Shweta Singhal¹, Nishtha Jatana², Ahmad F Subahi³, Charu Gupta^4,*, Osamah Ibrahim Khalaf⁵, Youseef Alotaibi⁶

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6755-6774, 2023, DOI:10.32604/cmc.2023.032308

Abstract Software needs modifications and requires revisions regularly. Owing to these revisions, retesting software becomes essential to ensure that the enhancements made, have not affected its bug-free functioning. The time and cost incurred in this process, need to be reduced by the method of test case selection and prioritization. It is observed that many nature-inspired techniques are applied in this area. African Buffalo Optimization is one such approach, applied to regression test selection and prioritization. In this paper, the proposed work explains and proves the applicability of the African Buffalo Optimization approach to test case selection and prioritization. The proposed algorithm… More >

Rubab Sheikh¹, Muhammad Imran Babar^2,*, Rawish Butt³, Abdelzahir Abdelmaboud⁴, Taiseer Abdalla Elfadil Eisa⁴

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6789-6806, 2023, DOI:10.32604/cmc.2023.028625

Abstract Regression testing is a widely used approach to confirm the correct functionality of the software in incremental development. The use of test cases makes it easier to test the ripple effect of changed requirements. Rigorous testing may help in meeting the quality criteria that is based on the conformance to the requirements as given by the intended stakeholders. However, a minimized and prioritized set of test cases may reduce the efforts and time required for testing while focusing on the timely delivery of the software application. In this research, a technique named TestReduce has been presented to get a minimal… More >

Noor Gul^1,2, Saeed Ahmed^1,3, Su Min Kim¹, Muhammad Sajjad Khan⁴, Junsu Kim^1,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5209-5227, 2023, DOI:10.32604/cmc.2023.026945

Abstract A cognitive radio network (CRN) intelligently utilizes the available spectral resources by sensing and learning from the radio environment to maximize spectrum utilization. In CRNs, the secondary users (SUs) opportunistically access the primary users (PUs) spectrum. Therefore, unambiguous detection of the PU channel occupancy is the most critical aspect of the operations of CRNs. Cooperative spectrum sensing (CSS) is rated as the best choice for making reliable sensing decisions. This paper employs machine-learning tools to sense the PU channels reliably in CSS. The sensing parameters are reconfigured to maximize the spectrum utilization while reducing sensing error and cost with improved… More >

J. R. Arunkumar^1,*, S. Velmurugan², Balarengadurai Chinnaiah³, G. Charulatha⁴, M. Ramkumar Prabhu⁴, A. Prabhu Chakkaravarthy⁵

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2635-2645, 2023, DOI:10.32604/csse.2023.031605

Abstract Nowadays, Wireless Sensor Network (WSN) is a modern technology with a wide range of applications and greatly attractive benefits, for example, self-governing, low expenditure on execution and data communication, long-term function, and unsupervised access to the network. The Internet of Things (IoT) is an attractive, exciting paradigm. By applying communication technologies in sensors and supervising features, WSNs have initiated communication between the IoT devices. Though IoT offers access to the highest amount of information collected through WSNs, it leads to privacy management problems. Hence, this paper provides a Logistic Regression machine learning with the Elliptical Curve Cryptography technique (LRECC) to… More >

Neema George^1,*, B. K. Anoop¹, Vinodh P. Vijayan²

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2281-2297, 2023, DOI:10.32604/csse.2023.028117

Abstract Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application. When workload execution, accuracy, and cost are accurately stabilized in opposition to the best possible framework in real-time, efficiency is attained. In addition, every workload or application required for the framework is characteristic and these essentials change over time. But, the existing method was failed to ensure the high Quality of Service (QoS). In order to address this issue, a Tricube Weighted Linear Regression-based Inter Quartile (TWLR-IQ) for Cloud Infrastructural Resource Optimization is introduced. A Tricube Weighted Linear Regression… More >

Tobias Drieschner^1,2,*, Andreas Kandelbauer¹, Bernd Hitzmann², Karsten Rebner¹

Journal of Renewable Materials, Vol.11, No.4, pp. 1643-1660, 2023, DOI:10.32604/jrm.2023.024429

Abstract For optimization of production processes and product quality, often knowledge of the factors influencing the process outcome is compulsory. Thus, process analytical technology (PAT) that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality. The present study aims at characterizing a well-known industrial process, the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters (FAME) for usage as biodiesel in a continuous micro reactor set-up. To this end, a… More >

Ali Çakmak^1,*, Sezai Kızıltuğ², Gökhan Mumcu³

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2731-2742, 2023, DOI:10.32604/cmes.2023.024517

Abstract In this paper, we define the curve at a constant distance from the edge of regression on a curve r(s) with arc length parameter s in Galilean 3-space. Here, d is a non-isotropic or isotropic vector defined as a vector tightly fastened to Frenet trihedron of the curve r(s) in 3-dimensional Galilean space. We build the Frenet frame of the constructed curve with respect to two types of the vector d and we indicate the properties related to the curvatures of the curve . Also, for the curve , we give the conditions to be a circular helix. Furthermore, we… More >

Weifeng Liu^1,2, Xin Yu^1,*, Qinyang Zhao³, Guang Cheng², Xiaobing Hou¹, Shengqi He⁴

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3199-3219, 2023, DOI:10.32604/cmc.2023.032595

Abstract Time series forecasting and analysis are widely used in many fields and application scenarios. Time series historical data reflects the change pattern and trend, which can serve the application and decision in each application scenario to a certain extent. In this paper, we select the time series prediction problem in the atmospheric environment scenario to start the application research. In terms of data support, we obtain the data of nearly 3500 vehicles in some cities in China from Runwoda Research Institute, focusing on the major pollutant emission data of non-road mobile machinery and high emission vehicles in Beijing and Bozhou,… More >

S. Sridevi^*, Jeevaa Katiravan

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 223-233, 2023, DOI:10.32604/iasc.2023.031928

Abstract Scientific workflows have gained the emerging attention in sophisticated large-scale scientific problem-solving environments. The pay-per-use model of cloud, its scalability and dynamic deployment enables it suited for executing scientific workflow applications. Since the cloud is not a utopian environment, failures are inevitable that may result in experiencing fluctuations in the delivered performance. Though a single task failure occurs in workflow based applications, due to its task dependency nature, the reliability of the overall system will be affected drastically. Hence rather than reactive fault-tolerant approaches, proactive measures are vital in scientific workflows. This work puts forth an attempt to concentrate on… More >

Nandhi Kesavan^*, Latha

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 327-337, 2023, DOI:10.32604/iasc.2023.030910

Abstract Climate change is the most serious causes and has a direct impact on biodiversity. According to the world’s biodiversity conservation organization, reptile species are most affected since their biological and ecological qualities are directly linked to climate. Due to a lack of time frame in existing works, conservation adoption affects the performance of existing works. The proposed research presents a knowledge-driven Decision Support System (DSS) including the assisted translocation to adapt to future climate change to conserving from its extinction. The Dynamic approach is used to develop a knowledge-driven DSS using machine learning by applying an ecological and biological variable… More >