• Title/Summary/Keyword: response database

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A Development of Real-time Vibration Monitoring and Analysis System Linked to the Integrated Management System of Ministry of Public Safety and Security (국민안전처 통합관리시스템 연계 가능한 시설물 진동 감지 및 분석 시스템 개발)

  • Lim, Ji-Hoon;Jung, Jin-Woo;Moon, Dae-Joong;Choi, Dong-Ho
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.20 no.3
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    • pp.130-139
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    • 2016
  • A frequency of earthquake occurrence in the Republic of Korea is increasing over the past few decades. In this situation, an importance of earthquake prevention comes to the fore because the earthquake does damage to structures and causes severe damage of human life. For the earthquake prevention, a real-time vibration measurement for structures is important. As an example, the United States of America and Japan have already been monitoring real-time earthquake acceleration for the important structures and the measured acceleration data has been managed by forming database. This database could be used for revising the seismic design specifications or predicting the damage caused by earthquake. In Korea, Earthquake Recovery Plans Act and Enforcement Regulations are revised and declared lately. Ministry of Public Safety and Security is constructing a integrated management system for the measured earthquake acceleration data. The purpose of this research is to develop a real-time vibration monitoring and analysis system for structures which links to the integrated management system. The developed system contains not only a monitoring function to show real-time acceleration data but also an analysis system to perform fast fourier transform, to obtain natural frequency and earthquake magnitude, to show response spectrum and power spectrum, and to evaluate structural health. Additionally, this system is designed to be able to link to the integrated management system of Ministry of Public Safety and Security. It is concluded that the developed system can be useful to build a safety management network, minimize maintenance cost of structures, and prevention of the structural damage due to earthquake.

Priority Analysis for Infrastructure Recovery from Volcanic Disaster (사회기반시설의 화산재해 복구 우선순위 산정)

  • Park, Hyung Keun;Kang, Kyo Seok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.3
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    • pp.989-998
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    • 2014
  • Recently volcanic eruptions and activities occurring in many parts of world have become a common global concern to many countries. The severity of these Volcanic disasters, such as of Mt. Eyjafjallajokull in Iceland and Mt. Merapi in Indonesia, have caused damages and causalities reaching astronomical levels. The infrastructure is categorized into 18sections that appropriately reflecting the survey data collected from various government agents, current inhabitant and engineers to accumulate a database on the priorities and preferences of restoring and reconstructing many kinds of infrastructure and facilities. The survey data was collect by using the "Likert 5 Scale Method" which emphasized the importance and priority of reconstruction and restoration for the specific facilities and infrastructures. The data was corrugated, organized and used in plotting and planning a strategic recovery agenda. The survey results were analyzed and verified to ensure the validity and reliability of the data by using chi-square test. This paper presents that recovery period and recovery cost to the total damage of infrastructure and facilities were used to make a recovery network with implemented construction management method. The research is expected that a more efficient and prompt recovery protocol and recovery plan can be executed and can be use as a reference and database.

A Study of Web Application Attack Detection extended ESM Agent (통합보안관리 에이전트를 확장한 웹 어플리케이션 공격 탐지 연구)

  • Kim, Sung-Rak
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.1 s.45
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    • pp.161-168
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    • 2007
  • Web attack uses structural, logical and coding error or web application rather than vulnerability to Web server itself. According to the Open Web Application Security Project (OWASP) published about ten types of the web application vulnerability to show the causes of hacking, the risk of hacking and the severity of damage are well known. The detection ability and response is important to deal with web hacking. Filtering methods like pattern matching and code modification are used for defense but these methods can not detect new types of attacks. Also though the security unit product like IDS or web application firewall can be used, these require a lot of money and efforts to operate and maintain, and security unit product is likely to generate false positive detection. In this research profiling method that attracts the structure of web application and the attributes of input parameters such as types and length is used, and by installing structural database of web application in advance it is possible that the lack of the validation of user input value check and the verification and attack detection is solved through using profiling identifier of database against illegal request. Integral security management system has been used in most institutes. Therefore even if additional unit security product is not applied, attacks against the web application will be able to be detected by showing the model, which the security monitoring log gathering agent of the integral security management system and the function of the detection of web application attack are combined.

