• Journal of Practical Engineering Education
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• v.6 no.2
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• pp.71-76
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• 2014

Improving lecture quality is very necessary for the service quality of education in universities, enterprises and education institutes. The student lecture evaluation survey data is a good tool for measuring lecture quality and have been often analyzed by simple statistical methods. This study presents an intelligent lecture quality improvement method that can improve student's overall satisfaction and performance by analyzing student lecture evaluation survey data. The method uses SOFM (Self-Organizing Feature Map) neural network and C4.5 to find the patterns in student's satisfaction and performance more correctly and then decide what to change in the lecture for the improvement of student's satisfaction and performance. We apply the proposed method to an enterprise lecture in Korea. We can find that it can improve the quality of an enterprise lecture by changing total lecture time, lecture material and organization of lecture schedule to be necessary improvements.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.79-90
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• 2023

Leadership development corresponds to the focus on the individual's success and competitiveness strategy. This is the optimal direction of the organization of attitude development because it covers two aspects of the student's personality development, professionally-oriented and self-centric. The aim of the study is to identify and compare the leadership level in second-and fourth-year students to see dynamics of development and implementation of the leadership phenomenon in the professional and personal making up of future specialists. Based on the theoretical analysis of the issue, the authors developed an objective and subjective diagnostic model for leadership skills. In this study, data of the objective diagnostic technique are the key. Subjective diagnostic technique for leadership skills provides insights for problem interpretation. At the level of the first group of respondents, the average Leadership Skills Level of the second-year students was quite low and was found within the medium level. The second group of respondents consisting of the fourth-year students showed a slight but effective improvement. The Leadership Skills of this group were found at a sufficient level. Positive dynamics was revealed for all criteria of leadership skills as a result of applying objective diagnostic methods: decreased percentage of students with negative and relatively low markers of Leadership Skills Level and corresponding increase in percentage of applicants with positive markers of Leadership Skills Level. Further research can be organized in the direction of identifying and developing successful universal and professionally-oriented tactics for leadership development in students as part of attitude development.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.2
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• pp.175-181
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• 2006

Wireless sensor network forms the self-organization network, and transfers the information among sensor nodes that have computing technology ability and wireless communication ability. The recent sensor network is study for low-power, micro, low cost of node is proceeded. Recently, the research of application services in wireless sensor networks is proceeded. Therefore, in this paper, we design the prototype of the real-time information service that support a user the information of temperature, illumination etc. And, we implement the alarm application service fer the disaster prevention on Internet base on IPv4/IPv6. We develop the module of the extract information using the query processing based on TinyOS, and the module of the server's database using MySQL data base management system and JDBC. Additionally, we develop the client module that receive the real-time sensing data using ODBC in Internet based on IPv4/IPv6.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.703-713
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• 2022

Accurate and rapid establishment of mobile communication is important in mobile communication system. Currently, the base station parameters to establish a network are determined by cell planning tool. However, it is necessary to perform new cell planning for each new installation of the base station, and there may be a problem that parameters are not suitable for the actual environment are set, such as obstacle information that is not applied in the cell planning tool. In this paper, we proposed methods for path loss prediction using DNN and topographical division using CNN in SON server. After topography classification, a SON server configures the base station parameters according to topography, and update parameters for each topography. The proposed methods can configure the base station parameters automatically that are considered topography information and environmental changes.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.172-180
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• 2009

This study considers some changes in the program production by the local broadcasting stations through the analysis of their programs. Currently, one of the biggest changes in the local broadcasting systems is that they focus on the self-produced contents about the community and expand the joint-production. In the case of KBS Daejeon, they try to activate various joint-produced programs together with the local broadcasting stations in Yeongnam province. MBC Daejeon has also strengthened the joint-production systems since 2002 by classifying MBC's 19 subsidiary stations around the country into 5 groups in order to strengthen the competitiveness. As for TJB, they work in the cooperation with other commercial broadcasting stations in other cities, including Busan, Kwangju, Jeonju, Ulsan, Daegu by sharing the programs which they produced. In conclusion, the local broadcasting systems should depart from the function as a mediating center of the central broadcasting network and strengthen the ability of producing programs in order to be able to function as a source of producing programs. Thus, local broadcasting stations should expand the joint production of the programs about the communities and the ratio of the organization of the self-produced programs.

• Journal of IKEEE
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• v.20 no.2
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• pp.177-180
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• 2016

The effect of varying thickness of Ag/Ti metal bilayer and annealing time have investigated for controlling self-organized nanoparticles (NPs) on 4H-SiC substrate. In addition, Glass and Si substrate which have different surface energy from SiC were fabricated for analyzing interaction of agglomeration. The results of FE-SEM indicated the different formation behaviors of NPs in various ranges of fabrication condition. The surface energy was measured by using a Contact Angle Analyzer. The formation of network-like NPs was observed on Glass and 4H-SiC, respectively, whereas it was not the case on Si substrates. It has been found that the size of NPs increases with decreasing surface energy, due to particle size-dependent hydrophilic properties of substrates. The different formation behavior was explained by using Young's equation for the contact angles between the metal and different substrates.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.78-89
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• 1999

Previous wavelet network structures are determined by considering the relationship between wavelet windows distribution of training patterns that are transformed into time-frequency space. Because it is separated two algorithms that determines wavelet network structure and that modifies parameters of network, learning process that minimizes output error of network is executed after the network structure is determined. But this method has some weakness that training patterns must be transformed into time-frequency space by additional preprocessing and the network structure should be fixed during learning process. In this paper, we propose a new constructing method for wavelet network structure by using differences between the output and the desired response without preprocessing. Because the algorithm perform network construction and error minimizing process simultaneously, it can determine the number of hidden nodes adaptively as with the complexity of problems. In addition, the network structure is optimized by inserting new hidden nodes in the area that has maximum error and extracting hidden nodes that has no effect to the output of network. This algorithm has no constraint condition that all training patterns must be known, because it removes preprocessing procedure for training patterns and it can be applied effectively to systems that has time varying outputs.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.316-321
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• 2007

The casualties due to slope failures such as landslide, rock fall, debris flow etc. are about 24% in total casualties caused by natural disasters for the last 10 years. And these slope failures are focused in the season in which typhoon and torrential rain take place. Not much attention, however, have been put into landslide mitigation research. Meanwhile, USN(Ubiquitous Sensor Network) forms the self-organization network, and transfers the information among sensor nodes that have computing technology ability. Accordingly, USN is embossed a social point technology. The objective of this paper is to develop a prototype system for slope failure monitoring using USN technology. For this we develop module that collects and change slope movement data measured by two tiltermeter and a tension wire, store transferred data in database. Also we develop application program that can easily analyze the data. We apply the prototype system to a test site at KICT for testing and analyzing the system's performance.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1575-1583
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• 2008

Wireless sensor network has merit of low-power, low-cost and self-organization network, so there are many researches substituted for existing wire network. As structure reinforcement work need a high accuracy, many sensors are installed in structure and connected with data logger for monitoring. However this wire data logger method takes a long time to install wires and installed wires obstruct to work. Additionally, wire data logger method represent sensor data by only numeric and graph, it is not able to support a rapid decision-making for working. To resolve wiring problem and support decision-making, we designed and implemented the monitoring system based in wireless sensor network. For verifying performance, accuracy and availability, we simulated and tested our system in real field. Consequently, wireless sensor network method is easier to install and deploy than wire data logger method, user is able to monitor instinctively and overall by 3D representation of structure and sensors, and it show not only accuracy but also performance for many sensors.