• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.371-377
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• 2013

This paper proposes three methods for improving the accuracy of auto-music transcription considering with time-varying tempo from monophonic sound. The first one that uses TV(Total Variation) filter for smoothing the pitch data reduces the fragmentation in the pitch segmentation result. Also, the measure finding method that combines three different ways based on pitch and energy of sound data, respectively as well as based on rules produces more stable result. In addition the temporal result of note-length encoding is corrected in optimal way that the resulted encoding minimizes the sum of quantization error in a measure while the sum of note-lengths is equal to the number of beats. In the experiment with 16 children songs, we obtained the improved result in which measure finding was complete, the accuracy of encoding for note-length and pitch was about 91.3 and 86.7, respectively.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.9-20
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• 2010

The LIDAR data can be efficiently utilized for automatic reconstruction of 3D models of objects on the terrain and the terrain itself. In this paper, we attempted to generate simulated waveforms of FW (Full-Waveform) LIDAR (LIght Detection And Ranging). We performed the geometric modeling of the sensor and objects, and the radiometric modeling of the waveform intensity. First, we compute the origins and directions of the sub-beams by considering the divergence effects of a laser beam. We then searched for the locations at which the sub-beams intersected with the objects, such as ground, buildings and trees. Finally, we generate the individual waveforms of the reflected sub-beams and the waveform of the entire beam by summing the individual ones. With the experimental results, we confirmed the waveforms were reasonably generated, showing the characteristics of the surfaces the beam interacted with.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.9
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• pp.713-718
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• 2015

The purpose of this study is to realize compressor-performance improvements in the fuel economy of an automotive air-conditioning system. We conduct cooling performance tests in a compressor calorimeter test stand. To improve the cooling performance, we investigate the increase in the suction flow rate and the decrease in the discharge dead volume. Based on the results of the test, we found that the cooling capacity and the coefficient of performance (COP) of the compressors were improved as follows. The cooling performance improved greater at high speeds than low speeds in the case of an increase in the suction flow rate increase, and it improved more at low speeds than at high speed when there was a decrease in the discharge dead volume. When both of the above factors were included, we observed that the improvement effects were generally balanced for both high- and low-speed modes, and there was a significant improvement in the discharge temperature. The improvement was found to be about 3.2% at low speed, 8.3% at high speed during in cooling performance improvement, about 5.8% at low speed and about 6.2% at high speed in COP improvement, and there was a decrease of about $3^{\circ}C$ at low speed and a $5^{\circ}C$ decrease at high speed in discharge temperature.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.17-18
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• 2007

