• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Journal of the Microelectronics and Packaging Society
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• v.25 no.1
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• pp.1-10
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• 2018

Recently, there has been rapid development in the field of flexible electronic devices, such as organic light emitting diodes (OLEDs), organic solar cells and flexible sensors. Encapsulation process is added to protect the flexible electronic devices from exposure to oxygen and moisture in the air. Using numerical simulation, we investigated the effects of the encapsulation layer on mechanical stability of the silicon chip, especially the fracture performance of center crack in multi-layer package for various loading condition. The multi-layer package is categorized in two type - a wide chip model in which the chip has a large width and encapsulation layer covers only the chip, and a narrow chip model in which the chip covers both the substrate and the chip with smaller width than the substrate. In the wide chip model where the external load acts directly on the chip, the encapsulation layer with high stiffness enhanced the crack resistance of the film chip as the thickness of the encapsulation layer increased regardless of loading conditions. In contrast, the encapsulation layer with high stiffness reduced the crack resistance of the film chip in the narrow chip model for the case of external tensile strain loading. This is because the external load is transferred to the chip through the encapsulation layer and the small load acts on the chip for the weak encapsulation layer in the narrow chip model. When the bending moment acts on the narrow model, thin encapsulation layer and thick encapsulation layer show the opposite results since the neutral axis is moving toward the chip with a crack and load acting on chip decreases consequently as the thickness of encapsulation layer increases. The present study is expected to provide practical design guidance to enhance the durability and fracture performance of the silicon chip in the multilayer package with encapsulation layer.

• Journal of Science Education
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• v.39 no.3
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• pp.358-375
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• 2015

The purposes of this study were to investigate the value, necessity and legitimacy of STEAM Education and to propose practical approaching methods for STEAM Education to be applicable in Korea through a variety of literature review, case studies and collecting suggestions from domestic and international educational experts. The research questions are as follows: (1) To investigate the perception, understanding and recognitions of domestic and foreign professionals in STEAM education. (2) To analyze policy implications for an improvement in STEAM. The following aspects of STEAM were found to be challenges in our current STEAM policy after analyzing multiple questionnaires with the professionals and case studies including their experiences, understanding, supports and directions of the policy from the governments. The results indicate that (1) there was a lack of precise and conceptual understanding of STEAM in respect to experience. Training sessions for teachers in this field to help transform their perception is necessary. Development of practical programs with an easy access is also required. It is important to get the aims of related educational activities recognized by the professionals and established standards for an evaluation. The experts perceived that a theme-based learning is the most preferred and effective approaching method and the programs that develop creative thinking and learning applicable to practice are required to promote. (2) The results indicate that there was a lack of programs and inducements for supporting outstanding STEAM educators. It is shown that making an appropriate environment for STEAM education takes the first priority before training numbers of teachers unilaterally, thus securing enough budget seems critical. The professionals also emphasize on developing specialized teaching materials that include diverse inter-related subjects such as science technology, engineering, arts and humanities and social science with diverse viewpoints and advanced technology. This work requires a STEAM network for teachers to link up and share their materials, documents and experiences. It is necessary to get corporations, universities, and research centers participated in the network. (3) With respect to direction, it is necessary to propose policy that makes STEAM education ordinary and more practical in the present education system. The professionals have recommended training sessions that help develop creative thinking and amalgamative problem-solving techniques. They require reducing the workload of teachers and changing teachers' perspectives towards STEAM. They further urge a tight cooperation between departments of the government related with STEAM.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.25 no.3
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• pp.366-379
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• 2015

