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18th International Symposium on Information Theory and Its Applications, ISITA 2024

作者： Ichijo, Naoki Maniwa, Ryota Nakahara, Yuta Shimada, Koshi Matsushima, Toshiyasu Waseda University Dept. of Pure and Applied Math. Tokyo Japan Kddi Corporation Tokyo Japan Waseda University Center for Data Science Tokyo Japan

ISBN: (纸本)9784885523519

Decision tree algorithms are one of the most popular methods in machine learning. However, most decision tree algorithms do not assume a stochastic model behind data. On the other hand, a meta-tree was recently proposed as a stochastic model with a tree structure. The prediction under the assumption of the meta-tree is decided using Bayesian decision theory. Although the optimal prediction can be calculated with an assumption of a known meta-tree, an approximation is necessary to obtain a prediction under the problem setting of an unknown meta-tree because of the marginalization of all possible meta-trees. In this paper, we propose an approximation method, where a subset of meta-trees is sequentially constructed, and the prediction is made by weighting the meta-trees. For the approximation, we clarify the approaches of constructing the subset and making predictions with weighted meta-trees. We also examine the effectiveness of the approaches in an experiment using synthetic data. In addition, we conduct an experiment on benchmark data to confirm the performance of the proposal. © 2024 The Institute of Electronics, Information and Communication Engineers.

关键词： Prediction models

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Block-Hash Signature (BHS) for Transaction Validation in Smart Contracts for Security and Privacy using Blockchain

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Journal of Mobile Multimedia 2023年第4期19卷 935-962页

作者： Bhatnagar, Sonika Dayal, Mohit Singh, Deepti Upreti, Shitiz Upreti, Kamal Kumar, Jitender Dept. of Computer Science & Engineering Government Polytechnic Baheri Bareilly India Dept. of Applied Science Bharati Vidyapeeth’s College of Engineering New Delhi India Dept. of Information Technology ABES Institute of Technology Ghaziabad India Dept.of Information Technology Asian Education Group (AEG) Noida India Dept. of Computer Science & Engineering Dr. Akhilesh Das Gupta Institute of Technology and Management New Delhi India Dept. of Computer Science & Engineering J.C Bose University of Science & Technology YMCA Haryana Faridabad India

Some of the well-known signature techniques like Winternitz and Lamport are not considered to be very appropriate for the usage of hashing or smart contracts in Blockchains security because of their size O(n²), which is prominently too high. Although in Blockchain, the security concern is on the top priority because of its distributed P2P design still, the security enhancement is required to sign and verify the documents forwarded to the peers, especially in Hyperledger Fabric. Here, this paper presents a new signature technique “Block-Hash” to enhance Blockchain security by using it in smart contracts as well as hashing with size 3Xn bits (n = 256, generally for SHA-256 Hashing) and which can score 112 bits security. The proposed signature can be used appropriately for signing a smart contract by the endorser or committer node. Also, it can be used with a hash algorithm in forming a Merkle tree. Apart from the description and implementation of Block-Hash Signature, this paper has covered the analysis of its security and correctness measures with a table for result comparison. © 2023 River Publishers.

关键词： blockchain security Digital signature hyperledger fabric smart contract

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Faster R-CNN in Healthcare and Disease Detection: A Comprehensive Review

Faster R-CNN in Healthcare and Disease Detection: A Comprehe...

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2025 International Conference on Electronics, Information, and Communication, ICEIC 2025

作者： Tian, Jiawei Lee, Seungho Kang, Kyungtae Major in Bio Artificial Intelligence Hanyang University Dept. of Computer Science and Engineering Ansan-si Korea Republic of Hanyang University Dept. of Applied Artificial Intelligence Ansan-si Korea Republic of Hanyang University Dept. of Artificial Intelligence Ansan-si Korea Republic of

