• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.201-212
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• 2009

There are various methods to trace output in software development to verify the consistency and completeness of requirements. Existing studies do present the trace meta-model or automated tools, but fail to list specifically traced output or traced items. Also, in regards to trace tables, which contain traced items, existing studies don‘t consider the whole software development process but merely its sub-process. Given this, the present study suggests an extended requirements tracetable that tracks output from the inception of the project through the architectural design phase to the application delivery, following up on the researcher’s previous study on a tracetable that considered only a sub-process of the whole development process. In addition, in order to address the problem of the tracking process becoming complicated with increased tracefields due to an extended trace table, the researcher suggests a method for normalizing a requirements tracetable that can integrate and separate by development process phase. Apply it to theH system development project of a D company, and this study caseverified application possibility of study, confirmed an effect of a chase to easily find out an error of requirements. Improve precision of a traceto verify consistency of requirements and completeness through this study, and will minimize failure of a software development.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.5
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• pp.1043-1054
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• 1988

The optimum cutting condition of rake angle in turning was investigated in SM45C and SM20C. Results of experiments in SM45C and SM20C are as follow. Specific cutting resistance became higher as the depth of cutting, feed or cutting velocity decreases at same rake angle and resistance became low value at 20.deg.(SM45C), 10.deg.(SM20C). The optimum cutting condition for SM45C is depth of cutting 0.7mm, rake angle 30.deg., cutting velocity 200mm/min, feed 0.1mm/rev, and for SM20C is depth of cut 0.5mm, rake angle 10.deg., cutting velocity 150mm/min, feed 0.1mm/rev.The rake angle for good roughness is 15.deg for SM45C, and that for SM20C is 25.deg. The roughness is influenced by feed and it has the lowest value at 0.1mm/rev and the cutting condition is closely related with the change of cutting velocity and feed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5150-5155
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• 2011

Alzheimer's disease (AD) and vascular dementia (VD) are the most common dementia. In this paper, we proposed a region selection for classification of AD, VD and normal (NOR) based on micro-Raman spectra from platelet. The preprocessing step is a smoothing followed by background elimination to the original spectra. Then we applied the minmax method for normalization. After the inspection of the preprocessed spectra, we found that 725-777, 1504-1592 and 1632-1700 $cm^{-1}$ regions are the most discriminative features in AD, VD and NOR spectra. We applied the feature transformation using PCA (principal component analysis) and NMF (nonnegative matrix factorization). The classification result of MAP(maximum a posteriori probability) involving 327 spectra transformed features using proposed local region showed about 92.8 % true classification average rate.

• Nutritional Sciences
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• v.5 no.1
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• pp.3-8
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• 2002

The purpose of this study was to investigate the effects of L-carnitine administration on lipid metabolism in streptozotocin-induced diabetes. Diabetes was induced by a single intraperitoneal injection of streptozotocin (50 mg/kg b.w.) and was confirmed by determination of urinary glucose secretion. Diabetic rats in the three L-carnitine treated groups were given L-carnitine, 50(D5O), 100(D100) and 200 (D200) mg/kg body weight, by subcutaneously every other day for four weeks, while animals in normal (N) and diabetic (DM) groups for control received saline by the same method. The daily weight gain was not different between normal and diabetic rats, but daily dietary intake was significantly higher in diabetic rats than in normal rat. Diabetic rats had a significantly lower carnitine concentration in both serum and liver compared to normal rats. Total carnitine concentration in serum was increased dose dependently upon carnitine administration, but statistic significance was shown only in D200 group. Diabetic rats had significantly higher serum triglyceride and cholesterol concentrations compared to normal rats. However there were no significant differences in liver L-carnitine administration to diabetic rats significantly decreased serum triglyceride but not cholesterol concentrations. In liver, triglyceride and cholesterol concentrations were not attired by L-carnitine administration. These results indicated that streptozotocin induced-diabetic rats have decreased carnitine and increased lipid concentrations compared with normal rats. Also it indicated that L-carnitine administration has an effect on the normalization of serum triglyceride concentrations in diabetic rats.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1924-1929
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• 2007

Nowadays, a lot of related data obtained from these research could be given a new present meaning to accomplish the original purpose of the whole research as a human project. The method of tumor classification based on microarray could contribute to being accurate tumor classification by finding differently expressing gene pattern statistically according to a tumor type. Therefore, the process to select a closely related informative gene with a particular tumor classification to classify tumor using present microarray technology with effect is essential. In this thesis, we used cDNA microarrays of 3840 genes obtained from neuronal differentiation experiment of cortical stem cells on white mouse with cancer, constructed accurate tumor classification model by extracting informative gene list through normalization separately and then did performance estimation by analyzing and comparing each of the experiment results. Result classifying Multi-Perceptron classifier for selected genes using Pearson correlation coefficient represented the accuracy of 95.6%.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.6
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• pp.90-94
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• 2021

