Journals / IASC / Vol.32, No.1

  • ARTICLE

    Optimized U-Net Segmentation and Hybrid Res-Net for Brain Tumor MRI Images Classification

    R. Rajaragavi1,*, S. Palanivel Rajan2
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 1-14, 2022, DOI:10.32604/iasc.2022.021206
    Abstract A brain tumor is a portion of uneven cells, need to be detected earlier for treatment. Magnetic Resonance Imaging (MRI) is a routinely utilized procedure to take brain tumor images. Manual segmentation of tumor is a crucial task and laborious. There is a need for an automated system for segmentation and classification for tumor surgery and medical treatments. This work suggests an efficient brain tumor segmentation and classification based on deep learning techniques. Initially, Squirrel search optimized bidirectional ConvLSTM U-net with attention gate proposed for brain tumour segmentation. Then, the Hybrid Deep ResNet and Inception Model used for classification. Squirrel… More >

  • ARTICLE

    Personalized Information Retrieval from Friendship Strength of Social Media Comments

    Fiaz Majeed1, Noman Yousaf2, Muhammad Shafiq3,*, Mohammed Ahmed Basheikh4, Wazir Zada Khan5, Akber Abid Gardezi6, Waqar Aslam7, Jin-Ghoo Choi3
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 15-30, 2022, DOI:10.32604/iasc.2022.015685
    (This article belongs to this Special Issue: Soft Computing Methods for Innovative Software Practices)
    Abstract Social networks have become an important venue to express the feelings of their users on a large scale. People are intuitive to use social networks to express their feelings, discuss ideas, and invite folks to take suggestions. Every social media user has a circle of friends. The suggestions of these friends are considered important contributions. Users pay more attention to suggestions provided by their friends or close friends. However, as the content on the Internet increases day by day, user satisfaction decreases at the same rate due to unsatisfactory search results. In this regard, different recommender systems have been developed… More >

  • ARTICLE

    Heart Disease Diagnosis Using Electrocardiography (ECG) Signals

    V. R. Vimal1,*, P. Anandan2, N. Kumaratharan3
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 31-43, 2022, DOI:10.32604/iasc.2022.017622
    Abstract

    Electrocardiogram (ECG) monitoring models are commonly employed for diagnosing heart diseases. Since ECG signals are normally acquired for a longer time duration with high resolution, there is a need to compress the ECG signals for transmission and storage. So, a novel compression technique is essential in transmitting the signals to the telemedicine center to monitor and analyse the data. In addition, the protection of ECG signals poses a challenging issue, which encryption techniques can resolve. The existing Encryption-Then-Compression (ETC) models for multimedia data fail to properly maintain the trade-off between compression performance and signal quality. In this view, this study… More >

  • ARTICLE

    Automated Learning of ECG Streaming Data Through Machine Learning Internet of Things

    Mwaffaq Abu-Alhaija, Nidal M. Turab*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 45-53, 2022, DOI:10.32604/iasc.2022.021426
    Abstract Applying machine learning techniques on Internet of Things (IoT) data streams will help achieve better understanding, predict future perceptions, and make crucial decisions based on those analytics. The collaboration between IoT, Big Data and machine learning can be found in different domains such as Health care, Smart cities, and Telecommunications. The aim of this paper is to develop a method for automated learning of electrocardiogram (ECG) streaming data to detect any heart beat anomalies. A promising solution is to use medical sensors that transfer vital signs to medical care computer systems, combined with machine learning, such that clinicians can get… More >

  • ARTICLE

    Development of IoT Based Fish Monitoring System for Aquaculture

    Abu Taher Tamim1, Halima Begum1, Sumaiya Ashfaque Shachcho1, Mohammad Monirujjaman Khan1,*, Bright Yeboah-Akowuah2, Mehedi Masud3, Jehad F. Al-Amri4
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 55-71, 2022, DOI:10.32604/iasc.2022.021559
    Abstract Aquaculture mainly refers to cultivating aquatic organisms providing suitable environments for various purposes, including commercial, recreational, public purposes. This paper aims to enhance the production of fish and maintain the aquatic environment of aquaculture in Bangladesh. This paper presents the way of using Internet of Things (IoT) based devices to monitor aquaculture’s basic needs and help provide things needed for the fisheries. Using these devices, various parameters of water will be monitored for a better living environment for fish. These devices consist of some sensors that will detect the Potential of Hydrogen (pH) level, the water temperature, and there will… More >

