• Journal of KIISE
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• v.41 no.9
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• pp.666-673
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• 2014

This paper proposes a scalable face recognition method for unconstrained face databases, and shows a simple experimental result. Existing face recognition research usually has focused on improving the recognition rate in a constrained environment where illumination, face alignment, facial expression, and background is controlled. Therefore, it cannot be applied in unconstrained face databases. The proposed system is face feature extraction algorithm for unconstrained face recognition. First of all, we extract the area that represent the important features(landmarks) in the face, like the eyes, nose, and mouth. Each landmark is represented by a high-dimensional LBP(Local Binary Pattern) histogram feature vector. The multi-scale LBP histogram vector corresponding to a single landmark, becomes a low-dimensional face feature vector through the feature reduction process, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis). We use the Rank acquisition method and Precision at k(p@k) performance verification method for verifying the face recognition performance of the low-dimensional face feature by the proposed algorithm. To generate the experimental results of face recognition we used the FERET, LFW and PubFig83 database. The face recognition system using the proposed algorithm showed a better classification performance over the existing methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.75-88
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• 2017

This study analyzed wind flows based on spatial and geomorphological characteristics of Daegu Metropolitan City. A three-stage analysis was performed, starting with a comparison of meteorological relationships between local wind direction (synoptic wind) and local wind flow. In the second stage the study area was subdivided into districts and suburban districts to analyze the relative change of local wind flow. In stage three, the formation of wind corridor for local wind flow, wind flow for the entire urban space, and spatial relationships between flows were verified comparatively using KLAM_21. Three results are notable, the first of which is a low correlation between synoptic wind of a region, and local wind, flow in terms of meteorology. Secondly, observations of local wind flow at five downtown districts and two suburban districts showed that there were diverse wind directions at each measurement point. This indicates that the spatial and geomorphological characteristics of areas neighboring the measurement points could affect the local wind flow. Thirdly, verifying the results analyzed using KLAM_21, compared to Atomatic Weather System(AWS) measurement data, confirmed the reliability of the numerical modelling analysis. It was determined that local wind flow in a city performs a spatial function and role in ameliorating the urban heat island phenomena. This indicates that, when an urban planning project is designed, the urban heat island phenomena could be ameliorated effectively and sustainably if local wind flow caused by immediate spatial and geomorphological characteristics is confirmed systematically and techniques are intentionally applied to connect the flows spatially within areas where urban heat islands occur.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.117-127
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• 2012

Identifying user requirements efficiently and reflecting them on the existing system is very important in a rapidly changing web and mobile environments. This study proposes the strategies to refining requirements and to prioritizing those refined requirements for changing of web and mobile application based on user requirements (e.g. mobile application comments, Q&A, reported information as discomfort factors). In order to refining the user requirements, those requirements are grouped by using the advancement of the software business of the Forum of standardization and the existing configuration-based programs. Then, we mapped them onto the PIECES framework to identifying whether the refined requirements are correctly reflected to the system in a way of valid and pure. To determine the priority of refined requirements, first, relative weights are given to software structure, requirements and categories of PIECES. Second, integration points on each requirement are counted to obtain the relative value of partial and overall score of a set of software structural requirements. In order to verifying the possibility and proving the effectiveness of proposing technique in this study, survey was conducted on changing requirements of mobile application which have been serviced at S University by targeting 15 people of work-related stakeholders.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.9
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• pp.1305-1310
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• 2010

In a practical design process, the method of extracting the design space information of the complex system for verifying, improving, and optimizing the design process by taking into account the design variables and their shape tolerance is very important. Finite element analysis has been successfully implemented and integrated with design of experiment such as D-Optimal array; thus, a response surface model and optimization tools have been obtained, and design variables can be optimized by using the model and these tools. Then, to guarantee the robustness of the design variables, a robust design should be additionally performed by taking into account the statistical variation of the shape tolerance of the optimized design variables. In this study, a new approach based on the use of the response surface model is proposed; in this approach, the standard normal distribution of the shape tolerance is considered. By adopting this approach, it is possible to simultaneously optimize variables and perform a robust design. This approach can serve as a means of efficiently modeling the trade-off among many conflicting goals in the applications of finite element analysis. A case study on the robust optimal design of disc brakes under thermal loadings was carried out to solve multiple objective functions and determine the constraints of the design variables, such as a thermal deformation and weight.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.895-905
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• 2019

Commercial Unmanned Aerial Vehicle (UAV) image processing software products currently used in the industry provides camera calibration information and block bundle adjustment accuracy. However, they provide mapping accuracy achievable out of input UAV images. In this paper, the quality of mapping is calculated by using orientation parameters from UAV image processing software. We apply the orientation parameters to the digital photogrammetric workstation (DPW) for verifying the reliability of the mapping quality calculated. The quality of mapping accuracy was defined as three types of accuracy: Y-parallax, relative model and absolute model accuracy. The Y-parallax is an accuracy capable of determining stereo viewing between stereo pairs. The Relative model accuracy is the relative bundle adjustment accuracy between stereo pairs on the model coordinates system. The absolute model accuracy is the bundle adjustment accuracy on the absolute coordinate system. For the experimental data, we used 723 images of GSD 5 cm obtained from the rotary wing UAV over an urban area and analyzed the accuracy of mapping quality. The quality of the relative model accuracy predicted by the proposed technique and the maximum error observed from the DPW showed precise results with less than 0.11 m. Similarly, the maximum error of the absolute model accuracy predicted by the proposed technique was less than 0.16 m.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.27-35
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• 2018

