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Image binarization is divided into global algorithm and local algorithm. Global binarization algorithms have a problem to describe objects that have similar brightness with a single threshold. Local binarization algorithms make boundary lines because these algorithms split the image into a specific size of blocks. Therefore, in this paper, we propose a binarization method to complement these problems. The proposed method uses triangular fuzzy membership function to classify the image into obvious regions and ambiguous regions. Obvious regions are binarized by using global binarization algorithm. Whereas ambiguous regions are binarized by using improved local algorithm. Experimental results show the proposed method binarizes the image with less information loss. Moreover, binarized image describes the object in more detail than global binarization methods and more natural than local binarization method.

This paper presents a new domain-specific language (DSL) and its interpreter. The purpose of the language is to be a tool for software developers and administrators that allows them to easily specify how configuration files in INI format should look like and what rules should their contents comply with. The interpreter of the language then takes a specification of a configuration file written in the DSL and verifies whether configuration files given as an input match the specification. The requirement for the language emerged at CERN (European Organization for Nuclear Research). The reason is that CERN, one of the biggest research organizations in the world, heavily uses SCADA (Supervisory Control and Data Acquisition) software for their industrial and scientific machines and SCADA developers needed to be able to verify that configuration files used by CERN's SCADA (WinCC Open Architecture) software are correct and comply with CERN standards. The newly designed DSL is primarily based on declarative paradigm and its core capabilities can be extended by JavaScript code injection. The language syntax is also a superset of INI files syntax so it feels familiar to people who want to use it for simple verification use cases. As for the interpreter, it uses Xtext-based parser to create abstract syntax trees and to integrate with the Eclipse Platform. The execution of the DSL code then uses a hybrid architecture which combines AST interpretation, translation of certain parts of AST into a JavaScript code and running JavaScript code on top of the Java Virtual Machine.

Under the circumstances in which the distribution rate of water supply reaches 98.6%, efforts for stable operation of facilities are being carried out through a variety of studies. The asset management of water supply system using a life cycle cost analysis model is expected to be settled and stabilized within the next decade through continuous researches. An analysis model is divided into several stages of initial installation cost, maintenance cost, and disposal/replacement cost. In this research, a portion of YW filtration plant’s data was used to conduct an LCC analysis. Through an LCC analysis, asset management was performed and ways to efficiently distribute a budget and to ensure stability were proposed.

In modern society, email is at the heart of communications in businesses. Its own simplicity of usage and low cost compared to other means of communications leave workers highly replying on it by using them for a variety of purposes from informal communications to exchanges of confidential information. However, possibly due to such trend of usage, a lot of problematic cases have occurred where a business’s security got in trouble by a worker’s careless email use. This study introduces a method to help detect such problematic and careless email use based on analyzing actual enterprise email data. It is designed to help discover email messages that have replies from someone but possibly asked no reply, which is the case we suggest can be a clue to the writer’s carelessness. The method involves building document vectors through a basic bag-of-words model and Word2Vec, which is a state-of-the-art method to create document vectors out of text documents. For an experiment of classifying email messages to find likely careless email messages, Enron email dataset was utilized to be input to the system we made. What the experiment results produce is a list of email messages to be watched before other email messages for the purpose of finding careless email messages.

Face Recognition is the most focused topic in the field of computer vision and pattern recognition. It has become a major thrust area for research in the last two decades due to the security aspects and demand for video. Face is focus of attention in the social intercourse and it plays a vital role in identification and recognition of individual emotions. Several facial recognition algorithms were developed and discussed in the literature but very little work is focused on facial recognition based on illumination. The appearance of the face image is usually affected by illumination conditions that hinder the facial recognition process. Hence in this paper, we propose and develop a new facial recognition algorithm based on Adaptive Haar Wavelet Transform called Tetrolet Transfrom. In Tetrolet transform, the determined orthonormal basis functions are adapted to geometrical features of the image follow a Truncated Gaussian Mixture Model (TGMM). The truncation on the feature vector has a significant influence in improving the recognition rate of the system.

These days, the company need for the introduction of the decision-making system that can be analyzed various types of information. Therefore, the IT-based EIS market is growing significantly every year. For SMEs it is necessary to negotiate a new concept of burden of requirements and the level of investment and advanced similar companies Most of the EIS systems are systems for large enterprises and public institutions, such as banks and SMEs are often used lacking. If you can take advantage of valuable data on the production site and management support system for SMEs it would be beneficial to the business strategy. AllFact is combined with collaboration solutions and applications, which is expected to contribute I be competitive SMEs through improved business processes. We will provide dashboard templates that are used primarily to support the existing domestic and international public institutions and large corporations, financial institutions Dashboard build professional system solutions for small businesses and small business owners was used in the decision-making.

