• Journal of Korean Neurosurgical Society
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• v.50 no.6
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• pp.486-491
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• 2011

Objective : Structural genetic variation, including copy-number variation (CNV), constitutes a substantial fraction of total genetic variability, and the importance of structural variants in modulating susceptibility is increasingly being recognized. CNV can change biological function and contribute to pathophysiological conditions of human disease. Its relationship with common, complex human disease in particular is not fully understood. Here, we searched the human genome to identify copy number variants that predispose to moya-moya type cerebrovascular disease. Methods : We retrospectively analyzed patients who had unilateral or bilateral steno-occlusive lesions at the cerebral artery from March, 2007, to September, 2009. For the 20 subjects, including patients with moyamoya type pathologies and three normal healthy controls, we divided the subjects into 4 groups : typical moyamoya (n=6), unilateral moyamoya (n=9), progression unilateral to typical moyamoya (n=2) and non-moyamoya (n=3). Fragmented DNA was hybridized on Human610Quad v1.0 DNA analysis BeadChips (Illumina). Data analysis was performed with GenomeStudio v2009.1, Genotyping 1.1.9, cnvPartition_v2.3.4 software. Overall call rates were more than 99.8%. Results : In total, 1258 CNVs were identified across the whole genome. The average number of CNV was 45.55 per subject (CNV region was 45.4). The gain/loss of CNV was 52/249, having 4.7 fold higher frequencies in loss calls. The total CNV size was 904,657,868, and average size was 993,038. The largest portion of CNVs (613 calls) were 1M-10M in length. Interestingly, significant association between unilateral moyamoya disease (MMD) and progression of unilateral to typical moyamoya was observed. Conclusion : Significant association between unilateral MMD and progression of unilateral to typical moyamoya was observed. The finding was confirmed again with clustering analysis. These data demonstrate that certain CNV associate with moyamoya-type cerebrovascular disease.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.1
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• pp.15-25
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• 2005

Embedded systems have a set of tasks to execute. These tasks can be implemented either on application specific hardware or as software running on a specific processor. The design of an embedded system involves the selection of hardware software resources, Partition of tasks into hardware and software, and performance evaluation. An accurate estimation of execution time for extreme cases (best and worst case) is important for hardware/software codesign. A tighter estimation of the execution time bound nay allow the use of a slower processor to execute the code and may help lower the system cost. In this paper, we consider an ARM-based embedded system and developed a tool to estimate the tight boundary of execution time of a task with loop bounds and any additional program path information. The tool we developed is based on an exiting timing analysis tool named 'Cinderella' which currently supports i960 and m68k architectures. We add a module to handle ARM ELF object file, which extracts control flow and debugging information, and a module to handle ARM instruction set so that the new tool can support ARM processor. We validate the tool by comparing the estimated bound of execution time with the run-time execution time measured by ARMulator for a selected bechmark programs.

• Journal of the Korean Society for Marine Environment & Energy
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• v.10 no.4
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• pp.201-210
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• 2007

Pollution by chemical substances such as POPs, EDCs and PBTs in the ecosystem has become more complex and varied, increasing the possibility of irreversible damage to human health or the ecosystem. It is necessary to have a exposure assessment in a multi-media environment for various chemical substances is required for efficient management. This study applied MUSEM(Multi-media Simplebox-systems Environmental Model), a multimedia environmental model that can simultaneously evaluate the possibility of exposure of hundreds of chemical substances in order to efficiently manage chemical substances that can have negative impact on human health or ecological environment through environmental contamination. MUSEM executed the modeling for Japan by setting all 47 prefectures of japan as the regional area for 62 chemical substances and the rest of the territory of japan, excluding regional area, as the continental area and made the estimation of concentration among environment media in each administrative area and made the sensitivity analysis on Tokyo area. The results of simulation for chemical distribution showed that most of the target chemicals located in water region. The result of sensitivity analysis for octanol-water partition rate showed that the concentration change of soil in urban/industrial area and sediment in freshwater was high. In the case of sensitivity analysis for degradation rate showed that the concentration change of freshwater, soil in urban/industrial area, and sediment in freshwater was high.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of the Korean Society of Radiology
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• v.12 no.7
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• pp.895-908
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• 2018

