• Annual Conference of KIPS
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• 2011.04a
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• pp.763-766
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• 2011

Timely management is an important activity in long running transactions. This can be seen in many Supply Chain scenarios where insufficient time management could lead to expensive compensations. Therefore, effective strategy for timely management in long running transactions is needed. In this paper, we propose our solution to detect and avoid violating deadline based on a comparison strategy of predicted complete time and required deadline. Three approaches are used. Firstly, we build Open Nested Transaction Model (ONTM) where deadline of top-level transactions are managed through a flexible time adjustment of lower level transactions. Secondly, workflow is introduced to WSTransaction framework which supports the algorithm to predict complete time and spot delaying activities. Thirdly, a rule-based coordinator is developed to decide the confirmation or cancelation of participants' ongoing activities. We also discuss a workflow example for implementation.

• Annual Conference of KIPS
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• 2011.11a
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• pp.1166-1169
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• 2011

In this paper, we design a Circle dot Code, In our scheme, we design a dot patterns for increasing maximum capacity and also for increasing robustness to Affine Transformation. Our code Can be extended according number of data circle. We use three data circle vision code. In this type code, after acquiring camera images for the Circle dot Codes, and perform error correction decoding using four position symbols and six CRC symbols. We perform graph based dot code analysis which determines the topological distance between dot pixels. Our code can be bridged the real world and ubiquitous computing environment.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.110-116
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• 2023

Recently, as various examples of machine learning have been applied in the healthcare field, deep learning technology has been applied to various tasks, such as electrocardiogram examination and body composition analysis using wearable devices such as smart watches. To utilize deep learning, securing data is the most important procedure, where human intervention, such as data classification, is required. In this study, we propose a model that uses a clustering algorithm, namely, the K-means clustering, to label body fat according to gender and age considering body size aspects, such as chest circumference and waist circumference, and classifies body fat into five groups from high risk to low risk using a convolutional neural network (CNN). As a result of model validation, accuracy, precision, and recall results of more than 95% were obtained. Thus, rational decision making can be made in the field of healthcare or obesity analysis using the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.8
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• pp.629-639
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• 1989

One of the major issues of the industrial vision systems is lengthy processing time due to bulky data for image coding. To reduce the processing time, a modified chain coding algorithm is proposed in such a way that it is more suitable for hardware implementation. A hardware chain coder is developed and used for learn and recognizing objects by extracting several features. It is shown that the desired vision system is much faster than a typical software based system so that it may be applicable to real-time industrial operations.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.1
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• pp.101-113
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• 1986

In this paper, a real-time pitch detector LPC vocoder as implemented on a high speed digital signal processor, NEC 7720, is described. The pitch detector was based mainly on the SIFT algorithm. The SIFT pitch detector consists primarily of a digital low pass filter, inverse filter, computation of autocorrelation, a peak picker, interpolation, V/UV defcision and a final pitch smoother. In our approach, modification, mainly on the V/UV decision and a final pitch smoother, was made to estimate more accurate pitches. An 16-bit fixed-point aithmatic was employed for all necessary computation and the simulated results were compared with the eye detected pitches obtained from real speech data. The pitch detector occupies 98.8% of the instruction ROM, 37% of the data ROM, and 94% of internal RAM and takes 15.2ms to estimate a pitch when an analysis frame is consisted of 128 sampled speech data. It is observed that the tested results were well agreed with the computer simulation results.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.5
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• pp.143-152
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• 1994

The velocity trajectory profile of trolley is designed to minimize both swinging while transportation of load and the stop position error at the final stop position. This profile is designed to be automatically programmed by the digital control algorithm when the length of chain and the desired travel distance are given as a priori. Also, to minimize both swinging and the stop position error the anti-swing controller which improves poor damping characteristics of the crane and the stop position controller are employed. The experimentalresults of sequential adaptation of the velocity trajectory profile and these two controllers show that this control scheme has excellent control performance as compared with that of the uncontrolled crane system.

• Annual Conference of KIPS
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• 2020.11a
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• pp.777-780
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• 2020

본 논문은 동일 목적지를 가진 다수의 사람들이 동일 이동 수단을 탑승하여 이동할 경우 발생하는 소요 시간의 감소를 위한 거점 군집에 대해 다루려 한다. 실제 도로망에서는 노드에 해당하는 사람들의 위치가 유동적으로 변화 하고 사람 간의 거리 값 또한 변화하게 된다. 따라서 동일한 목적지를 가진 다수의 사람들이 한 대의 차량을 탑승하여 이동한다고 가정할 때 차량의 최단 경로 및 소요 시간 감소를 목적을 기반으로 설계하였다. 차량의 최단 경로를 감소시키 위해서 사람들을 군집화 하는 방법을 사용하였고 그 결과 경유지가 감소 되어 차량의 이동 경로 값은 감소되었다. 또한, 전체 이동 소요 시간 역시 군집을 통해 감소시킬 수 있다. 본 논문에서는 이와 같이 군집을 이용한 최단 경로의 감소와 전체 이동시간 감소에 대한 알고리즘을 설계하고 구현하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.523-524
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• 2021

COVID-19 확산으로 인해 우리나라는 공공장소 출입 시 마스크 착용이 의무화되었고, 체온이 37.5℃ 이상일 경우 발열로 간주하여 출입을 금지함에 따라 이를 효율적으로 검사할 수 있는 자동화 시스템을 개발하고자 한다. 이를 위해 다양한 각도, 마스크의 착용 위치에 따른 자료를 수집하여 모델에 적용하였고, 실시간 영상은 96.5%의 높은 정확도를 보였고, 영상 처리 추론 속도는 28fps임을 확인했다. 본 논문은 딥러닝 알고리즘을 활용한 마스크 착용 판별 및 체온 측정 시스템을 제시한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.9-11
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• 2022

Applying Reinforcement Learning in everyday applications and varied environments has proved the potential of the of the field and revealed pitfalls along the way. In robotics, a learning agent takes over gradually the control of a robot by abstracting the navigation model of the robot with its inputs and outputs, thus reducing the human intervention. The challenge for the agent is how to implement a feedback function that facilitates the learning process of an MDP problem in an environment while reducing the time of convergence for the method. In this paper we will implement a reward shaping system avoiding sparse rewards which gives fewer data for the learning agent in a ROS environment. Reward shaping prioritizes behaviours that brings the robot closer to the goal by giving intermediate rewards and helps the algorithm converge quickly. We will use a pseudocode implementation as an illustration of the method.

• Annual Conference of KIPS
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• 2022.11a
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• pp.848-850
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• 2022

본 논문은 주택 청약 과정의 어려움을 줄이고 부적격 당첨으로 인한 불이익을 방지하기 위해 개발된 청약 자격 진단 알고리즘과 가점 계산 알고리즘의 설계 및 개발 결과를 제시한다. 청약 자격 판단 알고리즘은 적격 여부 판단을 위한 조건을 모두 고려하고, 부적격으로 진단될 경우 사유까지 상세하게 제공한다는 점에서 기존 서비스와 차별성을 가진다. 가점 계산 알고리즘은 자격 진단에서 적격으로 판단된 경우, 사용자 정보로 가점을 계산하고 결과를 제공한다. 분양 방식에 따라 가점 계산 기준에 차이가 있는데, 본 알고리즘은 해당 기준을 모두 고려하여 개발되었다는 점에서 실용적이다.