• Journal of the korean Society of Automotive Engineers
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• v.18 no.6
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• pp.23-32
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• 1996

차량에서 엔진은 가장 큰 질량 집중체(concentrated mass)이다. 만약 엔진이 적절하게 구속되지 않거나 절연되어 있지 않으면, 차체에 진동을 일으키는 원인이 된다. 엔진은 다양한 진동 교란을 받는데 엔진 마운트는 이러한 모든 것들을 고립시키는 역할을 해야 하며, 엔진은 정적인 장착 하중에 대한 지지와 전후, 좌우 및 수직 방향의 운동에 대해 적절한 강성을 가져야 한다. 또한 정숙성을 향상시키기 위해서는 엔진 마운트의 재료인 고무의 강성계수를 낮추는 것이 필요한데 이는 일반적으로 내구성의 저하를 가져온다. 따라서 개발과정에서 강성계수를 낮추는 변경을 하면 부품의 내구성을 보정함에 따르는 재평가 또한 필요하게 된다. 엔진 마운트에 쓰이는 고무부품의 해석은 엔진 마운트 시스템에 대한 진동 해석 및 내구수명의 예측과 병행해야 하며, 진동해석으로부터 얻은 하중 지지 능력 등의 모든 요구 특성을 만족하기 위해서는 고무 재료의 특성에 대한 지식, 엔진 마운트의 장착 위치에 대한 결정 능력과 함께 주어진 조건에 대한 형상의 최적 설계 능력 등이 요구된다. 본 연구에서는 기본적인 형상을 파라미터화하여 엔진 마운트의 형상을 최적화 하는 절차를 제안하였다. 현재 승용차에 널리 사용되고 있는 부시형(bush type) 엔진마운트를 적용 모델로 선택하였으며, 엔진 마운트의 기본적인 형상을 몇개의 파라미터를 사용하여 정의하고 설계 사양으로 주어지는 강성값과 각 파라미터들의 조합으로 구성되는 형상이 갖는 강성값의 차이가 최소가 되도록 파라미터 값들을 최적화하였다. 최적화된 파라미터 값들로 구성되는 형상을 내구 성능, 성형성등을 고려하여 최종 형상으로 결정한다. 내구성능의 예측은 금속부품의 내구수명 예측에 널리 이용되고 있는 방법이 방진 고무부품의 경우에도 적용 가능한지를 검토하고, 방진 고무부품에도 일반적으로 적용될수 있는 내구수명 예측방안의 개발 가능성을 타진해 보았다. 본 연구의 목표는 시제품을 제작하기 이전에 설계된 부품에 대한 스프링 상수 및 내구특성을 체계적으로 규명하여 제품 시험의 횟수를 줄이고, 보다 정밀한 제품을 제작할 수 있도록 하기 위한 것이다.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.5
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• pp.260-270
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• 2007

Owing to the improved wireless communication technologies, it is possible to provide streaming service of multimedia with PDAs and mobile phones in addition to desktop PCs. Since mobile client devices have low computing power and low network bandwidth due to wireless network, the transcoding technology to adapt media for mobile client devices considering their characteristics is necessary. However, since mobile clients use wireless network and the wireless network have less stable bandwidth according to distance from AP and environments, it is hard to support stable QoS to mobile clients. In this paper, we propose a dynamic bit rate control method for transcoding in order to supprot stable QoS of streaming media service to mobile clients via wireless network. The proposed method is shown to serve seamless streaming media service with adaptive bit rate control according to state of wireless network in real time and to reduce transmission failure from experiment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.395-404
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• 2013

A pattern matching algorithm plays an important role in traffic identification and classification based on predefined patterns for intrusion detection and prevention. As attacks become prevalent and complex, current patterns are written using regular expressions, called regexes, which are expressed into the deterministic finite automata(DFA) due to the guaranteed worst-case performance in pattern matching process. Currently, because of the increased complexity of regex patterns and their large number, memory-efficient DFA from states reduction have become the mainstay of pattern matching process. However, most of the previous works have focused on reducing only the number of states on a single automaton, and thus there still exists a state blowup problem under the large number of patterns. To solve the above problem, we propose a new state compression algorithm that merges states on multiple automata. We show that by merging states with the same input character on multiple automata, the proposed algorithm can lead to a significant reduction of the number of states in the original DFA by as much as 40.0% on average.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.683-686
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• 2018

Autonomous vehicles are the 4th industrial revolution that utilizes artificial intelligence(AI) and superconducting technology, and is a world-wide investment and research project. However, a Uber vehicle under test in Arizona, USA, was accidentally killed by pedestrians crossing the road in the dark night, and accidents occurred when the Tesla vehicle was exposedto the backlightof the sun. These problems were caused by misunderstandings and choice about sensors mounted on autonomous vehicles due to bad weather such as snow, rain, and sunlight. In this paper, we analyze the composition of the autonomous vehicle and the cause of the accident, and consider the criteria that should be judged in case of emergency in which human accidents may occur. This paper analyzes the composition of autonomous vehicles and causes of accidents, and considers the criteria that should be choice in an emergency where an accident may occur.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.737-743
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• 2017

