• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.2
• /
• pp.609-625
• /
• 2023

This study is a demand research for the selection of public safety science and technology equipment and suggests an empirical research method. The technology demand survey is the beginning of the selection of innovative technology. And it is the basis of collecting information required for the technology required in the market and helping to apply it to the field. The demand survey for police science and technology can reduce the uncertainty of crime prevention and help the smooth implementation of security policies. However, in Korea, adoption of security science and technology equipment was centered on social issues or researchers' opinions rather than the demands of field users. Until, there was no research has been conducted on the demands of field police officers for selection of security science and technology equipment in Korea. Also, there was no preferential study for the demand for security science and technology equipment. Therefore, this study proposes a methodology that can systematically identify the needs for the technology and equipment of field experts suitable for the public security situation for the selection of security science and technology equipment. Specifically, we propose a sample design for a technology classification system and a survey tool for technology awareness and satisfaction. It is expected that this tool will provide a classification system for security science and technology equipment selected for the Korean police and will help determine the priority of equipment suitable for the field.

• Genomics & Informatics
• /
• v.20 no.4
• /
• pp.48.1-48.7
• /
• 2022

Penalized regression has been widely used in genome-wide association studies for joint analyses to find genetic associations. Among penalized regression models, the least absolute shrinkage and selection operator (Lasso) method effectively removes some coefficients from the model by shrinking them to zero. To handle group structures, such as genes and pathways, several modified Lasso penalties have been proposed, including group Lasso and sparse group Lasso. Group Lasso ensures sparsity at the level of pre-defined groups, eliminating unimportant groups. Sparse group Lasso performs group selection as in group Lasso, but also performs individual selection as in Lasso. While these sparse methods are useful in high-dimensional genetic studies, interpreting the results with many groups and coefficients is not straightforward. Lasso's results are often expressed as trace plots of regression coefficients. However, few studies have explored the systematic visualization of group information. In this study, we propose a multi-level polar Lasso (MP-Lasso) chart, which can effectively represent the results from group Lasso and sparse group Lasso analyses. An R package to draw MP-Lasso charts was developed. Through a real-world genetic data application, we demonstrated that our MP-Lasso chart package effectively visualizes the results of Lasso, group Lasso, and sparse group Lasso.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.6C
• /
• pp.560-569
• /
• 2005

This paper proposes an algorithm for transmit antenna selection in a multi-input multi-output(MIMO) spatial multiplexing system with per antenna rate control(PARC) and an ordered successive interference cancellation (OSIC) receiver. The active antenna subset is determined at the receiver and conveyed to the transmitter using feedback information on transmission rate per antenna. We propose a serial decision procedure consisting of a successive process that tests whether antenna selection gain exists when the antenna with the lowest pre-processing signal to interference and noise ratio(SINR) is discarded at each stage. Furthermore, we show that 'reverse detection ordering', whereby the signal with the lowest SINR is decoded at each stage of successive decoding, widens the disparities among fractions of the whole capacity allocated to each individual antenna and thus maximizes a gain of antenna selection. Numerical results show that the proposed reverse detection ordering based serial antenna selection approaches the closed-loop MIMO capacity and that it induces a negligible capacity loss compared with the heuristic selection strategy even with considerably reduced complexity.

• The KIPS Transactions:PartD
• /
• v.14D no.5
• /
• pp.459-470
• /
• 2007

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Query processing for such a data stream should also be continuous and rapid, which requires strict time and space constraints. In most DSMS(Data Stream Management System), the selection predicates of continuous queries are grouped or indexed to guarantee these constraints. This paper proposes a new scheme tailed an ASC(Attribute Selection Construct) that collectively evaluates selection predicates containing the same attribute in multiple continuous queries. An ASC contains valuable information, such as attribute usage status, partially pre calculated matching results and selectivity statistics for its multiple selection predicates. The processing order of those ASC's that are corresponding to the attributes of a base data stream can significantly influence the overall performance of multiple query evaluation. Consequently, a method of establishing an efficient evaluation order of multiple ASC's is also proposed. Finally, the performance of the proposed method is analyzed by a series of experiments to identify its various characteristics.

