Journals / IASC / Vol.26, No.1


    Improved Teaching Learning Based Optimization and Its Application in Parameter Estimation of Solar Cell Models

    Qinqin Fan1,*, Yilian Zhang2, Zhihuan Wang1
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 1-12, 2020, DOI:10.31209/2018.100000042
    Abstract Weak global exploration capability is one of the primary drawbacks in teaching learning based optimization (TLBO). To enhance the search capability of TLBO, an improved TLBO (ITLBO) is introduced in this study. In ITLBO, a uniform random number is replaced by a normal random number, and a weighted average position of the current population is chosen as the other teacher. The performance of ITLBO is compared with that of five meta-heuristic algorithms on a well-known test suite. Results demonstrate that the average performance of ITLBO is superior to that of the compared algorithms. Finally, ITLBO is employed to estimate parameters… More >


    Application Centric Virtual Machine Placements to Minimize Bandwidth Utilization in Datacenters

    Muhammad Abdullah1,*, Saad Ahmad Khan1, Mamdouh Alenez2, Khaled Almustafa3, Waheed Iqbal1
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 13-25, 2020, DOI:10.31209/2018.100000047
    Abstract An efficient placement of virtual machines (VMs) in a cloud datacenter is important to maximize the utilization of infrastructure. Most of the existing work maximises the number of VMs to place on a minimum number of physical machines (PMs) to reduce energy consumption. Recently, big data applications become popular which are mostly hosted on cloud datacenters. Big data applications are deployed on multiple VMs and considered data and communication intensive applications. These applications can consume most of the datacenter bandwidth if VMs do not place close to each other. In this paper, we investigate the use of different VM placement… More >


    Model Predictive Control for Nonlinear Energy Management of a Power Split Hybrid Electric Vehicle

    Dehua Shi1,4, Shaohua Wang1,2,*, Yingfeng Cai1, Long Chen1, ChaoChun Yuan1, ChunFang Yin3
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 27-39, 2020, DOI:10.31209/2018.100000062
    Abstract Model predictive control (MPC), owing to the capability of dealing with nonlinear and constrained problems, is quite promising for optimization. Different MPC strategies are investigated to optimize HEV nonlinear energy management for better fuel economy. Based on Bellman’s principle, dynamic programming is firstly used in the limited horizon to obtain optimal solutions. By considering MPC as a nonlinear programming problem, sequential quadratic programming (SQP) is used to obtain the descent directions of control variables and the current control input is further derived. To reduce computation and meet the requirements of real-time control, the nonlinear model of the system is approximated… More >


    African Buffalo Optimization Algorithm for Collision-Avoidance in Electric Fish

    Julius Beneoluchi Odili1,*, A. Noraziah2, Mohd Helmy Abd Wahab3
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 41-51, 2020, DOI:10.31209/2018.100000059
    Abstract This paper presents the African Buffalo Optimization algorithm for collision avoidance among electric fishes. Collision-avoidance in electric fish finds correlation with the Travelling Salesman avoiding the cities he has earlier visited. Collision avoidance in electric is akin to collision-avoidance in modern day driverless cars being promoted by Google Incorporation and other similar companies. The concept of collision-avoidance is also very useful to persons with visual impairment as it will help them avoid collision with objects, vehicles, persons, especially other visually-impaired. After a number of experimental procedures using the concept of the travelling salesman’s problem to simulate collision-avoidance in electric fish,… More >


    Laparoscopic Training Exercises Using HTC VIVE

    Ayesha Hoor Chaudhry*, Faisal Bukhari, Waheed Iqbal, Zubair Nawaz, Muhammad Kamran Malik
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 53-59, 2020, DOI:10.31209/2019.100000149
    Abstract Laparoscopic surgery is a relatively new field in developing countries. There is a scarcity of laparoscopically trained doctors due to a lack of training and resources available in hospitals. Training and evaluation of medical professionals to develop laparoscopic surgical skills are important and essential as it improves the success rate and reduces the risk during real surgery. The purpose of this research is to develop a series of training exercises based on virtual reality using HTC Vive headset to emulate real-world training of doctors. This virtual training not only gives the trainee doctors mastery in their profession but also decreases… More >


    C5.0 Decision Tree Model Using Tsallis Entropy and Association Function for General and Medical Dataset

    Uma K.V1,*, Appavu alias Balamurugan S2
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 61-70, 2020, DOI:10.31209/2019.100000153
    Abstract Real world data consists of lot of impurities. Entropy measure will help to handle impurities in a better way. Here, data selection is done by using Naïve Bayes’ theorem. The sample which has posterior probability value greater than that of the threshold value is selected. C5.0 decision tree classifier is taken as base and modified the Gain calculation function using Tsallis entropy and Association function. The proposed classifier model provides more accuracy and smaller tree for general and Medical dataset. Precision value obtained for Medical dataset is more than that of existing method. More >


