• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.11a
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• pp.35-35
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• 2009

Capacitorless one transistor dynamic random access memory (1T-DRAM) cells were fabricated on the fully depleted strained-silicon-on-insulator (FD sSOI) and the effects of silicon back interface state on buried oxide (BOX) layer on the memory properties were evaluated. As a result, the fabricated 1T-DRAM cells showed superior electrical characteristics and a large sensing current margin (${\Delta}I_s$) between "1" state and "0" state. The back interface of SOI based capacitorless 1T-DRAM memory cell plays an important role on the memory performance. As the back interface properties were degraded by increase rapid thermal annealing (RTA) process, the performance of 1T-DRAM was also degraded. On the other hand, the properties of back interface and the performance of 1T-DRAM were considerably improved by post RTA annealing process at $450^{\circ}C$ for 30 min in a 2% $H_2/N_2$ ambient.

• The KIPS Transactions:PartD
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• v.8D no.1
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• pp.81-86
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• 2001

one key goal of software testing is to generate a 'good' test data set, which is consideres as the most difficult and time-consuming task. This paper discusses how genetic algorithns can be used for automatic generation of test data set for software testing. We employ mutation testing to show the effectiveness of genetic algorithms (GAs) in automatic test data generation. The approach presented in this paper is different from other in that test generation process requireas no lnowledge of implementation details of a program under test. In addition, we have conducted some experiments and compared our approach with random testing which is also regarded as a black-box test generation technique to show its effectiveness.

• Nuclear Engineering and Technology
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• v.46 no.3
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• pp.381-386
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• 2014

A highly reliable safety class controller for NPPs (Nuclear Power Plants) is mandatory as even a minor malfunction can lead to disastrous consequences for people, the environment or the facility. In order to enhance the reliability of a safety class digital controller for NPPs, we employed a diversity approach, in which a PLC-type controller and a PLD-type controller are to be operated in parallel. We built and used structured testbenches based on the classes supported by UVM for functional verification of the PLD-type controller designed for NPPs. We incorporated a UVM register model into the testbenches in order to increase the controllability and the observability of the DUT(Device Under Test). With the increased testability, we could easily verify the datapaths between I/O ports and the register sets of the DUT, otherwise we had to perform black box tests for the datapaths, which is very cumbersome and time consuming. We were also able to perform constrained random verification very easily and systematically. From the study, we confirmed the various advantages of using the UVM register model in verification such as scalability, reusability and interoperability, and set some design guidelines for verification of the NPP controllers.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.434-441
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• 2017

Containment venting is one of several essential measures to protect the integrity of the final barrier of a nuclear reactor during severe accidents, by which the uncontrollable release of fission products can be avoided. The authors seek to develop an optimization approach to venting operations, from a simulation-based perspective, using an integrated severe accident code, THALES2/KICHE. The effectiveness of the containment-venting strategies needs to be verified via numerical simulations based on various settings of the venting conditions. The number of iterations, however, needs to be controlled to avoid cumbersome computational burden of integrated codes. Bayesian optimization is an efficient global optimization approach. By using a Gaussian process regression, a surrogate model of the "black-box" code is constructed. It can be updated simultaneously whenever new simulation results are acquired. With predictions via the surrogate model, upcoming locations of the most probable optimum can be revealed. The sampling procedure is adaptive. Compared with the case of pure random searches, the number of code queries is largely reduced for the optimum finding. One typical severe accident scenario of a boiling water reactor is chosen as an example. The research demonstrates the applicability of the Bayesian optimization approach to the design and establishment of containment-venting strategies during severe accidents.

• Journal of the Semiconductor & Display Technology
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• v.18 no.2
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• pp.48-52
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• 2019

Virtual metrology, which is one of APC techniques, is a method to predict characteristics of manufactured films using machine learning with saving time and resources. As the photoresist is no longer a mask material for use in high aspect ratios as the CD is reduced, hard mask is introduced to solve such problems. Among many types of hard mask materials, amorphous carbon layer(ACL) is widely investigated due to its advantages of high etch selectivity than conventional photoresist, high optical transmittance, easy deposition process, and removability by oxygen plasma. In this study, VM using different machine learning algorithms is applied to predict the thickness of ACL and trained models are evaluated which model shows best prediction performance. ACL specimens are deposited by plasma enhanced chemical vapor deposition(PECVD) with four different process parameters(Pressure, RF power, $C_3H_6$ gas flow, $N_2$ gas flow). Gradient boosting regression(GBR) algorithm, random forest regression(RFR) algorithm, and neural network(NN) are selected for modeling. The model using gradient boosting algorithm shows most proper performance with higher R-squared value. A model for predicting the thickness of the ACL film within the abovementioned conditions has been successfully constructed.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.225-233
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• 2022

The recent outbreak of corona virus (COVID-19) infectious disease had made its forecasting critical cornerstones in most scientific studies. This study adopts a machine learning based time series model - Auto Regressive Integrated Moving Average (ARIMA) model to forecast COVID-19 confirmed cases in Botswana over 60 days period. Findings of the study show that COVID-19 confirmed cases in Botswana are steadily rising in a steep upward trend with random fluctuations. This trend can also be described effectively using an additive model when scrutinized in Seasonal Trend Decomposition method by Loess. In selecting the best fit ARIMA model, a Grid Search Algorithm was developed with python language and was used to optimize an Akaike Information Criterion (AIC) metric. The best fit ARIMA model was determined at ARIMA (5, 1, 1), which depicted the least AIC score of 3885.091. Results of the study proved that ARIMA model can be useful in generating reliable and volatile forecasts that can used to guide on understanding of the future spread of infectious diseases or pandemics. Most significantly, findings of the study are expected to raise social awareness to disease monitoring institutions and government regulatory bodies where it can be used to support strategic health decisions and initiate policy improvement for better management of the COVID-19 pandemic.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.369-379
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• 2014

