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Software industry is increasingly using Agile Methods due to its benefits. However the way industry practices agile methods is some time divergent to the basic Agile Principles. For example customer involvement in the entire software development process is considered essential; but under certain conditions this requirement is not so critical. We have studied in detail such an adaptation by a large software company using Agile Method i.e. SCRUM. The organization develops software products using SCRUM; however, after initial development; they customize the product for their potential customer. At no time (during initial development or customization stage), real customer is present at the development site; but still their products are immensely successful in terms of number of products sold, and customer satisfaction. In the real world case study we have analyzed reasons for the success of the organization and have studied in detail the circumstances which obviate the need of readily available customer. The results show that, extensive domain knowledge, prior experience of the product and experienced workforce mitigate the need of onsite customer.

The currently available approaches for processing natural language (NL) software requirements specifications are semi-automatic and require user intervention. Moreover, these approaches result in less accurate and imprecise object oriented software models. Recent research in the area attributes the informal nature of natural languages for less accurate analysis of software requirements. On the basis of this axiom, we have identified that direct translation of a natural language to a formal language is the actual problem. In this paper, we propose that instead of direct translation of a natural language to a formal language, first, we will transform the natural language text to a semi-formal language that is not only simple and easy to translate to a formal language but also provides with higher accuracy. We have incorporated Structured Business Vocabulary and Rules (SBVR) language as the semi-formal medium in natural language to object-oriented models. The presented approach automatically generates the object-oriented software models from natural language software specifications using SBVR as a pivot representation.

Measurement is a key issue in evaluation process. In this paper, we emphasized mainly three problems of the current evaluation approaches in the field of Adaptive Learning System (ALS): i) limits of adaptation specific measures, ii) a lack of consideration of business perspective, and iii) evaluation of the adaptation strategies effectiveness. In order to answer the already quoted points, we propose a specific adaptation measurement framework which integrates multiple perspectives of the problem.

Accurate estimation of software development effort needs to consider numerous factors in software projects such as project size, programming language, application type, team size, development platform and so on. Software methodology is one of the most effective parameters in this field. Basically, software methodologies are used in software projects in order to manage activities, artifacts, roles and disciplines. Researchers believe that methodologies can make project managers enable to deal with uncertain and complex nature of software projects. In spite of having noticeably advantages, using the methodologies may lead to inaccurate development effort estimation because there is no analytical evidence to clarify the real effect of using methodology on development effort. Underestimating the amount of effort required for utilizing methodology can have negative influences throughout the project. In this paper, an analysis was performed to draw the real situation of software projects in term of using methodologies. Furthermore, the effect of using methodologies on development effort was investigated to show how methodologies can affect the software development effort. A real and large dataset including 5052 software projects from various areas was used in this study. The results showed high interest to employ methodologies in recent software projects as well as high and significant impact of methodologies on development effort.

In this paper, we present Compute Unified Device Architecture i.e. CUDA based pyramidal image blending algorithm using an object oriented design patterns. This algorithm is an essential part of an image stitching process for a seamless panoramic mosaic. The CUDA framework is a novel GPU programming framework from NVIDIA. We introduce an object oriented framework for the CUDA based image processing. We illustrate a set of design patterns exploiting programming advantages of an object oriented language; such as encapsulation, code reusability, information hiding, complexity hiding and extensibility. We discuss the framework’s performance in terms of programming efforts, execution overhead and speedup factor achieved over the CPU one. We also talk about programming efforts required for adding the OpenGL Shading Language functionality to the framework.

The study of the correlation between software project and product attributes and its modules quality status (faulty or not) is the subject of several research papers in the software testing and maintenance fields. In this paper, a tool is built to change the values of software data sets’ attributes and study the impact of this change on the modules’ defect status. The goal is to find those specific attributes that highly correlate with the module defect attribute. An algorithm is developed to automatically predict the module defect status based on the values of the module attributes and based on their change from reference or initial values. For each attribute of those software projects, results can show when such attribute can be, if any, a major player in deciding the defect status of the project or a specific module. Results showed consistent, and in some cases better, results in comparison with most surveyed defect prediction algorithms. Results showed also that this can be a very powerful method to understand each attribute individual impact, if any, to the module quality status and how it can be improved.

