• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.37-47
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• 2018

The number of capabilities of Internet of Things (IoT) devices will exponentially grow over the next years. These devices may generate a vast amount of time-constrained data. In the context of IoT, data management should act as a layer between the objects and devices generating the data and the applications accessing the data for analysis purposes and services. In addition, most of IoT services will be content-centric rather than host centric to increase the data availability and the efficiency of data delivery. IoT will enable all the communication devices to be interconnected and make the data generated by or associated with devices or objects globally accessible. Also, fog computing keeps data and computation close to end users at the edge of network, and thus provides a new breed of applications and services to end users with low latency, high bandwidth, and geographically distributed. In this paper, we propose Edge-Fog cloud-based Hierarchical Data Delivery ($EFcHD^2$) method that effectively and reliably delivers IoT data to associated with IoT applications with ensuring time sensitivity. The proposed $EFcHD^2$ method stands on basis of fully decentralized hybrid of Edge and Fog compute cloud model, Edge-Fog cloud, and uses information-centric networking and bloom filters. In addition, it stores the replica of IoT data or the pre-processed feature data by edge node in the appropriate locations of Edge-Fog cloud considering the characteristic of IoT data: locality, size, time sensitivity and popularity. Then, the performance of $EFcHD^2$ method is evaluated through an analytical model, and is compared to fog server-based and Content-Centric Networking (CCN)-based data delivery methods.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.1-20
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• 2022

As the global business environment is rapidly changing due to the 4th industrial revolution, new jobs that did not exist before are emerging. Among them, the job that companies are most interested in is 'Data Scientist'. As information and communication technologies take up most of our lives, data on not only online activities but also offline activities are stored in computers every hour to generate big data. Companies put a lot of effort into discovering new opportunities from such big data. The new job that emerged along with the efforts of these companies is data scientist. The demand for data scientist, a promising job that leads the big data era, is constantly increasing, but its supply is not still enough. Although data analysis technologies and tools that anyone can easily use are introduced, companies still have great difficulty in finding proper experts. One of the main reasons that makes the data scientist's shortage problem serious is the lack of understanding of the data scientist's job. Therefore, in this study, we explore the job competencies of a data scientist by qualitatively analyzing the actual job posting information of the company. This study finds that data scientists need not only the technical and system skills required of software engineers and system analysts in the past, but also business-related and interpersonal skills required of business consultants and project managers. The results of this study are expected to provide basic guidelines to people who are interested in the data scientist profession and to companies that want to hire data scientists.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2237-2244
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• 2013

In this study, physics based K-DRUM(K-water Distributed RUnoff Model) using GIS spatial hydrologic data as input data was developed to account for the temperature variation according to the altitude change considering snow melt and cover. The model was applied for Pakistan Kunhar River Basin($2,500km^2$) to calculate long-term discharge considering snow melt and cover. Time series analysis of the temperature and rainfall data reveals that temperature and rainfall of the river basin differs significantly according to altitude change compared to domestic basin. Thus, applying temperature and altitude lapse rate during generate input data generation. As a result, calculated discharge shows good agreement with observed ones considering snow melt and accumulation characteristic which has the difference of 4,000 meter elevation above sea level. In addition, the simulated discharge strongly showed snow melting effect associated with temperature rise during the summer season.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.247-256
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• 2008

Recently, natural disasters like flooding damages have frequently occurred as to typhoons and local downpours affected by the climate changes. Many researches have actively been studied in analysing runoff models, the verification of their parameters, and the inflow on surfaces in order to lessen the damages. However, much time and effort needs in generating input files of the models in most current researches. Therefore, in this paper we develop a system for generating a simulation input data automatically. This system is connected to the EPA-SWMM based on the spatial data in the UIS systems and consists the simulation module for analysing urban flooding and the SWMM simulator module. Also, we construct a prototype using a range of regular inundation to generate a simulation input file. This system gives advantages showing inundation areas based on the map viewer as well as lessening errors of input data and simulation time.

