• The Journal of Fisheries Business Administration
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• v.17 no.2
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• pp.65-106
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• 1986

1, The Purpose of Study This is a study on the Evaluation of the operating of Fisheries Extension Services of Korea, for performing the activities such as guiding fisheries technique as well as offering industrial information to the fishermen in fishing village. By doing so, the Fisheries Extension Sevices(FES) can materialize the continued growth of fisheries, the social and economic development of fishing village, and the increase in income by enhancing the knowledge level of Fishermen, etc. In performing fisheries policy, this activity plays a great role on the research and development activity, and it has become practical since 1976 in Korea. In order to meet immediately with the problem of fisheries technical innovation and rapid environmental changes surrounding the fisheries, the fishermen should not only enhance their scientific and comprehensive capacity in fisheries technique but abtain various effective information. Generally, as most of all the fishemen are poor in the managerial structure and scattered in fishing villages, they have little opportunity in the contact of information. As a result, it is nessessary for the FES to perform the fishing business by the extension service officials who has received special training and acquired fisheries know-how in these fields. And yet, FES is under the unfullfilled circumstance in such factors as manpower, technical know-how, equipment, and the service system etc., which is required in promoting the social, economic development of fishing village and in resolving the high technique demand of fisherman. This study on the fisheries extension services have been studied from those backgrounds. 2. Research Method The data of collecting methods which were necessary in carrying out this study was adopted by the questionaire research on the present extension service activity, through the subject of the extension services (driving agency of the work and the officials), the object(fishemen) and the 3rd observers to the extension services (the authorities concerned). The research sample was taken by the sampling extraction of total 1, 774 men from the above 3 groups. And the research was carried out from August, 1986 to October, 1986, supported from the Fisheries Extension Office (FEO) located in field during the research process. In this study, the levels of the extension operating were determined and estimated in accordance with the extension service method, morale of extension service officials and the extension service system, etc. through the collected data of the research questionaire paper. And based on this result, the essential conditions of the extension services were grasped, and also we tried to present the various activity plan necessary to promote the operating of the extension services. The questionaire research data was calculated by the computer center of National Fisheries University of Pusan, and the total result was again tried on the one demension analysis along with two dimension analysis to search out the relativity between the questionaire, and the statistical test was done $\chi$$^2$test in significance level of l~5%. 3. Contents of Study This study consists of 7 chapters and the contents are as follows : Chapter I : The object and method of the study Chapter II : The assessment and analysis of the extension services Chapter III : The contents and method of the extension services Chapter IV : Analysis of the essential conditions for the extension services Chapter V : The evaluation of activities of extension services Chapter Ⅵ : Conclusion.4. Results and RecommendationTherefore, the results of this study estimated by logical process and analysis are as follows : 1) Most of Korean fishing villages and coastal fishermen have shown much concerns about fisheries technique and social changes, thus many of them were confronted with new problems on how to adapt and to meet changes. 2) Majority of fishermen estimated FEO as an organization of specific technologies with all the thing concerning the fisheries technique in general. Therefore the fishermen wanted to utilize the FEO as an adaptable method for the modern fisheries techniques as well as the environmental changes. 3) In contrast with the fast changes of the fisheries technique, the complexity and variety of technical system and the broadness of fishing village and fishermen, it was revealed that the necessary factors such as the facilities, manpower, budget, and the level of applying techniques of the FEO located in field were highly insufficient. Accordingly, the guiding efficiency was low and the extension services did not provide full solution to the various request from fishermen. 4) It is possible to classify the activation factor for the extension service into two large dimension ; personal dimension relevant to guidance officials and work dimension relevant to the organization. And it was found that the activation level of the work dimension was far lower than the personal dimension between them. So, the activation should be done first in the dimesion to promote the activation of the extension services. 5) The extension services officials are now demoralized in general, thus it is necessary to take reality into consideration : the expense of activity, the adequate endowment of activity scope and the reasonable operation of the position class, etc to enhance its morale. However, in order to do the FES activation, first of all, the systems should be established which is lain unsettled stage until now. And there must be change in the understanding of government i.e. the fisheries extension services are the essential policy subject to build up the base of fisheries growth and modernize the fisheries management. And it should be driven positively with the recognition of the "lasting project".g project".uot;.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.77-88
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• 2008