Writing parallel programs is not a simple task. Especially, writing parallel programs for a heterogeneous computing environment is even more difficult. Programs written in different programming languages are required to run on different platforms with different operating systems. In this paper, a parallel processing model is presented to allow programmers to write the programs for parallelism in a heterogeneous computing environment. The programs can be written in a sequential programming language that the programmers are familiar with and feel comfortable to write. The model facilitates implicit parallelism and the implementation of the parallelism will be automatically realized in the model. The details of parallelism are hidden from the programmers, thus the programmers can focus on the details of business logics. The programmers are also able to run the programs for simulation.

Indexing allows converting raw document collection into easily searchable representation. Bigger scale indexing poses some challenges such as how to distribute indexing computation efficiently on a cluster of nodes. MapReduce framework can be an effective tool for parallelizing such tasks as inverted index construction. We propose SciPDFindexer, distributed information retrieval system for scientific articles in PDF. For given large collection of scientific articles in PDF our system parses and extracts metadata from articles, and then indexes extracted content using our proposed scheme. Our contribution is the design of distributed IR system and indexing scheme that improve the overall indexing performance.

Actually, large database is not simply considered as a stream database because of streaming data is not only containing huge data volumes, but distributed, continuous, rapid, time varying. Therefore, the general techniques may not suit for streams exactly. Accuracy responses required of approximated answers is more important in stream processing for the similarity search. Therefore, we perform data reduction across synopsis data structure and to batch processing in a particular relevance way on the data stream computation model over sliding windows. Focus on similarity search in streaming environment, D-skyline method proposed in this paper concern useful aggregate as a preprocessing phase instead of original dataset repeatedly processing manner, in order to efficiently optimize both in space usage and error control. Our experimental evaluation would show the detailed effect on approximated analysis by using different kinds of skyline methods, then effectiveness and efficiency of our approach.

We propose BLFS (Block Link File System) supporting fast editing/writing for large-sized multimedia files. In the BLFS, when large-scale multimedia files are stored and edited, there is no data I/O but only modification of the metadata. Additionally, by sharing data blocks between multimedia files, we can save disk space. The BLFS was implemented in a Linux environment by modifying Ext3, and validated by applying the Linux multimedia file-editing tool ‘Avidemux’.

CMIS is a standard to support interoperability among content management systems, proposing a data model to represent process and manage resources. However, since CMIS does not provide the operations for group works and the related access control functionality, there are essential difficulties in supporting various group works other than simple sharing or management of resources. In this paper, we present a middleware named C2ware that provides collaborative services in a form of web service, supporting collaborative workspaces over CMIS repositories. For this, we provide a formal specification of general services required for group works. Based on the specification, the middleware creates workspaces over CMIS repository to support various types of asynchronous resource sharing, and provides collaborative services on the workspaces. In addition, to evaluate the effectiveness of C2ware, we develop a smartphone application which works together with the middleware, conducting an experiment with the application in various group works.

This paper proposes a virtual driving system for enhancing efficient driving style. We compared fuel economies and levels of consumable wear on three driving simulation test (none, visual, visual+auditory). The test results show that higher fuel economy can be achieved and consumable wear be reduced when they received feedback from the proposed system compared to driving without eco-driving training.

On the USN environment in industry safety, many problems came up during the operation such as data management in various sensor nodes, efficient process of context data, and absence of context cognition technology. In this paper, we suggest INSACO(Industrial SAfety Control) system to support a integrated sensor data management system based on sensor stream data process. Also, I suggest context cognition system providing context awareness using sensor data and the simplified circumstance information model. When it comes to realization and performance evaluation of this study, intelligent control system providing user interface that integrates data and video has established. fully-justified italicized text as it is here, below the author information.

Studies for indoor positioning system based on the FingerPrint method are increasing its importance. Improving the accuracy of FingerPrint DB using Wi-Fi AP(Access Point) can give great effects on positioning. In this paper, we analyze active Wi-Fi signal phenomena from reference AP which is accessed by multi-users. Some factors which can affect the accuracy of position are studied by comparing signal patterns in the DB and real-time active signals. We propose a modified FingerPrint DB method on both AP connection and AP disconnection which can improve performance accuracy of the positioning.

Computational eciency is an important theme in uid simulation since its heavy com- putational load is burden to designers. Our objective is to proposed a grid based method satisfying divergence free property without the projection method. The paper transforms the momentum conservation part of the Navier-Stokes equations to vector potential based equations. Our method do not need any global operations for mass conservation. The trans- formed equation is solved numerically in similar manner to fractional step method.

