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Arduino is a popular open source hardware toolkit for science and engineering education due to its easy use and various good examples. But, students or beginners who have no experience and knowledge of electronic engineering or programming languages still feel a considerable barrier to use Arduino. This study analyzes the barrier of beginners in using the open source hardware. In order to resolve the difficulty in firmware programming, we adopt a functional concise script composed of simplified service commands and minimum options to use the open hardware and proposes a new script-based open source hardware programming environment. From the comparison result with previous development toolkit, we confirm that the programming by the proposed script-based simple programming toolkit is substantially simple by adopting simple script and automatic generations of irrelevant instructions, type declarations and semicolons in programming the open source hardware of Arduino.

Techniques and models for mitigating risk in software development projects classified into three categories–namely, qualitative, quantitative, and intelligent approaches. This paper is to review the quantitative and intelligent risk models in software risk management for software development projects. Indeed, this area needs more effort from scholars and researchers in quantitative and intelligent risk models to mitigate risks. As future work, we will use these hybrid models of quantitative and intelligent for mitigating software risks in cloud computing such as neural network, genetic algorithm and others artificial intelligence techniques.

OLAP query execution costs many minutes by its enormous data and OLAP query properties. On the other hand, MOLAP has fast responses. But it has a physical space limit to materialize all cells in possible combinations. Therefore, MOLAP is unsuited to analyze large data. In this paper, to provide not only flexibility and expandability of ROLAP but also the speediness of MOLAP, the cloud server architecture is proposed which shares clients’ cube cache by P2P and manages central index on cube data on P2P nodes. Also, volatile inquiry-cubes on servers become efficient when it is queried in local memory. The Cloud P2P OLAP is grafted onto hierarchical hybrid P2P for fast query results and multi-dimensional range query, so that the index loads are distributed and the performance is improved..

This paper shows data fusion method with visible light image and infrared image. We assume an image is captured by FLIR image, which provides two images: visible light and infrared images. The details of the image are obtained in visible light image. This information is added to original low resolution infrared image and we assume this image as the detail strengthen infrared image. Experimental results section provides PSNR and MSE results. It is obvious that that proposed method with p=0.03 gives visually satisfactory results.

In the past, some researchers have shown that using more than one technique can reduce the risk of trusting only one method. At present many estimators use function point input in estimations based on COCOMO. This research paper includes the use and explanations related to advantages of these two “public domain” costing methods and the proposal of an integrated single model for size estimation. The problem of language dependency is well addressed and the language-weighted function point is introduced as the solution domain. Research paper demonstrates that the use of backfiring conversion factors is inherently inaccurate as there is no effective relationship between SLOC and FP. The use of homogeneous data can provide the acceptable results as established. It is demonstrated and established that the combination of physical size and functional size using the LOC and function points can affect the productivity. Using weighted function points as the main input in a COCOMO-like power function enables the effect of the programming language which enables the model to be easily adapted to other development environments. Such estimates are of very high degree of accuracy.

ARINC 653 applications using event synchronization may result in behaviors unexpected by the programmers when concurrency errors, such as race conditions, occur due to their non-deterministic executions. The errors can be debugged by means of previous visualization tools, such as System viewer, provided by ARINC 653 IDE. However, these tools do not consider race conditions, which require the programmers to analyze the process state transition considering event synchronization and to ratiocinate the occurrence of accesses to shared resources from source codes. This paper presents a visualization tool, called ConpathView that intuitively shows the aspect of the process execution with race conditions and the accesses to the shared memories based on the event services in ARINC 653 applications. The ConpathView enables to reduce visual complexity as well as to provide effective understanding of the aspect of the process execution. It provides concrete and practical information for debugging ARINC 653 applications by locating the accesses to the shared resources on the source code.

There are many methods that can be used to develop a Geographic Information System (GIS) as a representation of the data visualization on a digital map. One alternative that can be used is by using the Google service pack: Fusion Tables and Maps. This research described the development of a prototype for the visualization of GIS to web-based thematic map that was integrated with Google services. The proposed prototype features the upload and conversion of data from excel file XLS and XLSX format into Fusion Tables and displayed the data in a bar chart to explain the map of the area with different color degradation. This research also indicated that the results of upload process and data conversion can be carried out quicker than XLS excel file format as well as a high success rate of the process of merging two tables in Fusion Tables. This indicated that this concept can be implemented on a real thematic digital map system. Therefore, the proposed prototype in this article can be used to facilitate publication in the form of thematic maps on the data owned by the government or companies with using integrated GIS system efficiently. The final results of this research as shown by thematic map visualization systems were able to facilitate data analysis and assist in making decisions.

