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2nd International Conference on Advanced Research in Computing, ICARC 2022

作者： Panagoda, Mithila Lokuliyanage, Minuli Senarath, Amadi Nisansala, N.K.V.M. Nethmini Rajapakshe, R.W.A.D.U. Rajapaksha, U.U. Samantha Jayawardena, Chandimal Sri Lanka Institute of Information Technology Dept. of Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Deprt. of Computer System and Engineering Malabe Sri Lanka

ISBN: (纸本)9781665407410

The purpose of this research paper is to introduce a new navigation algorithm for Robot Operating system (ROS) based robots which will allow complete autonomous traversal in any given indoor environment. Turtle bot3 burger bot is the sample robot chosen for this project. This will be equipped with a Light Detection and Ranging (LIDAR) scanner with the default settings, ultrasound, Intel Real Sense camera, etc. Environment information gathered via these sensors will be sent into a remote computer for processing since the raspberry pie micro-controller with the turtle bot burger is not enough to carry out a high computation-intensive task. Once the information is received series of tasks will be carried out by the remote personal computer before executing the newly developed navigation algorithm. The data from the LIDAR scanner help to generate a 2-dimensional(2D) potential field graph. Then it will later be used for path planning by navigation algorithm. Furthermore, the Real sense camera is used for object boundary detection to produce more accurate data for the navigation algorithm. Once all the data proceed, data will return to the robot, where the navigation algorithm will start execution in parallel with a recovery behavior algorithm and scan algorithm. The recovery behavior algorithm is responsible for guiding the robot to face away from an obstacle in an event where the predetermined path is obstructed. Furthermore, it is responsible for maintaining accurate data in the cost map. Subsequently, the scanning algorithm will be used to generate maps. © 2022 IEEE.

关键词： Cameras

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A model of service-oriented architecture of e-certification system to support boat registration and site visit inspection to support maritime safety and crew health inspection

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Marine systems and Ocean technology 2023年第1-2期18卷 45-63页

作者： Saputra, Diaz Gaol, Ford Lumban Abdurachman, Edi Sensuse, Dana Indra Matsuo, Tokuro Department of Computer Science BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Department of Computer Science Binus Graduate Program - Master in Information System Bina Nusantara University Jakarta11480 Indonesia Department of Research in Management Bina Nusantara University Jakarta Indonesia Faculty of Computer Science University of Indonesia Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan City University of Macau China Asia University Taichung Taiwan

This article describes the architecture of software services that provide registration of small boat data to build maritime safety. The proposed system architecture which so-called SIMKAPEL aims to support small boat registration for maritime safety. It is developed from a conventional service-oriented architecture (SOA) with an open standard for data interoperability between elements. The goal of this research is to implement and evaluate the proposed architecture to support small boat registration and e-certification. Several parts of the architecture have been implemented as a platform that provides core services and data sources to be used by Ministry of Transportation, Directorate General of Sea Transportation, and other government agencies. Finally, the proposed SIMKAPEL platform with the SOA architecture is evaluated for its benefits to users through the expert opinion survey to measure its efficiency. The analysis results showed that SOA-based SIMKAPEL is feasible to use as a boat e-certification system. Furthermore, experiment results provide three parameters (e.g., maritime safety, namely, cargo/passengers, boat safety facilities, and maritime safety systems) with efficiency values of 42%, 46%, and 42%, respectively. The parameter with the highest efficiency shows a big effect on the level of safety of the boat and passengers. Thus, the parameters that need to be prioritized and need boat owners’ attention are cargo/passenger, boat safety equipment, and maritime safety system. © 2023, The Author(s).

关键词： Boat e-certification Boat online certification Cloud-based service Integrated system SOA architecture

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IntelliCross: Adaptive Pedestrian Crossing system

IntelliCross: Adaptive Pedestrian Crossing System

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Advanced Research in Computing (ICARC), International Conference on

作者： Udayanga Dissanayake Dinusha Weerasekara Hansika Sumanasekara Dodamgoda Ishara Pipuni Wijesiri Menaka Moonamaldeniya Department of Information Technology Sri Lanka Institute of Information Technology Sri Lanka Department of Computer System Engineering Sri Lanka Institute of Information Technology Sri Lanka Department of Computing Sri Lanka Institute of Information Technology Kandy Uni Sri Lanka

