• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7A
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• pp.1036-1045
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• 1999

In this paper, we proposed a causal ordering algorithms which is efficiently applicable to overlapped process group environments where one process may belong to several process groups. The ones is proposed to choose with topology of the network. We proposed receiver select algorithm in broadcast network, sender select algorithm in point-to-point network. Each algorithms removes unnecessary vector timestampes to reduce the message overhead required for the causual ordering. And, compressed vector timestamps using the locally maintained vector timestamp information of other processes and other groups to minimize the message overhead. Also, we logically proved the proposed causal ordering method, and compared the performance of the proposed algorithm with ones of other existing algorithms by computer simulation.

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2004.06a
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• pp.323-327
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• 2004

Leuconostoc citreum CBUE isolated from kimchi proved to harbor a small cryptic plasmid, pNS75. The complete nucleotide sequence of pNS75 was 1,821 bp and had a low G+C content of 39.2%. Computer analysis using DNASIS revealed one open reading frame (ORF), having ATG as putatitive start condon and potentially encoding proteins with molecular mass of 38 kDa. The chimeric plasmid pLeuCM was first constructed wih pNS75, pUC19 and chroamphenicol acetyltransferase (CAT) from Staphylococcus sp.. pLeuCM replicated and expressed chroamphenicol acetyltransferase in Leuconostoc citerum CBNF after transformation. To test the availability of shuttle vector as cloning vehicle of foreign gene, $\alpha$-amylase gene of Streptococcus bovis was cloned and all transformants secreated the $\alpha$-amylase successfully. The result indicates that pLeuCM is a potential shuttle vector for Leuconostoc spp. and lactic acid bacteria.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.950-954
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• 2004

According to the rapid advance of computer and communication techniques, the request of mobile internet services is highly increasing. However, the main obstacles for mobile vector map service environments, are large data volume and narrow wireless bandwidth. Among the many possible solutions, spatial data compression technique may contribute to reduce the load of bandwidth and client response time. This thesis proposes two methods for spatial data compression. The one is relative coordinates transformation method, and the other is client coordinates transformation method. And, this thesis also proposes the system architecture for experiments. The two compression methods could be evaluated the compression effect and the response time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.451-457
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• 2009

Most of objects in computer graphics may be represented by a form of mesh. The exact computation of vertex normal vectors is essential for user to apply a variety of geometric operations to the mesh and get more realistic rendering results. Most of the previous algorithms used a weight which resembles a local geometric property of a vertex of a mesh such as the interior angle, the area, and so on. In this paper, we propose an efficient algorithm for computing the normal vector of a vertex in meshes. Our method uses the conformal mapping which resembles synthetically the local geometric properties, and the mean value coordinates which may smoothly represent a relationship with the adjacent vertices. It may be confirmed by experiment that the normal vector of our algorithm is more exact than that of the previous methods.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1359-1371
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• 2020

In transmitting and receiving such a large amount of data, reliable data communication is crucial for normal operation of a device and to prevent abnormal operations caused by errors. Therefore, in this paper, it is assumed that an error correction code (ECC) that can detect and correct errors by itself is used in an environment where massive data is sequentially received. Because an embedded system has limited resources, such as a low-performance processor or a small memory, it requires efficient operation of applications. In this paper, we propose using an accelerated ECC-decoding technique with a graphics processing unit (GPU) built into the embedded system when receiving a large amount of data. In the matrix-vector multiplication that forms the Hamming code used as a function of the ECC operation, the matrix is expressed in compressed sparse row (CSR) format, and a sparse matrix-vector product is used. The multiplication operation is performed in the kernel of the GPU, and we also accelerate the Hamming code computation so that the ECC operation can be performed in parallel. The proposed technique is implemented with CUDA on a GPU-embedded target board, NVIDIA Jetson TX2, and compared with execution time of the CPU.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.719-728
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• 2022

