Data Consistency of Distributed Transaction for Order Management

The client/server method of networkcommunications is the most popular one. Its easeof implementation and scalability make it agood choice in many different kinds ofnetworking environments.A client transactionbecomes distributed if it invokes operations inseveral different servers. The general elements oftransaction processing are data capture andvalidation, transaction-dependent processing stepsand database maintenance. DatabaseManagement Systems (DBMS) are among the mostcomplicated applications. While DBMS maintainsall information in the database, applications canaccess this information through statements madein Structured Query Language (SQL), a languagefor specifying high-level operations. This systemintends to build a distributed transactionmanagement systemfor store ordering withrecovery control to guarantee the consistency ofdatabase.The servers accept the order oftransactions and then manipulate the transactionsto reach the goal.When the server crashes orconnection fails, the uncommitted transaction issaved at the client store as the recoverable objectsand will undo at the next time for databaseconsistency.This paper intends to apply twomethods for distributed transactions: namely FlatTransaction and Two Phase Commit Protocol

Artificial Neural Network Based on Genetic Algorithm for Medical data diagnosis

Artificial neural networks (ANNs) are new technology emerged from approximate simulation of human brain and they have been successfully applied in many fields. Many researchers have tried to achieve optimal or near-optimal weights in artificial neural networks by using efficient methods. The traditional back propagation learning type requires huge number of training cycles and higher network configuration. Genetic algorithm (GA) can perform global search as against the local one performed by the gradient-based methods. Thus, GA can easily handle functions that are highly non-linear, complex, and noisy whereas the traditional gradient-based methods are inefficient. In this paper, genetic algorithm is used to adjust weight units which are important to improve network training in artificial neural networks. In the resulting ANNs-GA optimization approach, a trained ANN serves as an input-output model whose inputs are optimized by using the GA methodology. GA is used as embedded feature selection method to select relevant attributes before applying them to ANNs. And the proposed method diagnoses the medical datasets and compares accuracy of ANNs

Topic Maps Extraction on Focused Web Pages By Clustering with Web Structure and Contents

Web mining is the use of data miningtechniques to automatically discover and extractinformation from Web documents and services.This area of research is so huge today partly dueto the interests of various research communities,the tremendous growth of information sourcesavailable on the Web and the recent interest in ecommerce.Web mining is often associated withIR and IE.Web page clustering is one of the majorpreprocessing steps in web mining analysis.In thispaper, clustering method is proposed to semiautomaticallyextract Topic Maps from a set ofweb pages. Firstly, the web pages are downloadedfrom the internet. To extract contents, removestopwords and stem. And Second calculate theTF_IDF, content similarity, link similarity.Finally, calculating the Newman’s method withthe weighting based on the similarities by contentsof web pages and types of links is applied todevelop the potential clusters. Then the systemgenerates the topic map by assuming the clustersas topics, the edges as associations, the web pagesrelated to the topic as occurrences from the resultof clustering. As the experimental result, morecompact and denser cluster

Reducing Error Rate for ASR using Semantic Error Correction Approach

Many application environments have already usedspeech interface. But the low speech recognition ratemakes it difficult to extend its application to newfields. In the human-computer interaction throughspoken dialogue are being investigated. AutomaticSpeech recognition (ASR) is the process of convertinga spoken speech into text that can be manipulated bythe computer. The state of the art in automatic speechrecognition has reached the point that searching forand extracting information from large speechrepositories. This system presents semantic-orientedapproach to correct both semantic and lexical errors,which is also more accurate for especially domainspecificspeech error correction. This paperdemonstrates the superior performance of thisapproach and some advantages over previous lexicalorientedapproaches by comparing such approaches.Experiments carried out on various speeches inEnglish syllable indicated a successful decrease in thenumber of errors and an improvement in overall errorcorrection rate

