Papers by International Journal of Information Sciences and Techniques (IJIST)
International Journal of Information Science & Techniques (IJIST) , 2025
The International Journal of Information Science & Techniques (IJIST) focuses on information syst... more The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
International Journal of Information Science & Techniques (IJIST), 2023
In this article the author analyzed the background of causation in linguocognitive aspect. The au... more In this article the author analyzed the background of causation in linguocognitive aspect. The author compared causative verbs in two languages by translating sentences from English to Uzbek.
International Journal of Information Sciences and Techniques (IJIST), 2013
This paper is concerned with the development of Back-propagation Neural Network for Bangla Speech... more This paper is concerned with the development of Back-propagation Neural Network for Bangla Speech Recognition. In this paper, ten bangla digits were recorded from ten speakers and have been recognized. The features of these speech digits were extracted by the method of Mel Frequency Cepstral Coefficient (MFCC) analysis. The mfcc features of five speakers were used to train the network with Back propagation algorithm. The mfcc features of ten bangla digit speeches, from 0 to 9, of another five speakers were used to test the system. All the methods and algorithms used in this research were implemented using the features of Turbo C and C++ languages. From our investigation it is seen that the developed system can successfully encode and analyze the mfcc features of the speech signal to recognition. The developed system achieved recognition rate about 96.332% for known speakers (i.e., speaker dependent) and 92% for unknown speakers (i.e., speaker independent).
International Journal of Information Sciences and Techniques (IJIST), 2013
OCR has been an active research area since last few decades. OCR performs the recognition of the ... more OCR has been an active research area since last few decades. OCR performs the recognition of the text in the scanned document image and converts it into editable form. The OCR process can have several stages like preprocessing, segmentation, recognition and post processing. The preprocessing stage is a crucial stage for the success of OCR, which mainly deals with noise removal. In the present paper, a modified technique for noise removal named as "K-Algorithm" has been proposed, which has two stages as filtering and binarization. The proposed technique shows improvised results in comparison to median filtering technique.
International Journal of Information Sciences and Techniques (IJIST), 2012
Classification is widely used technique in the data mining domain, where scalability and efficien... more Classification is widely used technique in the data mining domain, where scalability and efficiency are the immediate problems in classification algorithms for large databases. We suggest improvements to the existing C4.5 decision tree algorithm. In this paper attribute oriented induction (AOI) and relevance analysis are incorporated with concept hierarchy's knowledge and HeightBalancePriority algorithm for construction of decision tree along with Multi level mining. The assignment of priorities to attributes is done by evaluating information entropy, at different levels of abstraction for building decision tree using HeightBalancePriority algorithm. Modified DMQL queries are used to understand and explore the shortcomings of the decision trees generated by C4.5 classifier for education dataset and the results are compared with the proposed approach.
International Journal of Information Sciences and Techniques (IJIST), 2012
Named entity recognition (NER) is one of the applications of Natural Language Processing and is r... more Named entity recognition (NER) is one of the applications of Natural Language Processing and is regarded as the subtask of information retrieval. NER is the process to detect Named Entities (NEs) in a document and to categorize them into certain Named entity classes such as the name of organization, person, location, sport, river, city, country, quantity etc. In English, we have accomplished lot of work related to NER. But, at present, still we have not been able to achieve much of the success pertaining to NER in the Indian languages. The following paper discusses about NER, the various approaches of NER, Performance Metrics, the challenges in NER in the Indian languages and finally some of the results that have been achieved by performing NER in Hindi by aggregating approaches such as Rule based heuristics and Hidden Markov Model (HMM).
International Journal of Information Sciences and Techniques (IJIST), 2018
This work proposes to recognize a user's commands by analysing his/her brainwaves captured with s... more This work proposes to recognize a user's commands by analysing his/her brainwaves captured with single channel electroencephalogram (EEG). Whenever a user intends to issue one of the pre-defined commands, the proposed system prompts him/her all the candidate commands in turn. Then, the user is asked to be concentrated as possible as he/she can, when the desired command is shown. It is assumed that the concentration will present a certain pattern of "Yes" in the captured EEG, as opposed to a certain pattern of "No" when the user is relaxed. Accordingly, the task is to determine that the captured EEG is "Yes" or not. This work compares three recognition methods, respectively, based on Gaussian mixture models, hidden Markov models and recurrent neural network, and conducts experiments using 2400 test EEG samples recorded from 10 subjects.
International Journal of Information Sciences and Techniques (IJIST), 2012
An adaptive sliding mode control based on two neural networks is proposed in this paper for Quadr... more An adaptive sliding mode control based on two neural networks is proposed in this paper for Quadrotor stabilization. This approach presents solutions to conventional control drawbacks as chattering phenomenon and dynamical model imprecision. For that reason two ANN for each quadrotor helicopter subsystem are implemented in the control loop, the first one is a Single Hidden Layer network used to approximate on line the equivalent control and the second feed-forward Network is used to estimate the ideal corrective term. The main purpose behind the use of ANN in the second part of SMC is to minimize the chattering phenomena and response time by finding optimal sliding gain and sliding surface slope. The learning algorithms of the two ANNs (equivalent and corrective controller) are obtained using the direct Lyapunov stability method. The simulation results are given to highlight the performances of the proposed control scheme.
