• Title/Summary/Keyword: Context-Aware Model

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Design and Implementation of the Memory Management Module of a Vehicle Black Box (차량용 블랙박스의 메모리 관리 모듈 설계 및 구현)

  • Park, Ji-Sang;Jeon, Min-Ho;Lee, Myung-Eui
    • Journal of Advanced Navigation Technology
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    • v.18 no.3
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    • pp.209-214
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    • 2014
  • Current black boxes have a problem of storing unnecessary imagery data recordings without data classification. For this reason, users have to erase videos every time. This method is inadequate for black boxes with limited memory capacity. In this paper, we design and implement a system that recognizes traffic accident situations and saves these recordings by classifying them according to weighted values. The system was made to save video recorded at a 30-sec interval of every event to black box folders by changing names based on weighted value data under the external environment in a 1:10 scale model car. Based on this, when the tests were performed as a major car accident while driving, the videos were created in w2 folder, and when the tests were performed as a minor car accident while stopped, the videos were created in w1 folder.

A Distance Estimation Scheme Based on WLAN RF Properties for Localization of Mobile Terminals (WLAN 전파특성 기반 실내 위치설정을 위한 이동단말의 거리추정 기법)

  • Yang, Jeong-Woo;An, Gae-Il;Kim, Shin-Hyo;Chung, Byung-Ho;Kim, Tae-Yeon;Pyun, Ki-Hyun;Cho, Gi-Hwan
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39B no.7
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    • pp.449-458
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    • 2014
  • In the context-aware services, localization is an important technical element. Due to the easy to use and low cost, it was widely enabled with RF properties such as RSSI. However, RSSI is known to be not appropriated for indoor localization, because it tends to show big variance in time and is greatly effected with the multipath. This paper proposes a distance estimation process and its constituted methods for indoor localization, by making use of the other WLAN's RF property, CSI(Channel State Information). Firstly we define a comprehensive localization process, and suggest a calibration algorithm of environment factors in the path loss propagation model. Then, by implementing them with a commercial WLAN module, an the proposed process and methods are evaluated in terms of usefulness.

LSTM-based IPTV Content Recommendation using Watching Time Information (시청 시간대 정보를 활용한 LSTM 기반 IPTV 콘텐츠 추천)

  • Pyo, Shinjee;Jeong, Jin-Hwan;Song, Injun
    • Journal of Broadcast Engineering
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    • v.24 no.6
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    • pp.1013-1023
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    • 2019
  • In content consumption environment with various live TV channels, VoD contents and web contents, recommendation service is now a necessity, not an option. Currently, various kinds of recommendation services are provided in the OTT service or the IPTV service, such as recommending popular contents or recommending related contents which similar to the content watched by the user. However, in the case of a content viewing environment through TV or IPTV which shares one TV and a TV set-top box, it is difficult to recommend proper content to a specific user because one or more usage histories are accumulated in one subscription information. To solve this problem, this paper interprets the concept of family as {user, time}, extends the existing recommendation relationship defined as {user, content} to {user, time, content} and proposes a method based on deep learning algorithm. Through the proposed method, we evaluate the recommendation performance qualitatively and quantitatively, and verify that our proposed model is improved in recommendation accuracy compared with the conventional method.

Enhancing Empathic Reasoning of Large Language Models Based on Psychotherapy Models for AI-assisted Social Support (인공지능 기반 사회적 지지를 위한 대형언어모형의 공감적 추론 향상: 심리치료 모형을 중심으로)

  • Yoon Kyung Lee;Inju Lee;Minjung Shin;Seoyeon Bae;Sowon Hahn
    • Korean Journal of Cognitive Science
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    • v.35 no.1
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    • pp.23-48
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    • 2024
  • Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches-Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)-each leading to different patterns of interpreting clients' mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model's different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI.

