• Journal of Engineering Education Research
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• v.10 no.3
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• pp.64-78
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• 2007

For Korean researchers, English is essential. In fact, this is the case for any researcher who is a non-native English speaker, as recognition and success is predicated on being published, while publications that reach the broadest audiences are in English. Unfortunately, university science and engineering programs in Korea often do not provide formal coursework to help students attain greater competence in English composition. Aggravating this situation is the general lack of literature covering this specific pedagogical issue. While there is plenty of information to help native speakers with technical writing and much covering general English composition for EFL learners, there is very little information available to help EFL learners become better technical writers. Thus, the purpose of this report is twofold. First, as most Korean educators in science and engineering are not well acquainted with pedagogical issues of EFL writing, this report provides a general introduction to some relevant issues. It reviews the importance of contrastive rhetoric as well as some considerations for choosing the appropriate teaching approach, class arrangement, and use of computer assisted learning tools. Secondly, a course proposal is discussed. Based on a review of student writing samples as well as student responses to a self-assessment questionnaire, the proposed course is intended to balance the needs of Korean EFL learners to develop grammar, process, and genre skills involved in technical writing. Although, the scope of this report is very modest, by sharing the considerations made towards the development of an EFL technical writing course it seeks to provide a small example to a field that is perhaps lacking examples.

• Journal of forensic and investigative science
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• v.1 no.2
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• pp.5-19
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• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

• Journal of Animal Science and Technology
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• v.45 no.3
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• pp.343-354
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• 2003

Simulation studies were carried out to investigate the responses of selection for three carcass traits (longissimus muscle area: EMA, fat thickness: BF, and marbling score: MS) based on either adjusted phenotypes (APH) or estimated breeding values (EBV) in multivariate animal model with different breeding schemes. Selection responses were estimated and compared on six different models with respect to breeding schemes using either carcass measurements or real time ultrasonic (RTU) scans generated by Monte Carlo computer simulation supporting closed breeding population. From the base population with 100 sires and 2000 dams, 20 sires and 1000 dams by each generation were selected by either APH or EBV for 10 generations. Relative economic weights were equal of three traits as EMA(1): BF(－1) : MS(1) for standardized either APH or EBV. For first two models which were similarly designed with current progeny-test program in Korean cattle, three carcass traits with records either only on male progenies (Model 1) or on male and female progenies (Model 2) were used for selecting breeding stocks. Subsequently, generation intervals on males were assumed as 6${\sim}$10 years in these two models. The other two models were designed with tools of selection by RTU rather than carcass measurements with genetic correlations of 0.81${\sim}$0.97 between RTU and corresponding carcass traits in addition to whether with records (Model 4) or without records (Model 3) on female. In these cases, generation intervals on males were assumed as 2${\sim}$4 years. The remaining last two models were designed as similar with Models 3 and 4 except genetic correlations of 0.63${\sim}$0.68 between RTU and corresponding carcass traits with records (Model 6) and without records (Model 5) on females. The results from 10 replicates on each model and selecting methods suggested that responses indirect selection for carcass traits in Model 4 were 1.66${\sim}$2.44 times efficient rather than those in Model 1. Otherwise, in Model 6 with assuming moderate genetic correlations, those efficiencies were 1.18${\sim}$2.08 times with comparing to responses in Model 1. However, selection response for marbling score was the smallest among three carcass traits because of small variation of measurements. From these results, this study suggested that indirect selection using RTU technology for improving high meat qualities in Korean cattle would be valuable with modifying measuring rules of marbling score forward to large variation or modifying relative economic weight for selection.

• Korean Journal of Human Ecology
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• v.7 no.1
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• pp.51-67
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• 2004

