• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.49-71
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• 2021

Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.

• 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.

• Korean Journal of Materials Research
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• v.1 no.3
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• pp.156-167
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• 1991

The purpose of this study is to develop a data base for material selection of turbofan engines, which is preferred in these days on many application due to their high performance with economical operation. Hundreds of Super Alloys have been developed by this time, each having special properties. Since it is very difficult task for a design engineer to select materials of adequate Properties for specific engine components, a good data bate is strongly desired to manage informations on various kinds of materials. However, no basic research is reported in this area so far in our country. The operating conditions such as temperature, pressure, rpm of spools are assumed to be provided by other mechanical studies. Creep rupture strength, corrosion resistance, yield strength, thermal expansion, melting point, etc., are considered as typical properties in this study to search a group of candidate materials. Formability, manufacturing or purchase cost can also be important variables to be considered. As a result of this study, a user-friendly computer program has been developed for input of new material information, interactive material selection, and output of selection results. Finally, discussion is presented from. the viewpoint of materials engineering. A method to evaluate the performance of the selected materials is also suggested.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.59-71
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• 2012

PKI-based public key scheme is outstanding in terms of authenticity and privacy. Nevertheless its application brings big burden due to the certificate/key management. It is difficult to apply it to limited computing devices in WSN because of its high encryption complexity. The Bilinear Pairing emerged from the original IBE to eliminate the certificate, is a future significant cryptosystem as based on the DDH(Decisional DH) algorithm which is significant in terms of computation and secure enough for authentication, as well as secure and faster. The practical EC Weil Pairing presents that its encryption algorithm is simple and it satisfies IND/NM security constraints against CCA. The Random Oracle Model based IBE PKG is appropriate to the structure of our target system with one secret file server in the operational perspective. Our work proposes modification of the Weil Pairing as proper to the closed network for secret file distribution[2]. First we proposed the improved one computing both encryption and message/user authentication as fast as O(DES) level, in which our scheme satisfies privacy, authenticity and integrity. Secondly as using the public key ID as effective as PKI, our improved IBE variant reduces the key exposure risk.

• Journal of Korean Academy of Nursing
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• v.25 no.4
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• pp.617-632
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• 1995

Nowadays, most big hospitals have a computer system to manage their administration. For maxi mum effectiveness in managing the computer system, an analysis of the variables affecting its implementation is necessary from the beginning. This study was done to analyze the variables influencing the operation of a hospital information system (HIS). The theoretical base for this study considered the combined effects of user expectations of computerization, and computer-anxiety. The relationship between variables in the theoretical base were analyzed and the individual characteristics influencing each variable were also analyzed. This study was done in two steps. First, 344 nurses were given an initial questionnaire developed to evaluate the reliability of the items. Based on the results, a second revised questionnaire was administered to 88 nurses who had been working in the areas where HIS was applied. The results of the first and second steps of the study are as follows 1. The initial study was done with nurses who were trained on the computer system briefly before HIS was implemented. The individual characteristics influencing computer anxiety and expectation regarding computer system usage in that initial study included, length of career, type of degree or certification, previous experiences with a computer, training on a computer, desire for computer training, and level of acceptance of a computerized work environment. But in the second study with nurses working in areas of the hospital where HIS was introduced, the work site was the only influencing characteristics. There-fore, in applying a computer system, overcoming work-environment barriers will be more import-ant than any individual characteristics. 2. The computer anxiety of the nurses in both groups, before and after the computer system ap-plication, was below the average level but the expectation of the effects of computerization was above average. The nurses using the computer program showed an above average level of satis-faction with the computer system itself, and with its effect on their efficiency. Therefore, the ability of nurses operating HIS will be positively. predictive. 3. For the variables included in the theoretical framework of the study, all of the correlational coefficients were statistically significant in the analysis of variation correlation. Therefore, the theoretical base of the study, "expectation in con junction with computer anxiety" can be considered an model which can be evaluated. Accord-ing to our analysis, the higher the level of nurses' motivation to use the computer system and the lower the anxiety about computer usage, the higher the possibility of computer system acceptance by nurses. The results of this study showed that in applying a computer system in the hospital, the main characteristic influencing acceptance was where the individual worked rather than personal characteristics such as length of career, type of degree or certification, and previous experiences with a computer. Therefore, it is suggested that the first step in uncovering and eliminating hindrance factors in ap-plication of a computer system should be an analysis of working conditions in relation to the functional content of the computer system. The suitability of the theoretical model based on the hypothesis ap-plied in this study should be further tested.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.11-20
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• 2018

The Q&A board is widely used as a means of communicating service enquiries, and the need for efficient management of the enquiry system has risen because certain questions are being repeatedly and frequently registered. This study aims to construct a student-centered FAQ, centered on the unstructured data posted on the university homepage's Q&A board. We extracted major keywords from 690 postings registered in the recent 3 years, and conducted the semantic network analysis to find the relationship between the keywords and the centrality analysis in order to carry out network visualization. The most central keywords found through the analysis, in order of centrality, were application, curriculum, credit point, completion, graduation, approval, period, major, portal, department. Also, the major keywords were classified into 8 groups of course, register, student life, scholarship, library, dormitory, IT and commute. If the most frequent questions are organized into these areas to form the FAQ, based on the results above, it is expected to contribute to user convenience and the efficiency of administration by simplifying the service enquiry process for repeated questions, as well as enabling smooth two-way communication among the members of the university.

