• Title/Summary/Keyword: information user studies

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Development and User Study on Visualization Tools of Origin-Destination Data for Social Problems (Origin-Destination 기반 시각화 도구의 개발 및 사회 문제 해결을 위한 사용자 연구)

  • Changki Kim;Sungjin Hwang;Hansung Kim;Sugie Lee;Jaehyuk Cha;Kwanguk (Kenny) Kim
    • Journal of the Korea Computer Graphics Society
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    • v.30 no.3
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    • pp.9-22
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    • 2024
  • Mobility data is important to understand social phenomena and problem. Previous studies have utilized Origin-Destination (OD) visualization methods to represent human's mobility. However, the effectiveness of visualization tools as a method for understanding social phenomena remains unexplored. Therefore, in this study, we developed a visualization tool called SeoulOD-Vis to facilitate understanding social issues. It included three different modules: map visualization, condition selection, and detailed information presentation. We recruited 28 participants to evaluate the SeoulOD-Vis and compared it with a publicly available visualization tool. The results suggested that the SeoulOD-Vis had higher usability and problem-solving performances. Interview results suggested that it attributed to its 'condition selection' and 'detailed information presentation' modules. Our results will contribute to develop visualization tools to solve social problems using mobility data.

A Hybrid Recommender System based on Collaborative Filtering with Selective Use of Overall and Multicriteria Ratings (종합 평점과 다기준 평점을 선택적으로 활용하는 협업필터링 기반 하이브리드 추천 시스템)

  • Ku, Min Jung;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.85-109
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    • 2018
  • Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

Development of Information Extraction System from Multi Source Unstructured Documents for Knowledge Base Expansion (지식베이스 확장을 위한 멀티소스 비정형 문서에서의 정보 추출 시스템의 개발)

  • Choi, Hyunseung;Kim, Mintae;Kim, Wooju;Shin, Dongwook;Lee, Yong Hun
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.111-136
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    • 2018
  • In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

Recent Progress in Air-Conditioning and Refrigeration Research : A Review of Papers Published in the Korean Journal of Air-Conditioning and Refrigeration Engineering in 2015 (설비공학회 분야의 최근 연구 동향 : 2015년 학회지 논문에 대한 종합적 고찰)

  • Lee, Dae-Young;Kim, Sa Ryang;Kim, Hyun-Jung;Kim, Dong-Seon;Park, Jun-Seok;Ihm, Pyeong Chan
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.28 no.6
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    • pp.256-268
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    • 2016
  • This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2015. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) The research works on the thermal and fluid engineering were carried out in the areas of flow, heat and mass transfer, cooling and heating, and air-conditioning, the renewable energy system and the flow inside building rooms. Research issues dealing with air-conditioning machines and fire and exhausting smoke were reduced. CFD seems to be spreading to more research areas. (2) Research works on heat transfer area were carried out in the categories of heat transfer characteristics, pool boiling and condensing heat transfer and industrial heat exchangers. Researches on heat transfer characteristics included the economic analysis of GHG emission, micro channel heat exchanger, effect of rib angle on thermal performance, the airside performance of fin-and-tube heat exchangers, theoretical analysis of a rotary heat exchanger, heat exchanger in a cryogenic environment, the performance of a cross-flow-type, indirect evaporative cooler made of paper/plastic film. In the area of pool boiling and condensing, the bubble jet loop heat pipe was studied. In the area of industrial heat exchangers, researches were performed on fin-tube heat exchanger, KSTAR PFC and vacuum vessel at baking phase, the performance of small-sized dehumidification rotor, design of gas-injection port of an asymmetric scroll compressor, effect of slot discharge-angle change on exhaust efficiency of range hood system with air curtain. (3) In the field of refrigeration, various studies were carried in the categories of refrigeration cycle, alternative refrigeration/energy system, system control. In the refrigeration cycle category, a cold-climate heat pump system, $CO_2$ cascade systems, ejector cycles and a PCM-based continuous heating system were investigated. In the alternative refrigeration/energy system category, a polymer adsorption heat pump, an alcohol absorption heat pump and a desiccant-based hybrid refrigeration system were investigated. In the system control category, turbo-refrigerator capacity controls and an absorption chiller fault diagnostics were investigated. (4) In building mechanical system research fields, eighteen studies were reported for achieving effective design of the mechanical systems, and also for maximizing the energy efficiency of buildings. The topics of the studies included energy performance, HVAC system, ventilation, and renewable energies, piping in the buildings. Proposed designs, performance tests using numerical methods and experiments provide useful information and key data which can improve the energy efficiency of the buildings. (5) The field of architectural environment was mostly focused on indoor environment and building energy. The main researches of indoor environment were related to the user and location awareness technology applied dimming lighting control system, the lighting performance evaluation for light-shelves, the improvement evaluation of air quality through analysis of ventilation efficiency and the evaluation of airtightness of sliding and LS window systems. The subjects of building energy were worked on the energy saving estimation of existing buildings, the developing model to predict heating energy usage in domestic city area and the performance evaluation of cooling applied with economizer control. The studies were also performed related to the experimental measurement of weight variation and thermal conductivity in polyurethane foam, the development of flame spread prevention system for sandwich panels, the utilization of heat from waste-incineration facility in large-scale horticultural facilities.

