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  • Open Access

    ARTICLE

    Improved Load-Balanced Clustering for Energy-Aware Routing (ILBC-EAR) in WSNs

    D. Loganathan1,*, M. Balasubramani1, R. Sabitha2, S. Karthik2

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 99-112, 2023, DOI:10.32604/csse.2023.023120 - 01 June 2022

    Abstract Sensors are considered as important elements of electronic devices. In many applications and service, Wireless Sensor Networks (WSNs) are involved in significant data sharing that are delivered to the sink node in energy efficient manner using multi-hop communications. But, the major challenge in WSN is the nodes are having limited battery resources, it is important to monitor the consumption rate of energy is very much needed. However, reducing energy consumption can increase the network lifetime in effective manner. For that, clustering methods are widely used for optimizing the rate of energy consumption among the sensor… More >

  • Open Access

    ARTICLE

    Hybrid Flow Shop with Setup Times Scheduling Problem

    Mahdi Jemmali1,2,3,*, Lotfi Hidri4

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 563-577, 2023, DOI:10.32604/csse.2023.022716 - 01 June 2022

    Abstract The two-stage hybrid flow shop problem under setup times is addressed in this paper. This problem is NP-Hard. on the other hand, the studied problem is modeling different real-life applications especially in manufacturing and high performance-computing. Tackling this kind of problem requires the development of adapted algorithms. In this context, a metaheuristic using the genetic algorithm and three heuristics are proposed in this paper. These approximate solutions are using the optimal solution of the parallel machines under release and delivery times. Indeed, these solutions are iterative procedures focusing each time on a particular stage where… More >

  • Open Access

    ARTICLE

    Performance Analysis of Breast Cancer Detection Method Using ANFIS Classification Approach

    K. Nagalakshmi1,*, S. Dr. Suriya2

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 501-517, 2023, DOI:10.32604/csse.2023.022687 - 01 June 2022

    Abstract Breast cancer is one of the deadly diseases prevailing in women. Earlier detection and diagnosis might prevent the death rate. Effective diagnosis of breast cancer remains a significant challenge, and early diagnosis is essential to avoid the most severe manifestations of the disease. The existing systems have computational complexity and classification accuracy problems over various breast cancer databases. In order to overcome the above-mentioned issues, this work introduces an efficient classification and segmentation process. Hence, there is a requirement for developing a fully automatic methodology for screening the cancer regions. This paper develops a fully… More >

  • Open Access

    ARTICLE

    Framework for Effective Utilization of Distributed Scrum in Software Projects

    Basit Shahzad1, Wardah Naeem Awan1,*, Fazal-e-Amin2, Ahsanullah Abro3, Muhammad Shoaib4, Sultan Alyahya4

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 407-422, 2023, DOI:10.32604/csse.2023.022601 - 01 June 2022

    Abstract There is an emerging interest in using agile methodologies in Global Software Development (GSD) to get the mutual benefits of both methods. Scrum is currently admired by many development teams as an agile most known methodology and considered adequate for collocated teams. At the same time, stakeholders in GSD are dispersed by geographical, temporal, and socio-cultural distances. Due to the controversial nature of Scrum and GSD, many significant challenges arise that might restrict the use of Scrum in GSD. We conducted a Systematic Literature Review (SLR) by following Kitchenham guidelines to identify the challenges that More >

  • Open Access

    ARTICLE

    Skin Lesion Classification System Using Shearlets

    S. Mohan Kumar*, T. Kumanan

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 833-844, 2023, DOI:10.32604/csse.2023.022385 - 01 June 2022

    Abstract The main cause of skin cancer is the ultraviolet radiation of the sun. It spreads quickly to other body parts. Thus, early diagnosis is required to decrease the mortality rate due to skin cancer. In this study, an automatic system for Skin Lesion Classification (SLC) using Non-Subsampled Shearlet Transform (NSST) based energy features and Support Vector Machine (SVM) classifier is proposed. At first, the NSST is used for the decomposition of input skin lesion images with different directions like 2, 4, 8 and 16. From the NSST’s sub-bands, energy features are extracted and stored in More >