There has been growing demands to manage the water quality of west coastal region due to the large scale urbanization along the coastal zone, the possibility of application of TMDL(Total Maximum Daily Loadings) to Han river, and the natural disaster such as oil spill incident in Taean, Chungnam. However, no system has been developed for such purposes. In this background, the demand of GIS based effective water quality management has been increased to monitor water quality environment and propose best management alternatives for Han river and Kyeonggi bay. This study mainly focused on the development of integrated water quality management system for Han river bas in and its estuary are a connected to Kyeonggi bay to support integrated water quality management and its plan. Integration was made based on GIS by spatial linking between water quality attributes and location information. A GIS DB was built to estimate the amount of generated and discharged water pollutants according to TMDL technical guide and it included input data to use two different water quality models--W ASP7 for Han river and EFDC for coastal area--to forecast water quality and to suggest BMP(Best management Practices). The results of BOD, TN, and TP from WASP7 were used as the input to run EFDC. Based on the study results, some critical areas which have relatively higher pollutant loadings were identified, and it was also identified that the locations discharging water pollutant loadings to river and seasonal factor affected water quality. And the relationship of water quality between river and its estuary area was quantitatively verified. The results showed that GIS based integrated system could be used as a tool for estimating status-quo of water quality and proposing economically effective BMPs to mitigate water pollution. Further studies need to be made for improving system's capabilities such as adding decision making function as well as cost-benefit analysis, etc. Also, the concrete methodology for water quality management using the system need to be developed.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.1-22
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• 2009

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction and integration both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of techniques for Web service discovery have been proposed, but the discovery challenge has not been satisfactorily addressed. Unfortunately, most existing solutions are either too rudimentary to be useful or too domain dependent to be generalizable. In this paper, we propose a Web service organizing framework that combines clustering techniques with string matching and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. Our proposed approach has several appealing features : (1) It minimizes the requirement of prior knowledge from both service consumers and publishers; (2) It avoids exploiting domain dependent ontologies; and (3) It is able to visualize the semantic relationships among Web services. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service registries. We report on some preliminary results demonstrating the efficacy of the proposed approach.

• Journal of Korean Academy of Nursing
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• v.28 no.4
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• pp.958-969
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• 1998

In this study, we attempted to investigate the needs and problems of the terminal cancer patients and their family caregivers to provide them with nursing information to improve their quality of life and prepare for a peaceful death. Data was collected from August 1, 1995 to July 31, 1996 at the internal medicine unit of S hospital in Seoul area with the two groups of participants who were family members of terminal cancer patients seventy four of them were in-patients and 34 were out-patients who were discharged from the same hospital for home care. The research tool used in this study has been developed by selecting the questionnaires from various references, modifying them for our purpose and refining them based on the results of preliminary study. While general background information about the patients was obtained by reviewing their medical records, all other information was collected by interviewing the primary family caregivers of the patients using the questionnaire. The data collected were analyzed with the SPSS PC/sup +/ program. The results of this study are summarized as follows ; 1) Most frequently complained symptoms of the terminal cancer patients were in the order of pain(87%), weakness(86.1%), anorexia(83.3%) and fatigue (80.6%). 2) Main therapies for the terminal cancer patients were pain control (58.3%), hyperalimentation(47.2%) and antibiotics(21.3%). 3) Special medical devices that terminal cancer patients used most were oxygen device (11.1%), and feeding tube(5.6%). Other devices were used by less than 5% of the patients. 4) The mobility of 70.4% of the patients was worse than ECOG 3 level, they had to stay in bed more than 50% of a day. 5) Patients wanted their medical staffs to help relieve pain(45.4%), various physical symptoms(29.6%), and problems associated with their emotion(11.1%). 6) 16.7% of the family caregivers hoped for full recovery of the patients, refusing to admit the status of the patients. Also, 37% wished for the extension of the patient's life at least for 6 months. 7) Only 38.9% of the family members was preparing for the patient's funeral. 8) 45.4% of family caregivers prefer hospital as the place for the patient's death, 39.8% their own home, and 14.8% undetermined. 9) Caregivers of the patients were mostly close family members, i.e., spouse(62%), and sons and daughters or daughter-in-laws(21.3%). 10) 43.5% of the family caregivers were aware of hospice care. 46.8% of them learned about the hospice care from the mass media, 27.7% from health professionals, and the rest from books and other sources. 11) Caregivers were asked about the most difficult problems they encounter in home care, 41 of them pointed out the lack of health professionals they can contact, counsel and get help from in case of emergency, 17 identified the difficulty of finding appropriate transportation to hospital, and 13 stated the difficulty of admission in hospital as needed. 12) 93.6% of family caregivers demanded 24-hour hot line, 80% the visiting nurses and doctors, and 69.4% the volunteer's help. The above results indicate that terminal patients and their family caregivers demand help from qualified health professionals whenever necessary. Hospice care system led by well-trained medical and nursing staffs is one of the viable answers for such demands.

