Shahid Ali Mahar¹, Mumtaz Hussain Mahar¹, Javed Ahmed Mahar¹, Mehedi Masud², Muneer Ahmad³, NZ Jhanjhi^4,*, Mirza Abdur Razzaq¹

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 183-197, 2021, DOI:10.32604/iasc.2021.015755

Abstract Speech signal analysis for the extraction of speech elements is viable in natural language applications. Rhythm, intonation, stress, and tone are the elements of prosody. These features are essential in emotional speech, speech to speech, speech recognition, and other applications. The current study attempts to extract the pitch and duration from historical Sindhi sound clips using the functional contours model’s superposition. The sampled sound clips contained the speech of 273 undergraduates living in 5 districts of the Sindhi province. Several Python libraries are available for the application of this model. We used these libraries for the extraction of prosodic data… 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 >

Huijin Park, Soobin Ou, Jongwoo Lee^*

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 247-258, 2021, DOI:10.32604/iasc.2021.015274

Abstract Blind people are highly exposed to numerous dangers when they walk alone outside as they cannot obtain sufficient information about their surroundings. While proceeding along a crosswalk, acoustic signals are played, though such signals are often faulty or difficult to hear. The bollards can also be dangerous if they are not made with flexible materials or are located improperly. Therefore, since the blind cannot detect proper information about these obstacles while walking, their environment can prove to be dangerous. In this paper, we propose an object recognition system that allows the blind to walk safely outdoors. The proposed system can… More >

Quadri Noorulhasan Naveed¹, Ali M. Aseere¹, AbdulHafeez Muhammad², Saiful Islam³, Mohamed Rafik N. Qureshi³, Ansar Siddique^4,*, Mohammad Rashid Hussain¹, Samreen Shahwar⁵

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 111-129, 2021, DOI:10.32604/iasc.2021.015009

Abstract The escalating growth in digital technology is setting the stage for changes in university education, as E-learning brings students and faculties outside the contained classroom environment. While mobile learning is considered an emerging technology, there is comprehensive literature on mobile learning and its applications. However, there has been relatively little research on mobile learning recognition and readiness compared to mobile learning studies and implementations. The advent of mobile learning (M-learning) provides additional flexibility in terms of time and location. M-learning lacks an established place in university education. The influence of its critical success factors (CSFs) on the university education system… More >

Mohammed Abaker^1,*, Abdelzahir Abdelmaboud², Magdi Osman³, Mohammed Alghobiri⁴, Ahmed Abdelmotlab⁴

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 843-856, 2021, DOI:10.32604/iasc.2021.017714

Abstract The rock-fall is a natural hazard that results in many economic damages and human losses annually, and thus proactive policies to prevent rock-fall hazard are needed. Such policies require predicting the rock-fall occurrence and deciding to alert the road users at the appropriate time. Thus, this study develops a rock-fall early warning system based on logistic regression model. In this system, the logistic regression model is used to predict the rock-fall occurrence. The decision-making algorithm is used to classify the hazard levels and delivers early warning action. This study adopts two criteria to evaluate the system predictive performance, including overall… More >

Ibrahim B.M. Taha¹, Diaa-Eldin A. Mansour^2,*

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 739-752, 2021, DOI:10.32604/iasc.2021.017703

Abstract Power transformer is one of the more important components of electrical power systems. The early detection of transformer faults increases the power system reliability. Dissolved gas analysis (DGA) is one of the most favorite approaches used for power transformer fault prediction due to its easiness and applicability for online diagnosis. However, the imbalanced, insufficient and overlap of DGA dataset impose a challenge towards powerful and accurate diagnosis. In this work, a novel fault diagnosis for power transformers is introduced based on DGA by using data transformation and six optimized machine learning (OML) methods. Four data transformation techniques are used with… More >

Mohamed I. Mossad^1,*, Fahd A. banakhr¹, Sherif S. M. Ghoneim², Tarek A. AbdulFattah³, Mohamed Mahmoud Samy⁴

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 715-727, 2021, DOI:10.32604/iasc.2021.017534

Abstract This paper introduces voltage self-regulation of a variable speed single-phase induction generator-based wind energy conversion system (WECS) for stand-alone applications. The idea behind the voltage self-regulation technique proposed in this paper is adjusting the fixed capacitor’s effective value for exciting the single-phase induction generator. This adjustment is performed using an inexpensive Sinusoidal PWM (SPWM) switching circuit to short circuit the capacitor during different periods to make a virtual change of the capacitance value extracted from the fixed capacitor. That optimized fixed capacitor size is firstly determined using harmony search (HS) optimization technique. HS is also used to determine the capacitance… More >

Ayesha Maqbool^1,*, Farkhanda Afzal², Tauseef Rana³, Alina Mirza⁴

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 653-667, 2021, DOI:10.32604/iasc.2021.017506

Abstract This paper presents a co-operative, self-organisation method for Multiple Autonomous Vehicles aiming to share surveillance responsibilities. Spatial organization or formation configuration of multiple vehicles/agents’ systems is crucial for a team of agents to achieve their mission objectives. In this paper we present simple yet efficient thermodynamic inspired formation control framework. The proposed method autonomously allocates region of surveillance to each vehicle and also re-adjusts the area of their responsibilities during the mission. It provides framework for heterogeneous UAVs to scatter themselves optimally in order to provide maximum coverage of a given area. The method is inspired from a natural phenomenon… More >

Anshu Parashar^*, Nidhi Kalra, Jaskirat Singh, Raman Kumar Goyal

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 669-682, 2021, DOI:10.32604/iasc.2021.017478

Abstract Electrophysiological (EEG) signals provide good temporal resolution and can be effectively used to assess and diagnose children with Attention Deficit Hyperactivity Disorder (ADHD). This study aims to develop a machine learning model to classify children with ADHD and Healthy Controls. In this study, EEG signals captured under cognitive tasks were obtained from an open-access database of 60 children with ADHD and 60 Healthy Controls children of similar age. The regional contributions towards attaining higher accuracy are identified and further tested using three classifiers: AdaBoost, Random Forest and Support Vector Machine. The EEG data from 19 channels is taken as input… More >

Jinrong Hu¹, Lujin Li¹, Wenyi Yang², Zhe Wang³, Junhui Wang⁴, Yan Zhu^5,*

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 785-795, 2021, DOI:10.32604/iasc.2021.017467

Abstract The meridian theory, as an essential part of Traditional Chinese Medicine (TCM) fundamentals, provides an explanation of the spatial and functional relationship between the superficial part and the internal organs based on empiric observations. Cutaneous regions which are the body superficies on which the functions of the meridians are reflected, and the sites where the qi of the collateral’s spreads, play an important role in TCM clinical diagnosis and treatment of skin diseases. The survey of the literature on anatomical site, pathology in patients with skin disease, particularly in TCM perspective, clearly indicates that a better cutaneous region model and… More >