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N. Venkateswaran^1,*, K. Umadevi²
Computer Systems Science and Engineering, Vol.42, No.1, pp. 1-14, 2022, DOI:10.32604/csse.2022.021217
Abstract Huge data over the cloud computing and big data are processed over the network. The data may be stored, send, altered and communicated over the network between the source and destination. Once data send by source to destination, before reaching the destination data may be attacked by any intruders over the network. The network has numerous routers and devices to connect to internet. Intruders may attack any were in the network and breaks the original data, secrets. Detection of attack in the network became interesting task for many researchers. There are many intrusion detection feature selection algorithm has been suggested… More >

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Monday Eze^1,*, Charles Okunbor², Solomon Esomu³, Nneka Richard-Nnabu⁴, Kayode Oladapo¹, Oghenetega Avwokuruaye⁵, Abisola Olayiwola⁶, Akpovi Ominike⁷, Godwin Odulaja⁸, Oluwatobi Akinmerese¹
Computer Systems Science and Engineering, Vol.42, No.1, pp. 15-31, 2022, DOI:10.32604/csse.2022.021964
（This article belongs to the Special Issue: Advances in Computational Intelligence and its Applications)
Abstract Knowledge propagation is a necessity, both in academics and in the industry. The focus of this work is on how to achieve rapid knowledge propagation using collaborative study groups. The practice of knowledge sharing in study groups finds relevance in conferences, workshops, and class rooms. Unfortunately, there appears to be only few researches on empirical best practices and techniques on study groups formation, especially for achieving rapid knowledge propagation. This work bridges this gap by presenting a workflow driven computational algorithm for autonomous and unbiased formation of study groups. The system workflow consists of a chronology of stages, each made… More >

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K. Sathya^1,*, M. Rajalakshmi²
Computer Systems Science and Engineering, Vol.42, No.1, pp. 33-47, 2022, DOI:10.32604/csse.2022.022206
Abstract In the field of agriculture, the development of an early warning diagnostic system is essential for timely detection and accurate diagnosis of diseases in rice plants. This research focuses on identifying the plant diseases and detecting them promptly through the advancements in the field of computer vision. The images obtained from in-field farms are typically with less visual information. However, there is a significant impact on the classification accuracy in the disease diagnosis due to the lack of high-resolution crop images. We propose a novel Reconstructed Disease Aware–Convolutional Neural Network (RDA-CNN), inspired by recent CNN architectures, that integrates image super… More >

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Ali Alkhalifah^*, Fadwa Alorini, Reef Alturki
Computer Systems Science and Engineering, Vol.42, No.1, pp. 49-67, 2022, DOI:10.32604/csse.2022.021326
Abstract The revolution of technology and the rapid evolution of the digital world had a significant effect on the development and expansion of e-commerce. Last mile delivery, for which different app-based delivery services have recently emerged, is a new area of research that is not thoroughly addressed. Delivery service is one of the supporting platforms of e-commerce. One of the delivery issues is that many customers experience difficulties in communicating and coordinating with the logistics companies responsible for the delivery service. This challenge is emphasized in this study which introduces a new system to facilitate communication and coordination between customers and… More >

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Narongkorn Uthathip^1,*, Pornrapeepat Bhasaputra¹, Woraratana Pattaraprakorn²
Computer Systems Science and Engineering, Vol.42, No.1, pp. 69-86, 2022, DOI:10.32604/csse.2022.020120
（This article belongs to the Special Issue: Advances in Computational Intelligence and its Applications)
Abstract Generally, road transport is a major energy-consuming sector. Fuel consumption of each vehicle is an important factor that affects the overall energy consumption, driving behavior and vehicle characteristic are the main factors affecting the change of vehicle fuel consumption. It is difficult to analyze the influence of fuel consumption with multiple and complex factors. The Adaptive Neuro-Fuzzy Inference System (ANFIS) approach was employed to develop a vehicle fuel consumption model based on multivariate input. The ANFIS network was constructed by various experiments based on the ANFIS Parameter setting. The performance of the ANFIS network was validated using Root Mean Square… More >

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G. Anitha^1,*, S. Baghavathi Priya²
Computer Systems Science and Engineering, Vol.42, No.1, pp. 87-103, 2022, DOI:10.32604/csse.2022.020361
Abstract Human fall detection plays a vital part in the design of sensor based alarming system, aid physical therapists not only to lessen after fall effect and also to save human life. Accurate and timely identification can offer quick medical services to the injured people and prevent from serious consequences. Several vision-based approaches have been developed by the placement of cameras in diverse everyday environments. At present times, deep learning (DL) models particularly convolutional neural networks (CNNs) have gained much importance in the fall detection tasks. With this motivation, this paper presents a new vision based elderly fall event detection using… More >

