• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.9
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• pp.610-619
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• 2011

This paper investigates the simplified comfort index and control logic for VRF (Variable Refrigerant Flow) system by using 3 environmental factors such as temperature, humidity and air flow. Indoor test under thermal load was conducted to explore relationship of each environment factors that is related to simplified comfort index. Simplified comfort function that has 3 environmental variables was proposed based on survey results. Each factor is measured and comfort preference was surveyed by more than 30 subjects in the indoor comfort test. Moreover, control logic for VRF system was developed and then simulated by using thermal load calculation method and verified with test. The proposed comfort function was in good agreement with survey results, and also verification test trend of comfort change and maintenance are quite similar with survey. Furthermore, through the additional test data analysis some differences of comfort according to position of people staying in the test room were additionally investigated by air flow. People being under an exit of air in the indoor air-conditioner feel more comfortable condition and speed of response to comfort change is relatively fast.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.577-582
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• 2011

EMR(Electronic Medical Record) is an emerging technology that is highly-blended between non-IT and IT area. One of methodology to link non-IT and IT area is to construct databases. Nowadays, it supports before and after-treatment for patients and should satisfy all stakeholders such as practitioners, nurses, researchers, administrators and financial department and so on. In accordance with the database maintenance, DAS (Data as Service) model is one solution for outsourcing. However, there are some scalability and strategy issues when we need to plan to use DAS model properly. We constructed three kinds of databases such as plain-text, MS built-in encryption which is in-house model and custom AES (Advanced Encryption Standard) - DAS model scaling from 5K to 2560K records. To perform custom AES-DAS better, we also devised Bucket Index using Bloom Filter. The simulation showed the response times arithmetically increased in the beginning but after a certain threshold, exponentially increased in the end. In conclusion, if the database model is close to in-house model, then vendor technology is a good way to perform and get query response times in a consistent manner. If the model is DAS model, it is easy to outsource the database, however, some technique like Bucket Index enhances its utilization. To get faster query response times, designing database such as consideration of the field type is also important. This study suggests cloud computing would be a next DAS model to satisfy the scalability and the security issues.

• Journal of Nutrition and Health
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• v.29 no.3
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• pp.307-320
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• 1996

The enforcement and its effect of weight control program including nutrition education, exercise and behavioral modification therapy during 20 weeks were studied in primary school obese children. The sample consisted of treatment group(n=19) and control group (n=23). To evaluate the effects of weight control program, treatment group took pretest and posttest for nutrition knowledge, attitude and food habits. Nutrient intakes, serum lipid levels and anthropometric values were also measured. After weight control program, body weight of treatment group significantly decreased from 47.0$\pm$9.0kg to 45.9$\pm$8.5kg(p<0.001), but than of control group increased from 47.8$\pm$8.1kg to 49.0$\pm$8.7kg (p$\leq$0.05). Obesity index showed decline of 8.6% for treatment group and gain of 0.7% for control group. After self-control period, body weight and relate index in both groups were increased. For the nutrition knowledge test results, the posttest mean scores of treatment group showed the significant increase(p<0.001). For the attitude toward nutrition and food habit results, the posttest mean scores increased significantly (p<0.05, p<0.01). There was a decline of 28% in serum triglycerides, whereas serum total cholesterol increased 11% of baseline. These findings suggest that well-combined weight control program for obese children may result in a substantial loss of body weight during 14 weeks. In addition, these reuslts indicate that weight redution through weight control program can be a viable approach to help normalize serum lipids in obese children. Finally, these data suggest that it may be important to identify that affect weight loss and maintenance, and to examine how to manipulate these factors in weight control program.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.1
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• pp.29-39
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• 2018

In this study, the applicabilities of flood risk indices using FVI from IPCC, PSR method from OECD, and DPSIR method from EEA, were analyzed. Normalized values of daily maximum rainfall, hourly maximum rainfall, ten minute maximum rainfall, annual precipitation, total days of heavy rainfall (more than 80mm/day), density of population, density of asset, DEM, road statistics, river maintenance ratio, reservoir capacity, supply ratio of water supply and sewerage, and pumping capacity were constructed from 2000 to 2015 for nationwide 113 watersheds, to estimate flood risk indices. The estimated indices were compared to 4 different types of flood damage such as the number of casualties, damage area, the amount of flood damage, and flood frequency. The relationships between flood indices and different flood damage types demonstrated that the flood index using the PSR method shows better results for the amount of flood damage, the number of casualties and damage area, and the flood index using the DPSIR method shows better results for flood frequency.

