• Title/Summary/Keyword: Human-content interface

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A Study on the Development of a Quantified Module for the Evaluation of industrial Design Proposals (산업디자인 제품화 개발을 위한 정략적모듈의 개발)

  • 우흥룡;신학수;고을한;한석우;홍석기;김창현
    • Archives of design research
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    • v.9
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    • pp.801-810
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    • 1994
  • Design Problems are often both multidimensional and highly interactive. Very rarely does any part of a designed thing serve only one purpose. The activity of designing is thus a goal-directed activity and normally a goal-directed problem-solving activity. This means, problem solving is finding a way to get from some initial situation to a desired goal. Designers are transforming agents within a society whose goals are to improve the human condition through physical metamorphosis. Many theorist have agreed that designing involves problem solving or decision making. Accordingly evaluation plays an essential role in design activity. The evaluation factors include all attributes that have levels specified by quantitative and qualitative objectives Alternatives in multi-objective decision prOblems generally possess numerous attributes by which they can be described and compared. The evaluation factors include all attributes that have levels specified by quantitative and qualitative objectives. However since qualitative factors are difficult to quantify as numeral estimates, these factors have tended to be ignored without regard for their importance to human content. We adapted the Accumulative Evaluation Model as an evaluation algorithm for IDES. Industrial Design Evaluation System (IDES) consists of 3 major modules ( 1 Design Element, 2.Matrix, 3.Evaluation). It is intended to be an aid for design evaluation. The luther thinks IDES is a new design evaluation approach which could provide effective rating of design values to make value judgements. It is an attempt to provide industrial designers with access to design evaluation. The author's aim is to produce an Object-Oriented Evaluation System which can guide the designers and decision makers under complex design projects. It uses\ulcorner an Object-Oriented Programming for this prototype, Because of managing complexity (Flexibility and Reusability) and improving productivity(Extensibility & Maintainability and Programming by User) in software development process. The author has chose the C++ because it is a hybrid, rather than pure Object-Oriented Language.

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Deriving Topics for Safety of Folk Villages Following Scope and Content of ICT-Based DPD

  • Oh, Yong-Sun
    • International Journal of Contents
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    • v.12 no.2
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    • pp.12-23
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    • 2016
  • This paper presents a novel concept of Disaster Prevention Design (DPD) and its derived subjects and topics for the safety of folk villages in both Korea and Japan. Nowadays, design concepts are focused on 'human-oriented nature' as a whole and this tendency fits to be appropriate for disaster prevention against real dangers of a future society, which is expected to have far more complicated features. On the other hand, convergences have performed with other areas in the field of Information Communication Technology (ICT) so that we can easily find examples like 'the strategy of ICT-based convergence' of the Korean Government in 2014. Modern content designs including UI (user interface) and USN (ubiquitous sensor network) have been developed as one of the representative areas of ICT & UD (universal design) convergences. These days this novel concept of convergence is overcoming the existing limitations of the conventional design concept focused on product and/or service. First of all, from that point our deduced topic or subject would naturally be a monitoring system design of constructional structures in folk villages for safety. We offer an integrated model of maintenance and a management-monitoring scheme. Another important point of view in the research is a safety sign or sign system installed in folk villages or traditional towns and their standardization. We would draw up and submit a plan that aims to upgrade signs and sign systems applied to folk villages in Korea and Japan. According to our investigations, floods in Korea and earthquakes in Japan are the most harmful disasters of folk villages. Therefore, focusing on floods in the area of traditional towns in Korea would be natural. We present a water-level expectation model using deep learning simulation. We also apply this method to the area of 'Andong Hahoe' village which has been registered with the World Cultural Heritage of UNESCO. Folk village sites include 'Asan Oeam', 'Andong Hahoe' and 'Chonju Hanok' villages in Korea and 'Beppu Onsen' village in Japan. Traditional Streets and Markets and Safe Schools and Parks are also chosen as nearby test-beds for DPD based on ICT. Our final goal of the research is to propose and realize an integrated disaster prevention and/or safety system based on big data for both Korea and Japan.

Brain Correlates of Emotion for XR Auditory Content (XR 음향 콘텐츠 활용을 위한 감성-뇌연결성 분석 연구)

  • Park, Sangin;Kim, Jonghwa;Park, Soon Yong;Mun, Sungchul
    • Journal of Broadcast Engineering
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    • v.27 no.5
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    • pp.738-750
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    • 2022
  • In this study, we reviewed and discussed whether auditory stimuli with short length can evoke emotion-related neurological responses. The findings implicate that if personalized sound tracks are provided to XR users based on machine learning or probability network models, user experiences in XR environment can be enhanced. We also investigated that the arousal-relaxed factor evoked by short auditory sound can make distinct patterns in functional connectivity characterized from background EEG signals. We found that coherence in the right hemisphere increases in sound-evoked arousal state, and vice versa in relaxed state. Our findings can be practically utilized in developing XR sound bio-feedback system which can provide preference sound to users for highly immersive XR experiences.