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R. Punithavathi^1,*, M. Kowsigan², R. Shanthakumari³, Miodrag Zivkovic⁴, Nebojsa Bacanin⁴, Marko Sarac⁴
Computer Systems Science and Engineering, Vol.42, No.1, pp. 105-120, 2022, DOI:10.32604/csse.2022.020486
Abstract At present, health care applications, government services, and banking applications use big data with cloud storage to process and implement data. Data mobility in cloud environments uses protection protocols and algorithms to secure sensitive user data. Sometimes, data may have highly sensitive information, leading users to consider using big data and cloud processing regardless of whether they are secured are not. Threats to sensitive data in cloud systems produce high risks, and existing security methods do not provide enough security to sensitive user data in cloud and big data environments. At present, several security solutions support cloud systems. Some of… More >

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Yabin Xu^1,*, Lulu Cui¹, Xiaowei Xu²
Computer Systems Science and Engineering, Vol.42, No.1, pp. 121-132, 2022, DOI:10.32604/csse.2022.022758
Abstract Fracture toughness plays a vital role in damage tolerance design of materials and assessment of structural integrity. To solve these problems of complexity, time-consuming, and low accuracy in obtaining the fracture toughness value of nickel-based superalloys through experiments. A combination prediction model is proposed based on the principle of materials genome engineering, the fracture toughness values of nickel-based superalloys at different temperatures, and different compositions can be predicted based on the existing experimental data. First, to solve the problem of insufficient feature extraction based on manual experience, the Deep Belief Network (DBN) is used to extract features, and an attention… More >

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Bayan Al-Amri¹, Gofran Sami², Wajdi Alhakami^1,*
Computer Systems Science and Engineering, Vol.42, No.1, pp. 133-148, 2022, DOI:10.32604/csse.2022.021543
Abstract The vast revolution in networking is increasing rapidly along with technology advancements, which requires more effort from all cyberspace professionals to cope with the challenges that come with advanced technology privileges and services. Hence, Cognitive Radio Network is one of the promising approaches that permit a dynamic type of smart network for improving the utilization of idle spectrum portions of wireless communications. However, it is vulnerable to security threats and attacks and demands security mechanisms to preserve and protect the cognitive radio networks for ensuring a secure communication environment. This paper presents an effective secure MAC protocol for cognitive radio… More >

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1096

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E. Gothai^1,*, A. Baseera², P. Prabu³, K. Venkatachalam⁴, K. Saravanan⁵, S. SathishKumar⁶
Computer Systems Science and Engineering, Vol.42, No.1, pp. 149-163, 2022, DOI:10.32604/csse.2022.020619
Abstract The brain of humans and other organisms is affected in various ways through the electromagnetic field (EMF) radiations generated by mobile phones and cell phone towers. Morphological variations in the brain are caused by the neurological changes due to the revelation of EMF. Cellular level analysis is used to measure and detect the effect of mobile radiations, but its utilization seems very expensive, and it is a tedious process, where its analysis requires the preparation of cell suspension. In this regard, this research article proposes optimal broadcasting learning to detect changes in brain morphology due to the revelation of EMF.… More >

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M. P. Viswanathan^*, B. Anand
Computer Systems Science and Engineering, Vol.42, No.1, pp. 165-181, 2022, DOI:10.32604/csse.2022.020400
Abstract In this research work, single-stage fifteen levels cascaded DC-interface converter (CDDCLC) is proposed for sun arranged photovoltaic technology (PV) applications. The proposed geography is joined with help DC chopper and H-associate inverter to upgrade the power converter to accomplish the diminished harmonic profile. In assessment with the customary inverter structures, the proposed system is used with diminished voltage stress, decreased switch count and DC source tally. The proposed research work with cascaded DC link converter design requires three DC sources for combining fifteen-level AC output. This investigation structure switching technique is phase opposition and disposition pulse width modulation technique (POPD)… More >