  • ARTICLE

    Target Classification of Marine Debris Using Deep Learning

    Anum Aleem1, Samabia Tehsin1,*, Sumaira Kausar1, Amina Jameel2
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 73-85, 2022, DOI:10.32604/iasc.2022.021583
    Abstract Marine Debris is human-created waste dumped into the sea or ocean. It pollutes the aquatic environment and hence very dangerous for ocean species. Removal of marine debris from ocean is necessary to eliminate pollution and to secure aquatic life. A robust and automatic system is essential that detects unnecessary litter of plastic and other garbage at real-time. In this study, we have proposed deep learning based architecture for the detection and classification of marine debris. Histogram Equalization technique combined with Median Filter is used to enhance the contrast of images and to remove noise. Experiments are performed on challenging Forward… More >

  • ARTICLE

    Deriving Driver Behavioral Pattern Analysis and Performance Using Neural Network Approaches

    Meenakshi Malik1, Rainu Nandal1,*, Surjeet Dalal2, Vivek Jalglan3, Dac-Nhuong Le4,5
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 87-99, 2022, DOI:10.32604/iasc.2022.020249
    (This article belongs to this Special Issue: Intelligence 4.0: Concepts and Advances in Computational Intelligence)
    Abstract It has been observed that driver behavior has a direct and considerable impact upon factors like fuel consumption, environmentally harmful emissions, and public safety, making it a key consideration of further research in order to monitor and control such related hazards. This has fueled our decision to conduct a study in order to arrive at an efficient way of analyzing the various parameters of driver behavior and find ways and means of positively impacting such behavior. It has been ascertained that such behavioral patterns can significantly impact the analysis of traffic-related conditions and outcomes. In such cases, the specific vehicular… More >

  • ARTICLE

    Prevention of Runtime Malware Injection Attack in Cloud Using Unsupervised Learning

    M. Prabhavathy1,*, S. UmaMaheswari2
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 101-114, 2022, DOI:10.32604/iasc.2022.018257
    Abstract Cloud computing utilizes various Internet-based technologies to enhance the Internet user experience. Cloud systems are on the rise, as this technology has completely revolutionized the digital industry. Currently, many users rely on cloud-based solutions to acquire business information and knowledge. As a result, cloud computing services such as SaaS and PaaS store a warehouse of sensitive and valuable information, which has turned the cloud systems into the obvious target for many malware creators and hackers. These malicious attackers attempt to gain illegal access to a myriad of valuable information such as user personal information, password, credit/debit card numbers, etc., from… More >

  • ARTICLE

    Heart Failure Patient Survival Analysis with Multi Kernel Support Vector Machine

    R. Sujatha1, Jyotir Moy Chatterjee2, NZ Jhanjhi3, Thamer A. Tabbakh4, Zahrah A. Almusaylim5,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 115-129, 2022, DOI:10.32604/iasc.2022.019133
    Abstract Heart failure (HF) is an intercontinental pandemic influencing in any event 26 million individuals globally and is expanding in commonness. HF healthiness consumptions are extensive and will increment significantly with a maturing populace. As per the World Health Organization (WHO), Cardiovascular diseases (CVDs) are the major reason for all-inclusive death, taking an expected 17.9 million lives per year. CVDs are a class of issues of the heart, blood vessels and include coronary heart sickness, cerebrovascular illness, rheumatic heart malady, and various other conditions. In the medical care industry, a lot of information is as often as possible created. Nonetheless, it… More >

  • ARTICLE

    Deep Learning-Based Decoding and AP Selection for Radio Stripe Network

    Aman Kumar Mishra, Vijayakumar Ponnusamy*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 131-148, 2022, DOI:10.32604/iasc.2022.021017
    Abstract

    Cell-Free massive MIMO (mMIMO) offers promising features such as higher spectral efficiency, higher energy efficiency and superior spatial diversity, which makes it suitable to be adopted in beyond 5G (B5G) networks. However, the original form of Cell-Free massive MIMO requires each AP to be connected to CPU via front haul (front-haul constraints) resulting in huge economic costs and network synchronization issues. Radio Stripe architecture of cell-free mMIMO is one such architecture of cell-free mMIMO which is suitable for practical deployment. In this paper, we propose DNN Based Parallel Decoding in Radio Stripe (DNNBPDRS) to decode the symbols of User Equipments… More >

  • ARTICLE

    A Multi-Simplex Imperialist Competitive Paradigm for Solving Nonlinear Physical Systems

