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IAES International Journal of Artificial Intelligence (IJ-AI)

IJAI
Website

Published by Institute of Advanced Engineering and Science

ISSN : 20894872 EISSN : 22528938 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Engineering

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like genetic algorithm, ant colony optimization, etc); reasoning and evolution; intelligence applications; computer vision and speech understanding; multimedia and cognitive informatics, data mining and machine learning tools, heuristic and AI planning strategies and tools, computational theories of learning; technology and computing (like particle swarm optimization); intelligent system architectures; knowledge representation; bioinformatics; natural language processing; multiagent systems; etc.

Arjuna Subject : -

Articles 1,808 Documents

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Fuzzy Controller Design of Lighting Control System By Using VI Package Ragavan Saravanan
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 1, No 2: June 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (445.605 KB)

This paper describes how we design a lighting control system including hardware and software. Hardware includes Dimmer with relays Bulb light sensing circuit, control circuit, and 8255 expanding I/O circuit, PC, and bulb. Sensing circuit uses photo-resistance component to sense the environmental light and then transmit the signal of the lightness to the computer through an 8-bit A/D converter 0804. The control circuit applies reed relay in digital control way to adjust the variable resistor value of the traditional dimmer. Software incorporates LABVIEW graph- ical programming language and MATLAB Fuzzy Logic Toolbox to design the light fuzzy controller. The rule-base of the fuzzy logic controller either for the single input single output (SISO) system or the double inputs single output (DISO) system is developed and compared based on the op- eration of the bulb and the light sensor. The control system can dim the bulb automatically according to the environmental light. It can be applied to many fields such as control of streetlights and lighting control of car’s headlights and it is possible to save energy by dimming the bulb. Experimental results show that the fuzzy controller with the DISO system can make bulb response faster than with the SISO system under sudden change of environmental light.DOI: http://dx.doi.org/10.11591/ij-ai.v1i2.441

Classification of Atrial Arrhythmias using Neural Networks Jai Utkarsh; Raju Kumar Pandey; Shrey Kumar Dubey; Shubham Sinha; S. S. Sahu
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 7, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

Electrocardiogram (ECG) is an important tool used by clinicians for successful diagnosis and detection of Arrhythmias, like Atrial Fibrillation (AF) and Atrial Flutter (AFL). In this manuscript, an efficient technique of classifying atrial arrhythmias from Normal Sinus Rhythm (NSR) has been presented. Autoregressive Modelling has been used to capture the features of the ECG signal, which are then fed as inputs to the neural network for classification. The standard database available at Physionet Bank repository has been used for training, validation and testing of the model. Exhaustive experimental study has been carried out by extracting ECG samples of duration of 5 seconds, 10 seconds and 20 seconds. It provides an accuracy of 99% and 94.3% on training and test set respectively for 5 sec recordings. In 10 sec and 20 sec samples it shows 100% accuracy. Thus, the proposed method can be used to detect the arrhythmias in a small duration recordings with a fairly high accuracy.

Legal Documents Clustering and Summarization using Hierarchical Latent Dirichlet Allocation Ravi kumar Venkatesh
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 2, No 1: March 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (320.79 KB)

In a common law system and in a country like India, decisions made by judges are significant sources of application and understanding of law. Online access to the Indian Legal Judgments in the digital form creates an opportunities and challenges to the both legal community and information technology researchers. This necessitates organizing, analyzing, retrieving relevant judgment and presenting it in a useful manner to the legal community for quick understanding and for taking necessary decision pertaining to a present case. In this paper we propose an approach to cluster legal judgments based on the topics obtained from hierarchical Latent Dirichlet Allocation (hLDA) using similarity measure between topics and documents and to find the summarization of each document using the same topics. The developed topic based clustering model is capable of grouping the legal judgments into different clusters and to generate summarization in effective manner compare to our previous [1] approach.DOI: http://dx.doi.org/10.11591/ij-ai.v2i1.1186

Optimization study of fuzzy parametric uncertain system Tejal D. Apale; Ajay B. Patil
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

This paper deals with the analysis and design of the optimal robust controller for the fuzzy parametric uncertain system. An LTI system in which coefficients depends on parameters described by a fuzzy function is called as fuzzy parametric uncertain system. By optimal control design, we get control law and feedback gain matrix which can stabilize the system. The robust controller design is a difficult task so we go for the optimal control approach. The system can be converted into state space controllable canonical form with the α-cut property fuzzy. For optimal control design, we find control law and get the feedback gain matrix which can stabilize the system and optimizes the cost function. Stability analysis is done by using the Kharitonov theorem and Lyapunov-Popov method. The proposed method applied to a response of Continuous Stirred Tank Reactor (CSTR).

Privileged authenticity in reconstruction of digital encrypted shares Joydeep Dey; Anirban Bhowmik; Arindam Sarkar; Sunil Karforma
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Efficient message reconstruction mechanism depends on the entire partial shares received in random manner. This paper proposed a technique to ensure the authenticated accumulation of shares based on the privileged share. Threshold number of received shares inclusive of the privileged share, were being accumulated together to validate the original message. Although attaining threshold number of shares or more excluding the privileged share, it would not be possible to reconstruct the original message. Encryptional procedure has been put into the desired partial shares to confuse the evaesdroppers. Decisive parameter termed as hash tag has been extracted from the cumulative shares and bitwise checking procedure has been carried out. In appearance of first mismatch, rests of the checking bits were ignored, as test case put under failure transaction. Different statistical tests namely floating frequency, entropy value have proved the robustness of the proposed technique. Thus, extensive experiments were conducted to evaluate the security and efficiency with better productivity.