데이터베이스 튜닝은 일반적으로 데이터베이스 어플리케이션을 "좀 더 빠르게" 실행하게 하는 일련의 활동을 뜻한다[1]. 데이터베이스 관리자가 튜닝에 필요한 주먹구구식 룰(Rule of thumb)들을 모두 파악 하고 상황에 맞추어 적용하는 것은 비싼 비용과 오랜 시간을 요구한다. 그렇게 때문에 서로 다른 어플 리케이션들이 맞물려 있는 복잡한 서비스는 필수적으로 자동화된 데이터베이스 성능 관리와 튜닝을 필 요로 한다. 본 논문에서는 이를 해결하기 위하여 지식 도매인(Knowledge Domain)을 기초로 한 자동화 된 데이터베이스 튜닝 원칙(Tuning Principle)을 제시하는 시스템을 제안한다. 각각의 데이터베이스 튜닝 이론들은 지식 도매인의 지식으로 활용되며, 성능에 영향을 미치는 요소들을 개체(Object)와 콘셉트 (Concept)로 구성하고 추론 시스템을 통해 튜닝 원칙을 추론하여 쉽고 빠르게 현재 상황에 맞는 튜닝 방법론을 적용시킬 수 있다. 자동화된 데이터베이스 튜닝에 대해 여러 분야에 걸쳐 학문적인 연구가 이루어지고 있다. 그 예로써 Microsoft의 AutoAdmin Project[2], Oracle의 SQL 튜닝 아키텍처[3], COLT[4], DBA Companion[5], SQUASH[6] 등을 들 수 있다. 이러한 최적화 기법들을 각각의 기능적인 방법론에 따라 다시 분류하면 크게 Design Tuning, Logical Structure Tuning, Sentence Tuning, SQL Tuning, Server Tuning, System/Network Tuning으로 나누어 볼 수 있다. 이 중 SQL Tuning 등은 수치적으로 결정되어 이미 존재하는 정보를 이용하기 때문에 구조화된 모델로 표현하기 쉽고 사용자의 다양한 요구에 의해 변화하는 조건들을 수용하기 쉽기 때문에 이에 중점을 두고 성능 문제를 해결하는 데 초점을 맞추었다. 데이터베이스 시스템의 일련의 처리 과정에 따라 DBMS를 구성하는 개체들과 속성, 그리고 연관 관계들이 모델링된다. 데이터베이스 시스템은 Application / Query / DBMS Level의 3개 레벨에 따라 구조화되며, 본 논문에서는 개체, 속성, 연관 관계 및 데이터베이스 튜닝에 사용되는 Rule of thumb들을 분석하여 튜닝 원칙을 포함한 지식의 형태로 변환하였다. 튜닝 원칙은 데이터베이스 시스템에서 발생하는 문제를 해결할 수 있게 하는 일종의 황금률로써 지식 도매인의 바탕이 되는 사실(Fact)과 룰(Rule) 로써 표현된다. Fact는 모델링된 시스템을 지식 도매인의 하나의 지식 개체로 표현하는 방식이고, Rule 은 Fact에 기반을 두어 튜닝 원칙을 지식의 형태로 표현한 것이다. Rule은 다시 시스템 모델링을 통해 사전에 정의되는 Rule와 튜닝 원칙을 추론하기 위해 사용되는 Rule의 두 가지 타업으로 나뉘며, 대부분의 Rule은 입력되는 값에 따라 다른 솔루션을 취하게 하는 분기의 역할을 수행한다. 사용자는 제한적으로 자동 생성된 Fact와 Rule을 통해 튜닝 원칙을 추론하여 데이터베이스 시스템에 적용할 수 있으며, 요구나 필요에 따라 GUI를 통해 상황에 맞는 Fact와 Rule을 수동으로 추가할 수도 었다. 지식 도매인에서 튜닝 원칙을 추론하기 위해 JAVA 기반의 추론 엔진인 JESS가 사용된다. JESS는 스크립트 언어를 사용하는 전문가 시스템[7]으로 선언적 룰(Declarative Rule)을 이용하여 지식을 표현 하고 추론을 수행하는 추론 엔진의 한 종류이다. JESS의 지식 표현 방식은 튜닝 원칙을 쉽게 표현하고 수용할 수 있는 구조를 가지고 있으며 작은 크기와 빠른 추론 성능을 가지기 때문에 실시간으로 처리 되는 어플리케이션 튜닝에 적합하다. 지식 기반 모률의 가장 큰 역할은 주어진 데이터베이스 시스템의 모델을 통하여 필요한 새로운 지식을 생성하고 저장하는 것이다. 이를 위하여 Fact와 Rule은 지식 표현 의 기본 단위인 트리플(Triple)의 형태로 표현된다, 트리플은 Subject, Property, Object의 3가지 요소로 구성되며, 대부분의 Fact와 Rule들은 트리플의 기본 형태 또는 트리플의 조합으로 이루어진 C Condition과 Action의 두 부분의 결합으로 구성된다. 이와 같이 데이터베이스 시스템 모델의 개체들과 속성, 그리고 연관 관계들을 표현함으로써 지식들이 추론 엔진의 Fact와 Rule로 기능할 수 있다. 본 시스템에서는 이를 구현 및 실험하기 위하여 웹 기반 서버-클라이언트 시스템을 가정하였다. 서버는 Process Controller, Parser, Rule Database, JESS Reasoning Engine으로 구성 되 어 있으며, 클라이 언트는 Rule Manager Interface와 Result Viewer로 구성되어 었다. 실험을 통해 얻어지는 튜닝 원칙 적용 전후의 실행 시간 측정 등 데이터베이스 시스템 성능 척도를 비교함으로써 시스템의 효용을 판단하였으며, 실험 결과 적용 전에 비하여 튜닝 원칙을 적용한 경우 최대 1초 미만의 전처리에 따른 부하 시간 추가와 최소 약 1.5배에서 최대 약 3배까지의 처리 시간 개선을 확인하였다. 본 논문에서 제안하는 시스템은 튜닝 원칙을 자동으로 생성하고 지식 형태로 변형시킴으로써 새로운 튜닝 원칙을 파생하여 제공하고, 성능에 영향을 미치는 요소와 함께 직접 Fact과 Rule을 추가함으로써 커스터마이정된 튜닝을 수행할 수 있게 하는 장점을 가진다. 추후 쿼리 자체의 튜닝 및 인텍스 최적화 등의 프로세스 자동화와 Rule을 효율적으로 정의하고 추가하는 방법 그리고 시스템 모델링을 효과적으로 구성하는 방법에 대한 연구를 통해 본 연구를 더욱 개선시킬 수 있을 것이다.