With the increased interest on quiescent place for residential place, the noise generation from facilities needs to be minimized. One important noise source include sounds from operation of elevators. The elevator operates between floors and generates significantly annoying sounds to the nearby living spaces. It is recognized as the significant contributor inducing noise annoyance to residents. Elevator is supported to the building structure at several locations for movements between floors. In this study, the vibration reduction by use of polymer concrete on the support location was demonstrated. By measuring and comparing the vibration generation when supported on cement and polymer concrete, the noise reduction performance was evaluated. The polymer concrete was made in the form of being inserted into the wall that imitates the hoistway. The impact vibration was induced to the bracket and vibration transfer magnitude was measured. The damping ratio was evaluated through normalization and curve fitting of transient response, and comparison was performed for each resin mixing ratio. By use of polymer concrete, it was possible to reduce the vibration generation in an effect manner without sacrifice on the structural rigidity.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.785-794
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• 2019

Recently Deep Learning technology, one of the fourth industrial revolution technologies, is used to identify the hidden meaning of network data that is difficult to detect in the security arena and to predict attacks. Property and quality analysis of data sources are required before selecting the deep learning algorithm to be used for intrusion detection. This is because it affects the detection method depending on the contamination of the data used for learning. Therefore, the characteristics of the data should be identified and the characteristics selected. In this paper, the characteristics of malware were analyzed using network data set and the effect of each feature on performance was analyzed when the deep learning model was applied. The traffic classification experiment was conducted on the comparison of characteristics according to network characteristics and 96.52% accuracy was classified based on the selected characteristics.

• The Korean Journal of Applied Statistics
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• v.32 no.2
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• pp.301-317
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• 2019

There has been significant research conducted on how to discover various insights through text data using statistical techniques. In this study we analyzed text data produced by the Korean National Police Agency to identify trends in the work by year and compare work characteristics among local authorities by identifying distinctive keywords in documents produced by each local authority. A preprocessing according to the characteristics of each data was conducted and the frequency of words for each document was calculated in order to draw a meaningful conclusion. The simple term frequency shown in the document is difficult to describe the characteristics of the keywords; therefore, the frequency for each term was newly calculated using the term frequency-inverse document frequency weights. The L2 norm normalization technique was used to compare the frequency of words. The analysis can be used as basic data that can be newly for future police work improvement policies and as a method to improve the efficiency of the police service that also help identify a demand for improvements in indoor work.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.969-976
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• 2019

A lightweight artificial intelligence hardware has made great strides in many application areas. In general, a lightweight artificial intelligence system consist of lightweight artificial intelligence engine and preprocessor including feature selection, generation, extraction, and normalization. In order to achieve optimal performance in broad range of applications, lightweight artificial intelligence system needs to choose a good preprocessing function and set their respective hyper-parameters. This paper proposes a unified framework for a lightweight artificial intelligence system and utilization method for finding models with optimal performance to use on a given dataset. The proposed unified framework can easily generate a model combined with preprocessing functions and lightweight artificial intelligence engine. In performance evaluation using handwritten image dataset and fall detection dataset measured with inertial sensor, the proposed unified framework showed building optimal artificial intelligence models with over 90% test accuracy.

• Entomological Research
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• v.48 no.5
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• pp.390-399
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• 2018

In order to precisely assess gene expression levels, the suitable internal reference genes must be served to quantify real-time reverse transcription polymerase chain reaction (RT-qPCR) data. For armyworm, Mythimna separata, which reference genes are suitable for assessing the level of transcriptional expression of target genes have yet to be explored. In this study, eight common reference genes, including ${\beta}$-actin (${\beta}$-ACT), 18 s ribosomal (18S), 28S ribosomal (28S), glyceraldehyde-3-phosphate (GAPDH), elongation fator-alpha ($EF1{\alpha}$), TATA box binding protein (TBP), ribosomal protein L7 (RPL7), and alpha-tubulin (${\alpha}$-TUB) that in different developmental stages, tissues and insecticide treatments of M. separata were evaluated. To further explore whether these genes were suitable to serve as endogenous controls, three software-based approaches (geNorm, BestKeeper, and NormFinder), the delta Ct method, and one web-based comprehensive tool (RefFinder) were employed to analyze and rank the tested genes. The optimal number of reference genes was determined using the geNorm program, and the suitability of particular reference genes was empirically validated according to normalized HSP70, and MsepCYP321A10 gene expression data. We found that the most suitable reference genes for the different experimental conditions. For developmental stages, 28S/RPL7 were the optimal reference genes, both $RPL7/EF1{\alpha}$ were suitable for experiments of different tissues, whereas for insecticide treatments, $28S/{\alpha}-TUB$ were suitable for normalizations of expression data. In addition, $28S/{\alpha}-TUB$ were the suitable reference genes because they have the most stable expression among different developmental stages, tissues and insecticide treatments. Our work is the first report on reference gene selection in M. separata, and might serve as a precedent for future gene expression studies.