• Management & Information Systems Review
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• v.36 no.4
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• pp.33-51
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• 2017

With the advent of 'The Forth Industrial Revolution' and the growing demand for quality of life due to economic growth, needs for the quality of medical services are increasing. Artificial intelligence has been introduced in the medical field, but it is rarely used in chronic skin diseases that directly affect the quality of life. Also, atopic dermatitis, a representative disease among chronic skin diseases, has a disadvantage in that it is difficult to make an objective diagnosis of the severity of lesions. The aim of this study is to establish an intelligent severity recognition model of atopic dermatitis for improving the quality of patient's life. For this, the following steps were performed. First, image data of patients with atopic dermatitis were collected from the Catholic University of Korea Seoul Saint Mary's Hospital. Refinement and labeling were performed on the collected image data to obtain training and verification data that suitable for the objective intelligent atopic dermatitis severity recognition model. Second, learning and verification of various CNN algorithms are performed to select an image recognition algorithm that suitable for the objective intelligent atopic dermatitis severity recognition model. Experimental results showed that 'ResNet V1 101' and 'ResNet V2 50' were measured the highest performance with Erythema and Excoriation over 90% accuracy, and 'VGG-NET' was measured 89% accuracy lower than the two lesions due to lack of training data. The proposed methodology demonstrates that the image recognition algorithm has high performance not only in the field of object recognition but also in the medical field requiring expert knowledge. In addition, this study is expected to be highly applicable in the field of atopic dermatitis due to it uses image data of actual atopic dermatitis patients.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.126-138
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• 2017

Recently, the national interest in environment is increasing and for dealing with water environment-related issues swiftly and accurately, the demand to facilitate the analysis of water environment data using a GIS is growing. To meet such growing demands, a spatial network data-based stream network analysis map(Korean Reach File; KRF) supporting spatial analysis of water environment data was developed and is being provided. However, there is a difficulty in delineating catchment areas, which are the basis of supplying spatial data including relevant information frequently required by the users such as establishing remediation measures against water pollution accidents. Therefore, in this study, the development of a computer program was made. The development process included steps such as designing a delineation method, and developing an algorithm and modules. DEM(Digital Elevation Model) and FDR(Flow Direction) were used as the major data to automatically delineate catchment areas. The algorithm for the delineation of catchment areas was developed through three stages; catchment area grid extraction, boundary point extraction, and boundary line division. Also, an add-in catchment area delineation module, based on ArcGIS from ESRI, was developed in the consideration of productivity and utility of the program. Using the developed program, the catchment areas were delineated and they were compared to the catchment areas currently used by the government. The results showed that the catchment areas were delineated efficiently using the digital elevation data. Especially, in the regions with clear topographical slopes, they were delineated accurately and swiftly. Although in some regions with flat fields of paddles and downtowns or well-organized drainage facilities, the catchment areas were not segmented accurately, the program definitely reduce the processing time to delineate existing catchment areas. In the future, more efforts should be made to enhance current algorithm to facilitate the use of the higher precision of digital elevation data, and furthermore reducing the calculation time for processing large data volume.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.35-51
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• 2012