This study applied word embedding to feature for named entity recognition (NER) training, and used CRF as a learning algorithm. Named entities are phrases that contain the names of persons, organizations and locations and recognizing these entities in text is one of the important task of information extraction. Word embedding is helpful in many learning algorithms of NLP, indicating that words in a sentence are mapped by a real vector in a low-dimension space. We used GloVe, Word2Vec, and CCA as the embedding methods. The Reuters Corpus Volume 1 was used to create word embedding and the 2003 shared task corpus (English) of CoNLL was used for training and testing. As a result of comparing the performance of multiple techniques for word embedding to NER, it was found that CCA (85.96%) in Test A and Word2Vec (80.72%) in Test B exhibited the best performance. When using the word embedding as a feature of NER, it is possible to obtain better results than baseline that do not use word embedding. Also, to check that the word embedding well performed, we did additional experiment calculating the similarity between words.

This research focuses on the effect of brand perceptions formed through the usage of a smartphone on user satisfaction and on subsequent purchasing decisions for other smart devices of the same brand, using the theoretical background of the Expectation-Confirmation Model in IT. This study showed that the brand expectation confirmation before and after using a smartphone affected brand user experiences (perceived usefulness, perceived playfulness, and perceived aesthetics) significantly. This study is meaningful in that it has defined the perceived playfulness and perceived aesthetics in the existing ECM-IT as ‘user brand experience’ factors, and confirmed the relevant correlations. Also, the confirmation that smartphone usage experience can be fully transferred a user’s intention to purchase other smart devices is what differentiates this study with other studies. The research results show that the user’s playfulness and aesthetics perception formed through smartphone brand usage experience affects both the brand usage satisfaction and the purchase intention of portable and non-portable devices.

In Today’s World, the usage of Web is increased in a very fast manner. The User who is surfing the Web always wants to extract the meaningful information from the resources. As the number of user increased, the Web is diffusing day-by-day. To overcome this, Semantic Web Technologies such as Resource Description Framework along with Document Object Model are used to bring the clear answers to user queries by taking advantage of the availability of precise semantics of information in the context of the search engines. The DOM is a language- and platform-independent API designed for working with HTML/XML data. In this paper, the relevant search is processed by using the DOM Segment fusing function with probability ranking algorithm.

The introduction of BIM into complex buildings is essential and open BIM environment for communication between different kinds of work is an important element with the increasing demand for freeform buildings considering the value as being landmarks. IFC which is a standard integration model in the construction industry has been developed in buildingSMART International aiming for the interoperation of different information model tools. IFC is not only compatible for geometry information but also compatible for property information of the construction, and the standard protocol for data exchange in CAD tool representing BIM has been established for IFC. However, extensive time and costs have been spent since the geometry information is separately established and utilized in the certain software due to poor communication regarding precise geometry information in free-from projects of large scale. Information delivery has been insufficient because of not using BIM authoring tools but CAD-tools. The purpose of this study was to propose the process allowing the conversion of free-from shape into IFC file and the conversion with BIM software by coding the information regarding complex shape of free-from buildings. For this, the improvement in compatibility for geometry information and property information of free-form buildings is expected and improvement in communication and reduction in work duration and costs in different works in each area of the construction industry handling complex shape and property information are ultimately expected.

Coreference resolution is a task of finding all word expressions that refer to the same entity in a text. Anaphors generally refer to the nearest preceding individuals with same attributes. So, position information is one of the important features in coreference resolution. In order to resolve Korean coreferences, multi-stage resolution model is developed by classifying coreference types, and then restricted the context of each processing stage differently according to its characteristics. The experimental results show that the proposed system improved 4.4 percentage point compared with the context-unrestricted system. This means that the context-restricted method plays a positive role in Korean coreference resolution.

