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International Journal of Informatics and Communication Technology (IJ-ICT)
Published by Institute of Advanced Engineering and Science
ISSN : 22528776     EISSN : 27222616     DOI : -
Core Subject : Science,
Computer Science & IT
International Journal of Informatics and Communication Technology (IJ-ICT) is a common platform for publishing quality research paper as well as other intellectual outputs. This Journal is published by Institute of Advanced Engineering and Science (IAES) whose aims is to promote the dissemination of scientific knowledge and technology on the Information and Communication Technology areas, in front of international audience of scientific community, to encourage the progress and innovation of the technology for human life and also to be a best platform for proliferation of ideas and thought for all scientists, regardless of their locations or nationalities. The journal covers all areas of Informatics and Communication Technology (ICT) focuses on integrating hardware and software solutions for the storage, retrieval, sharing and manipulation management, analysis, visualization, interpretation and it applications for human services programs and practices, publishing refereed original research articles and technical notes. It is designed to serve researchers, developers, managers, strategic planners, graduate students and others interested in state-of-the art research activities in ICT.
Arjuna Subject : -
Articles 10 Documents
 1 
Search results for , issue "Vol 11, No 1: April 2022" : 10 Documents clear
Decision Making for Multi-Criteria Recommender System with Interaction and Non-Interaction Between Criteria Huynh, Tri
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp%p

Abstract

The recommender systems are increasingly being more inrested in many fields of the life, it is increasingly effective in finding information to suggest to users in big data systems. The multi-criteria recommender systems are alwaysresearched and improved to suit the diverse requirements of data and userpreferences today. The calculation to make a reasonable decision is required for the multi-criteria consulting system. Many operations have been applied todecision making. Most traditional recommender systems often use average calculations to calculate useful values used in decision making. In this paper, we offer a new approach to develope decision-making based on interaction andnon-interaction between criteria. In an information system, data always hasinteractive relationships that represent intrinsic values in the system. If we do not add these values to calculate decision-making, the decision making willnot be complete. We build a multi-criteria consulting model in both Item-based(compare and evaluate results with some existing models) and User-based(Compare decision making operations) with non-interactive and interactivedecisions. Experiments show that when using interactive values, the results aremuch better, contributing to improving the quality of the current multi-criteria consulting system.
Experimental Realization of Finger Gesture Recognizing Glove Sensor for Deaf and Dumb Person Kumar, Vikash
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp%p

Abstract

A majority of the human beings on this planet are deaf and dumb. The exchange of information between a deaf persons who knows sign language and the person doesn't poses a serious problem for them as compared to between who doesn't know the sign language. Since communication is the fundamental and one of the very important things to have in life therefore the person who doesn't know sign language feels alien in the atmosphere he lives in. Sign language is the non-verbal form of language which uses hand gestures to express feelings and to convey information and sign language is very popular among deaf community. This paper aim is to create a helping hand glove sensor for deaf people to communicate easily with other people. The glove has five flex sensors which are glued along lengths of five fingers on the glove. The glove produces a proportional change in resistance for every particular gesture. The analogue values which are the output of the sensors are converted into digital format. These gestures are analyzed using Arduino controller. This board compares the predefined voltage levels stored in the memory with the output of the flex sensor. And thus according to that a suitable match is found and a particular sentence is displayed on the LCD and also can be heard on the speaker. This is how the proposed sensor helps the deaf people to make their life easier than before and brings new colors to their life.
Detection of myocardial infarction on recent dataset using machine learning Nusrat Parveen; Satish R Devane; Shamim Akthar
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp20-31

Abstract

In developing countries such as India, with a large aging population and limited access to medical facilities, remote and timely diagnosis of myocardial infarction (MI) has the potential to save the life of many. An electrocardiogram is the primary clinical tool utilized in the onset or detection of a previous MI incident. Artificial intelligence has made a great impact on every area of research as well as in medical diagnosis. In medical diagnosis, the hypothesis might be doctors' experience which would be used as input to predict a disease that saves the life of mankind. It is been observed that a properly cleaned and pruned dataset provides far better accuracy than an unclean one with missing values. Selection of suitable techniques for data cleaning alongside proper classification algorithms will cause the event of prediction systems that give enhanced accuracy. In this proposal detection of myocardial infarction using new parameters is proposed with increased accuracy and efficiency of the existing model. Additional parameters are used to predict MI with more accuracy. The proposed model is used to predict an early diagnosis of MI with the help of expertise experiences and data gathered from hospitals.
A novel enhanced algorithm for efficient human tracking Mehdi Gheisari; Zohreh Safari; Mohammad Almasi; Amir Hossein Pourishaban Najafabadi; Abel Sridharan; Ragesh G K; Yang Liu; Aaqif Afzaal Abbasi
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp1-7

Abstract

Tracking moving objects has been an issue in recent years of computer vision and image processing and human tracking makes it a more significant challenge. This category has various aspects and wide applications, such as autonomous deriving, human-robot interactions, and human movement analysis. One of the issues that have always made tracking algorithms difficult is their interaction with goal recognition methods, the mutable appearance of variable aims, and simultaneous tracking of multiple goals. In this paper, a method with high efficiency and higher accuracy was compared to the previous methods for tracking just objects using imaging with the fixed camera is introduced. The proposed algorithm operates in four steps in such a way as to identify a fixed background and remove noise from that. This background is used to subtract from movable objects. After that, while the image is being filtered, the shadows and noises of the filmed image are removed, and finally, using the bubble routing method, the mobile object will be separated and tracked. Experimental results indicated that the proposed model for detecting and tracking mobile objects works well and can improve the motion and trajectory estimation of objects in terms of speed and accuracy to a desirable level up to in terms of accuracy compared with previous methods.
A review on notification sending methods to the recipients in different technology-based women safety solutions A. Z. M. Tahmidul Kabir; Al Mamun Mizan; Plabon kumar Saha; Nirmal Debnath; Tasnuva Tasneem
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp57-64