Cloud computing is internet-based computing where computing resources are offered over the Internet as scalable and on-demand services. In particular, in case a number of various cloud services emerge in accordance with development of internet and mobile technology, to select and provide services with which service users satisfy is one of the important issues. Most of previous works show the limitation in the degree of user satisfaction because they are based on so called concept similarity in relation to user requirements or are lack of versatility of user preferences. This paper presents cloud service selection reasoning which can be applied to the general cloud service environments including a variety of computing resource services, not limited to web services. In relation to the service environments, there are two kinds of services: atomic service and composite service. An atomic service consists of service attributes which represent the characteristics of service such as functionality, performance, or specification. A composite service can be created by composition of atomic services and other composite services. Therefore, a composite service inherits attributes of component services. On the other hand, the main participants in providing with cloud services are service users, service suppliers, and service operators. Service suppliers can register services autonomously or in accordance with the strategic collaboration with service operators. Service users submit request queries including service name and requirements to the service management system. The service management system consists of a query processor for processing user queries, a registration manager for service registration, and a selection engine for service selection reasoning. In order to enhance the degree of user satisfaction, our reasoning stands on basis of the degree of conformance to user requirements of service attributes in terms of functionality, performance, and specification of service attributes, instead of concept similarity as in ontology-based reasoning. For this we introduce so called a service attribute graph (SAG) which is generated by considering the inclusion relationship among instances of a service attribute from several perspectives like functionality, performance, and specification. Hence, SAG is a directed graph which shows the inclusion relationships among attribute instances. Since the degree of conformance is very close to the inclusion relationship, we can say the acceptability of services depends on the closeness of inclusion relationship among corresponding attribute instances. That is, the high closeness implies the high acceptability because the degree of closeness reflects the degree of conformance among attributes instances. The degree of closeness is proportional to the path length between two vertex in SAG. The shorter path length means more close inclusion relationship than longer path length, which implies the higher degree of conformance. In addition to acceptability, in this paper, other user preferences such as priority for attributes and mandatary options are reflected for the variety of user requirements. Furthermore, to consider various types of attribute like character, number, and boolean also helps to support the variety of user requirements. Finally, according to service value to price cloud services are rated and recommended to users. One of the significances of this paper is the first try to present a graph-based selection reasoning unlike other works, while considering various user preferences in relation with service attributes.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• The Journal of KAIRB
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• v.3 no.2
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• pp.19-27
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• 2021

Purpose: This study aimed to analyze the knowledge levels, attitudes, and factors affecting the choices on the education of the participants who completed their education of persons conducting clinical trial workers, and to assess the problems of the current education system for clinical trial workers, leading to improvements. Methods: Clinical trial workers (including principal investigators/subinvestigators, members of the Institutional Review Board [IRB], clinical research coordinators) who were affiliated to one of the 4 university hospitals running their own clinical trial center and IRB in Daegu and completed their education of persons conducting clinical trial workers were the subjects of this study. One hundred seven online questionnaires were answered from 2021-04-02 to 2021-04-17. Descriptive statistics and Pearson correlation analysis were used to analyze the acquired data. Independent t-test and 1-way analysis of variance were used to analyze the differences in the knowledge levels and attitudes following the characteristics of the education participants. Results: The baseline characteristics of the 107 participants were as follows: the majority of the participants were female (72.0%), were in their 30s (36.4%), had a nursing major (29.0%), were clinical research coordinators (63.6%), had never experienced a principal investigator (79.4%), had participated 3 or more educations (58.9%), had completed their maintenance course (55.1%), had 5 or more years of clinical trial experiences (34.6%). The fields on which participants had low levels of objective knowledge were "types and preparations on audits of clinical trials," "regulations on clinical trials (Pharmaceutical Affairs Act, Korea Good Clinical Practice)." The difficulties that the participants faced were on "annual educations" and "lack of information regarding the educations." Factors that showed significant differences in objective knowledge were sex (p=0.02), number of educations (p=0.004), the curriculum of 2020 (p=0.001). Age (p=0.004), having experienced a principal investigator (p=0.006), number of educations (p<0.001), the curriculum of 2020 (p<0.001), clinical trial career (p=0.001) were factors that significantly affected subjective knowledge. Attitudes toward the education were positively correlated with objective knowledge (r=0.20, p=0.04) and subjective knowledge (r=0.32, p=0.001). Major sources through which information on educations was acquired were "institutional notices," and major factors affecting the choices on the education were "when the education took place" and "where the education took place." "Within the affiliated institution," "Online classes (recorded)" and "IRB and review processes" were each the most preferred place, mode, and content of the education. Conclusion: Knowledge levels varied largely among participants who completed their education of persons conducting clinical trial workers, depending on their characteristics such as the number of educations. Participants also complained about their lack of information on educations. The quality of education may be improved if clinical trial organizations are designated as education facilities. Education programs must be developed considering the knowledge level and demand of the participants. Furthermore, as offline classes may be impossible due to pandemics such as the coronavirus disease 2019, the development of diverse and sophisticated online classes is looked forward to.