Identical and Incremental Routes Availability in Proposed MIN MALN and comparison with Alpha Network

Volume 6 Issue 2 March - May 2017

Research Paper

Identical and Incremental Routes Availability in Proposed MIN MALN and comparison with Alpha Network

Amardeep Gupta*

Head, PG Department of Computer Science and Information Technology, DAV College, Amritsar, Punjab, India.

Gupta, A. (2017). Identical and Incremental Routes Availability in Proposed MIN MALN and comparison with Alpha Network. i-manager’s Journal on Information Technology, 6(2), 8-10. https://doi.org/10.26634/jit.6.2.13570

Abstract

If the network is able to work, of course with degraded efficiency, in the presence of faults in critical components then the network is called as Fault-Tolerant. A network is single Fault-Tolerant, if it can work with full access in the presence of fault in single SE. If the network is able to provide connections from all sources to all destinations in the presence of k faults in the network, then this network is called as k Fault-Tolerant network. In this paper, routes available in the proposed MIN Modified Alpha Network (MALN) have been evaluated and compared with the existing Alpha (ALN) MIN.

Principal Component Analysis for Disease Diagnosis

Volume 6 Issue 2 March - May 2017

Research Paper

Principal Component Analysis for Disease Diagnosis

Juby Mathew*, R Vijayakumar**

* * Assistant Professor, Department of MCA, Amal Jyothi College of Engineering, Kanjirappally, Kerala, India.

** Professor and Dean, School of Computer Sciences, Mahatma Gandhi University, Kottayam, Kerala, India.

Mathew, J., and Kumar, R. V. (2017). Principal Component Analysis for Disease Diagnosis. i-manager’s Journal on Information Technology, 6(2), 1-7. https://doi.org/10.26634/jit.6.2.13569

Abstract

The new generation of personal authentication technologies based on individual biological characteristics is the core of various applications of the real or the virtual society. The volume of the medical data is increasing due to the presence of vast amount of features, the conventional rule mining technique is not competent to handle the data and to perform precise diagnosis. For instance, this paper intends to implement the improved rule mining technique to overcome limitations. The proposed method has two main contributing stages. The first stage is the robust feature extraction process using the improved Multi-Linear Principal Component Analysis (PCA), whereas the second stage is the classification process using Support Vector Machine. Principal Components Analysis (PCA) is the most commonly-used dimensionality reduction technique employed for the feature extraction of neural spikes.

Big Data-A Review

Volume 6 Issue 1 December - February 2017

Review Paper

Big Data-A Review

Hardeep Singh*, GURPREET SINGH**

* Assistant Professor, Department of Computer Science & Engineering, Guru Nanak Dev University Regional Campus, Sathiala, Amritsar, India.

** Assistant Professor, Department of Computer Science & Engineering, Guru Nanak Dev University Regional Campus, Fattu Dhinga, Kapurthala, India.

*** PG Scholar, Department of Computer Science & Engineering, Guru Nanak Dev University Regional Campus, Sathiala, Punjab, India.

Hardeep Singh, Gurpreet Singh and Gurpreet Singh (2017). Analysis of Image Enhancement Algorithms. i-manager’s Journal on Information Technology, 6(1), 36-43. https://doi.org/10.26634/jit.6.1.13507

Abstract

Big data is the current state-of-the-art topic creating its unique place in the research and industry minds to look into depth of topic to get valuable considerable results needed to meet the future data mining and analysis needs. Big data refers to the fast moving, large size of different structural form data increasing at fast pace. So, there also prevail the need of tools to tackle it as the current and traditional techniques are getting unfit for the current key challenges and security aspects of big data. This paper deals with characteristics of big data, applications of big data in various different fields as it has now became a multi-disciplinary aspect to review. Big data generation, storing, analysis and transmission are increasingly growing which has accompanied it as its characteristics. In this paper, different sections through an overlook on different aspects on big data, such as sources, security challenges, and future directions regarding big data mining and analysis have been discussed.

Analysis of Image Enhancement Algorithms

Volume 6 Issue 1 December - February 2017

Research Paper

Analysis of Image Enhancement Algorithms

Koushal Kumar*, Jaspreet Singh**

* Assistant Professor, Department of Computer Science, Sikh National College, Punjab, India.

