• Journal of Distribution Science
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• v.10 no.11
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• pp.89-99
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• 2012

Purpose - Mobile devices, especially mobile terminals capable of telecommunication and wireless connectivity, are leading the advancements in consumer electronics. Digital convergence drives the functions of various devices, such as cellular phones, MP3 players, personal digital assistants, and gaming, into a single device. This trend would continue and applications such as digital audio and video streaming (including personalized content delivery mechanisms) would soon be on a handheld device. As customers want mobile convergence devices, manufacturers are driving new initiatives in the emerging mobile device market. Given the roles played by device design and service content in user satisfaction of a mobile convergence device, this study focuses on identifying and measuring the constructs for the process by which user satisfaction is achieved. This study synthesizes the expectation-disconfirmation paradigm with empirical theories in user satisfaction. Device and service levels are separated, and nine key constructs for user satisfaction of mobile convergence devices are proposed. Insight into this process could help web-based businesses to improve user satisfaction, thus enhancing the effectiveness of e-commerce for sellers and buyers. Research design, data, methodology - This study draws on three users of mobile convergence devices as examples. To test there search model and hypotheses, survey questionnaires were sent to 607 mobile device users. Mobile device users were initially identified from several members, and subjects were randomly drawn. Data from 577 survey responses were finally analyzed. The unit of measurement and analysis in this research study is at a personal level. Results - The measurements for the constructs were developed and tested in a two-phase study. In the first phase, the device and service dimensions were identified, and instruments for measuring them were developed and tested. In the second phase, using the salient dimensions of the device and service as the formulating first-order factors, instruments were developed and empirically tested to measure satisfaction of the device and service. In measuring satisfaction of mobile convergence devices, the critical tasks are to identify the key constructs of such user satisfaction and to develop validated instruments to measure them. Hence, the results of this study have immediate implications for businesses and for research in user satisfaction of mobile convergence devices. Conclusions - This study provides reliable instruments for operationalizing key constructs in the analysis of user satisfaction of mobile convergence devices within the expectation-disconfirmation paradigm. Hence, convergence device makers will be able to examine whether their websites meet their customers' expectations by examining the device aspect of the mobile convergence device customers, and the service aspect expectations and disconfirmation. Moreover, the introduction of expectation and disconfirmation constructs brings the marketing aspect of convergence devices into focus for such retailers, an aspect crucial to the effective design of websites for online businesses. In addition,this study provides the metrics required to initiate future studies on user satisfaction of mobile convergence devices.

• Ecology and Resilient Infrastructure
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• v.3 no.4
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• pp.231-237
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• 2016

The purpose of this study is to analyze phosphate adsorption characteristic of the filter media applied in water purification technology. And it is also to observe the removal efficiency of the technology that was developed by combining the purification abilities of filter media and the vegetation mat. The filter media, Adphos, is the subject of this study. The result of adsorption test shows that $PO_4{^{3-}-P}$ adsorption characteristics of Adphos is determined by the Langmuir isotherm model fitting and the $q_m$ (maximum adsorption amount) value is calculated as 1.162 mg/g. To verify the removal efficiency of the purification technology, a lab-scale reactor, including a 400 mm depth of filter bed filled by Adphos, was manufactured. Yellow flag Iris (Iris pseudacours L.) was planted on the vegetation bed and the coir-roll was used to fix the root of vegetation. The reactor ran 8 hours per day over 71 days, and the results of filtration experiment show that average removal efficiency of SS, T-N and T-P were calculated as 94%, 41% and 64% respectively. With these results, it was proved that the purification technology is highly effective. And for the long-time use, a maintenance guide is also required.

• Asia pacific journal of information systems
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• v.22 no.1
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• pp.53-77
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• 2012