The prediction of short-term traffic flow is the theoretical basis of intelligent transportation as well as the key technology in traffic flow induction systems. The research on short-term traffic flow prediction has showed the considerable social value. At present, the support vector regression (SVR) intelligent prediction model that is suitable for small samples has been applied in this domain. Aiming at parameter selection difficulty and prediction accuracy improvement, the artificial bee colony (ABC) is adopted in optimizing SVR parameters, which is referred to as the ABC-SVR algorithm in the paper. The simulation experiments are carried out by comparing the ABC-SVR algorithm with SVR algorithm, and the feasibility of the proposed ABC-SVR algorithm is verified by result analysis. Continuously, the simulation experiments are carried out by comparing the ABC-SVR algorithm with particle swarm optimization SVR (PSO-SVR) algorithm and genetic optimization SVR (GA-SVR) algorithm, and a better optimization effect has been attained by simulation experiments and verified by statistical test. Simultaneously, the simulation experiments are carried out by comparing the ABC-SVR algorithm and wavelet neural network time series (WNN-TS) algorithm, and the prediction accuracy of the proposed ABC-SVR algorithm is improved and satisfactory prediction effects have been obtained.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4102-4111
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• 2023

In order to better perform thermal hydraulic calculation and analysis of supercritical water reactor, based on the experimental data of supercritical water, the model training and predictive analysis of the heat transfer coefficient of supercritical water were carried out by using the support vector machine (SVM) algorithm. The changes in the prediction accuracy of the supercritical water heat transfer coefficient are analyzed by the changes of the regularization penalty parameter C, the slack variable epsilon and the Gaussian kernel function parameter gamma. The predicted value of the SVM model obtained after parameter optimization and the actual experimental test data are analyzed for data verification. The research results show that: the normalization of the data has a great influence on the prediction results. The slack variable has a relatively small influence on the accuracy change range of the predicted heat transfer coefficient. The change of gamma has the greatest impact on the accuracy of the heat transfer coefficient. Compared with the calculation results of traditional empirical formula methods, the trained algorithm model using SVM has smaller average error and standard deviations. Using the SVM trained algorithm model, the heat transfer coefficient of supercritical water can be effectively predicted and analyzed.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.17-24
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• 2019

Use without permission of font files is a social problem. In the meantime, our court recognized font files as computer programs. Is the font file a computer program? This recognition arises from the inability to distinguish between computer programs and data. Expert recognition, on the other hand, does not recognize font files as computer programs. In this regard, there was a case in 2014 that INI files were not computer programs, but only data files. So, the attitude of the Supreme Court in 2001 only makes it difficult to distinguish between computer programs and data. The Supreme Court's decision needs to be changed. In addition, a new legal system should be in place to protect font files.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.1-10
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• 2021

Cyberbullying has become a severe issue and brought a powerful impact on the cyber world. Due to the low cost and fast spreading of news, social media has become a tool that helps spread insult, offensive, and hate messages or opinions in a community. Detecting cyberbullying from social media is an intriguing research topic because it is vital for law enforcement agencies to witness how social media broadcast hate messages. Twitter is one of the famous social media and a platform for users to tell stories, give views, express feelings, and even spread news, whether true or false. Hence, it becomes an excellent resource for sentiment analysis. This paper aims to detect cyberbully threats based on Naïve Bayes, support vector machine (SVM), and k-nearest neighbour (k-NN) classifier model. Sentiment analysis will be applied based on people's opinions on social media and distribute polarity to them as positive, neutral, or negative. The accuracy for each classifier will be evaluated.

• ETRI Journal
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• v.26 no.6
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• pp.605-614
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• 2004

In this paper, we investigate array calibration algorithms to derive a further improved version for correcting antenna array errors and RF transceiver errors in CDMA smart antenna systems. The structure of a multi-channel RF transceiver with a digital calibration apparatus and its calibration techniques are presented, where we propose a new RF receiver calibration scheme to minimize interference of the calibration signal on the user signals. The calibration signal is injected into a multi-channel receiver through a calibration signal injector whose array response vector is controlled in order to have a low correlation with the antenna response vector of the receive signals. We suggest a model-based antenna array calibration to remove the antenna array errors including mutual coupling errors or to predict the element patterns from the array manifold measured at a small number of angles. Computer simulations and experiment results are shown to verify the calibration algorithms.