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Intelligent Automation & Soft Computing

About the Journal

Intelligent Automation & Soft Computing: An International Journal seeks to provide a common forum for the dissemination of accurate results about the world of artificial intelligence, intelligent automation, control, computer science, modeling and systems engineering. It is intended that the articles published in the journal will encompass both the short and the long term effects of soft computing and other related fields such as robotics, control, computer, cyber security, vision, speech recognition, pattern recognition, data mining, big data, data analytics, machine intelligence and deep learning. It further hopes it will address the existing and emerging relationships between automation, systems engineering, system of computer engineering and soft computing. Intelligent Automation & Soft Computing is published monthly by Tech Science Press.

Indexing and Abstracting

SCIE: 2019 Impact Factor 1.276; Scopus CiteScore (Impact per Publication 2019): 2.0; SNIP (Source Normalized Impact per Paper 2019): 0.85; Essential Science Indicators(ESI), etc.

Previously published by TSI Press (http://www.wacong.org/autosoft/auto/), Intelligent Automation & Soft Computing starts to be published by Tech Science Press from the third issue of 2020 and supports Open Access Policy.

  • Automated Meter Reading Detection Using Inception with Single Shot Multi-Box Detector
  • Abstract Automated meter reading has recently been adopted by utility service providers for improving the reading and billing process. Images captured during meter reading are incorporated in consumer bills to prevent reporting false reading and ensure transparency. The availability of images captured during the meter reading process presents the potential of completely automating the meter reading process. This paper proposes a convolutional network-based multi-box model for the automatic meter reading. The proposed research leverages the inception model with a single shot detector to achieve high accuracy and efficiency compared to the existing state-of-the-art machine learning methods. We tested the multi-box detector… More
  •   Views:23       Downloads:20        Download PDF
  • CMMI Compliant Modernization Framework to Transform Legacy Systems
  • Abstract Legacy systems deteriorate due to changing business practices and recurrent problems such as high maintenance cost, lack of agility, and degraded performance. Modernization is highly desired especially for those organizations where key business processes are managed by legacy systems. During modernizing, two important aspects are usually ignored, i.e., the transformation of a legacy system to an enterprise solution, and considerations of quality concerns. This overlooking leads to a modernized information system that partially achieves the expected outcome. In this paper, we propose a Capability Maturity Model Integration (CMMI) Compliant Modernization Framework (CCMF) that addresses the problems of legacy systems by… More
  •   Views:12       Downloads:8        Download PDF
  • Hybridized Model with Activity Load Adjusting and QOS for Wi-Fi Network System
  • Abstract The establishment of multi-channel routing systems in WSNs has shown the reliability of the transmission across several channels. Meeting the service quality needs of all the applications is still a challenging task. Various surveys carried out, have suggested for the development of user-oriented Wireless Sensor Network (WSN) architectures. Throughout WSNs, the Optimized Link State Routing (OLSR) and the Adhoc On Demand Vector (AODV) are the multi-way routing systems that exhibit the reliability of the multipath delivery to fulfill the customer service quality requirements. The topology is modified only on requests, by selecting the best route based on the route weights… More
  •   Views:18       Downloads:10        Download PDF
  • An Enhanced Decentralized Virtual Machine Migration Approach for Energy-Aware Cloud Data Centers
  • Abstract Cloud computing is an increasingly important technology to deliver pay-as-you-go online computing services. In this study, the cloud service provider permits the cloud user to pay according to the user’s needs. Various methods have been used to reduce energy utilization in the cloud. The rapid increase of cloud users has led to increased energy consumption and higher operating costs for cloud providers. A key issue in cloud data centers is their massive energy consumption to operate and maintain computing services. Virtual machine (VM) migration is a method to reduce energy consumption. This study proposes enhanced decentralized virtual machine migration (EDVMM),… More
  •   Views:18       Downloads:16        Download PDF
  • A Study on Using a Wireless Sensor Network to Design a Plant Monitoring System
  • Abstract Traditional agriculture has to face different climatic factors, resulting in unstable crop yields, whereas a plant factory is indoors, thus avoiding different natural disasters and insect pests. It is also available for bulk production in all-weather all year-round, guaranteeing crop quality. This study uses a wireless sensor network (WSN) architecture for multi-monitoring of a plant environment, aiming to improve its growing environment quality. In terms of monitoring environment, the sensor modules at the end device nodes are combined with Arduino for capturing the sensor values, which are transmitted by wireless signal transmission. The data of wireless signals are further transmitted… More
  •   Views:11       Downloads:8        Download PDF
