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2024 International Conference on Knowledge Engineering and Communication Systems, ICKECS 2024

作者： Srivastava, Supriya Kaur, GeetKiran Himank Singla, Sanjay Chandigarh University Dept. of Computer Science & Engineering Mohali140413 India Chandigarh University Dept. of Computer Science & Engineering Gharuan India

ISBN: (纸本)9798350359688

Nowadays due to increasing cases of evidence alteration the need of a robust evidence protection system is increasing rapidly. This paper presents an innovative solution that combines the InterPlanetary File System (IPFS) with blockchain technology to enhance the security, immutability, and transparency of evidential data obtained from crime *** proposed system initiates by utilizing IPFS, a decentralized and distributed file storage protocol, to securely store multimedia evidence, such as photographs. The content-addressed nature of IPFS guarantees tamper-resistant storage, making it an ideal choice for preserving the integrity of sensitive evidentiary materials. The IPFS addresses obtained from IPFS are then embedded within the blockchain, establishing a decentralized and verifiable link between the evidence and its storage location. We use multi-signature wallet to upload the data on blockchain so that we can make it more secure and monitored about who is uploading evidence state data. To verify links and integrity of evidence usage we set up a system of periodical updates of state of evidence whenever accessed. These updates serve as a mechanism to record the state of the evidence at different points in time, adding an additional layer of reliability and accountability. © 2024 IEEE.

关键词： Blockchain

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ChatGPT Act as an Intelligence Officer

ChatGPT Act as an Intelligence Officer

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2023 IEEE International Workshop on Technologies for Defense and Security, TechDefense 2023

作者： Snidaro, Lauro Computer Science and Physics University of Udine Dept. Mathematics Udine Italy

ISBN: (纸本)9798350319392

This paper explores the potential of Large Language Models (LLMs), specifically ChatGPT, to facilitate the work of intelligence officers. LLMs have demonstrated remarkable capabilities in natural language processing and generation, making them valuable tools for information retrieval, analysis, and decision-making. This paper presents an initial overview of the capabilities of LLMs in intelligence operations. Through a case study on ChatGPT, we illustrate how intelligence officers can leverage LLMs to enhance their work, including data collection, fusion, analysis, report generation, and information sharing. The results showcase the vast potential and the limits of LLMs in supporting intelligence officers in their complex and demanding tasks. © 2023 IEEE.

关键词： Decision making

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Identification of Z Cam's Historical Counterpart: The Quest for an Ancient Nova

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Research in Astronomy and Astrophysics 2024年第12期24卷 31-42页

作者： Bo-Shun Yang Susanne M.Hoffmann University of Science and Technology of China Dept.of the History of Science and Scientific ArchaeologyHefei 230026China Friedrich Schiller University of Jena Faculty of Mathematics and Computer ScienceFUSION Group07737 JenaGermany

In recent astronomical discussions, attempts have been made to link the known dwarf nova Z Cam to historical celestial events, particularly the “guest star” phenomenon reported in China in 77 BCE. Despite other suggestions and the problems with regard to the location of the event in 77 BCE, its identification with Z Cam is used in the Variable Star Index of the AAVSO and in several research papers that aim to derive knowledge on the evolution of cataclysmic variables. Through the reconstruction of the super-constellation of the Purple Palace in the Han Dynasty, we found that Z Cam is actually located outside this enclosure, contradicting the records of the 77 BCE guest star being “within the Purple Palace.” With newly found text versions of the guest star in 77 BCE, we narrowed down the position given therein. Combining with a new analysis of accompanying divination text leads to the conclusion that this guest star was actually a comet. Finally, through meticulous examination and comparison, we conclude that the guest star of 369 CE appears the most plausible candidate for Z Cam's historical counterpart, aligning with both textual evidence and modern astronomical observations.

关键词： (stars) novae-cataclysmic variables-history and philosophy of astronomy-stars dwarf novae-stars evolution

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An Integrated Monitoring System for Aerial Drones and Underwater ROVs

An Integrated Monitoring System for Aerial Drones and Underw...