    Javaid Ali1, Shaukat Iqbal2, Salem Alkhalaf3,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 149-166, 2022, DOI:10.32604/iasc.2022.021788
    Abstract This paper proposes a novel gradient free multi-simplex topology fabric aided imperialist competitive algorithm (ICA) for solving nonlinear systems of algebraic equations by transforming them to equivalent global optimization problems. The high dependence of traditional gradient based solvers of such systems on initial guesses and the Jacobeans resulting in false convergence is the main motivation behind the present work. The present work provides a mechanism for enhancing exploitation powers of imperialist search phase of the algorithm and hence improves the convergence speed. The variants emerging from the proposed approach are applied to diverse nonlinear systems arising in different scientific areas… More >

  • ARTICLE

    Analysis of Inventory Model for Quadratic Demand with Three Levels of Production

    Dharamender Singh1, Majed G. Alharbi2, Anurag Jayswal1, Ali Akbar Shaikh3,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 167-182, 2022, DOI:10.32604/iasc.2022.021815
    Abstract The inventory framework is one of the standards of activity research fundamentals in ventures and business endeavors. Production planning includes all building production plans, including organizing and appointing exercises to every individual, gathering individuals or machines, and mastering work orders in every work environment. Production booking should take care of all issues, for example, limiting client standby time and production time; and viably utilizing the undertaking’s HR. This paper considered three degrees of a production inventory model for a consistent deterioration rate. This model assumes a significant part in the production of the board and assembling units. Request rate is… More >

  • ARTICLE

    Video Surveillance-Based Urban Flood Monitoring System Using a Convolutional Neural Network

    R. Dhaya1,*, R. Kanthavel2
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 183-192, 2022, DOI:10.32604/iasc.2022.021538
    Abstract The high prevalence of urban flooding in the world is increasing rapidly with the rise in extreme weather events. Consequently, this research uses an Automatic Flood Monitoring System (ARMS) through a video surveillance camera. Initially, videos are collected from a surveillance camera and converted into video frames. After converting the video frames, the water level can be identified by using a Histogram of oriented Gradient (HoG), which is used to remove the functionality. Completing the extracted features, the frames are enhanced by using a median filter to remove the unwanted noise from the image. The next step is water level… More >

  • ARTICLE

    Strengthening Software Make vs. Buy Decision: A Mixed-Method Approach

    Farooq Javeed1, Basit Shahzad2, Asadullah Shaikh3, Mana Saleh Al Reshan3,*, Saba Ahmad1, Hani Alshahrani3, Khairan Rajab3
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 193-205, 2022, DOI:10.32604/iasc.2022.021769
    Abstract Over the past few decades, multiple software development process models, tools, and techniques have been used by practitioners. Despite using these techniques, most software development organizations still fail to meet customer’s needs within time and budget. Time overrun is one of the major reasons for project failure. There is a need to come up with a comprehensive solution that would increase the chances of project success. However, the “make vs. buy” decision can be helpful for “in time” software development. Social media have become a popular platform for discussion of all sorts of topics, so software development is no exception.… More >

  • ARTICLE

    Optimization of Heat Treatment Scheduling for Hot Press Forging Using Data-Driven Models

    Seyoung Kim1, Jeonghoon Choi1, Kwang Ryel Ryu2,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 207-220, 2022, DOI:10.32604/iasc.2022.021752
    Abstract Scheduling heat treatment jobs in a hot press forging factory involves forming batches of multiple workpieces for the given furnaces, determining the start time of heating each batch, and sorting out the order of cooling the heated workpieces. Among these, forming batches is particularly difficult because of the various constraints that must be satisfied. This paper proposes an optimization method based on an evolutionary algorithm to search for a heat treatment schedule of maximum productivity with minimum energy cost, satisfying various constraints imposed on the batches. Our method encodes a candidate solution as a permutation of heat treatment jobs and… More >

  • ARTICLE

    Scrambling Based Riffle Shift on Stego-Image to Channelize the Ensured Data

    R. Bala Krishnan1, M. M. Anishin Raj2, N. Rajesh Kumar1, B. Karthikeyan3, G. Manikandan3,*, N. R. Raajan4
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 221-235, 2022, DOI:10.32604/iasc.2022.021775
    Abstract In recent years information hiding has got much attention as it acts as an alternate option for secured communication. The Secret content would get imbedded with the image using various possible image embodiment techniques, in which the Least Significant Bit (LSB) substitution is one of the preferred content embodiment strategy; however, asserting the quality and the originality of the content embedded image (stego) is yet a grievous concern in the field of Information Security. In this article, a proficient Scrambling Based Haar Wavelet Transform (SBHWT) approach has been sought to ensure the novelty of the stego-image that supports the safe… More >

