S. Godfrey Winster¹, A. Siva Kumar^2,*, R. Ramesh³

Computer Systems Science and Engineering, Vol.42, No.2, pp. 605-618, 2022, DOI:10.32604/csse.2022.022467

Abstract Cloud computing is a collection of distributed storage Network which can provide various services and store the data in the efficient manner. The advantages of cloud computing is its remote access where data can accessed in real time using Remote Method Innovation (RMI). The problem of data security in cloud environment is a major concern since the data can be accessed by any time by any user. Due to the lack of providing the efficient security the cloud computing they fail to achieve higher performance in providing the efficient service. To improve the performance in data security, the block chains… More >

Balakrishnan Natarajan^1,*, Pushpalatha Krishnan²

Computer Systems Science and Engineering, Vol.42, No.2, pp. 423-438, 2022, DOI:10.32604/csse.2022.022376

Abstract In existing methods for segmented images, either edge point extraction or preservation of edges, compromising contrast images is so sensitive to noise. The Degeneration Threshold Image Detection (DTID) framework has been proposed to improve the contrast of edge filtered images. Initially, DTID uses a Rapid Bilateral Filtering process for filtering edges of contrast images. This filter decomposes input images into base layers in the DTID framework. With minimal filtering time, Rapid Bilateral Filtering handles high dynamic contrast images for smoothening edge preservation. In the DTID framework, Rapid Bilateral Filtering with Shift-Invariant Base Pass Domain Filter is insensitive to noise. This… More >

Chin-Shyurng Fahn¹, Chang-Yi Kao^2,*, Meng-Luen Wu³, Hao-En Chueh⁴

Computer Systems Science and Engineering, Vol.42, No.2, pp. 451-463, 2022, DOI:10.32604/csse.2022.022368

Abstract With the evolution of video surveillance systems, the requirement of video storage grows rapidly; in addition, safe guards and forensic officers spend a great deal of time observing surveillance videos to find abnormal events. As most of the scene in the surveillance video are redundant and contains no information needs attention, we propose a video condensation method to summarize the abnormal events in the video by rearranging the moving trajectory and sort them by the degree of anomaly. Our goal is to improve the condensation rate to reduce more storage size, and increase the accuracy in abnormal detection. As the… More >

Faisal Bahadur^1,*, Arif Iqbal Umar¹, Insaf Ullah², Fahad Algarni³, Muhammad Asghar Khan²

Computer Systems Science and Engineering, Vol.42, No.2, pp. 589-604, 2022, DOI:10.32604/csse.2022.022319

Abstract Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate… More >

N. Veni^1,*, J. Manjula²

Computer Systems Science and Engineering, Vol.42, No.2, pp. 825-835, 2022, DOI:10.32604/csse.2022.022318

Abstract The advancement of automated medical diagnosis in biomedical engineering has become an important area of research. Image classification is one of the diagnostic approaches that do not require segmentation which can draw quicker inferences. The proposed non-invasive diagnostic support system in this study is considered as an image classification system where the given brain image is classified as normal or abnormal. The ability of deep learning allows a single model for feature extraction as well as classification whereas the rational models require separate models. One of the best models for image localization and classification is the Visual Geometric Group (VGG)… More >

Mudassir Shams¹, Naila Rafiq², Nasreen Kausar³, Nazir Ahmad Mir², Ahmad Alalyani^4,*

Computer Systems Science and Engineering, Vol.42, No.2, pp. 689-701, 2022, DOI:10.32604/csse.2022.022269

Abstract In this study, we construct a family of single root finding method of optimal order four and then generalize this family for estimating of all roots of non-linear equation simultaneously. Convergence analysis proves that the local order of convergence is four in case of single root finding iterative method and six for simultaneous determination of all roots of non-linear equation. Some non-linear equations are taken from physics, chemistry and engineering to present the performance and efficiency of the newly constructed method. Some real world applications are taken from fluid mechanics, i.e., fluid permeability in biogels and biomedical engineering which includes… More >

Komal Bashir^1,*, Mariam Rehman², Afnan Bashir³, Faria Kanwal¹

Computer Systems Science and Engineering, Vol.42, No.2, pp. 751-777, 2022, DOI:10.32604/csse.2022.022247

Abstract Knowledge Management (KM) has become a dynamic concept for inquiry in research. The management of knowledge from multiple sources requires a systematic approach that can facilitate capturing all important aspects related to a particular discipline, several KM frameworks have been designed to serve this purpose. This research aims to propose a Collaborative Knowledge Management (CKM) Framework that bridges gaps and overcomes weaknesses in existing frameworks. The paper also validates the framework by evaluating its effectiveness for the agriculture sector of Pakistan. A software LCWU aKMS was developed which serves as a practical implementation of the concepts behind the proposed CKMF… More >

Ling-Jing Kao¹, Chih-Chou Chiu^1,*, Yu-Fan Lin², Heong Kam Weng¹

Computer Systems Science and Engineering, Vol.42, No.2, pp. 493-508, 2022, DOI:10.32604/csse.2022.022166

Abstract Inter-purchase time is a critical factor for predicting customer churn. Improving the prediction accuracy can exploit consumer’s preference and allow businesses to learn about product or pricing plan weak points, operation issues, as well as customer expectations to proactively reduce reasons for churn. Although remarkable progress has been made, classic statistical models are difficult to capture behavioral characteristics in transaction data because transaction data are dependent and short-, medium-, and long-term data are likely to interfere with each other sequentially. Different from literature, this study proposed a hybrid inter-purchase time prediction model for customers of on-line retailers. Moreover, the analysis… More >

P. Anandraj^1,*, S. Ramabalan²

Computer Systems Science and Engineering, Vol.42, No.2, pp. 795-811, 2022, DOI:10.32604/csse.2022.022107

Abstract The design of controllers for robots is a complex system that is to be dealt with several tasks in real time for enabling the robots to function independently. The distributed robotic control system can be used in real time for resolving various challenges such as localization, motion controlling, mapping, route planning, etc. The distributed robotic control system can manage different kinds of heterogenous devices. Designing a distributed robotic control system is a challenging process as it needs to operate effectually under different hardware configurations and varying computational requirements. For instance, scheduling of resources (such as communication channel, computation unit, robot… More >

Asrar Bajaber^1,*, Mai Fadel¹, Lamiaa Elrefaei²

Computer Systems Science and Engineering, Vol.42, No.2, pp. 465-481, 2022, DOI:10.32604/csse.2022.022003

Abstract Touch gesture biometrics authentication system is the study of user's touching behavior on his touch device to identify him. The features traditionally used in touch gesture authentication systems are extracted using hand-crafted feature extraction approach. In this work, we investigate the ability of Deep Learning (DL) to automatically discover useful features of touch gesture and use them to authenticate the user. Four different models are investigated Long-Short Term Memory (LSTM), Gated Recurrent Unit (GRU), Convolutional Neural Network (CNN) combined with LSTM (CNN-LSTM), and CNN combined with GRU(CNN-GRU). In addition, different regularization techniques are investigated such as Activity Regularizer, Batch Normalization… More >