• Journal of Navigation and Port Research
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• v.31 no.10
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• pp.807-812
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• 2007

With the advent of Electronic Chart Display and Information Systems(ECDIS) and Automatic Identification Systems (AIS) as the principal navigation equipment of E-navigation strategy, mariners will begin to practice "e-navigation" and increasingly rely upon these systems to navigate safely and efficiently. However, these electronic systems require "e-inputs" in order to function. At present, the choices for e-input are limited, and they are installation dependent. This means that the mariner must be suitably equipped in order to use an alternative e-input. If the primary e-input is lost, and the vessel is not equipped to make use of suitable alternative e-inputs, then continued operations will have to be done the "old fashioned way" using conventional navigation The final objective is a recommendation of dual harbor positioning system on the most appropriate mix of positioning systems to satisfy the marine needs for radionavigation, positioning services.

• Journal of Technology Innovation
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• v.26 no.3
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• pp.37-68
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• 2018

Since the 20th century, automobiles, which are the most common means of transportation, have been evolving as the use of electronic control devices and automotive semiconductors increases dramatically. Automotive semiconductors are a key component in automotive electronic control devices and are used to provide stability, efficiency of fuel use, and stability of operation to consumers. For example, automotive semiconductors include engines control, technologies for managing electric motors, transmission control units, hybrid vehicle control, start/stop systems, electronic motor control, automotive radar and LIDAR, smart head lamps, head-up displays, lane keeping systems. As such, semiconductors are being applied to almost all electronic control devices that make up an automobile, and they are creating more effects than simply combining mechanical devices. Since automotive semiconductors have a high data rate basically, a microprocessor unit is being used instead of a micro control unit. For example, semiconductors based on ARM processors are being used in telematics, audio/video multi-medias and navigation. Automotive semiconductors require characteristics such as high reliability, durability and long-term supply, considering the period of use of the automobile for more than 10 years. The reliability of automotive semiconductors is directly linked to the safety of automobiles. The semiconductor industry uses JEDEC and AEC standards to evaluate the reliability of automotive semiconductors. In addition, the life expectancy of the product is estimated at the early stage of development and at the early stage of mass production by using the reliability test method and results that are presented as standard in the automobile industry. However, there are limitations in predicting the failure rate caused by various parameters such as customer's various conditions of use and usage time. To overcome these limitations, much research has been done in academia and industry. Among them, researches using data mining techniques have been carried out in many semiconductor fields, but application and research on automotive semiconductors have not yet been studied. In this regard, this study investigates the relationship between data generated during semiconductor assembly and package test process by using data mining technique, and uses data mining technique suitable for predicting potential failure rate using customer bad data.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3874-3884
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• 2000

