• Journal of Broadcast Engineering
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• v.10 no.3
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• pp.413-421
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• 2005

As the population of HDTV is growing, among many useful features of modern set top boxes (STBs) or digital video recorders (DVRs), video browsing, visual bookmark, and picture-in-picture capabilities are very frequently required. These features typically employ reduced-size versions of video frames, or thumbnail images. Most thumbnail generation approaches generate DC images directly from a compressed video stream. A discrete cosine transform (DCT) coefficient for which the frequency is zero in both dimensions in a compressed block is called a DC coefficient and is simply used to construct a DC image. If a block has been encoded with field DCT, a few AC coefficients are needed to generate the DC image in addition to a DC coefficient. However, the bit length of a codeword coded with variable length coding (VLC) cannot be determined until the previous VLC codeword has been decoded, thus it is required that all codewords should be fully decoded regardless of their necessary for DC image generation. In this paper, we propose a method especially for fast DC image generation from an I-frame using multiple-symbol lookup table (mLUT). The experimental results show that the method using the mLUT improves the performance greatly by reducing LUT count by 50$\%$.

• The Southeast Asian review
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• v.28 no.4
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• pp.161-196
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• 2018

The major object of this study is to analyze the political development of Myanmar's civilian government on the concept of defective democracy, and to investigate the main actors who delayed or stymied political development and their interrelation. In doing so, this study suggests the tasks required for political development overcoming the current political structure and behavior. The civilian government, which was launched in 2016, failed to achieve positive political development by following the behavior of military authoritarianism in terms of exercise of power and decision making structure. On the perspective of the government, delegative democracy and domain democracy have been strengthening since one person has taken over all political power and hesitate to take horizontal accountability for each power organizations. The military, which is responsible for national defence and security seeks illiberal democracy and exclusive democracy, keeping on an undemocratic constitution by the military and Burman ethnocentrism. The reasons why defective democracy has been occurred are that the lack of a group to run a democratic institutions and the limitation of power structure that fails to adhere to the principle of civilian control to the military due to long-term military rule. Therefore, there is a need for military's come back to barracks and transform the power structure to democratic of the civilian government which is tamed an authoritarian order for the political development in Myanmar. In order to achieve this, this study concludes that setting up a empowered democratic government is required.

• Journal of the Korean Geotechnical Society
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• v.37 no.11
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• pp.51-60
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• 2021

River scour erodes the soil around the pier, reducing the lateral bearing capacity of the pier and lowering the stability of the structure. In this study, in order to examine the effect of scouring on the stability of the structure, an experiment was performed to measure the natural frequency of the pier according to the excavation of the surrounding ground. Impact vibration test was conducted on the pier with the caisson foundation of the Mangyeonggang Bridge, which is scheduled to be demolished. Accelerometers were attached to the top, center, and bottom of the pier and the acceleration responses were measured by hitting those three points. The experimental results showed that the top hit showed consistent and reasonable results of the acceleration responses according to the hitting position. The measured accelerations were converted to the frequency domain through Fast Fourier Transform (FFT), and then the natural frequency was determined. In addition, to analyze the scour effect on the natural frequency of the pier, the ground around the pier was excavated and the natural frequency change was analyzed. As a result, the natural frequency showed the decreasing tendency according to the excavation depth, but the decrease was small due to the large stiffness of the caisson foundation.

• Journal of Microbiology and Biotechnology
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• v.34 no.2
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• pp.457-466
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• 2024

Cellobiose dehydrogenases (CDHs) are a group of enzymes belonging to the hemoflavoenzyme group, which are mostly found in fungi. They play an important role in the production of acid sugar. In this research, CDH annotated from the actinobacterium Cellulomonas palmilytica EW123 (CpCDH) was cloned and characterized. The CpCDH exhibited a domain architecture resembling class-I CDH found in Basidiomycota. The cytochrome c and flavin-containing dehydrogenase domains in CpCDH showed an extra-long evolutionary distance compared to fungal CDH. The amino acid sequence of CpCDH revealed conservative catalytic amino acids and a distinct flavin adenine dinucleotide region specific to CDH, setting it apart from closely related sequences. The physicochemical properties of CpCDH displayed optimal pH conditions similar to those of CDHs but differed in terms of optimal temperature. The CpCDH displayed excellent enzymatic activity at low temperatures (below 30℃), unlike other CDHs. Moreover, CpCDH showed the highest substrate specificity for disaccharides such as cellobiose and lactose, which contain a glucose molecule at the non-reducing end. The catalytic efficiency of CpCDH for cellobiose and lactose were 2.05 × 10⁵ and 9.06 × 10⁴ (M^-1 s^-1), respectively. The result from the Fourier-transform infrared spectroscopy (FT-IR) spectra confirmed the presence of cellobionic and lactobionic acids as the oxidative products of CpCDH. This study establishes CpCDH as a novel and attractive bacterial CDH, representing the first report of its kind in the Cellulomonas genus.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.97-107
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• 2011

Nowadays there are a lot of issues about copyright infringement in the Internet world because the digital content on the network can be copied and delivered easily. Indeed the copied version has same quality with the original one. So, copyright owners and content provider want a powerful solution to protect their content. The popular one of the solutions was DRM (digital rights management) that is based on encryption technology and rights control. However, DRM-free service was launched after Steve Jobs who is CEO of Apple proposed a new music service paradigm without DRM, and the DRM is disappeared at the online music market. Even though the online music service decided to not equip the DRM solution, copyright owners and content providers are still searching a solution to protect their content. A solution to replace the DRM technology is digital audio watermarking technology which can embed copyright information into the music. In this paper, the author proposed a new audio watermarking algorithm with two approaches. First, the watermark information is generated by two dimensional barcode which has error correction code. So, the information can be recovered by itself if the errors fall into the range of the error tolerance. The other one is to use chirp sequence of CDMA (code division multiple access). These make the algorithm robust to the several malicious attacks. There are many 2D barcodes. Especially, QR code which is one of the matrix barcodes can express the information and the expression is freer than that of the other matrix barcodes. QR code has the square patterns with double at the three corners and these indicate the boundary of the symbol. This feature of the QR code is proper to express the watermark information. That is, because the QR code is 2D barcodes, nonlinear code and matrix code, it can be modulated to the spread spectrum and can be used for the watermarking algorithm. The proposed algorithm assigns the different spread spectrum sequences to the individual users respectively. In the case that the assigned code sequences are orthogonal, we can identify the watermark information of the individual user from an audio content. The algorithm used the Walsh code as an orthogonal code. The watermark information is rearranged to the 1D sequence from 2D barcode and modulated by the Walsh code. The modulated watermark information is embedded into the DCT (discrete cosine transform) domain of the original audio content. For the performance evaluation, I used 3 audio samples, "Amazing Grace", "Oh! Carol" and "Take me home country roads", The attacks for the robustness test were MP3 compression, echo attack, and sub woofer boost. The MP3 compression was performed by a tool of Cool Edit Pro 2.0. The specification of MP3 was CBR(Constant Bit Rate) 128kbps, 44,100Hz, and stereo. The echo attack had the echo with initial volume 70%, decay 75%, and delay 100msec. The sub woofer boost attack was a modification attack of low frequency part in the Fourier coefficients. The test results showed the proposed algorithm is robust to the attacks. In the MP3 attack, the strength of the watermark information is not affected, and then the watermark can be detected from all of the sample audios. In the sub woofer boost attack, the watermark was detected when the strength is 0.3. Also, in the case of echo attack, the watermark can be identified if the strength is greater and equal than 0.5.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.139-155
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• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.