Manuscripts

Recent Papers

Research Paper

ECLAT based market basket analysis for electronic showroom

Market basket analysis is a data mining technique to discover associations between datasets. Association rule mining identifies a relationship between a large set of data items. When a large quantity of data is constantly obtained and stored in databases, several industries are becoming concerned with mining association rules from their databases. Market basket analysis examines customer buying patterns by identifying associations among various items that customers place in their shopping baskets. It is helpful to examine customer purchasing behavior and assists in increasing sales. So, this system is intended to develop a system for market basket analysis on Electronic showroom which will generate association rules among itemsets with the use of ECLAT (Equivalence Class Transformation) algorithm. This system supports the decision-making process for a market expert.

Published by: Moe Moe Hlaing

Author: Moe Moe Hlaing

Paper ID: V4I7-1140

Paper Status: published

Published: July 24, 2019

Full Details
Research Paper

Tanimoto coefficient based Word Sense Disambiguation

In many NLP applications such as machine translation, content analysis, and information retrieval, Word Sense Disambiguation (WSD) is an important technique. Word sense disambiguation is the essence of communication in a natural language. WSD process is useful for automatically identifying the correct meaning of an ambiguous word in the sentence or the query when it has multiple meanings. So, this system proposes as the Tanimoto coefficient based word sense disambiguation system to increase the precision of the NLP application. This system provides additional semantic as conceptually related words with the help of glosses to each keyword in the inputted sentence by disambiguating their meanings. This system uses the WordNet as the lexical resource that encodes concepts of each term.

Published by: Hnin Yu Yu Win, Htwe Htwe Pyone

Author: Hnin Yu Yu Win

Paper ID: V4I7-1141

Paper Status: published

Published: July 22, 2019

Full Details
Research Paper

Image segmentation by using global and local thresholding algorithm

Image segmentation is one of the most difficult and challenging tasks in many image processing. Several general-purpose algorithms and techniques have been developed in medical application. Image processing describes the analysis images and obtaining desired segmentation results. Many researchers have used various types of techniques to review the images. The goal of image segmentation is to partition an image into more meaningful and easier use to analyze the various features of that image. Segmentation techniques are involving detection, recognition, and measurement of features. The segmentation algorithm is based on color and gray value images. Among all the segmentation methods, the fundamental approach to segment an image is based on the intensity levels and is called a threshold-based. One of the widely used techniques is thresholding. Thresholding is the simplest approaches to separate object from the background and it is widely used for medical image processing. Thresholding technique creates a grayscale image into a binary image. Thresholdng and edge detection are an important technique in image processing. Thresholding techniques can be classified into two thresholdings. These are global thresholding and local thresholding. The local thresholding method is divideded the original image into small sub images. It determines a threshold value for each of subimages. Global thresholding method determines a single threshold value in the whole images. The thresholding values are depending upon the spatial coordinates. In this paper, we analyze an efficient segmentation of for three different thresholding methods. These methods are Otsu’s, Feng’s and Sauvola methods. The three thresholding algorithms have been simulated in MATLAB.

Published by: Hla Hla Myint, Phyo Phyo Wai, Dr. Moe Moe Zaw

Author: Hla Hla Myint

Paper ID: V4I7-1139

Paper Status: published

Published: July 19, 2019

Full Details
Review Paper

Common problems when driving on Internet of Things

Internet of Things is a platform where everyday devices become smarter, more intelligent on the processor, and every day communication becomes informative. In a few short years, the Internet of Things (IoT) has gone from a technology — or set of technologies- that were cutting edge to the situation today where connected household items, or automobiles, are common. However, growth is only really gathering speed now with San Francisco-based Cisco estimating that the "Internet of Everything cisco article" its take on the IoT could have has many as 50 billion connected devices by 2020. Not only are they trying to make the most of IoT integration to benefit their own company, but they’re also treading new ground and serving as role models for those who have yet to take the plunge. Directly or indirectly, the presented architectures propose to solve real-life problems by building and deployment of powerful Internet of Things notions. If the IoT has a problem or is exposed to weaknesses, then the enterprises that are connected to it are equally threatened. In fact, while security is undoubtedly one of the major issues impacting the development, there are a number of other problems that stem directly from this. Here are 7 major IoT problems for enterprises connecting to the IoT. These paper have an explaining of IoT architectural and big problems when connection on IoT.