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Relational Database SQL Test Auto-scoring System

  • Hur, Tai-Sung
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.11
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    • pp.127-133
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    • 2019
  • SQL is the most common language in data processing. Therefore, most of the colleges offer SQL in their curriculum. In this research, an auto scoring SQL test is proposed for the efficient results of SQL education. The system was treated with algorithms instead of using expensive DBMS(Data Base Management System) for automatic scoring, and satisfactory results were produced. For this system, the test question bank was established out of 'personnel management' and 'academic management'. It provides users with different sets of test each time. Scoring was done by dividing tables into two sections. The one that does not change the table(select) and the other that actually changes the table(update, insert, delete). In the case of a search, the answer and response were executed at first and then the results were compared and processed, the user's answers are evaluated by comparing the table with the correct answer. Modification, insertion, and deletion of table actually changes the data table, so data was restored by using ROLLBACK command. This system was implemented and tested 772 times on the 88 students in Computer Information Division of our college. The results of the implementation show that the average scoring time for a test consisting of 10 questions is 0.052 seconds, and the performance of this system is distinguished considering that multiple responses cannot be processed at the same time by a human grader, we want to develop a problem system that takes into account the difficulty of the problem into account near future.

A Development of Chatbot Q&A System to Answer Questions in Webpage - Focused on arts education matching services - (온라인 시스템 장애를 원활히 해결하기 위한 챗봇 Q&A시스템 개발 - 예술 교육 서비스를 중심으로 -)

  • Kim, Jae Min;Lee, Hye Moon;Kim, Myoung Young;Lee, Won Hyung;Yi, Dae Youmg
    • Journal of the Korean Society for Computer Game
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    • v.31 no.4
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    • pp.157-166
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    • 2018
  • Communication between customers and service providers is an important issue at sites where various businesses and transactions take place. In particular, the ability to solve problems quickly and accurately when a problem arises and when an inquiry is received is directly linked to trust in the site. In this paper, we propose a method of handling complaints and inquiries of site users by using chatbot technology on talent market platform site. First, we implemented chatbot that can communicate with the inquirers in real time, so that users can use the site usage and word search functions. For various errors and problems of the site which can not be defined by a few words or sentences, I have specified an error code and database it. Users of the site were able to contact chatbot with the error code that was output when an error occurred and get the corresponding response in real time. The chatbot implemented in this study provided a satisfactory experience because that was able to provide quick and accurate answers to users who experienced errors or inquiries when using the site. This will have a positive impact on the credibility and favorability of the site over the long term, and will help reduce manpower and time costs for error inquiries.

A Study on SIARD Verification as a Preservation Format for Data Set Records (행정정보 데이터세트 보존포맷으로서 SIARD 검증에 관한 연구)

  • Yoon, Sung-Ho;Lee, Jung-eun;Yang, Dongmin
    • Journal of Korean Society of Archives and Records Management
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    • v.21 no.3
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    • pp.99-118
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    • 2021
  • As the importance of data grows because of the advent of the next industrial revolution, foreign countries are pushing for long-term data preservation technology research. On the other hand, in Korea, administrative information data sets have been legislated as records management areas without specific long-term preservation measures. As a response, this study conducted basic, cross-validation tests on the Software Independent Archiving of Relational Database (SIARD), which was proposed as an administrative information data set preservation format in several prior works. First, the underlying verification test focuses on deriving the data, structure, and functionality of the data set that SIARD can preserve. The second cross-validation test aimed at verifying the interoperability of SIARD independent of the DBMS class. In addition, two verification tests have confirmed the SIARD feature delivery range. Consequently, the differences between the feature types specified in the SIARD 2.0 standard and those provided by the actual SIARD Suite have been derived. Based on verification test results, we are proposing a development plan to broaden SIARD functionality and set a direction to efficiently enhance SIARD for local situations.

A research on the emotion classification and precision improvement of EEG(Electroencephalogram) data using machine learning algorithm (기계학습 알고리즘에 기반한 뇌파 데이터의 감정분류 및 정확도 향상에 관한 연구)

  • Lee, Hyunju;Shin, Dongil;Shin, Dongkyoo
    • Journal of Internet Computing and Services
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    • v.20 no.5
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    • pp.27-36
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    • 2019
  • In this study, experiments on the improvement of the emotion classification, analysis and accuracy of EEG data were proceeded, which applied DEAP (a Database for Emotion Analysis using Physiological signals) dataset. In the experiment, total 32 of EEG channel data measured from 32 of subjects were applied. In pre-processing step, 256Hz sampling tasks of the EEG data were conducted, each wave range of the frequency (Hz); Theta, Slow-alpha, Alpha, Beta and Gamma were then extracted by using Finite Impulse Response Filter. After the extracted data were classified through Time-frequency transform, the data were purified through Independent Component Analysis to delete artifacts. The purified data were converted into CSV file format in order to conduct experiments of Machine learning algorithm and Arousal-Valence plane was used in the criteria of the emotion classification. The emotions were categorized into three-sections; 'Positive', 'Negative' and 'Neutral' meaning the tranquil (neutral) emotional condition. Data of 'Neutral' condition were classified by using Cz(Central zero) channel configured as Reference channel. To enhance the accuracy ratio, the experiment was performed by applying the attributes selected by ASC(Attribute Selected Classifier). In "Arousal" sector, the accuracy of this study's experiments was higher at "32.48%" than Koelstra's results. And the result of ASC showed higher accuracy at "8.13%" compare to the Liu's results in "Valence". In the experiment of Random Forest Classifier adapting ASC to improve accuracy, the higher accuracy rate at "2.68%" was confirmed than Total mean as the criterion compare to the existing researches.

