• Hwankyungkyoyuk
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• v.19 no.2 s.30
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• pp.133-146
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• 2006

The purpose of this study was to examine how environmental education teachers think about environmental teaching materials of their use in primary and secondary schools. For this purpose, six primary and secondary school teachers were selected for focus group discussion on October 17th, 2005. The discussion of focus group was recorded both on video and audio tapes. Teachers' discussion could be analyzed in the perspectives of two big ideas, 'content selection' and 'content organization and presentation'. The big ideas were categorized into several areas: 1) The idea of 'content selection' was classified into 4 areas such as integration, difficulty level, locality, and timeliness, 2) The idea of 'content organization and presentation' was classified into 4 areas such as learning motivation, teaching and teaming strategy, evaluation method, application of teaching materials. This study provided meaningful ideas, which can be used in developing environmental education materials as well as effective teaching and teaming strategies for school environmental educators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1348-1375
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• 2018

Support Vector Machine (SVM) is a well-known machine learning classification algorithm, which has been widely applied to many data mining problems, with good accuracy. However, SVM classification speed decreases with increase in dataset size. Some applications, like video surveillance and intrusion detection, requires a classifier to be trained very quickly, and on large datasets. Hence, this paper introduces two filter-based instance selection techniques for optimizing SVM training speed. Fast classification is often achieved at the expense of classification accuracy, and some applications, such as phishing and spam email classifiers, are very sensitive to slight drop in classification accuracy. Hence, this paper also introduces two wrapper-based instance selection techniques for improving SVM predictive accuracy and training speed. The wrapper and filter based techniques are inspired by Cuckoo Search Algorithm and Bat Algorithm. The proposed techniques are validated on three popular e-fraud types: credit card fraud, spam email and phishing email. In addition, the proposed techniques are validated on 20 other datasets provided by UCI data repository. Moreover, statistical analysis is performed and experimental results reveals that the filter-based and wrapper-based techniques significantly improved SVM classification speed. Also, results reveal that the wrapper-based techniques improved SVM predictive accuracy in most cases.

• IE interfaces
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• v.18 no.3
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• pp.253-267
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• 2005

Customer satisfaction becomes one of the important managerial concerns associated with corporate competency in current competitive environment for Internet communication service companies. Hence, it is demanding to improve a company's customer satisfaction through the total quality management perspective. In practice, engineers as well as the management hope to find major quality characteristics with Internet communication network that is closely related to customer satisfaction, consequently aiming to the raise of their company's customer satisfaction. This paper presents an empirical relationship analysis between network quality characteristics and customer satisfaction on Internet communication. Methodologically, the relationship analysis framework is based on the regression variable selection procedures. In this framework, it is implemented that; 1) iterative model building; and 2) consistent criteria application to statistical tests for selecting significant variables. A case study shows that; 1) the customer satisfaction on the network connection seems to be more closely related to the network quality characteristics compared with the customer satisfaction on the network speed; and 2) the download disconnection rate has relatively evident relationship with the customer satisfaction on the network connection.

• The KSFM Journal of Fluid Machinery
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• v.10 no.5
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• pp.20-26
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• 2007

Some gate valves are susceptible to pressure locking and thermal binding which prevent the safety function. The safety related gate valves susceptible to pressure locking and thermal binding shall be identified and taken preventive actions to ensure the safety function. The identification of the gate valves susceptible to pressure locking and thermal binding needs the evaluation of system design, valve and piping arrangement, test requirements, and operating conditions. Application of preventive methods should consider the system safety function, applicability, effectiveness, interface with system design, and cost. The selection procedure of valves susceptible to pressure locking and thermal binding can be effectively used in industry including nuclear power plants. In order to prevent the pressure locking, the hole can be drilled through the one disc of upstream side or down stream and the external equalizing line can be installed from bonnet to downstream or upstream. The double disc parallel seat valve type can be used instead of flexible wedge gate valve to prevent the thermal binding. The identification of gate valves susceptible to pressure locking and thermal binding, and preventive actions will meet the regulatory requirements and enhance the availability and safety of plants.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1706-1718
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• 1997

The rapid increase in the use of many commercial software products has necessitated a systematic and objective method of their evaluation and selection. Our study focuses on the assignment of weights and choice of proper models. First, the weights of attributes are assigned consistently by using the analytic hierarchy process. Second, many models, which can be suitable for the structure of evaluation and selection for software product, are collected, categorized into two types of model, and compared in terms of their strength and weakness. The models involved are four compensatory models and seven noncompensatory models. Finally, they are analyzed through the application of specific software products(database data modelers) in terms of their attributes. Our study enhances the applicability of models to a variety of user requirement utilizing the evaluating procedure and applications.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.1
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• pp.121-131
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• 2004