Applicability evaluation of GIS-based erosion models for post-fire small watershed in the wildland-urban interface (WUI 산불 소유역에 대한 GIS 기반 침식모형의 적용성 평가)

  • Shin, Seung Sook;Ahn, Seunghyo;Song, Jinuk;Chae, Guk Seok;Park, Sang Deog
    • Journal of Korea Water Resources Association
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    • v.57 no.6
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    • pp.421-435
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    • 2024
  • In April 2023, a wildfire broke out in Gangneung located in the east coast region due to the influence of the Yanggang-local wind. In this study, GIS-based RUSLE(Revised Universal Soil Loss Equation) and SEMMA (Soil Erosion Model for Mountain Areas) were used to evaluate the erosion rate due to vegetation recovery in a small watershed of the Gangneung WUI(Wildland-Urban Interface) fire. The small watershed of WUI fire has a low altitude range of 10-30 m and the average slope of 10.0±7.4° which corresponds to a gentle slope. The soil texture was loamy sand with a high organic content and the deep soil depth. As herbaceous layer regenerated profusely in the gully after the wildfire, the NDVI (Normalized Difference Vegetation Index) reached a maximum of 0.55. Simulation results of erosion rates showed that RUSLE ranged from 0.07-94.9 t/ha/storm and SEMMA ranged from 0.24-83.6 t/ha/storm. RUSLE overestimated the average erosion rate by 1.19-1.48 times compared to SEMMA. The erosion rates were estimated to be high in the middle slope where burned pine trees were widely distributed and the slope was steep and to be relatively low in the hollow below the gully where herbaceous layer recovers rapidly. SEMMA showed a rapid increase in erosion sensitivity under at certain vegetation covers with NDVI below 0.25 (Ic = 0.35) on post-fire hillslopes. Gentle slopes with high organic content and rapid recovery of natural vegetation had relatively low erosion rate compared to steep slopes. As subsequent infrastructure and human damages due to sediment disaster by heavy rain is anticipated in WUI fire areas, the research results may be used as basic data for targeted management and decision making on the implementation of emergency treatment after the wildfire.

Big Data based Tourist Attractions Recommendation - Focus on Korean Tourism Organization Linked Open Data - (빅데이터 기반 관광지 추천 시스템 구현 - 한국관광공사 LOD를 중심으로 -)

  • Ahn, Jinhyun;Kim, Eung-Hee;Kim, Hong-Gee
    • Management & Information Systems Review
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    • v.36 no.4
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    • pp.129-148
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    • 2017
  • Conventional exhibition management information systems recommend tourist attractions that are close to the place in which an exhibition is held. Some recommended attractions by the location-based recommendation could be meaningless when nothing is related to the exhibition's topic. Our goal is to recommend attractions that are related to the content presented in the exhibition, which can be coined as content-based recommendation. Even though human exhibition curators can do this, the quality is limited to their manual task and knowledge. We propose an automatic way of discovering attractions relevant to an exhibition of interests. Language resources are incorporated to discover attractions that are more meaningful. Because a typical single machine is unable to deal with such large-scale language resources efficiently, we implemented the algorithm on top of Apache Spark, which is a well-known distributed computing framework. As a user interface prototype, a web-based system is implemented that provides users with a list of relevant attractions when users are browsing exhibition information, available at http://bike.snu.ac.kr/WARP. We carried out a case study based on Korean Tourism Organization Linked Open Data with Korean Wikipedia as a language resource. Experimental results are demonstrated to show the efficiency and effectiveness of the proposed system. The effectiveness was evaluated against well-known exhibitions. It is expected that the proposed approach will contribute to the development of both exhibition and tourist industries by motivating exhibition visitors to become active tourists.

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A Study on Technical Elements for Vision Therapy based on VR HMD (VR HMD에서의 비전 테라피 활용을 위한 기술 요소 연구)

  • Choi, Sangmi;Kim, Jungho;Kwon, Soonchul;Lee, Seunghyun
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.12
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    • pp.161-168
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    • 2016
  • Thanks to mass production and provision of smartphones and the HMD (head mounted display), VR (virtual reality) is now being applied to various areas. The VR HMD is the interface equipment which allows users to have realistic experiences through human sensory organs such as vision and auditory sense. Since the majority of VR equipment is operated by the display for both eyes, 360-degree video content and the depth information, the VR mechanism is closely related to human senses, especially vision. Previous studies have focused on how to minimize negative impact such as motion sickness or visual fatigue. Little attention has been paid on research about the visual treatment. Therefore, the focus of this study is to develop technical elements for utilization of vision therapy with the VR HMD and explore possible areas to apply it. To this end, we analyzed the past case studies and technical elements to identify 16 areas for vision therapy. We also developed the optical parameters for utilization of the VR HMD visual targets. The result of this study is expected to be utilized for development of visual targets for vision therapy based on the VR HMD.