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2023 IEEE International Workshop on Technologies for Defense and Security, TechDefense 2023

作者： Cecchinato, Niccolo Toma, Andrea Scagnetto, Ivan Drioli, Carlo Foresti, Gian Luca University of Udine Dept. of Mathematics Computer Science and Physics Udine Italy

ISBN: (纸本)9798350319392

We present an integrated and intelligent cooperative platform for the detection, recognition and tracking of objects in the air, underwater and on the surface. The system is based on a data integration process driven by the coordinated use of Unmanned Aerial Vehicles (UAVs) and Unmanned Underwater Vehicles (UUVs) equipped with heterogeneous sensors (e.g., magnetometers, electro-optical sensors, cameras and microphones) sending the acquired data to a centralized Ground Control Station (GCS). When the area to be monitored is large, it is needed to partition it, assigning each part to different UAVs/UUVs. Thus, those UAVs and UUVs are the nodes of a communication network where data exchange is aimed at the communication of information relating to the detection/recognition/tracking of objects. This kind of messages is very important when, for example, the object being tracked moves out of the area of competence of a given UAV/UUV to enter another area surveyed by a different UAV/UUV. The system will be useful for ISTAR (Intelligence, Surveillance, Target Acquisition, Reconnaissance) applications including both the identification of static objects positioned on the seabed (e.g., unexploded bombs, underwater infrastructures, etc.) and the identification and tracking of objects moving underwater, on the surface or flying in the area of interest. A study on a secure and encrypted wireless connection between the fleet of drones and the GCS is also addressed and an effective method for changing data encryption keys during the mission is illustrated. © 2023 IEEE.

关键词： Internet of things

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A Comprehensive Analysis on Skin Cancer Classification Using Transfer Learning 3

A Comprehensive Analysis on Skin Cancer Classification Using...

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3rd International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2024

作者： Renu, Israt Zerin Haque, Md. Momenul Paul, Subrata Kumer Mou, Mahmuda Shirin Rahman, Md Nahid Gupta, Sudipta Sen Paul, Rakhi Rani Rabindra Maitree University Dept. of Computer Science and Engineering Kushtia7000 Bangladesh Qadirabad Dept. of Computer Science and Engineering Dayarampur Natore6431 Bangladesh University of Rajshahi Dept. of Computer Science and Engineering Rajshahi6205 Bangladesh

ISBN: (纸本)9798350388282

Skin cancer, a prevalent and potentially life-threatening disease, necessitates accurate and timely diagnosis for effective treatment. In addressing this critical healthcare challenge, this research proposes a novel approach to skin cancer classification. The study identifies the need for enhanced diagnostic accuracy and introduces a solution by integrating the efficiency of transfer learning, specifically utilizing the EfficientNet V2 architecture. The proposed methodology leverages pre-trained convolutional neural networks (CNNs) to extract high-level features from dermatological images, which are subsequently input into a sophisticated classifier, forming a robust framework for precise skin cancer classification. The research employs a diverse dataset comprising 3297 images sourced from the publicly available Skin Cancer ISIC archive dataset, ensuring comprehensive coverage of benign and malignant skin lesions. During the training phase, the proposed EfficientNet V2 transfer learning approach outperforms conventional methods, achieving an impressive accuracy of 84%, surpassing both Inception V3 (82%) and a generic CNN model (81%). Interpretability analysis is conducted to elucidate the decision-making process of the EfficientNet V2 model, providing insights into the key features influencing its predictions. This transparency is crucial for building trust in the model's recommendations and facilitating its seamless integration into clinical workflows. The EfficientNet V2 transfer learning approach emerges as a promising and effective solution for advancing skin cancer classification systems, contributing significantly to the ongoing efforts to improve diagnostic accuracy in dermatology. © 2024 IEEE.