In this work, we study analytical model such threshold voltage (V TH) and Subthreshold swing (SS)... more In this work, we study analytical model such threshold voltage (V TH) and Subthreshold swing (SS) for a new Surrounding Gate MOSFET. This new SG-MOSFET is composed of Dual-metal Gate (DMG) M 1 and M 2 with different work function, Graded Channel (GC) whose the doping is higher near the source side than the drain side and Dual Oxide Thickness (DOT). Analytical model for V TH and SS are developed by solving 2D Poisson equation using parabolic approximation method. Results for new device are compared to those obtained by numerical simulation and have been found to be in good agreement. Comparative study between (DMG-GC-DOT) SG MOSFET and with different device engineering shows that the new structure provides improved electron transport and reduced short channel effects (SCE).
International Journal of Information Sciences and Techniques (IJIST), 2011
In this paper we present a novel neural architecture to classify various types of VoD request arr... more In this paper we present a novel neural architecture to classify various types of VoD request arrival pattern using an unsupervised clustering Adaptive Resonance Theory 2 (ART2). The knowledge extracted from the ART2 clusters is used to prefetch the multimedia objects into the proxy server's cache, from the disk and prepare the system to serve the clients more efficiently before the user's arrival of the request. This approach adapts to changes in user request patterns over a period by storing the previous information. Each cluster is represented as prototype vector by generalizing the most frequently used video blocks that are accessed by all the cluster members. The simulation results of the proposed clustering and prefetching algorithm shows a significant increase in the performance of streaming server. The proposed algorithm helps the server's agent to learn user preferences and discover the information about the corresponding videos. These videos can be prefetched to the cache and identify those videos for the users who demand it.
Feature extraction is a method of capturing visual content of an image. The feature extraction is... more Feature extraction is a method of capturing visual content of an image. The feature extraction is the process to represent raw image in its reduced form to facilitate decision making such as pattern classification. We have tried to address the problem of classification MRI brain images by creating a robust and more accurate classifier which can act as an expert assistant to medical practitioners. The objective of this paper is to present a novel method of feature selection and extraction. This approach combines the Intensity, Texture, shape based features and classifies the tumor as white matter, Gray matter, CSF, abnormal and normal area. The experiment is performed on 140 tumor contained brain MR images from the Internet Brain Segmentation Repository. The proposed technique has been carried out over a larger database as compare to any previous work and is more robust and effective. PCA and Linear Discriminant Analysis (LDA) were applied on the training sets. The Support Vector Machine (SVM) classifier served as a comparison of nonlinear techniques Vs linear ones. PCA and LDA methods are used to reduce the number of features used. The feature selection using the proposed technique is more beneficial as it analyses the data according to grouping class variable and gives reduced feature set with high classification accuracy.
In this paper we present a novel neural architecture to classify various types of VoD request arr... more In this paper we present a novel neural architecture to classify various types of VoD request arrival pattern using an unsupervised clustering Adaptive Resonance Theory 2 (ART2). The knowledge extracted from the ART2 clusters is used to prefetch the multimedia objects into the proxy server's cache, from the disk and prepare the system to serve the clients more efficiently before the user's arrival of the request. This approach adapts to changes in user request patterns over a period by storing the previous information. Each cluster is represented as prototype vector by generalizing the most frequently used video blocks that are accessed by all the cluster members. The simulation results of the proposed clustering and prefetching algorithm shows a significant increase in the performance of streaming server. The proposed algorithm helps the server's agent to learn user preferences and discover the information about the corresponding videos. These videos can be prefetched to the cache and identify those videos for the users who demand it.
Cognitive assistance in knowledge engineering is a growing concern and information visualization ... more Cognitive assistance in knowledge engineering is a growing concern and information visualization is a very useful means to address this. This paper identifies some requirements for ontology visualization tools offering cognitive assistance and presents solutions with simple knowledge representations. This paper also identifies some of its features and describes areas need to be improved for effective visualization.
In today's world, data is generated at a very rapid speed and final destination of such data is d... more In today's world, data is generated at a very rapid speed and final destination of such data is database. Data is stored in database for easy and efficient way to manage these data. All the operations of data manipulation and maintenance are done using Database Management System. Considering the importance of data in organization, it is absolutely essential to secure the data present in the database. A secure database is the one which is reciprocated from different possible database attacks. Security models are required to develop for databases. These models are different in many aspects as they are dealing with different issues of the database security. They may different also because of they are taking different assumptions about what constitutes a secure database. So, it becomes very difficult for database security seekers to select appropriate model for securing their database. In this paper, we have discussed some of the attacks that can be possible with its counter measures and its control methods that can be possible. Securing database is important approach for the planning of explicit and directive based database security requirements. Ensuring security for database is very critical issues for the companies. As complexity of database increases, we may tend to have more complex security issues of database.
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Papers by International Journal of Information Sciences and Techniques (IJIST)
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.