• The Journal of Society for e-Business Studies
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• v.15 no.3
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• pp.25-44
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• 2010

In recent years, Ubiquitous City (u-City), the integrated and convergence of ubiquitous services, infrastructure, technologies and city management of the new future development city, is being initiated by the Korean government and local authorities as their new national growth engine. However, a performance measurement system for evaluating and monitoring the impacts of U-City implementation is yet to be established. This paper aims to develop an integrated performance management system (PMS) and extensively used as a tool for managing performance activities to support the visions and goals of the u-City operations. Based on current reviews on the literature and interviews with experts drew Critical Success Factors (CSF) and Key Performance Indicators (KPI) by four different measurement domains including U-City services, infrastructure, technologies, management and developed into an integrated performance measurement system based on the Balanced Scored Card (BSC) perspective. The system also provides number of examples of 'u-City Strategy Map' which illustrates a causal relationship between CSFs to execute u-City visions and goals.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.149-155
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• 2020

The Korea Highway Traffic Authority provides statistics that analyze the causes of traffic accidents that occurred since 2015 using the Traffic Accident Analysis System (TAAS). it was reported Through TAAS that the driver's forward carelessness was the main cause of traffic accidents in 2018. As statistics on the cause of traffic accidents, 51.2 percent used mobile phones and watched DMB while driving, 14 percent did not secure safe distance, and 3.6 percent violated their duty to protect pedestrians, representing a total of 68.8 percent. In this paper, we propose a system that has improved the advanced driver assistance system ADAS (Advanced Driver Assistance Systems) by utilizing CNN (Convolutional Neural Network) among the algorithms of Deep Learning. The proposed system learns a model that classifies the movement of the driver's face and eyes using Conv2D techniques which are mainly used for Image processing, while recognizing and detecting objects around the vehicle with cameras attached to the front of the vehicle to recognize the driving environment. Then, using the learned visual steering model and driving environment data, the hazard is classified and detected in three stages, depending on the driver's view and driving environment to assist the driver with the forward and blind spots.

• Spatial Information Research
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• v.18 no.4
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• pp.129-140
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• 2010

Large portal sites such as Google, NAVER provide Various services based on the map. Thus, interest and demand of users who want to obtain the region-related information has been increased. And services that combine the regional information with the map are provided currently at the large portal sites. However, the existing services of large portal sites do not provide enough detailed information and are inconvenient because acquisition process of related information is repeated. Therefore, the system that enables users to obtain detailed information related on the specific region synthetically and easily is needed. In this paper, we propose a system model using map interface and knowledge-processing in order to build the system that is useful for acquiring regional information. The model consists of 3-Layers: 'Regional Information Web-Documents Layer', 'Unique Regional Information Layer', and "Map-Interface Layer'. The Integrated Region~Related Information Searching System based on the model is implemented through the following 4-steps: (1) extracting the keywords that represent specific region (2) collecting the related web pages (3) extracting a set of related keywords and computing an association between the keywords (4) implementing a user interface. We verified validity on the model we proposed. knowledge-processing algorithm using affinity matrix, and UI that help users conveniently search by applying the system to region of the Goyang City. This system integrates regional information existing merely individual 'information' and provides users the 'knowledge' that is newly produced and organized. Users can obtain various detailed regional information and easily get related information through this system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.77-84
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• 2012

Face classification has wide applications in intelligent video surveillance, content retrieval, robot vision, and human-machine interface. Pose and expression changes, and arbitrary illumination are typical problems for face recognition. When the face is captured at a distance, the image quality is often degraded by blurring and noise corruption. This paper investigates the efficacy of multi-classifier decision level fusion for face classification based on the photon-counting linear discriminant analysis with two different cost functions: Euclidean distance and negative normalized correlation. Decision level fusion comprises three stages: cost normalization, cost validation, and fusion rules. First, the costs are normalized into the uniform range and then, candidate costs are selected during validation. Three fusion rules are employed: minimum, average, and majority-voting rules. In the experiments, unfocusing and motion blurs are rendered to simulate the effects of the long distance environments. It will be shown that the decision-level fusion scheme provides better results than the single classifier.

• Geophysics and Geophysical Exploration
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• v.20 no.3
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• pp.176-184
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• 2017

To interpret the seismic image precisely, random noises should be suppressed and the continuity of the image should be enhanced by using the appropriate smoothing techniques. Structure-Oriented Filter-Edge Preserving (SOF-EP) technique is one of the methods, that have been actively researched and used until now, to efficiently smooth seismic data while preserving the continuity of signal. This technique is based on the principle that diffusion occurs from large amplitude to small one. In a continuous structure such as a horizontal layer, diffusion or smoothing is operated along the layer, thereby increasing the continuity of layers and eliminating random noise. In addition, diffusion or smoothing across boundaries at discontinuous structures such as faults can be avoided by employing the continuity decision factor. Accordingly, the precision of the smoothing technique can be improved. However, in the case of the structure-oriented semblance technique, which has been used to calculate the continuity factor, it takes lots of time depending on the size of the filter and data. In this study, we first implemented the SOF-EP method and confirmed its effectiveness by applying it step by step to the field data. Next, we proposed and applied the corner response method which can efficiently calculate the continuity decision factor instead of structure-oriented semblance. As a result, we could confirm that the computation time can be reduced by about 6,000 times or more by applying the corner response method.