  • Optimal Eighth-Order Solver for Nonlinear Equations with Applications in Chemical Engineering
  • Abstract A new iterative technique for nonlinear equations is proposed in this work. The new scheme is of three steps, of which the first two steps are based on the sixth-order modified Halley’s method presented by the authors, and the last is a Newton step, with suitable approximations for the first derivatives appeared in the new scheme. The eighth-order of convergence of the new method is proved via Mathematica code. Every iteration of the presented scheme needs the evaluation of three functions and one first derivative. Therefore, the scheme is optimal in the sense of Kung-Traub conjecture. Several test nonlinear problems… More
  •   Views:10       Downloads:7        Download PDF
  • AUV Global Security Path Planning Based on a Potential Field Bio-Inspired Neural Network in Underwater Environment
  • Abstract As one of the classical problems in autonomous underwater vehicle (AUV) research, path planning has obtained a lot of research results. Many studies have focused on planning an optimal path for AUVs. These optimal paths are sometimes too close to obstacles. In the real environment, it is difficult for AUVs to avoid obstacles according to such an optimal path. To solve the safety problem of AUV path planning in a dynamic uncertain environment, an algorithm combining a bio-inspired neural network and potential field is proposed. Based on the environmental information, the bio-inspired neural network plans the optimal path for the… More
  •   Views:8       Downloads:6        Download PDF
  • Healthcare Device Security: Insights and Implications
  • Abstract Healthcare devices play an essential role in tracking and managing patient’s safety. However, the complexities of healthcare devices often remain ambiguous due to hardware, software, or the interoperable healthcare system problems. There are essentially two critical factors for targeting healthcare: First, healthcare data is the most valuable entity on the dark web; and the second, it is the easiest to hack. Data pilferage has become a major hazard for healthcare organizations as the hackers now demand ransom and threaten to disclose the sensitive data if not paid within the stipulated timeline. The present study enlists a thorough research on the… More
  •   Views:22       Downloads:10        Download PDF
  • Generation of Synthetic Images of Randomly Stacked Object Scenes for Network Training Applications
  • Abstract Image recognition algorithms based on deep learning have been widely developed in recent years owing to their capability of automatically capturing recognition features from image datasets and constantly improving the accuracy and efficiency of the image recognition process. However, the task of training deep learning networks is time-consuming and expensive because large training datasets are generally required, and extensive manpower is needed to annotate each of the images in the training dataset to support the supervised learning process. This task is particularly arduous when the image scenes involve randomly stacked objects. The present work addresses this issue by developing a… More
  •   Views:6       Downloads:3        Download PDF
  • Roughsets-based Approach for Predicting Battery Life in IoT
  • Abstract Internet of Things (IoT) and related applications have successfully contributed towards enhancing the value of life in this planet. The advanced wireless sensor networks and its revolutionary computational capabilities have enabled various IoT applications become the next frontier, touching almost all domains of life. With this enormous progress, energy optimization has also become a primary concern with the need to attend to green technologies. The present study focuses on the predictions pertinent to the sustainability of battery life in IoT frameworks in the marine environment. The data used is a publicly available dataset collected from the Chicago district beach water.… More
  •   Views:6       Downloads:5        Download PDF
  • Self-Adaptive Fault Recovery Mechanism Based on Task Migration Negotiation
  • Abstract Long Range Radio (LoRa) has become one of the widely adopted Low-Power Wide Area Network (LPWAN) technologies in power Internet of Things (PIoT). Its major advantages include long-distance, large links and low power consumption. However, in LoRa-based PIoT, terminals are often deployed in the wild place and are easily affected by bad weather or disaster, which could easily lead to large-scale operation faults and could seriously affect the normal operation of the network. Simultaneously, the distribution characteristics of outdoor terminals with wide coverage and large links lead to a sharp increase in the difficulty and cost of fault recovery. Given… More
  •   Views:6       Downloads:3        Download PDF
  • Tampering Detection Approach of Arabic-Text Based on Contents Interrelationship
  • Abstract Text information depends primarily on natural languages processing. Improving the security and usability of text information shared through the public internet has therefore been the most demanding problem facing researchers. In contact and knowledge sharing through the Internet, the authentication of content and the identification of digital content are becoming a key problem. Therefore, in this paper, a fragile approach of zero-watermarking based on natural language processing has been developed for authentication of content and prevention of misuse of Arabic texts distributed over the Internet. According to the proposed approach, watermark embedding, and identification was technically carried out such that… More
  •   Views:10       Downloads:5        Download PDF