As modern science is developed and advanced, examination and number of times using radiation are increasing daily. General diagnostic X-ray generator is installed on stationary form, But X-ray generator was developed because patient who is in the intensive care unit, operation room, emergency room can not move to general x-ray room. What we examine patient by x-ray generator is certainly necessary, So patient exposure is inevitable. but reducing radiation exposure is highly important matter about radiation technology, guardian, patient in the same hospital room, nurse etc. For this reason, rule regarding safety control of diagnostic x-ray generator revised for radiation worker, patient and protector proclaim that mobile diagnostic x-ray shield must placed in case of examine different location excluding operation room, emergency room, intensive care unit. But, radiogical technologist is having a lot of difficulties to examine with mobile x-ray generator, diagnostic x-ray shield partition, image plate and lead apron. So, when we use x-ray generator, we manufacture shield tools can be attached to the mobile x-ray generator On behalf of x-ray shield partition and conduct analysis and in comparison to part of body and distribution of dose rate and find way to reduce radiation exposure through distribution of dose rate of patient within the radiogical technologist, medical team. Mobile x-ray generator aimed at SHIMADZU inc. R-20, We manufactured equipment for shielding x-ray scattered x-ray by installing shielding wall from side to side based on support beam on the mobile x-ray generator. Shielding wall when moving can be folded and designed to expand when examine. Experiment measured five times in each by an angle for dose rate of eyes, thyroid, breast, abdomen and gonad on exposure condition of upper and lower extremity, chest, abdomen which is examined many times by mobile x-ray generator. We used dosimeter RSM-100 made by IJRAD and measured a horizontal dose rate by body part. The result of an experiment, shielding decreasing rate of the front and the rear showed 77 ~ 98.7%. Therefore using self-production shielding wall reduce scattered x-ray occurrence rate and confirm can decrease exposure dose consequently. Therefore, through this study, reduction result which is used shielding wall of self-production will be a role of shielding optimization and it could be answer about reduction of medical exposure recommended by ICRP 103.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.523-541
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• 2023

As accessibility to 3D printers increases, there is a growing frequency of exposure to chemicals associated with 3D printing. However, research on the toxicity and harmfulness of chemicals generated by 3D printing is insufficient, and the performance of toxicity prediction using in silico techniques is limited due to missing molecular structure data. In this study, quantitative structure-activity relationship (QSAR) model based on data-centric AI approach was developed to predict the toxicity of new 3D printing materials by imputing missing values in molecular descriptors. First, MissForest algorithm was utilized to impute missing values in molecular descriptors of hazardous 3D printing materials. Then, based on four different machine learning models (decision tree, random forest, XGBoost, SVM), a machine learning (ML)-based QSAR model was developed to predict the bioconcentration factor (Log BCF), octanol-air partition coefficient (Log Koa), and partition coefficient (Log P). Furthermore, the reliability of the data-centric QSAR model was validated through the Tree-SHAP (SHapley Additive exPlanations) method, which is one of explainable artificial intelligence (XAI) techniques. The proposed imputation method based on the MissForest enlarged approximately 2.5 times more molecular structure data compared to the existing data. Based on the imputed dataset of molecular descriptor, the developed data-centric QSAR model achieved approximately 73%, 76% and 92% of prediction performance for Log BCF, Log Koa, and Log P, respectively. Lastly, Tree-SHAP analysis demonstrated that the data-centric-based QSAR model achieved high prediction performance for toxicity information by identifying key molecular descriptors highly correlated with toxicity indices. Therefore, the proposed QSAR model based on the data-centric XAI approach can be extended to predict the toxicity of potential pollutants in emerging printing chemicals, chemical process, semiconductor or display process.