• Korean Journal of Optics and Photonics
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• v.17 no.1
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• pp.47-53
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• 2006

The Integrated Ballistics Identification Systems (IBIS) is widely used for bullet and casing signature identification. The IBIS obtains a pair of ballistic signatures from two bullets (or casings) using optical microscopy, and estimates a correlation score which can represent the degree of signature match. However, this method largely depends on lighting and surface conditions because optical image contrast is primarily a function of test surface's slope, shadowing, multiple reflections, optical properties, and illumination direction. Moreover, it can be affected with surface height variation. To overcome these problems and improve the identification system, we used well known surface topographic techniques, such as confocal microscopy and white-light scanning interferometry. The measuring instruments were calibrated by a NIST step height standard and verified by a NIST sinusoidal profile roughness standard and a commercial roughness standard. We also suggest a new analysis method for the ballistic identification. In this method, the maximum cross-correlation function CCFmax is used to quantify the degree of signature match. If the compared signatures were exactly the same, CCFmax would be $100\%$.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.116-127
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• 1996

In this paper, a scheme of classification of scaled textured images using normalized pattern spectrum incorporating arbitrary scale changes based on mathematical morphology is proposed in more general environments considering camera's zoom-in and zoom-out function. The normalized pattern spectrum means that firstly pattern spectrum is calculated and secondly interpolation is performed to incorporate scale changes according to scale change ratio in the same textured image class. Pattern spectrum is efficiently obtained by using both opening and closing, that is, we calculate pattern spectrum by opening method for pixels which have value more than threshold and calculate pattern spectrum by closing method for pixels which have value less than threshold. Also we compare classification accuracy between gray scale method and binary method. The proposed approach has the advantage of efficient information extraction, high accuracy, less computation, and parallel implementation. An important advantage of the proposed method is that it is possible to obtain high classification accuracy with only (1:1) scale images for training phase.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.1
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• pp.75-82
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• 2000

In this paper, a new low power 16-bit ALU has been designed, fabricated and tested at the transistor level. The designed ALU performs 16 instructions and has a two-stage pipelined architecture. For the reduction of switched capacitance, the ELM adder of the proposed ALU is inactive while the logical operation is performed and P(propagation) block has a dual bus architecture. A new efficient P and G(generation) blocks are also proposed for the above ALU architecture. ELM adder, double-edge triggered register and the combination of logic style are used for low power consumption as well. As a result of simulations, the proposed architecture shows better power efficient than conventional architecture$^{[1,2]}$ as the number of logic operation to be performed is increased over that of arithmetic to logic operation to be performed is 7 to 3, compared to conventional architecture. The proposed ALU was fabricated with 0.6${\mu}m$ single-poly triple-metal CMOS process. As a result of chip test, the maximum operating frequency is 53MHz and power consumption is 33mW at 50MHz, 3.3V.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.1
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• pp.20-27
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• 2010

This paper describes a design of 5-stage pipelined de-blocking filter with power reduction scheme and proposes a efficient memory architecture and filter order for high performance H.264/AVC Decoder. Generally the de-blocking filter removes block boundary artifacts and enhances image quality. Nevertheless filter has a few disadvantage that it requires a number of memory access and iterated operations because of filter operation for 4 time to one edge. So this paper proposes a optimized filter ordering and efficient hardware architecture for the reduction of memory access and total filter cycles. In proposed filter parallel processing is available because of structured 5-stage pipeline consisted of memory read, threshold decider, pre-calculation, filter operation and write back. Also it can reduce power consumption because it uses a clock gating scheme which disable unnecessary clock switching. Besides total number of filtering cycle is decreased by new filter order. The proposed filter is designed with Verilog-HDL and functionally verified with the whole H.264/AVC decoder using the Modelsim 6.2g simulator. Input vectors are QCIF images generated by JM9.4 standard encoder software. As a result of experiment, it shows that the filter can make about 20% total filter cycles reduction and it requires small transposition buffer size.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.31-41
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• 2012

The law enforcement agencies in the worldwide are confiscating or retaining computer systems involved in a crime/civil case, if there are any, at the preliminary investigation stage, even though the case does not involve a cyber-crime. They are collecting digital evidences from the suspects's systems and using them in the essential investigation procedure. It requires much time, though, to collect, duplicate and analyze disk images in general crime cases, especially in cases in which rapid response must be taken such as kidnapping and murder cases. The enterprise forensics, moreover, it is impossible to acquire and duplicate hard disk drives in mass storage server, database server and cloud environments. Therefore, it is efficient and effective to selectively collect only traces of the behavior of the user activities on operating systems or particular files in focus of triage investigation. On the other hand, if we acquire essential digital evidences from target computer, it is not forensically sound to collect just files. We need to use standard digital evidence container from various sources to prove integrity and probative of evidence. In this article, we describe a new digital evidence container, we called Xebeg, which is easily able to preserve collected digital evidences selectively for using general technology such as XML and PKZIP compression technology, which is satisfied with generality, integrity, unification, scalability and security.