Science-related Articles Recommendation System from Big Data

Under the explosive increase of global data,the term Big data is mainly used to describeenormous datasets. With the availability ofincreasingly large quantities of digitalinformation, it is becoming more difficult forresearchers to extract and find relevant articlespertinent to their interests. In this system, wepropose an approach to discover andrecommend the desired articles by combiningcollaborative filtering (CF) with topic modeling.Correlated Topic Model (CTM) is used formodeling topics. Our approach not onlyconsiders the interactions between users throughcollaborative filtering but also learns theproperties of items involved through topicmodeling to improve recommendation. In orderto handle a large dataset, a Big data analyticstool Hadoop is used to perform processing overdistributed clusters. The proposed approachlearns the accuracy of the recommendation

Analyzing Word Error Rate using String Metrics Algorithm

The android speech recognizer acquiresspeech at run time through a microphone andprocesses the sampled speech to recognize theuttered text. But the output texts do not matchwith users’ data because English and Myanmartexts are different. This system thereforeproposed a method for obtaining more detailabout actual translation errors in the generatedoutput by using the Word Error Rate (WER)based on the string matching algorithms. Thispaper has investigated string metrics andcompared the performance of edit distance likeLeveshtein Distance (LD), Q-gram, cosinesimilarity and dice coefficient by conducting anexperiment on the Myanmar name using androidspeech recognizer output. In order to better fit avariety of android recognition problem overstrings, using the edit distance of LD isconsidered to be an appropriate approach. Thispaper shows over several experiments that thedistance obtains goods results in comparisonwith other normalized edit distance

Improving delivery service applying shortest path algorithm for large Road Network

Graphs and networks are collections of nodesand arcs.Numeric values on the links can representthe actual length of the link. This system presents thedelivery service problem by means of shortest pathalgorithm. Suppliers have to find the path plan to theplace where their products are being delivered,especially. in reference to the geographic position ofthe objects, its surroundings and the shortest path ofthe destination place from their current place. Forlarge road network, the method is based onpreprocessing and prepared for static graphs, i.e,graphs with fixed topology and edge costs.This system solves the suppliers’ Facingproblem in finding the shortest path by using A*Shortest Algorithm. A* is the most popular algorithmbeing used in finding the shortest path because of itsflexibility and potentially search in a huge area ofthe map

Forecasting for Myanmar Currency Exchange Rates By using Back Propagation Neural Network

Nowadays, forecasting of exchange ratesplays an important role in internationaleconomics. Additional to basic economic andfinancial news, investors and traders employ intheir decision process technical tools to analyzethe transaction data.In this paper, the system based on neuralnetworks implemented for forecasting MyanmarCurrency exchange ratesusing artificial neuralnetwork. The system uses back-propagationalgorithm to train the exchange rates. Feedforward neural network is used to improve theefficiency of the back-propagation. MultilayerPerceptron (MLP) network is the mainarchitecture. Network architecture parametersespecially number of input and number of hiddenlayers are analyzed.System performance isevaluated in terms of Mean Absolute Error(MAE). Daily historical price data for currencypairs for the last three years are inputted to thesystem. The system is implemented usingprogramming language C#

An Analysis on Tourism Industry Development of Beach Resorts within Ayeyarwady Region

Chaungtha and Ngwesaung beaches are situated in the southwestern part of Myanmar within Ayeyarwady Region. It is located in Rakhine coastal region. These beaches are popular and attractive tourist sites in Myanmar after Ngapali Beach. The paper mainly focuses on tourism industry development. The objectives of this paper are to assess the basic tourism requirements, to assess on tourism development, to find out the perception of tourists and local people on tourism industry and to make a comparative analysis on the development of tourism industry within beach resorts. The research use both quantitative and qualitative methods. Primary data conducted by interviews and discussions with tourists, visitors, local people, hotel managers, authority and responsible persons of departments concerned. Secondary data are also applied in this research; these data are obtained from various departments. The importance of 4As in assessment on perception of tourists is presented in this paper. SWOT analysis is also employed for identifying the strength, weakness, opportunities and treats. This research paper examines the positive and negative impacts of tourism development for beach resorts. According to the interview method, foreign tourists more prefer Ngwesaung to Chaungtha because of natural scenic beauty of blue sea, white sand and lovely sun. Domestic tourists more prefer Chaungtha