• Journal of KIISE:Software and Applications
• /
• v.34 no.9
• /
• pp.869-879
• /
• 2007

This paper proposes a neural network based approach for automatic human emotion recognition in textile images. To investigate the correlation between the emotion and the pattern, the survey is conducted on 20 peoples, which shows that a emotion is deeply affected by a pattern. Accordingly, a neural network based classifier is used for recognizing the pattern included in textiles. In our system, two schemes are used for describing the pattern; raw-pixel data extraction scheme using auto-regressive method (RDES) and wavelet transformed data extraction scheme (WTDES). To assess the validity of the proposed method, it was applied to recognize the human emotions in 100 textiles, and the results shows that using WTDES guarantees better performance than using RDES. The former produced the accuracy of 71%, while the latter produced the accuracy of 90%. Although there are some differences according to the data extraction scheme, the proposed method shows the accuracy of 80% on average. This result confirmed that our system has the potential to be applied for various application such as textile industry and e-business.

• Journal of Korean Library and Information Science Society
• /
• v.51 no.2
• /
• pp.355-379
• /
• 2020

Digital Library System(DLS) for the school library is a key access tool for school library materials. The purpose of this study was to find ways to improve the accessibility of materials through analysis of students' information search behavior in DLS. Data were collected through recording of 42 participants' DLS search process, and questionnaire. As a result, the search success rate and search satisfaction were found to be lower when the main purpose of DLS is simple leisure reading, information needs are relatively ambiguous, and when user experiences the complicated situations in the search process. The satisfaction level of search time sufficiency was the highest, and the search result satisfaction was the lowest. Besides, there was a need to improve DLS, such as integrated search of other library collection information, the recommendation of related materials, the print output of collection location, voice recognition through mobile apps, and automatic correction of search errors. Through this, the following can be suggested. First, DLS should complement the function of providing career information by reflecting the demand of education consumers. Second, improvements to DLS functionality to the general information retrieval system level must be made. Third, an infrastructure must be established for close cooperation between school library field personnel and DLS management authorities.

• Journal of KIISE:Software and Applications
• /
• v.30 no.3_4
• /
• pp.278-284
• /
• 2003

Speech act is the speaker's intentions indicated through utterances. It is important for understanding natural language dialogues and generating responses. This paper proposes the method of two stage that increases the performance of the korean speech act decision. The first stage is to select features from the part of speech results in sentence and from the context that uses previous speech acts. We use x$^2$ statistics(CHI) for selecting features that have showed high performance in text categorization. The second stage is to determine speech act with selected features and Neural Network. The proposed method shows the possibility of automatic speech act decision using only POS results, makes good performance by using the higher informative features and speed up by decreasing the number of features. We tested the system using our proposed method in Korean dialogue corpus transcribed from recording in real fields, and this corpus consists of 10,285 utterances and 17 speech acts. We trained it with 8,349 utterances and have test it with 1,936 utterances, obtained the correct speech act for 1,709 utterances(88.3%). This result is about 8% higher accuracy than without selecting features.

• Journal of KIISE:Software and Applications
• /
• v.30 no.7_8
• /
• pp.672-680
• /
• 2003

A shopbot is a software agent whose goal is to maximize buyer´s satisfaction through automatically gathering the price and quality information of goods as well as the services from on-line sellers. In the response to shopbots´ activities, sellers on the Internet need the agents called pricebots that can help them maximize their own profits. In this paper we adopts Q-learning, one of the model-free reinforcement learning methods as a price-setting algorithm of pricebots. A Q-learned agent increases profitability and eliminates the cyclic price wars when compared with the agents using the myoptimal (myopically optimal) pricing strategy Q-teaming needs to select a sequence of state-action fairs for the convergence of Q-teaming. When the uniform random method in selecting state-action pairs is used, the number of accesses to the Q-tables to obtain the optimal Q-values is quite large. Therefore, it is not appropriate for universal on-line learning in a real world environment. This phenomenon occurs because the uniform random selection reflects the uncertainty of exploitation for the optimal policy. In this paper, we propose a Mixed Nonstationary Policy (MNP), which consists of both the auxiliary Markov process and the original Markov process. MNP tries to keep balance of exploration and exploitation in reinforcement learning. Our experiment results show that the Q-learning agent using MNP converges to the optimal Q-values about 2.6 time faster than the uniform random selection on the average.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.37-58
• /
• 2011

