• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Korean Journal of Construction Engineering and Management
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• v.15 no.1
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• pp.87-100
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• 2014

Environmental problems and the shortage of natural resources are currently gathering more attention in Korea and international countries. With these problems, it is reported that most current domestic buildings are emitting approximately 138 million tons of greenhouse gas. According to a recent report from the investigation of Korean housing population, the total number of households is approximately 12.9 millions, and the apartments that were built more than 15 years ago amounted to 3.1 millions. This shows that the rates of old apartment housings are increasing. Therefore, it is necessary to consider the deteriorated facilities and environmental improvement. Also, the construction industry is benefited by improving these housings which may need either remodeling or reconstruction. Environmental friendly buildings are a rising consideration for remodeling and reconstruction projects; it helps to determine many business matters in construction. The main purpose of this research is to improve environmental condition in apartments with comparison analysis between remodeling and reconstruction alternatives. This research is focused on characteristics of remodeling and reconstruction and it sets up the same condition with each level in order to evaluate the value of environmental friendliness and analyze its definition. The result of this research provides a unique emitting rate at a novel framework and this will cause the reduction of $CO_2$. It is analyzed that the remodeling construction can reduce the great amount of $CO_2$. Therefore, it will be a good decision guideline in selecting the most eco-friendly alternative to improve environment for building construction. Although reconstruction is a popular alternative nowadays in Korea, this research can provide a reason why decision makers should put more emphasis on remodeling as an environment-friendly alternative.

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.4
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• pp.337-348
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• 2012

The Yellow Sea Ecoregion Conservation Project is a joint international project which is carried out under the purposes of conserving the habitats in the Yellow Sea Ecoregion and biodiversity from various threats that damage ecosystems, informing the importance and value of the Yellow Sea Ecoregion, and promoting the understanding and interests of Korea, China and Japan. Subsequent to the Yellow Sea Ecoregion Planning Programme which had been performed during the period from 2002 to 2006, the Yellow Sea Ecoregion Support Project has been performed over 7 years in total from 2007 to 2014. Panasonic is sponsoring the financing of the project, and the organizations in charge of the project by country are Korea Institute of Ocean Science & Technology for Korea and World Wide Fund for Nature branches for China and Japan. While the Yellow Sea Ecoregion Planning Programme was focused on the biological assessment and the selection of potential priority area by scientific review, the Yellow Sea Ecoregion Support Project is oriented toward practical activities targeting more diversified stakeholder. Especially, this project plans to support direct conservation activities in the region and participation and cooperation from local residents. The project plan is comprised of 3 phases. During the first period from 2008 to 2009, small grant projects were operated targeting 16 institutions of Korea and China, and for the second period from 2010 to 2012, one place each was selected as demonstration site for habitat conservation in Korea and China respectively and supported for three years to introduce the conservation method based on international standards such as the management of marine protected areas, ecosystem-based management and community-based management and simultaneously to develop habitat conservation activities suitable for national and regional characteristics. During the period from 2013 to 2014 which is the last phase, the project plans to distribute the performance of small grant projects and demonstration site activities through a series of forums among stakeholder. Through the activities described above, the recognition of general public on the conservation of the Yellow Sea Ecoregion was changed positively, and community-based management began to be reflected in the policies for the marine protected areas of central and local government.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.4
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• pp.315-322
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• 2011

The importance of aquafarming is increasing all over the world, however the coastal environment in the semi-closed inner bay has been aggravated due to the long term production and the high stocking density. For the sustainable aquafarming, there is a requirement for a eco-friendly fishery management by the estimation of ecological carrying capacity. The model development and application is still in the initial step, because it has to consider the whole ecosystem and all culture activities. As an alternative, there is a requirement for ecological indicator to assess the ecological performance. This study tried the estimation of ecological carrying capacity using ecological indicator. The production and the facility of the oyster farms was 4,935M/T, $49ind./m^3$ in Geoje-Hansan Bay(2008). Filtration pressure indicator was 0.203 which could provide a guidance on the present level of culture development. According to the environmental characteristics and the present oyster farms in Geoje-Hansan Bay, the newly assessed filtration pressure for the acceptable ecological carrying capacity was 0.102. Consequently, ecological carrying capacity in Geoje-Hansan Bay was 2,480M/T, $25ind./m^3$ and this represents the level of culture that can be introduced into Geoje-Hansan Bay without leading to significant changes to ecological process, species, populations or communities. Our study utilized the ecological indicator to estimate ecological carrying capacity of oyster farming for sustainable productivity and this could be the scientific basis for the eco-friendly fishery management.