The intelligent life-log system proposed in this paper is intended to identify and record a myriad of everyday life information as to the occurrence of various events based on when, where, with whom, what and how, that is, a wide variety of contextual information involving person, scene, ages, emotion, relation, state, location, moving route, etc. with a unique tag on each piece of such information and to allow users to get a quick and easy access to such information. Context awareness generates and classifies information on a tag unit basis using the auto-tagging technology and biometrics recognition technology and builds a situation information database. In this paper, we developed an active modeling method and an application that recognizes expressionless and smile expressions using lip lines to automatically record emotion information.

• Journal of IKEEE
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• v.24 no.2
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• pp.632-637
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• 2020

The non-intrusive load monitoring (NILM) is an important way to cost-effective real-time monitoring the energy consumption and time of use for each appliance in a home or business using aggregated energy from a single recording meter. In this paper, we collect from the smart farm's power consumption data acquisition system to the server via an LTE modem, converted the total power consumption, and the power of individual electric devices into HDF5 format and performed NILM analysis. We perform NILM analysis using open source denoising autoencoder (DAE), long short-term memory (LSTM), gated recurrent unit (GRU), and sequence-to-point (seq2point) learning methods.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.1-8
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• 2003

Various methods have been studying to maintain and apply the multimedia inform abruptly increasing over all social fields, in recent years. For retrieval of still images, we is implemented content-based image retrieval system in this paper that make possible to retrieve similar objects from image database after segmenting query object from background if user request query. Query image is processed median filtering to remove noise first and then object edge is detected it by canny edge detection. And query object is segmented from background by using convex hull. Similarity value can be obtained by means of histogram intersection with database image after securing color histogram from segmented image. Also segmented image is processed gray convert and wavelet transform to extract spacial gray distribution and texture feature. After that, Similarity value can be obtained by means of banded autocorrelogram and energy. Final similar image can be retrieved by adding upper similarity values that it make possible to not only robust in background but also better correct object retrieval by using object segmentation method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.5
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• pp.609-616
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• 2007

Palletizing is necessary to promote the efficiency of storage and shipping tasks. These are, however some of the most monotonous, heavy and laborious tasks in the factory. Therefore many types of robot palletizing systems have been developed, but many robot motion commands still depend on the teaching pendent. That is, an operator inputs the motion command lines one by one. It is very troublesome, and most of all, the user must know how to type the code. That is why we propose a new GUI (Graphic User Interface) Palletizing System. To cope with this issue, we proposed a 'PLP' (Pallet Loading Problem) algorithm, Fast Algorithm and realize 3D auto-patterning visualization interface. Finally, we propose the robot palletizing simulator. Internally, the schematic of this simulator is as follows. First, an user inputs the physical information of object. Second, simulator calculates the optimal pattern for the object and visualizes the result. Finally, the calculated position data of object is passed to the robot simulator. To develop the robot simulator, we use an articulated robot, and analyze the kinematics and dynamics. Especially, All problem including thousands of boxes were completely calculated in less than 1 second and resulted in optimal solutions by the Fast Algorithm.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.447-453
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• 2020

In this paper, we propose a system to extract effective speaker representations from a speech signal using a deep learning method. Based on the fact that speech signal contains identity unrelated information such as text content, emotion, background noise, and so on, we perform a training such that the extracted features only represent speaker-related information but do not represent speaker-unrelated information. Specifically, we propose an auto-encoder based disentanglement method that outputs both speaker-related and speaker-unrelated embeddings using effective loss functions. To further improve the reconstruction performance in the decoding process, we also introduce a discriminator popularly used in Generative Adversarial Network (GAN) structure. Since improving the decoding capability is helpful for preserving speaker information and disentanglement, it results in the improvement of speaker verification performance. Experimental results demonstrate the effectiveness of our proposed method by improving Equal Error Rate (EER) on benchmark dataset, Voxceleb1.

• Composites Research
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• v.32 no.2
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• pp.120-126
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• 2019

Advanced fiber fabrics have been utilized in not only anti-stabbing and bullet-proofing for body armor but also various industrial fields including vehicular armor and spacecraft structure. Furthermore, there have been a number of research to improve the ballistic performance of advanced fabrics introducing many computational approaches. In our research, an advanced fabric, Heracron manufactured in South Korea was modelled firstly using Autodyn, a commercial software specializing in impact and explosion phenomenon. The sensitivity of the input parameters was also confirmed by conducting simulations. To verify the numerical modelling, we measured and compared the simulation results with velocity decrements after impact involving one, three, and five layers of Heracron under 200-500 m/s impacts by an aluminum spherical projectile. The Heracron fabric was successfully modelled using Autodyn.