• Journal of Educational Research in Mathematics
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• v.20 no.1
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• pp.85-102
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• 2010

Linear programming(LP) is useful for finding the best way in a given condition for some list of requirements represented as linear equations. This study analysed LP in mathematics contexts and LP in school mathematics contexts, considered learning process of LP from an epistemological point of view, and explored a hypothetical learning trajectory of LP. The differences between mathematics contexts and school mathematics contexts are whether they considered that the convex polytope $\Omega$ is feasible/infeasible or bounded/unbounded or not, and whether they prove the theorem that the optimum is always attained at a vertex of the polyhedronor not. And there is a possibility that students could not understand what is maximum and minimum of a linear function when the domain of the function is limited. By considering these three aspects, we constructed hypothetical learning trajectory consisted of 4 steps. The first step is to see a given linear expression as linear function, the second step is to partition a given domain by straight lines, the third step is to construct the conception of y-intercept by relating lines and the range of k, and the forth step is to identify whether there exists the optimum in a given domain or not.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.44 no.5
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• pp.72-79
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• 2012

In this study, to understand the aging factor and mechanism in different partitions of the beeswax-treated volumes, the duplicated beeswax-treated volume was artificially aged at $80^{\circ}C$ of temperature and 65% of relative humidity and then a physical and optical properties of an aged volumes was analyzed. Also, the degraded components of the beeswax samples isolated from different partitions of aged volumes was measured using a gas chromatography/mass spectroscopy (GC/MS). In results, the surface of beeswax-treated volume which is primarily affected by a main aging factors such as light, oxygen, moisture was more deteriorated than the inside of that volume. However, unlike inside of the book volume which was made from paper, the inside of beeswax-treated volume wax was also considerably deteriorated. The inside of the beeswax-treated volume is largely unaffected by the oxygen and humidity during aging due to the water repellency and the air permeation resistance of beeswax. Therefore, it is confirmed that aging factors and mechanisms in the inside of the volume are different from thats of the outside of the volume. This fact was also verified by the results of GC/MS analysis of an beeswax samples which was sampled from different partitions of aged volumes. As result as GC/MS analysis of the beeswax extracted from the outside of the aged volume, the low molecular compounds with a carbon length of $C_9-C_{20}$ (fatty acid, etc) were increased and the compounds with a carbon length of above $C_{34}$ (ester, etc) were also increased. But the compounds with a chain length of $C_{21}-C_{36}$ (hydrocarbon, alcohol, etc) were decreased. In case of the aged beeswax of inside, the low molecular compounds with a carbon length of $C_9-C_{20}$ (fatty acid, etc) and the compounds with a chain length of $C_{21}-C_{36}$ (hydrocarbon, alcohol, etc) were increased. While, the compounds with a carbon length of above $C_{34}$ (ester, etc) were decreased.

• The Korean Journal of Pesticide Science
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• v.19 no.4
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• pp.345-353
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• 2015

The aim of this study is to develop residue analysis method for fenoxanil, a MBI (melanin biosynthesis inhibitor) propionamide fungicide, had mainly been used to control rice blast, and disease of other crops, fruits, and vegetables by using GLC/NPD and GC/MS. Extraction with acetone and partition with n-hexane/dichloromethane (80/20, v/v) were performed from hulled rice, soybean, Kimchi cabbage, green pepper, and apple, then column clean-up with florisil was applied. Mean recoveries were 82.2%-109.1% with less than 7.2% of coefficients of variation and limit of quantitation was set at the concentration of 0.04 mg/kg from the five agricultural products through the determination by GLC/NPD equipped with DB-5 capillary column and single laboratory validation. As a confirmatory method, GC/MS selected ion monitoring (SIM) was set from m/z 125.0, 188.9, and 293.0. Developed method is expected to apply the single residue analysis of fenoxanil in agricultural products.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.177-187
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• 1999

Up to date, in many application fields of GSIS, we usually have used vector-based spatial overlay or grid-based spatial algebra for extraction and analysis of spatial data. But, because these methods are based on traditional crisp set, concept which is used these methods. shows that many kinds of spatial data are partitioned with sharp boundary. That is not agree with spatial distribution pattern of data in the real world. Therefore, it has a error that a region or object is restricted within only one attribution (One-Entity-one-value). In this study, for improving previous methods that deal with spatial data based on crisp set, we are suggested to apply into spatial overlay process the concept of fuzzy set which is good for expressing the boundary vagueness or ambiguity of spatial data. two methods be given. First method is a fuzzy interval partition by fuzzy subsets in case of spatially continuous data, and second method is fuzzy boundary set applied on categorical data. with a case study to get a land suitability map for the development site selection of new town, we compared results between Boolean analysis method and fuzzy spatial overlay method. And as a result, we could find out that suitability map using fuzzy spatial overlay method provide more reasonable information about development site of new town, and is more adequate type in the aspect of presentation.