** Research Scholar, Department of Computer Science, Guru Nanak Dev University, Amritsar, Punjab, India.

Koushal Kumar and Jaspreet Singh (2017). Analysis of Image Enhancement Algorithms. i-manager’s Journal on Information Technology, 6(1), 25-35. https://doi.org/10.26634/jit.6.1.13506

Abstract

Due to the restrictions of image-catching gadgets or the presence of a non-ideal environment, the quality of digital images may get corrupted. Much of the time, these images might demand a certain level of enhancement for satisfactory visual representation. Image enhancement is a procedure to evacuate the undesirable distortion due to deterioration in contrast, unwanted noise, improper intensity saturation, blurring effect, etc., and determine the hidden information that are contained in images. The main goal of Image enhancement is to process an image so that the result is more suitable than original image for particular application. Many image enhancement techniques are based on spatial operations performed on local neighborhoods of input pixels. Conventional global histogram equalization few times becomes a reason for immoderate contrast enhancement, thus local histogram equalization may cause block effect. Therefore to conquer these problems, a new way for image contrast enhancement is presented in this research work. The curiosity of the proposed strategy is that the weighted average of the histogram equalized, gamma corrected, and the original image are combined to obtain the enhanced processed image. The proposed algorithm not only achieves contrast enhancement, but also preserves a sufficient level of brightness level. This study will highlight various image enhancement techniques along with their benchmark results. Empirical study results demonstrate that the proposed algorithm has good performance on enhancing contrast and clarity for a larger part of images.

Historical Tamil Character Recognition based on Clustering

Volume 6 Issue 1 December - February 2017

Research Paper

Historical Tamil Character Recognition based on Clustering

G. Prabhakaran*, R. Meera**

* Assistant Professor, Department of Computer Science and Engineering, E.G.S. Pillay Engineering College, Nagapattinam, India.

** PG Scholar, Department of Computer Science and Engineering, E.G.S. Pillay Engineering College, Nagapattinam, India.

G. Prabhakaran and R. Meera (2017). Historical Tamil Character Recognition based on Clustering. i-manager’s Journal on Information Technology , 6(1), 19-24. https://doi.org/10.26634/jit.6.1.13505

Abstract

A novel method using clustering algorithm is proposed to recognize the tamil characters in a given document. Many algorithms and processing techniques exist, which are used only for certain languages and hard specific file formats. This does not involve any pre-processing on the documents like contrast adjustments or filtering of noises on the image. Considering all these negativities, a novel method is proposed in this project, where the input can be of any file type which undergoes pre-processing like contrast adjustment before applying the procedure. Above all, this method is used to replace the historical Tamil words in the earlier Tamil documents to the words corresponding to them that are in use today.

Recognition of Offline Handwritten Gujarati Numerals

Volume 6 Issue 1 December - February 2017

Research Paper

Recognition of Offline Handwritten Gujarati Numerals

Bharat C. Patel*, Manish M. Kayasth**

* Assistant Professor and I/c Principal, Smt. Tanuben & Dr. Manubhai Trivedi College of information Science, Surat, India.

** Assistant Professor and HOD, UCCC & SPBCBA & SDHG College of BCA and IT, Surat, India.

Bharat C. Patel and Manish M. Kayasth (2017). Recognition of Offline Handwritten Gujarati Numerals. i-manager’s Journal on Information Technology, 6(1), 14-18. https://doi.org/10.26634/jit.6.1.13504

Abstract

In Optical Character Recognition, written characters are recognized by computer based system. Such characters might be computer generated or handwritten. In case writing process is over, it is considered as offline writing. This paper proposes offline handwritten Gujarati numerals (0-9) recognition. Offline handwritten character recognition is an important area of pattern recognition. The entire character recognition task is logically divided into Image acquisition, preprocessing, feature extraction, classification, and recognition steps. To recognize Gujarati numeral features, such as hole, straight-line, number of open/end edge and open edge present in different zone(s), etc., are extracted. As per the result of different extracted features for particular Gujarati numeral, classification is carried out. Methodology, Implementation of it, and the results obtained are presented in the paper.

Performance Evaluation of MANET Routing Protocols using NETSIM

Volume 6 Issue 1 December - February 2017

Research Paper

Performance Evaluation of MANET Routing Protocols using NETSIM

Gurpreet Singh*, Hardeep Singh**

* Assistant Professor, Department of Computer Science and Engineering, Guru Nanak Dev University Regional Campus, Sultanpur Lodhi, Punjab, India.

** Assistant Professor, Department of Computer Science and Engineering, Guru Nanak Dev University Regional Campus, Sathiala, Punjab, India.

Gurpreet Singh and Hardeep Singh (2017). Performance Evaluation of MANET Routing Protocols using NETSIM. i-manager’s Journal on Information Technology, 6(1), 8-13. https://doi.org/10.26634/jit.6.1.13503

Abstract

Mobile Ad Hoc Network (MANET) is a wireless, infrastructureless network where each node acts as a router, transmitter, and data sink. The objective of this paper is to evaluate the performance of reactive, proactive, and hybrid routing protocols of Mobile Ad-Hoc networks (MANET's) for Custom application. The authors’ have evaluated three routing protocols, i.e. AODV, OLSR, and ZRP by using NETSIM simulator tool. The performance of these routing protocols is examined by two application metrics: throughput and delay. The study of protocols will be carried out and finally the results will be presented as to which routing protocol is a better one for MANET.