• Journal of Information Science Theory and Practice
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• v.7 no.4
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• pp.56-64
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• 2019

Planting intercropping in rubber plantations is another alternative for generating more income for farmers. However, farmers still lack the knowledge of choosing plants. In addition, information for decision making comes from many sources and is knowledge accumulated by the expert. Therefore, this research aims to create a decision support system for growing rubber trees for individual farmers. It aims to get the highest income and the lowest cost by using semantic web technology so that farmers can access knowledge at all times and reduce the risk of growing crops, and also support the decision supporting system (DSS) to be more intelligent. The integrated intercropping ontology and rule are a part of the decision-making process for selecting plants that is suitable for individual rubber plots. A list of suitable plants is important for decision variables in the allocation of planting areas for each type of plant for multiple purposes. This article presents designing and developing the intercropping ontology for DSS which defines a class based on the principle of intercropping in rubber plantations. It is grouped according to the characteristics and condition of the area of the farmer as a concept of the rubber plantation. It consists of the age of rubber tree, spacing between rows of rubber trees, and water sources for use in agriculture and soil group, including slope, drainage, depth of soil, etc. The use of ontology for recommended plants suitable for individual farmers makes a contribution to the knowledge management field. Besides being useful in DSS by offering options with accuracy, it also reduces the complexity of the problem by reducing decision variables and condition variables in the multi-objective optimization model of DSS.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.2
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• pp.73-80
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• 2013

Due to the fact that possible risk associated with soil-crop-food chain transfer, metal contamination in croplands has become a major topic of wide concern. Accumulation of toxic metals in edible parts of crops grown in contaminated soils has been reported from number of crops including rice, soybean, wheat, maize, and vegetables. Therefore, in order to ensure food safety, measures are needed to be taken in mitigating metal pollution and subsequent uptake by crop plants. Present paper critically reviewed some of the cost effective remediation techniques used in minimizing metal uptake by crops grown in contaminated soils. Liming with different materials such as limestone ($CaCO_3$), burnt lime (CaO), slaked lime [$Ca(OH)_2$], dolomite [$CaMg(CO_3)_2$], and slag ($CaSiO_3$) has been widely used because they could elevate soil pH rendering metals less-bioavailable for plant uptake. Zn fertilization, use of organic amendments, crop rotation and water management are among the other techniques successfully employed in reducing metal uptake by crop plants. However, irrespectively the mitigating measure used, heterogeneous accumulation of metals in different crop species is often reported. The inconsistency might be attributed to the genetic makeup of the crops for selective uptake, their morphological characteristics, position of edible parts on the plants in respect of their distance from roots, crop management practices, the season and to the soil characteristics. However, a sound conclusion in this regard can only be made when more scientific evidence is available on case-specific researches, in particular from long-term field trials which included risks and benefits analysis also for various remediation practices.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.29-45
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• 2009

In the information age, cheap price of information processing and advances in personalization technology have allowed companies to enhance the relationships with their existing customers and to expand their customer base by effectively attracting new customers. However, most customers are reluctant to provide their personal information to companies. This study explores the tension between companies' desire to collect personal information to offer personalized services and their customers' privacy concerns. The psychological reactance theory suggests that when individuals feel that their behavioral choice is threatened or restricted, they are motivated to restore their freedom. Therefore, despite the expected benefits from personalized services, customers may perceive the services to be restrictive of their freedom to choose. This adverse effect may undermine the relationships between companies and their customers. We conducted experiments to explore the dynamic roles of transactional and environmental factors in motivating customers to provide personal information. We revisited online privacy issues from the perspective of psychological reactance. For the experiments, we created an online shop and randomly assigned the participants to one of the two experimental conditions-high and low levels of information requirements. The results of the experiment indicate that threatening the free choice serves as a transactional cost in online profiling. On the other hand, the expected benefits of personalization services have positive correlations with customers' willingness to provide personal information. This study explains privacy based on transactional and environmental factors. Our findings also indicate that the environmental factors such as the Internet privacy risk and trust propensity do not significantly affect the willingness to provide personal information when firms required much personal information. Implications and contributions are discussed.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.119-124
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• 2017

