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BC-SBOM: Blockchain-based SBOM Management System 27

BC-SBOM: Blockchain-based SBOM Management System

引用

27th international conference on advanced Communications Technology, ICACT 2025

作者： Song, Ahyun Seo, Euiseong Kim, Heeyoul Department of Computer Science and Engineering Sungkyunkwan University Korea Republic of Division of Computer Science and Engineering Kyonggi University Korea Republic of

ISBN: (纸本)9791188428137

This paper presents BC-SBOM, a novel blockchainbased system designed to enhance the management of Software Bills of Materials (SBOMs). By leveraging blockchain technology, BC-SBOM ensures secure storage and sharing of SBOMs, while providing a comprehensive global view of dependencies among software components. The system also supports rapid propagation of alerts for newly discovered vulnerabilities, thereby increasing responsiveness to potential threats. Offering superior reliability, transparency, and availability compared to traditional SBOM tools, BC-SBOM aims to significantly improve the management of complex software systems and contribute to the advancement of software security practices. Copyright 2025 Global IT Research Institute (GIRI). All rights reserved.

关键词： Blockchain

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A Robust Lane Detection and Tracking Method based on vanishing point for Multi-environment Situation

A Robust Lane Detection and Tracking Method based on vanishi...

引用

2024 international conference on computer Vision and Image Processing, CVIP 2024

作者： Zhou, Guimin Zhang, Dongmin Zhu, Futang Yang, Dongsheng Shien-Ming Wu School of Intelligent Engineering South China University of Technology: Guangzhou Guangzhou51400 China : Shenzhen Shenzhen518118 China

ISBN: (纸本)9781510688384

Lane detection and tracking technologies play a crucial role in advancing autonomous driving and advanced driver assistance systems (ADAS). However, the existing methods struggle to achieve accurate detection across diverse environments. In this study, we proposed an adaptive lane detection and tracking algorithm based on the vanishing point. Initially, the edges of the lane lines were extracted using the ROI and 2D-FIR filter. Next, the vanishing point of the image is detected using Gabor filters, and adaptive inverse perspective transformation is achieved through coordinate conversion. Eventually, the detection of lane lines through the dynamic sliding window is attained by introducing the spatio-temporal sequence module, while tracking is performed with the adaptive Kalman filter by leveraging the lane width constraint. The method was tested on our dataset, which covers seven different environments and comprises over 4644 frames. The experimental results demonstrate that the accuracy of the detection is 92.9% and the center offset is close to 5.4 pixels. © 2025 SPIE.

关键词： advanced driver assistance systems

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engineering Design and Prototyping Methodology in Complex Environments: The In-Bore Welding Tool 4th

Engineering Design and Prototyping Methodology in Complex En...

引用

4th international conference of the Italian Association of Design Methods and Tools for Industrial engineering

作者： Claps, Vincenzo Di Giacomo, Antonio Salvato, Rocco Sorgente, Donato Mozzillo, Rocco Basilicata Univ CREATE Engn Sch Campus Macchia Romana Potenza Italy Politecn Bari Dept Mech Math & Management Via Orabona 4 I-70125 Bari Italy

ISBN: (纸本)9783031765964;9783031765971

The engineering process is a critical area in the design and development of devices for scientific, industrial and technological applications. This process involves the conceptualization, design, prototyping and production of equipment suitable for specific operations or functions. The main objectives of equipment engineering are to optimize the performance, efficiency of functionality, safety and reliability of devices, as well as to reduce costs and production time. The application of advanced engineering methodologies, such as computer-Aided Design (CAD), systems analysis and advanced manufacturing techniques such as Additive Manufacturing (AM), allows the creation of high specialized and high performance equipment to satisfy the specific needs of modern industries. In the framework of advanced technologies such as nuclear fusion, equipment engineering plays a key role in solving complex challenges and developing innovative solutions involving various aspects of engineering knowledge. This paper presents the design and prototyping process of a tool for in-bore welding of pipes used in fusion nuclear power plants, called In-Bore Welding Tool (IBWT).

关键词： Design Methods Additive Manufacturing engineering Design CAD Prototyping

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Comprehensive Review: Advancing Cognitive Computingthrough theory of Mind Integration and Deep Learning in Artificial Intelligence 24

Comprehensive Review: Advancing Cognitive Computingthrough T...