Natural Language Processing Model for Data Visualization Interaction in Chatbot Environment (챗봇 환경에서 데이터 시각화 인터랙션을 위한 자연어처리 모델)

  • Oh, Sang Heon;Hur, Su Jin;Kim, Sung-Hee
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.11
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    • pp.281-290
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    • 2020
  • With the spread of smartphones, services that want to use personalized data are increasing. In particular, healthcare-related services deal with a variety of data, and data visualization techniques are used to effectively show this. As data visualization techniques are used, interactions in visualization are also naturally emphasized. In the PC environment, since the interaction for data visualization is performed with a mouse, various filtering for data is provided. On the other hand, in the case of interaction in a mobile environment, the screen size is small and it is difficult to recognize whether or not the interaction is possible, so that only limited visualization provided by the app can be provided through a button touch method. In order to overcome the limitation of interaction in such a mobile environment, we intend to enable data visualization interactions through conversations with chatbots so that users can check individual data through various visualizations. To do this, it is necessary to convert the user's query into a query and retrieve the result data through the converted query in the database that is storing data periodically. There are many studies currently being done to convert natural language into queries, but research on converting user queries into queries based on visualization has not been done yet. Therefore, in this paper, we will focus on query generation in a situation where a data visualization technique has been determined in advance. Supported interactions are filtering on task x-axis values and comparison between two groups. The test scenario utilized data on the number of steps, and filtering for the x-axis period was shown as a bar graph, and a comparison between the two groups was shown as a line graph. In order to develop a natural language processing model that can receive requested information through visualization, about 15,800 training data were collected through a survey of 1,000 people. As a result of algorithm development and performance evaluation, about 89% accuracy in classification model and 99% accuracy in query generation model was obtained.

Analysis of Internet Biology Study Sites and Guidelines for Constructing Educational Homepages (인터넷상의 고등학교 생물 학습사이트 비교분석 및 웹사이트 구축방안에 관한 연구)

  • Kim, Joo-Hyun;Sung, Jung-Hee
    • Journal of The Korean Association For Science Education
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    • v.22 no.4
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    • pp.779-795
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    • 2002
  • Internet, a world wide network of computers, is considered as a sea of information because it allows people to share information beyond the barriors of time and space. However, in spite of the unmeasurable potential applications of the internet, its use in the field of biology education has been extremely limited mainly due to the scarcity of good biology-related sites. In order to provide useful guidelines for constructing user-friendly study sites, which can help high school students with different intellectual levels to study biology, comparative studies were performed on selected educational sites. Initially, hundreds of related sites were examined, and, subsequently, four distinct sites were selected not only because they are well organized, but also because each is unique in its contents. Also, a survey was carried out against the users of each site. The survey results indicated that the high school students regard the web-based biology study tools as effective teaching methods although there might be some bias in criteria for selecting target sites. In addition to the detailed biology topics and the related biology informations, multimedia data including pictures, animations and movies are found to be one of the important ingredients for desirable biology study sites. Thus, the inclusion of multimedia components should also be considered when developing a systematic biology study site. Overall, the role of the cyber space is expected to become more and more important. Since the development of the user-satisfied and self-guided sites require interdisciplinary collaborational efforts which should be made to promote extensive communication among teachers, education professionals, and computer engineers. Furthermore, the introduction of good biology study sites to the students by their teachers is also important factor for the successful web-based education.

