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26th International Conference on computer and Information Technology, ICCIT 2023

作者： Jony, Asaduzzaman Islam, Muhammad Nazrul Sarker, Iqbal H. Dept. of Computer Science and Engineering Dhaka Bangladesh Dept. of Computer Science and Engineering Dhaka Bangladesh Edith Cowan University PerthWA-6027 Australia

ISBN: (纸本)9798350359015

Nowadays DNS spoofing has become one of the terrible attacks which is triggered by exploiting IP address conflict detection vulnerability on the DHCP server side. DHCP server running on latest operating systems can detect IP address conflict which makes proposed attack ineffective. On the other hand, DNS spoofing attack using server side DNS cache poisoning is very difficult and unfeasible task as the public DNS servers are very secured and deployed behind several security appliances. Again, DNS spoofing attack is initiated by poisoning the client's DNS cache, which is uncertain as it requires a malware to be installed in target user's computer. Therefore, the objective of this study is to introduce an innovative approach for ethically launching a DNS spoofing attack within a Local Area Network (LAN) for illustrating the vulnerabilities and security flaws of the DNS protocol. To achieve this objective, attacker introduces a rogue DHCP server in the LAN and forcefully redirects user's traffic to a malicious or rogue default gateway. Secondly, a python (scapy) based DNS spoofing engine is deployed in the rogue DHCP server that tampers the DNS responses replied by the DNS server. The scapy alters the IP address of legitimate website with an IP address of malicious or phishing website which is managed by the attacker and looks like legitimate website. As a result, compromised user is redirected to that identical looking phishing website and becomes victim of phishing attack. Finally, the effectiveness and validation of the proposed attack were demonstrated using the Kali Linux and multi-vendor network emulation software (EVE-NG). © 2023 IEEE.

关键词： DNS Spoofing Ethical Considerations LAN security Phishing Python Scapy Rogue DHCP Wireshark

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STUDY ON A SIMPLIFIED MODEL OF A HIGH-RISE SHEAR-TYPE BUILDING FOR EVALUATION OF Q–Δ RESONANCE

Journal of Structural and Construction Engineering

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Journal of Structural and Construction engineering 2023年第803期88卷 59-70页

作者： Anamizu, Ryosuke Kohiyama, Masayuki School of Science for Open and Environmental Systems Graduate School of Science and Technology Keio University Japan Dept. of System Design Engineering Faculty of Science and Technology Keio University Japan

To evaluate Q–Δ resonance, which is a torsional resonance phenomenon caused by geometric non-linearity, we proposed a simplified model for an n-story non-eccentric building model with a shear-type structure. We designed and fabricated a four-story small-scale specimen assuming a non-eccentric steel structure with a height of 324 m, and conducted shaking table tests. As a result, the occurrence of Q–Δ resonance was confirmed as predicted by the simplified model. In addition, the simplified model reproduced the resonance amplitude in a finite element model of the specimen with the out-of-plane rotation of slabs constrained and its validity was confirmed. © 2023 Authors. All rights reserved.

关键词： Tall buildings

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The Effects of Selected Preferred Music on Perceived Emotions through Audiovisual Stimuli 9

The Effects of Selected Preferred Music on Perceived Emotion...

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9th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data science, BCD 2024

作者： Thaiwong, Thunrada Fukumoto, Makoto Graduate School of Computer Science and Engineering Fukuoka Institute of Technology Fukuoka Japan Fukuoka Institute of Technology Dept. of Computer Science and Engineering Fukuoka Japan

ISBN: (纸本)9798350394191

Music surrounds us, and there is no denying that music in visual media can shape and evoke emotions. Yet, understanding how musical preference influences emotions through audio and visual stimuli remains an important task. To address this task, we investigated the role of musical preference effect on perceived emotions induced through music and visual stimuli (i.e., animation), using a 7-point scale for valence-arousal ratings and physiological responses in electroencephalogram (EEG) band power. The perceived emotions are categorized into four states: happiness, calmness, fear, and sadness. One emotional state contains 4 sessions: (1) Preferred Music, (2) Unfamiliar Music, (3) Preferred Music+Animation, and (4) Unfamiliar Music+ Animation. Behavior-wise, the rating results showed that the presence of preferred music resulted in higher perceived valence ratings, particularly in happiness. However, no stimulus had a significant effect on perceived arousal ratings and satisfaction ratings. Physiologically, the EEG indexes showed that the presence of preferred music appears to affect an increase in alpha power across various emotions except sadness, whereas unfamiliar music seems to affect beta power, particularly in happiness and calmness. Overall, these findings supported that musical preference is an affective factor reflecting the levels of valence and alpha power in EEG. Nevertheless, our findings did not confirm a significant difference between only preferred music and combining it with animation. Interestingly, we also found that participants were more likely to be attracted to and perceive positive (i.e., happiness and calmness) emotions easily through preferred music and/or visual stimuli than negative (i.e., fear) emotions. © 2024 IEEE.