关键词： Decision making

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NLP Powered Restaurant Chatbot for Exceptional Customer Engagement 2

NLP Powered Restaurant Chatbot for Exceptional Customer Enga...

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2nd International Conference on Advancement in Computation and computer Technologies, InCACCT 2024

作者： Goyal, Diya Guru Prasad, M.S. Garg, Ishika Tewari, Shashank Pandu N, K. Asha, P.N. Dept. of Computer Science and Engineering Dehradun India Srinivas University Institute of Engineering & Technology Dept. of Computer Science and Engineering Surathkal India REVA University School of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350371314

Technology is very volatile in nature, in a way that it keeps on changing daily. Restaurants are no different in the effects of this changing scenario. The primary objective of this research paper is to explore the historical trajectory of restaurants, analyze the current trends shaping the industry, and delve into the potential of chatbot integration to overcome existing challenges. Chatbots can play a pivotal role in enhancing the performance of businesses as per the research done. An integrated Dialog Flow application has been proposed, incorporating Rule-based grammar matching and M.L matching algorithms. This proposed work is trying to make NLP-based chatbots which may expedite the endeavor of businesses to produce and become profitable. © 2024 IEEE.

关键词： Python

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Enhancing 5G Efficiency: Regression Analysis for Resource Allocation Optimization in Wireless Networks

Enhancing 5G Efficiency: Regression Analysis for Resource Al...

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2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Padmageetha, B.G. Kumar Naik, Pramod Patil, Mallanagouda Dayananda Sagar University Dept. of Computer Applications Bengaluru India Dayananda Sagar University Dept. of Computer Science and Engineering Bengaluru India RVITM Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350378092

The advent of 5G networks signifies a major breakthrough in mobile communications, providing better data rates, low latency, and improved connectivity. Efficient resource allocation within 5G networks is paramount to fully leverage these capabilities, ensuring optimal performance and user satisfaction. Traditional resource allocation methods often struggle to keep pace with the dynamic and complex nature of 5G environments. The potential benefits of machine learning (ML) is explored in this research to enhance resource allocation in 5G networks. We begin by examining the unique challenges posed by 5G networks, by ML approaches employed for resource allocation, including supervised learning such as Trees, SVM, Neural Networks. Our study we train the model using MATLAB simulator. Analysis on the response and residual plot is conducted for predicted response. Analysis and comparative study is made to find the best performance metric suitable for the predicting the model for resource allocation. The study shows the improvisation in the metrics of regression learner. Simulation results demonstrate significant improvements in network performance. Finally, we have done the comparison between the results of MATLAB simulation. This study gives better decisions to service providers to enhance the overall performance of network © 2024 IEEE.

关键词： MATLAB

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An Effective Method to Detect DHCP Starvation Attack using Port Scanning

An Effective Method to Detect DHCP Starvation Attack using P...

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2023 International Conference on Next-Generation Computing, IoT and Machine Learning, NCIM 2023

作者： Jony, Asaduzzaman Miah, Abu Saleh Musa Islam, Muhammad Nazrul Dept. of Computer Science and Engineering Dhaka Bangladesh The University of Aizu Dept. of Computer Science and Engineering Aizuwakamatsu Japan Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350316001

Nowadays, the DHCP starvation attack is a crucial attack that denied the services for the legitimate network user where the attacker mainly occupies all the IP addresses in the DHCP server pool. Most of the existing studies proposed ICMP (Internet Control Message Protocol) and the ARP (Address Resolution Protocol) based techniques to detect the DHCP starvation attack. However, the ICMP-based detection is ineffective if the client has an active host-based firewall that blocks the ICMP ECHO REQUEST, while the ARP-based detection does not work for DHCP networks separated by a DHCP relay agent and works only within the same or local network. Therefore, the objective of this research is to propose an effective technique to detect DHCP starvation attack detection through port scanning to address the limitations of ICMP and ARP-based detection methods. To attain this objective, this study first highlights the limitations of existing detection methods demonstrating insightful facts. Secondly, the study proposed a port scan-based DHCP starvation attack detection method for local and remote (relay) DHCP networks. Finally, the effectiveness and validation of the proposed techniques were demonstrated using the Multivendor Network Emulation Software (EVE-NG). The study showed that the proposed port scanning-based technique could accurately detect the DHCP starvation attack while overcoming the limitations of the ICMP and ARP techniques. © 2023 IEEE.