• Korean Chemical Engineering Research
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• v.54 no.5
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• pp.621-629
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• 2016

Recently, the researches on quantitative structure activity relationship (QSAR) for describing toxicities or activities of chemicals based on chemical structural characteristics have been widely carried out in order to estimate the toxicity of chemicals in multiuse facilities. Because the toxicity of chemicals are explained by various kinds of molecular descriptors, an important step for QSAR model development is how to select significant molecular descriptors. This research proposes a statistical selection of significant molecular descriptors and a new QSAR model based on partial least square (PLS). The proposed QSAR model is applied to estimate the logarithm of partition coefficients (log P) of 130 polychlorinated biphenyls (PCBs) and lethal concentration ($LC_{50}$) of 14 PCBs, where the prediction accuracies of the proposed QSAR model are compared to a conventional QSAR model provided by OECD QSAR toolbox. For the selection of significant molecular descriptors that have high correlation with molecular descriptors and activity information of the chemicals of interest, correlation coefficient (r) and variable importance of projection (VIP) are applied and then PLS model of the selected molecular descriptors and activity information is used to predict toxicities and activity information of chemicals. In the prediction results of coefficient of regression ($R^2$) and prediction residual error sum of square (PRESS), the proposed QSAR model showed improved prediction performances of log P and $LC_{50}$ by 26% and 91% than the conventional QSAR model, respectively. The proposed QSAR method based on computational toxicology can improve the prediction performance of the toxicities and the activity information of chemicals, which can contribute to the health and environmental risk assessment of toxic chemicals.

• Management & Information Systems Review
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• v.34 no.5
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• pp.191-212
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• 2015

Unlike the existing researches related to salespersons, this study intends to place the focus on salespersons' psychological characteristic as an element affecting their selling behavior. This is because employees' psychological characteristic is very likely to affect their devotion and commitment to relationship with customers and long-term production by a company. In particular, salespersons are likely to get a feeling of fatigue or loss, or make a cynical or cold response to customers because of frequent interaction with them, and to show emotional indifference in an attempt to keep their distance from customers. But the likelihood can vary depending on salespersons' own psychological characteristic; in particular, the occurrence of these phenomena is very likely to vary significantly depending on relationship belief in interpersonal relations. In the field of psychology, under way are researches related to personal psychological characteristics to improve the quality of interpersonal relations and to maximize personal performance and enhance situational adaptability during this process; it is a personal relationship belief that is recently mentioned as such a psychological characteristic. For salespersons having frequent interaction with customers, particularly, relationship belief can be a very important element in forming relations with customers. So this study aims at determining how salespersons' relationship belief affects negative emotion regulation strategies and prosocial behavior to customer. As a result, salespersons' relationship belief was found to have effects on their negative emotion regulation strategies and prosocial behavior to customer. Negative emotion regulation strategies was found to have effects on prosocial behavior. Salespersons with intimate relationship belief try to use active regulation, support-seeking regulation and salespersons with controlling relationship belief try to use avoidant/distractive regulation. Intimate relationship belief was found to have more prosocial behavior, controlling relationship belief was found to have less prosocial behavior to customer. salespersons' negative emotion regulation strategies was found to have effects on their prosocial behavior to customer. Active, support-seeking influence prosocial behavior to customer positively, avoidant/distractive regulation influence prosocial behavior to customer negatively.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.17-23
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• 2020

Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.661-676
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• 2017

