• Therapeutic Science for Rehabilitation
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• v.2 no.1
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• pp.24-35
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• 2013

The Purpose of this study was to determine the clinical effectiveness of mirror therapy for stroke. Moreover, this paper was designed to summarize clarified information of neurological plasticity by mirror therapy to finally define the neurological mechanism. Mirror therapy improves the stroke patients' hand and arm motor function. It also has a positive influence on recovering performance of activities of daily living and relieving pain. However, it is not evident that mirror therapy restores visual neglect. There are various ways of recovering stroke. Fundamentally, all the theories are on a bases of restoration of premotor area. Premotor area which is associated with motor control increases the activation of primary motor area and finally improves patients' motor function. If primary motor area is completely damaged, premotor area and supplementary motor substitute for primary motor area. In summary of literature survey, there are not enough evidence to verify the effectiveness and neurological mechanism of mirror therapy. In future, more researches should be conducted to verify the neurological recovery through mirror therapy. Then, mirror therapy will be acknowledged as a clinically effective treatment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2121-2128
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• 2015

In this paper presents a method of extracting reliable and regions of interest (ROI) in barcode for the purpose of factory automation. backgrounds are separated based on directional components and the characteristics of detected patterns. post-processing is performed on candidate images with analysis of problems caused by blur, rotation and areas of high similarity. In addition, the resizing factor is used to achieve faster calculations through image resizing. The input images contained multiple product or barcode for application to diverse automation environments; a high extraction success rate is accomplished despite the maximum shooting distance of 80 cm. Simulations involving images with various shooting distances gave an ROI detection rate of 100% and a post-processing success rate of 99.3%.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.6
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• pp.601-605
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• 2020

In large ships with complex structures, it is difficult to locate workers. In particular, it is not easy to detect when a worker falls down, making it difficult to respond quickly. Thus, research is being conducted to detect fallen workers using a camera or by attaching a device to the body. Existing image-based fall detection systems have been designed to detect a person's body parts; hence, it is difficult to detect them in various ships and postures. In this study, the entire fall area was extracted and deep learning was used to detect the fallen shipworker based on the image. The data necessary for learning were obtained by recording falling states at the shipyard. The amount of learning data was augmented by flipping, resizing, and rotating the image. Performance evaluation was conducted with precision, reproducibility, accuracy, and a low error rate. The larger the amount of data, the better the precision. In the future, reinforcing various data is expected to improve the effectiveness of camera-based fall detection models, and thus improve safety.

• Journal of KIISE:Software and Applications
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• v.37 no.5
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• pp.363-369
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• 2010

Demonstration-based learning has the advantage that a user can easily teach his/her robot new task knowledge just by demonstrating directly how to perform the task. However, many previous demonstration-based learning techniques used a kind of attribute-value vector model to represent their state spaces and policies. Due to the limitation of this model, they suffered from both low efficiency of the learning process and low reusability of the learned policy. In this paper, we present a new demonstration-based learning method, in which the relational model is adopted in place of the attribute-value model. Applying the relational instance-based learning to the training examples extracted from the records of the user demonstrations, the method derives a relational instance-based policy which can be easily utilized for other similar tasks in the same domain. A relational policy maps a context, represented as a pair of (state, goal), to a corresponding action to be executed. In this paper, we give a detail explanation of our demonstration-based relational policy learning method, and then analyze the effectiveness of our learning method through some experiments using a robot simulator.

• Journal of KIISE:Software and Applications
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• v.35 no.5
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• pp.325-334
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• 2008

The goal of text categorization is to classify documents into a certain number of pre-defined categories. The previous studies in this area have used a large number of labeled training documents for supervised learning. One problem is that it is difficult to create the labeled training documents. While it is easy to collect the unlabeled documents, it is not so easy to manually categorize them for creating training documents. In this paper, we propose a new text categorization method based on semi-supervised learning. The proposed method uses only unlabeled documents and keywords of each category, and it automatically constructs training data from them. Then a text classifier learns with them and classifies text documents. The proposed method shows a similar degree of performance, compared with the traditional supervised teaming methods. Therefore, this method can be used in the areas where low-cost text categorization is needed. It can also be used for creating labeled training documents.

• Journal of Welding and Joining
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• v.12 no.2
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• pp.11-19
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• 1994

