• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.3
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• pp.347-354
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• 2014

The color appearance of a yarn-dyed woven fabric depends on the color of the yarn as well as on the weave structure. Predicting the final color appearance or formulating the recipe is a difficult task, considering the interference of colored yarns and structure variations. In a modern fabric design process, the intended color appearance is attained through a digital color methodology based on numerous color data and color mixing recipes (i.e., color prediction models, accumulated in CAD systems). For successful color reproduction, accurate color prediction models should be devised and equipped for the systems. In this study, the final colors of yarn-dyed woven fabrics were predicted using six geometric-color mixing models (i.e., simple K/S model, log K/S model, D-G model, S-N model, modified S-N model, and W-O model). The color differences between the measured and the predicted colors were calculated to evaluate the accuracy of various color models used for different weave structures. The log K/S model, D-G model, and W-O model were found to be more accurate in color prediction of the woven fabrics used. Among these three models, the W-O model was found to be the best one as it gave the least color difference between the measured and the predicted colors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.364-380
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• 2016

The most popular approach in object classification is based on the bag of visual-words model, which has several fundamental problems that restricting the performance of this method, such as low time efficiency, the synonym and polysemy of visual words, and the lack of spatial information between visual words. In view of this, an object classification based on weakly supervised E2LSH and saliency map weighting is proposed. Firstly, E2LSH (Exact Euclidean Locality Sensitive Hashing) is employed to generate a group of weakly randomized visual dictionary by clustering SIFT features of the training dataset, and the selecting process of hash functions is effectively supervised inspired by the random forest ideas to reduce the randomcity of E2LSH. Secondly, graph-based visual saliency (GBVS) algorithm is applied to detect the saliency map of different images and weight the visual words according to the saliency prior. Finally, saliency map weighted visual language model is carried out to accomplish object classification. Experimental results datasets of Pascal 2007 and Caltech-256 indicate that the distinguishability of objects is effectively improved and our method is superior to the state-of-the-art object classification methods.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.446-456
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• 2007

Increased access to broadband networks has led to a fast-growing demand for voice and video over IP(VVoIP) applications such as Internet telephony(VoIP), videoconferencing, and IP television(IPTV). For pro-active troubleshooting of VVoIP performance bottlenecks that manifest to end-users as performance impairments such as video frame freezing and voice dropouts, network operators cannot rely on actual end-users to report their subjective quality of experience(QoE). Hence, automated and objective techniques that provide real-time or online VVoIP QoE estimates are vital. Objective techniques developed to-date estimate VVoIP QoE by performing frame-to-frame peak-signal-to-noise ratio(PSNR) comparisons of the original video sequence and the reconstructed video sequence obtained from the sender-side and receiver-side, respectively. Since processing such video sequences is time consuming and computationally intensive, existing objective techniques cannot provide online VVoIP QoE. In this paper, we present a novel framework that can provide online estimates of VVoIP QoE on network paths without end-user involvement and without requiring any video sequences. The framework features the "GAP-model", which is an offline model of QoE expressed as a function of measurable network factors such as bandwidth, delay, jitter, and loss. Using the GAP-model, our online framework can produce VVoIP QoE estimates in terms of "Good", "Acceptable", or "Poor"(GAP) grades of perceptual quality solely from the online measured network conditions.

• IMMUNE NETWORK
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• v.4 no.1
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• pp.44-52
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• 2004

Background: As a potent antigen presenting cell and a powerful inducer of antigen specific immunity, dendritic cells (DCs) are being considered as a promising anti-tumor therapeutic module. The expected therapeutic effect of DCs in renal cell carcinoma was tested in the mouse model. Established late-stage tumor therapeutic (E-T) and minimal residual disease (MRD) model was considered in the in vivo experiments. Methods: Syngeneic renal cell carcinoma cells (RENCA) were inoculated either subcutaneously (E-T) or intravenously (MRD) into the Balb/c mouse. Tumor cell lysate pulsed-DCs were injected twice in two weeks. Intraperitoneal DC injection was started 3 week (E-T model) or one day (MRD model) after tumor cell inoculation. Two weeks after the final DC injection, the tumor growth and the systemic immunity were observed. Therapeutic DCs were cultured from the bone marrow myeloid lineage cells with GM-CSF and IL-4 for 7 days and pulsed with RENCA cell lysate for 18 hrs. Results: Compared to the saline treated group, tumor growth (E-T model) or formation (MRD model) was suppressed in pulsed-DC treated group. RENCA specific lymphocyte proliferation was observed in the RENCA tumor-bearing mice treated with pulsed-DCs. Primary cytotoxic T cell activity against RENCA cells was increased in pulsed-DC treated group. Conclusion: The data suggest the possible anti-tumor effect of cultured DCs in established or minimal residual disease/metastasis state of renal cell carcinoma. Systemic tumor specific immunity including cytotoxic T cell activity was modulated also in pulsed-DC treated group.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.51-61
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• 2023

Travel demand estimation of E-Scooter is the start point of solving the regional demand-supply imbalance problem and plays pivotal role in a linked transportation system such as Mobility-as-a-Service (a.k.a. MaaS). Most focuses on developing trip generation model of shared E-Scooter but it is no study on selection of an appropriate zone scale when it comes to estimating travel demand of E-Scooter. This paper aimed for selecting an optimal TAZ scale for developing trip distribution model for shared E-Scooter. The TAZ scale candidates were selected in 250m, 500m, 750m, 1,000m square grid. The shared E-Scooter usage historical data were utilized for calculating trip distance and time, and then applying to developing gravity model. Mean Squared Error (MSE) is applied for the verification step to select the best suitable gravity model by TAZ scale. As a result, 250m of TAZ scale is the best for describing practical trip distribution of shared E-Scooter among the candidates.