Objectives: The objective of this study is to assess airborne particulate matter(PM) pollution and its effect on health of residents living near Ansim Briquette Fuel Complex in Daegu metropolitan region. Methods: The California Puff(CALPUFF) dispersion model, version 5.8, which can estimate the dispersion direction and range of airborn $PM_{10}$ was used to determine the possible areas affected by $PM_{10}$ pollutants emitted from Ansim briquette fuel complex. The CALPUFF modeling with 200 m grid-cell resolution was performed based on $PM_{10}$ emissions estimated from the amount of coal consumption in the fuel complex for four months in 2012. The Weather Research and Forecasting(WRF) fields were processed using CALMET to produce CALPUFF-ready meteorological inputs. Also, the distance from Ansim Briquette Fuel Complex to the residence of each environmental pneumoconiosis patient was analyzed. In addition, the affecting region of the pollutants emitted from briquette factories in Ansim Briquette Fuel Complex was determined. Results: CALPUFF modeling results showed that the highest concentrations of $PM_{10}$ were found near around the fuel complex. The modeled $PM_{10}$ distributions were characterized by significant decreases in concentration with distance from the complex. Seasonally, the highest concentration of $45{\mu}g/m^3$ was calculated in October which was mostly due to the distinct variation of amount of emission. Additional modeling with the maximum $PM_{10}$ emission of about 88 tons per year in 1986 showed that the highest concentration in October was nearly increased by 8 times than the concentration modeled with emission of 2010. As a result of medical examination and interviews for the residents in Ansim Briquette Fuel Complex and its surroundings, 8 environmental pneumoconiosis patients were found. These patients do not have occupational exposure and history. These patients have lived 0.3~1.1 km area in Ansim Briquette Fuel Complex and its surroundings. Conclusions: Airborne particles emitted from Ansim Briquette Fuel Complex can contribute to significant increase in $PM_{10}$ concentration in residential areas near around the complex. Especially, the residents near fuel complex may exposed to the pollutants emitted from the factories in Ansim Briquette Fuel Complex.

• Applied Chemistry for Engineering
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• v.27 no.4
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• pp.391-396
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• 2016

The absorption efficiency of amine $CO_2$ absorbent (KoSol-5) developed by KEPCO research institute was evaluated using a 0.1 MW test bed. The performance of post-combustion technology to capture two tons of $CO_2$ per day from a slipstream of the flue gas from a 500 MW coal-fired power station was first confirmed in Korea. Also the analysis of the absorbent regeneration energy was conducted to suggest the reliable data for the KoSol-5 absorbent performance. And we tested energy reduction effects by improving the absorption tower inter-cooling system. Overall results showed that the $CO_2$ removal rate met the technical guideline ($CO_2$ removal rate : 90%) suggested by IEA-GHG. Also the regeneration energy of the KoSol-5 showed about $3.05GJ/tonCO_2$ which was about 25% reduction in the regeneration energy compared to that of using the commercial absorbent MEA (Monoethanolamine). Based on current experiments, the KoSol-5 absorbent showed high efficiency for $CO_2$ capture. It is expected that the application of KoSol-5 to commercial scale $CO_2$ capture plants could dramatically reduce $CO_2$ capture costs.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.1-16
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• 2015