ISBN: (纸本)9798331510756

This review examines the applications, challenges, and prospects of Faster Region-based Convolutional Neural Networks (Faster R-CNN) in healthcare and disease detection. Through a meta-analysis of Web of science literature from 2017 to 2024, we provide insights into the evolving landscape of Faster R-CNN in medical contexts. The algorithm can be applied to medical image analysis across various modalities, including radiography, computed tomography, magnetic resonance imaging, ultrasound, microscopy, and endoscopy. Its applications extend to optical RGB images for dermatological and surgical uses, as well as broader healthcare areas such as posture detection, medication recognition, and assistive technologies. Despite its success, Faster R-CNN faces challenges in handling subtle abnormalities, addressing class imbalance in medical datasets, ensuring result interpretability, and managing patient privacy. Our analysis reveals dominant application areas, technological advancements, and integration trends with other artificial intelligence technologies. The review highlights Faster R-CNN's significant impact on improving diagnostic accuracy and healthcare delivery while acknowledging the need for continued research to address limitations. Emerging directions include real-time disease detection and advancements in personalized medicine, underscoring Faster R-CNN's potential to further transform healthcare practices and patient outcomes. © 2025 IEEE.

关键词： computerized tomography

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InterACT: Enhancing Human-AI Interaction 2

InterACT: Enhancing Human-AI Interaction

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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Katta, Jithendra Kodumuru, Nikhil Reddy Katta, Swathi School of Engineering and Applied Sciences The George Washington University WashingtonDC United States Vignana Bharathi Institute of Technology Computer Science & Engineering dept. Hyderabad India

ISBN: (纸本)9798331505745

The rapid advancement of large language models and computer vision systems has opened new frontiers in artificial intelligence. This paper introduces InterACT, a novel cross-modal system that integrates leading language and vision models to enable more intuitive and context-aware human AI interactions. By leveraging the strengths of both modalities, InterACT processes natural language queries to guide object detection in visual environments, bridging the gap between linguistic and visual understanding. We evaluate the performance of three language models of varying sizes in conjunction with an advanced object detection model, exploring the balance between computational efficiency and interaction quality. Our experiments demonstrate InterACT's potential across diverse real-world scenarios, revealing promising results in maintaining contextual relevance and adaptability. This research contributes to the growing field of cross-modal AI systems and lays the groundwork for more sophisticated human AI interactions, with implications for applications ranging from assistive technologies to educational tools. © 2025 IEEE.

关键词： Object detection

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Grammatical Evolution of Synthesizable Finite State Machine-Based Behavioural Level Hardware Description Language Codes 16th

Grammatical Evolution of Synthesizable Finite State Machine-...

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16th International Joint Conference on Computational Intelligence, IJCCI 2024

作者： Majeed, Bilal McEllin, Jack Sarma, Rajkumar Youssef, Ayman Mota Dias, Douglas Ryan, Conor BDS Labs Dept. of CSIS University of Limerick Limerick Ireland Dept. of Computers and Systems Electronics Research Institute Cairo Egypt Department of Computer Science & Applied Physics Atlantic Technological University Galway Ireland

ISBN: (纸本)9789897587214

The importance of designing efficient and accurate digital circuits has grown due to the widespread use of wearable, ready-made, and custom electronic products. These digital circuits are typically sequential and designed using synthesizable Hardware Description Languages (HDLs) that can be translated into hardware. A large part of this exercise comprises designing synthesizable HDLs for sequential circuits, which are challenging to design and test, thus requiring much time for the engineers to construct them. This paper proposes using Grammatical Evolution (GE) to evolve the synthesizable HDL codes for sequential circuits on the behavioural or algorithmic level in SystemVerilog. The codes evolved in this work are of JK-Flip Flop (JK-FF), 3-bit UpDown Counter (UDC), and 8-Floor Elevator (8FE), all from the perspective of Finite State Machines (FSMs). Circuits such as 3-bit UDC and JK-FF are the basic blocks in many circuits in the industry, while 8FE is a real-life example mimicking 3-bit UDC but with a few practical exceptions. All circuits are evolved using two types of grammars. The G1 Type Grammar evolves parts of the code, while the more powerful and generic G2 Type Grammar evolves the full HDL codes for these sequential circuits. The GE-based evolution of these synthesizable design codes using both types of grammar achieves a success rate of over 86% for all circuits. Moreover, all the solution circuits evolved with the best achieved success score under the respective hyperparameter settings for G1 and G2 Type Grammar are synthesised, and their synthesis reports are compared against the synthesis reports of Gold (human-designed) circuits. The synthesis is performed using Cadence Genus at Generic Process Design Kit (GPDK) 45, 90, and 180 nm technology libraries. The synthesis results show that machine-generated designs often perform as well as or better than human-designed circuits. © 2024 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Flip flop circuits

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The Integration of 6G and Blockchain into an Efficient AIoT-Based Smart Education Model 6

The Integration of 6G and Blockchain into an Efficient AIoT-...

