• 전자공학회논문지 IE
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• v.47 no.1
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• pp.48-55
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• 2010

The goal of this paper is to determine optimal hardware platform for specific applications. In order to develop an understanding of how select the optimal platform, we focus upon the real-time embedded vehicle system for processing forward image and sound. In this paper we propose to measure parameters such as instructions, execution cycle, required memory size for program and data by using ARMulator. We have measured three types of processor cores: ARM7, ARM9 and ARM10. The results of the study indicated that the proposed methods could measure the minimal requirements of hardware platform for specific applications. By defining lower limit of hardware specifications in embedded systems, we can minimize expenses with suitable system performance without implementing the system.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.119-124
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• 2022

Successful underwater localization requires a large-scale, parallel computing environment that can be mounted on various underwater robots. Accordingly, we propose a design method for an artificial intelligence computing platform for underwater localization. The proposed platform consists of a total of four hardware modules. Transponder and hydrophone modules transmit and receive sound waves, and the FPGA module rapidly pre-processes the transmitted and received sound wave signals in parallel. Jetson module processes artificial intelligence based algorithms. We performed a sound wave transmission/reception experiment for underwater localization according to distance in an actual underwater environment. As a result, the designed platform was verified.

• Journal of Korea Trade
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• v.23 no.7
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• pp.45-63
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• 2019

Purpose - This study aims to examine the factors that affect consumers' intention to use a global business-to-consumer sharing platform. Design/methodology - The questionnaire collected 300 copies from June 25 to July 11, 2019, of which 281 were used for statistical processing. The structural equation model (SEM) was used to test hypothesis in this research. Findings - The results showed that information innovation, personalization, and personal innovation influenced perceived usefulness, and social connectivity did not affect perceived usefulness. And perceived usefulness greatly influenced the intention to use. Research limitations/implications - The limitations of the study are that most of the survey respondents were in their twenties and could not grasp the perception of sharing economy services for various age groups. This paper derived implications that sharing platform promotes sharing and cooperation, which are the basic principles of international trade, to increase the intrinsic value of resources by cyclically using and utilizing limited resources around the world. Originality/value - It aims to contribute to the growth of consumer value-related industries and the welfare of society by providing implications from the point of view of sharing platform services.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1283-1292
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• 2022

At present, several artificial intelligence projects in the healthcare and medical field are competing with each other, and the interfaces between the systems lack unified specifications. Thus, this study presents an artificial intelligence platform for healthcare and medical fields which adopts the deep learning technology to provide algorithms, models and service support for the health and medical enterprise applications. The suggested platform can provide a large number of heterogeneous data processing, intelligent services, model managements, typical application scenarios, and other services for different types of business. In connection with the suggested platform application, we represents a medical service which is corresponding to the trusted and comprehensible tracking and analyzing patient behavior system for Health and Medical treatment using Internet of Behavior concept.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.279-291
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• 2024

The "Korea Institute of Geoscience and Mineral (KIGAM) Quake" is a web-based open platform developed for publicly serving seismological data from 61 stations operated by KIGAM in Korea. The service provides meta-information related to observatory sites, sensors, and recorders necessary for utilizing the seismological data, as well as mainly observed continuous and strong-motion waveforms. The data is available through both the web and International Federation of Digital Seismograph Networks (FDSN) web services (open API), a unified data-providing interface in seismology. The platform aims to strengthen its open nature by offering a signal processing function for strong ground motions that can be controlled by user requests. The processed results can be downloaded in ASCII format, designed to meet the increased demands and accessibility in the earthquake engineering field. The platform also offers earthquake research information produced by KIGAM, such as recent major earthquake source information and academic annual report of earthquakes. Additionally, a site flat file was constructed for the geotechnical characteristics of 61 KIGAM station (KGNET) sites based on direct investigations and estimations.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.477-482
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• 2016

As being the advanced analytics indispensable on big data for agile decision-making and tactical planning in enterprises, distributed processing platforms, such as Hadoop and Spark which distribute and handle the large volume of data on multiple nodes, receive great attention in the field. In Spark platform stack, Spark SQL unveiled recently to make Spark able to support distributed processing framework based on SQL. However, Spark SQL cannot effectively handle advanced analytics that involves machine learning and graph processing in terms of iterative tasks and task allocations. Motivated by these issues, this paper proposes the design of SQL-based big data optimal processing engine and processing framework to support advanced analytics in Spark environments. Big data optimal processing engines copes with complex SQL queries that involves multiple parameters and join, aggregation and sorting operations in distributed/parallel manner and the proposing framework optimizes machine learning process in terms of relational operations.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2095-2107
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• 2000

In maned ship, crews may have risks as they manage damage control system in IPMS in damage situations such as fire in a ship. So the application of unmaned autonomous systms can reduce the number of boarding crews and attribute to safe marine transportation. The paper suggests an intelligent system of the fire fighting control using fuzzy logic in Integrated Platform Management System which can take measures against fire situation of a ship excluding unnecessary warnings with undamaged situations. The system here detected the fire more accurately and adopted more appropriate measures according to ship status compared with conventional systems. Of all, a reduction of false detection of fires was noted.

• Journal of Information Processing Systems
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• v.5 no.4
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• pp.187-196
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• 2009

This paper presents compact cryptographic hardware architecture suitable for the Mobile Trusted Module (MTM) that requires low-area and low-power characteristics. The built-in cryptographic engine in the MTM is one of the most important circuit blocks and contributes to the performance of the whole platform because it is used as the key primitive supporting digital signature, platform integrity and command authentication. Unlike personal computers, mobile platforms have very stringent limitations with respect to available power, physical circuit area, and cost. Therefore special architecture and design methods for a compact cryptographic hardware module are required. The proposed cryptographic hardware has a chip area of 38K gates for RSA and 12.4K gates for unified SHA-1 and SHA-256 respectively on a 0.25um CMOS process. The current consumption of the proposed cryptographic hardware consumes at most 3.96mA for RSA and 2.16mA for SHA computations under the 25MHz.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.1203-1206
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• 2017

인터넷 기술이 발전함에 따라 사물인터넷(Internet of Things, IoT)이 미래의 새로운 성장 동력으로 주목받고 있다. 인터넷에 연결되는 디바이스의 수가 증가됨에 따라 다양한 서비스 제공을 위해 여러 IoT 업체들은 IoT 플랫폼을 연구, 개발 중에 있다. 하지만 이들 플랫폼은 타 플랫폼과 호환이 되지 않아 상호연동에 한계를 가진다. 따라서 본 논문에서는 타 플랫폼과의 상호 연동을 위해 IoT 플랫폼별(oneM2M, AllJoyn, IoTivity) 서비스 계층을 조사하고 해당 계층에서 지원하는 기능들을 분석하여 어떠한 기능들이 상호연동에 필요한지에 대해 연구한다.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.4
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• pp.289-293
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• 2016

As more mobile devices are equipped with multi-core CPUs and are required to execute many compute-intensive multimedia applications, it is important to optimize the systems, considering the underlying parallel hardware architecture. In this paper, we implement and optimize ray-tracing application tailored to a given mobile computing platform with multiple heterogeneous processing elements. In this paper, a lightweight ray-tracing application is specified and implemented in Kahn process network (KPN) model-of-computation, which is known to be suitable for the description of real-time applications. We take an open-source C/C++ implementation of ray-tracing and adapt it to KPN description in the Distributed Application Layer framework. Then, several possible configurations are evaluated in the target mobile computing platform (Exynos 5422), where eight heterogeneous ARM cores are integrated. We derive the optimal degree of parallelism and a suitable distribution of the replicated tasks tailored to the target architecture.