Information is a valuable asset regardless of the size of the enterprise and information security is an essential element for the survival and prosperity of the enterprise. However, in the case of large corporations, Security is ensured through rapid introduction of information security management system. but In the case of SMEs, security systems are not built or construction is delayed due to complex factors such as budget constraints, insufficient security guidelines, lack of security awareness. In this paper, we analyze the actual situation of information security management of SMEs through questionnaires, and We would like to suggest a comprehensive security plan for SMEs in free or inexpensive ways. We believe that by applying the method presented in this paper, SMEs will be able to implement the lowest cost basic information security and will benefit SMEs who plan to establish an information security plan.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.295-298
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• 2014

In recently, a climatic change(such as subtropical climate and frequent unusual high temperature) and the open-trade policies of agricultural & livestock products are increasing the outbreak risk of highly pathogenic avian influenza(HPAI) and foot and mouth disease(FMD), and accordingly the socio-economic damage and impacts are also increasing due to the cases such as damage from the last 5 times of FMD outbreak(3,800 billion won), from 10 years public control cost of Pine Wilt Disease (PWD)(238.3 billion won), and from the increased invasive pests of exotic plant like isoptera. Therefore, the establishment of new operation strategy of IoT(Internet of Things) based satellite early warning system(SEWS) for plants and animals as a subsystem of national disaster response and management system is being required, where the forensic technology & measures should be applied as a government policy to estimate the post compensation and to carry out the legal responsibility.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.43-56
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• 2024

Purpose: The injection molding process, crucial for plastic shaping, encounters difficulties in sustaining product quality when replacing injection machines. Variations in machine types and outputs between different production lines or factories increase the risk of quality deterioration. In response, the study aims to develop a system that optimally adjusts conditions during the replacement of injection machines linked to molds. Methods: Utilizing a dataset of 12 injection process variables and 52 corresponding sensor variables, a predictive model is crafted using Decision Tree, Random Forest, and XGBoost. Model evaluation is conducted using an 80% training data and a 20% test data split. The dependent variable, classified into five characteristics based on temperature and pressure, guides the prediction model. Bayesian optimization, integrated into the selected model, determines optimal values for process variables during the replacement of injection machines. The iterative convergence of sensor prediction values to the optimum range is visually confirmed, aligning them with the target range. Experimental results validate the proposed approach. Results: Post-experiment analysis indicates the superiority of the XGBoost model across all five characteristics, achieving a combined high performance of 0.81 and a Mean Absolute Error (MAE) of 0.77. The study introduces a method for optimizing initial conditions in the injection process during machine replacement, utilizing Bayesian optimization. This streamlined approach reduces both time and costs, thereby enhancing process efficiency. Conclusion: This research contributes practical insights to the optimization literature, offering valuable guidance for industries seeking streamlined and cost-effective methods for machine replacement in injection molding.

• 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 the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6550-6557
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• 2013

The public road construction projects awarded by the regional construction and management office, which is an affiliate of the Ministry of Land, Infrastructure and Transport, are managed by construction supervision officers. These officials frequently visit a large number of construction sites to conduct inspections and supervision tasks. Therefore, the site management efficiency is essential in terms of the time and money spent in travelling to the sites. The introduction of a site monitoring management system is considered necessary to minimize the number of site visits and enable remote monitoring of the construction progress to enhance the business efficiency of the construction supervision officers. In this study, a remote site monitoring system was constructed using web cameras for public road construction works. The trial applications were implemented by selecting ten constructions sites. The effectiveness of the system was analyzed to assess its applicability. In an assessment of the applicability of the verification results, remote site monitoring showed cost savings of approximately 35% compared to the existing site management. The guidelines for applying the site monitoring management system were provided, the introduction plan was investigated, and the improvement method was presented. The results showed that the system is likely to minimize the unnecessary site visits, remove the risk factors at vulnerable areas in the sites beforehand, and prevent a range of disasters and accidents. In addition, the quality of the infrastructures is likely to improve through the prevention of accidents and the elimination of substandard and faulty construction work.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.2
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• pp.1-11
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• 2018

