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5th International Conference on Advanced Research in Computing, ICARC 2025

作者： Kariyawasam, K.P.W.D.V. Kahandagamage, P.N. Fernando, M.R.R. Fernandopulle, J.M. Jayasinghearachchi, Vishan Dissanayaka, Kapila Dept. of Software Engineering Sri Lanka Dept. of Information Technology Sri Lanka Dept. of Computer Science Sri Lanka

ISBN: (纸本)9798331530983

In recent years, the Sri Lankan tea industry has fallen behind its competitors in the global tea market. This decline is caused by the challenges in productivity and resource management due to the limitations of traditional crop monitoring methods. This study presents a prototype system architecture that integrates multispectral imagery and IoT technologies to enhance plantation monitoring. The proposed system uses drones to capture high-resolution multispectral images and IoT devices to collect real-time environmental data, providing a comprehensive approach to assessing plant yield and detecting stress. Built on a hexagonal architecture, the system emphasizes modularity, reliability, and scalability by ensuring a clear separation of core functionalities from external components. This design facilitates easy adaptation to various crop types and agricultural contexts, enabling flexibility in deployment and use. This flexible framework can serve as a blueprint for improving decision-making and management practices across diverse plantation environments. © 2025 IEEE.

关键词： Risk perception

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Heuristic approaches for hiding sensitive frequent itemsets in uncertain databases 5

Heuristic approaches for hiding sensitive frequent itemsets ...

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5th International Conference on Pattern Analysis and Intelligent systems, PAIS 2023

作者： Lefkir, Mira Nouioua, Farid Fournier-Viger, Phillipe University Mohamed El Bachir El Ibrahimi of Bordj Bou Arreridj BBA Dept. of Computer Science Algeria Shenzhen University College of Computer Science and Software Engineering Shenzhen China

ISBN: (纸本)9798350381450

Pattern mining is a core objective within data mining, involving the detection of frequent itemsets (collections of values) within databases. This process serves to extract valuable insights from the data, facilitating informed decision-making. In recent times, a range of algorithms has emerged to adapt this task to the realm of uncertain *** has a wide range of applications, such as analyzing medical data to identify correlated symptoms based on their existential probabilities. However, pattern mining algorithms also pose the risk of revealing sensitive information. As far as we know, there is no existing solution that addresses the inadvertent disclosure of sensitive itemsets when pattern mining algorithms are employed on uncertain databases. This paper addresses this problem by proposing three heuristic approaches, which ensure that sensitive expected frequent itemsets are not discovered while minimizing undesirable side effects for other itemsets. The first heuristic approach (called aggregate) deletes some transactions from an uncertain database. The second approach (named disaggregate) removes some selected items from each transaction. And the third approach (called the hybrid approach) combines the two previous approaches, and deletes some selected items from some selected transactions. An experimental evaluation is presented to assess and compare the effectiveness of the three approaches. © 2023 IEEE.

关键词： Data mining

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INDUSTRIAL METAVERSE IN SUPPLY CHAIN MANAGEMENT: APPLICATIONS, CONCEPTS, AND OPEN RESEARCH PATHS

INDUSTRIAL METAVERSE IN SUPPLY CHAIN MANAGEMENT: APPLICATION...

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2024 Winter Simulation Conference, WSC 2024

作者： van der Valk, Hendrik Kunert, Julia Harke, Niklas Langenbach, Katharina TU Dortmund University NRW Dortmund Germany Fraunhofer Institute for Software and Systems Engineering ISST NRW Dortmund Germany Dept. of IT in Production and Logistics TU Dortmund University NRW Dortmund Germany

ISBN: (纸本)9798331534202

This research study examines the applications of the industrial metaverse in supply chain management. Thus, it reviews and analyzes the up-to-date knowledge along the Supply Chain Operations Reference Model. Therefore, a structured literature review is conducted. We derive six core functionalities of the industrial metaverse in supply chains: visibility and monitoring, prediction, simulation, collaboration, training, and optimization. Furthermore, their presence along the different phases of a supply chain is investigated. Besides the functionalities, the relationship between the industrial metaverse and simulation applications and digital twins is analyzed, and a brief description of possible metaverse architectures is provided. This study additionally derives research gaps within the emerging field of metaverse applications and research and defines paths to tackle them. © 2024 IEEE.

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MSMA: Multi-Agent Trajectory Prediction in Connected and Autonomous Vehicle Environment with Multi-Source Data Integration 24

MSMA: Multi-Agent Trajectory Prediction in Connected and Aut...