To extract hand tracks and hand shape features from continuous sign language videos for gesture classification using backpropagation neural network. Horn Schunck optical flow (HSOF) extracts tracking features and Active Contours (AC) extract shape features. A feature matrix characterizes the signs in continuous sign videos. A neural network object with backpropagation training algorithm classifies the signs into various words sequences in digital format. Digital word sequences are translated into text with matching and the suiting text is voice translated using windows application programmable interface (Win-API). Ten signers, each doing sentences having 30 words long tests the performance of the algorithm by computing word matching score (WMS). The WMS is varying between 88 and 91 percent when executed on different cross platforms on various processors such as Windows8 with Inteli3, Windows8.1 with inteli3 and windows10 with inteli3 running MATLAB13(a).

The purpose of this study was to propose a competency model after exploring the major competencies that must be equipped by students participating in the LINC of K- University and then undergoing expert consultation. The research method relates to categorize the major procedures of competency development according to Lucia and Lepsinger’s (1999) categories and the major procedures and techniques integrated several preceding studies and cases to reconstruct a competency model development procedure. The results showed the four core competencies of the LINC of K-University as ‘intellectual inquiry and self-development’, ‘field experience’, ‘creativity’, and ‘global competitiveness’. The final competencies determined were named as the ‘SMART Core Competency Model’ with the purpose of branding, by connection to the Smart CC of the specialized human resource training program of the LINC at K-University. The results will be used as basic data for the development of an educational platform and the composition of a curriculum based on K-University core competencies.

Recently, there are increasing numbers of sensors that report data from our physical environment. A sensor network consists of a number of spatially distributed and communicating sensor resources. Sensor networks have provided us with facilities to collect information and track certain phenomena in the physical environment based on the region of interest. W3C(World Wide Web Consortium) semantic sensor network group supports to develop an ontology to describe sensors and sensor networks for use in sensor network and sensor web applications. This paper proposes a semantic system architecture based on service provider for data acquisition from heterogeneous sensing sources. And, we design a semantic data model of service provider based on context Ontology. This architecture can help to make a meaning information for deciding an environment situation and assisting efficiently to manage facilities.

Many comparative studies on the performance of machine learning (ML) techniques for web cost estimation (WCE) have been reported in the literature. However, not much attention have been given to understanding the conceptual differences and similarities that exist in the application of these ML techniques for WCE, which could provide credible guide for upcoming practitioners and researchers in predicting the cost of new web projects. This paper presents a comparative analysis of three prominent machine learning techniques – Case-Based Reasoning (CBR), Support Vector Regression (SVR) and Artificial Neural Network (ANN) – in terms of performance, applicability, and their conceptual differences and similarities for WCE by using data obtained from a public dataset (www.tukutuku.com). Results from experiments show that SVR and ANN provides more accurate predictions of effort, although SVR require fewer parameters to generate good predictions than ANN. CBR was not as accurate, but its good explanation attribute gives it a higher descriptive value. The study also outlined specific characteristics of the 3 ML techniques that could foster or inhibit their adoption for WCE.

The Enterprise Management System is the representative system supporting information about important decision making of a company's information system management. SMS (System Management System), which manages the various system status in the information system, uses TCP/IP communication-based SNMP (Simple Network Management Protocol) to collect, process, and save different system information, and provide information for users to make decisions. However, SNMP cannot guarantee the data transmission reliability in regard to system circuit error, delay, and short that may occur during the information collection. Consequently, it involves the issue of inaccuracy of the SMS information. In addition, it is difficult to guarantee the data transmission reliability due to different system problems in the TCP/IP communication. In this study, we applied the SPT (Safe Proper Time) technology to guarantee the reliability of TCP/IP communication, safely linked the intranet system information to the internet network, using the MQSPT-based Open API technology. We designed it to be able to manage the system in the intranet environment efficiently even on the internet network. This study suggests designing and constructing the MQSPT-based Open API SMS architecture.

The motivation of this paper is based on a hypothesis that non-linear decision nodes provide a better classification performance than axis-parallel decision nodes do in many practical problems, such as image classification, and voice classification. The algorithm – MNCS_DT is introduced in this paper to create non-linear splits nodes by novel discriminant analysis in decision tree for multi-classification problem and take cost-sensitive problem into account when the features are selected. In experiment part, we use four UCI data sets to compare the performance of MNCS_DT and C4.5 CS by costs and error rates. The performance of MNCS_DT is better than C4.5 CS. And eight data sets from UCI are used to compare the performance of three different feature sets measured by accuracy, G-mean, and operation time. The performance of feature set consisting of features that follow multivariate normal distribution and altered information gain values higher than average one is better than two other feature sets in most data sets.