Realtime Video Visualization based on 3D GIS (3차원 GIS 기반 실시간 비디오 시각화 기술)

  • Yoon, Chang-Rak;Kim, Hak-Cheol;Kim, Kyung-Ok;Hwang, Chi-Jung
    • Journal of Korea Spatial Information System Society
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    • v.11 no.1
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    • pp.63-70
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    • 2009
  • 3D GIS(Geographic Information System) processes, analyzes and presents various real-world 3D phenomena by building 3D spatial information of real-world terrain, facilities, etc., and working with visualization technique such as VR(Virtual Reality). It can be applied to such areas as urban management system, traffic information system, environment management system, disaster management system, ocean management system, etc,. In this paper, we propose video visualization technology based on 3D geographic information to provide effectively real-time information in 3D geographic information system and also present methods for establishing 3D building information data. The proposed video visualization system can provide real-time video information based on 3D geographic information by projecting real-time video stream from network video camera onto 3D geographic objects and applying texture-mapping of video frames onto terrain, facilities, etc.. In this paper, we developed sem i-automatic DBM(Digital Building Model) building technique using both aerial im age and LiDAR data for 3D Projective Texture Mapping. 3D geographic information system currently provide static visualization information and the proposed method can replace previous static visualization information with real video information. The proposed method can be used in location-based decision-making system by providing real-time visualization information, and moreover, it can be used to provide intelligent context-aware service based on geographic information.

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A study on the Application of Optimal Evacuation Route through Evacuation Simulation System in Case of Fire (화재발생 시 대피시뮬레이션 시스템을 통한 최적대피경로 적용에 관한 연구)

  • Kim, Daeill;Jeong, Juahn;Park, Sungchan;Go, Jooyeon;Yeom, Chunho
    • Journal of the Society of Disaster Information
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    • v.16 no.1
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    • pp.96-110
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    • 2020
  • Recently, due to global warming, it is easily exposed to various disasters such as fire, flood, and earthquake. In particular, large-scale disasters have continuously been occurring in crowded areas such as traditional markets, facilities for the elderly and children, and public facilities where various people stay. Purpose: This study aims to detect a fire occurred in crowded facilities early in the event to analyze and provide an optimal evacuation route using big data and advanced technology. Method: The researchers propose a new algorithm through context-aware 3D object model technology and A* algorithm optimization and propose a scenario-based optimal evacuation route selection technique. Result: Using the HPA* E algorithm, the evacuation simulation in the event of a fire was reproduced as a 3D model and the optimal evacuation route and evacuation time were calculated for each scenario. Conclusion: It is expected to reduce fatalities and injuries through the evacuation induction technique that enables evacuation of the building in the shortest path by analyzing in real-time via fire detection sensors that detects the temperature, flame, and smoke.

A Wireless Sensor Network Systems to Identify User and Detect Location Transition for Smart Home (지능형 주택을 위한 구성원 식별 및 위치 이동 감지 센서 네트워크 시스템)

  • Lee, Seon-Woo;Yang, Seung-Yong
    • Journal of KIISE:Information Networking
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    • v.37 no.5
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    • pp.396-402
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    • 2010
  • The tracking of current location of residents is an essential requirement for context-aware service of smart houses. This paper presents a wireless sensor network system which could detect location transition such as entrance and exit to a room and also identify the user who passed the room, without duty of wearing any sort of tag. We designed new sensor node to solve the problem of short operation lifetime of previous work[1] which has two pyroelectric infrared (PIR) sensors and an ultrasonic sensor, as well as a 2.4 GHz radio frequency wireless transceiver. The proposed user identification method is to discriminate a person based on his/her height by using an ultrasonic sensor. The detection idea of entering/exiting behavior is based on order of triggering of two PIR sensors. The topology of the developed wireless sensor network system is simple star structure in which each sensor node is connected to one sink node directly. We evaluated the proposed sensing system with a set of experiments for three subjects in a model house. The experimental result shows that the averaged recognition rate of user identification is 81.3% for three persons. and perfect entering/exiting behavior detection performance.