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24th COTA International Conference of Transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024

作者： Chen, Xi Bhadani, Rahul Sun, Zhanbo Head, Larry Dept. of Systems and Industrial Engineering Univ. of Arizona TucsonAZ United States Dept. of Electrical and Computer Engineering Univ. of Alabama in Huntsville HuntsvilleAL United States School of Transportation and Logistics Southwest Jiaotong Univ. Chengdu China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

The prediction of surrounding vehicle trajectories is crucial for collision-free path planning. In this study, we focus on a scenario where a connected and autonomous vehicle (CAV) serves as the central agent, utilizing both sensors and communication technologies to perceive its surrounding traffics consisting of autonomous vehicles (AVs), connected vehicles (CVs), and human-driven vehicles (HDVs). Our trajectory prediction task is aimed at all the detected surrounding vehicles. To effectively integrate the multi-source data from both sensor and communication technologies, we propose a deep learning framework called MSMA utilizing a cross-attention module for multi-source data fusion. Vector map data is utilized to provide contextual information. The trajectory data set is collected in CARLA simulator with synthesized data errors introduced. Numerical experiments demonstrate that in a mixed traffic flow scenario, the integration of data from different sources enhances our understanding of the environment. This notably improves trajectory prediction accuracy, particularly in situations with a high CV market penetration rate. © ASCE.

关键词： Data fusion

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A Study of software Health Management in Unmanned Aerial Vehicle systems 2

A Study of Software Health Management in Unmanned Aerial Veh...

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2nd International Workshop on Intelligent software engineering, ISE 2023

作者： Park, Jinseok Choi, Eu-Teum Lee, Seongjin Dept. of Aerospace Software Engineering Gyeongsang National University Jinju Korea Republic of Convergence Research Center for Materials and Mechanical Systems Jinju Korea Republic of Dept. of AI Convergence Engineering Gyeongsang National University Jinju Korea Republic of

Unmanned Aerial Vehicles (UAVs) must operate their installed software without errors to complete their mission. software faults cause errors in the software. Most of them are removed through the Verification and Validation process in the development phase. However, developers and testers cannot eliminate all faults due to the inability to account for all uncertain environments and conditions. System health management is the technology that helps UAVs successfully perform missions by mitigating errors during operation. However, there are errors that the existing UAV System Health Management cannot diagnose because errors are not deterministic nor explicit. This paper analyzes two UAV systems, PX4 and Ardupilot, to categorize software errors. It also assesses whether the existing UAV System Health Management can diagnose these errors. Our study can help developers and researchers better understand the characteristics of software errors in UAV systems and set the direction for future work in UAV software health management. © 2023 Copyright for this paper by its authors.

关键词： Errors

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Classification of Skin Lesions using Squeeze and Excitation Attention based Hybrid Model of DenseNet and EfficientNet

Classification of Skin Lesions using Squeeze and Excitation ...

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Decision Aid Sciences and Application (DASA), International Conference on

作者： Senanur Armağan Esra Gündoğan Mehmet Kaya Dept. of Computer Engineering Firat University Elaziğ Turkey Dept. of Software Engineering Firat University Elaziğ Turkey

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

Skin cancer, like all other types of cancer, is a health problem where early diagnosis saves the patient's life. Successful detection of skin lesions in dermoscopic images enables this process to be managed more quickly. Deep learning architectures have advanced significantly in recent years, particularly in the classification of medical images. For the multi-class classification of skin lesions, a hybrid model was developed in this study utilizing the convolutional neural network architectures of DenseNet and EfficientNet. In addition, SE (Squeeze and Excitation) attention mechanism is integrated into both models. Experimental results show that the inclusion of SE attention mechanism provides a noticeable improvement in classification accuracy. This study not only contributes to the development of effective skin lesion classification systems, but also It also provides valuable insights into the synergistic effects of combining neural network architectures with attention mechanisms.

关键词： Deep learning Training Visualization Attention mechanisms Accuracy Skin Data models Lesions Convolutional neural networks Skin cancer

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Academic Use of ChatGPT: Examining the Trends According to Disciplines

Academic Use of ChatGPT: Examining the Trends According to D...