关键词： Animation

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Automated Attendance Management system 5

Automated Attendance Management System

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5th IEEE International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2023

作者： Goyal, Pranshu Nigam, Vishwas Khan, Shahnaw A.J. Singh, Shashi Kant Galgotias College Of Engineering And Technology Dept. Of Computer Science And Engineering India

ISBN: (纸本)9798350330861

the manual process of recording and managing attendance in educational institutions and organizations is often time-consuming, prone to errors, and inefficient. To address these challenges, there is a growing need for automated attendance management systems. This research paper presents the design and implementation of an Automated Attendance Management system (AAMS) using modern technologies. The AAMS utilizes various technologies such as biometric recognition, RFID (Radio Frequency Identification), and computer vision to accurately and efficiently track attendance. The system aims to simplify the attendance recording process for both students and instructors, reduce administrative burden, and improve overall efficiency. The proposed AAMS incorporates biometric recognition techniques, such as fingerprint scanning or facial recognition, to identify and verify the identity of individuals. © 2023 IEEE.

关键词： Efficiency

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Cross-Domain Adaptation Through Adversarial Teaching for Unmanned Ariel Vehicles in Smart Cities 22

Cross-Domain Adaptation Through Adversarial Teaching for Unm...

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22nd International Learning and Technology Conference, L and T 2025

作者： Mazhar Ul Haq, Qazi Yao, Leethar Lin, Bo-Yu Yuan Ze University Dept. of IBPI and Computer Science and Engineering Zhongli Taiwan National Taipei University of Technology Dept. of Electrical Engineering Taipei Taiwan

ISBN: (纸本)9798331532215

Person re-identification has been an important issue of surveillance systems in smart cities. However, this requires huge datasets to supervise deep learning models for accurately identifying and tracking people in smart cities. In this paper, we propose adversarial learning in integration with a mutual mean teaching model known as adversarial teaching to take the issue of domain adaptation. Initially, they learn a source dataset in a supervised way. This model information is then transferred to another model through unsupervised learning and pseudo-labels are generated by generative adversarial learning. The multi-class invariance is handled by adversarial learning. The performance of the proposed model is evaluated on two different datasets source and target datasets. Multiple experiments on Duke and Market datasets indicate higher accuracy of F-1 score on both datasets compared to previous methods, demonstrating the superior performance of the proposed method. © 2025 IEEE.

关键词： Adversarial machine learning

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Performance Analysis of Hybrid MPI and OpenMP on Smith-Waterman Algorithm 3

Performance Analysis of Hybrid MPI and OpenMP on Smith-Water...

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3rd International Conference on Intelligent systems, Advanced Computing, and Communication, ISACC 2025

作者： Ninama, Keyur Patel, Jainamkumar Girish, K.K. Reddy, Manideep Raya V S R S Bhowmik, Biswajit National Institute of Technology Karnataka Maharshi Sushrut CAS Lab BRICS Laboratory Dept. of Computer Science and Engineering Mangalore India National Institute of Technology Karnataka Ishwarchandra Vidyasagar AIT Lab BRICS Laboratory Dept. of Computer Science and Engineering Mangalore India National Institute of Technology Karnataka Maharshi Kanad QC Lab BRICS Laboratory Dept. of Computer Science and Engineering Mangalore India National Institute of Technology Karnataka BRICS Laboratory Dept. of Computer Science and Engineering Mangalore India

ISBN: (纸本)9798331523893

In the rapidly advancing field of bioinformatics, sequence alignment is a pivotal task for elucidating genetic statistics and evolutionary relationships. As the volume and complexity of biological data continue to grow, it becomes imperative to employ effective computational techniques to manage this expansion. The Smith-Waterman algorithm is a key tool for sequence alignment;however, its performance can be constrained by the substantial size of contemporary datasets. To overcome this limitation, this paper explores a hybrid parallelization strategy that integrates message passing interface (MPI) with open multi-processing (OpenMP). This approach aims to significantly enhance the algorithm's efficiency by leveraging the strengths of both parallelization models. By optimizing the scalability and execution speed of the Smith-Waterman algorithm on advanced high-performance computing (HPC) systems, the hybrid technique not only improves performance but also enables more rapid and accurate biological data analysis. © 2025 IEEE.

关键词： Open Data

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Real-time Event Streaming for Financial Enterprise system with Kafka 3

Real-time Event Streaming for Financial Enterprise System wi...

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3rd IEEE Asian Conference on Innovation in Technology, ASIANCON 2023

作者： Sanjana, N. Raj, Sinchana Vishalakshi Prabhu, H. Sandhya, S. Rv College of Engineering Dept. of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798350302288

Real-time event streaming refers to the continuous and immediate processing and analysis of events as they occur in real time. Presently, Apache Kafka is a very popular and preferred framework for real-time data streaming. Data stream pipelines to serve enormous data for large organizations are built between systems in Kafka for real-time streaming. Kafka provides a distributed, scalable, and fault-tolerant platform for capturing, storing, and processing streams of events. It provisions seamless integration with different systems and applications, enabling real-time data analysis and processing. Thus, event streaming with Kafka is a modern approach to processing and analyzing large volumes of data in real-time. Event streaming with Kafka has a wide range of applications in varied industries such as finance, e-commerce, and more. It has the potential to transform the way businesses operate by enabling faster decision-making, improved operational efficiency, and better customer experiences. With financial enterprise application as our main goal, we focus on how Kafka could be a better-suited alternative to enhance event streaming. © 2023 IEEE.