This study analyzed the effects of nutrition technicians' hygiene education on cooking workers' performance of hygiene management in order to ensure the security of school meals. The situation of cooking workers' disposition in subject schools was elementary school(51.1%) and middle school(48.9%) and the type of meals was rural area type(54.2%), urban type(36.5%). and island and isolated area type(9.3%). The methods of meals management were single cooking(88.2%) and joint cooking and management(11.8%). The type of distributing meals was distributing in a dining room(93.5%), in a classroom(3.7%), and in both dining room and classroom(2.8%). Nutrition technicians' employment form included regular(53.5%) and daily(88.2%). Their education was junior college graduate(50.2%), university graduate(44.8%). and graduate school students(5.0%). Cooking workers' employment form included daily(88.2%) and regular (11.1%). suggesting that most were regular. Most cooking workers(77.4%) had at least high school certificate. Regarding the situation of cooking workers' disposition in subject schools, the number of student per one cooking worker was found as 91-120(37.2%), 61-90(22.6%). 60 and under(21.l %). 121-15006.7%). and 151 and over(2.5%). Cooking workers' level of performance of hygiene management was post-working stage(66.37/75 marks), pre-working stage(64.22/75 marks). and working stage(20.34/25 marks), The counting of meals articles in a pre-working stage(20.34/25 marks). temperature and required time in a working stage(18.78/25 marks), and machinery equipment and hygiene in a pre-working stage(21.40/25 marks) showed lowest of performance, which suggest poor service of hygiene. Cooking workers' performance of hygiene management by working stage showed the significant difference with school class(p<.001), type of schools with meals(p<.05). state of cooking workers' employment(p<.001), and cooking worker's disposition(p<.05). A working stage showed the significant difference with type of schools with meals(p<.05). A post-working stage showed the significant difference according to type of schools with meals(p<.05), and the methods of meals management(p<.05), and cooking workers' disposition(p<.05). In the execution of hygiene education, individual hygiene was highest(94.8%), followed by the management of machinery equipment and tools(89.7%), food poisoning and microorganism(94.7%), and the method of food treatment(76.4%). A yearly plan of hygiene education included established(83.9%) and not established(l6.1%). Regular education included not executed(25.1%), 2-3 times a month(l6.1%), and more than 4 a month(4.0%) and occasional education was not executed(57.0%), 1-3 times a month(26.3%), and more than 4 a month(l5.7%). In the methods for hygiene education, oral education(95.7%) was used most, followed by demonstration(10.5%), poster/photo(10.5%), video/slide(3.7%), and computer(3.7%). Frequency of improvement and complement of hygiene education included once a month(56.3%), once a year(20.7%), by quarter(l1.5%), and every six months(1l.5%). Newspaper was used most in materials of hygiene education, followed by internet, TV, nutrition technician's reeducation, information exchange between members, educational office's training, and reference book, and educational office's material. and symposium. Cooking workers' assessment of the effect of hygiene education was conducted through observation(56.8%), check table(l5.2%), question(l4.0%), and examination(14.0%). The reason of cooking workers' low level of performance included habitual custom(53.9%), lack of understanding(20.4%), overwork(l4.6%), and lack of knowledge(l1.l%) and the reason of difficulty in hygiene education included lack of time(55.3%), lack of understanding(27.6%), lack of knowledge and information(8.7%), and lack of budget(48.0%).

• Journal of the Korean Society of Safety
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• v.10 no.3
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• pp.81-95
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• 1995

Now, safety assurance in construction sites should be accomplished by its own organization rather than control of the code or government. It is believed that the safety assurance can be considerably improved by a lecture or an education using the existing theories or literatures up to now, but it is thought that fundamental safety assurance we not able to be accomplished without developing safety devices '||'&'||' equipment or taking fundamental measures, based on the result analyzed from workers behaviors. There are various behaviors of the workers showed in construction site, but only tests for hammerusing works such as form, re-bar, stone workers directly related to the grip strength are mainly performed, investigated and measured here for the study. The above works are similar to power grip, 7th picture on seven items which are categorized for hand grip types(Ammermin 1956 ; Jones ; Kobrick 1958). Measurements of grip strength are commonly taken in anthropometric surveys. They are easy to administer but unfortunately it is rather dubious whether they yield any data that are of interest to the engineer. Very fewer controls of tools are grasped and squeesed studies showed very little overall correlation between grip strength and other measures of bodily strength (Laubach, Kromer, and Thordsen 1972), but hammer-using work which is practically progressed in construction site are mainly influenced with grip strength. According to the investigation on work measurement, it is shown that 77% of form worker are using hammer to be related to grip strength. In this study, it is particularly noticed that wearing safety gloves in construction site is required for workers safety but 20% difference between grip strength with safety gloves and without ones are commonly neglected in the site(Fig. 1). Nevertheless, safety operation with consideration of the above 20% difference is not considered in the construction site. Factors of age, kinds of work, working time, with or without safety gloves are in vestigated '||'&'||' collected at the sites for this study. Test, not at each working hour but at 14 : 00 when the almost all of the workers think the most tired, resulting from the questionaires, also when it is shown on the research report has been performed and compared for main kinds of works : form '||'&'||' re-bar work. Tests were performed with both left SE rightand of the workers simultaneously in construction site using Rand Dynamometer(Model 78010, Lafayette Instrument Co., Indiana, U.S.A) by reading grip strength on the gauge while they are pulling, and then by interviewing on their ages, works, experiences and etc., directly. The above tests have been performed for the dates of 15th march-26th May '95 with consideration of site condition. And even if various factors of ambient temperature on the testing date, working condition, individual worker's habit and worker's condition of the previous ate are concerned with the study. Those are considered as constants in this study. Samples are formwork 53, rebar 62, electrician 5, plumber 4, welding 1 from D construction Co., Ltd, ; formwork 12, re-bar 5, electrician 2, from S construction Co., Ltd, , formwork 78, re-bar 18, plumber 31, electrician 13, labor 48, plumber 31, plasterer 15, concrete placer 6, water proof worker 3, maisony 5 from B construction Co., Ltd. As In the previously mentioned, main aspect to be investigated in this study will be from '||'&'||' re-bar work because grip strength will be directly applied to these two kinds of works ; form '||'&'||' re-bar work, eventhough there are total 405 samples taken. It is thought that a frequency of accident occurrence will be mainly two work postures "looking up '||'&'||' looking down" to be mainly sorted, but this factor is not clarified in this study because It will be needed a lot of work more. Tests has been done at possible large scale of horizontally work-extended sites within one hour in order to prevent or decrease errors '||'&'||' discrepancies from time lag of the test. Additionally, the statistical package computer program SPSS PC＋has been used for the study.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.139-166
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• 2010

The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.