  • Open Access

    ARTICLE

    Machine Learning and Artificial Neural Network for Predicting Heart Failure Risk

    Polin Rahman1, Ahmed Rifat1, MD. IftehadAmjad Chy1, Mohammad Monirujjaman Khan1,*, Mehedi Masud2, Sultan Aljahdali2

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 757-775, 2023, DOI:10.32604/csse.2023.021469 - 01 June 2022

    Abstract Heart failure is now widely spread throughout the world. Heart disease affects approximately 48% of the population. It is too expensive and also difficult to cure the disease. This research paper represents machine learning models to predict heart failure. The fundamental concept is to compare the correctness of various Machine Learning (ML) algorithms and boost algorithms to improve models’ accuracy for prediction. Some supervised algorithms like K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Decision Trees (DT), Random Forest (RF), Logistic Regression (LR) are considered to achieve the best results. Some boosting algorithms like Extreme Gradient… More >

  • Open Access

    ARTICLE

    Lexicalized Dependency Paths Based Supervised Learning for Relation Extraction

    Huiyu Sun*, Ralph Grishman

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 861-870, 2022, DOI:10.32604/csse.2022.030759 - 09 May 2022

    Abstract Log-linear models and more recently neural network models used for supervised relation extraction requires substantial amounts of training data and time, limiting the portability to new relations and domains. To this end, we propose a training representation based on the dependency paths between entities in a dependency tree which we call lexicalized dependency paths (LDPs). We show that this representation is fast, efficient and transparent. We further propose representations utilizing entity types and its subtypes to refine our model and alleviate the data sparsity problem. We apply lexicalized dependency paths to supervised learning using the More >

  • Open Access

    ARTICLE

    An Improved Genetic Algorithm for Berth Scheduling at Bulk Terminal

    Xiaona Hu1,2, Shan Ji3, Hao Hua4, Baiqing Zhou1,*, Gang Hu5

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1285-1296, 2022, DOI:10.32604/csse.2022.029230 - 09 May 2022

    Abstract Berth and loading and unloading machinery are not only the main factors that affecting the terminal operation, but also the main starting point of energy saving and emission reduction. In this paper, a genetic Algorithm Framework is designed for the berth allocation with low carbon and high efficiency at bulk terminal. In solving the problem, the scheduler’s experience is transformed into a regular way to obtain the initial solution. The individual is represented as a chromosome, and the sub-chromosomes are encoded as integers, the roulette wheel method is used for selection, the two-point crossing method… More >

  • Open Access

    ARTICLE

    Cold-Start Link Prediction via Weighted Symmetric Nonnegative Matrix Factorization with Graph Regularization

    Minghu Tang1,2,3,*, Wei Yu4, Xiaoming Li4, Xue Chen5, Wenjun Wang3, Zhen Liu6

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1069-1084, 2022, DOI:10.32604/csse.2022.028841 - 09 May 2022

    Abstract Link prediction has attracted wide attention among interdisciplinary researchers as an important issue in complex network. It aims to predict the missing links in current networks and new links that will appear in future networks. Despite the presence of missing links in the target network of link prediction studies, the network it processes remains macroscopically as a large connected graph. However, the complexity of the real world makes the complex networks abstracted from real systems often contain many isolated nodes. This phenomenon leads to existing link prediction methods not to efficiently implement the prediction of… More >

  • Open Access

    ARTICLE

    Real-time Safety Helmet-wearing Detection Based on Improved YOLOv5

    Yanman Li1, Jun Zhang1, Yang Hu1, Yingnan Zhao2,*, Yi Cao3

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1219-1230, 2022, DOI:10.32604/csse.2022.028224 - 09 May 2022

    Abstract Safety helmet-wearing detection is an essential part of the intelligent monitoring system. To improve the speed and accuracy of detection, especially small targets and occluded objects, it presents a novel and efficient detector model. The underlying core algorithm of this model adopts the YOLOv5 (You Only Look Once version 5) network with the best comprehensive detection performance. It is improved by adding an attention mechanism, a CIoU (Complete Intersection Over Union) Loss function, and the Mish activation function. First, it applies the attention mechanism in the feature extraction. The network can learn the weight of… More >

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