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24th Pan-Hellenic Conference on Informatics, PCI 2020

作者： Ballas, Ioannis Tsakanikas, Vassilios Pefanis, Evaggelos Tampakas, Vassilios Distributed Intelligent Systems and Data Lab Department of Electrical and Computer Engineering University of Peloponnese Greece

ISBN: (纸本)9781450388979

Big Data paradigm has placed pressure on well-established relational databases during the last decade. Both academia and industry have proposed several alternative database schemes in order to model the captured data more efficiently. Among these approaches, graph databases seem the most promising candidate to supplement relational schemes. Within this study, a comparison is performed among Neo4j, one of the leading graph databases, and Apache Spark, a unified engine for distributed large-scale data processing environment, in terms of processing limits. The results reveal that Neo4j is limited to the physical RAM memory of the processing environment. Yet, until this limit is reached, the processing engine of Neo4j outperforms the Apache Spark engine. © 2020 ACM.

关键词： Graph Databases

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An Ensemble Machine Learning Technique for Stroke Prognosis

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computer systems Science & engineering 2023年第10期47卷 413-429页

作者： Mesfer Al Duhayyim Sidra Abbas Abdullah Al Hejaili Natalia Kryvinska Ahmad Almadhor Uzma Ghulam Mohammad Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz University Al-Kharj16273Saudi Arabia Department of Computer Science COMSATS UniversityIslamabad53000Pakistan Computer Science Department Faculty of Computers&Information TechnologyUniversity of TabukTabuk71491Saudi Arabia Information Systems Department Faculty of ManagementComenius University in BratislavaOdbojárovBratislava440Slovakia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakaka72388Saudi Arabia Department of Computer Science and Software Engineering International Islamic UniversityIslamabad44000Pakistan

Stroke is a life-threatening disease usually due to blockage of blood or insufficient blood flow to the *** has a tremendous impact on every aspect of life since it is the leading global factor of disability and *** can range from minor to severe(extensive).Thus,early stroke assessment and treatment can enhance survival *** prediction is extremely time and resource *** prediction methods such as Modern Information and Communication Technologies(ICTs),particularly those inMachine Learning(ML)area,are crucial for the early diagnosis and prognosis of ***,this research proposed an ensemble voting model based on three Machine Learning(ML)algorithms:Random Forest(RF),Extreme Gradient Boosting(XGBoost),and Light Gradient Boosting Machine(LGBM).We apply data preprocessing to manage the outliers and useless instances in the ***,to address the problem of imbalanced data,we enhance the minority class’s representation using the Synthetic Minority Over-Sampling Technique(SMOTE),allowing it to engage in the learning process *** reveal that the suggested model outperforms existing studies and other classifiers with 0.96%accuracy,0.97%precision,0.97%recall,and 0.96%*** experiment demonstrates that the proposed ensemble voting model outperforms state-of-the-art and other traditional approaches.

关键词： Stroke prediction machine learning ensemble model data analysis Synthetic Minority Over-Sampling

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Data-driven Online Decision Support for Hotel Site Selection 9

Data-driven Online Decision Support for Hotel Site Selection

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9th Edition of IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2021

作者： Kumarage, Imal Weerakeshara, Nuwanga Chamika, Thanuja Rathnapala, Heshan Nawinna, Dasuni Gamage, Narmada Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9781665432405

Location is one of the fundamental factors that determine hotel success. The location, once selected, cannot be changed without a significant investment. This research aims to identify the location-specific factors that affect Sri Lankan coastal hotels. The factors that affect the location rating have been assessed under location attraction, accessibility, and popularity. An ensemble learning model has been trained to predict the location score of a hypothetical location, assess the manner accessibility affects hotel performance, and predict location popularity based on the surrounding competition. The results show that this method can assess hotel location and performance, with significant accuracy and the identified location-related factors that contribute to a hotel's success can be used by hoteliers and investors to improve decision making. © 2021 IEEE.

关键词： Location

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Model for Recognition of Sign Language and Hand Gesture by Hard Hearing People

Model for Recognition of Sign Language and Hand Gesture by H...

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Sustainable Communication Networks and Application (ICSCNA), International Conference on

作者： Manjula R Jagadeesan S Venkadeshan Ramalingam Vetriselvi T Johnpeter T Department of Computing Technologies College of Engineering and Technology SRM Institute of Science and Technology Chennai India Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore Tamilnadu India Information Technology Department University of Technology and Applied Sciences Sultanate of Oman Department of IOT School of Computer Science and Engineering Vellore Institute of Technology Vellore Tamilnadu India Department of Computer Science and Engineering K.Ramakrishnan College of Engineering Trichy India

Hard hearing and deaf people are communicating with other people using the sign language. This is the only way of communication of such people to convey Since this is the only means by which these individuals can communicate, it is imperative that others be able to understand their language. Sign language recognition by computer begins with the acquisition of sign gestures and ends with recognition and conversion to text or voice. Static and dynamic are the two ways of sign gestures used. This study aims at focusing on the dynamic gesture recognition and the steps for recognizing sign language are discussed. The collected data are preprocessed and feature are extracted for classification. Finally the results are all investigated and developed for single user.