  • ARTICLE

    Applying t-SNE to Estimate Image Sharpness of Low-cost Nailfold Capillaroscopy

    Hung-Hsiang Wang1, Chih-Ping Chen2,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 237-254, 2022, DOI:10.32604/iasc.2022.020665
    (This article belongs to this Special Issue: Soft Computing Methods for Intelligent Automation Systems)
    Abstract Machine learning can classify the image clarity of low-cost nailfold capillaroscopy (NC) and can be applied to the design verification for other medical devices. The method can be beneficial for systems that require a large number of image datasets. This investigation covers the design, integration, image sharpness estimation, and deconvolution sharpening of the NC. The study applies this device to record two videos and extract 600 photos, including blurry and sharp images. It then uses the Laplace operator method for blur detection of the pictures. Statistics are recorded for each image’s Laplace score and the distribution of clear photos in… More >

  • ARTICLE

    IoT-Based Reusable Medical Suit for Daily Life Use in the Era of COVID-19

    Abdelhamied A. Ateya1,2, Abeer D. Algarni1, Hanaa A. Abdallah1,2, Naglaa F. Soliman1,2,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 255-270, 2022, DOI:10.32604/iasc.2022.021322
    Abstract Coronavirus disease (COVID-19) is a big problem that scares people all over the world. Life over the world has changed, new aspects for daily life have been introduced. A main problem with COVID-19 is the way it spreads. Covid-19 spreads, primarily, through contact with an infected person when they cough or sneeze, or with an infected surface. Thus, a novel way to make a protection against COVID-19 is to stay away or make yourself isolated from infected people and surfaces. To this end, this work, mainly, aims to design and develop a novel auto-sterilized suit embedded with some medical sensors… More >

  • ARTICLE

    Restoration of Adversarial Examples Using Image Arithmetic Operations

    Kazim Ali*, Adnan N. Quershi
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 271-284, 2022, DOI:10.32604/iasc.2022.021296
    Abstract The current development of artificial intelligence is largely based on deep Neural Networks (DNNs). Especially in the computer vision field, DNNs now occur in everything from autonomous vehicles to safety control systems. Convolutional Neural Network (CNN) is based on DNNs mostly used in different computer vision applications, especially for image classification and object detection. The CNN model takes the photos as input and, after training, assigns it a suitable class after setting traceable parameters like weights and biases. CNN is derived from Human Brain's Part Visual Cortex and sometimes performs even better than Haman visual system. However, recent research shows… More >

  • ARTICLE

    Evaluation of Natural Language Software Interfaces to Databases

    Fiaz Majeed1, Muhammad Shoaib2, Monagi H. Alkinani3, Wazir Zada Khan4, Shahzada Khurram5, Akber Abid Gardezi6, Muhammad Shafiq7,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 285-299, 2022, DOI:10.32604/iasc.2022.015488
    (This article belongs to this Special Issue: Soft Computing Methods for Innovative Software Practices)
    Abstract Relational databases are still important in modern times due to their many advantages, such as ease of interaction, simplicity and data integrity. In this regard, structured query language (SQL) and technical knowledge about database schemas are the basic building blocks for retrieving information from relational databases. Generally, non-expert users cannot skillfully write technical queries on the target database. To this end, many database natural language interfaces (NLIDB) have been developed to greatly facilitate users. However, each system provides a different interface for new users, so beginners can use different interactive modes to enter keyword-based queries. For users, migrating from one… More >

  • ARTICLE

    A Morphological Image Segmentation Algorithm for Circular Overlapping Cells

    Fuchu Zhang1, Yanpeng Wu2,*, Miaoqing Xu2, Sanjun Liu3, Changling Peng2, Zhichen Gao4
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 301-321, 2022, DOI:10.32604/iasc.2022.021929
    Abstract Cell segmentation is an important topic in medicine. A cell image segmentation algorithm based on morphology is proposed. First, some morphological operations, including top-hat transformation, bot-hat transformation, erosion operation, dilation operation, opening operation, closing operation, majority operation, skeleton operation, etc., are applied to remove noise or enhance cell images. Then the small blocks in the cell image are deleted as noise, the medium blocks are removed and saved as normal cells, and the large blocks are segmented as overlapping cells. Each point on the edge of the overlapping cell area to be divided is careful checked. If the shape of… More >

  • ARTICLE

    Intrusion Detection System for Energy Efficient Cluster Based Vehicular Adhoc Networks