Financial firms, especially large scaled firms such as KB bank, NH bank, Samsung Card, Hana SK Card, Hyundai Capital, Shinhan Card, etc. should be securely dealing with the personal financial information. Indeed, people have tended to believe that those big financial companies are relatively safer in terms of information security than typical small and medium sized firms in other industries. However, the recent incidents of personal information privacy invasion showed that this may not be true. Financial firms have increased the investment of information protection and security, and they are trying to prevent the information privacy invasion accidents by doing all the necessary efforts. This paper studies how effectively a financial firm will be able to avoid personal financial information privacy invasion that may be deliberately caused by internal staffs. Although there are several literatures relating to information security, to our knowledge, this is the first study to focus on the behavior of internal staffs. The big financial firms are doing variety of information security activities to protect personal information. This study is to confirm what types of such activities actually work well. The primary research model of this paper is based on Theory of Planned Behavior (TPB) that describes the rational choice of human behavior. Also, a variety of activities to protect the personal information of financial firms, especially credit card companies with the most customer information, were modeled by the four-step process Security Action Cycle (SAC) that Straub and Welke (1998) claimed. Through this proposed conceptual research model, we study whether information security activities of each step could suppress personal information abuse. Also, by measuring the morality of internal staffs, we checked whether the act of information privacy invasion caused by internal staff is in fact a serious criminal behavior or just a kind of unethical behavior. In addition, we also checked whether there was the cognition difference of the moral level between internal staffs and the customers. Research subjects were customer call center operators in one of the big credit card company. We have used multiple regression analysis. Our results showed that the punishment of the remedy activities, among the firm's information security activities, had the most obvious effects of preventing the information abuse (or privacy invasion) by internal staff. Somewhat effective tools were the prevention activities that limited the physical accessibility of non-authorities to the system of customers' personal information database. Some examples of the prevention activities are to make the procedure of access rights complex and to enhance security instrument. We also found that 'the unnecessary information searches out of work' as the behavior of information abuse occurred frequently by internal staffs. They perceived these behaviors somewhat minor criminal or just unethical action rather than a serious criminal behavior. Also, there existed the big cognition difference of the moral level between internal staffs and the public (customers). Based on the findings of our research, we should expect that this paper help practically to prevent privacy invasion and to protect personal information properly by raising the effectiveness of information security activities of finance firms. Also, we expect that our suggestions can be utilized to effectively improve personnel management and to cope with internal security threats in the overall information security management system.

• Journal of Biomedical Engineering Research
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• v.20 no.2
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• pp.173-182
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• 1999

Contrast-enhanced CT has an important role in assessing liver lesions, the optimal protocol to get most effective result is not clear. The mein goal when deciding injention protocol is to optimize lesion detectability with rapid scanning when lesion to liver contrast is maximum. For this purpose, we developed a physiological model of the contrast medium enhancement based on the compartment modeling and pharmacokinetics. Blood supply to liver is achieved in two paths. This dual supply characteristic distinguishes the CT enhancement of liver from that of the other organs. The first path is by hepatic artery and to second, by portal vein. However, it is assumed that only gepatic artery can supply blood to hepatocellular carcinoma(HCC) compartment, thus, the difference of contrast enhancement is resulted between normal liver tissue and hepatic tumor. By solving differential equations for each compartment simultaneously using the computer program Matlab, CT contrast-enhancement curves were simulated. The simulated enhancement curves for aortic, hepatic, portal vein, and HCC compartments were compared with the mean enhancement curves from 24 patients exposed to the same protocols as the simulation. These enhancement curves showed a good agreement. Furthermore, we simulated lesion-to-liver curves for various injection protocols, and the effects were analyzed. The variables to be considered in the injection protocol were injection rate, dose, and concentration of contrast material. These data may help to optimize scanning protocols for better diagnosis.

• Food Science of Animal Resources
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• v.34 no.6
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• pp.736-741
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• 2014

This study developed probabilistic models to determine the initiation time of growth of Pseudomonas spp. in combinations with $NaNO_2$ and NaCl concentrations during storage at different temperatures. The combination of 8 NaCl concentrations (0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, and 1.75%) and 9 $NaNO_2$ concentrations (0, 15, 30, 45, 60, 75, 90, 105, and 120 ppm) were prepared in a nutrient broth. The medium was placed in the wells of 96-well microtiter plates, followed by inoculation of a five-strain mixture of Pseudomonas in each well. All microtiter plates were incubated at 4, 7, 10, 12, and $15^{\circ}C$ for 528, 504, 504, 360 and 144 h, respectively. Growth (growth initiation; GI) or no growth was then determined by turbidity every 24 h. These growth response data were analyzed by a logistic regression to produce growth/no growth interface of Pseudomonas spp. and to calculate GI time. NaCl and $NaNO_2$ were significantly effective (p<0.05) on inhibiting Pseudomonas spp. growth when stored at $4-12^{\circ}C$. The developed model showed that at lower NaCl concentration, higher $NaNO_2$ level was required to inhibit Pseudomonas growth at $4-12^{\circ}C$. However, at $15^{\circ}C$, there was no significant effect of NaCl and $NaNO_2$. The model overestimated GI times by $58.2{\pm}17.5$ to $79.4{\pm}11%$. These results indicate that the probabilistic models developed in this study should be useful in calculating the GI times of Pseudomonas spp. in combination with NaCl and $NaNO_2$ concentrations, considering the over-prediction percentage.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.11
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• pp.915-924
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• 2014

In an aero gas-turbine engine, a surface air-oil heat exchanger (SAOHE) is used to cool the oil system for the gearboxes and electric generators. The SAOHE is installed inside the fan casing of the engine in order to dissipate the heat from the oil system into the bypass duct stream. The purpose of this study was to develop an effective numerical method for designing an SAOHE for an aero gas-turbine engine. A two-dimensional model using a porous medium was developed to evaluate the aero-thermal performance of the fins of the heat exchanger, and a one-dimensional flow and thermal network program was developed to save time and cost in the evaluation of the heat exchanger performance. Using this network program, the pressure drop and heat transfer performance of the heat exchanger were predicted, and the results were compared with two-dimensional computational fluid dynamics results and experiment data for validation.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• Journal of Korea Technology Innovation Society
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• v.21 no.1
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• pp.420-453
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• 2018