Technology can be defined diversely according to the ways of its usage. In this paper, we define technology as a tool making new product and service using the developed results of science and engineering for improving the quality of human life. Technology management (TM) is important factor in the business planning of a company. Many companies have performed TM for developing new products and protecting their intellectual properties (IP). Patent is a typical IP, so we propose a TM approach using new patent analysis method. In this paper, we combine time series regression and clustering techniques. To assess the performance of our research, we will make experiment using the biotechnology patent data from the United State Patent and Trademark Office.

This paper describes a framework for steel surface defects detection and classification. We use SIFT for defects regions detection and features extraction for the following SVM classification. This approach can generate many feature points for training the classifier from a few images. We also propose a voting strategy for the final decision that handles the problem of multiple outputs of a given input image with a specific defect type. In addition, this approach improves the classification performance. Experimental results demonstrate the effectiveness of the proposed method on steel surface defects detection and classification.

In this paper, we attempt to simultaneously mix the user experience with the system development lifecycle to show the effectiveness of the application from usability perspectives and user experience, we build an application using three different development environments, namely, IBM DB2, Visual Basic, and MS Excel. The study reveals that spontaneous mixture of user experience and system development life cycle models could significantly provide high acceptance of products from different users. Despite the fancy user interface, the analysis indicates that the mixture should be a norm for developing applications. Study also demonstrates the effectiveness of the mixture by ensuring good quality outcomes. In addition, we evaluate the interface and functionalities of the application from the usability standpoint and user’s perspectives.

This paper is focused on the measure for the reliability of clinical performance ability using computer-based examination. The subjects consisted of 84 doctors working in a medical institute located in Metropolitan area from November 21 to December 21, 2011. The reliability of this paper in skill was good with a Cronbach’s alpha of 0.88. Clinical courtesy was significantly higher in interns than in residents and physicians(p=.02). In conclusion, this paper revealed that reliability was appropriate as evaluation method for the reliable performance ability using computer-based examination.

Public repositories for microarray data have been constructed by some researches which follow the standards such as MIAME-compliant data and MAGE-OM/ML. However, enough consideration has not been taken into the design of storage structure for the hierarchy of microarray data. In this paper, we propose alternative mapping strategy to mine the structural similarity and an advanced mapping rule from the algorithm. Object-relational mapping technique is used for extracting advanced storage design schema for microarray data and structural similarity of elements is evaluated for efficient storage construction. The mapping strategy reduced the number of relational tables remarkably.

Cloud computing and IPv6 are among two of the most prominent trends impacting the IT industry. In order to fully use heterogeneous network resources, there is a need to design a network where all resources can interconnect in cloud computing deployment. At present, IPv4 networks are still dominant and IPv6 is the next internet protocol that is being adopted. In cloud computing deployment, IPv6 is the solution for mobility and is seen to have a good impact in cloud computing network deployment. Due to the difficulty associated with upgrading the entire Internet backbone to support IPv6 it is easy to upgrade routers in the access network and allow for the greater benefits of IPv6 than to upgrade all routers in the Internet backbone network. To integrate both IPv4 and IPv6 interoperability for cloud computing there is a need of Translation Protocol and Tunneling mechanisms. In this paper, we proposed an IPv4 and IPv6 interoperability framework for cloud computing deployment.

The cluster web server does not only allow clients to access a site that will provide better response time but also provides an another level of redundancy in the case of the whole site failure. In advance of a simple load balancing, this requires a comprehensive scheme for traffic management, which includes the principle of an optimal load balancing for the process of client requests across multiple clusters of the real servers. This paper presents an optimal load balancing algorithm base on ANFIS (Adaptive Neuro-Fuzzy Inference System) modeling and FIS (Fuzzy Inference Engine) for the local status of the real servers using the performance metrics, and show the benefits provided by the suggested method in the load-balancing performance.

The scheme for the full-text search has drawn much attention due to its popular use in web document searches and enterprises’ document searches. The full-text search leads to a large size of index files and thus may consume massive computing resources for its processing. In this paper, we present both the system architecture of a full-text search engines with a huge volume of indexed data and its multi-level cache scheme. The presented system architecture and cache scheme were implemented in a commercial search engine, which has capacity enough to process more than 5-milion queries per day and index about 70-milion web documents crawled in Korea. In economic respect, the proposed cache scheme is very crucial for our full-text search engine.