In general, testing DB applications is much more difficult than testing other types of software. The fact that the DB states as much as the input data influence and determine the procedures and results of program testing is one of the decisive reasons for the difficulties. In order to create and maintain proper DB states for testing, it not only takes a lot of time and efforts, but also requires extensive IT expertise and business knowledge. Despite the difficulties, there are not enough research and tools for the needed help. This article reports the result of research on automatic creation and maintenance of DB states for testing DB applications. As its core, this investigation develops an automation tool which collects relevant information from a variety of sources such as log, schema, tables and messages, combines collected information intelligently, and creates pre- and post-Images of database tables proper for application tests. The proposed procedures and tool are expected to be greatly helpful for overcoming inefficiencies and difficulties in not just unit and integration tests but including regression tests. Practically, the tool and procedures proposed in this research allows developers to improve their productivity by reducing time and effort required for creating and maintaining appropriate DB sates, and enhances the quality of DB applications since they are conducive to a wider variety of test cases and support regression tests. Academically, this research deepens our understanding and introduces new approach to testing enterprise systems by analyzing patterns of SQL usages and defining a grammar to express and process the patterns.

• Journal of Intelligence and Information Systems
• /
• v.24 no.1
• /
• pp.141-166
• /
• 2018

Information technology improves the efficiency of humanities research. In humanities research, information technology can be used to analyze a given topic or document automatically, facilitate connections to other ideas, and increase our understanding of intellectual history. We suggest a method to identify and automatically analyze the relationships between arguments contained in unstructured data collected from humanities writings such as books, papers, and articles. Our method, which is called history mining, reveals influential relationships between arguments and the philosophers who present them. We utilize several classification algorithms, including a deep learning method. To verify the performance of the methodology proposed in this paper, empiricists and rationalism - related philosophers were collected from among the philosophical specimens and collected related writings or articles accessible on the internet. The performance of the classification algorithm was measured by Recall, Precision, F-Score and Elapsed Time. DNN, Random Forest, and Ensemble showed better performance than other algorithms. Using the selected classification algorithm, we classified rationalism or empiricism into the writings of specific philosophers, and generated the history map considering the philosopher's year of activity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2000.10a
• /
• pp.284-287
• /
• 2000

Recently, developing medical devices have a tendency becoming the module for satisfying user's mutual complex needs. Because the most effective method for the observation of patients condition a diagnosis and a treatment is collecting data from various devices and controling operation following it. Module tendency is more popular due to manage easily totally many individual systems. This study implemented communication protocol to control by one control system connecting modular medical devices. Implemented system consist of one master module controlling all module and managing communication and many Slave modules. Communication between each modules introduced SPI(Serial Peripheral Interface) among many synchronous serial communication methods for the exact transmission and receipt of data. All communication executes by packet format. This can detect error. And, this protocol introduced PNP(Plug And Play) function that auto-detect connecting or removing module during running. This protocol exactly transmitted and received in faster speed more than 1Mbps. And in practical application to the ventilator this confirmed to give and take real-time data. And various functions by th central control system is implemented in this protocol.

• The Journal of the Korea Contents Association
• /
• v.18 no.3
• /
• pp.486-498
• /
• 2018

This study is a descriptive research study conducted to provide useful preliminary data that is helpful for self-initiated learning through a preference trend-based learning method by analyzing the personality types of university students in an area. In this study, the self-administered MBTI form $M^{(R)}$ test was performed on 695 students of 10 departments at K University, from September 18 to 22, 2017, using an automatic scoring system. Collected data was analyzed with descriptive statistics and Chi-square test, using the SPSS Win 22.0 Program, to sort the target students into one of 16 different personality types and examine psychological function and temperament by their personality. Differences in personality type preference by gender were as follows: for judging function, the male students had a strong preference for the T type (thinking type) while the female students showed a high preference for the F type (feeling type), and in the case of the pattern of behavior and lifestyle, the male students and the female students had a strong preference for the P type (perceiving type) and the J type (judging type), respectively. In addition, there were significant differences for each major and each department in personality type, psychological function and temperament. In conclusion, personality type was found to vary by gender, major and department. It would be necessary to develop a manual for learning methods reflecting individual preference.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.9
• /
• pp.1898-1905
• /
• 2012