    R. Lavanya1,*, S. Kannan2
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 323-337, 2022, DOI:10.32604/iasc.2022.021467
    Abstract A vehicular ad hoc network (VANET), a subfield of mobile adhoc network (MANET) is defined by its high mobility by demonstrating the dissimilar mobility patterns. So, VANET clustering techniques are needed with the consideration of the mobility parameters amongst the nearby nodes for constructing the stable clustering techniques. At the same time, security is also a major design issue in VANET, this can be resolved by the intrusion detection systems (IDS). In contrast to the conventional IDS, VANET based IDS are required to be designed in such a way that the functioning of the system does not affect the real-time… More >

  • ARTICLE

    Machine Learning for Modeling and Control of Industrial Clarifier Process

    M. Rajalakshmi1, V. Saravanan2, V. Arunprasad3, C. A. T. Romero4, O. I. Khalaf5, C. Karthik1,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 339-359, 2022, DOI:10.32604/iasc.2022.021696
    (This article belongs to this Special Issue: Soft Computing Methods for Intelligent Automation Systems)
    Abstract In sugar production, model parameter estimation and controller tuning of the nonlinear clarification process are major concerns. Because the sugar industry’s clarification process is difficult and nonlinear, obtaining the exact model using identification methods is critical. For regulating the clarification process and identifying the model parameters, this work presents a state transition algorithm (STA). First, the model parameters for the clarifier are estimated using the normal system identification process. The STA is then utilized to improve the accuracy of the system parameters that have been identified. Metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and State Transition… More >

  • ARTICLE

    Massive MIMO Codebook Design Using Gaussian Mixture Model Based Clustering

    S. Markkandan1,*, S. Sivasubramanian2, Jaison Mulerikkal3, Nazeer Shaik4, Beulah Jackson5, Lakshmi Naryanan6
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 361-375, 2022, DOI:10.32604/iasc.2022.021779
    Abstract The codebook design is the most essential core technique in constrained feedback massive multi-input multi-output (MIMO) system communications. MIMO vectors have been generally isotropic or evenly distributed in traditional codebook designs. In this paper, Gaussian mixture model (GMM) based clustering codebook design is proposed, which is inspired by the strong classification and analytical abilities of clustering techniques. Huge quantities of channel state information (CSI) are initially saved as entry data of the clustering process. Further, split into N number of clusters based on the shortest distance. The centroids part of clustering has been utilized for constructing a codebook with statistic… More >

  • ARTICLE

    Heart Rate Detection Using SVM Based on Video Imagery

    Wu Zeng1, Yi Sheng1,*, Qiuyu Hu1, Zhanxiong Huo1, Yingge Zhang1, Yuxuan Xie2
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 377-387, 2022, DOI:10.32604/iasc.2022.017748
    Abstract According to the World Health Organization, the death rate of cardiovascular diseases ranks first in the composition of disease deaths. Research shows that the heart rate can be employed as an important physiological parameter to measure the health status of people’s cardiac health. A pressure pulse is formed by the periodic beating and contraction of the heart, so its rate and the pressure pulse signal have a distinct synchronous periodicity. Certain wavelengths of light are known to be absorbed by the capillaries in the human skin, where this absorption fluctuates in accordance with the heartbeat as the capillary blood volume… More >

  • ARTICLE

    COVID-19 Cases Prediction in Saudi Arabia Using Tree-based Ensemble Models

    Abdulwahab Ali Almazroi1, Raja Sher Afgun Usmani2,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 389-400, 2022, DOI:10.32604/iasc.2022.020588
    Abstract COVID-19 pandemic has affected more than 144 million people and spread to over 200 countries. The prediction of COVID-19 behaviour and trend is crucial to prevent its spreading. Kingdom of Saudi Arabia (KSA) is Asia’s fifth largest country, and it hosts the two holiest cities of the Islamic world. KSA hosts millions of pilgrims every year, and it is of great importance to predict the COVID-19 spread to organize these religious activities and bring life to normality in KSA. This study proposes four tree-based ensemble methods to predict the COVID-19 daily new cases in KSA. Tree-based ensemble methods are suggested… More >