Analysis of the Achievements of Daegu Happiness Competency Education with a Focus on Curriculum (대구행복역량교육의 성과 분석: 교육과정 편성·운영을 중심으로)

  • Park, Chanho;Chung, Il-Hwan
    • Korean Journal of Comparative Education
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    • v.28 no.4
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    • pp.221-248
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    • 2018
  • The purpose of this study was to analyze the performance of the Daegu Happiness Competency Education Program. It was confirmed that students, parents, teachers, and education professions are aware of the middle and higher level of education for happiness in Daegu in terms of the formation and operation of the curriculum. There is no significant difference between students and parents in terms of average value, and teachers' perception level is relatively high, which is understandable in that teachers are the subjects of the curriculum organization and operation. In addition, there was no statistically significant difference between the parents and the school level, but there were significant differences between students and teachers. In particular, students' and teachers' perceptions were lowered as the number of schools increased, unlike the predictions. They showed the lowest results in the special schools, autonomous schools and special schools. The reason for this is that Daegu Happiness Competency Education was implemented in 2014, and it was because there was little room to recognize and accept the new curriculum due to the burden of college entrance examination or employment. In the future, it will naturally improve as the education process is settled, but here we can find suggestions for the establishment of Daegu Happiness Competency Education.

Consumer Responses to Retailer's Location-based Mobile Shopping Service : Focusing on PAD Emotional State Model and Information Relevance (유통업체의 위치기반 모바일 쇼핑서비스 제공에 대한 소비자 반응 : PAD 감정모델과 정보의 상황관련성을 중심으로)