引用

8th international conference on computer Science and Application engineering, CSAE 2024

作者： Liu, Shuyan Wang, Kangsheng School of Information Science and Engineering Yunnan University Yunnan Kunming China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China

ISBN: (纸本)9798400718090

In this article, we will review our advances in intelligence modeling the mind and explore various efforts to mimic the processes that would allow humans to perform cognition files and line widgets of processing. It presents ideas and stresses how understanding cognitive functions is vital for AI progress. Three principal modeling strategies are examined: cognitive mind modeling, assignation mind modeling, and intelligent body mind modeling. In the article, he explores a few theories, such as symbol systems and the ACT-R framework. It further argues that learning seems limited in encoding models of the mind, citing its successes in language-oriented tasks and its limitations in translating basic mechanisms like reward to model-level language and data from neuroscience. Additionally, it investigates ways of assessing and enhancing learning theory of mind abilities based on tasks that utilize end-to-end function. The review reiterates the need for an improved understanding of human-level thought processing to develop intelligent systems that can better discern intentions and feelings. It provides some ideas on evaluating this based on deep learning approaches. The review argues that viewing learning through the lens of systems yields new insights into human thought and social behavior that could enable the development of novel and more adaptive AI technologies. © 2024 Copyright held by the owner/author(s).

关键词： Contrastive Learning

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Frozen Food Supply Chain Monitoring with IoT 19

Frozen Food Supply Chain Monitoring with IoT

引用

19th international conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Mohd Kassim, Mohd Sallehin Rozman, Muhammad Haziq bin Yahya, Faridah Advanced Telecommunication Technology Cluster International Industrial and Institutional Partnership Department Computer Engineering Technology Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia Internet of Thing Computer Engineering Technology Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia Computer Engineering Technology Section Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia

ISBN: (纸本)9798331507817

This project aimed to implement a prototype capable of real-time monitoring and control of various parameters in information management setting with Internet of Things (IoT). Research methodology involved designing and implementing the system prototype to resemble a supply container or transportation truck with installed sensors controlled by a microcontroller. Main components used temperature sensors (AHT20), RFID reader for access control, GPS module for location tracking, and a web/mobile dashboard for remote monitoring. Additionally, a robust database system was developed to store sensor readings and transaction history, ensuring data integrity and facilitating seamless communication between components for real-time data transmission. Key findings indicate that the system effectively monitors temperature, manages access control through RFID authentication, tracks real-time location via GPS, and provides a user-friendly dashboard interface for data visualization. © 2025 IEEE.

关键词： Access control

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computer graphics and image processing techniques based on visual communication design 4

Computer graphics and image processing techniques based on v...

引用

4th international conference on computer Vision, Application, and Algorithm, CVAA 2024

作者： Chen, Zhaoguo College of Arts Shandong Agricultural Engineering University Shandong Province Jinan250103 China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

To fully harness the capabilities of computer graphics and image processing technologies and elevate the quality of visual communication design, this paper presents a comprehensive suite of innovative methodologies. Firstly, the fundamental principles of primary colors are utilized to formulate a series of vector functions, facilitating the precise calculation of error distances and the establishment of an intricate visual communication zoning model. Subsequently, through the exhaustive extraction of pertinent feature information from graphics and images, we achieve the scientific encoding of coefficient-constrained features and determine the corresponding hyperplanes to acquire the relevant parameters for visual communication. Eventually, the implementation of advanced design image expression algorithms markedly enhances the effectiveness of visual communication image representation. The empirical findings reveal that these visual communication design methods exhibit remarkable reliability and feasibility, effectively boosting image recognition accuracy across four distinct image categories with varying levels of complexity, thereby yielding exceptional visual communication outcomes. © 2025 SPIE.

关键词： Design Visual communications Visualization computer graphics Image processing Image storage Color Image segmentation Image enhancement

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Differential Protection for Distribution Grids Based on Dual Compressed Sensing theory

Differential Protection for Distribution Grids Based on Dual...

引用

2024 international conference Optoelectronic Information and Optical engineering, OIOE 2024

作者： Duan, Yahui Wu, Tonghua Chen, Wei Dai, Wei Cao, Yuhan Cao, Wenjun School of China EU Institute for Clean and Renewable Energy Huazhong University of Science and Technology Wuhan430074 China The State Key Laboratory of Technology and Equipment for Defense against Power System Operational Risks Nari Technology Co. Ltd. Jiangsu211106 China The State Key Laboratory of Advanced Electromagnetic Technology Huazhong University of Science and Technology Wuhan430074 China State Grid Hebei Electronic Power Research Institute Hebei250002 China State Grid Shandong Electronic Power Research Institute Shandong050011 China

ISBN: (数字)9781510688209

ISBN: (纸本)9781510688193

With the increasing integration of distributed renewable energy sources into distribution networks, the characteristics of fault currents in distribution networks have undergone significant changes. Traditional three-stage current protection is no longer sufficient to meet the protection requirements. In theory, a differential protection scheme can better fulfill the requirements of rapid and accurate fault detection and clearance in distribution networks. Differential protection relies on real-time communication for information exchange between devices, and many researchers have incorporated wireless networks such as 5G into distribution network differential protection. Given the exponential growth of data in distribution networks and the security considerations of wireless communication like 5G, this paper proposes a secure protection technique for distribution network differential protection based on dual compressed sensing theory. This technique employs two compressed sensing schemes to compress the data before transmission, reducing the amount of data transferred while enhancing security. Subsequently, secure determinations are made based on the data at both ends processed through the compressed sensing algorithm, ensuring the security of communication in distribution network differential protection while achieving the same level of protection performance as traditional differential protection schemes. © 2025 SPIE.

