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International Journal of Informatics and Communication Technology (IJ-ICT)

IJICT
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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 8 Documents

Search results for , issue "Vol 8, No 1: April 2019" : 8 Documents clear

Predicting heart ailment in patients with varying number of features using data mining techniques T R Stella Mary; Shoney Sebastian
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 8, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Data mining can be defined as a process of extracting unknown, verifiable and possibly helpful data from information. Among the various ailments, heart ailment is one of the primary reason behind death of individuals around the globe, hence in order to curb this, a detailed analysis is done using Data Mining. Many a times we limit ourselves with minimal attributes that are required to predict a patient with heart disease. By doing so we are missing on a lot of important attributes that are main causes for heart diseases. Hence, this research aims at considering almost all the important features affecting heart disease and performs the analysis step by step with minimal to maximum set of attributes using Data Mining techniques to predict heart ailments. The various classification methods used are Naïve Bayes classifier, Random Forest and Random Tree which are applied on three datasets with different number of attributes but with a common class label. From the analysis performed, it shows that there is a gradual increase in prediction accuracies with the increase in the attributes irrespective of the classifiers used and Naïve Bayes and Random Forest algorithms comparatively outperforms with these sets of data.

Enabling social WEB for IoT inducing ontologies from social tagging Mohammed Alruqimi; Noura Aknin
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 8, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Semantic domain ontologies are increasingly seen as the key for enabling interoperability across heterogeneous systems and sensor-based applications. The ontologies deployed in these systems and applications are developed by restricted groups of domain experts and not by semantic web experts. Lately, folksonomies are increasingly exploited in developing ontologies. The “collective intelligence”, which emerge from collaborative tagging can be seen as an alternative for the current effort at semantic web ontologies. However, the uncontrolled nature of social tagging systems leads to many kinds of noisy annotations, such as misspellings, imprecision and ambiguity. Thus, the construction of formal ontologies from social tagging data remains a real challenge. Most of researches have focused on how to discover relatedness between tags rather than producing ontologies, much less domain ontologies. This paper proposed an algorithm that utilises tags in social tagging systems to automatically generate up-to-date specific-domain ontologies. The evaluation of the algorithm, using a dataset extracted from BibSonomy, demonstrated that the algorithm could effectively learn a domain terminology, and identify more meaningful semantic information for the domain terminology. Furthermore, the proposed algorithm introduced a simple and effective method for disambiguating tags.Semantic domain ontologies are increasingly seen as the key for enabling interoperability across heterogeneous systems and sensor-based applications. The ontologies deployed in these systems and applications are developed by restricted groups of domain experts and not by semantic web experts. Lately, folksonomies are increasingly exploited in developing ontologies. The “collective intelligence”, which emerge from collaborative tagging can be seen as an alternative for the current effort at semantic web ontologies. However, the uncontrolled nature of social tagging systems leads to many kinds of noisy annotations, such as misspellings, imprecision and ambiguity. Thus, the construction of formal ontologies from social tagging data remains a real challenge. Most of researches have focused on how to discover relatedness between tags rather than producing ontologies, much less domain ontologies. This paper proposed an algorithm that utilises tags in social tagging systems to automatically generate up-to-date specific-domain ontologies. The evaluation of the algorithm, using a dataset extracted from BibSonomy, demonstrated that the algorithm could effectively learn a domain terminology, and identify more meaningful semantic information for the domain terminology. Furthermore, the proposed algorithm introduced a simple and effective method for disambiguating tags.

Notice of Retraction A survey of arabic text classification models Ahed M. F. Al Sbou
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 8, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Notice of Retraction-----------------------------------------------------------------------After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IAES's Publication Principles.We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.The presenting author of this paper has the option to appeal this decision by contacting info@iaesjournal.com.-----------------------------------------------------------------------There is a huge content of Arabic text available over online that requires an organization of these texts. As result, here are many applications of natural languages processing (NLP) that concerns with text organization. One of the is text classification (TC). TC helps to make dealing with unorganized text. However, it is easier to classify them into suitable class or labels. This paper is a survey of Arabic text classification. Also, it presents comparison among different methods in the classification of Arabic texts, where Arabic text is represented a complex text due to its vocabularies. Arabic language is one of the richest languages in the world, where it has many linguistic bases. The research in Arabic language processing is very few compared to English. As a result, these problems represent challenges in the classification, and organization of specific Arabic text. Text classification (TC) helps to access the most documents, or information that has already classified into specific classes, or categories to one or more classes or categories. In addition, classification of documents facilitate search engine to decrease the amount of document to, and then to become easier to search and matching with queries.