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A Novel Algorithm for Vertex Sum Distinguishing Total Coloring Based on Multiobjective Optimization

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Journal of engineering Science and Technology Review 2021年第6期14卷 107-115页

作者： Huanping, Zhao Dangqin, Xue Huojie, Shi School of Computer and Software Nanyang Institute of Technology Nanyang473004 China School of Intelligent Manufactuing Nanyang Institute of Technology Nanyang473004 China Department of Biological Systems Engineering Washington State University PullmanMI98101 United States

Graph coloring is an important research field in graph theory. In vertex sum distinguishing total coloring, the constraint condition, that is, the color sum of each vertex is different from that of its associated edges is added on the basis of the normal total coloring. A novel algorithm was designed to increase the vertex sum distinguishing total coloring effciency. Subobjective functions were designed according to the vertex constraint, edge constraint, vertex-edge constraint, and vertex-edge sum constraint to improve the vertex sum distinguishing total coloring efficiency of random graphs. In each subobjective function, iterative swap was performed step by step using the coloring matrix and color set complement, in which the conflict was handled following the idea of impressed variation, thereby realizing the vertex sum distinguishing total coloring of random graphs. In the end, the lower bound of chromatic number in the vertex sum distinguishing total coloring was proven through the theoretical analysis and experimental comparison. Results demonstrate that when the order of a graph is smaller than 1000 and the edge density is smaller than 0.1, the conflict handling function can be converged at a high rate. When the order of the graph is greater than 1000, the convergence rate of the algorithm declines rapidly, and the accurate coloring result can be obtained only by increasing the coloring quantity, indicating that the vertex sum distinguishing total chromatic number of a connected graph with the order of not smaller than 3 ranged from μΣt(G) to μΣt(G)+3. This finding is consistent with the algorithm analysis result. On this basis, this algorithm can effectively complete the vertex sum distinguishing total coloring of random graphs, and its time complexity does not exceed O(n3). The proposed algorithm provides evidence for exploring complex networks, transportation, and network security © 2021 School of Science, IHU. All rights reserved

关键词： Multiobjective optimization

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Coherency-Constrained Spectral Clustering for Proactive Load Shedding: A Tri-Level Model

Coherency-Constrained Spectral Clustering for Proactive Load...

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IEEE General Meeting Power& Energy Society

作者： Mario D. Baquedano-Aguilar Arturo Bretas Sean Meyn Department of Electrical & Computer Engineering University of Florida Gainesville FL USA Distributed Systems Group Pacific Northwest National Laboratory Richland WA USA G2Elab Grenoble INP CNRS Université Grenoble Alpes Grenoble France

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

In low-inertia power grids, traditional load-shedding methods can be ineffective, causing instability and unnecessary grid islanding. This work introduces a distributed tri-level optimization model for proactive load shedding to prevent grid islanding considering generator coherency identification. Preventing islanding is crucial because it reduces the need for additional load shedding and transmission line tripping, thereby maintaining frequency stability. This is especially important in systems heavily dependent on non-dispatchable resources like wind and solar. The model employs generator coherency identification through spectral clustering using synchronizing coefficients. The results are then used as constraints in a dynamic graph based on power flow measurements to identify coherent areas for load shedding under highly stressed conditions. This approach offers practical applications and holds promise for real-world use.

关键词： Wind Islanding Power transmission lines Load shedding Power system stability Transmission line measurements Generators Stability analysis Load modeling Stress measurement

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Success Factors of Requirement Elicitation in the Field of software engineering

Success Factors of Requirement Elicitation in the Field of S...

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Advancements in Computing (ICAC), International Conference on

作者： Buddhima Attanayaka Dasuni Nawinna Kalpani Manathunga Pradeep K.W. Abeygunawardhana Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka Department of Computer Systems & Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka

ISBN: (纸本)9798350398106

Requirement elicitation (RE) is a cognitively challenging and time-consuming task in software development due to the numerous challenges associated with it including conflicting requirements, unspoken, or assumed requirements, difficulty meeting with relevant stakeholders, stakeholder resistance to change, and not enough time set aside for meetings with all stakeholders. The prime causes of software implementation failure have been identified as inadequacies in the treatment of requirements. Without collecting the quality requirement, cannot achieve the goal of a quality software product. Through identifying the success factors affecting requirement elicitation, the paths to the quality requirements can be identified. The success factors identify through this research are experience, business analyst skills, stakeholder relationship, organizational elicitation process. This study aims to identify the factors affecting requirement elicitation based on the data collected from business analysts and similar positions in the software industry through a survey, interviews, and analyzed data to provide the initial validation for the identified factors. Through the analysis, we identified the main factors affecting successful requirement elicitation with a perfect significance value of less than 0.05 for all factors.