Traffic accident is one of the major cause of death worldwide for the last several decades. According to the statistics of world health organization, approximately 1.24 million deaths occurred on the world's roads in 2010. In order to reduce future traffic accident, multipronged approaches have been adopted including traffic regulations, injury-reducing technologies, driving training program and so on. Records on traffic accidents are generated and maintained for this purpose. To make these records meaningful and effective, it is necessary to analyze relationship between traffic accident and related factors including vehicle design, road design, weather, driver behavior etc. Insight derived from these analysis can be used for accident prevention approaches. Traffic accident data mining is an activity to find useful knowledges about such relationship that is not well-known and user may interested in it. Many studies about mining accident data have been reported over the past two decades. Most of studies mainly focused on predict risk of accident using accident related factors. Supervised learning methods like decision tree, logistic regression, k-nearest neighbor, neural network are used for these prediction. However, derived prediction model from these algorithms are too complex to understand for human itself because the main purpose of these algorithms are prediction, not explanation of the data. Some of studies use unsupervised clustering algorithm to dividing the data into several groups, but derived group itself is still not easy to understand for human, so it is necessary to do some additional analytic works. Rule based learning methods are adequate when we want to derive comprehensive form of knowledge about the target domain. It derives a set of if-then rules that represent relationship between the target feature with other features. Rules are fairly easy for human to understand its meaning therefore it can help provide insight and comprehensible results for human. Association rule learning methods and subgroup discovery methods are representing rule based learning methods for descriptive task. These two algorithms have been used in a wide range of area from transaction analysis, accident data analysis, detection of statistically significant patient risk groups, discovering key person in social communities and so on. We use both the association rule learning method and the subgroup discovery method to discover useful patterns from a traffic accident dataset consisting of many features including profile of driver, location of accident, types of accident, information of vehicle, violation of regulation and so on. The association rule learning method, which is one of the unsupervised learning methods, searches for frequent item sets from the data and translates them into rules. In contrast, the subgroup discovery method is a kind of supervised learning method that discovers rules of user specified concepts satisfying certain degree of generality and unusualness. Depending on what aspect of the data we are focusing our attention to, we may combine different multiple relevant features of interest to make a synthetic target feature, and give it to the rule learning algorithms. After a set of rules is derived, some postprocessing steps are taken to make the ruleset more compact and easier to understand by removing some uninteresting or redundant rules. We conducted a set of experiments of mining our traffic accident data in both unsupervised mode and supervised mode for comparison of these rule based learning algorithms. Experiments with the traffic accident data reveals that the association rule learning, in its pure unsupervised mode, can discover some hidden relationship among the features. Under supervised learning setting with combinatorial target feature, however, the subgroup discovery method finds good rules much more easily than the association rule learning method that requires a lot of efforts to tune the parameters.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.9
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• pp.917-925
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• 2006

The aim of our research was to apply experimental design methodology in the optimization of photocatalytic degradation of azo dye(Reactive orange 16). The reactions were mathematically described as a function of parameters amount of $TiO_2(x_1)$, and dye concentration($x_2$) being modeled by the use of the Box-Behnken method. The results show that the responses of color removal(%)($Y_1$) in photocatalysis of dyes were significantly affected by the synergistic effect of linear term of $TiO_2(x_1)$ and dye concentration($x_2$). Significant factors and synergistic effects for the $COD_{Cr}$, removal(%)($Y_2$) were the linear term of $TiO_2(x_1)$ and dye concentration($x_2$). However, the quadratic term of $TiO_2(x_1^2)$ and dye concentration($x_2^2$) had an antagonistic effect on $Y_1$ and $Y_2$ responses. Canonical analysis indicates that the stationary point was a saddle point for $Y_1$ and $Y_2$, respectively. The estimated ridge of maximum responses and optimal conditions for $Y_1:(X_1,\;X_2)$=(1.11 g/L, 51.2 mg/L) and $Y_2:(X_1,\;X_2)$=(1.42 g/L, 72.83 mg/L) using canonical analysis was 93% and 73%, respectively.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.1
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• pp.85-92
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• 2005

The performance of a novel fermentation process, adopting a sludge blanket type configuration for higher hydrolysis/acidogenesis of the municipal primary sludge, was investigated under batch and semi-continuous conditions with various pH and temperature conditions. This acid elutriation slurry reactor provided higher system performance with a short HRT (5 days) and higher acidogenic effluent quality under pH 9 and thermophilic ($55^{\circ}C$) conditions. The hydrolysis of the sludge was revealed to be significantly dependent on seasonal effects for sludge characteristics but with little impact on acidogenesis. Based on the rainy season at the optimum conditions, VFA production and recovery fraction ($VFA_{COD}/COD$) were $0.18\;g\;VFA_{COD}\;g^{-1}\;VSS_{COD}$ and 63%. As byproducts, nitrogen and phosphorus releasing were $0.006\;g\;N\;g^{-1}\;VSS_{COD}$ and $0.003\;g\;P\;g^{-1}\;VSS_{COD}$, respectively. For the mass balance in a full-scale plant($Q=158,880\;m^3\;day^{-1}$) based on the rainy season, the VFA and non-VFA(as COD) production were $3,110\;kg\;VFA_{COD}\;day^{-1}$ and $1,800\;kg\;COD\;day^{-1}$, resulting in an increase of organics of $31\;mg\;COD\;L^{-1}$ and $20\;mg\;VFA_{COD}\;L^{-1}$ and nutrients of $0.7\;mg\;N\;L^{-1}$ and $0.3\;mg\;P\;L^{-1}$ in the influent sewage. The economical benefit from this process application was estimated to be about $67 per $1,000m^3$ of sewage except for energy requirements and also, better benefits can be expected during the dry season. Also, the results revealed that the process has various additional advantages such as pathogen-free stabilized solids production, excellent solids control and economical benefits.

