• Journal of the Korean Society of Clothing and Textiles
• /
• v.40 no.5
• /
• pp.788-800
• /
• 2016

This study proposes an execution protocol for fashion therapy. Research on fashion therapy are limited and insufficient for the current need for the establishment of a fashion therapy theory. This study introduces cognitive behavior therapy, embodied cognition, and object relations theory as theories that underlie fashion therapy. A fashion therapy system model is provided based on the analysis of art therapy to explore its applicability to fashion therapy. The fashion therapy system model utilizes fashion items to managing pain and stress to better competence, encouragement and self-expression mechanisms to improve social, psychological, emotional and behavioral functions. In addition, 8 phases of the fashion therapy process (inquiry, forming rapport, assessment, goal-objective, observation, selection of strategy and design, practice, and the final evaluation and closing of fashion therapy) are suggested for developing a practical fashion therapy program. This study is to help overcome a negative perspective on fashion that provokes an excessive spending behavior and to make a practical contribution by creating more social value through fashion. The significance of the study is in the attempt to create an interdisciplinary approach of psychotherapy and fashion that can be extend into the fashion and textile discipline.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.38 no.3
• /
• pp.24-40
• /
• 2001

The design and implementation of agents is an essential part of the development of immersive types of tutoring systems using virtual reality. This paper proposes several effective mechanisms for the design and implementation of agents. Unlike existing researches we focus on accommodating diversity of agents' behavior in the proposed mechanisms. First, we define the space object based on the field theory. The introduction of the field theory allows us to approach the space objects in a structural manner rather than by their classification. We can also achieve dynamic genesis and extinction of the space objects, and derivation of overall changes in spatio-temporal situations. Second, we classify the behavior of agents into composite behaviors and primitive actions in order to achieve its dynamic planning. Finally, we distribute the knowledge among agents and their associated objects according to their interrelations. By this distribution, we can handle the otherwise prohibitively large amount of knowledge related to agents' behaviors and construct a dynamic environment. By implementing a situation with agent's navigation across a composite space object, we demonstrate the effectiveness of these schemes presented above.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.12 no.1
• /
• pp.43-52
• /
• 1994

This paper outlines a new approach to the line generalization when preparing small scale map on the basis of existing large scale digital map. Line generalizations are conducted based on Douglas algorithm using 1/25,000 scale topographic maps of southeastern JEJU island which produced by National Geographic Institute to analyze the fitness to the original and problems of graphical representation. Compare to the same scale map which was generated by manual method, a verity of small, but sometimes significant errors ＆ modification of topological relationship have been detected. The research gives full details of three algorithms that operationalize the smallest visible object method, together with some empirical results. A comparison of the results produced by the new algorithms with those produced by manual generalization and Douglas method of data reduction is provided. Also this paper presents the preliminary results of an relationships between the size of smallest visual object and requiring data storages for each algorithms.

• Phonetics and Speech Sciences
• /
• v.10 no.2
• /
• pp.51-60
• /
• 2018

This study aims to compare the word decoding skills, phonological awareness (PA), rapid automatized naming (RAN) skills, and letter knowledge of first graders with developmental dyslexia (DD) and those who were typically developing (TD). Eighteen children with DD and eighteen TD children, matched by nonverbal intelligence and discourse ability, participated in the study. Word decoding of Korean language-based reading assessment(Pae et al., 2015) was conducted. Phoneme-grapheme correspondent words were analyzed according to whether the word has meaning, whether the syllable has a final consonant, and the position of the grapheme in the syllable. Letter knowledge asked about the names and sounds of 12 consonants and 6 vowels. The children's PA of word, syllable, body-coda, and phoneme blending was tested. Object and letter RAN was measured in seconds. The decoding difficulty of non-words was more noticeable in the DD group than in the TD one. The TD children read the syllable initial and syllable final position with 99% correctness. Children with DD read with 80% and 82% correctness, respectively. In addition, the DD group had more difficulty in decoding words with two patchims when compared with the TD one. The DD group read only 57% of words with two patchims correctly, while the TD one read 91% correctly. There were significant differences in body-coda PA, phoneme level PA, letter RAN, object RAN, and letter-sound knowledge between the two groups. This study confirms the existence of Korean developmental dyslexics, and the urgent need for the inclusion of a Korean-specific phonics approach in the education system.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.26 no.3
• /
• pp.95-104
• /
• 1989

This paper presents a new shadow testing acceleration scheme for ray tracing called Hybrid Shadow Testing (HST) based on a conditional switching between the conventinal shadow testing method and Crow's shadow volume method, where the shadow polygons as well as the object polygons are registered onto the corresponding cells under the 3-D space subdivision environment. Despite the preprocessing time for the generation and registration of the shadow polygons, the total shadow testing time of the proposed algorithm, HST was approximately 50% of that of the conventional shadow testing method for several examples while the total ray tracing time was typically reduced by 30% from the conventional approach. This due to the selective use of the shadow volume method with a compromise between the maximal utilisation of shadow's spatial coherency and minimising the computational overhead for checking ray intersections with the shadow polygons. A parameter, $N_{th}$ denoting the critical number of shadow polygons between successive reflection points was used as a guideline for switching the shadow testing scheme between the conventional method and shadow volume method. A method for calculating $N_{th}$ from such statistical data as the number of object polygons, average polygon size average peripheral length of the polygons was proposed, resulting in good agreement with the experimental results.

