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18th International Conference on Ubiquitous Information Management and Communication, IMCOM 2024

作者： Omer, Muhammad Ali, Sardar Jaffar Raza, Syed Muhammad Le, Duc-Tai Choo, Hyunseung College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Sungkyunkwan University Dept. of Computer Science and Engineering Suwon Korea Republic of Sungkyunkwan University Dept. of AI System Engineering Suwon Korea Republic of Sungkyunkwan University Dept. of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798350331011

With Industry 4.0's technological advancements, the convenience and affordability of Artificial Intelligence (AI) and IoT have increased. However, customers still face long waiting times in payment queues during the smart shopping experience. Current solutions rely on expensive sensor-based RFIDs or simple barcodes, making them impractical and limited in scalability. This paper proposes an economically smart solution with two cameras on NVIDIA JETSON NANO for realtime object monitoring and automated shopping. Communication between modules is facilitated by TCP/IP and HTTP protocols. By utilizing the YOLO v7, real-time monitoring is achieved. This innovative approach revolutionizes the customer experience by providing a seamless interface and time-saving features. Additionally, it offers potential integration with e-commerce businesses and payment gateways, further enhancing the overall customer and vendor experience. © 2024 IEEE.

关键词： Graphical user interfaces

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Traffic Classification For Botnet Detection Using Deep Learning 3

Traffic Classification For Botnet Detection Using Deep Learn...

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3rd International Conference on Smart Cities, Automation and Intelligent Computing Systems, ICON-SONICS 2023

作者： Hossen, Md. Sagar Ahmad, Tohari Institut Teknologi Sepuluh Nopember Department of Informatics Surabaya Indonesia Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781509062805

In this modern world, we are naturally dependent on technology, which is constantly evolving. At the same time, our fear of data fraud is increasing every day. The ever-increasing number of attacks on our servers indicates that people have learned to adapt to new technologies. In addition, the number of botnet attacks is not insignificant, and botnets threaten computer networks. This can impact security systems, including malware distribution, phishing, spamming, and click fraud. Due to their harmful effects, botnets must be identified as soon as possible. Due to the dynamic character of botnets, however, detection has proven difficult. In this proposed method, deep learning is used to analyze and predict botnet data, and model performance metrics such as accuracy, precision, Recall, and F1 score are compared to prior work. In the proposed procedure, patterns are also discussed by analyzing botnet data. Various scenarios and sensors separate the NCC and NCC-2 datasets. The NCC dataset is separated into 13 scenarios, while the NCC-2 dataset is separated into 3 sensors. The dataset is preprocessed using the clean method, the null value handling method, the imbalance method, and the feature selection method to extract the essential characteristics. The dataset is then trained using LSTM, GRU, and Bi-LSTM models, and 99.93% accuracy is achieved. © 2023 IEEE.

关键词： Long short-term memory

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Improved Bare Bones Particle Swarm Optimization based on Cauchy Distribution and its Application in Spectral Reconstruction 8

Improved Bare Bones Particle Swarm Optimization based on Cau...

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8th International Conference on Computational Intelligence and Applications, ICCIA 2023

作者： Zhang, Xinmeng Cui, Guihua Ruan, Xiukai Chen, Qifan Cui, Di Gao, Xiaohong Yao, Yuan Wenzhou University College of Electrical and Electronic Engineering Wenzhou China Middlesex University London Computer Science and Informatics London United Kingdom

ISBN: (纸本)9798350339741

In view of the shortcomings that particle swarm optimization is easy to fall into local optima and difficult to solve complex problems, the combination of Gaussian distribution and Cauchy distribution was used in the position updating formula to improve the particle diversity, and Cauchy perturbation was added to the swarm optimal position to further improve its global searching ability. In the experiment, ten benchmark test functions were used to test two proposed modifications in the study, and compared with the four classical particle swarm algorithms, the results show that the proposed algorithm had high solving accuracy and good solving stability, especially in solving complex functions. The proposed algorithm was utilized in spectral reconstruction based on wideband multi-illuminant imaging. The experimental results confirm that comparing with the classical PSO algorithm, the proposed algorithm is good at searching for global optimum especially for complicated engineering problems. © 2023 IEEE.

关键词： Particle swarm optimization (PSO)

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Velocity-aided Channel Estimation for Spatially Selective mmWave Massive MIMO Communications 31

Velocity-aided Channel Estimation for Spatially Selective mm...