This paper presents an On-board Smart Device (OSD) for moving vehicle, based on a smooth integration of Android-based devices and a Micro-control Unit (MCU). The MCU is used for the acquisition and transmission of various vehicle-borne data. The OSD has threefold functions: Record, Report and Alarm. Based on these RRA functions, the OSD is basically a safety and convenience oriented smart device, where it facilitates alert services such as accident report and rescue as well as alarm for the status of vehicle. In addition, voice activated interface is developed for the convenience of users. Vehicle data can also be uploaded to a remote server for further access and data manipulation. Therefore, unlike conventional blackboxes, the developed OSD lends itself to a user-friendly smart device for vehicle safety: It basically stores monitoring images in driving plus vehicle data collection. Also, it reports on accident and enables subsequent rescue operation. The developed OSD can thus be considered an essential safety smart device equipped with comprehensive wireless data service, image transfer and voice activated interface.

• Proceedings of the KSRS Conference
• /
• 2006.03a
• /
• pp.178-186
• /
• 2006

기상 수치예보는 (Numerical Weather Pridiction, NWP)는 바람, 기온, 등과 같은 기상요소의 시간 변화를 나타내는 물리방정식을 컴퓨터로 풀어 미래의 대기 상태를 예상하는 과학적인 방법으로 지구를 상세한 격자 2진부호(GRIdded Binary, 이하 GRIB)로 나누어 그 격자점에서의 값으로 대기 상태를 나타낸다. 지구 각지에서의 각종 관측자료를 기초로 격자점상의 현재값을 구한다. 대용량의 격자데이터는 이진형태이어서 컴퓨터, 서버 저장장치에서 동일형태 데이터로 존재한다. 우리나라 최초의 저궤도 관측 위성인 다목적 실용위성 KOMPSAT-1호(이하, 아리랑 위성1호)는 전자광학카메라(Electro Optical Camera, EOC)를 탑재하여 1999년 12월 21일에 발사된 이후 2006년 1월 현재까지 6여년간 성공적으로 임무를 수행, 7049여회의 영상을 획득하여 국가적으로 귀중한 자료로 활용하고 있다. 아리랑 위성1호는 일일 2-3회 EOC영상을 획득하고 있으며, 임무계획(Mission Planning)은 MP(Mission Planner)가 사용자로부터 자료를 수집하여 임무분석 및 계획 서브시스템(MAPS)에 의해 계산되어진 위성의 제도예측 데이터에 촬영하고자하는 목표지점 좌표를 입력하여 자동명령생성기(KSCG)에 의해 계산된 촬영 경사각도(Tilt)값을 위성에 전송하여 목표지역의 영상을 획득하게 된다. 위성영상 획득에 있어 고가의 위성을 운영하면서 기상의 상태를 정확히 예측하여 실패없이 유효한 영상을 획득하는 것이 무엇보다 중요하다. 본 논문에서는 효율적인 위성임무계획을 위한 기상수치예보 자료를 분석하여 앞으로 발사하게 될 고해상 카메라 탑제위성인 아리랑 위성2호와 3호에 적용하고자 한다. the sufficient excess reactivity to override this poisoning must be inserted, or its concentration is decreased sufficiently when its temporary shutdown is required. As ratter of fact, these have an important influence not only on reactor safety but also on economic aspect in operation. Considering these points in this study, the shutdown process was cptimized using the Pontryagin's maximum principle so that the shutdown mirth[d was improved as to restart the reactor to its fulpower at any time, but the xenon concentration did not excess the constrained allowable value during and after shutdown, at the same time all the control actions were completed within minimum time from beginning of the shutdown.및 12.36%, $101{\sim}200$일의 경우 12.78% 및 12.44%, 201일 이상의 경우 13.17% 및 11.30%로 201일 이상의 유기의 경우에만 대조구와 삭제 구간에 유의적인(p<0.05) 차이를 나타내었다.는 담수(淡水)에서 10%o의 해수(海水)