This paper is a study to classify malicious applications in Android environment. And studying the threat and behavioral analysis of malicious Android applications. In addition, malicious apps classified by machine learning were performed as experiments. Android behavior analysis can use dynamic analysis tools. Through this tool, API Calls, Runtime Log, System Resource, and Network information for the application can be extracted. We redefined the properties extracted for machine learning and evaluated the results of machine learning classification by verifying between the overall features and the main features. The results show that key features have been improved by 1~4% over the full feature set. Especially, SVM classifier improved by 10%. From these results, we found that the application of the key features as a key feature was more effective in the performance of the classification algorithm than in the use of the overall features. It was also identified as important to select meaningful features from the data sets.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.211-219
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• 2012

In this paper, we described the software development for verifying the integrity of output data of TCP/IP for VLBI Correlation Subsystem (VCS) correlation block and proposed the performance improvement method in order to prevent the data loss of correlation output. The VCS correlation results are saved at the Data Archive system through TCP/IP packet transmission. In this paper, the integrity verification software is developed so as to confirm the integrity of correlation result saved at the data archive system using TCP/IP packet information of VCS. The 3-step integrity verification process is proposed by using the developed software, its effectiveness was confirmed in consequence of correlation experiments. In addition, TCP/IP packet transmission must be completed within minimum integration period. However, there is not only TCP/IP packet loss occurred but also the problem of correlation result integrity affected in account of a large quantity of packets and data during short integration time. In this paper, the reason of TCP/IP packet loss is analyzed and the modified methods for FPGA(Field Programmable Gate Array) of VCS are proposed, the integrity problem of correlation results will be solved.

• Journal of Korean Society of Forest Science
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• v.102 no.2
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• pp.189-197
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• 2013

The Cancun Agreements under the United Nations Framework Convention on Climate Change require developing countries aiming to undertake REDD+ activities to develop a national strategy or action plan, addressing the drivers of deforestation and forest degradation, a measurement, reporting and verifying (MRV) system including forest monitoring system, and safeguards to ensure equity and co-benefits for local communities and indigenous peoples, and biodiversity. The Government of Indonesia and the Government of Norway established REDD+ cooperation through signing a 'Letter of Intent' in May, 2010. Indonesia agreed on 'a two year suspension on all new concessions for conversion of peat and natural forest'. In turn, Norway agreed to support Indonesia's REDD+ implementation efforts up to one billion United States dollars. Indonesia's REDD+ national strategy (June, 2012) accepted most of the requests included in the 'Letter of Intent'. The REDD+ national strategy, however, does not reflect requests of the Cancun Agreements which noted identification of the drivers of deforestation and forest degradation and guarantee of real greenhouse gas emissions reductions. Indonesia lays emphasis on Norwegian requests which includes expected financial support rather than the Cancun Agreements which have a weak legally-binding requirements.

• Journal of the Korea Society for Simulation
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• v.15 no.1
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• pp.35-42
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• 2006

Sensor network, that is an infrastructure of ubiquitous computing, consists of a number of sensor nodes of which hardware is very small. The network topology and routing scheme of the network should be determined according to its purpose, and its hardware and software may have to be changed as needed from time to time. Thus, the sensor network simulator being capable of verifying its behavior and estimating performance is required for better design. Sensor network simulators currently existing have been developed for specific hardwares or operating systems, so that they can only be used for such systems and do not provide any means to estimate the amount of power consumption and program execution time which are major issues for system design. In this study, we develop the sensor network simulator that can be used to design and verify various sensor networks without regarding to types of applications or operating systems, and also has the capability of predicting the amount of power consumption and program execution time. For this purpose, the simulator is developed by using machine instruction-level discrete-event simulation scheme. As a result, the simulator can be used to analyze program execution timings and related system behaviors in the actual sensor nodes in detail. Instruction traces used as workload for simulations are executable images produced by the cross-compiler for ATmega128L microcontroller.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.787-796
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• 2012

The aim of this study is to closely examine the changes in their metabolic syndrome index and autonomic nerve systems after the 16-weeks's combined exercise program is carried out on low-level physical strength group (PAPS 4-5 level students). They were divided into two groups; exercise training group (15) and control group (15). This program consisted of five-times-a-week's warm-ups, main activities and warm-downs and it takes 50 minutes per trial. Through SPSS 19.0, all averages and standard deviations of dependent variables were calculated. We first performed Shapiro-Wilk's normality test of the variables. Before verifying the effect of combined exercise program, we tested the equality of means of the variables between combined-exercise-programmed-group and control group through a two-sample t-test and carried out a paired t-test to check if the changes in the variables of two groups before and after 16 weeks are statistically significant. Every statistical test is performed at a significance level of ${\alpha}$=.05. The results are as follows. When it came to metabolic syndrome index, there were statistically meaningful changes in waist measurement, triglyceride, glucose with empty stomach and HDL-C. Also, when it came to autonomic nerve system, there were meaningful changes in all variables. Consequently, it seems that the 16-weeks combined exercise program has positive effects on low level physical strength students.