Joddat Fatima^1,*, Amina Jameel², Muhammad Usman Akram³, Adeel Muzaffar Syed¹, Malaika Mushtaq³

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1489-1504, 2022, DOI:10.32604/iasc.2022.025935

Abstract The long twisted fragile tube, termed as spinal cord, can be named as the second vital organ of Central Nervous System (CNS), after brain. In human anatomy, all crucial life activities are controlled by CNS. The spinal cord does not only control the flow of information from the brain to rest of the body, but also takes charge of our reflexes control and the mobility of body. It keeps the body upright and acts as the main support for the flesh and bones. Spine deformity can occur by birth, due to aging, injury or spine surgery. In this research article,… More >

Henry Ugochukwu Ukwu^*, Kamil Yurtkan

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1819-1838, 2022, DOI:10.32604/iasc.2022.025695

Abstract The primary goal of this paper is to describe a proposed framework for identifying human face expressions. A methodology has been proposed and developed to identify facial emotions using an axes-angular feature extracted from facial landmarks for 4D dynamic facial expression video data. The 4D facial expression recognition (FER) problem is modeled as an unbalanced problem using the full video sequence. The proposed dataset includes landmarks that are positioned to be fiducial features: around the brows, eyes, nose, cheeks, and lips. Following the initial facial landmark preprocessing, feature extraction is carried out. Input feature vectors from gamma axes and magnitudes… More >

R. Meena^1,*, V. Thulasi Bai²

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1643-1658, 2022, DOI:10.32604/iasc.2022.025305

Abstract The Covid-19 outbreak has an unprecedented effects on people's daily lives throughout the world, causing immense stress amongst individuals owing to enhanced psychological disorders like depression, stress, and anxiety. Researchers have used social media data to detect behaviour changes in individuals with depression, postpartum changes and stress detection since it reveals critical aspects of mental and emotional diseases. Considerable efforts have been made to examine the psychological health of people which have limited performance in accuracy and demand increased training time. To conquer such issues, this paper proposes an efficient depression detection framework named Improved Chimp Optimization Algorithm based Convolution… More >

T. Vetriselvi^1,*, J. Albert Mayan², K. V. Priyadharshini³, K. Sathyamoorthy⁴, S. Venkata Lakshmi⁵, P. Vishnu Raja⁶

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1537-1551, 2022, DOI:10.32604/iasc.2022.025235

Abstract Recently, the bounteous amount of data/information has been available on the Internet which makes it very complicated to the customers to calculate the preferred data. Because the huge amount of data in a system is mandated to discover the most proper data from the corpus. Content summarization selects and extracts the related sentence depends upon the calculation of the score and rank of the corpus. Automatic content summarization technique translates from the higher corpus into smaller concise description. This chooses the very important level of the texts and implements the complete statistics summary. This paper proposes the novel technique that… More >

M. Sangeetha^1,*, S. Malathi²

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1587-1601, 2022, DOI:10.32604/iasc.2022.025192

Abstract Software testing is an effective means of verifying software stability and trustworthiness. It is essential in the software development process and needs a huge quantity of resources such as labor, money, and time. Automated software testing can be used to save manual work, shorten testing times, and improve testing performance. Recently, Software Bug Prediction (SBP) models have been developed to improve the software quality assurance (SQA) process through the prediction of bug parts. Advanced deep learning (DL) models can be used to classify faults in software parts. Because hyperparameters have a significant impact on the performance of any DL model,… More >

Yazeed Yasin Ghadi¹, Israr Akhter², Suliman A. Alsuhibany³, Tamara al Shloul⁴, Ahmad Jalal², Kibum Kim^5,*

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1455-1471, 2022, DOI:10.32604/iasc.2022.025013

Abstract Event detection systems are mainly used to observe and monitor human behavior via red green blue (RGB) images and videos. Event detection using RGB images is one of the challenging tasks of the current era. Human detection, position and orientation of human body parts in RGB images is a critical phase for numerous systems models. In this research article, the detection of human body parts by extracting context-aware energy features for event recognition is described. For this, silhouette extraction, estimation of human body parts, and context-aware features are extracted. To optimize the context-intelligence vector, we applied an artificial intelligence-based self-organized… More >

S. Rajagopal^1,*, T. Ramakrishnan², S. Vairaprakash³

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1927-1941, 2022, DOI:10.32604/iasc.2022.024998

Abstract Video capsule endoscope (VCE) is a developing methodology, which permits analysis of the full gastrointestinal (GI) tract with minimum intrusion. Although VCE permits for profound analysis, evaluating and analyzing for long hours of images is tiresome and cost-inefficient. To achieve automatic VCE-dependent GI disease detection, identifying the anatomical region shall permit for a more concentrated examination and abnormality identification in each area of the GI tract. Hence we proposed a hybrid (Long-short term memory-Visual Geometry Group network) LSTM-VGGNET based classification for the identification of the anatomical area inside the gastrointestinal tract caught by VCE images. The video input data is… More >

Arpit Jain^1,*, Adesh Kumar², Anand Prakash Shukla³, Hammam Alshazly⁴, Hela Elmannai⁵, Abeer D. Algarni⁵, Roushan Kumar⁶, Jitendra Yadav⁶

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 2007-2021, 2022, DOI:10.32604/iasc.2022.024770

Abstract Network on chip (NoC) is an integrated communication system on chip (SoC), efficiently connecting various intellectual property (IP) modules on a single die. NoC has been suggested as an enormously scalable solution to overcome the communication problems in SoC. The performance of NoC depends on several aspects in terms of area, latency, throughput, and power. In this paper, the 2D and 3D mesh NoC performance on Virtex-5 field-programmable gate array (FPGA) is studied. The design is carried in Xilinx ISE 14.7 and the behavior model is followed based on XY and XYZ routing for 2D and 3D mesh NoC respectively.… More >

A. Jameer Basha¹, N. Rajkumar², Mohammed A. AlZain³, Mehedi Masud⁴, Mohamed Abouhawwash^5,6,*

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1693-1706, 2022, DOI:10.32604/iasc.2022.024714

Abstract In the healthcare applications, Internet of Medical Things (IoMT) comforts the communication processes between the medical devices and the humans via wireless network. Moreover, this communication helps both the physicians and the patients to contact remotely for the diagnosis of the disease’s wearable devices sensor signals. However, IoMT system violates the privacy preserving of Patient’s Health Record (PHR) as well as self-sovereign identity of patient. In this regard, security action should be taken. Previous techniques used in IoMT are in lack of data consistency, confidentiality, and inaccessible of data. To overcome these issues, the fog computing-based technology is used in… More >

R. S. Latha¹, K. Venkatachalam², Jehad F. Al-Amri³, Mohamed Abouhawwash^4,5,*

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1803-1818, 2022, DOI:10.32604/iasc.2022.024539

Abstract Generation of massive data is increasing in big data industries due to the evolution of modern technologies. The big data industries include data source from sensors, Internet of Things, digital and social media. In particular, these big data systems consist of data extraction, preprocessing, integration, analysis, and visualization mechanism. The data encountered from the sources are redundant, incomplete and conflict. Moreover, in real time applications, it is a tedious process for the interpretation of all the data from different sources. In this paper, the gathered data are preprocessed to handle the issues such as redundant, incomplete and conflict. For that,… More >