• Korean Journal of Computational Design and Engineering
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• v.15 no.3
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• pp.212-221
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• 2010

Proposed in the paper is a methodology to generate kinematic template for 3D JIG models. Recently, according to increase of the rate of automatic facility in manufacturing system, the 3D manufacturing and verification research and development have been issued. So, unlike in the past, moving 3D facilities are very various like JIGs, turn table, AS/RS worked in the automated manufacturing industry. Because 3D mesh models are used in these kinds of 3D simulation, users have to define the kinematic information manually. This 3D mesh data doesn't have parametric information and design history of the 3D model unlike the design level data. So, it is lighter than 3D design level data and more efficient to render on the 3D virtual manufacturing environment. But, when user wants to find a common axis located between the links, the parameter information of the model has to reconstruct for defining kinematic construction. It takes a long time and very repetitive to define an axis and makes a joint using 3D mesh data and it is non-intuitive task for user. This paper proposed template model that provides kinematic information of the JIG. This model is kinds of a state diagram to describe a relation between links. So, this model can be used for a kinematic template to the JIG which has a same mechanism. The template model has to be registered in the template library to use in the future, after user made the model of the specific type of the 3D JIG model.

• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.21-31
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• 2018

We introduces a system that enables fast and effective visualization of natural disaster data such as typhoons, tsunamis, floods, and flooding to help make informed decisions in disaster situations. Data containing disaster information consists of a few hundred megabytes to many tens and hundreds of gigabytes, which can not be handled by a PC. This system was implemented in the form of a client-server based service to generate and output results from high-performance servers. The server in a built-in, high-performance cluster handles client requests and sends the result of visualization to the client. Clients can receive the results in any form of images, videos, or 3D graphic model by specifying a desired time frame, effectively viewing the results with a user-friendly GUI.

• Journal of Korea Spatial Information System Society
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• v.7 no.1 s.13
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• pp.53-62
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• 2005

A challenging task in the LBS system engineering is to implement a highly scalable system architecture which can manage moderate-size configurations handling thousands of moving items as well as upper-end configurations handling distributed computing system architecture that consists of multiple data processors, each dedicated to keeping records relevant to a different geographical zone and a different time zone. In this paper, we explain a prototype location data server structuring major components of GALIS by employing the TMO programming scheme, including the execution engine middleware developed to support real-time distributed object programming and real-time distributed computing system design. We present how to generate realistic location sensing reports and how to process such location reports and location-related queries. Some experimental results showing performance factors regarding distributed query processing are also explained.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.585-588
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• 2003

This study attempts to develop a skeleton model to link construction schedule and 3D object for drawings in 4D system. Generally, the construction schedule and 3D object can be linked in 4D system by imported files which are made in specific S/Ws such as CAD S/W and scheduling S/W. Those methods have a difficulties for operating 4D data because extra work needs to link 4D data for each activity. This study develops a 4D model which the 4D data can be self-generated within the system. The suggested model can reduce the initial input data for new project by integrating schedule and 3D object in 4D system.

• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.468-475
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• 2014

The recommend system is getting more difficult real time recommend by lager preference data set, computing power and recommend algorithm. For this reason, recommend system is proceeding actively one's studies toward distribute processing method of large preference data set. This paper studied distribute processing method of large preference data set using hadoop distribute processing platform and mahout machine learning library. The recommend algorithm is used Co-occurrence Matrix similar to item Collaborative Filtering. The Co-occurrence Matrix can do distribute processing by many node of hadoop cluster, and it needs many computation scale but can reduce computation scale by distribute processing. This paper has simplified distribute processing of co-occurrence matrix by changes over from four stage to three stage. As a result, this paper can reduce mapreduce job and can generate recommend file. And it has a fast processing speed, and reduce map output data.

• Journal of Internet of Things and Convergence
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• v.4 no.2
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• pp.1-6
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• 2018

Techniques for generating new sample data from higher dimensional data such as images have been utilized variously for speech synthesis, image conversion and image restoration. This paper adopts Progressive Growing of Generative Adversarial Networks(PG-GANs) as an implementation model to generate high-resolution images and to enhance variation of the generated images, and applied it to fashion image data. PG-GANs allows the generator and discriminator to progressively learn at the same time, continuously adding new layers from low-resolution images to result high-resolution images. We also proposed a Mini-batch Discrimination method to increase the diversity of generated data, and proposed a Sliced Wasserstein Distance(SWD) evaluation method instead of the existing MS-SSIM to evaluate the GAN model.