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31st European Signal Processing Conference, EUSIPCO 2023

作者： Vlachos, Evangelos Mavrokefalidis, Christos Berberidis, Kostas Industrial Systems Institute ATHENA Research Center Patras Greece Dept. of Computer Engineering and Informatics University of Patras Patras Greece

ISBN: (纸本)9789464593600

This paper focuses on addressing the challenge of estimating multiple-input multiple-output (MIMO) channels for wireless communication between a ground base-station and a moving vehicle. One recently recognised model for time-varying channels incorporates spatial selectivity, which is referred to as beam squint, and is particularly relevant in the millimeter-wave (mmWave) range. In such scenarios, it is essential to account for the beam squint when attempting to recover channel parameters using a training sequence. However, the use of a training sequence alone may be insufficient for this purpose. To overcome this issue, in this work, we propose a channel estimation approach that exploits information provided by the control module of the vehicle, namely its velocity. The estimation problem that is designed, regards the channel both in a parametric and a non-parametric form and the alternating direction method of multipliers is utilised to efficiently solve it. It is demonstrated via simulations that considerable gains can be achieved if information from the control unit of the vehicle can be appropriately introduced and exploited. © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Opinions Are Not Always Positive: Debiasing Opinion Summarization With Model-Specific and Model-Agnostic Methods 30

Opinions Are Not Always Positive: Debiasing Opinion Summariz...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Zhang, Yanyue Lai, Yilong Wang, Zhenglin Li, Pengfei Zhou, Deyu He, Yulan School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China Department of Informatics King's College London United Kingdom The Alan Turing Institute United Kingdom

ISBN: (纸本)9782493814104

As in the existing opinion summary data set, more than 70% are positive texts, the current opinion summarization approaches are reluctant to generate the negative opinion summary given the input of negative opinions. To address such sentiment bias, two approaches are proposed through two perspectives: model-specific and model-agnostic. For the model-specific approach, a variational autoencoder is proposed to disentangle the input representation into sentiment-relevant and sentiment-irrelevant components through adversarial loss. Therefore, the sentiment information in the input is kept and employed for the following decoding which avoids interference of content information with emotional signals. To further avoid relying on some specific opinion summarization frameworks, a model-agnostic approach based on counterfactual data augmentation is proposed. A dataset with a more balanced emotional polarity distribution is constructed using a large pre-trained language model based on some pairwise and mini-edited principles. Experimental results show that the sentiment consistency of the generated summaries is significantly improved using the proposed approaches, while their semantics quality is unaffected. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Semantics

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Moodle-based Learning Management System Design as a Learning Media at SMKN 40 Jakarta 7

Moodle-based Learning Management System Design as a Learning...

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7th International Conference on New Media Studies, CONMEDIA 2023

作者： Setya, Oktaviano Nanda Prima Widodo Nugraheni, Murien State Jakarta University Informatics and Computer Engineering Education Jakarta Indonesia State Jakarta University Information System and Technology Jakarta Indonesia

ISBN: (纸本)9798350307504

Indonesia is currently in the final stages of the COVID-19 pandemic, which has changed the world of the online learning. Online learning has many benefits, one of which students can learn anywhere and anytime. SMK Negeri 40 Jakarta is one of the vocational high schools located in DKI Jakarta. Based on observation at SMKN 40 Jakarta, teachers use a learning management system for daily learning. Therefore, a Moodle-based learning management system is needed. Learning Management System is a web application to manage various learning activities automatically, which is built using Moodle platform with RAD (Rapid Application Development) methodology. The result is a Moodle-based learning management system application that can be useful in supporting the teaching and learning process at school. Based on the results of black box testing and user acceptance testing, the learning management system created is very good, therefore it can be concluded this application can be accepted and implemented at SMK Negeri 40 Jakarta. © 2023 IEEE.

关键词： Black-box testing

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ZKP Protocols for Usowan,Herugolf,and Five Cells

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Tsinghua Science and Technology 2024年第6期29卷 1651-1666页

作者： Daiki Miyahara Léo Robert Pascal Lafourcade Takaaki Mizuki Graduate School of Informatics and Engineering The University of Electro-CommunicationsTokyo 1828585Japan MIS Lab University of Picardy Jules VerneAmiens 80000France Laboratory of Computer Science Modelling and Systems OptimisationUniversity of Clermont AuvergneClermont-Ferrand 63178France Cyberscience Center Tohoku UniversitySendai 9808578Japan

A Zero-Knowledge Proof (ZKP) protocol allows a participant to prove the knowledge of some secret without revealing any information about it. While such protocols are typically executed by computers, there exists a line of research proposing physical instances of ZKP protocols. Up to now, many card-based ZKP protocols for pen-and-pencil puzzles, like Sudoku, have been designed. Those games, mostly edited by Nikoli, have simple rules, yet designing them in card-based ZKP protocols is non-trivial. In this work, we propose a card-based ZKP protocol for Usowan, a Nikoli game. In Usowan, for each room of a puzzle instance, there is exactly one piece of false information. The goal of the game is to detect this wrong data amongst the correct data and also to satisfy the other rules. Designing a card-based ZKP protocol to deal with the property of detecting a liar has never been done. In some sense, we propose a physical ZKP for hiding of a liar. This work extends a previous paper appearing in Ref. [1]. In this extension, we propose two other protocols, for Herugolf and Five Cells. The puzzles are specifically chosen because each of those three puzzles shares a common constraint, connectivity. However, showing the connected configuration cannot be done with generic approach and brings new construction to the existing connectivity ZKP protocol. Indeed, in Herugolf, the connectivity is handled with a given length of cell which is decremental (i.e., the length of each connected cell decreases by one at each step). For Five Cells, there is an additional step in the setup allowing to encode all the information needed to ensure a valid ZKP protocol.

