• Title/Summary/Keyword: Logical Data Model

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A Model for evaluating the efficiency of inputting Hangul on a telephone keyboard (전화기 자판의 한글 입력 효율성 평가 모형)

  • Koo, Min-Mo;Lee, Mahn-Young
    • The KIPS Transactions:PartD
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    • v.8D no.3
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    • pp.295-304
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    • 2001
  • The standards of a telephone Hangul keyboard should be decided in terms of objective factors : the number of strokes and fingers’moving distance. A number of designers will agree on them, because these factors can be calculated in an objective manner. So, We developed the model which can evaluate the efficiency of inputting Hangul on a telephone keyboard in terms of two factors. As compared with other models, the major features of this model are as follows : in order to evaluate the efficiency of Hangul input on a telephone keyboard, (1) this model calculated not a typing time but the number of strokes ; (2) concurrence frequency that had been counted on KOREA-1 Corpus was used directly ; (3) a total set of 67 consonants and vowels was used ; and (4) this model could evaluate a number of keyboards that use a kind of syllabic function key-the complete key, the null key and the final consonant key and also calculate a lot of keyboards that adopt no syllabic function key. However, there are many other factors to judge the efficiency of inputting Hangul on a telephone keyboard. If we want to make more accurate estimate of a telephone Hangul keyboard, we must consider both logical data and experimental data as well.

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Development of a Simulation Model for Supply Chain Management of Precast Concrete (프리캐스트 콘크리트 공급사슬 관리를 위한 시뮬레이션 모형 개발)

  • Kwon, Hyeonju;Jeon, Sangwon;Lee, Jaeil;Jeong, Keunchae
    • Korean Journal of Construction Engineering and Management
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    • v.22 no.5
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    • pp.86-98
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    • 2021
  • In this study, we developed a simulation model for supply chain management of Precast Concrete (PC) based construction. To this end, information on the Factory Production/Site Construction system was collected through literature review and field research, and based on this information, a simulation model was defined by describing the supply chain, entities, resources, and processes. Next, using the Arena simulation software, a simulation model for the PC supply chain was developed by setting model frameworks, data modules, flowchart modules, and animation modules. Finally, verification and validation were performed using five review methodologies such as model check, animation check, extreme value test, average value test, and actual case test to the developed model. As a result, it was found that the model adequately represented the flows and characteristics of the PC supply chain without any logical errors and provided accurate performance evaluation values for the target supply chains. It is expected that the proposed simulation model will faithfully play a role as a performance evaluation platform in the future for developing management techniques in order to optimally operate the PC supply chain.

Mobile Context Based User Behavior Pattern Inference and Restaurant Recommendation Model (모바일 컨텍스트 기반 사용자 행동패턴 추론과 음식점 추천 모델)

  • Ahn, Byung-Ik;Jung, Ku-Imm;Choi, Hae-Lim
    • Journal of Digital Contents Society
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    • v.18 no.3
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    • pp.535-542
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    • 2017
  • The ubiquitous computing made it happen to easily take cognizance of context, which includes user's location, status, behavior patterns and surrounding places. And it allows providing the catered service, designed to improve the quality and the interaction between the provider and its customers. The personalized recommendation service needs to obtain logical reasoning to interpret the context information based on user's interests. We researched a model that connects to the practical value to users for their daily life; information about restaurants, based on several mobile contexts that conveys the weather, time, day and location information. We also have made various approaches including the accurate rating data review, the equation of Naïve Bayes to infer user's behavior-patterns, and the recommendable places pre-selected by preference predictive algorithm. This paper joins a vibrant conversation to demonstrate the excellence of this approach that may prevail other previous rating method systems.