关键词： Network security

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Adchat-TVQA: Innovative Application of LLMs-Based Text-Visual Question Answering Method in Advertising Legal Compliance Review 5

Adchat-TVQA: Innovative Application of LLMs-Based Text-Visua...

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5th International Conference on Machine Learning and computer Application, ICMLCA 2024

作者： Gao, Ruiling Hou, Yingqi Tang, Weijie Zhang, Jin Hu, Yanbo Huang, Haiyun Tan, Wen'an Li, Liping Shanghai Polytechnic University Dept. of Computer Engineering Shanghai China Donghua University Dept. of Computer Science Shanghai China Tufts University Dept. of Computer Science MedfordMA United States

ISBN: (纸本)9798331530334

Advertising legal compliance reviews have always been time-consuming and labor-intensive, and existing Large Language Models(LLMs) are far worse performing than senior industry experts. In this paper, we propose a novel LLMs-based text-visual question answering method called Adchat-TVQA for advertising legal compliance review. After reading an advertising image and the corresponding review question, it will first understand the content on the image through multimodal learning, then optimize the question with Zero-Shot Chain-of-Thought (CoT) prompting method based on predefined industry expert experience, and finally input the augmented question into the large language model for inquiry. The feasibility of this method is verified through system prototype implementation and end-to-end functional tests. In addition, we summarized the characteristics of advertising images and added image segmentation and text box transpose to the data processing process for system performance improvement. Performance testing of the text visual cognitive question task on the AIWIN2021 dataset shows that the method scores higher than Microsoft's LayoutLM, with an increasement of the score from 51.52% to 52.74%. © 2024 IEEE.

关键词： Marketing

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Energy Efficient LEDCA Analysis for Improved Throughput in Wireless Sensor Networks 6

Energy Efficient LEDCA Analysis for Improved Throughput in W...

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6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Padmageetha, B.G. Naik, Pramod Kumar Patil, Mallanagouda Dept.of Computer Applications Dayananda Sagar University Bengaluru India Dept. of Computer science and Engineering Dayananda Sagar University Bengaluru India Dept. of Computer science and Engineering RVITM Bengaluru India

ISBN: (纸本)9798331522667

Wireless Sensor Networks (WSNs) face significant challenges in terms of energy conservation, scalability, and data throughput owing to their limited node energy resources. This paper presents a low-energy data-centric algorithm (LEDCA), a novel energy-aware clustering and routing protocol designed to optimize energy efficiency and improve throughput in WSNs. Through simulations, LEDCA demonstrated a Packet Delivery Ratio (PDR) of up to 90%, throughput of 255,217 bps, and average latency of 159 ms, validating its efficiency in resource-constrained environments. The algorithm integrates residual energy awareness by prioritizing high-energy nodes for Cluster Head (CH) roles, dynamically adjusting routing paths, and balancing the network load to prevent premature node failure. By applying an Energy Mapping Node and a real-time Energy Mapping Table, LEDCA minimizes re-clustering, reduces data redundancy, and ensures stable data transmission even under high-density networks. Simulation results also show LEDCA's scalability of LEDCA, with A9_T_200 achieving the highest throughput under extended transmission ranges and A3_T_200 achieving the lowest latency, making it suitable for energy-sensitive and latency-critical applications. Future enhancements, such as integrating Non-Orthogonal Multiple Access (NOMA) and dynamic resource allocation, could further improve LEDCA’s interference management and scalability of LEDCA for IoT and 5G/6G networks, addressing the needs of next-generation applications. © 2025 IEEE.

关键词： Resource allocation

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