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.55-68
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• 1999

Many ITS services require map databases in digital form to meet desired needs. Due to the dynamic nature of ITS and the sheer diversity of applications, the design and development of spatial databases to meet those needs pose a major challenge to both the public and private sectors. This challenge is further complicated by the necessity to transfer locationally referenced information between different kinds of databases and spatial data handling systems so that ITS products will work seamlessly across the region and nation. The Purpose of this paper is to develop the framework-models commonly to reference locations in the various applications and systems-the ITS Map Datum and LRS(Location Referencing System). The ITS Map Datum consists of the around control points which are the prime intersections (nodes) of the nationwide road network In this study, the major points have been determined along wish link-node modeling procedure. LRS, defined as a system for determining the position (location) of an entity relative to other entities or to some external frame of reference, has also been set up using CSOM type method. The method has been implemented using ArcView GIS software over the Kangnam and Seocho districts in the city of Seoul, showing that the implemented LRS scheme can be used successfully elsewhere. With the proper advent of the K.ITS architecture and services, the procedure can be used to improve the data sharing and to inter operate among systems, enhancing the efficiency both in terms of money and time.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1162-1162
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• 2001

Whereas NIR spectroscopy has been applied in agriculture for more than 20 years, few studies refer to those plant substances occurring only in smaller amounts. Nevertheless there is a growing interest today to support efficiently activities in the production of high-quality medicinal and spice plants by this fast and non-invasive method. Therefore, it was the aim of this study to develop new NIR methods for the reliable prediction of secondary metabolites found as valuable substances in various plant species. First, sophisticated NIR methods were established to perform fast quality analyses of intact fennel, caraway and dill fruits deriving from single-plants [1]. Later on, a characterization of several leaf drugs and the corresponding fresh material has been successfully performed. In this context robust calibrations have been developed for dried peppermint, rosemary and sage leaves for the determination of their individual essential oil content and composition [2]. A specially adopted NIR method has been developed also for the analysis of carnosic acid in the leaves of numerous rosemary and sage gene bank accessions. Carnosic acid is an antioxidative substance for which several health promoting properties including cancer preservation are assumed. Also some other calibrations have been developed for non-volatile substances such as aspalathin (in unfermented rooibos leaves), catechins (in green tea) and echinacoside (in different Echinacea species) [3]. Some NIR analyses have also been successfully performed on fresh material, too. In spite of the fact that these measurements showed less accuracy in comparison to dried samples, the calibration equations are precise enough to register the individual plant ontogenesis and genetic background. Based on the information received, the farmers and breeders are able to determine the right harvest time (when the valuable components have reached their optimum profile) and to select high-quality genotypes during breeding experiments, respectively. First promising attempts have also been made to introduce mobile diode array spectrometers to collect the spectral data directly on the field or in the individual natural habitats. Since the development of reliable NIRS methods in this special field of application is very time-consuming and needs continuous maintenance of the calibration equations over a longer period, it is convenient to supply the corresponding calibration data to interested user via NIRS network. The present status of all activities, preformed in this context during the last three years, will be presented in detail.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.270-283
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• 2012

With the advent of multi-channel TV, IPTV and smart TV services, excessive amounts of TV program contents become available at users' sides, which makes it very difficult for TV viewers to easily find and consume their preferred TV programs. Therefore, the service of automatic TV recommendation is an important issue for TV users for future intelligent TV services, which allows to improve access to their preferred TV contents. In this paper, we present a recommendation model based on statistical machine learning using a collaborative filtering concept by taking in account both public and personal preferences on TV program contents. For this, users' preference on TV programs is modeled as a latent topic variable using LDA (Latent Dirichlet Allocation) which is recently applied in various application domains. To apply LDA for TV recommendation appropriately, TV viewers's interested topics is regarded as latent topics in LDA, and asymmetric Dirichlet distribution is applied on the LDA which can reveal the diversity of the TV viewers' interests on topics based on the analysis of the real TV usage history data. The experimental results show that the proposed LDA based TV recommendation method yields average 66.5% with top 5 ranked TV programs in weekly recommendation, average 77.9% precision in bimonthly recommendation with top 5 ranked TV programs for the TV usage history data of similar taste user groups.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.587-592
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• 2018

Because the brightness of an AMOLED is determined by the flowing current, each pixel of AMOLED operates via A current driving method. Therefore, it is necessary to supply power to adjust the amount of current according to THE user's requirement for AMOLED driving. In this study, an IP driver block was designed and a simulation was conducted for an AMOLED display, which supplies power as selected by users. The IP driver design focused on regulating the output power due to the OLED characteristics for the diode electric current according to the voltage to be activated by pulse-skipping mode (PSM) under low loads, and 1.5 MHz pulse-width modulation (PWM) for medium/high loads. The IP driver was designed to eliminate the ringing effects appearing from the dis-continue mode (DCM) of the step-up converter. The ringing effects destroy the power switch within the IC, or increase the EMI to the surrounding elements. The IP driver design minimized this through a ringing killer circuit. Mobile applications were considered to enable true shut-down capability by designing the standby current to fall below $1{\mu}A$ to disable it. The driver proposed in this paper can be applied effectively to the same system as the AMOLED display dual power management circuit.