ISBN: (数字)9798331530983

ISBN: (纸本)9798331530990

Urban traffic management at pedestrian crossings presents considerable issues, such as pedestrian safety, congestion, and effective prioritizing of emergency vehicles. Traditional traffic signal systems are frequently static, unable to respond to real-time changes in pedestrian flow, vehicle density, and environmental variables. To overcome these issues, an IoT-based adaptive pedestrian crossing system, "IntelliCross," is presented. The system detects emergency vehicle sirens using sound sensors and automatically adjusts pedestrian signals to green to prioritize emergency vehicle passage, resulting in faster response times and shorter delays. Furthermore, machine learning algorithms alter signal timings based on real-time pedestrian counts and vehicle density, assuring smooth traffic flow and pedestrian safety. Vulnerable pedestrians, such as the elderly and disabled, are accommodated by dynamically extending green light durations to ensure safe crossing. The technology also includes real-time meteorological data, such as rain, to extend green light durations and improve pedestrian safety. IntelliCross, by combining IoT sensors with machine learning, offers a scalable and cost-effective solution for improving urban traffic management, closing crucial gaps in present systems, and contributing to the development of smart cities. Public surveys demonstrate considerable support for systems that prioritize emergency vehicles while also assuring pedestrian safety, proving the system's ability to revolutionize urban traffic infrastructure.

关键词： Pedestrians Adaptive systems Rain Smart cities Green products Real-time systems Sensor systems Safety Vehicle dynamics Meteorology

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Improved Demonstration-Knowledge Utilization in Reinforcement Learning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2139-2150页

作者： Liu, Yanyu Zeng, Yifeng Ma, Biyang Pan, Yinghui Gao, Huifan Zhang, Yuting Xiamen University Xiamen Key Laboratory of Big Data Intelligent Analysis and Decision Department of Automation Xiamen361102 China Northumbria University Department of Computer and Information Sciences NewcastleNE1 8ST United Kingdom Minnan Normal University Department of Computer Science Zhangzhou363000 China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China

Reinforcement learning (RL) has made great success in recent years. Generally, the learning process requires a huge amount of interaction with the environment before an agent can achieve acceptable performance. This motivates many techniques, such as incorporating prior knowledge which is usually presented as experts' demonstration, and using a probability distribution to represent state-and-action values, to accelerate the learning process. The methods perform well when the prior knowledge is genuinely correct and no much change occurs to the learning environment. However, the requirement is not perfectly realistic in many complex applications. The demonstration knowledge may not reflect the true environment and even be full of noise. In this article, we introduce a dynamic distribution merging method to improve knowledge utilization in a general RL algorithm, namely Q-learning. The new method adapts a normal distribution to represent state-action values and merges the prior and learned knowledge in a discriminative way. We theoretically analyze the new learning method and demonstrate its empirical performance over multiple problem domains. © 2020 IEEE.

关键词： Merging

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Improved Metaheuristics with Deep Learning Enabled Movie Review Sentiment Analysis

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computer systems Science & Engineering 2023年第10期47卷 1249-1266页

作者： Abdelwahed Motwakel Najm Alotaibi Eatedal Alabdulkreem Hussain Alshahrani MohamedAhmed Elfaki Mohamed K Nour Radwa Marzouk Mahmoud Othman Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Prince Saud AlFaisal Institute for Diplomatic Studies RiyadhSaudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

Sentiment Analysis(SA)of natural language text is not only a challenging process but also gains significance in various Natural Language Processing(NLP)*** SA is utilized in various applications,namely,education,to improve the learning and teaching processes,marketing strategies,customer trend predictions,and the stock *** researchers have applied lexicon-related approaches,Machine Learning(ML)techniques and so on to conduct the SA for multiple languages,for instance,English and *** to the increased popularity of the Deep Learning models,the current study used diverse configuration settings of the Convolution Neural Network(CNN)model and conducted SA for Hindi movie *** current study introduces an Effective Improved Metaheuristics with Deep Learning(DL)-Enabled Sentiment Analysis for Movie Reviews(IMDLSA-MR)*** presented IMDLSA-MR technique initially applies different levels of pre-processing to convert the input data into a compatible ***,the Term Frequency-Inverse Document Frequency(TF-IDF)model is exploited to generate the word vectors from the pre-processed *** Deep Belief Network(DBN)model is utilized to analyse and classify the ***,the improved Jellyfish Search Optimization(IJSO)algorithm is utilized for optimal fine-tuning of the hyperparameters related to the DBN model,which shows the novelty of the *** experimental analyses were conducted to validate the better performance of the proposed IMDLSA-MR *** comparative study outcomes highlighted the enhanced performance of the proposed IMDLSA-MR model over recent DL models with a maximum accuracy of 98.92%.