This study suggests a new method not only to produce the 1 km-resolution seasonal prediction but also to improve the seasonal prediction skill of temperature over South Korea. This method consists of four stages of experiments. The first stage, EXP1, is a low-resolution seasonal prediction of temperature obtained from Pusan National University Coupled General Circulation Model, and EXP2 is to produce 1 km-resolution seasonal prediction of temperature over South Korea by applying statistical downscaling to the results of EXP1. EXP3 is a seasonal prediction which considers the effect of temperature changes according to the altitude on the result of EXP2. Here, we use altitude information from ASTER GDEM, satellite observation. EXP4 is a bias corrected seasonal prediction using genetic algorithm in EXP3. EXP1 and EXP2 show poorer prediction skill than other experiments because the topographical characteristic of South Korea is not considered at all. Especially, the prediction skills of two experiments are lower at the high altitude observation site. On the other hand, EXP3 and EXP4 applying the high resolution elevation data based on remote sensing have higher prediction skill than other experiments by effectively reflecting the topographical characteristics such as temperature decrease as altitude increases. In addition, EXP4 reduced the systematic bias of seasonal prediction using genetic algorithm shows the superior performance for temporal variability such as temporal correlation, normalized standard deviation, hit rate and false alarm rate. It means that the method proposed in this study can produces high-resolution and high-quality seasonal prediction effectively.

• Korean Journal of Soil Science and Fertilizer
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• v.10 no.1
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• pp.55-60
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• 1977

In order to study the availability of soil P and applied P to rice plant under water-logged system, a pot experiment with five soils having different levels of available P (24, 64, 100, 144 and 231 ppm) under four levels of applied P (0, 30, 60 and 90 ppm) was conducted. The availability of P was measured in terms of plant performance and the behaviors of P in soils were studied through the fractionation of various forms of P and by measuring the adsorption and desorption characteristics. The results are summarized us following. 1. The rice plant responded to applied P in the soils containing less than 144 ppm of available P as measured by Lancaster's method in terms of number of tillers in early growth stages. However, when the response of rice plant to applied P was evaluated in terms of grain yield there was no response even in the soil containing 24 ppm of available P. 2. Applied P was fixed as Al-P at the early stages and converted into Fe-P at later stages. 3. The P adsorption maxima of soils measured by Langmuir's isotherm ranged from 70 to 100mg/100g. No relationships between the level of available P and P adsorption maxima were observed. 4. There was a trend that the higher the level of available P, the higher the release of water soluble p. 5. The reduction of soil increased the level of available P by the factor of 1.8 times of air dried soils.

• Economic and Environmental Geology
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• v.49 no.6
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• pp.459-467
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• 2016

Due to the limited areal space for installation, borehole heat exchangers (BHEs) at depths deeper than 300 m are considered for geothermal heating and cooling in the urban area. The deep vertical closed-loop BHEs are unconventional due to the depth and the range of the typical installation depth is between 100 and 200 m in Korea. The BHE in the study consists of 50A (outer diameter 50 mm, SDR 11) PE U-tube pipe in a 150 mm diameter borehole with the depth of 300 m. In order to compensate the buoyancy caused by the low density of PE pipe ($0.94{\sim}0.96g/cm^3$) in the borehole filled with ground water, 10 weight band sets (4.6 kg/set) were attached to the bottom of U-tube. A thermal response test (TRT) and fundamental basic surveys on the thermophysical characteristics of the ground were conducted. Ground temperature measures around $15^{\circ}C$ from the surface to 100 m, and the geothermal gradient represents $1.9^{\circ}C/100m$ below 100 m. The TRT was conducted for 48 hours with 17.5 kW heat injection, 28.65 l/min at a circulation fluid flow rate indicates an average temperature difference $8.9^{\circ}C$ between inlet and outlet circulation fluid. The estimated thermophysical parameters are 3.0 W/mk of ground thermal conductivity and 0.104 mk/W of borehole thermal resistance. In the stepwise evaluation of TRT, the ground thermal conductivity was calculated at the standard deviation of 0.16 after the initial 13 hours. The sensitivity analysis on the borehole thermal resistance was also conducted with respect to the PE pipe diameter and the thermal conductivity of backfill material. The borehole thermal resistivity slightly decreased with the increase of the two parameters.