Comparative Analysis of Cultivation Region of Angelica gigas Using a GC-MS-Based Metabolomics Approach (GC-MS 기반 대사체학 기술을 응용한 참당귀의 산지비교분석)

  • Jiang, Guibao;Leem, Jae Yoon
    • Korean Journal of Medicinal Crop Science
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    • v.24 no.2
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    • pp.93-100
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    • 2016
  • Background: A set of logical criteria that can accurately identify and verify the cultivation region of raw materials is a critical tool for the scientific management of traditional herbal medicine. Methods and Results: Volatile compounds were obtained from 19 and 32 samples of Angelica gigas Nakai cultivated in Korea and China, respectively, by using steam distillation extraction. The metabolites were identified using GC/MS by querying against the NIST reference library. Data binning was performed to normalize the number of variables used in statistical analysis. Multivariate statistical analyses, such as Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) were performed using the SIMCA-P software. Significant variables with a Variable Importance in the Projection (VIP) score higher than 1.0 as obtained through OPLS-DA and those that resulted in p-values less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Among the 19 variables extracted, styrene, ${\alpha}$-pinene, and ${\beta}$-terpinene were selected as markers to indicate the origin of A. gigas. Conclusions: The statistical model developed was suitable for determination of the geographical origin of A. gigas. The cultivation regions of six Korean and eight Chinese A. gigas. samples were predicted using the established OPLS-DA model and it was confirmed that 13 of the 14 samples were accurately classified.

The Proposal for the Model of Users' Addictions in Social Gaming

  • Anuar, Tengku Fauzan Tengku;Song, Seung Keun
    • Cartoon and Animation Studies
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    • s.40
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    • pp.337-365
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    • 2015
  • The objective of this study proposes the new user's addiction model in 'Social Network Games' (SNGs). Research model is derived from the separation of two characteristics. First one is logical characteristics that includes 'Functional' (F), 'Keystroke' (K), and 'Goal' (G). Second one is feeling characteristics that consists a few factors such as 'Emotion' (E), 'Social' (S), and 'Affection' (A). For the pre-test, a total of 30 participants responded to survey in order to inspect the fitness of research questionnaire, roughly validity of the proposed model, and the direction of this reseach. After that for the main test, a total 300 users participated in this research. The final number of effective participants were 261 because 39 were insincere respondents and without playing SNGs who were excluded. Then we examined the measurement model by performing 'Partial Least Squares - Structural Equation Modeling' (PLS-SEM) analysis to test the research hypothesis empirically. The results of the measurement and structural model test lend support to the proposed research model by providing a good fit to the construct data. Interestingly, the model showed the significant effects of the interaction between eleven hypothesis(H1,H2,H3,H4,H5,H6,H7,H8,H9,H10, H12). Only one hypothesis decision t-value not supported that is involved the relationship between SNGs Addiction and Keystroke, H11(1.193). This research expect to contributes to an exploratory SNGs research to clarify the base of addition and will aids understanding of users' behavior associated with SNGs development.

A Comprehensive Model of Purchasing Intention of Customers in Agricultural Products Online Shopping Malls (농산물 온라인 쇼핑몰에서의 고객의 구매의도에 관한 포괄적 모형)

  • Lim, Dongsup;Yoon, Cheolho
    • Information Systems Review
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    • v.17 no.3
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    • pp.159-181
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    • 2015
  • This study proposes a comprehensive model of purchasing intention of customers in agricultural products online shopping malls. In this study, we derived the factors through the literature reviews and logical reasoning and classified the factors as a business point of view, an information systems point of view and an agricultural characteristics point of view, and developed the integrated research model which is the factors affect purchase intentions by mediating trust and the perceived usefulness. A total of 329 samples of a valid survey data from the members of small agricultural online shopping malls were collected and the research model was empirically analyzed by a confirmatory factor analysis and path analyses using structural equation modeling with the data. The results show that the product quality and the service quality of the business point of view have effects on the trust, however the price adequacy and entertainment have no effect on the trust and the perceived usefulness respectively, also the advertising exposure has no effect on the trust but it has an effect on the purchase intention directly. The information quality and the ease of use of the information systems point of view have an effect on the trust and perceived usefulness. At last, the seasonal product of the agricultural characteristics point of view has effects on perceived usefulness but the regional brand has no effect on the trust. The results of this study provide strategic implications for successful development and operation of agricultural products online shopping malls.

Design of A Database Architecture for Hierarchical Security Policy Model (계층적 구조 보안 정책 모델을위한 데이터 베이스 구조 설계)

  • Yun, Yeo-Wung;Hwang, Yoon-Cheol;Um, Nam-Kyeong;Kim, Kwun-Woo;Lee, Sang-Ho
    • The KIPS Transactions:PartC
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    • v.8C no.6
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    • pp.711-720
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    • 2001
  • An enlarging a scale of logical domain organizing Internet, security policy association among entities become complicated. Establishment and control of security policies for each system is a hard problem to solve because of the environment and composite factors with variable properties. In this paper, to solve this actual problems, we orgainze a hierarchical structure of network and than we design the structure of database to apply security policies for secure communication. This enables efficient management of security data and association of security policy by using designed data structure between different domain in hierarchical structure with make secure communication possible.

