• 제어로봇시스템학회논문지
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• 제14권1호
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• pp.27-35
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• 2008

A navigation system is one of the important components of an unmanned ground vehicle (UGV). A GPS receiver collects data signals transmitted by (Earth orbiting) satellites. However, these data signals may contain many errors resulting misinformation and depending on one's position (environment), reception may be impossible. The proposed self-driven algorithm uses three low-cost GPS in order to minimize errors of existing inexpensive single GPS's driving algorithm. By using reliable final data, which is analyzed and combined from each of three GPS's received data signals, gathering a vehicle's steering performance information and its current pin-point position is improved even with error containing signals or from a place where signal gathering is impossible. The purpose of this thesis is to explain navigation system algorithm using multiple GPS and compass sensor and prove the algorithm through experiments.

• 식품보건융합연구
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• 제9권4호
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• pp.19-23
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• 2023

The integration of ChatGPT, an AI-powered language model, is causing a profound transformation within the food industry, impacting various domains. It offers novel capabilities in recipe creation, personalized dining, menu development, food safety, customer service, and culinary education. ChatGPT's vast culinary dataset analysis aids chefs in pushing flavor boundaries through innovative ingredient combinations. Its personalization potential caters to dietary preferences and cultural nuances, democratizing culinary knowledge. It functions as a virtual mentor, empowering enthusiasts to experiment creatively. For personalized dining, ChatGPT's language understanding enables customer interaction, dish recommendations based on preferences. In menu development, data-driven insights identify culinary trends, guiding chefs in crafting menus aligned with evolving tastes. It suggests inventive ingredient pairings, fostering innovation and inclusivity. AI-driven data analysis contributes to quality control, ensuring consistent taste and texture. Food writing and marketing benefit from ChatGPT's content generation, adapting to diverse strategies and consumer preferences. AI-powered chatbots revolutionize customer service, improving ordering experiences, and post-purchase engagement. In culinary education, ChatGPT acts as a virtual mentor, guiding learners through techniques and history. In food safety, data analysis prevents contamination and ensures compliance. Overall, ChatGPT reshapes the industry by uniting AI's analytics with culinary expertise, enhancing innovation, inclusivity, and efficiency in gastronomy.

• 한국자동차공학회논문집
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• 제18권5호
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• pp.108-114
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• 2010

The injection nozzle of an electro-hydraulic injector is being opened and closed by movement of a injector's needle which is balanced by pressure at the nozzle seat and at the needle control chamber, at the opposite end of the needle. In this study, the effects of needle movement in a piezo-driven injector on unsteady cavitating flows behavior inside nozzle were investigated by cavitation numerical model based on the Eulerian-Lagrangian approach. Aimed at simulating the 3-D two-phase flow behavior, the three dimensional geometry model along the central cross-section regarding of one injection hole with real design data of a piezo-driven diesel injector has been used to simulate the cavitating flows for injection time by at fully transient simulation with cavitation model. The cavitation model incorporates many of the fundamental physical processes assumed to take place in cavitating flows. The simulations performed were both fully transient and 'pseudo' steady state, even if under steady state boundary conditions. As this research results, we found that it could analyze the effect the pressure drop to the sudden acceleration of fuel, which is due to the fastest response of needle, on the degree of cavitation existed in piezo-driven injector nozzle.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1692-1695
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• 1997

In this paper, a new control scheme for master-slave control of telerobot is proposed. The porposed method can be classified into unilater master-slave control methods in the aspect of the data flow. But the master arm in the proposed control scheme can deliver operator the similar kinesthetic sense as other bilateral force reflecting master arms do. The principle concept is that the sensed operator's force/torque is used as the reference input for a damping controller type of telerobot controller which track the operators efforts. Master arm and master controller can be implemented in a simple form, and it needs not be driven by actuators, but force sensing capability.