Development of Risk Analysis Structure for Large-scale Underground Construction in Urban Areas (도심지 대규모 지하공사의 리스크 분석 체계 개발)

  • Seo, Jong-Won;Yoon, Ji-Hyeok;Kim, Jeong-Hwan;Jee, Sung-Hyun
    • Journal of the Korean Geotechnical Society
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    • v.26 no.3
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    • pp.59-68
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    • 2010
  • Systematic risk management is necessary in grand scaled urban construction because of the existence of complicated and various risk factors. Problems of obstructions, adjacent structures, safety, environment, traffic and geotechnical properties need to be solved because urban construction is progressed in limited space not as general earthwork. Therefore the establishment of special risk management system is necessary to manage not only geotechnical properties but also social and cultural uncertainties. This research presents the technique analysis by the current state of risk management technique. Risk factors were noticed and the importance of each factor was estimated through survey. The systemically categorized database was established. Risk extraction module, matrix and score module were developed based on the database. Expected construction budget and time distribution can be computed by Monte Carlo analysis of probabilities and influences. Construction budgets and time distributions of before and after response can be compared and analyzed 80 the risks are manageable for entire whole construction time. This system will be the foundation of standardization and integration. Procurement, efficiency improvement, effective time and resource management are available through integrated management technique development and application. Conclusively decrease in cost and time is expected by systemization of project management.

The Prediction of Purchase Amount of Customers Using Support Vector Regression with Separated Learning Method (Support Vector Regression에서 분리학습을 이용한 고객의 구매액 예측모형)

  • Hong, Tae-Ho;Kim, Eun-Mi
    • Journal of Intelligence and Information Systems
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    • v.16 no.4
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    • pp.213-225
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    • 2010
  • Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.

Genome Wide Expression Analysis of the Effect of Pinelliae Rhizoma Extract on Psychological Stress (반하(半夏)가 스트레스로 인한 생쥐의 뇌조직 유전자변화에 미치는 영향 연구)

  • Jeong, Jong-Hyo;Cho, Su-In;Song, Young-Gil;Kim, Ha-Na;Kim, Kyeong-Ok
    • Journal of Oriental Neuropsychiatry
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    • v.26 no.1
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    • pp.63-78
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    • 2015
  • Objectives: Pinelliae Rhizoma has traditionally been used as an anti-depressant in oriental medicine. This study is to investigate the effect of Pinelliae Rhizoma extract (PRe) on psychological stress in genome wild expression of mice. Methods: After giving physical stress to mice, PRe was orally administered with 100 mg/kg/day for five days. After extracting whole brain tissue from the mice, their genome changes were observed by micorarray analysis method. The genome changes were analyzed by IMAGENE 4.0, TREEVIEW, FatiGo algorithems, BOND database, cytoscape program, etc. Results: 1. PRe administered group were remained at normal level; 60% of increase was shown in expressed genes by physical stress, and 65% of decrease was shown in expressed genes by psychological stress. 2. Genes with increased expression in control group that remained at a normal state in PRe administered group were involved with the gene of a cellular metabolic process on biological process, protein binding on molecular function, and cell part on cell composition. The pathway was found to be cytokin-cytokin receptor interaction. 3. Genes with decreased expression in control group that remained at a normal state in PRe administered group were involved with the gene of a cellular metabolic process on biologiacl detail and coupled ATPaes activity on molecular function. This gene related path was Ubiquintin mediated proteolysis etc. 4. Core node genes analyzed by protein interaction network were Vinculin, Cell sdivision cycle 42 homolog (S. cerevisiae) etc. They played an important role in maintaining cytoskeleton and controlling cell cycle. Conclusions: Several genes were up-regulated and down-regulated in response to psychological stress. The expression of most of the genes that were altered in response to psychological stress was restored to normal levels in PRe treated mice. When the interaction network information was analyzed, the recovery of the core node genes in PRe treated mice indicates that this final set of genes may be the effective target of PRe.