    Enhancing the Classification Accuracy in Sentiment Analysis with Computational Intelligence Using Joint Sentiment Topic Detection with MEDLDA

    PCD Kalaivaani1,*, Dr. R Thangarajan2
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 71-79, 2020, DOI:10.31209/2019.100000152
    Abstract Web mining is the process of integrating the information from web by traditional data mining methodologies and techniques. Opinion mining is an application of natural language processing to extract subjective information from web. Online reviews require efficient classification algorithms for analysing the sentiments, which does not perform an in–depth analysis in current methods. Sentiment classification is done at document level in combination with topics and sentiments. It is based on weakly supervised Joint Sentiment-Topic mode which extends the topic model Maximum Entropy Discrimination Latent Dirichlet Allocation by constructing an additional sentiment layer. It is assumed that topics generated are dependent… More >


    Advanced ICT and IoT Technologies for the Fourth Industrial Revolution

    Soo Kyun Kim*, Mario Köppen, Ali Kashif Bashir, Yuho Jin
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 83-85, 2020, DOI:10.31209/2019.100000129
    Abstract This article has no abstract. More >


    Finding Temporal Influential Users in Social Media Using Association Rule Learning

    Babar Shazad1, Hikmat Ullah khan2, Zahoor-ur-Rehman1, Muhammad Farooq2, Ahsan Mahmood1, Irfan Mehmood3,*, Seungmin Rho3, Yunyoung Nam4,*
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 87-98, 2020, DOI:10.31209/2019.100000130
    Abstract The social media has become an integral part of our daily life. The social web users interact and thus influence each other influence in many aspects. Blogging is one of the most important features of the social web. The bloggers share their views, opinions and ideas in the form of blog posts. The influential bloggers are the leading bloggers who influence the other bloggers in their online communities. The relevant literature presents several studies related to identification of top influential bloggers in last decade. The research domain of finding the top influential bloggers mainly focuses on feature centric models. This… More >


    Implementation of Local Area VR Environment using Mobile HMD and Multiple Kinects

    Soo-Kyun Kim1, Chang-Hee Lee2, Sun-Jeong Kim2, Chang-Geun Song2, Jung Lee2,*
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 99-105, 2020, DOI:10.31209/2019.100000131
    Abstract Recently, the development of HMDs such as Oculus Rift, HTC Vive, and PSVR has led to an increase in the interest of people in virtual reality (VR), and many related studies have been published. This leads to an additional cost increase in configuring the VR system. Also, space problems are caused. When the treadmill is installed, additional space is required, which may adversely affect the popularization of VR. In this paper, we propose a local area VR environment that solves cost and space problems using human tracking using several Kinect and solves the hygiene problems using smartphone-based mobile HMD. More >


    A Novel Knowledge-Based Battery Drain Reducer for Smart Meters

    Isma Farah Siddiqui1, Scott Uk-Jin Lee2,*, Asad Abbas3
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 107-119, 2020, DOI:10.31209/2019.100000132
    Abstract The issue of battery drainage in the gigantic smart meters network such as semantic-aware IoT-enabled smart meter has become a serious concern in the smart grid framework. The grid core migrates existing tabular datasets i.e., Relational data to semantic-aware tuples in its Resource Description Framework (RDF) format, for effective integration among multiple components to work aligned with IoT. For this purpose, WWW Consortium (W3C) recommends two specifications as mapping languages. However, both specifications use entire RDB schema to generate data transformation mapping patterns and results large quantity of unnecessary transformation. As a result, smart meters use huge computing resources, maximum… More >


    A Method for Planning the Routes of Harvesting Equipment using Unmanned Aerial Vehicles

    Vitaliy Mezhuyev1,*, Yurii Gunchenko2, Sergey Shvorov3, Dmitry Chyrchenko3
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 121-132, 2020, DOI:10.31209/2019.100000133
    Abstract The widespread distribution of precision farming systems necessitates improvements in the methods for the control of unmanned harvesting equipment (UHE). While unmanned aerial vehicles (UAVs) provide an effective solution to this problem, there are many challenges in the implementation of technology. This paper considers the problem of identifying optimal routes of UHE movement as a multicriteria evaluation problem, which can be solved by a nonlinear scheme of compromises. The proposed method uses machine learning algorithms and statistical processing of the spectral characteristics obtained from UAV digital images. Developed method minimizes the resources needed for a harvesting campaign and reduces the… More >


    Distinction Between Real Faces and Photos by Analysis of Face Data

    Byong Kwon Lee1, Yang Sun Lee2,*
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 133-139, 2020, DOI:10.31209/2019.100000134
    Abstract Biometric user authentication using the face has been applied mainly to access control systems. However, access is allowed even when a photo is presented instead of an actual face. This can facilitate illegal access including attending as a substitute or substitute authentication. An alternative approach has been implemented to solve this problem. The approach determines between a real face and a photo of a face using a UV sensor but this requires substantial cost and installation process because additional hardware (the UV sensor) is necessary. This paper proposes a three-step approach to identify between a real image and a photo.… More >