The Statistical regression model has been used to construct crash prediction models, despite its limitations in assuming data distribution and functional form. In response to the limitations associated with the statistical regression models, a few studies based on non-parametric methods such as neural networks have been proposed to develop crash prediction models. However, these models have a major limitation in that they work as black boxes, and therefore cannot be directly used to identify the relationships between crash frequency and crash factors. A genetic programming model can find a solution to a problem without any specified assumptions and remove the black box effect. Hence, this paper investigates the application of the genetic programming technique to develope the crash prediction model. The data collected from the Gyeongbu expressway during the past three years (2010-2012), were separated into straight and curve sections. The random forest technique was applied to select the important variables that affect crash occurrence. The genetic programming model was developed based on the variables that were selected by the random forest. To test the goodness of fit of the genetic programming model, the RMSE of each model was compared to that of the negative binomial regression model. The test results indicate that the goodness of fit of the genetic programming models is superior to that of the negative binomial models.

• Journal of Nutrition and Health
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• v.6 no.1
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• pp.39-46
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• 1973

This study was projected to get basic data which can provide a basis for future direction in nutritional education, and also to find the way how to improve the nutritional supply by evaluating the current nutritional intake of average high school students through the survey study of their daily packed lunch. Five hundred twenty seven students from two boys high school and two girls high school including one general and one vocational school respectively were chosen as random sampling technique. Four hundred forty nine among the 527 students had brought lunch. The contents of lunch box were weighed and converted into nutritional values according to the food composition table and compared with recommended dietary allowances. The results compared and classified by sex, School and housewives' educational level were as follows: 1. The nutritional supply in the lunch box was 671 Cal of energy and 22.3 gm of protein for male students which were respectively 55.9% and 74.2% of the dietary recommendations. On the other side female student's lunch boxes were found to contain 495 Cal of energy and 21.3gm of protein which are respectively 61.8% and 80% of the dietary prescriptions. Excluding niacin, all vitamins and minerals were found to be short. 2. Calorie intake in the vocational high school was found to be higher than in the general high school but lower in protein intake especially significant difference (P<0.01) in animal protein. 3. From the nutritional point of view the educational backgrouud of the housewives was not found to have any influence in the way of preparing the lunch boxes. 4. Nutrients of lunch box were heavily inclined to grain rather than to side dishes.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.2027-2034
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• 2021

Using multi-temporal KOMPSAT-3/3A high-resolution satellite images, the Normalized Difference Vegetation Index (NDVI) for the area around the Fukushima daiichi nuclear power plant was determined, and the pattern of vegetation changes was analyzed. To calculate the NDVI, surface reflectance from the KOMPSAT-3/3A satellite image was used. Satellite images from four years were used, and the zones where the images overlap was designated as the area of interest (AOI) for the study, and by setting a profile passing through highly vegetated area as a data analysis method, the changes by year were examined. In addition, random points were extracted within the AOI and displayed as a box plot to quantitatively indicate change of NDVI distribution pattern. The main results of this study showed that the NDVI in 2014 was low within AOI in the vicinity of the nuclear power plant, but vegetated area continued to expand until 2021. These results were also confirmed in the change monitoring results shown in a profile or box plot. In disaster areas where access is restricted, such as the Fukushima nuclear power plant area, where it is difficult to collect field data, obtaining land cover classification products with high accuracy using satellite images is challenging, so it is appropriate to analyze them using primary outputs such as vegetation indices obtained from high-resolution satellite imagery. It is necessary to establish an international cooperation system for jointly utilizing satellite images. Meanwhile, to periodically monitor environmental changes in neighboring countries that may affect the Korean peninsula, it is necessary to establish utilization models and systems using high-resolution satellite images.

• Journal of Oral Medicine and Pain
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• v.14 no.1
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• pp.123-131
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• 1989

The purpose of this study is to evaluate an effect of levamisole on the chemical crcinogenesis in the submandibular salivary gland of rats through histopathologic observation. 60 male Sprague Dawley rats were employed in this study, divided into one control and two experimental groups. An pellet of 5 mg of 9, 10-dimethyl-1,2-benzathracene(DMBA) powder was implanted into submandibular salivary gland of each animal among 20 in control. And each animal among 20 in experimental group 1 received 0.7 mg of levamisole hydrochloride orally every day starting at the beginning of the fifth week after DMBA implantation under the same methods as in control. And each animal among 20 in experimental group 2 received the same treatment as in control at the beginning of the fifth week after oral administration of levamisole hydrochloride under the same method as experimental group 1. Each 5 animals in control at the end of 2nd, 4th, 6th 8th, week after experiments, and each 10 animals in experimental group 1,2 at the end of 6th, 8th week after experiments were sacrificed at random. Also the specimens from experimental sites of submandibular salivary glands were routinely processed for histopathologic observation under Hematoxilin-eosin(H-E) staining. The obtained results were as follows : 1. In control, generally, the glandular ductal cell showed the tendency of dysplasia or malignancy with progression of experiment. 2. In experimental group 1, generally, the dysplasia or malignancy of the glandular ductal cell was less prominent than in control, while the lymphocyte infiltration and fibrosis were prominent. 3. In experimental group 2, generally, the dysplasia of the glandular ductal cell was significantly less prominent than in control, while the fibrosis was prominent. 4. Under above results levamisole was thought to delay or prevent the chemical carcinogenesis in the submandibular salivary gland.