  • Realization of IoT Integration System of LED Based on Particle Swarm Optimization
  • Abstract The purpose of this research is to design an intelligent LED lighting control system with wireless remote control. Since the designed system is mainly based on Android applications, it controls wireless lighting modules through a sever by means of a smartphone, tablet computer, or another handheld mobile device, and the values displayed on the handheld device are used to monitor the establishment and design of the electricity state and multiple-LED light control scenarios in real time. The server is connected with a touch human-machine interface, digital meter, wireless lighting controller, infrared learning module, and other devices through RS-232 and RS-485… More
  •   Views:5       Downloads:3        Download PDF
  • Decision Support System Tool for Arabic Text Recognition
  • Abstract The National Center for Education Statistics study reported that 80% of students change their major or institution at least once before getting a degree, which requires a course equivalency process. This error-prone process varies among disciplines, institutions, regions, and countries and requires effort and time. Therefore, this study aims to overcome these issues by developing a decision support tool called TiMELY for automatic Arabic text recognition using artificial intelligence techniques. The developed tool can process a complete document analysis for several course descriptions in multiple file formats, such as Word, Text, Pages, JPEG, GIF, and JPG. We applied a comparative… More
  •   Views:9       Downloads:5        Download PDF
  • Computer Vision Based Robotic Arm Controlled Using Interactive GUI
  • Abstract This paper presents the design and implementation of a robotic vision system operated using an interactive Graphical User Interface (GUI) application. As robotics continue to become a more integral part of the industrial complex, there is a need for automated systems that require minimal to no user training to operate. With this motivation in mind, the system is designed so that a beginner user can operate the device with very little instruction. The application allows users to determine their desired object, which will be picked up and placed by a robotic arm into the target location. The application allows users… More
  •   Views:11       Downloads:7        Download PDF
  • A Fuzzy-Based Bio-Inspired Neural Network Approach for Target Search by Multiple Autonomous Underwater Vehicles in Underwater Environments
  • Abstract An essential issue in a target search is safe navigation while quickly finding targets. In order to improve the efficiency of a target search and the smoothness of AUV’s (Autonomous Underwater Vehicle) trajectory, a fuzzy-based bio-inspired neural network approach is proposed in this paper. A bio-inspired neural network is applied to a multi-AUV target search, which can effectively plan search paths. In the meantime, a fuzzy algorithm is introduced into the bio-inspired neural network to make the trajectory of AUV obstacle avoidance smoother. Unlike other algorithms that need repeated training in the parameters selection, the proposed approach obtains all the… More
  •   Views:9       Downloads:5        Download PDF
  • Ontology-Based Verification of UML Class Model XOR Constraint and Dependency Relationship Constraints
  • Abstract Unified Modeling Language (UML) models are considered important artifacts of model-driven engineering (MDE). This can automatically transform models to other paradigms and programming languages. If a model has bugs, then MDE can transfer these to a new code. The class model is a key component of UML that is used in analysis and design. Without a formal foundation, UML can create only graphical diagrams, making it impossible to verify properties such as satisfiability, consistency and consequences. Different techniques have been used to verify UML class models, but these do not support some important components. This paper transforms and verifies unsupported… More
  •   Views:42       Downloads:13        Download PDF
  • Study of Sugarcane Buds Classification Based on Convolutional Neural Networks
  • Abstract Accurate identification of sugarcane buds, as one of the key technologies in sugarcane plantation, becomes very necessary for its mechanized and intelligent advancements. In the traditional methods of sugarcane bud recognition, a significant amount of algorithms work goes into the location and recognition of sugarcane bud images. A Convolutional Neural Network (CNN) for classifying the bud conditions is proposed in this paper. Firstly, we convert the colorful sugarcane images into gray ones, unify the size of them, and make a TFRecord format data set, which contains 1100 positive samples and 1100 negative samples. Then, a CNN mode is developed to… More
  •   Views:12       Downloads:5        Download PDF
  • Device Security Assessment of Internet of Healthcare Things
  • Abstract Security of the Internet of Healthcare Things (IoHT) devices plays a vital role in e-healthcare today and there has been a rapid increase in the use of networked devices of IoHT in the present healthcare services. However, these networked devices are also highly vulnerable to attackers who constantly target the security of devices and their components to gain access to the patients’ data. Infringement of patients’ data is not only a violation of privacy but can also jeopardize patients’ health if the health records are tampered with. Once the device has been intruded upon, attackers can not only change the… More
  •   Views:22       Downloads:18        Download PDF