    Word Embedding Based Knowledge Representation with Extracting Relationship Between Scientific Terminologies

    Mucheol Kim*, Junho Kim, Mincheol Shin
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 141-147, 2020, DOI:10.31209/2019.100000135
    Abstract With the trends of big data era, many people want to acquire the reliable and refined information from web environments. However, it is difficult to find appropriate information because the volume and complexity of web information is increasing rapidly. So many researchers are focused on text mining and personalized recommendation for extracting users’ interests. The proposed approach extracted semantic relationship between scientific terminologies with word embedding approach. We aggregated science data in BT for supporting users’ wellness. In our experiments, query expansion is performed with relationship between scientific terminologies with user’s intention. More >


    Noise Cancellation Based on Voice Activity Detection Using Spectral Variation for Speech Recognition in Smart Home Devices

    Jeong-Sik Park1, Seok-Hoon Kim2,*
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 149-159, 2020, DOI:10.31209/2019.100000136
    Abstract Variety types of smart home devices have a main function of a human-machine interaction by speech recognition. Speech recognition system may be vulnerable to rapidly changing noises in home environments. This study proposes an efficient noise cancellation approach to eliminate the noises directly on the devices in real time. Firstly, we propose an advanced voice activity detection (VAD) technique to efficiently detect speech and non-speech regions on the basis of spectral property of speech signals. The VAD is then employed to enhance the conventional spectral subtraction method by steadily estimating noise signals in non-speech regions. On several experiments, our approach… More >


    An E-Assessment Methodology Based on Artificial Intelligence Techniques to Determine Students’ Language Quality and Programming Assignments’ Plagiarism

    Farhan Ullah1,4,*, Abdullah Bajahzar2, Hamza Aldabbas3, Muhammad Farhan4, Hamad Naeem1, S. Sabahat H. Bukhari4,5, Kaleem Razzaq Malik6
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 169-180, 2020, DOI:10.31209/2019.100000138
    Abstract This research aims to an electronic assessment (e-assessment) of students’ replies in response to the standard answer of teacher’s question to automate the assessment by WordNet semantic similarity. For this purpose, a new methodology for Semantic Similarity through WordNet Semantic Similarity Techniques (SS-WSST) has been proposed to calculate semantic similarity among teacher’ query and student’s reply. In the pilot study-1 42 words’ pairs extracted from 8 students’ replies, which marked by semantic similarity measures and compared with manually assigned teacher’s marks. The teacher is provided with 4 bins of the mark while our designed methodology provided an exact measure of… More >


    Emotion-Based Painting Image Display System

    Taemin Lee1, Dongwann Kang2, Kyunghyun Yoon1, Sanghyun Seo3,*
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 181-192, 2020, DOI:10.31209/2019.100000139
    Abstract As mobile devices have tremendously developed, people can now get sensor data easily. These data are not only physical data such as temperature, humidity, gravity, acceleration, etc. but also human health data such as blood pressure, heart pulse rate, etc. With this information, Internet of Things (IoT) technology has provided many systems to support human health care. Systems for human health care support physical health care like checking blood pressure, pulse rate, etc. However, the demand for physical health care as well as mental health care is increasing. So, a system, which automatically recommends a painting to users based on… More >


    Weighted or Non-Weighted Negative Tree Pattern Discovery from SensorRich Environments

    Juryon Paik*
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 193-204, 2020, DOI:10.31209/2019.100000140
    Abstract It seems to be sure that the IoT is one of promising potential topics today. Sensors are the one that lead the current IoT revolution. The advances of sensor-rich environments produce the massive volume of raw data that is enlarging faster than the rate at which it is being handled. JSON is a lightweight data-interchange format and preferred for IoT applications. Before JSON, XML was de factor standard format for interchanging data. The common point is that their structure scheme is the tree. Tree structure provides data exchangeability and heterogeneity, which encourages user-flexibilities. Therefore, JSON sensor format is an easy… More >


    Detecting Outlier Behavior of Game Player Players Using Multimodal Physiology Data

    Shinjin Kang1, Taiwoo Park2,*
    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 205-214, 2020, DOI:10.31209/2019.100000141
    Abstract This paper describes an outlier detection system based on a multimodal physiology data clustering algorithm in a PC gaming environment. The goal of this system is to provide information on a game player’s abnormal behavior with a bio-signal analysis. Using this information, the game platform can easily identify players with abnormal behavior in specific events. To do this, we propose a mouse device that measures the wearer's skin conductivity, temperature, and motion. We also suggest a Dynamic Time Warping (DTW) based clustering algorithm. The developed system examines the biometric information of 50 players in a bullet dodge game. This paper… More >

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