• Journal of the Korean Chemical Society
• /
• v.55 no.6
• /
• pp.1030-1041
• /
• 2011

We investigated the understanding of pre-service science teacher about the chemistry concept of middle school curriculum using some items in National Assessment of Educational Achievement and analyzed the result according to background variables of pre-service science teacher. The result was that there were some pre-service science teachers who select incorrect answer at all items, pre-service science teachers don't fully understand the concept needed to solve item. And the percentage of correct answer at some items was low regardless of selection of chemistry as an elective subject at CSAT(College Scholastic Ability Test). We found some facts through the depth interviews to find the cause of the result. First, the misconception acquired in middle school days is tend not to change until college student. Second, the formation of misconception is affected by the study habit with which solve problem by simple calculation and memory without essential understanding. Third, the study habit with which solve problem by simple calculation and memory without essential understanding could not replace misconceptions acquired in middle school days with scientific concept regardless of selection of chemistry as an elective subject at CSAT.

• KIPS Transactions on Software and Data Engineering
• /
• v.9 no.12
• /
• pp.411-418
• /
• 2020

In the field of information security, IDS(Intrusion Detection System) is normally classified in two different categories: signature-based IDS and anomaly-based IDS. Many studies in anomaly-based IDS have been conducted that analyze network traffic data generated in cyberspace by machine learning algorithms. In this paper, we studied pre-processing methods to overcome performance degradation problems cashed by rare classes. We experimented classification performance of a Machine Learning algorithm by reconstructing data set based on rare classes and semi rare classes. After reconstructing data into three different sets, wrapper and filter feature selection methods are applied continuously. Each data set is regularized by a quantile scaler. Depp neural network model is used for learning and validation. The evaluation results are compared by true positive values and false negative values. We acquired improved classification performances on all of three data sets.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• autumn
• /
• pp.19-26
• /
• 2003

In the face of the deterioration of tobacco manufacturing plant, we've got the plan for now manufacturing factory for the competitiveness, modernization, rationalization and environment. To achieve the goals, it was necessary to plan and investigate in the early stage of project. Consequently. We determined to introduce the CM in the early stage. We Performed the whole phase of CM services front the pre design phase services like feasibility analysis of site and building, plant master plan, selection of manufacturing facilities and drawing up the RFP, to maintenance management phase after the completion of a construction work. Contrary to the another CM projects, YongJu New Tobacco Manufacturing Plant CM organized the CM team with expert in field before the design development. This study analyze and evaluate the CM services of YongJu project which performed on the pre design phase. The purpose of this study is to emphasize the importance of pre design phase CM and support that CM services will start from the pre design phase.

• Proceedings of the KSR Conference
• /
• 2011.10a
• /
• pp.589-594
• /
• 2011

Selecting an appropriate railway system in urban railway project is an important step for an efficient public transport policy. This paper attempts to solve the railway system selection problems in the (pre)feasibility study or preliminary research of urban railway project, by the rough transportation demand forecasting and financial analysis. There are two stages in this paper: in stage one, we review the worthwhile and various criteria which presented in precedent studies; whereas in stage two, an structured selection criteria is proposed for determining the appropriate railway system in urban railway project. The utilization of the proposed criteria is demonstrated with the case of a newtown in the metropolitan area. The results show that proposed criteria can be used to make the rational decision for governmental financial condition and social benefit.

• Proceedings of the KSPS conference
• /
• 2002.11a
• /
• pp.183-186
• /
• 2002

The speech detection is one of the important problems in real-time speech recognition. The accurate detection of speech boundaries is crucial to the performance of speech recognizer. In this paper, we propose a speech detector based on Mel-band selection through training. In order to show the excellence of the proposed algorithm, we compare it with a conventional one, so called, EPD-VAA (EndPoint Detector based on Voice Activity Detection). The proposed speech detector is trained in order to better extract keyword speech than other speech. EPD-VAA usually works well in high SNR but it doesn't work well any more in low SNR. But the proposed algorithm pre-selects useful bands through keyword training and decides the speech boundary according to the energy level of the sub-bands that is previously selected. The experimental result shows that the proposed algorithm outperforms the EPD-VAA.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.33 no.8
• /
• pp.813-818
• /
• 2009

Design analysis and computer experiments (DACE) model is widely used to express efficiently nonlinear responses in the field of engineering design. As a DACE model, kriging model can approximately replace a simulation model that is very expensive or highly nonlinear. The kriging model is composed of the summation of a global model and a local model representing deviation from the global model. The local model is determined by correlation coefficient with the pre-sampled points, where the accuracy and robustness of the kriging model depends on the selection of proper correlation coefficients. Therefore, to achieve the robust kriging model, the range of the correlation coefficients is explored with respect to the degrees of the global model. Based on this study we propose the proper orders of the global model and range of parameters to make accurate and robust kriging model.