• MALSORI
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• no.51
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• pp.151-165
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• 2004

For educational and research purposes, a Korean speech recognition platform is designed. It is based on an object-oriented architecture and can be easily modified so that researchers can readily evaluate the performance of a recognition algorithm of interest. This platform will save development time for many who are interested in speech recognition. The platform includes the following modules: Noise reduction, end-point detection, met-frequency cepstral coefficient (MFCC) and perceptually linear prediction (PLP)-based feature extraction, hidden Markov model (HMM)-based acoustic modeling, n-gram language modeling, n-best search, and Korean language processing. The decoder of the platform can handle both lexical search trees for large vocabulary speech recognition and finite-state networks for small-to-medium vocabulary speech recognition. It performs word-dependent n-best search algorithm with a bigram language model in the first forward search stage and then extracts a word lattice and restores each lattice path with a trigram language model in the second stage.

• International Journal of Safety
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• v.4 no.2
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• pp.36-42
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• 2005

A study on fire phenomena in a subway transit mass station has been carried out as a part of disaster prevention plan at the subway station. The ventilation facilities installed in both the platform and the trackway are designed to convert into a smoke exhaust system in emergency situation, creating an environment necessary for evacuation. 3 dimensional Numerical Simulations based on the CFD are carried out using a simulation tool, Fire Dynamic Simulator. Total of six different cases are made and performances are compared each other to find optimal vents operation to ensure safer environment for evacuation at the platform area considering the installation of platform screen door.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1243-1248
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• 2022

A mobile platform that can robustly operate in unstructured environments such as construction sites is an essential problem for smart construction technology development. In this paper, we introduce a mobile robot platform that can be applied to the unstructured environment to support the collection of geographical information at construction sites. The proposed mobile platform is designed to cope with not only vertical slopes but also side slopes, and the performance of overcoming the step difference of the proposed platform was analyzed through simulation experiments.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.147-158
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• 2021

The digital transformation and COVID-19 are also causing major changes in teaching-learning methods. The biggest change is the spread of remote training and the emergence of various innovative learning platforms. Distance education has been criticized for not meeting technology trends and field demands..However, the problem of distance education is being solved through a system that supports various interactions and collaborations and supports customized learning paths. The researcher conducted a case study on domestic and foreign learning platforms that provide non-face-to-face ICT education. Based on the case study results, the researcher presented the functional characteristics of a learning platform that effectively supports non-face-to-face learning. In common, these sites faithfully supported the basic functions of the information system. In addition to learning progress check and learning guidance, some innovative learning platforms were providing differentiated functions in practice support, performance management, mentoring, learning data analysis, curation provision, and CDP support. Most learning platforms supported one-way, superficial interaction. If the platform effectively supports a variety of learning experiences and provides an integrated learning experience thanks to the development of IT technology, user satisfaction with the learning platform, intention to continue learning, and achievement will increase.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.73-84
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• 2019

Machine learning as a service, the so-called MLaaS, has recently attracted much attention in almost all industries and research groups. The main reason for this is that you do not need network servers, storage, or even data scientists, except for the data itself, to build a productive service model. However, machine learning is often very difficult for most developers, especially in traditional science due to the lack of well-structured big data for scientific data. For experiment or application researchers, the results of an experiment are rarely shared with other researchers, so creating big data in specific research areas is also a big challenge. In this paper, we introduce the KISTI-ML platform, a community-based rapid AI model development for scientific data. It is a place where machine learning beginners use their own data to automatically generate code by providing a user-friendly online development environment. Users can share datasets and their Jupyter interactive notebooks among authorized community members, including know-how such as data preprocessing to extract features, hidden network design, and other engineering techniques.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.932-935
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• 2004

In this paper, we present a framework that is easy to develop, modify, maintain and extend a control and monitoring software for any kinds of instruments. The presented framework is composed of three XML documents (IID, MAP, and CMIML) and two tools (Virtual Instrument Wizard, Generator). Interface information about behaviors and states of instruments is written on IID. Mapping information between the interface information in IID and API of a real instrument driver is written on MAP. Finally information about control and monitoring software is written on CMIML. IID, MAP and CMIML are written with XML format to provide common usage and platform independence of the suggested framework. VI Wizard generates CMIML (platform independent intermediate document) using IID and existing CMIML, and Generator generates source code of a control and monitoring software (platform dependent code) automatically using CMIML and MAP. The suggested framework that automatically generates control and monitoring software based on GUI provides easy development and maintenance. Also, reusability can be increased by reusing platform independent software description documents.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1516-1529
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• 2016

