• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1496-1521
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• 2012

Uncertainty is ubiquitous in target tracking wireless sensor networks due to environmental noise, randomness of target mobility and other factors. Sensing results are always unreliable. This paper considers unreliability as it occurs in wireless sensor networks and its impact on target-tracking accuracy. Firstly, we map intersection pairwise sensors' uncertain boundaries, which divides the monitor area into faces. Each face has a unique signature vector. For each target localization, a sampling vector is built after multiple grouping samplings determine whether the RSS (Received Signal Strength) for a pairwise nodes' is ordinal or flipped. A Fault-Tolerant Target-Tracking (FTTT) strategy is proposed, which transforms the tracking problem into a vector matching process that increases the tracking flexibility and accuracy while reducing the influence of in-the-filed factors. In addition, a heuristic matching algorithm is introduced to reduce the computational complexity. The fault tolerance of FTTT is also discussed. An extension of FTTT is then proposed by quantifying the pairwise uncertainty to further enhance robustness. Results show FTTT is more flexible, more robust and more accurate than parallel approaches.

• The Journal of the Korea Contents Association
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• v.15 no.2
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• pp.139-150
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• 2015

This study highlighted influences which affect purchase intention of audience to viewing performance. And after grouping audience types by applying the cluster analysis to samples which are collected by survey, this study examined how purchase intentions influence audience to viewing performance by each audience type. Thus, to improve the reliability to classify audience type, the sample was selected by considering neither age group nor previous experience of viewing performance arts. Factor analysis and reliability analysis was performed to analyze the effect of purchase intention according to the type of audience. And we used AMOS program to verify using SEM(Structural Equation Modeling) how affect it was with moderating variable of audience type. Through surveying and analyzing th results, we confirmed that viewing motivation and quality of performing work have significant effect on purchase intention and significant moderating effect according to audience type. Therefore, we contribute to make suitable strategy that they figure out audience type, when performing art organizations make marketing strategy.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.295-303
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• 2021

The relevance of the research is due to the fact that the issue of poverty is one of the most acute social problems of the beginning of the third millennium. The phenomenon of poverty is widespread in third world countries as well as it is observed in relatively developed countries. Poverty rates in Latin America are threatening. Consequently, the issue of social and economic inequality in these countries has become extremely acute. The purpose of the research: to identify the causes of poverty and social inequality and substantiate the main directions of poverty reduction in third world countries. The research methods: comparative analysis; index method; systematization; grouping; generalization. Results. The classification of the causes of poverty has been carried out and the directions of its overcoming in the countries of Latin America on groups of indicators have been defined, namely: 1) political; 2) economic; 3) demographic; 4) regional-geographical; 5) social; 6) qualification; 7) personal. Based on the Net Domestic Product indicator, a comparison of economic indicators of the studied countries has been carried out. It has been revealed that from 1990 to 2018 income inequality increased in 52 of 119 countries studied, and decreased in 57 states. Inequality has increased in the world's most populous countries, particularly China and India. In general, countries with growing inequality are home to more than two-thirds (71%) of the world's population. Trends in the distribution of income in the world have been investigated by applying the Gini index, the high level of which is observed in Latin America (Colombia 48,9%, Panama 46,1%, Chile and Mexico 45,9%). The forecast of the impact of the Covid-19 pandemic on this issue has been outlined; the ways of its impact on the economies of the countries have been studied. As a result of the study, the main directions and mechanisms of the strategy for poverty reduction and social inequality in the third world countries have been identified. The implementation of the poverty reduction strategy presented in this academic paper may have a positive impact on the economic situation of the population of Latin American countries.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2756-2766
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• 2024

Small rod-controlled pressurized water reactors (PWR) are the ideal energy source for vessel propulsion, benefiting from their high reactivity control efficiency. Since the control rods (CRs) increase the complexity of reactivity control, this paper seeks to study the performance of CRs in small rod-controlled PWRs to extend the lifetime and reduce power offset due to CRs. This study investigates CR grouping, move-in/out strategies, and axially non-uniform design effects on core neutron physics metrics. These metrics include axial offset (AO), core lifetime (CL), fuel utilization (FU), and radial power peaking factor (R-PPF). To simulate the movement of the CRs, a "Critical-CR-burnup" function was developed in OpenMC. In CR designs, the CRs are grouped into three banks to study the simultaneous and prioritized move-in/out strategies. The results show CL extension from 590 effective full power days (EFPDs) to 638-698 EFPDs. A lower-worth prioritized strategy minimizes AO and the extremum values decrease from -0.69 and + 0.81 to -0.28 and + 0.51. Although an axially non-uniform CR design can improve AO at the beginning of cycle (BOC), considering the overall CR worth change is crucial, as a significant decrease can adversely impact axial power distribution during the middle of cycle (MOC).