This study aims to investigate the relationship between outcome control and project performance and also examine the factors affecting the outcome control exercised in the offshore information system development projects. To achieve these objectives, field survey was conducted, and 144 survey questionnaires were used for analysis. Research results show that there is positive relationship between outcome control and project performance, and some factors affecting the outcome control such as role clarity, goal alignment and benefit and risk share are verified. Research implications are discussed.

Geotweets are tweets containing latitude and longitude coordinates, and studies on geotweets have employed a wide range of methodologies, such as content analysis, sen sentiment analysis as well as geovisualizing and statistical analysis. However, there have been limitations in applying such analytical methodologies with a comprehensive approach due to researchers’ different academic backgrounds and various environments under which systems are implemented. To overcome these problems, this study proposes a Python-based method for compiling, storing, analyzing, and visualizing geotweet data. In this study, the proposed system architecture is applied in a case study for analyzing Seoul’s geotweet data.

Big Data is a huge amount of data generated continuously and it extracts the meaning, structure, and relationships in enormously large data sets. Metadata is defined as data about data, where is comes from, and when it was taken etc. Metadata is a supplementary data and is generally related with a certain piece of data (big data) that is more important. Metadata helps in making value added decisions and information about own data travelling for big data. This paper communicates about big data, metadata and their management associated to u-agriculture mobile services and lime lights more on sensors that are integrated and built-in. B&M (Big and Meta) data management is very challenging and is strong topic for research currently. Firstly, this paper reviews B&M data and their management. Also presents relationship between big data and Metadata and challenges. And also types of sensors, techniques, technologies, applications, and advantages of various types of sensors for u-agriculture mobile services in their decision making. Finally presents architecture for U-Agriculture Mobile Services based on Sensor-Cloud Infrastructure which helps not only farms and also applications, services provides and organisations in management of B&M data.

Big data is an emerging and very considerable technology for gathering and analyzing a huge volume of real-time produced data efficiently and effectively, but it has also a great volume of sensitive data arising invasion of privacy. Big data analyses can give us very customized and effective analysis results, but this technology can be abused for privacy invasion of personal users. This paper introduces sensitive information which can be collected and/or synthesized at the data collection stage, data analysis stage, and presentation service stage. And then this paper proposes a double layered architecture for preserving user privacy. The proposed architecture provides two steps for masking sensitive information from the big data processing databases, and these steps are presented in detail with some examples in this paper.

This study is about the application of global citizenship education for young children into the Nuri curriculum through virtual intercultural exchange by the action research method for 1 year. For the research, qualitative methods were used. According to the research results, the global citizenship education for young children into the Nuri curriculum could develop the ways on creative integration of activities by yearly life themes. Teaching and learning methods, teacher education and the strategies for integration were to be careful about relationship building via help from virtual intercultural exchange. To integrate global citizenship education with the yearly curriculum, the use of different approaches to the content areas should be considered. The findings of the study showed that the effects of global citizenship education for young children were the building a world view focusing on mutual respect, reconceptualization of friend, improved social perspective-taking skills and growing concern for multicultural languages. Moreover, there was more positive collaboration between the kindergarten and the families.

With the help of highly advanced information and communication technology (ICT), various learning tools and contents have been developed for learning. Smart learning has been promoted in all of the educational areas; it has been raised the possibility of creativity in learning. This work tried to investigate how pre-service teachers were utilizing their smart learning tools and how they were thinking of their smart learning experience in their classes. In that regard, data was collected from various ways such as surveys, interviews, and brief writings of the participants. For this study, both qualitative and quantitative methods were utilized. According to the research result, pre-service teachers frequently used smart devices, but the type of using smart devices was broadly ‘limited using’. It means that pre-service teachers do not possess qualitatively meaningful digital literacy of pre-service teachers to poster their smart learning. However, the experience of integrating smart devices into their learning process can help pre-service teachers to be aware of the implication of creative teaching and learning.