An information retrieval system has to retrieve all and only documents which are relevant to a user query, even if index terms and query terms are not matched exactly. However, term mismatches between index terms and qucry terms have been a serious obstacle to the enhancement of retrieval performance. In this paper, we discuss automatic term normalization between words in text corpora and their application to a Korean information retrieval system. We perform two types of term normalizations to alleviate semantic term mismatches: equivalence class and co-occurrence cluster. First, transliterations, spelling errors, and synonyms are normalized into equivalence classes bv using contextual similarity. Second, context-based terms are normalized by using a combination of mutual information and word context to establish word similarities. Next, unsupervised clustering is done by using K-means algorithm and co-occurrence clusters are identified. In this paper, these normalized term products are used in the query expansion to alleviate semantic tem1 mismatches. In other words, we utilize two kinds of tcrm normalizations, equivalence class and co-occurrence cluster, to expand user's queries with new tcrms, in an attempt to make user's queries more comprehensive (adding transliterations) or more specific (adding spc'Cializationsl. For query expansion, we employ two complementary methods: term suggestion and term relevance feedback. The experimental results show that our proposed system can alleviatl' semantic term mismatches and can also provide the appropriate similarity measurements. As a result, we know that our system can improve the rctrieval efficiency of the information retrieval system.

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.223-243
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• 2017

A Hangul input method consists of two core components: key layout for primitive units (Natja), and binding rules to form more complex, composite units from primitive ones. However, careless design and implementation of an input method may result in ambiguity and inability of contiguous typing, when it comes to handle composite Hangul units. This is due to the collective nature of Hangul, namely, existence of implicit boundaries between units and syllables. This issue gets more challenging for the context-dependent 2-beolsik method, mobile environment having significantly fewer keys, and yet addition of the support for Old Hangul. For the sake of the management of complexity, we devised a system in which the binding rule is divided into two layers rather than one. Based on this concept, we implemented a tool program that, given the primitive units and their binding rules, generates input details of every composite unit and detects any potential ambiguity and conflicts. We presented the actual analysis result for Samsung Cheonji-in and KT Naratgeul, two of the most popular mobile Hangul input methods used in Korea.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1495-1501
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• 2006

In this paper, It is purposed to Develope Development of Home Automation Remote Control System using W Color touch LCD(liquid crystal display). This control remotely with remote control innovative and ergonomic design, right combination of LCD and hard buttons and its industry leading technology puts your customers at the cutting-edge of home entertainment. Remote Control for casual users is programmed automatically programmed with multiple free step macros and IR commands. Radio Frequency (RF) operation provides 50-100 inch range though walls and doors. Editor includes a vast library of IR codes for hundreds of brands and models of A/V components. This database is constantly growing with the inclusion of new devices every month. Keep your software up to date by using the Live Update feature. Rather than un-installing and re-installing the software, you download updates to the software from the internet.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.53-63
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• 2004

Recurrent-Cascade-Correlation(RCC) is a supervised teaming algorithm that automatically determines the size and topology of the network. RCC adds new hidden neurons one by one and creates a multi-layer structure in which each hidden layer has only one neuron. By second order RCC, new hidden neurons are added to only one hidden layer. These created neurons are not connected to each other. We present a generalization of the RCC Architecture by combining the standard RCC Architecture and the second order RCC Architecture. Whenever a hidden neuron has to be added, the new RCC teaming algorithm automatically determines whether the network topology grows vertically or horizontally. This new algorithm using sigmoid, tanh and new activation functions was tested with the morse-benchmark-problem. Therefore we recognized that the number of hidden neurons was decreased by the experiments of the RCC network generalization which used the activation functions.