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Livestock Telemedicine System Prediction Model for Human Healthy Life (인간의 건강한 삶을 위한 가축원격 진료 예측 모델)

  • Kang, Yun-Jeong;Lee, Kwang-Jae;Choi, Dong-Oun
    • Journal of Korea Entertainment Industry Association
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    • v.13 no.8
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    • pp.335-343
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    • 2019
  • Healthy living is an essential element of human happiness. Quality eating provides the basis for life, and the health of livestock, which provides meat and dairy products, has a direct impact on human health. In the case of calves, diarrhea is the cause of all diseases.In this paper, we use a sensor to measure calf 's biometric data to diagnose calf diarrhea. The collected biometric data is subjected to a preprocessing process for use as meaningful information. We measure calf birth history and calf biometrics. The ontology is constructed by inputting environmental information of housing and biochemistry, immunity, and measurement information of human body for disease management. We will build a knowledge base for predicting calf diarrhea by predicting calf diarrhea through logical reasoning. Predict diarrhea with the knowledge base on the name of the disease, cause, timing and symptoms of livestock diseases. These knowledge bases can be expressed as domain ontologies for parent ontology and prediction, and as a result, treatment and prevention methods can be suggested.

A Study on CPPS Architecture integrated with Centralized OPC UA Server (중앙 집중식 OPC UA 서버와 통합 된 CPPS 아키텍처에 관한 연구)

  • Jo, Guejong;Jang, Su-Hwan;Jeong, Jongpil
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.3
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    • pp.73-82
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    • 2019
  • In order to build a smart factory, building a CPPS (Cyber Physical Product System) is an important system that must be accompanied. Through the CPPS, it is the reality of smart factories to move physical factories to a digital-based cyber world and to intelligently and autonomously monitor and control them. But The existing CPPS architectures present only an abstract modeling architecture, and the research that applied the OPC UA Framework (Open Platform Communication Unified Architecture), an international standard for data exchange in the smart factory, as the basic system of CPPS It was insufficient. Therefore, it is possible to implement CPPS that can include both cloud and IoT by collecting field data distributed by CPPS architecture applicable to actual factories and concentrating data processing in a centralized In this study, we implemented CPPS architecture through central OPC UA Server based on OPC UA conforming to central processing OPC UA Framework, and how CPPS logical process and data processing process are automatically generated through OPC UA modeling processing We have proposed the CPPS architecture including the model factory and implemented the model factory to study its performance and usability.

Prediction of Ground Subsidence Hazard Area Using GIS and Probability Model near Abandoned Underground Coal Mine (GIS 및 확률모델을 이용한 폐탄광 지역의 지반침하 위험 예측)

  • Choi, Jong-Kuk;Kim, Ki-Dong;Lee, Sa-Ro;Kim, Il-Soo;Won, Joong-Sun
    • Economic and Environmental Geology
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    • v.40 no.3 s.184
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    • pp.295-306
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    • 2007
  • In this study, we predicted areas vulnerable to ground subsidence near abandoned underground coal mine at Sam-cheok City in Korea using a probability (frequency ratio) model with Geographic Information System (GIS). To extract the factors related to ground subsidence, a spatial database was constructed from a topographical map, geo-logical map, mining tunnel map, land characteristic map, and borehole data on the study area including subsidence sites surveyed in 2000. Eight major factors were extracted from the spatial analysis and the probability analysis of the surveyed ground subsidence sites. We have calculated the decision coefficient ($R^2$) to find out the relationship between eight factors and the occurrence of ground subsidence. The frequency ratio model was applied to deter-mine each factor's relative rating, then the ratings were overlaid for ground subsidence hazard mapping. The ground subsidence hazard map was then verified and compared with the surveyed ground subsidence sites. The results of verification showed high accuracy of 96.05% between the predicted hazard map and the actual ground subsidence sites. Therefore, the quantitative analysis of ground subsidence near abandoned underground coal mine would be possible with a frequency ratio model and a GIS.