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6th World Symposium on Communication Engineering, WSCE 2023

作者： Lioupa, Anna Memos, Vasileios A. Stergiou, Christos L. Ishibashi, Yutaka Psannis, Konstantinos E. School of Information Sciences University of Macedonia Dept. of Applied Informatics Thessaloniki Greece Graduate School of Engineering Nagoya Institute of Technology Dept. of Computer Science Nagoya Japan

ISBN: (纸本)9798350339505

The technological advances impact the future classrooms and the whole education system. The evolution of 6G promises faster speeds based on terahertz, wireless communication, the leverage of artificial intelligence (AL), virtually reality (VR) and generally a fully connected world. The use of applications of IoT and AIoT improves the education environment, but the intelligent network services undoubtedly gather, store and analyze big data which are vulnerable to attackers. As a solution we may consider the technology of blockchain. The trust and security of next generation intelligent networks are essential part of their design. In this article we suggest a data security system based on blockchain for AL applications in 6G networks. First, we present two Al-enabled applications, indoor positioning and mobile payment within the framework of 6G in the university area. We present the efficiency of blockchain in data security for Al-enabled systems using two case studies of indoor positioning system and mobile payment. The 6G system which is fully supported by Al and the integration of this in technology of blockchain, is ensured the security in future wireless communication. © 2023 IEEE.

关键词： Blockchain

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Exploring OSINT for Modern Day Reconnaissance

Exploring OSINT for Modern Day Reconnaissance

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2023 Annual International Conference on Emerging Research Areas: International Conference on Intelligent Systems, AICERA/ICIS 2023

作者： Ram, Ajay S. Thalakkat, Arya Udayan, Devika Khader, Aiby A. Hari, K. George, Vipin Government Engineering College Dept. of Computer Science and Engg. Thrissur India School of Technology and Applied Science Dept. of Cyber Forensics Kottayam India Kerala Police Academy Dept. of Computer Application Thrissur India Kerala Police Academy Police Computer Lab Thrissur India Kerala Police Academy Thrissur India

ISBN: (纸本)9798350303452

The Internet's growth has connected users globally, forming a vast network of data. As new social media platforms with diverse features emerge, individuals are drawn to sharing their personal data online. This inclination stems from a desire to display social status. However, this openness poses risks, as personal data uploaded to the internet can easily unveil one's online identity. Extracting such data is a straightforward process, as a simple correlation of evidence with an online profile can summarize a user's identity. By combining various sources of information linked to a specific individual, a comprehensive profile can be created. As the digital landscape expands, Open Source Intelligence (OSINT) has become an invaluable tool for gathering information. OSINT involves searching and accessing publicly available data to extract relevant information, analyze patterns, and draw conclusions. It encompasses activities like web scraping, data mining, social media monitoring, and online research. OSINT is crucial for understanding public sentiment, identifying potential threats, conducting background checks, investigating crimes, and performing competitive analysis. This paper investigates the impact of OSINT as a modern day reconnaissance tool. Through case studies and real-world examples, the research demonstrates the effectiveness of OSINT in enhancing situational awareness, supporting decision-making for law enforcement agencies, and using OSINT as a modern-day reconnaissance tool. © 2023 IEEE.

关键词： Data mining

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Impact of Learning Style based Teaching on Students Performance in a Formal Methods Course for computer Scientists 11

Impact of Learning Style based Teaching on Students Performa...