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808

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S. Karthik¹, M. Santhosh^1,*, M. S. Kavitha¹, A. Christopher Paul²
Computer Systems Science and Engineering, Vol.42, No.1, pp. 183-199, 2022, DOI:10.32604/csse.2022.021698
Abstract Automated biomedical signal processing becomes an essential process to determine the indicators of diseased states. At the same time, latest developments of artificial intelligence (AI) techniques have the ability to manage and analyzing massive amounts of biomedical datasets results in clinical decisions and real time applications. They can be employed for medical imaging; however, the 1D biomedical signal recognition process is still needing to be improved. Electrocardiogram (ECG) is one of the widely used 1-dimensional biomedical signals, which is used to diagnose cardiovascular diseases. Computer assisted diagnostic models find it difficult to automatically classify the 1D ECG signals owing to… More >

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Yu Xue^1,2,*, Bernard-Marie Onzo¹, Romany F. Mansour^3,4, Shoubao Su⁴
Computer Systems Science and Engineering, Vol.42, No.1, pp. 201-211, 2022, DOI:10.32604/csse.2022.022158
Abstract Coronavirus disease 2019 (Covid-19) is a life-threatening infectious disease caused by a newly discovered strain of the coronaviruses. As by the end of 2020, Covid-19 is still not fully understood, but like other similar viruses, the main mode of transmission or spread is believed to be through droplets from coughs and sneezes of infected persons. The accurate detection of Covid-19 cases poses some questions to scientists and physicians. The two main kinds of tests available for Covid-19 are viral tests, which tells you whether you are currently infected and antibody test, which tells if you had been infected previously. Routine… More >

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Hsin-Pin Fu^1,*, Tsung-Sheng Chang², Chien-Hung Liu³, Li-Chun Liu¹
Computer Systems Science and Engineering, Vol.42, No.1, pp. 213-227, 2022, DOI:10.32604/csse.2022.021767
（This article belongs to the Special Issue: Recent Trends in Software Engineering and Applications)
Abstract The advantages of a cloud computing service are cost advantages, availability, scalability, flexibility, reduced time to market, and dynamic access to computing resources. Enterprises can improve the successful adoption rate of cloud computing services if they understand the critical factors. To find critical factors, this study first reviewed the literature and established a three-layer hierarchical factor table for adopting a cloud computing service based on the Technology-Organization-Environment framework. Then, a hybrid method that combines two multi-criteria decision-making tools—called the Fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical… More >

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896

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R. Malavika^1,*, M. L. Valarmathi²
Computer Systems Science and Engineering, Vol.42, No.1, pp. 229-243, 2022, DOI:10.32604/csse.2022.020947
Abstract Web service applications are increasing tremendously in support of high-level businesses. There must be a need of better server load balancing mechanism for improving the performance of web services in business. Though many load balancing methods exist, there is still a need for sophisticated load balancing mechanism for not letting the clients to get frustrated. In this work, the server with minimum response time and the server having less traffic volume were selected for the aimed server to process the forthcoming requests. The Servers are probed with adaptive control of time with two thresholds L and U to indicate the… More >

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947

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C. Saravanakumar^1,*, R. Priscilla¹, B. Prabha², A. Kavitha³, M. Prakash⁴, C. Arun⁵
Computer Systems Science and Engineering, Vol.42, No.1, pp. 245-256, 2022, DOI:10.32604/csse.2022.022122
Abstract Cloud Computing provides various services to the customer in a flexible and reliable manner. Virtual Machines (VM) are created from physical resources of the data center for handling huge number of requests as a task. These tasks are executed in the VM at the data center which needs excess hosts for satisfying the customer request. The VM migration solves this problem by migrating the VM from one host to another host and makes the resources available at any time. This process is carried out based on various algorithms which follow a predefined capacity of source VM leads to the capacity… More >

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R. Kanthavel^1,*, R. Dhaya²
Computer Systems Science and Engineering, Vol.42, No.1, pp. 257-269, 2022, DOI:10.32604/csse.2022.021606
Abstract Osteoarthritis is the most common class of arthritis that involves tears down the soft cartilage between the joints of the knee. The regeneration of this cartilage tissue is not possible, and thus physicians typically suggest therapeutic measures to prevent further deterioration over time. Normally, bringing about joint replacement is a remedial course of action. Expose itself in joint pain recognized with a normal X-ray. Deep learning plays a vital role in predicting the early stages of osteoarthritis by using the MRI pictures of muscles of the knee muscle. It can be used to accurately measure the shape and texture of… More >