Yoruba Language and Numerals’ Offline Interpreter Using Morphological and Template Matching Olakanmi Olufemi Oladayo
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 3, No 2: June 2014
Publisher : Institute of Advanced Engineering and Science

Yoruba as a language has passed through generation reformations making some of the old documents in the archive to be unreadable by the present generation readers. Apart from this, some Yoruba writers usually mixed English numerals while writing due to brevity and conciseness of English numeral compare to Yoruba numerals which are combination of several characters. Re-typing such historical documents may be time consuming, therefore a need for an efficient Optical Character Reader (OCR) which will not only effectively recognize Yoruba texts but also converts all the English numerals in the document to Yoruba numerals.Several Optical Character Reader (OCR) systems had been developed to recognize characters or texts of some languages such as English, Arabic, Japanese, Chinese, and Korean, however, despite the significant contribution of Yoruba language to historical documentation and communication, it was observed that there is no particular OCR system for the language. In this paper correlation and template matching techniques were used to develop an OCR for the recognition of Yoruba based texts and convert English numerals in the document to Yoruba numerals. Experimental results show the relatively high accuracy of the developed OCR when it was tested on all size Yoruba alphabets and numerals.

A fuzzy neighborhood rough set method for anomaly detection in large scale data EL Meziati Marouane; Ziyati Elhoussaine
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 1: March 2020
Publisher : Institute of Advanced Engineering and Science

Mining Outlier in database is to find exceptional objects that deviate from the rest of the datasets. Besides classical outlier analysis algorithms, recent studies have focused on mining local outliers. The outliers that have density distribution significantly different from their neighborhood. However, the existing outlier detection algorithms suffer the drawbacks that they are inefficient in dealing with large scale datasets. In this paper, we propose a novel approach for outlier detection with voluminous data. This approach involves a neighborhood fuzzy rough set theory to rank outlier according to fuzzy membership function computed in rough approximation space. In order to improve the speed of computation, an efficient parallel computing system based on Map Reduce model is developed

Grading of Soybean Leaf Disease Based on Segmented Image Using K-means Clustering Sachin Balkrishna Jadhav; Sanjay B. Patil
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 5, No 1: March 2016
Publisher : Institute of Advanced Engineering and Science

Traditional method used for disease scoring scale to grade the plant diseases is mainly based on neckaed eye observation by agriculture expert or plant pathlogiest. In this method percentage scale was exclusively used to define different disease severities in an illustrated series of disease assessment keys for field crops.The assessment of plant leaf diseases using this aaproach which may be subjective, time consuming and cost effective.Also aacurate grading of leaf diseases is essential to the determination of pest control measures. In order to improve this process, here we propose a technique for automatically quantifying the damaged leaf area using k means clustering, which uses square Euclidian distances method for partition of leaf image.For grading of soybean leaf disese which appear on leaves based on segmented diseased region are done automatically by estiamting thae ratio of the unit pixel expressed under diseased region area and unit pixel expressed under Leaf region area.For experiment purpose samples of Bacterial Leaf Blight Septoria Brown spot, Bean Pod Mottle Virus infected soybean leaf images were taken for analysis.Finally estiamated diseased severity and its grading is compared with manual scoring based on conventional illustrated key diagram was conducted. Comparative assessment results showed a good agreement between the numbers of percentage scale grading obtained by manual scoring and by image analysis The result shows that the proposed method is precise and reliable than visual evaluation performed by patahlogiest.

Artificial intelligence in education: integrating serious gaming into the language class classdojo technology for classroom behavioral management Yassine Benhadj; Mohammed El Messaoudi; Abdelhamid Nfissi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

The aim of the study at hand was to examine students' perceptions of game elements used in gamification application. ClassDojo, as a study case, was implemented class-wide in a Moroccan High School EFL classroom. Data was gathered and saved directly through the application. It is qualitative research that opted for structured interviews to collect data. The findings were evaluated in so far as class motivation, participation, cooperation, discipline, attendance, and classroom discourse are concerned. This study has shown a crystal clear improvement in terms of discipline, motivations and classroom participation, suggesting the great need to conduct more research with a view to determine if these areas could be positively or negatively impacted when integrating ClassDojo in classroom management on a large scale. The findings of this study are of much significance to decision makers, curriculum developers, syllabus designers, and teachers in both senior and junior schools in Morocco.

Parser Extraction of Triples in Unstructured Text Shaun D'Souza
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 5, No 4: December 2016
Publisher : Institute of Advanced Engineering and Science

The web contains vast repositories of unstructured text. We investigate the opportunity for building a knowledge graph from these text sources. We generate a set of triples which can be used in knowledge gathering and integration. We define the architecture of a language compiler for processing subject-predicate-object triples using the OpenNLP parser. We implement a depth-first search traversal on the POS tagged syntactic tree appending predicate and object information. A parser enables higher precision and higher recall extractions of syntactic relationships across conjunction boundaries. We are able to extract 2-2.5 times the correct extractions of ReVerb. The extractions are used in a variety of semantic web applications and question answering. We verify extraction of 50,000 triples on the ClueWeb dataset.

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
Imam Much Ibnu Subroto

Contact Email
imam@unissula.ac.id

Phone
-

Journal Mail Official
ijai@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA

Abstract

Abstract

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Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Imam Much Ibnu Subroto

Contact Email imam@unissula.ac.id

Phone -

Journal Mail Official ijai@iaesjournal.com

Editorial Address -

Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Imam Much Ibnu Subroto

Contact Email
imam@unissula.ac.id

Phone
-

Journal Mail Official
ijai@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA