• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.3
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• pp.353-364
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• 1998

Consumer knowledge has been discussed as an important concept to understand information processing such as information search and evaluation process. It has been defined as the amounts and contents of information in consumer's memory accumulated by experiences. According to literature review, experts who have much knowledge are likely to retrieve their information related to products for a purchase efficiency. Therefore, they are likely to simplify the information processing for a choice. The purpose of this study was to examine the relationship between clothing product knowledge and evaluative criteria for a purchase. The results were as follows; First, it was found out that evaluative criteria were composed of four dimensions such as the management, the esthetic, the fitness and the brand. Therefore, it is implied that evaluative criteria for purchasing clothing products were multidimensional. Second, the level of objective knowledge was low, and consumers perceived that they didn't have much knowledge related with clothing products. Also, the relationships between objective and subjective knowledge were positive but low. Third, the evaluative criteria were effected by the level of consumer's knowledge significantly. In subjective knowledge, the subjects in a high group considered all criteria more deeply than in a low group. But there was a significant difference only in the esthetic between two groups in objective knowledge. The results of this study imply that consumer knowledge may influence evaluation process. Knowledgeable consumer would consider product attributes deeply for evaluating clothing products, and especially, the esthetic would be an important factor as an attribute including the instrumental and expressive functions in a purchase phase. Therefore, consumer knowl- edge would be a basis of predicting expert's information processing and managing heavy buyer or loyal consumers in apparel industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1726-1743
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• 2014

DDoS (Distributed Denial of Service) has been a continuous threat to the cyber world with the growth in cyber technology. This technical evolution has given rise to a number of ultra-sophisticated ways for the attackers to perform their DDoS attack. In general, the attackers who generate the denial of service, use the vulnerabilities of the TCP. Some of the vulnerabilities like SYN (synchronization) flooding, and IP spoofing are used by the attacker to create these Distributed Reflected Denial of Service (DrDoS) attacks. An attacker, with the assistance of IP spoofing creates a number of attack packets, which reflects the flooded packets to an attacker's intended victim system, known as the primary target. The proposed scheme, Efficient Spoofed Flooding Defense (ESFD) provides two level checks which, consist of probing and non-repudiation, before allocating a service to the clients. The probing is used to determine the availability of the requested client. Non-repudiation is taken care of by the timestamp enabled in the packet, which is our major contribution. The real time experimental results showed the efficiency of our proposed ESFD scheme, by increasing the performance of the CPU up to 40%, the memory up to 52% and the network bandwidth up to 67%. This proves the fact that the proposed ESFD scheme is fast and efficient, negating the impact on the network, victim and primary target.

• Journal of KIISE
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• v.43 no.4
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• pp.470-479
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• 2016

As the number of various types of media data such as UCC (User Created Contents) increases, research is actively being carried out in many different fields so as to provide meaningful media services. Amidst these studies, a semantic web-based media classification approach has been proposed; however, it encounters some limitations in video classification because of its underlying ontology derived from meta-information such as video tag and title. In this paper, we define recognized objects in a video and activity that is composed of video objects in a shot, and introduce a reasoning approach based on description logic. We define sequential rules for a sequence of shots in a video and describe how to classify it. For processing the large amount of increasing media data, we utilize Spark streaming, and a distributed in-memory big data processing framework, and describe how to classify media data in parallel. To evaluate the efficiency of the proposed approach, we conducted an experiment using a large amount of media ontology extracted from Youtube videos.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.10
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• pp.77-83
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• 2004

In low-power VLSI systems, it is effective to suppress leakage current by shutting down megablocks in idle states. Recently, multi-threshold voltage CMOS (MTCMOS) is widely accepted to shutdown power supply. However, it requires short wake-up time as operating frequency increases. This causes large current surge during wake-up process, and it often leads to system malfunction due to severe Power line noise. In this paper, a novel wake-up scheme is proposed to solve this problem. It exploits pipelined wake-up strategy in several stages that reduces maximum current on the power line and its corresponding power line noise. To evaluate its efficiency, the proposed scheme was applied to a multiplier block in the Compact Flash memory controller chip. Power line noise in shutdown and wake-up process was simulated and analyzed. From the simulation results, the proposed scheme was proven to greatly reduce the power line noise compared with conventional schemes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.2
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• pp.141-153
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• 1987