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Xin Liu¹, Siya Xu¹, Chao Yang², Zhili Wang^1,*, Hao Zhang³, Jingye Chi¹, Qinghan Li⁴
Computer Systems Science and Engineering, Vol.42, No.1, pp. 271-287, 2022, DOI:10.32604/csse.2022.022103
Abstract With the development of internet of vehicles, the traditional centralized content caching mode transmits content through the core network, which causes a large delay and cannot meet the demands for delay-sensitive services. To solve these problems, on basis of vehicle caching network, we propose an edge collaborative caching scheme. Road side unit (RSU) and mobile edge computing (MEC) are used to collect vehicle information, predict and cache popular content, thereby provide low-latency content delivery services. However, the storage capacity of a single RSU severely limits the edge caching performance and cannot handle intensive content requests at the same time. Through… More >

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V. R. Balaji^1,*, T. Kalavathi², J. Vellingiri³, N. Rajkumar⁴, Venkat Prasad Padhy⁵
Computer Systems Science and Engineering, Vol.42, No.1, pp. 289-301, 2022, DOI:10.32604/csse.2022.020971
Abstract Data offloading at the network with less time and reduced energy consumption are highly important for every technology. Smart applications process the data very quickly with less power consumption. As technology grows towards 5G communication architecture, identifying a solution for QoS in 5G through energy-efficient computing is important. In this proposed model, we perform data offloading at 5G using the fuzzification concept. Mobile IoT devices create tasks in the network and are offloaded in the cloud or mobile edge nodes based on energy consumption. Two base stations, small (SB) and macro (MB) stations, are initialized and the first tasks randomly… More >

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876

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Ali Algarni¹, Mahmoud Ragab^2,3,4,*, Wardah Alamri⁵, Samih M. Mostafa⁶
Computer Systems Science and Engineering, Vol.42, No.1, pp. 303-318, 2022, DOI:10.32604/csse.2022.022152
Abstract The accuracy of the statistical learning model depends on the learning technique used which in turn depends on the dataset’s values. In most research studies, the existence of missing values (MVs) is a vital problem. In addition, any dataset with MVs cannot be used for further analysis or with any data driven tool especially when the percentage of MVs are high. In this paper, the authors propose a novel algorithm for dealing with MVs depending on the feature selection (FS) of similarity classifier with fuzzy entropy measure. The proposed algorithm imputes MVs in cumulative order. The candidate feature to be… More >

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Jing Peng^1,2,3, Jingfu Yang², Chaoyang Xia², Xiaojie Li², Yanfen Guo², Ying Fu², Xinlai Chen⁴, Zhe Cui^1,3,*
Computer Systems Science and Engineering, Vol.42, No.1, pp. 319-333, 2022, DOI:10.32604/csse.2022.022314
Abstract Cardiac anatomy segmentation is essential for cardiomyopathy clinical diagnosis and treatment planning. Thus, accurate delineation of target volumes at risk in cardiac anatomy is important. However, manual delineation is a time-consuming and labor-intensive process for cardiologists and has been shown to lead to significant inter-and intra-practitioner variability. Thus, computer-aided or fully automatic segmentation methods are required. They can significantly economize on manpower and improve treatment efficiency. Recently, deep convolutional neural network (CNN) based methods have achieved remarkable successes in various kinds of vision tasks, such as classification, segmentation and object detection. Semantic segmentation can be considered as a pixel-wise task,… More >

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Suraya Hamid¹, Shahrul Nizam Ismail¹, Muzaffar Hamzah^2,*, Asad W. Malik³
Computer Systems Science and Engineering, Vol.42, No.1, pp. 335-350, 2022, DOI:10.32604/csse.2022.021927
（This article belongs to the Special Issue: Application of the Information Technology During the Complex Pandemic Times Especially in the Education Sector)
Abstract Learning analytics is an emerging technique of analysing student participation and engagement. The recent COVID-19 pandemic has significantly increased the role of learning management systems (LMSs). LMSs previously only complemented face-to-face teaching, something which has not been possible between 2019 to 2020. To date, the existing body of literature on LMSs has not analysed learning in the context of the pandemic, where an LMS serves as the only interface between students and instructors. Consequently, productive results will remain elusive if the key factors that contribute towards engaging students in learning are not first identified. Therefore, this study aimed to perform… More >