• Korean Journal of Community Nutrition
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• v.8 no.6
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• pp.803-813
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• 2003

Literature suggests that iron deficiency anemia is prevalent among pregnant women all over the world. This study was designed to evaluate the iron status of pregnant women during the fist five months, with the intention of determining ways to reduce the prevalence of iron deficiency anemia among pregnant women in Korea. We collected dietary information and measured the biochemical status of iron in 171 pregnant women over 16 weeks of gestation (=16.7$\pm$2.34 week). Dietary intakes for 3 days were collected using the 24 hour recall and food record methods. The daily Fe intake was measured using the food frequency method. The Body Mass Index (BMI), calculated by using the pre-pregnancy weight and height, indicated that 31.3% of subjects were under-weight. We divided the subjects into normal and anemic group by using the serum ferritin levels. It appeared that the mean dietary intake of iron was 52.3% of the recommended level for pregnant women. The dietary quality evaluation showed that pregnant women ate only 58% of the recommended amount in the food groups of meat, fish, eggs, beans and milk and dairy products. The hematological indices showed that the mean Hemoglobin (Hb) was 11.9 g/dl, Hematocrit (Hct) was 35.1%, ferritin was 23.9 $ng/ml$, and transferrin was 297.3 ${\mu}g/dl$. The dietary intake of iron was significantly lower and the vitamin C intake was significantly higher in the anemic group. The pre-pregnancy BMI was significantly lower in the anemic group. Variables affecting iron intake were the Fe intake frequency index and the food group score. The Fe index showed significantly positive correlation with the pre-pregnancy food intake and the food group score. Hb showed a significantly positive correlation with the pre-pregnancy food intake. We concluded that strategies to improve iron status be implemented in the pre-pregnant stage so as to reduce the prevalence of iron deficiency and that we should stress on the importance of an adequate diet as well as the maintenance of a heathy weight.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.177-194
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• 2007

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

• The KIPS Transactions:PartA
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• v.15A no.6
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• pp.325-334
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• 2008

Flash memory is widely used as a storage medium for mobile devices such as cell phones, MP3 players, PDA's due to its tiny size, low power consumption and shock resistant characteristics. Additionally, some computer manufacturers try to replace hard-disk drives used in Laptops or personal computers with flash memory. More recently, there are some literatures on developing a flash memory-aware $B^+$-tree index for an efficient key-based search in the flash memory storage system. They focus on minimizing the number of "overwrites" resulting from inserting or deleting a sequence of key values to/from the $B^+$-tree. However, in addition to this factor, the size of a physical page allocated to a node can affect the maintenance cost of the $B^+$-tree. In this paper, with diverse experiments, we compare and analyze the costs of construction and search of the $B^+$-tree and the space requirement on flash memory as the node size increases. We also provide sorting-based or non-sorting-based algorithms to be used when inserting a key value into the node and suggest an header structure of the index node for searching a given key inside it efficiently.

• Journal of agriculture & life science
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• v.45 no.5
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• pp.127-143
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• 2011

Assessment of APC has focused on large size, specialization, and structuralization based on business performance. In the future, first, it should be complemented to have correlation with management efficiency. Second, because of the rate of weight for each index, it is necessary to develop a specific index or adjust allotting of marks so that there can be correlation between indexes. Third, since APCs have high values in the composite assessment and low values in the sales amount, it is necessary to develop various kinds of indexes, including the index to evaluate processing value-added, that of customer satisfaction with assessment, and that of customer relationship maintenance performance through introduction of a customer relationship management system (CRM), in pursuit of balance. Lastly, the results of this study are expected to be able to help make APCs efficient in relation to integration of production organizations so that they will convert and develop into a basic product processing center in coping with changes in internal and external environment of agricultural marketing.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.5
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• pp.35-42
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• 2018

In order to seek out methods to reduce safety accidents caused by construction machinery and equipment, this study collects data about safety accidents and draws main risk factors by construction from the data, through SNA. It aimed to suggest safety management points to be used in future construction fields, by analyzing risk index of such factors. The finding can be summarized: First, Backhoe Bucket is the risk factor for crash accidents of average workers in earth works; boring machines-maintenance is the risk factor for fall accidents of construction machinery operators in foundation works; bending machine-reinforcing rod processing is the risk factor for jamming accidents of reinforcing rod engineers in frame works; and mobile crane-hook is the risk factor for crash accidents of average workers in lifting works. Second, works can be arranged in turn, according to the risk index: earth, lifting, frame and foundation works. Risk factors can be also arranged according to the risk index: Backhoe in earth works, pile drivers in foundation works, bending machines in frame works and mobile cranes in lifting works. This study has some limits, in that it only analyzed main machinery/equipment, among various kinds of them, for earth, foundation, frame and temporary works (lifting works) and used data collected over three years. Therefore, it is necessary to conduct an analysis using big data, by collecting additional data about a lot of machinery/equipment in future construction fields.

• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.1-13
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• 2007

The necessity of future index is increasing to predict the future location of moving objects promptly for various location-based services. A representative research topic related to future index is the probability trajectory prediction technique that improves reliability using the past trajectory information of moving objects in the road network environment. However, the prediction performance of this technique is lowered by the heavy load of extensive future trajectory search in long-range future queries, and its index maintenance cost is high due to the frequent update of future trajectory. Thus, this paper proposes the Probability Cell Trajectory-Tree (PCT-Tree), a cell-based future indexing technique for efficient long-range future location prediction. The PCT-Tree reduces the size of index by rebuilding the probability of extensive past trajectories in the unit of cell, and improves the prediction performance of long-range future queries. In addition, it predicts reliable future trajectories using information on past trajectories and, by doing so, minimizes the cost of communication resulting from errors in future trajectory prediction and the cost of index rebuilding for updating future trajectories. Through experiment, we proved the superiority of the PCT-Tree over existing indexing techniques in the performance of long-range future queries.