• Applied Chemistry for Engineering
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• v.26 no.1
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• pp.29-34
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• 2015

N,N'-Diferuloyl-putrescine (DFP) present in plants such as Sophora japonica has been reported to have skin depigmentative and antioxidative activities. In this study, DFP, usually presents in nature a very little amount and its derivative (DFP-D) were synthesized in a large quantity for the use as functional cosmetical materials. The antioxidative activities of synthesized DFP and DFP-D were evaluated by the 1,1-diphenyl-2-picrylhydrazyl (DPPH) assay, chemiluminescence assay, and cell protective effect induced by $^1O_2$, stress. DFP and DFP-D showed DPPH radical scavenging activities ($FSC_{50}$) at $61.25{\pm}2.25{\mu}M$ and $12.92{\pm}0.72{\mu}M$, respectively. ROS (reactive oxygen species) scavenging activities ($OSC_{50}$) in the $Fe^{3+}-EDTA/H_2O_2$ system of DFP and DFP-D were 2 times ($1.84{\pm}0.12{\mu}M$) and 13 times ($0.174{\pm}0.01{\mu}M$), respectively higher than that of L-ascorbic acid. $^1O_2$, one of ROS playing a key role in the skin photo-aging, induces cellular membrane damages. DFP-D ($50{\mu}M$) showed good cell protective effects (${\tau}_{50}=80.2min$) about 2 times more than that of (+)-${\alpha}$-tocopherol (${\tau}_{50}=43.6min$). These results suggest that the great antioxidative activities of DFP and DFP-D could be applied to cosmetic industries as functional cosmetic materials.

• Journal of Bio-Environment Control
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• v.22 no.1
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• pp.27-33
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• 2013

In order to provide basic data for the development of a controlled environment cultivation system and standardization of the structures, structural status and improvement methods were investigated for the fruit tree greenhouses of grape, pear, and peach. The greenhouses for citrus and grape cultivation are increasing while pear and persimmon greenhouses are gradually decreasing due to the advance of storage facilities. In the future, greenhouse cultivation will expand for the fruit trees which are more effective in cultivation under rain shelter and are low in storage capability. Fruit tree greenhouses were mostly complying with standards of farm supply type models except for a pear greenhouse and a large single-span peach greenhouse. It showed that there was no greenhouse specialized in each species of fruit tree. Frame members of the fruit tree greenhouses were mostly complying with standards of the farm supply type model or the disaster tolerance type model published by MIFAFF and RDA. In most cases, the concrete foundations were used. The pear greenhouse built with the column of larger cross section than the disaster tolerance type. The pear greenhouse had also a special type of foundation with the steel plate welded at the bottom of columns and buried in the ground. As the results of the structural safety analysis of the fruit tree greenhouses, the grape greenhouses in Gimcheon and Cheonan and the peach greenhouses in Namwon and Cheonan appeared to be vulnerable for snow load whereas the peach greenhouse in Namwon was not safe enough to withstand wind load. The peach greenhouse converted from a vegetable growing facility turned out to be unsafe for both snow and wind loads. Considering the shape, height and planting space of fruit tree, the appropriate size of greenhouses was suggested that the grape greenhouse be 7.0~8.0 m wide and 2.5~2.8 m high for eaves, while 6.0~7.0 m wide and 3.0~3.3 m of eaves height for the pear and peach greenhouses.