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Kexin Zhang¹, Bin Lin^2,*, Jixin Chen¹, Xinlong Wu¹, Chao Lu³, Desheng Zheng¹, Lulu Tian⁴
Computer Systems Science and Engineering, Vol.42, No.1, pp. 351-360, 2022, DOI:10.32604/csse.2022.021132
Abstract Deep learning techniques have outstanding performance in feature extraction and model fitting. In the field of aero-engine fault diagnosis, the introduction of deep learning technology is of great significance. The aero-engine is the heart of the aircraft, and its stable operation is the primary guarantee of the aircraft. In order to ensure the normal operation of the aircraft, it is necessary to study and diagnose the faults of the aero-engine. Among the many engine failures, the one that occurs more frequently and is more hazardous is the wheeze, which often poses a great threat to flight safety. On the basis… More >

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S. Palpandi^1,*, T. Meeradevi²
Computer Systems Science and Engineering, Vol.42, No.1, pp. 361-371, 2022, DOI:10.32604/csse.2022.021412
Abstract Skin cancer is usually classified as melanoma and non-melanoma. Melanoma now represents 75% of humans passing away worldwide and is one of the most brutal types of cancer. Previously, studies were not mainly focused on feature extraction of Melanoma, which caused the classification accuracy. However, in this work, Histograms of orientation gradients and local binary patterns feature extraction procedures are used to extract the important features such as asymmetry, symmetry, boundary irregularity, color, diameter, etc., and are removed from both melanoma and non-melanoma images. This proposed Efficient Classification Systems for the Diagnosis of Melanoma (ECSDM) framework consists of different schemes… More >

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920

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Gowdham Chinnaraju^*, S. Nithyanandam
Computer Systems Science and Engineering, Vol.42, No.1, pp. 373-386, 2022, DOI:10.32604/csse.2022.020993
Abstract Wireless Sensor Networks (WSNs) gained wide attention in the past decade, thanks to its attractive features like flexibility, monitoring capability, and scalability. It overcomes the crucial problems experienced in network management and facilitates the development of diverse network architectures. The existence of dynamic and adaptive routing features facilitate the quick formation of such networks. But flexible architecture also makes it highly vulnerable to different sorts of attacks, for instance, Denial of Service (DoS). Grey Hole Attack (GHA) is the most crucial attack types since it creates a heavy impact upon the components of WSN and eventually degrades the performance of… More >

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Liang Jin^1,*, Qinghui Meng¹, Shuang Liang²
Computer Systems Science and Engineering, Vol.42, No.1, pp. 387-395, 2022, DOI:10.32604/csse.2022.017745
Abstract The energy consumption of train operation occupies a large proportion of the total consumption of railway transportation. In order to improve the operating energy utilization rate of trains, a multi-objective particle swarm optimization (MPSO) algorithm with energy consumption, punctuality and parking accuracy as the objective and safety as the constraint is built. To accelerate its the convergence process, the train operation progression is divided into several modes according to the train speed-distance curve. A human-computer interactive particle swarm optimization algorithm is proposed, which presents the optimized results after a certain number of iterations to the decision maker, and the satisfactory… More >

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842

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B. Sakthivel^1,*, K. Jayaram², N. Manikanda Devarajan³, S. Mahaboob Basha⁴, S. Rajapriya⁵
Computer Systems Science and Engineering, Vol.42, No.1, pp. 397-406, 2022, DOI:10.32604/csse.2022.021637
Abstract Approximate Computing is a low power achieving technique that offers an additional degree of freedom to design digital circuits. Pruning is one of the types of approximate circuit design technique which removes logic gates or wires in the circuit to reduce power consumption with minimal insertion of error. In this work, a novel machine learning (ML) -based pruning technique is introduced to design digital circuits. The machine-learning algorithm of the random forest decision tree is used to prune nodes selectively based on their input pattern. In addition, an error compensation value is added to the original output to reduce an… More >

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Ibrahim El rube'^*, Sameer Alsharif
Computer Systems Science and Engineering, Vol.42, No.1, pp. 407-421, 2022, DOI:10.32604/csse.2022.022400
Abstract This article presents a method for the description of key points using simple statistics for regions controlled by neighboring key points to remedy the gap in existing descriptors. Usually, the existent descriptors such as speeded up robust features (SURF), Kaze, binary robust invariant scalable keypoints (BRISK), features from accelerated segment test (FAST), and oriented FAST and rotated BRIEF (ORB) can competently detect, describe, and match images in the presence of some artifacts such as blur, compression, and illumination. However, the performance and reliability of these descriptors decrease for some imaging variations such as point of view, zoom (scale), and rotation.… More >

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