Microsoft, PayPal, and Facebook is a few examples how a micro independent software vendor (Micro-ISV) can be a world class enterprise. The successful examples of many startups on software product encourages a lot of IT entrepreneurship to create a micro-ISV. Creating a micro-ISV is not a big deal on IT entrepreneurship, however to make it grow and survive is something that is not stress-free. Creating micro-ISV is a high risk activity that need a careful survival planning, a vital product planning, even a brilliant marketing plan to make the product is received with limited resources that they have. This paper makes an effort to identify several key patterns that can work as a survival model for micro-ISV to build a product. As a result, this paper proposes seven survival patterns that can be useful for startup to start their journey as a micro-ISV. The survival patterns are composed from six micro-ISV on the developing country that is observed and interviewed by using case study approach.

This plan explores the marketing potential for the use of Big Data along with visual analytics in neonatal intensive care units. The goal of this technology is to provide more efficient and streamlined data collection and display methods for an extremely vulnerable segment of the population. The applicability of this technology is explored through various business models which address the short, medium, and long term marketing goals, such as SWOT, TOWS, and a Strategic Road Map. The results provide strong support for potential market application in Korea as well as abroad.

The number of mobile application development projects appeared to be one of the fastest on the planet that rapidly grows to be highly competitive and the state of this becomes imaginable and unfathomable to deliberate. As smartphones invade everything from business to education to medical to homes, when everything around us revolves in mobile platforms, we tend to ask questions about how is it possible for mobiles to increase popularity and demand for mobile applications? While there are numbers of mobile applications, there are still issues that need to be polished. There is a need of a systematic process of mobile app development that aims to maximize fault detection, making results exceptional to use and may help software developers become reliable to with the approaches and techniques they are using. This study discusses the use of mobile applications and the rapid growth in the mobile app industry. This study presents a mobile development process spiral method. Here, the authors explained the first to fifth iteration. There are many development methodologies that developers can follow, but the authors believe that spiral method is simplified and effective for developing a mobile application. As the mobile application development is changing the way software developers do their best practices for the best mobile apps in keeping their customers engaged in to them and by delivering the best app there is, the most important thing for our software developers is to develop a high quality app that is not only functional but definitely a progressive one.

The Ministry of Education Malaysia (MOE) implemented the National Physical Fitness Standard (SEGAK) for Malaysian School Children Assessment Program. Ever since, the SEGAK assessment data had been collected by the respective teachers in every school twice a year, then its summary is being submitted to the State Department of Education manually through email. This creates problems such as lack of a standardized report format, complex formula in calculating SEGAK score and different data interpretation. In this paper, an integrated and automated SEGAK submission and analysis system is proposed. The system, which is known as Health Monitoring System (HEMS), is a web based system developed with an automated pre-processing method and implemented three tier architecture. HEMS have a centralized database that collects the assessment data from seven districts in Terengganu. A total of 35,681 data was collected from 213 primary schools, and 27,201 data from 44 secondary schools, giving a big total of 67,519 data. During the pre-processing, 4,637 data or 6.9% of the collected data were excluded due to wrong and incomplete information. Using HEMS template, the submitted data have a consistent format of data types. HEMS generates an automated analysis and reporting for the use of related authorities.

Design patterns, a solution for the specific context and the problem, give benefits to us what a good design creates if we adequately use them in accordance with their purposes and principles. However, if we do not use them with inadequate purposes, using design patterns can be causes of increasing costs and decreasing maintainability and system performance. An industrial robot completes its given task through a series of hardware device’s primitive movements, controlled by an application using the APIs provided by specific hardware vendors. However, required movements of a robot change frequently because the given task changes often. This requires changes on hardware devices. As a consequence of this, APIs, controlling the hardware device change, and we also should modify the corresponding application. Therefore, an industrial robot software application should be designed such that it can easily trace hardware device’s change impacts on the application as well as it defines ordered composite primitive movements for completing the required task. This paper implements parts of an application that use hardware dependent APIs by using the command pattern and validates whether it support each change impact analysis.

In Seoul, Korea, air pollution data are available to the public as numeric values on the concentration of pollutants in the air on a webpage. The numeric information is not conducive to determining the air pollution level intuitively. To address this problem, this study developed and implemented a program for visualizing the air pollution level for six pollutants (i.e., sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and two sizes of particulate matter (PM10 and PM2.5)) by obtaining real-time air pollution data using SK Planet Air Quality Request API and generating a keyhole markup language (KML) file defined to visualize the data on Google Earth intuitively. The KML file is linked to Google Earth using the Network Link feature to visualize the air pollution data for Seoul on the three-dimensional (3D) space. The visualized pollution data is expected to promote an intuitive understanding of the data compared to the existing numeric information.

Agile development is truly the need of the hour due to its numerous advantages which are in line with the present business trends. A successful requirement engineering serves as a foundation for success for any software development project. Functional requirements point towards the product services and non-functional requirements are related to the emergent properties of the system. Correct and speedy elicitation of functional and non-functional requirements contribute a great deal towards successful requirement engineering process. Many techniques have been proposed in the past for requirement elicitation for agile development, but they do not take into consideration a holistic automatic approach concerning functional and non-functional requirements. This paper proposes a supervised learning based automated (neural network with the genetic algorithm) approach for successfully classifying functional and non-functional requirements from multiple requirements documents in an agile environment. It is implemented on two data sets and further analysis, and comparison of this model is made with an another implemented model (SVM with RBF kernel) based on precision, recall, and accuracy. This paper contributes in simplifying and automating the requirement engineering process; thus, making the life easier for many stakeholders.