In the growth of the government's investment in national R&D project and the abuse of research expense, an effective control and management mechanism is strongly demanded. However, an excessive regulation might hinder the R&D performance, which also endangers the underlying objective of R&D policy. Especially, an excessive regulation on the R&D expenditure may damage the SMEs (Small and Medium sized Enterprises) where securing an adequate level of R&D funding is vital. This study investigates the R&D funding and R&D performance of SMEs participating in the national R&D project by using fixed effect panel model. As a result, this paper reveals the effectiveness of 'Government R&D subsidy'. However, that of 'private R&D fund' is not supported strongly. Also, this paper empirically demonstrates the efficiency of both 'Government R&D subsidy' and 'Private R&D fund' as the R&D costs are spent discretionarily (as the degree of 'Indirect Cost Ratio' increases). Especially, the effectiveness of 'Private R&D fund' can be moderated by 'Indirect Cost Ratio'. On the basis of the conclusions, this paper draws an implication that can increase R&D performance of SMEs through the interactions of manifold administrative values (i.e. effectiveness, efficiency and responsibility).

• The Journal of Pediatrics of Korean Medicine
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• v.32 no.3
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• pp.1-15
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• 2018

Objectives Alismatis Rhizoma has been known to suppress inflammation and allergic reaction. However, the cellular target of Alismatis Rhizoma and its mechanism of action remain unclear. This study was designed to examine the effect of Alismatis Rhizoma extract (ALC) on the RBL-2H3 mast cells in vitro and on the OVA/alum sensitized mice ex vivo. Methods In the study, RBL-2H3 mast cells were cultured in minimal essential medium (MEM) for 24 hours, and treated separately with cyclosporin A and varying doses of ALC, and then stimulated with Phorbol 12-myristate 13-acetate (PMA) (50 ng/ml) and Ionomycin ($0.5{\mu}M$). The levels of IL-13, IL-4 were measured by ELISA analysis. The mRNA levels of IL-4, IL-5, IL-6, IL-13, GM-CSF, $TNF-{\alpha}$ were analyzed with Real-time PCR. Also, manifestations of MAPKs transcription factors and $NF-{\kappa}B$ p65 translocation were analyzed by western blotting in vitro. Subsequently, for ex vivo experiment, we induced allergic inflammation on Balb/c mice by OVA/alum and administered ALC orally. And we measured serum OVA-specific IgE level and IL-4, IL-13 in the splenocyte culture supernatant by ELISA analysis. Results ALC was shown to suppress mRNA expression of IL-4, IL-5, IL-6, IL-13, GM-CSF, $TNF-{\alpha}$, and to inhibit the IL-13, IL-4 production. Also ALC reduced an activation of mast cells specific signal MAPKs transcription factors and $NF-{\kappa}B$ p65 from the western blot analysis in in vitro experiment. In ex vivo, ALC oral adminstration decreased the level of OVA-specific IgE in serum, and IL-4, IL-13 in the splenocyte culture supernatant. Conclusions ALC is shown to reduce inflammation and allergic response by suppressing Th2 cytokines through the regulation of transcription factors MAPKs and $NF-{\kappa}B$ p65 in mast cells. Administration of ALC suppressed OVA-specific IgE in ovalbumin allergy model through the inhibition of Th2 cytokine. In conclusion, ALC can be considered as an effective treatment for allergic diseases such as atopic dermatitis.

• Journal of Venture Innovation
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• v.1 no.1
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• pp.67-82
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• 2018

Lately, recognition of Corporate Social Responsibility (CSR) has been changing. CSR turned out to be a powerful tool which a company incorporates to improve its image. Nowadays, it is no longer an option, but a shared sense which is a source of corporate growth and competitiveness. CSR has changed with times and the economic environment, especially as the global value chain (GVC) came to be more vital, it became accepted as an effective means of growth strategy for small and medium exporters. For SMEs exporters, participating in GVC requires that they meet international standards for CSR demanded by global enterprises. Reflecting this trend, exporters should strive to achieve both goals of social responsibility fulfillment and efficient growth through CSR activities. As one of the key measures for a sustainable growth of an organization, the following are the policy implications. First, it is necessary to establish a national organization dedicated to CSR for small businesses. The central government should establish an organization which is exclusively responsible for CSR of SMEs and oversee the task of CSR of small businesses. Second, the development and verification of the CSV evaluation model should be promoted. The international trend of CSR should be promptly spread out to individual firms and supported to maximize economic effects through consultancy. Third, it should be linked to global advancement. CSR reports by small and mid-size businesses will have to be written to ensure that they have a real effect on the global value chain.