Wen-Tsai Sung¹, Sung-Jung Hsiao^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3529-3548, 2022, DOI:10.32604/cmc.2022.020613

Abstract This research uses the improved Quantum Particle Swarm Optimization (QPSO) algorithm to build an Internet of Things (IoT) life comfort monitoring system based on wireless sensing networks. The purpose is to improve the quality of intelligent life. The functions of the system include automatic basketball court lighting system, monitoring of infants’ sleeping posture and accidental falls of the elderly, human thermal comfort measurement and other related life comfort services, etc. On the hardware system of the IoT, this research is based on the latest version of ZigBee 3.0, which uses optical sensors, 3-axis accelerometers, and temperature/humidity sensors in the IoT… More >

Palli Padmini¹, C. Paramasivam¹, G. Jyothish Lal², Sadeen Alharbi^3,*, Kaustav Bhowmick⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4027-4051, 2022, DOI:10.32604/cmc.2022.020065

Abstract The present work presents a statistical method to translate human voices across age groups, based on commonalities in voices of blood relations. The age-translated voices have been naturalized extracting the blood relation features e.g., pitch, duration, energy, using Mel Frequency Cepstrum Coefficients (MFCC), for social compatibility of the voice-impaired. The system has been demonstrated using standard English and an Indian language. The voice samples for resynthesis were derived from 12 families, with member ages ranging from 8–80 years. The voice-age translation, performed using the Pitch synchronous overlap and add (PSOLA) approach, by modulation of extracted voice features, was validated by… More >

Sung-Jung Hsiao¹, Wen-Tsai Sung^2,*

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 729-748, 2022, DOI:10.32604/iasc.2022.020332

Abstract In this study, a multisensory physiological measurement system was built with wireless transmission technology, using a DSPIC30F4011 as the master control center and equipped with physiological signal acquisition modules such as an electrocardiogram module, blood pressure module, blood oxygen concentration module, and respiratory rate module. The physiological data were transmitted wirelessly to Android-based mobile applications via the TCP/IP or Bluetooth serial ports of Wi-Fi. The Android applications displayed the acquired physiological signals in real time and performed a preliminary abnormity diagnosis based on the measured physiological data and built-in index diagnostic data provided by doctors, such as blood oxygen concentration,… More >

Adnan Ashraf¹, Abdulwahab Ali Almazroi², Waqas Haider Bangyal^3,*, Mohammed A. Alqarni⁴

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 191-206, 2022, DOI:10.32604/iasc.2022.015810

Abstract Particle Swarm Optimization (PSO) is a well-known extensively utilized algorithm for a distinct type of optimization problem. In meta-heuristic algorithms, population initialization plays a vital role in solving the classical problems of optimization. The population’s initialization in meta-heuristic algorithms urges the convergence rate and diversity, besides this, it is remarkably beneficial for finding the efficient and effective optimal solution. In this study, we proposed an enhanced variation of the PSO algorithm by using a quasi-random sequence (QRS) for population initialization to improve the convergence rate and diversity. Furthermore, this study represents a new approach for population initialization by incorporating the… More >

Yu Xue^1,*, Asma Aouari¹, Romany F. Mansour², Shoubao Su³

Journal of Cyber Security, Vol.3, No.2, pp. 117-124, 2021, DOI:10.32604/jcs.2021.017018

Abstract One of the main problems of machine learning and data mining is to develop a basic model with a few features, to reduce the algorithms involved in classification’s computational complexity. In this paper, the collection of features has an essential importance in the classification process to be able minimize computational time, which decreases data size and increases the precision and effectiveness of specific machine learning activities. Due to its superiority to conventional optimization methods, several metaheuristics have been used to resolve FS issues. This is why hybrid metaheuristics help increase the search and convergence rate of the critical algorithms. A… More >

A. Manjula^1,*, L. Kalaivani², M. Gengaraj²

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 451-465, 2021, DOI:10.32604/iasc.2021.016088