  • Lee, Hyun-Hwa;Moon, Hee-Kang
    • Journal of Distribution Research
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    • v.17 no.2
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    • pp.63-92
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    • 2012
  • This study investigated consumer intention to use a location-based mobile shopping service (LBMSS) that integrates cognitive and affective responses. Information relevancy was integrated into pleasure-arousal-dominance (PAD) emotional state model in the present study as a conceptual framework. The results of an online survey of 335 mobile phone users in the U.S. indicated the positive effects of arousal and information relevancy on pleasure. In addition, there was a significant relationship between pleasure and intention to use a LBMSS. However, the relationship between dominance and pleasure was not statistically significant. The results of the present study provides insight to retailers and marketers as to what factors they need to consider to implement location-based mobile shopping services to improve their business performance. Extended Abstract : Location aware technology has expanded the marketer's reach by reducing space and time between a consumer's receipt of advertising and purchase, offering real-time information and coupons to consumers in purchasing situations (Dickenger and Kleijnen, 2008; Malhotra and Malhotra, 2009). LBMSS increases the relevancy of SMS marketing by linking advertisements to a user's location (Bamba and Barnes, 2007; Malhotra and Malhotra, 2009). This study investigated consumer intention to use a location-based mobile shopping service (LBMSS) that integrates cognitive and affective response. The purpose of the study was to examine the relationship among information relevancy and affective variables and their effects on intention to use LBMSS. Thus, information relevancy was integrated into pleasure-arousal-dominance (PAD) model and generated the following hypotheses. Hypothesis 1. There will be a positive influence of arousal concerning LBMSS on pleasure in regard to LBMSS. Hypothesis 2. There will be a positive influence of dominance in LBMSS on pleasure in regard to LBMSS. Hypothesis 3. There will be a positive influence of information relevancy on pleasure in regard to LBMSS. Hypothesis 4. There will be a positive influence of pleasure about LBMSS on intention to use LBMSS. E-mail invitations were sent out to a randomly selected sample of three thousand consumers who are older than 18 years old and mobile phone owners, acquired from an independent marketing research company. An online survey technique was employed utilizing Dillman's (2000) online survey method and follow-ups. A total of 335 valid responses were used for the data analysis in the present study. Before the respondents answer any of the questions, they were told to read a document describing LBMSS. The document included definitions and examples of LBMSS provided by various service providers. After that, they were exposed to a scenario describing the participant as taking a saturday shopping trip to a mall and then receiving a short message from the mall. The short message included new product information and coupons for same day use at participating stores. They then completed a questionnaire containing various questions. To assess arousal, dominance, and pleasure, we adapted and modified scales used in the previous studies in the context of location-based mobile shopping service, each of the five items from Mehrabian and Russell (1974). A total of 15 items were measured on a seven-point bipolar scale. To measure information relevancy, four items were borrowed from Mason et al. (1995). Intention to use LBMSS was captured using two items developed by Blackwell, and Miniard (1995) and one items developed by the authors. Data analyses were conducted using SPSS 19.0 and LISREL 8.72. A total of usable 335 data were obtained after deleting the incomplete responses, which results in a response rate of 11.20%. A little over half of the respondents were male (53.9%) and approximately 60% of respondents were married (57.4%). The mean age of the sample was 29.44 years with a range from 19 to 60 years. In terms of the ethnicity there were European Americans (54.5%), Hispanic American (5.3%), African-American (3.6%), and Asian American (2.9%), respectively. The respondents were highly educated; close to 62.5% of participants in the study reported holding a college degree or its equivalent and 14.5% of the participants had graduate degree. The sample represents all income categories: less than $24,999 (10.8%), $25,000-$49,999 (28.34%), $50,000-$74,999 (13.8%), and $75,000 or more (10.23%). The respondents of the study indicated that they were employed in many occupations. Responses came from all 42 states in the U.S. To identify the dimensions of research constructs, Exploratory Factor Analysis (EFA) using a varimax rotation was conducted. As indicated in table 1, these dimensions: arousal, dominance, relevancy, pleasure, and intention to use, suggested by the EFA, explained 82.29% of the total variance with factor loadings ranged from .74 to .89. As a next step, CFA was conducted to validate the dimensions that were identified from the exploratory factor analysis and to further refine the scale. Table 1 exhibits the results of measurement model analysis and revealed a chi-square of 202.13 with degree-of-freedom of 89 (p =.002), GFI of .93, AGFI = .89, CFI of .99, NFI of .98, which indicates of the evidence of a good model fit to the data (Bagozzi and Yi, 1998; Hair et al., 1998). As table 1 shows, reliability was estimated with Cronbach's alpha and composite reliability (CR) for all multi-item scales. All the values met evidence of satisfactory reliability in multi-item measure for alpha (>.91) and CR (>.80). In addition, we tested the convergent validity of the measure using average variance extracted (AVE) by following recommendations from Fornell and Larcker (1981). The AVE values for the model constructs ranged from .74 through .85, which are higher than the threshold suggested by Fornell and Larcker (1981). To examine discriminant validity of the measure, we again followed the recommendations from Fornell and Larcker (1981). The shared variances between constructs were smaller than the AVE of the research constructs and confirm discriminant validity of the measure. The causal model testing was conducted using LISREL 8.72 with a maximum-likelihood estimation method. Table 2 shows the results of the hypotheses testing. The results for the conceptual model revealed good overall fit for the proposed model. Chi-square was 342.00 (df = 92, p =.000), NFI was .97, NNFI was .97, GFI was .89, AGFI was .83, and RMSEA was .08. All paths in the proposed model received significant statistical support except H2. The paths from arousal to pleasure (H1: ${\ss}$=.70; t = 11.44), from information relevancy to intention to use (H3 ${\ss}$ =.12; t = 2.36), from information relevancy to pleasure (H4 ${\ss}$ =.15; t = 2.86), and pleasure to intention to use (H5: ${\ss}$=.54; t = 9.05) were significant. However, the path from dominance to pleasure was not supported. This study investigated consumer intention to use a location-based mobile shopping service (LBMSS) that integrates cognitive and affective responses. Information relevancy was integrated into pleasure-arousal-dominance (PAD) emotional state model as a conceptual framework. The results of the present study support previous studies indicating that emotional responses as well as cognitive responses have a strong impact on accepting new technology. The findings of this study suggest potential marketing strategies to mobile service developers and retailers who are considering the implementation of LBMSS. It would be rewarding to develop location-based mobile services that integrate information relevancy and which cause positive emotional responses.

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