• Land and Housing Review
• /
• v.14 no.4
• /
• pp.95-102
• /
• 2023

Numerous investigations have explored the integration of machine leaning algorithms with high-resolution drone image for object detection in urban settings. However, a prevalent limitation in vehicle extraction studies involves the reliance on bounding boxes rather than instance segmentation. This limitation hinders the precise determination of vehicle direction and exact boundaries. Instance segmentation, while providing detailed object boundaries, necessitates labour intensive labelling for individual objects, prompting the need for research on automating unsupervised instance segmentation in vehicle extraction. In this study, a novel approach was proposed for vehicle extraction utilizing unsupervised SVM classification applied to vehicle bounding boxes in drone images. The method aims to address the challenges associated with bounding box-based approaches and provide a more accurate representation of vehicle boundaries. The study showed promising results, demonstrating an 89% accuracy in vehicle extraction. Notably, the proposed technique proved effective even when dealing with significant variations in spectral characteristics within the vehicles. This research contributes to advancing the field by offering a viable solution for automatic and unsupervised instance segmentation in the context of vehicle extraction from image.

• Korean Journal of Remote Sensing
• /
• v.40 no.2
• /
• pp.151-166
• /
• 2024

Coastal debris presents a significant environmental threat globally. This research sought to improve the monitoring methods for coastal debris by employing deep learning and remote sensing technologies. To achieve this, an object detection approach utilizing the You Only Look Once (YOLO)v8 model was implemented to develop a comprehensive image dataset for 11 primary types of coastal debris in our country, proposing a protocol for the real-time detection and analysis of debris. Drone imagery was collected over Sinja Island, situated at the estuary of the Nakdong River, and analyzed using our custom YOLOv8-based analysis program to identify type-specific hotspots of coastal debris. The deployment of these mapping and analysis methodologies is anticipated to be effectively utilized in managing coastal debris.

• Journal of KIISE:Software and Applications
• /
• v.26 no.9
• /
• pp.1105-1113
• /
• 1999

객체 지향 소프트웨어의 확장과 더불어 소프트웨어의 재사용성의 중요도가 부각되면서 소프트웨어를 콤포넌트 단위로 구현하는 추세이다. 따라서 콤포넌트 기반의 소프트웨어 개발에서의 통합 테스트가 중요한 이슈로 떠오르고 있다. 그러나 콤포넌트들의 통합 테스트에 대한 연구는 미흡한 상태이다. 본 논문에서는 UML을 기반으로 체계적인 통합 테스트 모형을 제안하고. 나아가 본 논문에서는 "멀티미디어 정보처리 시스템"의 사례를 본 논문의 콤포넌트 통합 테스트 모형에 적용한 결과를 분석하여 기술한다. 콤포넌트 통합 테스트 모형은 UML(Unified Modeling Language)의 순서도(sequence diagram)와 협력도(collaboration diagram)를 이용하여 전체 시스템에서 UML의 사건흐름을 구성하는 콤포넌트들 사이의 인터페이스 영역에 존재하는 오류들을 추출한다. 그리고 UML을 기반으로 통합 테스트를 수행함으로써, 테스트 준비 작업을 줄이고, 기존의 UML 지원 도구들과 연계하여 테스트 자동화 도구의 구현을 앞당길 수 있다. 또한 시스템의 순차적 흐름 뿐 아니라, 동시에 수행되는 흐름에 대한 정보까지 모두 수용하여 테스트함으로써, 콤포넌트 기반의 분산 환경의 특성에 적합하다. Abstract As the object-oriented approach to software development becomes more mature, software development from pre-existing, independently developed components becomes an important aim of software engineering. Therefore, integration testing becomes an important aspect of component-based software development. However, there has been little work done in the area of the component-based integration testing. In this paper, we propose the "component integration test model" which is based on UML. Furthermore, we describe a case study on "Multimedia Information Processing System" conducted to analyse the result from which our model is applied. Our model extracts the faults, which exist in interfaces of components, using sequence diagram and collaboration diagram of UML(Unified Modeling Language). As our model is based on UML, the preparation effort for testing is reduced and its test-tools can be implemented more easily through linking existing UML tool. And our model accepts the information of concurrent flow represented by collaboration diagram as well as sequential flow, so it is more suitable to component-based distributed environment.based distributed environment.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.3
• /
• pp.121-128
• /
• 2010

Whenever and wherever, recognizing location of object such as human as well as things, ubiquitous Location-Based Service which provides useful service based on this are rising as an important service. In this paper, we implemented customized real time 1:1 e-CRM system that can communicate with user's mobile phone through using Location-Based Service of mobile phone. Among various scenarios that are applicable to designed system, development and test were conducted based on scenario that provides shopping information and discount information to customers through SMS as they approach to vicinity of large discount store and allow them to download discount coupons through Call Back. The suggested system will be applied to various service event and can be used as a customized real time marketing method according to user's personal activity area.

• The Journal of Korea Robotics Society
• /
• v.19 no.1
• /
• pp.98-105
• /
• 2024

This paper proposes a new approach with a distance-based regularization to the entropy applied to the NBV (Next-Best-View) selection with NeRF (Neural Radiance Fields). 3D reconstruction requires images from various viewpoints, and selecting where to capture these images is a highly complex problem. In a recent work, image acquisition was derived using NeRF's ray-based uncertainty. While this work was effective for evaluating candidate viewpoints at fixed distances from a camera to an object, it is limited when dealing with a range of candidate viewpoints at various distances, because it tends to favor selecting viewpoints at closer distances. Acquiring images from nearby viewpoints is beneficial for capturing surface details. However, with the limited number of images, its image selection is less overlapped and less frequently observed, so its reconstructed result is sensitive to noise and contains undesired artifacts. We propose a method that incorporates distance-based regularization into entropy, allowing us to acquire images at distances conducive to capturing both surface details without undesired noise and artifacts. Our experiments with synthetic images demonstrated that NeRF models with the proposed distance and entropy-based criteria achieved around 50 percent fewer reconstruction errors than the recent work.