关键词： Decision making

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Evaluating Machine Learning Methods for Bangla Text Emotion Analysis

Evaluating Machine Learning Methods for Bangla Text Emotion ...

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2024 Asia Pacific Conference on Innovation in Technology, APCIT 2024

作者： Akter, Tahmina Akter, Mst. Sharmin Mahmud, Tanjim Islam, Dilshad Hossain, Mohammad Shahadat Andersson, Karl Port City International University Dept. of Computer Science and Engineering Chittagong Bangladesh Rangamati Science and Technology University Dept. of Computer Science and Engineering Rangamati4500 Bangladesh Chattogram Veterinary and Animal Sciences University Dept. of Physical and Mathematical Sciences Bangladesh University of Chittagong Dept. of Computer Science and Engineering Chittagong4331 Bangladesh Luleå University of Technology Cybersecurity Laboratory Luleå97187 Sweden

ISBN: (纸本)9798350361537

Text-based emotion identification goes beyond simple sentiment analysis by capturing emotions in a more nuanced way, akin to shades of gray rather than just positive or negative sentiments. This paper details our experiments with emotion analysis on Bangla text. We collected a corpus of user comments from various social media groups discussing socioeconomic and political topics to identify six emotions: sadness, disgust, surprise, fear, anger, and joy. We evaluated the performance of four widely used machine learning algorithms - RF, DT, k-NN, and SVM - alongside three popular deep learning algorithms - CNNs, LSTM, and Transformer Learning - using TF-IDF feature extraction and word embedding techniques. The results showed that among the machine learning algorithms, DT, RF, k-NN, and SVM achieved accuracy scores of 82%, 84%, 73%, and 83%, respectively. In contrast, the deep learning models CNN and LSTM both achieved higher performance with an accuracy of 85% and 86% respectively. These findings highlight the effectiveness of traditional ML and DL approaches in detecting emotions from Bangla social media texts, indicating significant potential for further advancements in this area. © 2024 IEEE.

关键词： Contrastive Learning

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An Edge AI and Adaptive Embedded system Design for Agricultural Robotics Applications 25

An Edge AI and Adaptive Embedded System Design for Agricultu...

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30th Asia and South Pacific Design Automation Conference, ASP-DAC 2025

作者： Huang, Chun-Hsian Chen, Zhi-Rui Hsu, Huai-Shu Dept. Electrical Engineering National Changhua University of Education Changhua Taiwan Dept. Computer Science and Information Engineering National Taitung University Taitung Taiwan

ISBN: (纸本)9798400706356

This work presents the AgrBot, an agricultural robot designed to intelligently estimate and predict crop pest and disease severity (PDS). The AgrBot incorporates two binarized neural network (BNN) hardware modules for recognizing target crops and estimating their PDS. In a resource-constrained FPGA-based design, these BNN hardware modules can be configured on-demand, showcasing system adaptivity. Furthermore, a multimodal model that integrates crop images, sensor data, and time features is presented for predicting PDS. Employing edge artificial intelligence (AI) through the BNN hardware modules and the multimodal model enables the AgrBot to determine if biological agents are applied to protect crops from pests and diseases, creating a comprehensive agricultural cyber-physical system (CPS). Experimental results demonstrate accuracies of 76.3% for recognizing target crops, 65.3% for estimating PDS, and 67% for predicting PDS. In comparison to existing microprocessor-based design methods, the AgrBot's BNN hardware modules improve frames per second (FPS) by a factor of 790, while the multimodal model reduces processing time by up to 50.9%. © 2025 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Digital storage

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Design and Implementation of Smart Classroom Using Cisco Packet Tracer 1

Design and Implementation of Smart Classroom Using Cisco Pac...

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1st IEEE International Conference on Advances in Electronics, Communication, Computing and Intelligent Information systems, ICAECIS 2023

作者： Duvvuri, Kavya Kanisettypalli, Harshitha Kunisetty, Jaswanth Khanna, Manju Amrita School of Engineering Dept. of Computer Science Engineering Bengaluru India

ISBN: (纸本)9798350348057

Schools and colleges play a very crucial role in everyone's life. It is very important to impart good morals and safe education to future generations. As days go by, the necessity for faster job completion and smarter devices is increasing. The safety of students becomes important as the number of students enrolling in schools is gradually increasing. Discipline and time management skills must be imparted to students from a tender age in the school environment. Both safety and discipline can be ensured by making use of devices that are smarter and remotely controllable. Through this work, we have introduced the design of a smart classroom using a network simulation called Cisco Packet Tracer. The work is based on the concept of the Internet of Things. It has multiple subsystems that together make the class a wonderful place for students to build their future. © 2023 IEEE.

关键词： Students

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