  • ARTICLE

    Fully Authentication Services Scheme for NFC Mobile Payment Systems

    Munefah Alshammari*, Shadi Nashwan
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 401-428, 2022, DOI:10.32604/iasc.2022.022065
    Abstract One commonly used wireless communication technology is Near-Field Communication (NFC). Smartphones that support this technology are used in contactless payment systems as identification devices to emulate credit cards. This technology has essentially focused on the quality of communication services and has somewhat disregarded security services. Communication messages between smartphones, the point of sale (POS), and service providers are susceptible to attack due to existing weaknesses, including that an adversary can access, block and modify the transmitted messages to achieve illegal goals. Therefore, there have been many research proposals in regards to authentication schemes for NFC communications in order to prevent… More >

  • ARTICLE

    Intelligent Agriculture Technology Based on Internet of Things

    Lili Sun1, Hairui Sun2, Ning Cao1, Xiuli Han3, Guangsheng Cao3, Wei Huo3, Dongjie Zhu4,*, Russell Higgs5
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 429-439, 2022, DOI:10.32604/iasc.2022.021526
    Abstract Although the application of agricultural product traceability technology is a key point to realize Modern Agricultural IoT, it has still encountered various food safety problems. For example, immature environmental monitoring technology of agricultural products, weak product traceability and imperfect product monitoring equipment. For this reason, this paper studies and compares several emerging technologies of the things Internet, then it analyzes the functional diversity and practicability of the Modern Agricultural IoT. It builds the experimental environment based on the agricultural product traceability technology, so as to realize the monitoring of crop growth environment and traceability. The result plays a positive role… More >

  • ARTICLE

    Requirement Design for Software Configuration and System Modeling

    Waqar Mehmood1, Abdul Waheed Khan2, Waqar Aslam3, Shafiq Ahmad4, Ahmed M. El-Sherbeeny4, Muhammad Shafiq5,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 441-454, 2022, DOI:10.32604/iasc.2022.016116
    (This article belongs to this Special Issue: Soft Computing Methods for Innovative Software Practices)
    Abstract Software Configuration Management (SCM) aims to control the development of complex software systems. Traditional SCM systems treat text files as central artifacts, so they are mainly developed for source code. Such a system is not suitable for model-based software development with model-centric artifacts. When applying traditional systems to model-based software development, new challenges such as model mapping, differentiation, and merging arise. Many existing methods mainly use UML or domain-specific languages to determine model differences. However, as far as we know, there is no such technology for System Modeling Language (SysML) models. SysML covers the entire development life cycle of various… More >

  • ARTICLE

    Design and Realization of Non Invasive Fetal ECG Monitoring System

    Abdulfattah Noorwali1, Ameni Yengui2,*, Kaiçar Ammous2, Anis Ammous1
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 455-466, 2022, DOI:10.32604/iasc.2022.020574
    Abstract Early fetal cardiac diseases and heart abnormalities can be detected and appropriately treated by monitoring fetal health during pregnancy. Advancements in computer sciences and the technology of sensors show that is possible to monitor fetal electrocardiogram (fECG). Both signal processing and experimental aspects are needed to be investigated to monitor fECG. In this study, we aim to design and realize a non invasive fECG monitoring system. In the first part of this work, a remote study process of the electrical activity of the heart is achieved. In fact, our proposed design considers transmitting the detected signals in real time using… More >

  • ARTICLE

    Massive IoT Malware Classification Method Using Binary Lifting

    Hae-Seon Jeong1, Jin Kwak2,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 467-481, 2022, DOI:10.32604/iasc.2022.021038
    Abstract Owing to the development of next-generation network and data processing technologies, massive Internet of Things (IoT) devices are becoming hyperconnected. As a result, Linux malware is being created to attack such hyperconnected networks by exploiting security threats in IoT devices. To determine the potential threats of such Linux malware and respond effectively, malware classification through an analysis of the executed code is required; however, a limitation exists in that each heterogeneous architecture must be analyzed separately. However, the binary codes of a heterogeneous architecture can be translated to a high-level intermediate representation (IR) of the same format using binary lifting… More >

  • ARTICLE

    Coronavirus Decision-Making Based on a Locally -Generalized Closed Set

    M. A. El Safty1,*, S. A. Alblowi2, Yahya Almalki3, M. El Sayed4
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 483-498, 2022, DOI:10.32604/iasc.2022.021581
    (This article belongs to this Special Issue: Intelligence 4.0: Concepts and Advances in Computational Intelligence)
    Abstract Real-world applications now deal with a massive amount of data, and information about the world is inaccurate, incomplete, or uncertain. Therefore, we present in our paper a proposed model for solving problems. This model is based on the class of locally generalized closed sets, namely, locally simply* alpha generalized closed* sets and locally simply* alpha generalized closed** sets (briefly, -sets and -sets), based on simply* alpha open set. We also introduce various concepts of their properties and their relationship with other types, and we are studying several of their properties. Finally, we apply the concept of the simply* alpha open… More >