The Construction of QoS Integration Platform for Real-time Negotiation and Adaptation Stream Service in Distributed Object Computing Environments (분산 객체 컴퓨팅 환경에서 실시간 협약 및 적응 스트림 서비스를 위한 QoS 통합 플랫폼의 구축)

  • Jun, Byung-Taek;Kim, Myung-Hee;Joo, Su-Chong
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.11S
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    • pp.3651-3667
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    • 2000
  • Recently, in the distributed multimedia environments based on internet, as radical growing technologies, the most of researchers focus on both streaming technology and distributed object thchnology, Specially, the studies which are tried to integrate the streaming services on the distributed object technology have been progressing. These technologies are applied to various stream service mamgements and protocols. However, the stream service management mexlels which are being proposed by the existing researches are insufficient for suporting the QoS of stream services. Besides, the existing models have the problems that cannot support the extensibility and the reusability, when the QoS-reiatedfunctions are being developed as a sub-module which is suited on the specific-purpose application services. For solving these problems, in this paper. we suggested a QoS Integrated platform which can extend and reuse using the distributed object technologies, and guarantee the QoS of the stream services. A structure of platform we suggested consists of three components such as User Control Module(UCM), QoS Management Module(QoSM) and Stream Object. Stream Object has Send/Receive operations for transmitting the RTP packets over TCP/IP. User Control ModuleI(UCM) controls Stream Objects via the COREA service objects. QoS Management Modulel(QoSM) has the functions which maintain the QoS of stream service between the UCMs in client and server. As QoS control methexlologies, procedures of resource monitoring, negotiation, and resource adaptation are executed via the interactions among these comiXments mentioned above. For constmcting this QoS integrated platform, we first implemented the modules mentioned above independently, and then, used IDL for defining interfaces among these mexlules so that can support platform independence, interoperability and portability base on COREA. This platform is constructed using OrbixWeb 3.1c following CORBA specification on Solaris 2.5/2.7, Java language, Java, Java Media Framework API 2.0, Mini-SQL1.0.16 and multimedia equipments. As results for verifying this platform functionally, we showed executing results of each module we mentioned above, and a numerical data obtained from QoS control procedures on client and server's GUI, while stream service is executing on our platform.

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Perception and Appraisal of Urban Park Users Using Text Mining of Google Maps Review - Cases of Seoul Forest, Boramae Park, Olympic Park - (구글맵리뷰 텍스트마이닝을 활용한 공원 이용자의 인식 및 평가 - 서울숲, 보라매공원, 올림픽공원을 대상으로 -)

  • Lee, Ju-Kyung;Son, Yong-Hoon
    • Journal of the Korean Institute of Landscape Architecture
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    • v.49 no.4
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    • pp.15-29
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    • 2021
  • The study aims to grasp the perception and appraisal of urban park users through text analysis. This study used Google review data provided by Google Maps. Google Maps Review is an online review platform that provides information evaluating locations through social media and provides an understanding of locations from the perspective of general reviewers and regional guides who are registered as members of Google Maps. The study determined if the Google Maps Reviews were useful for extracting meaningful information about the user perceptions and appraisals for parks management plans. The study chose three urban parks in Seoul, South Korea; Seoul Forest, Boramae Park, and Olympic Park. Review data for each of these three parks were collected via web crawling using Python. Through text analysis, the keywords and network structure characteristics for each park were analyzed. The text was analyzed, as were park ratings, and the analysis compared the reviews of residents and foreign tourists. The common keywords found in the review comments for the three parks were "walking", "bicycle", "rest" and "picnic" for activities, "family", "child" and "dogs" for accompanying types, and "playground" and "walking trail" for park facilities. Looking at the characteristics of each park, Seoul Forest shows many outdoor activities based on nature, while the lack of parking spaces and congestion on weekends negatively impacted users. Boramae Park has the appearance of a city park, with various facilities providing numerous activities, but reviewers often cited the park's complexity and the negative aspects in terms of dog walking groups. At Olympic Park, large-scale complex facilities and cultural events were frequently mentioned, emphasizing its entertainment functions. Google Maps Review can function as useful data to identify parks' overall users' experiences and general feelings. Compared to data from other social media sites, Google Maps Review's data provides ratings and understanding factors, including user satisfaction and dissatisfaction.