레이저 가공기술은 재료가공 분야에서 넓은 응용분야를 가지고 있으며, 특히 절단, 용접, 열처리 등의 가공분야에서 고정밀도와 자동화의 용이성으로 인해 생산성이 높은, 고부가가치의 첨단응용 기술로 부각되고 있다. 특히 레이저절단은 타 절단법에 비교되는 절단정도, 열영향, 생산성, 작업 환경등의 각종 우위성으로 박판 및 후판절단분야에서 급속한 보급을 보이기 시작하였다. 현재 대 부분의 레이저 가공기는 CNC화 되어가고 있는 추세이며, 레이저 절단의 경우 생산성증대 및 고 정밀화를 위하여 CAD/CAM인터페이스에 의한 자동화가 필연적인 상황이다. 뿐만아니라 고출력 레이저 발전기를 가공 기본체에 탑재한 탑재형 레이저가공기의 출현으로 대형부재의 절단이 가능 하게 되었으며, 더불어 절단공정의 무인화를 지향하는 각종 시스템이 개발되고 있다. 이와 같은 무인화, 생산성증대, 작업시간단축과 러닝 코스트 및 재료의 절감을 위한 노력의 일환으로 컴 퓨터에 의한 자동 및 반자동 네스팅 시스템의 개발을 들 수 있다. 레이저에 의한 2차원 절단응 용분야에서의 네스팅작업은 설계가 끝난 각 부품의 절단작업의 전단계로서 수행되며, 일반적으로 네스팅공정이 완료되면 절단경로를 결정하고 가공조건과 함께 수치제어공작기계의 제어에 필요한 NC코드를 생성하게 된다. 최근에는 이와 같은 네스팅 시스템이 일부 생산현장에 적용되고 있 으나 이러한 시스템들의 대부분이 외국에서 개발된 것을 수입하여 사용하는 실정이다. 2차원 패턴의 최적자동배치문제는 비단 레이저 절단과 같은 열가공 분야에서 뿐만 아니라 블랭킹 금형, 의류, 유리, 목재등 여러분야에서 응용이 가능하며 패키지의 국산화가 시급한 실정이다. 네스 팅작업은 적용되는 분야에 따라 요구사항과 구속조건이 달라지며 이로 인해 알고리즘과 자료구 조도 달라지게 되나 공통적인 목표는 주어진 영역안에서 겹침없이 배치하면서 버림율을 최소화 하는 것이다. 지난 10여년간 여러 산업의 응용분야에서는 네스팅시스템의 도입이 활발하게 이 루어지고 있는데 수동에 반자동 및 자동에 이르기까지 다양하나 자동네스팅시스템의 경우 배치 효율의 신뢰성이 비교적 부족하기 때문에 아직까지는 생산현장에서 기피하는 실정이다. 배치알 고리즘의 관점에서 볼 때 이러한 문제들은 NP-complete문제로 분류하며 제한된 시간안에 최적의 해를 구하기가 가능한 조합 최적화 문제로 알려져 있다. 따라서 이 글에서는 레이저 절단분야 에서의 네스팅시스템에 관한 개요와 최근의 연구동향 그리고 몇 가지 전형적인 네스팅 알고리 즘들을 소개하고 비교분석을 통해 개선점을 간략하게 논의하고자 한다.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.267-273
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• 2011

In this paper, we proposed the method to detect brain tumor region in MR images. Our method is composed of 3 parts, detection of tumor slice, detection of tumor region and tumor boundary detection. In the tumor slice detection step, a slice which contains tumor regions is distinguished using symmetric analysis in 3D brain volume. The tumor region detection step is the process to segment the tumor region in the slice distinguished as a tumor slice. And tumor region is finally detected, using spatial feature and symmetric analysis based on the cluster information. The process for detecting tumor slice and tumor region have advantages which are robust for noise and requires less computational time, using the knowledge of the brain tumor and cluster-based on symmetric analysis. And we use the level set method with fast marching algorithm to detect the tumor boundary. It is performed to find the tumor boundary for all other slices using the initial seeds derived from the previous or later slice until the tumor region is vanished. It requires less computational time because every procedure is not performed for all slices.

• The Journal of Korean society of community based occupational therapy
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• v.1 no.2
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• pp.61-69
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• 2011

This paper proposes that people with disability can be successfully supported by smart homes only when their needs of the technological interventions are understood and integrated in traditional universal design. Understanding the patient's home environment is an integral part of treatment and discharge planning. This paper suggests on architectural barriers commonly found in the home, ways to eliminate them and a general overview of methods for assessment and intervention. It is expected that the electronics, information and communication technology can be an alternative of traditional universal designs for motor dysfucntion, sensory dysfunction and cognitive dysfunction.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.127-129
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• 2016

근래 소규모항만이 흩어져 있는 연안도서해역에서는 빈번한 폭풍의 내습으로 신규 외곽시설을 포함한 항만정비사업이 지속적으로 이루어지고 있다. 이들 항만의 경우 늘어나는 물동량에 대응하기 위해 수역시설 및 부두의 배치에 변화를 가져오고 일부 항만의 경우 만입구, 항내, 수로 등 특정해역의 준설이 다양하게 이루어지고 있어서 개발과 유지 준설에 따른 정온도의 검토가 필요한 실정이다. 본 연구에서는 바람, 파랑상호간 간섭, 흐름과의 상호작용, 쇄파 및 구조물에 대한 반사를 반영하여 수치실험을 수행하고 특히 준설작업의 규모, 방향에 따른 정온도에서 결과에 차이를 나타내어 평면배치계획에 수정을 기할 수 있게 되었다. 수치실험에는 50면 재현빈도 심해설계파 내습시 영역을 광역, 중간역, 상세역으로 하여 네스팅 기법으로 개방해역조건을 반영하였으며 외곽시설에서 해수소통 개구부의 변화에 대한 영향을 분석하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.358-359
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• 2018

In this paper, opencv and android studio are used to distinguish between objects ahead of the blind. When the movement is detected in a positive direction in connection with the camera of the smartphone, the user is informed that the part of the camera is being rabelified and continues to track using the mean shift algorithm. A C ++ program based on OpenCV-based was used for real-time motion observation and the application will be produced by android studio. As a result of the study, objects that move with Labeling are identified and the box area is specified using the mean shift algorithm to move the box along with the object to track objects in real time.