关键词： Zero-Knowledge Proof(ZKP)protocol playing cards card-based cryptography physical assumptions Usowan Herugolf FiveCells

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To Risk Analyse, or Not to Risk Analyse: That’s the Question 18th

To Risk Analyse, or Not to Risk Analyse: That’s the Ques...

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18th IFIP WG 11.12 International Symposium on Human Aspects of Information Security and Assurance, HAISA 2024

作者： Bergström, Erik Andersson, Simon Lundgren, Martin School of Engineering Jönköping University Jönköping Sweden Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden School of Informatics University of Skövde Skövde Sweden

ISBN: (纸本)9783031725586

Risk analysis is a key activity for organisations that are looking to protect their valuable information assets against threats, such as malicious actors. It is one of the essential parts of risk management and is used to justify and prioritise what assets require the attention of which potential security controls. Risk management, and more specifically, risk analysis, is an activity that should be performed continuously. However, recent studies indicate that this is not always the case. As such, this paper investigates risk analysis as it is performed in practice in different Swedish public sector organisations. The results are based on semi-structured interviews with 17 senior security experts, an analysis of standards, and a national method support aiming to fill the gap between standard and practice. The results are presented in three themes: how, when and why risk analysis is performed. Of note, we identify that there is an issue of overlooking specific assets or systems when establishing an organisational-wide risk profile and a general recognition of the necessity for risk analysis, albeit not always in alignment with a classic risk analysis. © IFIP International Federation for Information Processing 2025.

关键词： Cybersecurity Information security Risk analysis

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MMDDI-MGPFF: Multi-Modal Drug Representation Learning with Molecular Graph and Pharmacological Feature Fusion for Drug-Drug Interaction Event Prediction

MMDDI-MGPFF: Multi-Modal Drug Representation Learning with M...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Wang, Guishen Guo, Zhitong You, Guilin Xu, Ming Cao, Chen Hu, Xiaowen School of Life Sciences Jilin University Changchun China College of Computer Science and Engineering Changchun University of Technology Changchun China Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing China School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing China

ISBN: (纸本)9798350386226

Drug-drug interactions pose a significant challenge in healthcare, directly impacting patient safety and treatment efficacy. Although recent advances in computational methods have improved drug-drug interaction (DDI) event prediction, many existing models face difficulties in effectively fusing features across different DDI tasks. To address these limitations, we introduce MMDDI-MGPFF, a novel multi-modal drug representation learning framework that integrates molecular graphs and pharmacological feature fusion to improve DDI prediction. Our model leverages a graph isomorphism network (GIN) for efficient encoding of molecular structures, coupled with an autoencoder for learning sequence-based drug features, encompassing both biological and pharmacological characteristics. We propose a multi-modal fusion approach that employs multi-head attention and deep neural networks to seamlessly integrate these graph and sequence modalities. Comprehensive experiments on a benchmark dataset demonstrate that MMDDI-MGPFF significantly outperforms state-of-the-art methods in DDI prediction tasks. Ablation studies further corroborate the efficacy of our model's components, particularly the GIN and the integration of multi-feature drug representations. This work advances the field of DDI prediction by providing a more holistic and accurate approach to drug representation and interaction modeling. © 2024 IEEE.

关键词： Deep neural networks

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Risk Assessment of Linkedin Profiles 8

Risk Assessment of Linkedin Profiles

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8th International Conference on computer Science and engineering, UBMK 2023

作者： Aydin, Arzum Bahtiyar, Serif Istanbul Technical University Cyber Security and Privacy Research Lab SPFLab. Faculty of Computer and Informatics Engineering Maslak Istanbul Turkey

ISBN: (纸本)9798350340815

Fake or fraudulent accounts are a significant problem in social networking that is often addressed by the users of various social networking platforms involving Linkedin. Fraudulent accounts generally try to convince people about their identity that they are authentic. Adversaries use fake profiles or they impersonate a real identity on social networks to obtain more privileges. Therefore, it is critical to understand problems regarding fraudulent profiles. In this paper, we propose new sustainable framework to assess risks about profiles in social networking platforms. The framework is implemented as a web extension and it is analyzed with ITU alumni profiles in Linkedin. The analyses results show that there are different profiles within one community in Linkedin that may be significant threat for social network users. © 2023 IEEE.

关键词： Risk assessment

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