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International Artificial Intelligence and Data Processing Symposium (IDAP)

作者： Abdullah Bircan Dilek Mandal İrfan Kösesoy Dept. of Computer Engineering Kocaeli University Kocaeli Turkey Dept. of Software Engineering Kocaeli University Kocaeli Turkey

ISBN: (数字)9798331531492

ISBN: (纸本)9798331531508

With the rapid advancement of large language models, particularly ChatGPT, have had a profound impact both in the academic world and in commercial applications. The innovative solutions offered by this technology in areas such as natural language processing, data analysis, and human-computer interaction have led to the emergence of new research domains across various disciplines. However, there has been no comprehensive examination in the literature of which academic disciplines focus on ChatGPT and which areas have attracted more *** study aims to systematically examine academic publications related to ChatGPT and to identify the disciplines in which this technology is more widely adopted, as well as the areas where intensive research is conducted. To this end, a specially developed tool was utilized to scan all academic publications pertaining to ChatGPT, allowing for a comprehensive interdisciplinary analysis. The results of the analysis reveal the academic fields in which ChatGPT is most intensively utilized, highlighting the differences among these fields. Notably, there is a concentration in categories such as “Medical Sciences,” “computer Sciences,” and “Education Sciences,” which also stand out among the most cited publications. Our findings indicate that ChatGPT has gained broad acceptance within the academic community, with certain disciplines leading the way in this regard. Furthermore, the interactions among categories sharing common keywords demonstrate how ChatGPT facilitates interdisciplinary knowledge flow.

关键词： Data analysis Large language models Chatbots Market research Data models

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ATL Model Checking for Analysis of Ethereum Smart Contracts

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Transactions of the Korean Institute of Electrical Engineers 2021年第12期70卷 2006-2014页

作者： Nam, Wonhong Kil, Hyunyoung Dept. of Software Korea Aerospace University Korea Republic of Dept. of Computer Science and Engineering Konkuk University Korea Republic of

A blockchain is a growing list of cryptographically secured blocks to maintain shared data on decentralized systems, in order to archive transactions between untrusted participants. Smart contracts are computer programs that automatically execute legal events according to the terms of contracts. Although the Ethereum blockchain has been successfully applied to a number of interesting applications, there have been several events that subtle flaws in smart contracts induce a huge amount of financial loss such as the DAO attack. Accordingly, to analyze smart contracts, we propose a novel formal verification technique to employ ATL (Alternating-time Temporal Logic) model checking. Our methodology represents the interaction between users and smart contracts with a two-player game and verify game properties by using MCMAS that is an efficient ATL model checker. © The Korean Institute of Electrical Engineers

关键词： Smart contract

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Defensive Reflexes of Drones

Defensive Reflexes of Drones

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International Conference on computer Theory and Applications (ICCTA)

作者： Adnan Akpınar Ensar Gul Dept. of Computer Engineering Maltepe University Istanbul Turkiye Dept. of Software Engineering Maltepe University Istanbul Turkiye

ISBN: (数字)9798331529680

ISBN: (纸本)9798331529697

Object detection is an image processing method that aims to detect the object from the images taken through cameras. In this context, it has become possible for drones to detect an object and predict the object’s distinctive features. In this study, object detection and classification methods were employed to enable drones to develop a defense mechanism by making a distinction between threatening and non-threatening objects approaching them, thereby autonomously protecting themselves, independently of the pilot, against potentially threatening objects.

关键词： Object detection Machine learning Feature extraction Cameras computer security Drones

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Online Complaint Management System using Image Recognition 8

Online Complaint Management System using Image Recognition

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8th International Conference on Communication and Electronics systems, ICCES 2023

作者： Balakrishnan, S. Janet, J. Rohith, T. Sakthivel, R. Sanjaiy Kumar, T.N. Sri Krishna College of Engg. and Technology Dept. of Computer Science and Business Systems Tamilnadu Coimbatore India Sri Krishna College of Engg. and Technology Dept. of Computer Science and Engineering Tamilnadu Coimbatore India

ISBN: (纸本)9798350396638

Clean and safe environments are the responsibility of the government. Currently, people have to lodge their complaints with the Municipal Corporation, and then workers take time to respond to them. In this paper we have made a platform to overcome the communication gap between the user and the municipal corporation. This research study proposes an online complaint management system in a web application, where the citizen can lodge a complaint by taking a picture. After the picture being uploaded, image recognition is used to automatically detect the problem raised by the user and Google map API to detect the location automatically. As soon as the problem has been resolved, the municipal corporation must upload a completed status picture to verify that the work has been completed. The aim of this application is to overcome the communication gap between user and Municipal Corporation, to simplify the process of raising complaints and to maintain a clean and safe environment. © 2023 IEEE.

关键词： Image recognition

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