• Journal of Environmental Health Sciences
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• v.46 no.2
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• pp.136-149
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• 2020

Objectives: The purpose of this study was to perform an aggregate human risk assessment for benzene in an industrial complex using the CalTOX model and to improve the reliability and predictability of the model by analyzing the uncertainty and sensitivity of the predicted assessment results. Methods: The CalTOX^TM 4.0 beta model was used to evaluate a selected region, and @Risk 7.6 software was used to analyze uncertainty and sensitivity. Results: As a result of performing the aggregate risk assessment on the assumption that 6.45E+04 g/d of benzene would be emitted into the atmosphere over two decades, 3% of the daily source term to air remained in the selected region, and 97% (6.26E+04 g/d) moved out of the region. As for exposure by breathing, the predicted LADD_inhalation was 2.14E-04 mg/kg-d, and that was assessed as making a 99.99% contribution to the LADD_total. Regarding human Risk_cancer assessment, the predicted human cancer risk was 5.19E-06 (95% CI; 4.07E-06-6.81E-06) (in the 95th percentile corresponding to the highest exposure level, a confidence interval of 90%). As a result of analyzing sensitivity, 'source term to air' was identified as the most influential variable, followed by 'exposure time, active indoors (h/day)', and 'exposure duration (years)'. Conclusions: As for the results of the human cancer risk assessment for the selected region, the predicted human cancer risk was 5.19E-06 (95% CI; 4.07E-06-6.81E-06) (in the 95th percentile, corresponding to the highest exposure level, a confidence interval of 90%). As a result of analyzing sensitivity, 'source term to air' was found to be most influential.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.187-197
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• 2004

This paper presents the effects of cylinder shell elasticity on effective bulk modulus of oil $K_e$ in automotive hydraulic dampers. A theoretical model of cylinder shell bulk modulus $K_c$ based on the elasticity theory of thick-walled cylinder incorporating not only radial but longitudinal deformation is proposed. In a cylinder, values of $K_c$ by the new model and traditional models are computed and the discrepancies among them are discussed. In a twin-tube type automotive damper, the variation of $K_e$ under different pressure values in chambers of the damper cylinder, based on different theoretical models for $K_c$ is computed. Through these computations, it is shown that remarkable discrepancies in computed values of $K_e$ might occur according to the $K_e$ models in connection with $K_c$ models.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1059-1062
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• 1998

This paper which can simulate FRIENDS(Flexible Reliable Intelligent Electrical eNergy Delivery System) model of distribution electrical system presents a new algorithm. In the operation of FRIENDS model, dispersed energy storage(DES) systems have an important role. We can use the active and reactive power of DES to control customer's voltage. In this, the former means load levelling operation and the later means voltage control operation of DES. We focus our research on load levelling operation of DES. We develope an algorithm to get an optimal capacity and operation schedule of DES and then apply it to the FRIENDS model. The results show the effectiveness of the proposed method.

• Ocean and Polar Research
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• v.37 no.2
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• pp.161-177
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• 2015

This study analyzes the stock assessment of yellow croaker caught mainly by the Korean stow net and gill net fisheries focusing on single species and multiple fisheries. This study standardizes fishing efforts for the two fisheries using the general linear model and uses a surplus production model based on the exponential growth model. The Clarke Yoshimoto Pooley model estimates a maximum sustainable yield(MSY), an allowable biological catch(ABC), fishing efforts for MSY($E_{MSY}$) and for ABC($E_{ABC}$). The bio-economic model is used to estimate the maximum economic yield(MEY) and fishing efforts for MEY($E_{MSY}$). Also, the study employs an economic analysis to estimate the economic interaction between stow net and gill net fisheries. The economic analysis shows the profit accruing to the two fisheries from estimated ABC. Finally, the study compares TACs based on single species and single fishery to TAC based on single species and multiple fisheries. The study proposes that the TAC assessment is necessary for single species and multiple fisheries in order to preserve resources.

• Asia pacific journal of information systems
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• v.25 no.1
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• pp.1-24
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• 2015

Electronic Commerce or e-commerce implies such an industry where goods and services are bought and sold over electronic systems. This is rapidly growing sectors in Bangladesh which influence local and international trade. Government of Bangladesh has also initiated quite a good number of measures for the expansion of e-commerce. However, low adoption of e-commerce is not uncommon in Bangladesh. The objective of this study is to determine the factors that influence the adoption of e-commerce services in Bangladesh. Extended version of Technology Acceptance Model (TAM) is envisaged as the theoretical backbone of the study. Reliability analysis using Cronbach's Alpha test indicates that the research model is internally consistent. The study reveals that 35 percent of respondents became interested in e-commerce services from advertisement on Internet or other electronic media. The findings of the study shows that all the four constructs, namely-Computer Self Efficacy, Perceived Credibility, Perceived Usefulness and Perceived Ease of Use have significant effect on the adoption of e-commerce. The study has also demonstrated that Perceived Usefulness appeared as the most important factor in describing user's adoption of e-commerce.