Taxonomic Study on Five Dendrobium Species from Mt. Poppa Area

Mt. Poppa area is mostly covered with tropical evergreen forests and distribution of many wild orchids. Among them, five species of Dendrobium are described in this research. All collected species are fully described with necessary photographs. Moreover, the artificial key to the species of the plants is also described. The system of Seidenfaden (1992) was adopted as the classification system in the present research

2D image reconstruction using bicubic interpolation

2D image reconstruction is an important task in many applications of computer vision. The objective of image reconstruction is to recover a degraded image based on mathematical and statistical models. When an image is sent via network, image’s size is reduced to fast and low cost. Although the small size images are very useful in the data storage and image transmission, the detail and clear information can’t be received from small image. So, small image is needed to enlarge to get visual contents clearly. In enlarged image, some pixel positions are lost and needed to fill. Interpolation is the process which generates pixels to fill in the blanks. In this paper, image reconstruction approach is developed based on bicubic interpolation method. This method can produce good image with fine detailed information. This approach can be used to assist in photo editing processes and other computer vision applications

2D image reconstruction using bicubic interpolation

2D image reconstruction is an important taskin many applications of computer vision. The objectiveof image reconstruction is to recover a degradedimage based on mathematical and statistical models.When an image is sent via network, image’s size isreduced to fast and low cost. Although the small sizeimages are very useful in the data storage and imagetransmission, the detail and clear information can’t bereceived from small image. So, small image isenlarged to get visual contents clearly. In enlargedimage, some pixel positions are needed to fillInterpolation is the process which generate pixels tofill in the blanks. In this paper, image reconstructionapproach is developed based on bicubic interpolationmethod. This method can produce good image withfine detailed information. This approach can be usedto assist in photo editing processes and othercomputer vision applications

Image resampling using non-adaptive interpolation

Image resampling is a process which change the sizeof an image. It generates output image of thespecified dimension with the help of the interpolationtechniques. The up-sampled images are lost finedetailed information due to artifacts. This is aproblem to define detail content clearly. This is achallenge to restore the lost information. Manyrestoration methods have been developed Theproposed framework is based on non-adaptiveinterpolation method. Non-adaptive method is fasterthan adaptive one. This framework can interpolateand produce good image with fine detailedinformation. This approach can assit in photoediting process and other image processingapplication

Image Zooming with Linear Interpolation

Image zooming is a vital role in image processing. The zoomed images can be distorted because of blocky or jaggy effects. Sometimes, there is a problem to define the content of image or photo. The distorted image is needed to restore its fine detailed information. Our main idea is to restore or sharp blurred images. Many iterpolation methods have been developed in the last decade. We proposed an interpolation framework based on iterative linear interpolation method that can interpolate and produce good image with fine detailed information. Although linear interpolation use the same value for the whole image pixel values, our experiment show good and useful result with color image. This approach can assist in medical image analysis and photo editing process with efficient zooming method

Myanmar Traditional Naming System by Using Rule-based Expert System With Forward Chaining

Integrating AI technology with other computer-based information system increases the capability of computers. An expert system is a kind of computer program, which is assumed as an important role in astrology for creating people’s name with good fortune and jobs, marriage partner and charms according to BAYDIN method. This rule-based expert system can create names based on the known facts and rules by using inference engine focused on forward chaining approach. In this system, rules are used from rule based and forward chaining approach is used to inference. This system can give not only user’s new name with charms, marriage partner and work but also checking user’s current name with BRYDIN method to know name classes within short time of period by using knowledge derived from expert astrologers’ researches. It is implemented by using C# language and Microsoft Access 2007 platform

Implementation of Recommender System for Book Store Using Decision Tree Technique

The proposed system is the recommender system for book store using decision tree induction technique which is the data mining technique of the recommendation to extract rules in terms of entropy and information gain and to recommend the item to the customer. There had been various kinds of recommendation systems with different techniques. The recommendation system is to recommend the item that the customers wanted to buy and easy buying for customers .In addition ,many vendors are trying to compete each other to give good services to the customers who use their system to get their satisfaction and to promote and sale their product. The proposed system can determine what kind of item the customer really want to buy

Comparison of Levenshtein Distance Algorithm and Needleman-Wunsch Distance Algorithm for String Matching

String similarity measures play anincreasingly important role in text related researchand applications in tasks and operate on stringsequences and character composition. A string metricis a metric that String_Based measures similarity ordissimilarity (distance) between two strings forapproximate string matching or comparison.Determining similarity between texts is crucial tomany applications such as clustering, duplicateremoval, merging similar topics or themes, textretrieval and etc. Among many methods of Stringsimilarity, Levenshtein Distance Algorithm andNeedleman-Wunsch Distance Algorithm are used inthis proposed system. The proposed system intendedto present by comparing Levenshtein DistanceAlgorithm and Needleman-Wunsch DistanceAlgorithm based on their f-score. So, user can searcheffectively the required song by typing the title ofsongs or artist name using English language in thisproposed system. Then the proposed system retrievethe user’s required song information with similarityscore. The matching efficiencies of these algorithmsare compared by searching f-score and executiontime. The proposed system uses song title and artistfeature of billboard song dataset from year 1965-2015 and implements using Java programminglanguage