A quick response (QR) code is a two-dimensional barcode in which a lot of information can be recorded. There are many online QR code generators that conveniently make QR codes. Recognition of QR codes with a smartphone is easy and fast. Therefore, QR codes are widely used in various industries, such as manufacturing, logistics, transportation, retail stores, advertising, education, and office automation. This paper proposes the design of a QR code–based client–server tour guide system, which comprises a web server, a streaming server, and an archive system. The client is a smartphone application that recognizes the information in a QR code when the user takes a picture of it. Then, the client accesses the web resource designated by the QR code. A web site can provide a video closely related to the tourist attraction to which the QR code is attached. In addition to playing videos, the web site provides many kinds of useful information to tourists.

Distributed Denial of Service (DDoS) poses the highest rate of vulnerability to cloud computing in terms of availability with ability to destruct the Data-Center (DC) resources. The fortunate part of the attackers is these kinds of attacks are easier to launch the obscure flood towards victim DC and the unfortunate part of detection mechanism is to uncover the attack events and to protect the victim. In order to adapt and automate the detection mechanism in large scale network, agent based detection helps in improving the efficiency of detection. An increase in the network scale will also require the increase in agents deployed in the network to detect the vulnerability DDoS attack threats. This agent based DDoS Mechanism not only protects against huge DDoS flood, but also distinguishes the traffic characteristics by continuous traffic probing to classify the flash crowd traffic event and DDoS attack threat. Jade tool is used to simulate the experiment for our proposed detection scheme.

Most of colleges have made efforts to adapt National Competency Standards (NCS) into their education system by developing and offering courses about NCS vocational competencies such as communication skills. However, instructors are suffering from teaching NCS vocational competencies. In specific, they are having difficulty in assessing students’ achievement due to a lack of objectivity and consistency of existing assessment instruments of NCS vocational competency. In a preceding study, the researchers developed a performance assessment instrument to assess NCS communication skills. The assessment instrument for document comprehension skills and document writing skills were developed for descriptive assessments and essay assessments instrument and the assessment instrument for listening comprehension skills and linguistic expression skills were developed in the form of tester checklists and testee checklists. The purpose of this study is to test the reliability and usability of the developed NCS communication skills performance assessment instrument. In order to test the reliability of NCS communication skill assessment instrument, Cronbach α and the reliability of evaluators were examined. The usability of the performance assessment instrument was tested by three instructors who were teaching communication courses. As the result of analyzing the Cronbach α, coefficient of intraclass correlation, and Cohen’s Kappa value to test the reliability, all assessment instruments showed high reliability. The result of the usability test of assessment instrument by instructors also showed high usability. In particular, we were able to identify improvement points of developed tool through interview with instructors.

The purpose of this study is to examine the influence of SNS information service quality on reuse intention. Reliability and interaction are selected as moderating variables in order to understand more about the influence of the independent variables of the four factors - responsiveness, ease of use, usefulness, and interest - on the dependent variable of reuse intention. The results of analysis of the 331 responses showed that two of the four SNS information service quality factors had a significant impact on the reuse intention of users; ease of use and interest. It was also found that interaction and reliability had a significant moderating effect on the relationship between ease of use and reuse intention

This paper implements artificial neuralnetworkin predictingthe understanding level ofstudent’scourse. By implementing artificial neural network based on backpropagation algorithm, an institution can give a fair decision in prediction level of students' understanding of particular course / subject. This method was chosen because it is able to determine the level of students' understanding of the subject based on input from questionnaires given. The study was conducted into two ways, namely training and testing. Data will be divided into two parts, the first data for the training process and the second reading data of the testing process. The training process aims to identify or search for goals that are expected to use a lot of patterns. Thus, it will be able to produce the best pattern to train the data. After reaching the goal of training which is based on the best pattern, then it will be tested with new data to seeat the accuracy of the target data using Matlab 6.1 software. The results show that it can accelerate the process of prediction of students' understanding. By using architectural models 6-50-1 as the best model, some architectural models are tested and the result of prediction is reach to 87.75%. In other word, this model is good enough to make predictions on the level of students' understanding of the subject.

The purposes of this study are to investigate university students’ emotional responses and the characteristics regarding lecture voice preference. 45 years old female professor’s lecture voice samples were collected with laryngitis and normal condition. 66 female university students who majored in speech language pathology and early childhood education listened the lecture voice samples, and then filled the Adjective Checklist and responded questionnaire items. As a result, the university female students had negative emotions to hoarse lecture voice sample and positive emotions to normal lecture voice sample. And they showed significant higher scores related to unfavorable lecture voice characters after listening to a hoarse lecture voice sample. These results suggested that the importance of professor’s voice quality and necessity of controlling voice problems.