Walid Brahim Jianhua Ma Bernady O. Apduhan Graduate School of Computer and Information Sciences Hosei University Tokyo Japan Department of Information Science Faculty of Science and Engineering Kyushu Sangyo University Fukuoka Japan

Eyeblink detection is essential for assessing physiological and psychological states in various applications. Radar technology offers a promising solution for non-intrusive and reliable eyeblink detection. This ongoing work investigates the effects of movements on eyeblink detectability using FMCW radar. The proposed methodology relies on the use of Adaptive Variational Mode Decomposition algorithm (AVMD) for blink signal extraction. Extensive experiments were performed to assess the performance under challenging conditions, analyzing the influence of body, head, and mouth movements on blink detectability. An in-depth analysis of movement impacts, identification of underlying reasons, and potential mitigation strategies is presented. This research provides a comprehensive evaluation, useful for the next step of research to provide a more reliable radar-based blink detection solution.

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An Exploratory Computational Approach for Elucidating a Nonstructural Protein Interaction in Dengue Virus 2

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Procedia computer science 2024年 245卷 470-479页

作者： Alam Ahmad Hidayat Rudi Nirwantono Bens Pardamean Mathematics Department School of Computer Science Bina Nusantara University Indonesia 11480 Biotechnology Department Faculty of Engineering Bina Nusantara University Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia 11480

As the dengue infection still impacts hundreds of millions of people globally, unprecedented efforts in dengue drug development have been more progressive in recent decades. Computational methods provide a fast, sustainable, and efficient screening of active compounds and newly created drug molecules, including those specifically targeting nonstructural proteins (NS) of dengue viruses. In this work, protein modeling for the NS proteins of DENV-2/16681 strain was performed using a template-based homology modeling for the NS3 protein and an Artificial Intelligence (AI)-based prediction via AlphaFold for the NS4B protein. Moreover, the protein-protein interaction between the two structures was predicted using the HADDOCK server, which employs information about active and passive residues of the interaction interface to guide the docking process. After the modeling and its respective refinement process, the predicted structures of NS3 and NS4B improved their steric clashing scoring from MolProbity assessment. The refined models were then docked, and the resulting docking pose was analyzed to extract the interacting residues based on the polar contacts within the interface of the two proteins. Our result presents a preliminary study to create a dataset related to in silico molecular interactions of the NS3-NS4B interaction of different DENV types. It is helpful for building a computational pipeline for elucidating protein-ligand problems in dengue drug screenings.

关键词： bioinformatics computational biology dengue protein docking structural biology

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