  • ARTICLE

    A Mathematical Optimization Model for Maintenance Planning of School Buildings

    Mehdi Zandiyehvakili1, Babak Aminnejad2,*, Alireza Lork3
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 499-512, 2022, DOI:10.32604/iasc.2022.021461
    (This article belongs to this Special Issue: Soft Computing and Machine Learning in Industrial Systems)
    Abstract This article presents a methodology to optimize the maintenance planning model and minimize the total maintenance costs of a typical school building. It makes an effort to provide a maintenance schedule, focusing on maintenance costs. In the allocation of operations to the school equipment, the parameter of its age was also taken into account. A mathematical optimization model to minimize the school maintenance cost in a three-year period was provided in the GAMS software with CPLEX solver. Finally, the optimum architecture of the Perceptron multi-layer neural network was used to predict the schedule of equipment operations and maintenance costs. The… More >

  • ARTICLE

    Process Optimization Method for Day Ward Based on Bayesian Decision-Tree

    Ting Chen1, Kai Pu2, Lanzhen Bian3, Min Rao4, Jing Hu5, Rugang Lu1,*, Jinyue Xia6
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 513-523, 2022, DOI:10.32604/iasc.2022.022510
    Abstract The day surgery management mode is mainly decentralized management, with clinical departments as the unit, and with reference to the experience of inter project operation management in benchmark hospitals, the empirical management is implemented. With the development of day surgery, the extensive decentralized management mode has been unable to meet the needs of the current day surgery development situation. At first, the paper carefully analyzes the existing problems in the day surgery process in the day ward of the Children’s Hospital of Nanjing Medical University. And then, the concerns of doctors, nurses, anesthesiologists and other hospital staff in day ward,… More >

  • ARTICLE

    Prediction of Suitable Candidates for COVID-19 Vaccination

    R. Sujatha1, B. Venkata Siva Krishna1, Jyotir Moy Chatterjee2, P. Rahul Naidu1, NZ Jhanjhi3,*, Challa Charita1, Eza Nerin Mariya1, Mohammed Baz4
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 525-541, 2022, DOI:10.32604/iasc.2022.021216
    Abstract In the current times, COVID-19 has taken a handful of people’s lives. So, vaccination is crucial for everyone to avoid the spread of the disease. However, not every vaccine will be perfect or will get success for everyone. In the present work, we have analyzed the data from the Vaccine Adverse Event Reporting System and understood that the vaccines given to the people might or might not work considering certain demographic factors like age, gender, and multiple other variables like the state of living, etc. This variable is considered because it explains the unmentioned variables like their food habits and… More >

  • ARTICLE

    Modernization Framework to Enhance the Security of Legacy Information Systems

    Musawwer Khan1, Islam Ali1, Wasif Nisar1, Muhammad Qaiser Saleem2, Ali S. Ahmed2, Haysam E. Elamin3, Waqar Mehmood4, Muhammad Shafiq5,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 543-555, 2022, DOI:10.32604/iasc.2022.016120
    (This article belongs to this Special Issue: Soft Computing Methods for Innovative Software Practices)
    Abstract Due to various issues such as lack of agility, low performance, security issues, and high maintenance costs, the organization replaces its legacy information system (LIS). However, with the expansion of information technology, the security of the old system has received great attention. The protection of legacy data and information is critical to the organization. However, achieving safety through modernization, redevelopment, or redesign of LIS is a time-consuming and costly solution, especially in small and medium enterprises (SMEs). In addition, newly developed systems often lose inherent business rules, data integrity, and user trust. In this paper, we propose a Security Modernization… More >

  • ARTICLE

    Performance Analysis of Photovoltaic Systems and Energy Return on the Environment Economy

    Murad A. A. Almekhlafi1, Fahd N. Al-Wesabi2,3, Anwer Mustafa Hilal4, Manar Ahmed Hamza4,*, Abdelzahir Abdelmaboud5, Mohammed Rizwanullah4
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 557-571, 2022, DOI:10.32604/iasc.2022.020576
    Abstract Using fossil fuels and non-renewable forms of energy has many adverse effects on the global ecosystem, and global demand exceeds the limited available resources. Renewable energy is one of the essential elements of social and economic development in any civilized country. This study comprises a feasibility study of the implementation of PV systems in a hybrid diesel network and analyzes the relationship between the effective uses of photovoltaic systems, the return of energy to the environment, and that country’s national economy. As a potential solution for the public and private utilities, the sunny web design application was used to calculate… More >