Transportation and logistics of agricultural products have been one of the major interests of many researches. Most of researches have been limited to presuming these as a first dimensional process or considering only economic value of agricultural products at each stage of logistics. However, the particular characteristics of agricultural products, such as quality change during transportation or extensively scattered origins, require examining these problems as a whole system. Network model has been adopted to represent nodes, which stand for spatial location of demand and supply of agricultural products, and communication between these nodes. Based on network theory and advanced marketing potential function, an optimal routes selection model is developed. The model employed network simplex method for routes optimization. The application of the model focused on transportation network organization to reflect different market prices for different locations and resulted in optimum routes and profit improvement of the applied agricultural product.

• Journal of Information Processing Systems
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• v.4 no.4
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• pp.121-132
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• 2008

VLSI chips have been tested using various automatic test equipment (ATE). Although each ATE has a similar structure, the language for ATE is proprietary and it is not easy to convert a test program for use among different ATE vendors. To address this difficulty we propose a tester structure expression language, a tester language with a novel format. The developed language is called the general tester language (GTL). Developing an interpreter for each tester, the GTL program can be directly applied to the ATE without conversion. It is also possible to select a cost-effective ATE from the test program, because the program expresses the required ATE resources, such as pin counts, measurement accuracy, and memory capacity. We describe the prototype environment for the GTL and the tester selection tool. The software size of the prototype is approximately 27,800 steps and 15 manmonths were required. Using the tester selection tool, the number of man-hours required in order to select an ATE could be reduced to 1/10. A GTL program was successfully executed on actual ATE.

• Food Science and Biotechnology
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• v.15 no.4
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• pp.485-493
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• 2006

Lactococcus species are noninvasive and nonpathogenic microorganisms that are widely used in industrial food fermentation and as well-known probiotics. They have been modified by traditional methods and genetic engineering to produce useful food-grade materials. The application of genetically modified lactococci in the food industry requires their genetic elements to be safe and stable from integration with endogenous food microorganisms. In addition, selection for antibiotic-resistance genes should be avoided. Several expression and secretion signals have been developed for the production and secretion of useful proteins in lactococci. Food-grade systems composed of genetic elements from lactic acid bacteria have been developed. Recent developments in this area have focused on food-grade selection markers, stabilization, and integration strategies, as well as approaches for controlled gene expression and secretion of foreign proteins. This paper reviews the expression and secretion signals available in lactococci and the development of food-grade markers, food-grade cloning vectors, and integrative food-grade systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5425-5448
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• 2018

Wireless sensor network has been widely used in Internet of Things (IoT) applications to support large and dense networks. As sensor nodes are usually tiny and provided with limited hardware resources, the existing multiple access methods, which involve high computational complexity to preserve the protocol performance, is not available under such a scenario. In this paper, we propose an intelligent Medium Access Control (MAC) protocol selection scheme based on machine learning in wireless sensor networks. We jointly consider the impact of inherent behavior and external environments to deal with the application limitation problem of the single type MAC protocol. This scheme can benefit from the combination of the competitive protocols and non-competitive protocols, and help the network nodes to select the MAC protocol that best suits the current network condition. Extensive simulation results validate our work, and it also proven that the accuracy of the proposed MAC protocol selection strategy is higher than the existing work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1128-1145
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• 2022

Owing to the rapid development of information science, data analysis based on machine learning has become an interdisciplinary and strategic area. Marine predators algorithm (MPA) is a novel metaheuristic algorithm inspired by the foraging strategies of marine organisms. Considering the randomness of these strategies, an improved algorithm called co-evolutionary cultural mechanism-based marine predators algorithm (CECMPA) is proposed. Through this mechanism, search agents in different spaces can share knowledge and experience to improve the performance of the native algorithm. More specifically, CECMPA has a higher probability of avoiding local optimum and can search the global optimum quickly. In this paper, it is the first to use CECMPA to perform feature subset selection and optimize hyperparameters in support vector machine (SVM) simultaneously. For performance evaluation the proposed method, it is tested on twelve datasets from the university of California Irvine (UCI) repository. Moreover, the coronavirus disease 2019 (COVID-19) can be a real-world application and is spreading in many countries. CECMPA is also applied to a COVID-19 dataset. The experimental results and statistical analysis demonstrate that CECMPA is superior to other compared methods in the literature in terms of several evaluation metrics. The proposed method has strong competitive abilities and promising prospects.