Adnan Muhammad Shah, KangYoon Lee^*

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1719-1735, 2022, DOI:10.32604/iasc.2022.019666 - 09 October 2021

Abstract Online physician reviews (OPRs) critically influence the patients’ consultation decisions on physician rating websites. The increasing number of OPRs contributes to the challenge of information overload. The worth of development needs to be explored further. Based on the OPRs collected from RateMDs and Healthgrades, and Plutchik’s wheel on human emotions framework, the purpose of this study was to examine the impact of emotional intensity (positive and negative) incorporated in OPRs on review helpfulness (RH). The proposed model was empirically tested using data from two physician rating websites and applying a mixed-methods approach (text mining and… More >

G. Prathiba^1,*, M. Santhi²

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1611-1626, 2022, DOI:10.32604/iasc.2022.018975 - 09 October 2021

Abstract High-quality, high-resolution flash ADCs are used in reliable VLSI (Very Large-Scale Integrated) circuits to minimize the power consumption. An analogue electrical signal is converted into a discrete-valued sequence by these ADCs. This paper proposes a four-bit 1.2GS/s low-power Clocked Flash ADC (C-FADC). A low-power Clocked-Improved Threshold Inverter Quantization (CITIQ) comparator, an Adaptive Bubble Free (ABF) logic circuit, and a compact Binary Encoder (BE) are all part of the presented structure. A clock network in the comparator circuit reduces skew and jitters, while an ABF logic circuit detects and corrects fourth order bubble faults detected from More >

Ao Xiong¹, Meng Chen^1,*, Shaoyong Guo¹, Yongjie Li², Yujing Zhao², Qinghai Ou³, Chuan Liu⁴, Siwen Xu⁵, Xiangang Liu⁶

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1641-1654, 2022, DOI:10.32604/iasc.2022.018881 - 09 October 2021

Abstract To solve the problem of energy consumption optimization of edge servers in the process of edge task unloading, we propose a task unloading algorithm based on reinforcement learning in this paper. The algorithm observes and analyzes the current environment state, selects the deployment location of edge tasks according to current states, and realizes the edge task unloading oriented to energy consumption optimization. To achieve the above goals, we first construct a network energy consumption model including servers’ energy consumption and link transmission energy consumption, which improves the accuracy of network energy consumption evaluation. Because of More >

S. Balammal@Geetha^*, R. Muthukkumar, V. Seenivasagam

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1737-1752, 2022, DOI:10.32604/iasc.2022.018822 - 09 October 2021

Abstract Content-Based Image Retrieval (CBIR) is an approach of retrieving similar images from a large image database. Recently CBIR poses new challenges in semantic categorization of the images. Different feature extraction technique have been proposed to overcome the semantic breach problems, however these methods suffer from several shortcomings. This paper contributes an image retrieval system to extract the local features based on the fusion of scale-invariant feature transform (SIFT) and KAZE. The strength of local feature descriptor SIFT complements global feature descriptor KAZE. SIFT concentrates on the complete region of an image using high fine points… More >

K. Ambika^1,*, M. Balasingh Moses²

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1809-1823, 2022, DOI:10.32604/iasc.2022.018580 - 09 October 2021

Abstract In addition to replacing desktop-based methods, cloud computing is playing a significant role in several areas of data management. The health care industry, where so much data is needed to be handled correctly, is another arena in which artificial intelligence has a big role to play. The upshot of this innovation led to the creation of multiple healthcare clouds. The challenge of data privacy and confidentiality is the same for different clouds. Many existing works has provided security framework to ensure the security of data in clouds but still the drawback on revocation, resisting collusion… More >

Umanesan Ramakrishnan^1,*, Nandhagopal Nachimuthu²

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1547-1559, 2022, DOI:10.32604/iasc.2022.017123 - 09 October 2021

Abstract Recently, various research fields have begun dealing with massive datasets forseveral functions. The main aim of a feature selection (FS) model is to eliminate noise, repetitive, and unnecessary featuresthat reduce the efficiency of classification. In a limited period, traditional FS models cannot manage massive datasets and filterunnecessary features. It has been discovered from the state-of-the-art literature that metaheuristic algorithms perform better compared to other FS wrapper-based techniques. Common techniques such as the Genetic Algorithm (GA) andParticle Swarm Optimization (PSO) algorithm, however, suffer from slow convergence and local optima problems. Even with new generation algorithms such… More >

Zhen Xu¹, Xiaoqian Zeng¹, Genlin Ji^1,*, Bo Sheng²

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1703-1717, 2022, DOI:10.32604/iasc.2022.016919 - 09 October 2021

Abstract Anomaly detection in surveillance videos is an extremely challenging task due to the ambiguous definitions for abnormality. In a complex surveillance scenario, the kinds of abnormal events are numerous and might co-exist, including such as appearance and motion anomaly of objects, long-term abnormal activities, etc. Traditional video anomaly detection methods cannot detect all these kinds of abnormal events. Hence, we utilize multiple probabilistic models inference to detect as many different kinds of abnormal events as possible. To depict realistic events in a scene, the parameters of our methods are tailored to the characteristics of video… More >

Jui-Chung Kao¹, Chia-Nan Wang^2,*, Viet Tinh Nguyen³ and Syed Tam Husain³

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1451-1466, 2022, DOI:10.32604/iasc.2022.021778 - 09 October 2021

Abstract According to a new study by the International Labor Organization (ILO), the COVID-19 pandemic has had a strong impact on the garment industry in the Asia-Pacific region. A sharp drop in retail sales in key export markets has affected workers and businesses across supply chains. To ensure the effectiveness and efficiency of garment supply chain, choosing a sustainable supplier should be a main concern of all businesses. The supplier selection problem in garment industry involves multiple quantitative and qualitative criteria. There have been many research and literatures about the development and application of Multicriteria Decision… More >

Hashem Alyami¹, Mohd Nadeem², Wael Alosaimi³, Abdullah Alharbi³, Rajeev Kumar^4,*, Bineet Kumar Gupta⁴, Alka Agrawal², Raees Ahmad Khan²

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 707-716, 2022, DOI:10.32604/iasc.2022.020780 - 22 September 2021

Abstract Software or web application security is the main objective in the era of Information Technology (IT) and Artificial Intelligence (AI). Distinguishing proof of security at the initial stage produces significant results to comprehend the administration of security relics for best potential outcomes. A security alternative gives several methods and algorithms to ensure the software security. Security estimation is the vital factor in assessing, administrating, controlling security to improve the nature of security. It is to be realized that assessment of security at early stage of development helps in identifying distinctive worms, dangers, weaknesses and threats.… More >

Wen-Tsai Sung¹, Sung-Jung Hsiao^2,*, Chung-Yen Hsiao¹

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1223-1240, 2022, DOI:10.32604/iasc.2022.020746 - 22 September 2021

Abstract This research is based on the system architecture of Edge Computing in the AIoT (Artificial Intelligence & Internet of Things) field. In terms of receiving data, the authors proposed approach employed the camera module as the video source, the ultrasound module as the distance measurement source, and then compile C++ with Raspberry Pi 4B for image lane analysis, while Jetson Nano uses the YOLOv3 algorithm for image object detection. The analysis results of the two single-board computers are transmitted to Motoduino U1 in binary form via GPIO, which is used for data integration and load… More >