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11th IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2022

作者： Schorr, Ruth Frankfurt University of Applied Sciences Dept. of Computer Science and Engineering Frankfurt Germany

ISBN: (纸本)9781665491174

Teaching a formal methods course can be challenging. Students perceive formal methods as difficult, too mathematical and practical irrelevant. Students show low motivation for the subject, they just want to pass the course with minimal effort. Grades in mandatory formal methods courses are typically below average. In order to address the problems, we analyzed the learning styles of our students. In this work-inprogress paper, we present the changes made to our teaching framework and their impact on student performance. This paper is an experience report on improving performance of master students in formal methods at Frankfurt University of applied sciences. © 2022 IEEE.

关键词： Formal methods

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Asynchronous Traffic Shaping and Redundancy: Avoiding Unbounded Latencies in In-Car Networks

arXiv

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arXiv 2025年

作者： Lübeck, Teresa Meyer, Philipp Häckel, Timo Korf, Franz Schmidt, Thomas C. Dept. Computer Science Hamburg University of Applied Sciences Germany

Time-Sensitive Networking (TSN) enhances Ethernet-based In-Vehicle Networks (IVNs) with real-time capabilities. Different traffic shaping algorithms have been proposed for time-critical communication, of which the Asynchronous Traffic Shaper (ATS) is an upcoming candidate. However, recent research has shown that ATS can introduce unbounded latencies when shaping traffic from non-FIFO systems. This impacts the applicability of ATS in IVNs, as these networks often use redundancy mechanisms that can cause non-FIFO behaviour. In this paper, we approach the problem of accumulated delays from ATS by analyzing the scenarios that generate latency and by devising placement and configurations of ATS schedulers to prevent this behavior. Our solution successfully mitigates problematic preconditions that lead to unbounded delays, which we evaluate in simulations. Through a realistic IVN simulation case study, we demonstrate the occurrence of unbounded latencies and validate the effectiveness of our approach in avoiding them. Copyright © 2025, The Authors. All rights reserved.

关键词： Time division multiple access

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ECDSA-based tamper detection in medical data using a watermarking technique

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International Journal of Cognitive Computing in Engineering 2024年第1期5卷 78-87页

作者： Ch, Rupa Vivek K, Naga Srivastava, Gautam Reddy Gadekallu Department CSE VR Siddhartha Engineering College Andhra Pradesh Vijayawada520 007 India Dept of Math and Computer Science Brandon University MB Canada Dept. of Computer Science and Math Lebanese American University Beirut1102 Lebanon Centre of Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara Punjab Rajpura140401 India Lebanese American University Department of Electrical and Computer Engineering Byblos Lebanon Lovely Professional University Division of Research and development Phagwara India Jiaxing University College of Information Science and Engineering Jiaxing China

Telemedicine is a form of healthcare delivery that employs communication technology to provide medical care to patients remotely. The use of telemedicine has seen a significant increase in recent years, presenting challenges such as patient privacy, data security, the need for reliable communication technology, and the potential for misdiagnosis without a physical examination. Digital Watermarking can assist in addressing such issues by incorporating a unique identifier into an image that can be used to authenticate its validity. To tackle these issues, this study proposes a robust digital watermarking approach tailored to brain medical images, combining hashing, the Elliptic Curve Digital Signature Algorithm (ECDSA), and the Integer Wavelet Transform-Discrete Cosine Transform (IWT-DCT). This method utilizes the Secure Hash Algorithm (SHA-256) to first segment the brain's Region of Interest (RoI). Subsequently, the hashed RoI, along with an ECDSA signature, is embedded into the high-frequency sub-bands of the medical image using IWT-DCT. The embedding process strategically alters the coefficients of the high-frequency sub-bands to accommodate the signature while minimizing perceptual distortion. The technique leverages the robustness of transformed-domain image watermarking techniques against various attacks and combines it with SHA-256 for integrity and ECDSA for authentication purposes. The results demonstrate that the suggested approach is robust to a variety of image processing techniques, including noise addition, filtering, and compression while maintaining high levels of imperceptibility. Key metrics such as the Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), and Structural Similarity Index (SSIM) were used to evaluate performance. The suggested strategy exhibited a substantial improvement over existing methods. The PSNR increased to 68.67, indicating higher image quality, while the MSE reduced to 0.96, demonstrating closer pixel values to the or

关键词： Mean square error

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