While global manufacturing is becoming more competitive due to variety of customer demand, increase in production cost and uncertainty in resource availability, the future ability of manufacturing industries depends upon the implementation of Smart Factory. With the convergence of new information and communication technology, Smart Factory enables manufacturers to respond quickly to customer demand and minimize resource usage while maximizing productivity performance. This paper presents the development of a big data analytics platform architecture for Smart Factory. As this platform represents a conceptual software structure needed to implement data-driven decision-making mechanism in shop floors, it enables the creation and use of diagnosis, prediction and optimization models through the use of data analytics and big data. The completion of implementing the platform will help manufacturers: 1) acquire an advanced technology towards manufacturing intelligence, 2) implement a cost-effective analytics environment through the use of standardized data interfaces and open-source solutions, 3) obtain a technical reference for time-efficiently implementing an analytics modeling environment, and 4) eventually improve productivity performance in manufacturing systems. This paper also presents a technical architecture for big data infrastructure, which we are implementing, and a case study to demonstrate energy-predictive analytics in a machine tool system.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.2
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• pp.123-128
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• 2022

This paper proposes a mobile robot platform for education that can experiment with various autonomous driving algorithms such as obstacle avoidance and path planning. The platform consists of a robot module and a remote controller module, both of which are based on the Arduino Nano 33 IoT embedded board. The robot module is designed as a differential drive type using two encoder motors, and the speed of the motor is controlled using PID control. In the case of the remote controller module, a command to control the robot platform is received with a 2-axis joystick input, and an elliptical grid mapping technique is used to convert the joystick input into a linear and angular velocity command of the robot. WiFi and Zigbee are used for communication between the robot module and the remote controller module. The proposed robot platform was tested by measuring and comparing the linear velocity and angular velocity of the actual robot according to the linear velocity and angular velocity commands of the robot generated by the input of the joystick.

• The Journal of Information Systems
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• v.31 no.3
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• pp.131-152
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• 2022

Purpose The purpose of this study was to investigate the intention of using a news media platform using block chain through media company workers in a situation where various platform services using block chain are being newly released in the media industry. Therefore, in this paper, we intend to explore the development direction of the news media platform service using the block chain in the future by deriving implications through the characteristics of the block chain, user characteristics, and self-determination factors. Design/methodology/approach This study conducted a survey on the main characteristics of blockchain, user characteristics, self-determination, resistance to innovation, etc., and designed a research model by integrating factors on the continuity of intention to use the news media platform. Findings According to the empirical analysis result, in this study, it was confirmed that the intention to use the blockchain news media platform is significantly related to decentralization, which is a characteristic variable of the blockchain, perceived risk, which is a user characteristic variable, and competence and relationship, which is a self-determination variable. In addition, it was confirmed that it affects the perceived ease of use with respect to the intention to use. In addition, in this study, news writers write more careful articles as they cannot edit articles once written, which can contribute to improving the quality of news content.

• Proceedings of the Polymer Society of Korea Conference
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• 2006.10a
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• pp.152-152
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• 2006

Polyolefins show a very healthy growth rate among commodity polymer resins due to their low feedstock prices, recyclable and environmentally friendly characteristics and easily controllable performances. Capacity investment in polyolefin field is now moving from technology region to consumer region and feedstock region. Therefore, key success factors for polyolefin business in the other region such as Korea are cost reduction, development of highly value-added products and new applications and substitution of PVC, PS, PET and other EPs. To add additional value to commodity polyolefin products, high level of platform technology such as catalyst, process and structure-properties relationship is needed. Progress on polyolefin products has been very closely related to catalyst and process technology. According to this trend, SK Corporation has devoted a lot of research effort into development of new value-added polyolefin products based on the proprietary technology platform.