  • ARTICLE

    Intelligent Chimp Metaheuristics Optimization with Data Encryption Protocol for WSN

    P. Manjula1,*, Dr. S. Baghavathi Priya2
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 573-587, 2022, DOI:10.32604/iasc.2022.020969
    Abstract Recent developments in low power electronic devices integrated into wireless communication technologies resulted in the domain of wireless sensor networks (WSN), which finds in applications in diverse data gathering and tracking applications. Since WSN is mostly deployed in harsh and inaccessible environments, it is necessary to design energy efficient and security solutions. The clustering technique is an effective way to lengthen the lifetime of WSN. But most of the clustering techniques elect cluster heads (CHs) irrespective of clusters. To resolve this issue, this paper presents a new intelligent metaheuristics based energy aware clustering with data encryption protocol (IMEAC-DEP) for WSN.… More >

  • ARTICLE

    DAMFO-Based Optimal Path Selection and Data Aggregation in WSN

    S. Sudha Mercy1,*, J. M. Mathana2, J. S. Leena Jasmine3
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 589-604, 2022, DOI:10.32604/iasc.2022.021068
    Abstract Wireless Sensor Network (WSN) encompasses several tiny devices termed as Sensor Nodes (SN) that have restriction in resources with lower energy, memory, together with computation. Data Aggregation (DA) is required to optimize WSN for secured data transmission at Cluster Head (CH) together with Base Station (BS). With regard to the Energy Efficiency (EE) along with the privacy conservation requirements of WSN in big-data processing and aggregation, this paper proposed Diversity centered Adaptive Moth-Flame Optimization (DAMFO) for Optimal Path Selection (OPS) and DA in WSN. In the proposed work, initially, the Trust Evaluation (TE) process is performed. The Pompeiu Distance-centered Fuzzy… More >

  • ARTICLE

    A Design Framework for Smart Ration Shop Using Blockchain and IoT Technologies

    D. Malathi1, Vijayakumar Ponnusamy2,*, S. Saravanan3, D. Deepa4, Tariq Ahamed Ahanger5
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 605-619, 2022, DOI:10.32604/iasc.2022.022083
    Abstract The Public Distribution System (PDS) distributes the subsidized food and non-food items to poor populations through fair price shops (FPS). The PDS has been criticized for its urban bias and its failure to serve the underprivileged sections of the community effectively. The Current system manual-based data management and ledger management gives rise to much corruption in the process of extricating the poor from those who are less needy. There are chances for the block market because of the current methodology of data management. This article proposes a blockchain technology-based smart ration shop system that uses immutable smart contract-based transactions to… More >

  • ARTICLE

    Application of Fuzzy FoPID Controller for Energy Reshaping in Grid Connected PV Inverters for Electric Vehicles

    M. Manjusha1,*, T. S. Sivarani2, Carol J. Jerusalin1
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 621-641, 2022, DOI:10.32604/iasc.2022.020560
    Abstract By utilizing Fuzzy based FOPID-controller, this work is designed via the energy reshaping concept for Grid connected Photovoltaic (PV) systems for electric vehicles and this PV module has its own inverter which is synchorised with the utility grid. In grid connected PV system, the mitigation plays an important role where the capacity of PV arrays increases it maintains power quality and it is necessary to comply with some requirements such as harmonic mitigation. Unless a maximum power point tracking (MPPT) algorithm is used, PV systems do not continuously produce their theoretical optimal power. Under various atmospheric conditions, MPPT is obtained… More >

  • ARTICLE

    Detecting and Analysing Fake Opinions Using Artificial Intelligence Algorithms

    Mosleh Hmoud Al-Adhaileh1, Fawaz Waselallah Alsaade2,*
    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 643-655, 2022, DOI:10.32604/iasc.2022.021225
    (This article belongs to this Special Issue: Soft Computing and Machine Learning in Industrial Systems)
    Abstract In e-commerce and on social media, identifying fake opinions has become a tremendous challenge. Such opinions are widely generated on the internet by fake viewers, also called fraudsters. They write deceptive reviews that purport to reflect actual user experience either to promote some products or to defame others. They also target the reputations of e-businesses. Their aim is to mislead customers to make a wrong purchase decision by selecting undesired products. Such reviewers are often paid by rival e-business companies to compose positive reviews of their products and/or negative reviews of other companies’ products. The main objective of this paper… More >

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