关键词： Corpus linguistics sentiment analysis natural language processing deep learning word embedding

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Development of a Dempster-Shafer Model for Diagnosing Mental Health Disorders on Social Media

Development of a Dempster-Shafer Model for Diagnosing Mental...

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International Seminar on Research of information technology and Intelligent systems (ISRITI)

作者： Ayahri Hadi Nasyuha Ananda Hadi Ilyas Widyastuti Andriyani Aloysius Agus Subagyo Dept. of Information System Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Dept. of Information System Faculty Of Engineering And Computer Science Universitas Dharmawangsa Medan Indonesia Dept. of Master of Information Technology Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Dept. of Accounting Information System Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

The rapid proliferation of social media has been paralleled by an increase in mental health concerns, often reflected in users' online behaviors and text posts. Traditional methods for diagnosing mental health disorders do not effectively leverage this vast amount of data, nor do they address the ambiguities and uncertainties inherent in natural language processing of social media content. A novel diagnostic model based on the Dempster-Shafer evidence theory is developed specifically for analyzing social media text. The model aims to enhance the precision of mental health disorder diagnoses by incorporating probabilistic reasoning and handling uncertainty in the data more effectively than traditional binary classification methods. It integrates linguistic cues, sentiment analysis, and behavioral indicators extracted from user posts to assess the likelihood of various mental health conditions. We collected a dataset comprising social media posts tagged with mental health keywords, verified by clinical annotations. The Dempster-Shafer model was trained with features derived from text analytics, including sentiment scores, thematic elements, and engagement metrics. The model’s performance was evaluated against standard classification models through metrics such as accuracy, sensitivity, and specificity. The Dempster-Shafer model demonstrated superior capability in handling the uncertainty and imprecision of social media data, showing an improvement in diagnostic accuracy by 15% over traditional models. The findings suggest that applying Dempster-Shafer theory in mental health diagnostics can effectively utilize the nuanced and sparse data available on social media, offering a promising tool for early identification and intervention in mental health issues.

关键词： Measurement Seminars Analytical models Sentiment analysis Accuracy Social networking (online) Mental health Sensitivity and specificity Data models Standards

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Detecting and Mitigating Distributed Denial of Service Attacks in Software-Defined Networking

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computers, Materials & Continua 2025年第6期83卷 4515-4535页

作者： Abdullah M.Alnajim Faisal Mohammed Alotaibi Sheroz Khan Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia College of Computer Engineering and Sciences Department of information systemPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Electrical Engineering College of Engineering and Information TechnologyOnaizah CollegesQassim56447Saudi Arabia

Distributed denial of service(DDoS)attacks are common network attacks that primarily target Internet of Things(IoT)*** are critical for emerging wireless services,especially for applications with limited *** attacks pose significant risks to entrepreneurial businesses,preventing legitimate customers from accessing their *** attacks require intelligent analytics before processing service *** denial of service(DDoS)attacks exploit vulnerabilities in IoT devices by launchingmulti-point distributed *** attacks generate massive traffic that overwhelms the victim’s network,disrupting normal *** consequences of distributed denial of service(DDoS)attacks are typically more severe in software-defined networks(SDNs)than in traditional *** centralised architecture of these networks can exacerbate existing vulnerabilities,as these weaknesses may not be effectively addressed in this *** preliminary objective for detecting and mitigating distributed denial of service(DDoS)attacks in software-defined networks(SDN)is to monitor traffic patterns and identify anomalies that indicate distributed denial of service(DDoS)*** implements measures to counter the effects ofDDoS attacks,and ensure network reliability and availability by leveraging the flexibility and programmability of SDN to adaptively respond to *** authors present a mechanism that leverages the OpenFlow and sFlow protocols to counter the threats posed by DDoS *** results indicate that the proposed model effectively mitigates the negative effects of DDoS attacks in an SDN environment.