Recently ICT, new technologies such as IoT, Cloud, and Artificial Intelligence are changing the information society explosively. But personal information leakage incidents of consignee's company are increasing more and more because of the expansion of consignment business and the latest threats such as Ransomware and APT. Therefore, in order to strengthen the security of consignee's company, this study derived the checklists through the analysis of the status such as the feature of consignment and the security standard management system and precedent research. It also analyzed laws related to consignment. Finally we found out the relative importance of checklists after it was applied to proposed AHP(Analytic Hierarchy Process) Model. Relative importance was ranked as establishment of an internal administration plan, privacy cryptography, life cycle, access authority management and so on. The purpose of this study is to reduce the risk of leakage of customer information and improve the level of personal information protection management of the consignee by deriving the check items required in handling personal information of consignee and demonstrating the model. If the inspection activities are performed considering the relative importance of the checklist items, the effectiveness of the input time and cost will be enhanced.

• Journal of Korean Academy of Nursing Administration
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• v.7 no.2
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• pp.265-284
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• 2001

The case management has been applied to improve the quality of care and the cost-effectiveness in the most health care institutions. In a way of case management, the critical pathway(CP) has been executed in many acute care settings, focused on the diagnoses with high cost, high volume, and high risk. This study was conducted to develop a case management program using CP as an intervention of patients with lumbar spinal stenosis for the surgery of posterolateral fusion, and to find out the effects of the critical pathway on the quality of nursing care, patient satisfaction as an outcome of care, length of stay and medical charge, and nurses' job satisfaction. At the same time, patients' functional states were checked with the Oswestry Low Back Pain Index, to show that the CP would not decrease the patients' function compared to the control group. The subjects were 25 control patients with a usual operation of lumbar fusion and 25 experimental patients with CP. They were all female, aged $50s{\sim}70s$, admitted in the Orthopedic surgery ward of a university hospital. Also nurses on the floor using CP were asked to respond to measurement tool of job satisfaction before and after the application of CP, and compared with other nurses on the different wards. Data were analyzed with t-test for continuous variables and chi-square for non-parametric variables in addition to the reliability test of the measurement tools. The results of this study were as followings: 1. Patients' functional states The differences in Oswestry scores of the experimental and control groups assessed at preoperation and at discharge were not statistically significant. The change in scores of the experimental group measured at preoperation and at discharge was larger than that of the control group, however the difference was not statistically significant. The results indicate that the CP did not decrease the patients' functional status. 2. The quality of nursing care The total of quality of nursing care given to the experimental group was better than that of the control group(P=.000). In addition, the experimental group showed better scores of quality of every item of care than the control group(P=.000 -.004). 3. Patient satisfaction Patients of the experimental group were not more satisfied with general care than the control group. But they were more satisfied with discharge care of 'explanation about medication, body posture, and brace application' and 'explanation about the adjustment of daily living and exercise during recovery'(P= .047, P=.028). 4. Nurses' job satisfaction Nurses working with the CP showed more job satisfaction than before the CP introduction(P=.048). But the control group of nurses on a different floor showed no change in job satisfaction at the same period of time. 5. Length of stay and medical charge The mean length of stay of the experimental group was shorter than that of the control group without statistical significance. The charge of medication and treatment of the experimental group were smaller than that of the control group(P=.011, P=.000). The results of the study support that the case management using critical pathway enables to improve the quality of care and job satisfaction, to reduce the medical charge, and consequently to increase satisfaction with care. However, the case management should be instituted focusing on the quality improvement of nursing and the client satisfaction, not just for the purpose of cost-effectiveness of health care facilities.