A Content-based Video Rate-control Algorithm Interfaced to Human-eye (인간과 결합한 내용기반 동영상 율제어)

  • 황재정;진경식;황치규
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.3C
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    • pp.307-314
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    • 2003
  • In the general multiple video object coder, more interested objects such as speaker or moving object is consistently coded with higher priority. Since the priority of each object may not be fixed in the whole sequence and be variable on frame basis, it must be adjusted in a frame. In this paper, we analyze the independent rate control algorithm and global algorithm that the QP value is controled by the static parameters, object importance or priority, target PSNR, weighted distortion. The priority among static parameters is analyzed and adjusted into dynamic parameters according to the visual interests or importance obtained by camera interface. Target PSNR and weighted distortion are proportionally derived by using magnitude, motion, and distortion. We apply those parameters for the weighted distortion control and the priority-based control resulting in the efficient bit-rate distribution. As results of this paper, we achieved that fewer bits are allocated for video objects which has less importance and more bits for those which has higher visual importance. The duration of stability in the visual quality is reduced to less than 15 frames of the coded sequence. In the aspect of PSNR, the proposed scheme shows higher quality of more than 2d13 against the conventional schemes. Thus the coding scheme interfaced to human- eye proves an efficient video coder dealing with the multiple number of video objects.

DENTIN PERMEABILITY CHANCE ACCORDING TO THE PROCESS OF COMPOMER RESTORATION (컴포머 충전과정에 따른 상아질 투과도의 변화)

  • Cho, Hye-Jin;Lee, Kyung-Ha;Lee, Se-Joon;Lee, Kwang-Won
    • Restorative Dentistry and Endodontics
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    • v.27 no.4
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    • pp.382-388
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    • 2002
  • Compomer is composed of matrix and filler : matrix is made of the combination of resins and polycarboxylic molecules that are light-cured, and a filler is a glass component which is capable of ion-release. The resin content of compomers produces polymerization shrinkage which can adversely affect marginal adaptation. Pretreatment is a fundamental step which is treated with conditioner or primer in the use of these materials. Microleakage of restorative materials has been investigated mostly by dye penetration method. Dye penetration method was not quantitative and not measured repeatedly. Fluid filtration method, introduced and developed by Pashley's group, has been extensively used for 20 years for research purpose to understand the physiology of dentin, as well as the effects of various restorative treatments on dentin permeability. It permits quantitative, nondestructive measurment of microleakage in a longitudinal manner. The purpose of this study was to evaluate the change of dentin permeability according to the process of compomer restoration. In this study. Cl V cavities were prepared on buccal surface of thirty extracted human molars. The prepared cavities were etched by 37% phosphoric acid. The experimental teeth were randomly divided into three groups. Each group was treated with following materials Group 1 : Prime & Bond NT/Dyract AP, Group2: Single Bond/F2000 compomer, Group 3 : Syntac Single Component/Compoglass. The bonding agent and compomer were applied for each group following manufacturers information. Dentin permeability of each group was measured at each process by fluid filtration method; Step 1 : preparation(smear layer). Step 2 : etching(smear layer removal), Step 3 : applying the bonding agent, Step 4 : filling the compomer. Dentin permeability was expressed by hydraulic conductance ($\mu\textrm{l}$ min$^{-1}$cm$H_2O$$^{-1}$). The data were analysed statistically using One-way ANOVA and Sheffe's method. The results were as follows : 1. Dentin permeability differences between each process were significant except between step 1 and step 2(p<0.01). 2. Dentin permeability after removal of smear layer was highly increased(p<0.01). 3. In most case, decrease of dentin permeability was obtained by applying bonding agent(p<0.01). 4. Dentin permeability differences among the experimental groups were not significant(p>0.05). 5. None of compomers used in this study showed perfect seal at the interface.

Multi-classifier Decision-level Fusion for Face Recognition (다중 분류기의 판정단계 융합에 의한 얼굴인식)

  • Yeom, Seok-Won
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.4
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    • pp.77-84
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    • 2012
  • Face classification has wide applications in intelligent video surveillance, content retrieval, robot vision, and human-machine interface. Pose and expression changes, and arbitrary illumination are typical problems for face recognition. When the face is captured at a distance, the image quality is often degraded by blurring and noise corruption. This paper investigates the efficacy of multi-classifier decision level fusion for face classification based on the photon-counting linear discriminant analysis with two different cost functions: Euclidean distance and negative normalized correlation. Decision level fusion comprises three stages: cost normalization, cost validation, and fusion rules. First, the costs are normalized into the uniform range and then, candidate costs are selected during validation. Three fusion rules are employed: minimum, average, and majority-voting rules. In the experiments, unfocusing and motion blurs are rendered to simulate the effects of the long distance environments. It will be shown that the decision-level fusion scheme provides better results than the single classifier.

The Audience Behavior-based Emotion Prediction Model for Personalized Service (고객 맞춤형 서비스를 위한 관객 행동 기반 감정예측모형)

  • Ryoo, Eun Chung;Ahn, Hyunchul;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.73-85
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    • 2013
  • Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.