• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.1-7
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• 2017

Forensic Engineering is the art and science of professionals qualified to serve as engineering experts in courts of law or in arbitration proceedings. Buses using compressed natural gas (CNG) trend to be extended in use internationally as optimal counterplan for reducing discharge gas of light oil due to high concern about environment. However, CNG buses is equipped with composite pressure vessels (CPVs); since the CPVs contain compressed natural gas, the risks in the case of accident is very high. In this study, the bursting test for the pressure vessel depending on the heat treatment conditions of the vessel in which the actual ruptured accident occurred, after the bursting test, the fracture pattern analysis had performed. The mechanical materials properties test using Instrumented Indentation Test had performed to confirm the mechanical properties for each heat treatment cases. Also, the fractography analysis and metallographic analysis had performed to find out the difference of each heat treatment case. By comparing normal vessel with abnormal vessel which have defect of heat treatment conditions in term of the bursting patterns and characteristics of containers using various forensic engineering methods, especially, it is possible to understand how important the heat treatment process is in the high pressure vessel unlike any product.

• Design & Manufacturing
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• v.17 no.3
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• pp.34-40
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• 2023

In this study, real-time collection of mold vibration signals during injection molding processes was achieved through IoT devices installed on the mold surface. To analyze changes in the collected vibration signals, injection molding was performed under six different process conditions. Analysis of the mold vibration signals according to process conditions revealed distinct trends and patterns. Based on this result, cosine similarity was applied to compare pattern changes in the mold vibration signals. The similarity in time and acceleration vector space between the collected data was analyzed. The results showed that under identical conditions for all six process settings, the cosine similarity remained around 0.92±0.07. However, when different process conditions were applied, the cosine similarity decreased to the range of 0.47±0.07. Based on these results, a cosine similarity threshold of 0.60~0.70 was established. When applied to the analysis of mold vibration signals, it was possible to determine whether the molding process was stable or whether variations had occurred due to changes in process conditions. This establishes the potential use of cosine similarity based on mold vibration signals in future applications for real-time monitoring of molding process changes and anomaly detection.

• Clinical and Experimental Reproductive Medicine
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• v.13 no.1
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• pp.21-28
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• 1986

It is now apparent that many cases of amenorrhea. oligomenorrhea. corpus luteum deficiency, galactorrhea, and infertility are due to hyperprolactinemia. We investigated the relationships between serum prolactin values and factors such as menstrual pattern, frequency of galactorrhea etc, in 135 hyperproIactinemic patients at the Seoul National University Hospital during a period of 6 years, from January, 1979 to December, 1984. The results was as follows: 1. Menstrual pattern changed according to the serum prolactin level. The frequency of amenorrhea is 1.7 percent in patients with serum prolactin levels ranged from $25{\sim}40ng/ml$, whereas 72.4 percent in patients with serum prolactin levels above 100ng/ml. 2. The incidence of galactorrhea in hyperprolactinemic patients was 3.1 percent and the frequency of galactorrhea had direct relationship with the serum prolactin level and/or the frequency of abnormal menstrual pattern. 3. The incidence of pituitary tumor in hyperprolactinemic patients was 104 percent and sixty percent of patients with serum prolactin levels above 100ng/ml had a pituitary tumor . 4. There was an inverse correlation between serum prolactin and progesletone value. 5. The frequency of anovulatory menstrual cycle evidenced by basal body temperature is 23.9 percent in patients with serum prolactin levels ranged from $20{\sim}40ng/ml$, whereas 76.9 percent in patients with serum prolactin levels above 100ng/ml.

• Journal of Yeungnam Medical Science
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• v.2 no.1
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• pp.71-75
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• 1985

The clinical state with EEG pattern similar to interval discharge of epileptics is named as latent epilepsy, which does not necessarily mean that the patient will develop epilepsy later. However, since there is possibility of developing epilepsy on later date, antiepileptic mainly dilantin was tried to control the abnormal EEG. Since January to October 1985, total 580 headache sases with more than moderately abnormal EEG Visited the Neurology clinic. Among them 162 cases with interval seizure pattern (ISP) of epilepsy were selected for the study. The main ISP was 1. diffuse theta and/or delta bursts and 2. spikes. Since the study is only analysis of clinical treatment of 162 cases Without previous planning based on financial aid, about 30% of the patients did not return after the 1st EEG examination, in 42% failed to follow the EEG after the treatment and only remaining 28% of the cases were studied. Among 29 patients who were treated with Dilantin 100mg tid po, 16 improved and 13 not. Of the 13, 4 showed partial Improvement and partial progression. Case 1. In 4 weeks of antiepileptic the ray (AR), spikes disappeared but in 2 months developed bursts. Case 2. In 17days of AR, spikes and bursts disappeared but in 3 months bursts reccured. Case 3. In 1 week of AR, bursts disappeared but spikes developed. Case 4. In 3 months of AR, no change of spikes and bursts and she discontinued the AR. In 6 months she developed grandmal seizure. Eighteen cases, treated with other drugs except antiepileptics, all showed improvement. The other drugs were vincaprol, polygammalon, aronamin, ATP and hydergine. The improved cases had spikes more often than theta bursts. In view of the small number of the cases due to dropping most patients out of present study, it is considered meaningless to perform statistical analysis. Further well planned study With more patients is to be expected.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.2
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• pp.47-56
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• 2015