The prediction of the exact behavior of multistory building is one of the most complicated problem encountered in structural engineering practice. An efficient computer method for the three dimensional analysis of building structures is presented in this paper. A multistory building is idealized as an assemblage of a series of rectangular plane frames interconnected by rigid floor diaphragms. The matrix condensation technique is employed for the reduction of degrees of freedom, which results in a significant saving in computational efforts and the required memory size. Kinematical approach was used to assemble condensed stiffness matrices of plane frames into a three dimensional stick model stiffness matrix. The static analysis follows the modified tridiagonal approach. Since this procedure utilizes the condensed stiffness matrix of the structure, the dynamic equations of motion for the story displacement are developed by assigning proper mass for each story. Analysis results of several example structures are compared to those obtained by using the well-known SAP IV for verification of the accuracy and efficiency of the computer program PFS which was developed utilizing the method proposed in this study. The analysis method proposed in this study can be used as an efficient and economical means for the analysis of multistory buildings.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.151-161
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• 2009

Audio Video Standard (AVS) is the audio and video compression standard that was developed for domestic video applications in China. AVS employs low complexity tools to minimize degradation of RD performance of the state-the-art video codec, H.264/AVC. The AVS video codec consists of $8{\times}8$ block prediction and the same size transform to improve compression efficiency for VGA and higher resolution sequences. Currently, the AVS has been adopted more and more for IPTV services and mobile applications in China. So, many consumer electronics companies and multimedia-related laboratories have been developing applications and chips for the AVS. In this paper, we implemented the AVS video decoder and optimize it on TI's Davinci EVM DSP board. For improving the decoding speed and clocks, we removed unnecessary memory operations and we also used high-speed VLD algorithm, linear assembly, intrinsic functions and so forth. Test results show that decoding speed of the optimized decoder is $5{\sim}7$ times faster than that of the reference software (RM 5.2J).

• Journal of IKEEE
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• v.15 no.4
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• pp.345-353
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• 2011

Recently portable mobile devices such as smart-phones and notebooks have rapidly increasing demands. Those devices consume more power because they are expected to offer more complex functionality including multimedia features. For these reasons engineering efforts are changing to focus on maximizing energy efficiency within a limited battery capacity instead of increasing computational performance. In this paper, we propose a battery management system using event driven programming technique on a embedded processor. We also show that the proposed system satisfies SBS (Smart Battery Specification) v1.1. The proposed system maintains minimum code size and memory size comparing to those of RTOSs. The proposed system can be also easily incorporated in the conventional RTOSs as a form of firmware.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.246-254
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• 2020

In this paper, we propose a learning based compressive sensing algorithm for the purpose of side scan sonar image denoising. The proposed method is based on Iterative Shrinkage and Thresholding Algorithm (ISTA) framework and incorporates a powerful strategy that reinforces the non-linearity of deep learning network for improved performance. The proposed method consists of three essential modules. The first module consists of a non-linear transform for input and initialization while the second module contains the ISTA block that maps the input features to sparse space and performs inverse transform. The third module is to transform from non-linear feature space to pixel space. Superiority in noise removal and memory efficiency of the proposed method is verified through various experiments.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.71-82
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• 2012

In this paper, we propose a license plate detection method with improved Adaboost learning and MCT (Modified Census Transform). The MCT represents the local structure patterns as integer numbered feature values which has robustness to illumination change and memory efficiency. However, since these integer values are discrete, a lookup table is needed to design a weak classifier for Adaboost learning. Some previous research efforts have focused on minimization of exponential criterion for Adaboost optimization. In this paper, a method that uses MCT and improved Adaboost learning based on Newton's optimization to exponential criterion is proposed for license plate detection. Experimental results on license patch images and field images demonstrate that the proposed method yields higher performance of detection rates with low false positives than the conventional method using the original Adaboost learning.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12C
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• pp.1055-1061
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• 2008

H.264 is the prominent video coding standard in various applications such as real-time streaming and digital multimedia broadcasting, since it provides enhanced compression performance, error resilience tools, and network adaptation. Compression efficiency of H.264 has been improved, however, it requires more computing and memory access than traditional methods. In this paper we proposed adaptive intra fast algorithm for real-time video surveillance system reducing the encoding complexity of H264/A VC. For this aim, temporal interrelationship between macroblock in the previous and the current frame is used to decide the encoding mode of macroblock fast. As a result, though video quality was deteriorated a little, less than 0.04dB, and bit rate was somewhat increased in suggested method, however, proposed method improved encoding time significantly and, in particular, encoding time of an image with little changes of neighboring background such as surveillance video was more shortened than traditional methods.