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.125-130
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• 2010

Cooperative learning is a successful teaching strategy in which small teams, each with students of different levels of ability, use a variety of learning activities to improve their understanding of a subject. Each member of a team is responsible not only for learning what is taught but also for helping teammates learn, thus creating an atmosphere of achievement. In this study, we have propose an english, math education program to the children of elementary school and cooperative learning program technique was applied to implement the program. By cooperative learning program, learners will be performed at the same time learning cooperatively. Finally, we have implement a prototype of cooperative learning program and take a usability test with elementary school children. A complementary team to score and mixed was found to be most effective.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.4
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• pp.708-725
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• 2018

The advancement of digital technology has made changes in the fashion system and trend development process inevitable. This article clarifies changes in the modern fashion industry system and the causes of comprehensive changes that result from the development of digital technology. The methodology of this study is based on literature and case studies based on the information magazine most used by fashion industry workers. This study classifies fashion systems into 5 types and 14 types in detail. The study results indicate the way to change the fashion style trend schedule per year, fast/ultrafast fashion system, fashion rental system, DTC system and change of fashion system by consumer participation. The causes of the changes in fashion system are indicated that an increase of trend sensitivity due to an increase in the diffusion rate of information, expansion of expression of personality through digital network, increase of possibility of grouping of small number of tastes and change of prosumer possible changes in the environment. This study provides basic data on fashion system research and the construction of an appropriate response strategy for a changing environment.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.5
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• pp.500-505
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• 2012

Recently, a high speed spindle is an essential part of machine tools to satisfy latest demand of high precision product and machining of hard materials. But, there are many disadvantages such as heat generation of built-in-motor, bearing friction, noise, vibration and displacement because of the high speed. Many researches on spindle systems have been conducted for solving these problems. In this study, technical trend of machine tools spindle systems are analyzed with patent PSM, mapping and grouping. The analysis is carried out for the applied patent during January 2000 and December 2009 in Korea, Japan, EU and U.S.A. And development of the direction, strategy and promising technologies of the spindle system are suggested.

• Journal of Soil and Groundwater Environment
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• v.16 no.6
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• pp.1-9
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• 2011

A bibliographical review of Gy sampling theory for particulate materials was conducted to provide readers with useful means to reduce errors in soil contamination investigation. According to the Gy theory, the errors caused by the heterogeneous nature of soil include; the fundamental error (FE) caused by physical and chemical constitutional heterogeneity, the grouping and segregation error (GE) aroused from gravitational force, long-range heterogeneous fluctuation error ($CE_2$), the periodic heterogeneity fluctuation error ($CE_3$), and the materialization error (ME) generated during physical process of sample treatment. However, the accurate estimation of $CE_2$ and $CE_3$ cannot be estimated easily and only increasing sampling locations can reduce the magnitude of the errors. In addition, incremental sampling is the only method to reduce GE while grab sampling should be avoided as it introduces uncertainty and errors to the sampling process. Correct preparation and operation of sampling tools are important factors in reducing the incremental delimitation error (DE) and extraction error (EE) which are resulted from physical processes in the sampling. Therefore, Gy sampling theory can be used efficiently in planning a strategy for soil investigations of non-volatile and non-reactive samples.

• Journal of Information Technology Applications and Management
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• v.12 no.3
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• pp.111-128
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• 2005

This paper examines the validity of the newly developed IT consulting SERVQUAL measurement tool. In an attempt to measure Ire IS customers' expectations and perceived quality of the services they received, the researchers developed a diagnostic tool of SERVQUAL based on the solid theoretical background, which can specifically be applied to the IT consulting service sector. This on-going research so far, has been applied to six (6) different organizations that have received IT consulting services over the past years. From the preliminary data collected, the correlation and the factor analyses were conducted to understand the underlying concept and refinement of the measurement tool. Although the correlation analysis showed a little tendency of collinearity among some of the variables, all showed sound relationship of the proposed hypotheses. The exploratory factor analytic approach was chosen because it does not set any priori constraints on the estimation of components or the number of components to be extracted. The number of different factor solutions was extracted and tested to see which solution represents better grouping of the variables. The Crombach's Alpha was computed on different combinations of the factor solutions to ensure validity. The results show 8-dimensional IT consulting SERVQUAL measures which they are, assurance, knowledge & skill, customer relationship, support, empathy, process management, expertise, and education, seem more appropriate than the originally proposed 6 dimensions. The study approach was non-experimental cross-sectional research design. The longitudinal design of follow-up studies to periodically revise and refine current measure is strongly recommended for fine tuning of the tool.