In an energy saving server cluster environment, the power modes of servers are controlled according to load situation, that is, by making ON only minimum number of servers needed to handle current load while making the other servers OFF. This algorithm works well under normal circumstances, but does not guarantee QoS under abnormal circumstances such as sharply rising or falling loads. This is because the number of ON servers cannot be increased immediately due to the time delay for servers to turn ON from OFF. In this paper, we propose a new prediction algorithm of the power consumption for improving QoS under not only normal but also abnormal circumstances. The proposed prediction algorithm consists of two parts: prediction based on the conventional time series analysis and prediction adjustment based on trend analysis. We performed experiments using 15 PCs and compared performance for 4 types of conventional time series based prediction methods and their modified methods with our prediction algorithm. Experimental results show that Exponential Smoothing with Trend Adjusted (ESTA) and its modified ESTA (MESTA) proposed in this paper are outperforming among 4 types of prediction methods in terms of normalized QoS and number of good reponses per power consumed, and QoS of MESTA proposed in this paper is 7.5% and 3.3% better than that of conventional ESTA for artificial load pattern and real load pattern, respectively.

• Journal of Convergence for Information Technology
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• v.7 no.1
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• pp.55-60
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• 2017

In order to provide intelligent services without human intervention in the Internet of Things environment, it is necessary to analyze the big data generated by the IoT device and learn the normal pattern, and to predict the abnormal symptoms such as faulty or malfunction based on the learned normal pattern. The purpose of this study is to implement a machine learning model that can predict product failure by analyzing big data generated in various devices of product process. The machine learning model uses the big data analysis tool R because it needs to analyze based on existing data with a large volume. The data collected in the product process include the information about product faulty, so supervised learning model is used. As a result of the study, I classify the variables and variable conditions affecting the product failure, and proposed a prediction model for the product failure based on the decision tree. In addition, the predictive power of the model was significantly higher in the conformity and performance evaluation analysis of the model using the ROC curve.

• Reproductive and Developmental Biology
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• v.33 no.1
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• pp.41-48
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• 2009

Placenta is the main nutrition source for the fetus during pregnancy. Thus, it has a pivotal function in the pregnant process. Many functions of the placenta have been elucidated. An abnormal placenta is associated with a high rate of pregnancy failure in somatic cloned bovine. Differentially expressed genes (DEGs) were examined in a comparison between normal and cloned bovine placenta using annealing control primer (ACP)-based GeneFishing PCR. Using 120 ACPs, nearly 80 genes were identified and the fragments of 42 DEGs were sequenced. 38 of these genes were known genes and four were unknown. To determine the DEGs result, six target clones expressing on one-side of a normal and a clone placenta were selected. Through an analysis of the target genes using the real-time PCR, the expressing pattern was found to be somewhat different from the DEGs. Additionally, several genes appeared with the same expression pattern. Taken together, this suggests that the target genes would be essential for research into what influences the placental formative mechanisms during fetal development.

• The korean journal of orthodontics
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• v.25 no.6 s.53
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• pp.723-731
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• 1995

Type I and type II collagens are considered the major collagens of bone and cartilage respectively. Monitoring the patterns of those gene and protein expressions during development will provide a basis for the understanding of the normal and abnormal growths. This study was undertaken to investigate the expression of collagen genes and proteins involved in the developing human mandible. Fifty embryos and fetuses were studied with Alcian blue-PAS, Masson's Trichrome, reverse transcription polymerase chain reaction (RT-PCR), Western blot analysis, and Southern blot analysis. Our results showed that $pro-{\alpha}1(II)$ collagen gene expression begins in the 5th week. Type II collagen is synthesized in mesenchymal cells in advance: of overt chondrogenesis. The gene expression for type II collagen was highest during the appearance of Meckel's cartilage. There was a switch in collagen protein expression from type I to type II during the appearance stage of Meckel's cartilage. The distribution of the mRNA for type II collagen corresponded well with the pattern of type II collagen protein. The endochondral ossification was observed where there was direct replacement of cartilage by bone.

• Biomedical Science Letters
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• v.12 no.4
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• pp.349-354
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• 2006

Induction of apoptosis allows the organism to get rid of abnormal cells and also of tumor cells. Understanding the mechanism involved in Ultraviolet radiation (UV) induced apoptosis may improve its therapeutic efficacy. In this study, we present expression of poly (ADP-ribose) polymerase (PARP) during apoptosis induced by UV in HeLa $S_3$ cells. Four different assays were performed in this study: morphological assessment of apoptotic cells and cell viability, DNA fragmentation analysis by agarose gel electrophoresis, quantitative assay of fragmented DNA, and expression of PARP by the western blot analysis. The percentages of apoptotic HeLa $S_3$ cells irradiated with $75J/m^2$ UV was increased continuously from 3 hrs incubation. DNA ladder pattern was appeared at 6 hrs. The amount of nucleosomal DNA fragments in cells treated UV increased from 3 to 12 hrs incubation and gradually decreased. The cleavage of PARP in HeLa $S_3$ cells irradiated with UV was induced, and the cleavage of PARP was more delayed in the cells pretreated with $5J/m^2$ UV and subsequently irradiated with $75J/m^2$ UV. than that in the cells only irradiated with $75J/m^2$ UV. Thus these data suggest that the cleavage of PARP relates with DNA fragmentation associated with apoptosis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.342-344
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• 2018

This paper shows the possibility to substitute statistical methods such as mean imputation, correlation coefficient analysis, graph correlation analysis for the proposed algorithm, and replace statistician for processing various abnormal data measured in the water treatment process with it. In addition, this study aims to model a data-filtering system based on a recent fractile pattern and a deep learning-based LSTM algorithm in order to improve the reliability and validation of the algorithm, using the open-sourced libraries such as KERAS, THEANO, TENSORFLOW, etc.