An Empirical Study on the Importance of Psychological Contract Commitment in Information Systems Outsourcing (정보시스템 아웃소싱에서 심리적 계약 커미트먼트의 중요성에 대한 연구)

  • Kim, Hyung-Jin;Lee, Sang-Hoon;Lee, Ho-Geun
    • Asia pacific journal of information systems
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    • v.17 no.2
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    • pp.49-81
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    • 2007
  • Research in the IS (Information Systems) outsourcing has focused on the importance of legal contracts and partnerships between vendors and clients. Without detailed legal contracts, there is no guarantee that an outsourcing vendor would not indulge in self-serving behavior. In addition, partnerships can supplement legal contracts in managing the relationship between clients and vendors legal contracts by itself cannot deal with all the complexity and ambiguity involved with IS outsourcing relationships. In this paper, we introduce a psychological contract (between client and vendor) as an important variable for IS outsourcing success. A psychological contract refers to individual's mental beliefs about his or her mutual obligations in a contractual relationship (Rousseau, 1995). A psychological contract emerges when one party believes that a promise of future returns has been made, a contribution has been given, and thus, an obligation has been created to provide future benefits (Rousseau, 1989). An employmentpsychological contract, which is a widespread concept in psychology, refers to employer and employee expectations of the employment relationship, i.e. mutual obligations, values, expectations and aspirations that operate over and above the formal contract of employment (Smithson and Lewis, 2003). Similar to the psychological contract between an employer and employee, IS outsourcing involves a contract and a set of mutual obligations between client and vendor (Ho et al., 2003). Given the lack of prior research on psychological contracts in the IS outsourcing context, we extend such studies and give insights through investigating the role of psychological contracts between client and vendor. Psychological contract theory offers highly relevant and sound theoretical lens for studying IS outsourcing management because of its six distinctive principles: (1) it focuses on mutual (rather than one-sided) obligations between contractual parties, (2) it's more comprehensive than the concept of legal contract, (3) it's an individual-level construct, (4) it changes over time, (5) it affects organizational behaviors, and (6) it's susceptible to organizational factors (Koh et al., 2004; Rousseau, 1996; Coyle-Shapiro, 2000). The aim of this paper is to put the concept, psychological contract commitment (PCC), under the spotlight, by finding out its mediating effects between legal contracts/partnerships and IS outsourcing success. Our interest is in the psychological contract commitment (PCC) or commitment to psychological contracts, which is the extent to which a partner consistently and deeply concerns with what the counter-party believes as obligations during the IS project. The basic premise for the hypothesized relationship between PCC and success is that for outsourcing success, client and vendor should continually commit to mutual obligations in which both parties believe, rather than to only explicit obligations. The psychological contract commitment playsa pivotal role in evaluating a counter-party because it reflects what one party really expects from the other. If one party consistently shows high commitment to psychological contracts, the other party would evaluate it positively. This will increase positive reciprocation efforts of the other party, thus leading to successful outsourcing outcomes (McNeeley and Meglino, 1994). We have used matched sample data for this research. We have collected three responses from each set of a client and a vendor firm: a project manager of the client firm, a project member from the vendor firm with whom the project manager cooperated, and an end-user of the client company who actually used the outsourced information systems. Special caution was given to the data collection process to avoid any bias in responses. We first sent three types of questionnaires (A, Band C) to each project manager of the client firm, asking him/her to answer the first type of questionnaires (A).

A Study on People Counting in Public Metro Service using Hybrid CNN-LSTM Algorithm (Hybrid CNN-LSTM 알고리즘을 활용한 도시철도 내 피플 카운팅 연구)

  • Choi, Ji-Hye;Kim, Min-Seung;Lee, Chan-Ho;Choi, Jung-Hwan;Lee, Jeong-Hee;Sung, Tae-Eung
    • Journal of Intelligence and Information Systems
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    • v.26 no.2
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    • pp.131-145
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    • 2020
  • In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.