关键词： Software-defined networking(SDN) distributed denial of service(DDoS)attack sampling Flow(sFlow) OpenFlow OpenDaylight controller

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Planning Software Release and Testing Stop Time under Budgetary and Reliability Constraints 18

Planning Software Release and Testing Stop Time under Budget...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Singh, Veenu Kumar, Vijay Singh, V.B. Amity University Amity Institute of Information Technology Uttar Pradesh Noida India Amity University Aias Department of Applied Mathematics Uttar Pradesh Noida India Jawaharlal Nehru University School of Computer and System Sciences New Delhi India

ISBN: (纸本)9789380544519

To thrive in the competitive market, organizations are opting to release their products early, followed by an ongoing testing process to eliminate any remaining bugs through the delivery of patches. Software patches refer to small programs introduced to the users to rectify faults, introduce new features, or enhance existing functionality. After going through the literature, it is observed that researchers have worked on testing-effort based SRGM, but none have addressed the aspect of reliability and cost in the context of determining the optimal time for software release and optimal time to stop software testing while patching is considered. To bridge this gap, we have introduced a testing effort based SRGM implementing patching, with the objective of making the software cost-effective and reliable. The numerical illustration has been done using Statistical Package for Social Sciences. and Genetic Algorithm (GA). © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Generalized Modified Weibull (GMW) Genetic Algorithm (GA) Reliability Software Reliability Growth Model (SRGM) Statistical Package for Social Sciences (SPSS) Testing Cost

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Source-free Domain Adaptation with Multiple Alignment for Efficient Image Retrieval

Source-free Domain Adaptation with Multiple Alignment for Ef...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Ni, Jinghui Cui, Hui Zhao, Lihai Li, Fengling Han, Xiaohui Xu, Lijuan Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology Shandong Academy of Sciences China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science China Quan Cheng Laboratory China Shandong Open University China University of Technology Sydney Australia

ISBN: (纸本)9798350368741

Domain adaptation techniques help models generalize to target domains by addressing domain discrepancies between the source and target domain data distributions. These techniques are particularly valuable for cross-domain hashing retrieval, as they reduce training costs while maintaining high retrieval efficiency. However, existing unsupervised domain adaptative hashing methods often require access to both source and target domain data, which may raise privacy concerns regarding source domain data. To address these concerns, restricting access to source domain data is crucial, but this restriction also makes the alignment process between domains more challenging. In this paper, we propose a Source-free Domain Adaptive Hashing with Multiple Alignment (SFDAH-MA) approach for image retrieval. SFDAH-MA integrates model structure alignment, class moment alignment, and semantic relationship alignment to maximize inter-domain knowledge transfer. This comprehensive alignment strategy not only enhances retrieval performance across domains but also minimizes reliance on source domain data, thereby supporting data privacy protection. Extensive experiments show that SFDAH-MA achieves state-of-the-art performance in source-free settings and achieves comparable results to existing unsupervised domain adaptive hashing methods under conventional settings. The source codes of our method are available at: https://***/Nikphyc/SFDAH-MA. © 2025 IEEE.

关键词： Deep hashing image retrieval source-free domain adaptation

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Geometric behavior of the generalized Hadid-Luchko convolution operator in the open unit ball

Geometric behavior of the generalized Hadid-Luchko convoluti...

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2023 International Conference on Fractional Differentiation and Its Applications, ICFDA 2023

作者： Hadid, Samir B. Ibrahim, Rabha W. Obaiys, Suzan J. Nadia M. G, Al-Saidi Ajman University Department of Mathematics and Sciences College of Humanities and Sciences Ajman United Arab Emirates Ajman United Arab Emirates Lebanese American University Department of Computer Science and Mathematics Beirut Lebanon University of Malaya Faculty of Computer Science and Information Technology Department of Computer System & Technology Kuala Lumpur Malaysia University of Technology Department of Applied Sciences Iraq

ISBN: (纸本)9798350321685

In this effort, by consuming the k-symbol calculus, we generalize the Hdid-Luchko function (the Mittag-Leffler function of several variables). Some inequalities are established containing the normalized type of this function. In addition, we illustrate a list of conditions on the function to recognize some special geometric properties in a unit ball. Our theory is based on the differential subordination of several variables. © 2023 IEEE.

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