关键词： Compressed sensing Data transmission Matrices Data communications Wireless communications Network security Reconstruction algorithms computer security Signal processing Signal to noise ratio

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Enhancing Malicious URL Detection with advanced Machine Learning Techniques 1

Enhancing Malicious URL Detection with Advanced Machine Lear...

引用

1st international conference on Advances in computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Alavala, Hemanth Reddy Singh, Shambhavi Joshi, Priyam Basavaraju, Sagar Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798331518578

Malicious URLs pose a significant threat to online security. The can steal our personal information and can even hack out system. Refraining ourselves from using such malicious websites is the need of the hour. This paper presents a comprehensive evaluation of various machine learning algorithms which are used to effectively detect and mitigate these threats. This research explores the performance of traditional machine learning techniques including Random Forests, Decision Trees, Logistic Regression, Support Vector Machines, as well as advanced techniques like XGBoost, LightGBM, and CatBoost while the previous works focused on only traditional classification techniques. Additionally, this work investigates the potential of deep learning models, including LSTM and CNN, to capture intricate patterns within URL sequences. Machine learning algorithms are evaluated using the evaluations metrics including Accuracy, Recall, Precision and F1 score. Experimental Results and analysis have shown that advanced models outperform traditional classification techniques. These results valuable insights into the most effective approaches for safeguarding online users from malicious attacks. © 2025 IEEE.

关键词： Phishing

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Application of computer vision technology in interactive teaching tools

Application of computer vision technology in interactive tea...

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2024 international conference on Physics, Photonics, and Optical engineering, ICPPOE 2024

作者： Zhang, Suping Guangzhou Huashang Vocational College Guangzhou511300 China

ISBN: (数字)9781510689121

ISBN: (纸本)9781510689114

As the digital age progresses, the intersection of computer vision technology and education is drawing significant attention, enabling the development of interactive teaching tools that redefine how knowledge is imparted. While these tools promise to enhance the educational experience through increased engagement and personalized learning pathways, a critical enabling component is the ability to swiftly and reliably detect and interpret educational content and student interactions. This paper puts forth an improved object detection paradigm within this context using an advanced YOLO (You Only Look Once) algorithm modified for the unique requirements of interactive educational environments. We introduce a secondary feature fusion technique within the YOLO framework to enhance detection accuracy—key to maintaining the flow and interactivity of the educational experience. The innovative approach includes lightweight separable convolutions replacing traditional convolution modules to minimize network load and an enrichment of the DarkNet-53 backbone with dense connections for better feature propagation. In addition, we implement a dual-stage feature fusion strategy that consolidates the strengths of different network layers to ensure comprehensive feature extraction. Our proposed enhanced YOLO algorithm addresses the persisting challenge of precision in object detection to effectively facilitate the deployment of computer vision in interactive teaching, propelling the education sector towards a more engaging and sophisticated future. © 2025 SPIE.

关键词： computer vision

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Robust Rice Leaf Disease Detection using advanced Preprocessing and Deep CNNs for Class Imbalance Resolution 1

Robust Rice Leaf Disease Detection using Advanced Preprocess...

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1st international conference on Intelligent Systems and Computational Networks, ICISCN 2025

作者： Poorani, S. Singh, Komal Priya Stella Mary, I. Brinda, P. Srimathi, S. Jegajothi, B. Kongu Engineering College Department of Computer Technology Perundurai Erode India Babasaheb Bhimrao Ambedkar University Lucknow India Christ University Department of Computer Science Yeshwanthpur Campus Bangalore India Veltech Hightech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Computer Science and Engineering Avadi Chennai India Saveetha School of Engineering Simats Department of Bio Technology Chennai India Srs Tech Solutions Chennai India

ISBN: (纸本)9798331529246

This study addresses the growing challenges posed by plant diseases, particularly in the rice industry, which is vital for many communities. The research propose a robust framework that integrates Deep Convolutional Neural Networks (Deep CNN) with advanced preprocessing techniques to identify rice leaf diseases, including Brown Spot, Leaf Blast, Hispa, and healthy leaves. Our approach employs normalization to enhance convergence during training and data augmentation to improve model generalizability. Additionally, implement the Synthetic Minority Over-sampling Technique (SMOTE) to create synthetic samples for under-represented classes, addressing class imbalance within the dataset. Experimental results demonstrate the model's impressive accuracy, achieving 98.2% for Brown Spot, 97.5% for Leaf Blast, 94.3% for Hispa, and 96.8% for healthy leaves. Furthermore, our method outperforms established CNN architectures such as AlexNet, VGG16, and ResNet50, showcasing the effectiveness of sophisticated preprocessing in enhancing plant disease detection systems and supporting food security initiatives. © 2025 IEEE.

关键词： Convolutional neural networks

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