关键词： Resistance Industries software Stakeholders Task analysis Interviews Business

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A Secure and Reliable Supply chain management approach integrated with IoT and Blockchain

A Secure and Reliable Supply chain management approach integ...

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Business Analytics for Technology and Security (ICBATS), International Conference on

作者： Humaira Ashraf Maria Hanif Uswa Ihsan Fatima Al-Quayed Mamoona Humayun NZ Jhanjhi Department of Computer Science and Software Engineering International Islamic University Islamabad Islamabad Pakistan Department of Computer Science College of Computer and Information Sciences Jouf University Sakakah Saudi Arabia Department of Information Systems College of Computer and Information Sciences Jouf University Sakakah Saudi Arabia School of Computer Science and Engineering (SCE) Taylor’s University Malaysia

Nowadays, secure and reliable management of logistics is highly needed. Logistics is the delivery of goods from producers to legitimate consumers in accurate amounts and good conditions. The use of low-capable sensor nodes in smart logistics makes it vulnerable to many security threats. Smart logistics necessitated the delivery of suitable information to the authorized person at the appropriate time and place, which is only feasible with a stable infrastructure. This paper presents an authentication scheme together with blockchain technology to provide a secure supply chain management system. The presented authentication mechanism is based on standard KERBOROS scheme which is a ticket-based scheme. The scheme is evaluated by BAN logic which shows that it is an effective scheme in terms of improved response time and encryption/decryption time along with key generation time.

关键词： Supply chain management Databases Data integrity Supply chains Authentication Product delivery Blockchains

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Web Application to predict Skin Disease: An Approach Using Deep Learning Algorithm

Web Application to predict Skin Disease: An Approach Using D...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Eelanila Thayalan Ayingaran Arumugavel Sharujan Ganeshan Makenthiran Dalaxshan Harinda Fernando Kaushalya Rajapakse Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798350394634

ISBN: (纸本)9798350394641

The Disease Prediction System revolutionizes healthcare with advanced machine learning techniques for early detection of skin diseases, notably focusing on skin cancer. Through image processing and Transfer Learning, it excels in identifying potential malignancies, enabling timely interventions. Its capabilities extend to benign tumors and growth disorders, utilizing the ResNet50 Model for precise identification. Additionally, it predicts skin reactions associated with various dermatological conditions, such as Urticaria Hives and Warts, leveraging the efficientnetB0 Model. Integration of the VGG16 Model enhances diagnostic accuracy for inflammatory skin conditions. This holistic approach prioritizes patient-centric care, leveraging diverse datasets and intricate pattern recognition in medical images. The system’s proactive nature embodies personalized solutions for early detection, timely intervention, and improved patient outcomes. Its versatility and accuracy underscore itstransformative potential in healthcare delivery. By harnessing diverse datasets and recognizing intricate patterns within medical images, it heralds a new era of personalized healthcare solutions. In essence, the Disease Prediction System exemplifies the transformative potential of machine learning in healthcare, ensuring the highest standards of diagnostic accuracy and efficacy, while prioritizing patient well-being and quality oflife.

关键词： Transfer learning Medical services Skin Pattern recognition Medical diagnostic imaging Standards Robots

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Minimizing Occlusion Effect on Multi-View Camera Perception in BEV with Multi-Sensor Fusion

arXiv

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arXiv 2025年

作者： Kumar, Sanjay Truong, Hiep Sharma, Sushil Sistu, Ganesh Scanlan, Tony Grua, Eoin Eising, Ciarán Department of Electronic and Computer Engineering University of Limerick Ireland Research Centre University of Limerick Ireland Lero The Irish Software Research Centre University of Limerick Ireland DSW Valeo Kronach Germany Valeo Vision Systems Ireland

Autonomous driving technology is rapidly evolving, offering the potential for safer and more efficient transportation. However, the performance of these systems can be significantly compromised by the occlusion on sensors due to environmental factors like dirt, dust, rain, and fog. These occlusions severely affect vision-based tasks such as object detection, vehicle segmentation, and lane recognition. In this paper, we investigate the impact of various kinds of occlusions on camera sensor by projecting their effects from multi-view camera images of the nuScenes dataset into the Bird’s-Eye View (BEV) domain. This approach allows us to analyze how occlusions spatially distribute and influence vehicle segmentation accuracy within the BEV domain. Despite significant advances in sensor technology and multi-sensor fusion, a gap remains in the existing literature regarding the specific effects of camera occlusions on BEV-based perception systems. To address this gap, we use a multi-sensor fusion technique that integrates LiDAR and radar sensor data to mitigate the performance degradation caused by occluded cameras. Our findings demonstrate that this approach significantly enhances the accuracy and robustness of vehicle segmentation tasks, leading to more reliable autonomous driving systems. https://***/OmX2NEeOzAE © 2025, CC BY.

关键词： Image segmentation

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