• 한국멀티미디어학회논문지
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• 제8권2호
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• pp.201-210
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• 2005

본 논문에서는 입력 데이터 특성을 반영하여 전력 효율이 좋은 2차원 DCT/IDCT 구조를 제안한다. 일반적으로 비디오와 영상 데이터 압축에 있어서 제로 또는 작은 값들이 입력 데이터의 많은 부분을 차지하므로 제안 방식에서는 이러한 특성을 이용하여 소모 전력을 줄인다. 특히, 간단한 AND와 비트-슬라이스 매스크(MASK)를 사용하여 곱셈기와 누산기 (accumulator) 내에서 제로를 곱하는 것을 생략하고 요구되는 세분화된 가산기들의 비트-슬라이스를 동적으로 활성화 또는 비 활성화한다. 제안 방식을 1-D DCT/IDCT에 적용하여 얻은 결과에서는 매트릭스 전치에서 전력 절감을 위해 이용되는 불필요한 부호확장비트(SEBs)를 갖고 있지 않음을 보여주고 있다. 비트 레벨 트랜지션 빈도 시뮬레이션(bit-level transition activity simulations)을 통해 기존의 설계에 비해 뚜렷한 전력 절감 효과를 확인하였다.

• Journal of Computational Design and Engineering
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• 제1권4호
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• pp.233-242
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• 2014

A magnetically levitated vehicle (Maglev) system is under commercialization as a new transportation system in Korea. The Maglev is operated by an unmanned automatic control system. Therefore, the plan of train operation should be carefully established and validated in advance. In general, when making a train operation plan, statistically predicted traffic data is used. However, a traffic wave often occurs in real train service, and demand-driven simulation technology is required to review a train operation plan and service quality considering traffic waves. We propose a method and model to simulate Maglev operation considering continuous demand changes. For this purpose, we employed a discrete event model that is suitable for modeling the behavior of railway passenger transportation. We modeled the system hierarchically using discrete event system specification (DEVS) formalism. In addition, through implementation and an experiment using the DEVSim++ simulation environment, we tested the feasibility of the proposed model. Our experimental results also verified that our demand-driven simulation technology can be used for a priori review of train operation plans and strategies.

• 대한전기학회논문지
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• 제41권4호
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• pp.433-441
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• 1992

This paper describes an algorithm that can efficiently analyze the ECG signal using frame knowledge representation technique. Input to the analysis process is a set of significant points which have been extracted from an original sampled signal(lead II) by the syntactic peak recognition algorithm. The hierarchical property of ECG signal is represented by hierarchical AND/OR graph. The semantic information and constraints of the ECG signal are desctibed by frame. As the control mechanism for labeling points, the search mechanism with the mixed paradigms of data-driven and model driven hypothesis formation, scoring function, hypothesis modification network and instance inheritance are used. We used the CSE database in order to evaluate the performance of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.105.6-105
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• 2002

Contents 1We developed a new type of lower part of the human-sized BWR (biped walking robot) driven by a new actuator based on the ball screw which has high strength and high gear ratio. Each leg of the robot is composed of three pitch Joints and one roll joint. In all, a 8 degree-of-freedom robot was developed. A new type of actuator for the robot is proposed, which is composed of four bar link mechanism driven by the ball screw. The BWR was designed to walk autonomously by adapting small DC motors for the robot actuators and has an embeded controller system including host computer, batteries and motor drivers. In the performance test, we had basic stable walking data so far, but we f...

• 제어로봇시스템학회논문지
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• 제10권11호
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• pp.1100-1106
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• 2004

In this report, a self-organizing fuzzy neural network is proposed to control chemical feeding, which is one of the most important problems in water treatment process. In the case of the learning according to raw water quality, the self-organizing fuzzy network, which can be driven by plant operator, is very effective, Simulation results of the proposed method using the data of water treatment plant show good performance. This algorithm is included to chemical feeder, which is composed of PLC, magnetic flow-meter and control valve, so the intelligent control of chemical feeding is realized.

• 한국정밀공학회지
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• 제27권9호
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• pp.34-42
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• 2010

Agricultural automation has become more and more important by environmental change. The automation demands the highest technology due to the ever changing various conditions in agriculture system. In the paper, semi-autonomous pesticide spray robot system has been developed for rose farming in the glass house. The robot is in autonomous mode during pesticide spraying process driven on pipe rail. The robot is manually driven while moving from a rail to the next rail. The drive platform and autonomous operation control system are developed based on IT fusion technology. The pesticide spray system is also developed with nozzles and booms for precision mist spray system. Experimental data of nozzle test is also included.