Development of Process for Interoperability Improvement of BIM Data for Free-form Buildings Design using the IFC Standard

Jeongwon Ryu,Jiyong Lee,Jungsik Choi 보안공학연구지원센터(IJSEIA) 2016 International Journal of Software Engineering and Vol.10 No.2

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.

Effect of Smartphone Brand Satisfaction on the Purchase of Other Smart Devices of the Same Brand

Minyoung Noh,Myungsin Chae,Byungtae Lee,Moonsoo Yoon 보안공학연구지원센터(IJSEIA) 2016 International Journal of Software Engineering and Vol.10 No.2

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.

Big and Meta Data Management for U-Agriculture Mobile Services

Chandra Sukanya Nandyala,Haeng-Kon Kim 보안공학연구지원센터(IJSEIA) 2016 International Journal of Software Engineering and Vol.10 No.2

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.

Optical Flow Hand Tracking and Active Contour Hand Shape Features for Continuous Sign Language Recognition with Artificial Neural Networks

P.V.V.Kishore,M.V.D.Prasad 보안공학연구지원센터(IJSEIA) 2016 International Journal of Software Engineering and Vol.10 No.2

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).

Towards Conceptual Predictive Modeling for Big Data Framework

Jeong-Sig Kim,Eung-Sung Kim,Jin-Hong Kim 보안공학연구지원센터(IJSEIA) 2016 International Journal of Software Engineering and Vol.10 No.1

Predictive modeling is the process of creating a statistical model from data with the purpose of predicting future behavior. In recent years, the amount of available data has increased exponentially and “Big Data Analysis” is expected to be at the core of most future innovations. Due to the rapid development in the field of data analysis, there is still a lack of consensus on how one should approach predictive modeling problems in general. Another innovation in the field of predictive modeling is the use of data analysis competitions for model selection. This competitive approach is interesting and seems fruitful, but one could ask if the framework provided by for example Gane Project based on big data framework gives a trustworthy resemblance of real-world predictive modeling problems. In this thesis, we will state and test a set of hypotheses about predicative modeling, both in general and in the scope of data analysis competitions. We will then describe a conceptual big data framework for approaching predictive modeling problems. To test the validity and usefulness of this framework, we will participate in a series of predictive modeling competitions on the platform provided by Gane, and describe our approach to these competitions.

Patent Big Data Analysis by R Data Language for Technology Management

Sunghae Jun 보안공학연구지원센터(IJSEIA) 2016 International Journal of Software Engineering and Vol.10 No.1

Real-time AR Edutainment System Using Sensor Based Motion Recognition

Sungdae Hong,Hyunyi Jung,Sanghyun Seo 보안공학연구지원센터(IJSEIA) 2016 International Journal of Software Engineering and Vol.10 No.1

Recently the Natural User Interface (NUI) technology which is capable of appreciating the whole human body has come to the fore with the development of digital technology. And this new interface has settled as the competitive contents in the growing experiential learning contents market, by arousing participants’ interests and maximizing their learning effect, through a gesture recognition-based noncontact type interactive education. This study suggests various interpretations on the basis of the education contents production which enables participant to experience the human body in real time. Also it has developed a gesture interface by utilizing the Kinect sensor that can recognize a participant’s skeleton and behavior, and its education contents design has produced the end product by using Unity 3D authoring tool which can combine the real-time 3D model and animation together. Consequently, participant will be able to learn various inner organs such as brain and heart by different gestures, and the developed real-time human body exploring augmented reality system is expected to be widely used in many educational institutions

Visible and Infrared Data Fusion

Gwanggil Jeon 보안공학연구지원센터(IJSEIA) 2016 International Journal of Software Engineering and Vol.10 No.2

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.

Dynamic Multi-level Indexes for Cloud P2P OLAP

Nam Hun Park,Kil Hong Joo,Jin Tak Choi 보안공학연구지원센터(IJSEIA) 2016 International Journal of Software Engineering and Vol.10 No.2

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..

Quantitative and Intelligent Risk Models in Risk Management for Constructing Software Development Projects : A Review

Abdelrafe Elzamly,Burairah Hussin 보안공학연구지원센터(IJSEIA) 2016 International Journal of Software Engineering and Vol.10 No.2

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.