Abstract

Women have progressed a lot in terms of social empowerment and economics. They are going for higher education, jobs, and many other similar endeavors, but harassment cases have also been on the rise. So, women’s safety is a big concern nowadays, especially in developing countries. Many previous studies and attempts were made to create a feasible safety solution for women. Out of various features to ensure women’s safety in critical situations, location tracking is a very common and key feature in most previously proposed solutions. This study found mechanisms of sending the location to different types of recipients in various women safety solutions. In addition, the advantages and drawbacks of location sending methods in women's safety solutions were analyzed.
About decentralized swarms of asynchronous distributed cellular automata using inter-planetary file system’s publish-subscribe experimental implementation Vincent Manuceau
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp32-44

Abstract

This research describes the simple implementation of asynchronous distributed cellular automata and decentralized swarms of asynchronous distributed cellular automata built on top of inter-planetary file system’s publish-subscribe (IPFS PubSub) experimentation. Various publish-subscribe(PubSub) models are described. As an illustration, two distributed versions and a decentralized swarm version of a 2D elementary cellular automaton are thoroughly detailed to highlight the simplicity of implementation with IPFS and the inner workings of these kinds of cellular automata (CA). Both algorithms were implemented, and experiments were conducted throughout five datacenters of Grid’5000 testbed in France to obtain preliminary performance results in terms of network bandwidth usage. This work is prior to implementing a large-scale decentralized epidemic propagation modeling and prediction system based upon asynchronous distributed cellular automata with application to the current pandemic of SARS-CoV-2 coronavirus disease 2019 (COVID-19).
Correcting optical character recognition result via a novel approach Otman Maarouf; Rachid El Ayachi; Mohamed Biniz
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp8-19

Abstract

Optical character recognition (OCR) is a recognition system used to recognize the substance of a checked picture. This system gives erroneous results, which necessitates a post-treatment, for the sentence correction. In this paper, we proposed a new method for syntactic and semantic correction of sentences it is based on the frequency of two correct words in the sentence and a recursive technique. This approach starts with the frequency calculation of each two words successive in the corpora, the words that have the greatest frequency build a correction center. We found 98% using our approach when we used the noisy channel. Further, we obtained 96% using the same corpus in the same conditions.
Multiple educational data mining approaches to discover patterns in university admissions for program prediction Julius Cesar O. Mamaril; Melvin A. Ballera
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp45-56

Abstract

This paper presented the utilization of pattern discovery techniques by using multiple relationships and clustering educational data mining approaches to establish a knowledge base that will aid in the prediction of ideal college program selection and enrollment forecasting for incoming freshmen. Results show a significant level of accuracy in predicting college programs for students by mining two years of student college admission and graduation final grade scholastic records. The results of educational predictive data mining methods can be applied in improving the services of the admission department of an educational institution, particularly in its course alignment, student mentoring, admission forecast, marketing, and enrollment preparedness.
An internet of things-based irrigation and tank monitoring system Tayo Dorcas Obasanya; Ilesanmi Banjo Oluwafemi; Oluwaseyi Olawale Bello; Taiwo Abdulazeez Lawal
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp65-75

Abstract

Agriculture plays a significant role in the development of a nation and provides the main source of food production, income, and employment to nations. It was the most practiced occupation in Nigeria and this formed the backbone of the economy in the early 1960s before the discovery of crude oil, which has led to the derail of sufficient food production, exportation, and the agricultural economy at large. Over time, the dry season has always been challenging with little or no rainfall and there are no irrigation facilities that incorporate different saving practices to adapt to these climate changes on their own. In this paper, a cost-effective internet of things irrigation system that is capable of reducing water wastage, manual labor, monitoring tank water level and that can be controlled remotely is designed. The system integrated Arduino UNO with a soil moisture sensor, HCSR04 ultrasonic sensor, and ESP8266 Wi-Fi module that gives the system capable of being controlled remotely via the internet, thus achieving optimal irrigation using the internet of things (IoT). Some of the challenges facing the existing irrigation system are water wastage, poor performance, and high cost of implementation. The design system helps to control water supply to crops when it is needed, and also monitors soil moisture, temperature, and water tank level. After carrying out the experiments for 15 days, the system saved approximately 49% of the water used in traditional irrigation method. The system is useful in large farming areas to minimize human effort and reduce the cost of hiring personnel.
A convolutional neural network for skin cancer classification Nur Nafi'iyah; Anny Yuniarti
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp76-84

Abstract

Skin diseases can be seen clearly by oneself and others. Although this disease is visible on the skin, sometimes we worry if this skin disease is not mild. Some people experience skin diseases directly and quickly go to a dermatologist to have their complaints and symptoms checked. This skin protects the body, especially from the sun, so it can lead to death if something goes wrong. One example of a skin disease that can be deadly is skin cancer or skin tumors. In this research, we classified skin cancer into Benign and Malignant using the convolution neural network (CNN) algorithm. The purpose of this research is to develop the CNN architecture to help identify skin diseases. We used a dataset of 3,297 skin cancer images which are publicly available on the Kaggle website. We propose two CNN architectures that differ in the number of parameters. The first architecture has 6,427,745 parameters, and the second architecture has 2,797,665. With both architectures, the accuracy of the first model is 93%, and the second model is 74%. The first model with the number of parameters 6,427,745 We save for use in the creation of the website. We created a web-based application with the Django framework for skin disease identification.

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