Published by: Khine Khine Aung, Nwet Nwet Than

Author: Khine Khine Aung

Paper ID: V4I7-1138

Paper Status: published

Published: July 18, 2019

Full Details
Review Paper

Technologies usages of big data in small and medium sized enterprises

Big Data means a large chunk of raw data that is collected, stored and analyzed through various means which can be utilized by organizations to increase their efficiency and take better decisions. Big Data can be in both - structured and unstructured forms. Structured Data is more easily analyzed and organized into the database. Unstructured Data, on the other hand, is much harder to analyze and uses a variety of formats. Also, it is not easily interpreted by traditional data models and processes. We come to a place that at the same time becomes the starting point for the potential use of Big Data in small and medium-sized organizations, that is basing the decision-making process fully on the results of analyzes of diversified data. Thanks to this approach, the decisions made, both strategic and operational, are subject to a lower risk of failure. Big data provides an opportunity for organizations to gain insights from their data in order to make better decision. Large companies in several sectors are achieving enormous improvements by applying big data analytics. Small and medium enterprises (SMEs), which have smaller size and less revenue, can also benefit from big data to add value to their business. This also applies to Big Data database technologies, which is applicable in various sectors of the economy, but due to the high investment costs of implementing this technology in the business processes of business entities, so far only large corporations and larger enterprises can afford such technologies. In this paper, already ex-plained about Big Data analysis data of Google, IBM and other related enterprise company and Big Data future research.

Published by: Nwet Nwet Than, Khine Khine Aung

Author: Nwet Nwet Than

Paper ID: V4I7-1137

Paper Status: published

Published: July 18, 2019

Full Details
Research Paper

Comparative study of C5.0 and Cart Algorithms in crop pest detection

Most of the people who live in our country, Myanmar are farmers and they work mainly on farming and crop growing. Data mining can help farmers to increase crop yield in agriculture field of country development. Crops can be protected from pests by predicting and enhancing crop cultivation by using data mining approaches. The purpose of this paper is to study a comparison of two data mining approaches C5.0 and CART algorithms. This paper also presents oneR feature selection method for filtering crop pest dataset attributes instead of using full attribute set. C5.0 proved its efficiency by giving more accurate result rapidly and holding less memory while comparing the CART algorithm.

Published by: Myint Myint Than, Mang Biak Song

Author: Myint Myint Than

Paper ID: V4I7-1136

Paper Status: published

Published: July 18, 2019

Full Details
Research Paper

Usage and satisfaction of electronic information resources available in the engineering college libraries of Chittoor district by the students and faculty members: A study

The present study deals with the usage and satisfaction of electronic information resources by the students and faculty members available in the engineering college libraries in Chittoor District, Andhra Pradesh. A total number of 1900 questionnaires were distributed and filled-in questionnaires 1216 have been received. The study found that the majority of the respondents (29.3%) browse electronic information resources every day. The study reveals that majority of the respondents (50.8%) said that e-mail alerts from the Publishers/Distributors are the awareness factor for them. The study also found that the majority (66.6%) of the respondents are accessing e-journals frequently and 83.6% opined that the electronic information resources are most useful for their academic purpose.

Published by: M. N. Mythili Rajyalakshmi

Author: M. N. Mythili Rajyalakshmi

Paper ID: V4I6-1144

Paper Status: published

Published: July 8, 2019

Full Details
Research Paper

Dynamic sealing design for Wankel Engines

The development of the Wankel engine is mainly dependent on the solution of the apex and face seal. In the Wankel engine, one of the major disadvantages of power loss is the improper sealing between the rotor and cylinder wall. To overcome this problem we can use the following modified design of sealing. This dynamic seal provides efficient sealing and along with this, a modified lubrication system is also implemented which helps to prevent the burning loss of lubricating oil inside the cylinder. This two possible modification can help to get lower wear and tear of seals, lower exhaust emission gases and also it will help to prevent the loss of lubrication oil inside the engine.

Published by: Rushikesh Puranik, Aman Akotkar

Author: Rushikesh Puranik

Paper ID: V4I6-1140

Paper Status: published

Published: July 1, 2019

Full Details
Research Paper

Panorama image processing system using Scale-Invariant Feature Transform (SIFT)

Image stitching is the process to generate one large panoramic image from collective relative image sequence without overlapping. Panoramic photo stitching is the process of combining multiple photographic images with overlapping fields of view to produce a panorama. The process to generate a panoramic view can be divided into three main components - image feature detection, image matching, and blending. Scale Invariant Feature Transform (SIFT) used to extract the features from the images and matching them which is a part of image registration. SIFT features are invariant to rotation, translation, image scaling and partially invariant to a 3D viewpoint, illumination changes and image noise. Image transformation is estimated using holography. Image blending technique is used to blend the images together to get a panoramic view. Main applications of panoramic view include creating a virtual environment for virtual reality, modeling the 3D environment using images acquired from the real world.

Published by: Nay Myo Aung

Author: Nay Myo Aung

Paper ID: V4I6-1142

Paper Status: published

Published: June 27, 2019

Full Details
Research Paper

Deepfakes : How a pervert shook the world

Recently a software has made it easy to create hyper-realistic face swaps in videos that leaves little-to-no traces of manipulation, in what is known as “deepfake” videos. Scenarios, where these AI manipulated/generated videos, are used for political distress, blackmail or even terrorism are easily envisioned as a near dystopia. This paper explores the various aspects of deepfake videos including its consequences and newly developed innovations in detecting deepfakes.

Published by: Ronit Chawla

Author: Ronit Chawla

Paper ID: V4I6-1143

Paper Status: published

Published: June 22, 2019

Full Details