A new complexity reduction methods of V-BLAST MIMO system in a communication channel Sunita Panda; Rosalin Samantaray; Pradyumna Ku. Mohapatra; R.N. Panda; Padma Sahu
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 8, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

To design most reliable wireless communication system we need an efficient method which can be proposed in this paper is V-BLAST technique which is most powerful tool in MIMO system. To improve the channel capacity and data rate efficiently we need manifold antennas together with the transmitter and receiver. In this paper we have analyzed different equalizers performance using V-BLAST algorithm. We have proposed two methods i.e. low complexity QR algorithm and another is consecutive iterations reduction method. This methods compare with traditional finding methods such as ZF, MMSE, SIC and ML. The proposed algorithm shows that it not only reduce the computational complexity but we can achieve significant bit error rate (BER) and probability error compared to traditional VBLAST techniques.

Recent trends in big data using hadoop Chetna Kaushal; Deepika Koundal
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 8, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Big data refers to huge set of data which is very common these days due to the increase of internet utilities. Data generated from social media is a very common example for the same. This paper depicts the summary on big data and ways in which it has been utilized in all aspects. Data mining is radically a mode of deriving the indispensable knowledge from extensively vast fractions of data which is quite challenging to be interpreted by conventional methods. The paper mainly focuses on the issues related to the clustering techniques in big data. For the classification purpose of the big data, the existing classification algorithms are concisely acknowledged and after that, k-nearest neighbor algorithm is discreetly chosen among them and described along with an example.

A novel sketch-based 3D model retrieval approach based on skeleton Jing Zhang; Bao Sheng Kang; Bo Jiang; Di Zhang
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 8, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Since the skeleton represents the topology structure of the query sketch and 2D views of 3D model, this paper proposes a novel sketch-based 3D model retrieval algorithm which utilizes skeleton characteristics as the features to describe the object shape. Firstly, we propose advanced skeleton strength map (ASSM) algorithm to create the skeleton which computes the skeleton strength map by isotropic diffusion on the gradient vector field, selects critical points from the skeleton strength map and connects them by Kruskal's algorithm. Then, we propose histogram feature comparison algorithm which adopts the radii of the disks at skeleton points and the lengths of skeleton branches to extract the histogram feature, and compare the similarity between two skeletons using the histogram feature matrix of skeleton endpoints. Experiment results demonstrate that our approach which combines these two algorithms significantly outperforms several leading sketch-based retrieval approaches.

Randomized scheduling algorithm for virtual output queuing switch at the presence of non-uniform traffic Ali Ghiasian; Majid Jamali
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 8, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Virtual Output Queuing (VOQ) is a well-known queuing discipline in data switch architecture that eliminates Head Of Line (HOL) blocking issue. In VOQ scheme, for each output port, a separate FIFO is maintained by each input port. Consequently, a scheduling algorithm is required to determine the order of service to virtual queues at each time slot. Maximum Weight Matching (MWM) is a well-known scheduling algorithm that achieves the entire throughput region. Despite of outstanding attainable throughput, high complexity of MWM makes it an impractical algorithm for implementation in high-speed switches. To overcome this challenge, a number of randomized algorithms have been proposed in the literature. But they commonly perform poorly when input traffic does not uniformly select output ports. In this paper, we propose two randomized algorithms that outperform the well-known formerly proposed solutions. We exploit a method to keep a parametric number of heavy edges from the last time matching and mix it by randomly generated matching to produce a new schedule. Simulation results confirm the superior performance of the proposed algorithms.

Security in wireless sensor networks Bahae Abidi; Abdelillah Jilbab; Mohamed El Haziti
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 8, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Even in difficult places to reach, the new networking technique allows the easy deployment of sensor networks, although these wireless sensor networks confront a lot of constraints. The major constraint is related to the quality of information sent by the network. The wireless sensor networks use different methods to achieve data to the base station. Data aggregation is an important one, used by these wireless sensor networks. But this aggregated data can be subject to several types of attacks and provides security is necessary to resist against malicious attacks, secure communication between severely resource constrained sensor nodes while maintaining the flexibility of the topology changes. Recently, several secure data aggregation schemes have been proposed for wireless sensor networks, it provides better security compared with traditional aggregation. In this paper, we try to focus on giving a brief statement of the various approaches used for the purpose of secure data aggregation in wireless sensor networks.

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