Abstract The fast-growing field of mechanical robotization necessitates a well-designed and controlled version of electric drives. The concept of control concerning mechanical characteristics also requires a methodology in which the system needs to be modeled precisely and deals with uncertainty. The proposed method provides the enhanced performance of Switched Reluctance Motor (SRM) by controlling its speed and minimized torque ripple. Proportional-Integral-Derivative (PID) controllers have drawn more attention in industry automation due to their ease and robustness. The performances are further improved by using fractional order (Non-integer) controllers. The Modified Particle Swarm Optimization (MPSO) based optimization approach is employed to acquire the… More >

Ahmed S. Ghiduk^1,*, Moheb R. Girgis³, Eman Hassan^2,4, Sultan Aljahdali¹

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 147-164, 2021, DOI:10.32604/iasc.2021.015708

Abstract Path-based testing involves two main steps: 1) finding all paths throughout the code under test; 2) creating a test suite to cover these paths. Unfortunately, covering all paths in the code under test is impossible. Path-based testing could be achieved by targeting a subset of all feasible paths that satisfy a given testing criterion. Then, a test suite is created to execute this paths subset. Generating those paths is a key problem in path testing. In this paper, a new path testing technique is presented. This technique employs Particle Swarm Optimization (PSO) for generating a set of paths to satisfy… More >

Haibo Liu^1,*, Yujie Dong², Fuzhong Wang¹

Energy Engineering, Vol.118, No.3, pp. 679-689, 2021, DOI: 10.32604/EE.2021.014630

Abstract For the problems of nonlinearity, uncertainty and low prediction accuracy in the gas outburst prediction of coal mining face, the least squares support vector machine (LSSVM) is proposed to establish the prediction model. Firstly, considering the inertia coefficients as global parameters lacks the ability to improve the solution for the traditional particle swarm optimization (PSO), an improved PSO (IPSO) algorithm is introduced to adjust different inertia weights in updating the particle swarm and solve the fitness to stagnate. Secondly, the penalty factor and kernel function parameter of LSSVM are searched automatically, and the regression accuracy and generalization performance is enhanced… More >

Omar Almomani^*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 409-429, 2021, DOI:10.32604/cmc.2021.016113

Abstract Network Intrusion Detection System (IDS) aims to maintain computer network security by detecting several forms of attacks and unauthorized uses of applications which often can not be detected by firewalls. The features selection approach plays an important role in constructing effective network IDS. Various bio-inspired metaheuristic algorithms used to reduce features to classify network traffic as abnormal or normal traffic within a shorter duration and showing more accuracy. Therefore, this paper aims to propose a hybrid model for network IDS based on hybridization bio-inspired metaheuristic algorithms to detect the generic attack. The proposed model has two objectives; The first one… More >

JIGANG LEI^1,#, ZHENYAO XU^2,#, SUKE LI¹, MENG LI¹, ZHIKAI WANG³, PING LI¹, JING WANG¹, YINGLU CHEN¹, XIAOLE SONG¹, CHENGJIE REN¹, MEIPING SHEN¹, CHENGXIANG DAI^1,*

BIOCELL, Vol.45, No.3, pp. 537-546, 2021, DOI:10.32604/biocell.2021.014569

Abstract Psoriasis is an autoimmune-related chronic inflammatory disease with an approximate prevalence of 2–3% around the world, involving increased keratinocyte proliferation. Indeed, Th17 cells and IL-17 play critical roles in the pathogenesis of psoriasis. The monoclonal antibodies against cytokines have been shown to have effectively immunosuppressive effects on human psoriasis. However, there are still some patients that have no response to these treatments. Some patients have even serious side-effects which may affect their life. Mesenchymal stem cells have the ability of immunosuppressive and anti-inflammatory effects, which may be an alternative therapy with more safety and efficacy for human psoriasis. Moreover, the… More >