• Wind and Structures
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• v.30 no.4
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• pp.433-450
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• 2020

The strong turbulence characteristic of typhoon not only will significantly change flow field characteristics surrounding the large-scale wind turbine and aerodynamic force distribution on surface, but also may cause morphological evolution of coast dune and thereby form sand storms. A 5MW horizontal-axis wind turbine in a wind power plant of southeastern coastal areas in China was chosen to investigate the distribution law of additional loads caused by wind-sand coupling movement of coast dune at landing of strong typhoons. Firstly, a mesoscale Weather Research and Forecasting (WRF) mode was introduced in for high spatial resolution simulation of typhoon "Megi". Wind speed profile on the boundary layer of typhoon was gained through fitting based on nonlinear least squares and then it was integrated into the user-defined function (UDF) as an entry condition of small-scaled CFD numerical simulation. On this basis, a synchronous iterative modeling of wind field and sand particle combination was carried out by using a continuous phase and discrete phase. Influencing laws of typhoon and normal wind on moving characteristics of sand particles, equivalent pressure distribution mode of structural surface and characteristics of lift resistance coefficient were compared. Results demonstrated that: Compared with normal wind, mesoscale typhoon intensifies the 3D aerodynamic distribution mode on structural surface of wind turbine significantly. Different from wind loads, sand loads mainly impact on 30° ranges at two sides of the lower windward region on the tower. The ratio between sand loads and wind load reaches 3.937% and the maximum sand pressure coefficient is 0.09. The coupling impact effect of strong typhoon and large sand particles is more significant, in which the resistance coefficient of tower is increased by 9.80% to the maximum extent. The maximum resistance coefficient in typhoon field is 13.79% higher than that in the normal wind field.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.89-98
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• 2016

In this paper, we proposed an automated areal feature matching method based on geometric similarity without user intervention and is applied into areal features of many-to-many relation, for confusion of spatial data-sets of different scale and updating cycle. Firstly, areal feature(node) that a value of inclusion function is more than 0.4 was connected as an edge in adjacency matrix and candidate corresponding areal features included many-to-many relation was identified by multiplication of adjacency matrix. For geometrical matching, these multiple candidates corresponding areal features were transformed into an aggregated polygon as a convex hull generated by a curve-fitting algorithm. Secondly, we defined matching criteria to measure geometrical quality, and these criteria were changed into normalized values, similarity, by similarity function. Next, shape similarity is defined as a weighted linear combination of these similarities and weights which are calculated by Criteria Importance Through Intercriteria Correlation(CRITIC) method. Finally, in training data, we identified Equal Error Rate(EER) which is trade-off value in a plot of precision versus recall for all threshold values(PR curve) as a threshold and decided if these candidate pairs are corresponding pairs or not. To the result of applying the proposed method in a digital topographic map and a base map of address system(KAIS), we confirmed that some many-to-many areal features were mis-detected in visual evaluation and precision, recall and F-Measure was highly 0.951, 0.906, 0.928, respectively in statistical evaluation. These means that accuracy of the automated matching between different spatial data-sets by the proposed method is highly. However, we should do a research on an inclusion function and a detail matching criterion to exactly quantify many-to-many areal features in future.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4274-4281
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• 2023

Blanket is of vital importance for engineering application of the fusion reactor. Nuclear heat deposition in materials is the main heat source in blanket structure. In this paper, the three-dimensional method for thermal-hydraulics/neutronics coupling analysis is developed and applied for the full-scale module of the helium-cooled ceramic breeder tritium breeding blanket (HCCB TBB) designed for China Fusion Engineering Test Reactor (CFETR). The explicit coupling scheme is used to support data transfer for coupling analysis based on cell-to-cell mapping method. The coupling algorithm is realized by the user-defined function compiled in Fluent. The three-dimensional model is established, and then the coupling analysis is performed using the paralleled Coupling Analysis of Thermal-hydraulics and Neutronics Interface Code (CATNIC). The results reveal the relatively small influence of the coupling analysis compared to the traditional method using the radial fitting function of internal heat source. However, the coupling analysis method is quite important considering the nonuniform distribution of the neutron wall loading (NWL) along the poloidal direction. Finally, the structure optimization of the blanket is carried out using the coupling method to satisfy the thermal requirement of all materials. The nonlinear effect between thermal-hydraulics and neutronics is found during the blanket structure optimization, and the tritium production performance is slightly reduced after optimization. Such an adverse effect should be thoroughly evaluated in the future work.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.143-163
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• 2016

The demographics of Internet users are the most basic and important sources for target marketing or personalized advertisements on the digital marketing channels which include email, mobile, and social media. However, it gradually has become difficult to collect the demographics of Internet users because their activities are anonymous in many cases. Although the marketing department is able to get the demographics using online or offline surveys, these approaches are very expensive, long processes, and likely to include false statements. Clickstream data is the recording an Internet user leaves behind while visiting websites. As the user clicks anywhere in the webpage, the activity is logged in semi-structured website log files. Such data allows us to see what pages users visited, how long they stayed there, how often they visited, when they usually visited, which site they prefer, what keywords they used to find the site, whether they purchased any, and so forth. For such a reason, some researchers tried to guess the demographics of Internet users by using their clickstream data. They derived various independent variables likely to be correlated to the demographics. The variables include search keyword, frequency and intensity for time, day and month, variety of websites visited, text information for web pages visited, etc. The demographic attributes to predict are also diverse according to the paper, and cover gender, age, job, location, income, education, marital status, presence of children. A variety of data mining methods, such as LSA, SVM, decision tree, neural network, logistic regression, and k-nearest neighbors, were used for prediction model building. However, this research has not yet identified which data mining method is appropriate to predict each demographic variable. Moreover, it is required to review independent variables studied so far and combine them as needed, and evaluate them for building the best prediction model. The objective of this study is to choose clickstream attributes mostly likely to be correlated to the demographics from the results of previous research, and then to identify which data mining method is fitting to predict each demographic attribute. Among the demographic attributes, this paper focus on predicting gender, age, marital status, residence, and job. And from the results of previous research, 64 clickstream attributes are applied to predict the demographic attributes. The overall process of predictive model building is compose of 4 steps. In the first step, we create user profiles which include 64 clickstream attributes and 5 demographic attributes. The second step performs the dimension reduction of clickstream variables to solve the curse of dimensionality and overfitting problem. We utilize three approaches which are based on decision tree, PCA, and cluster analysis. We build alternative predictive models for each demographic variable in the third step. SVM, neural network, and logistic regression are used for modeling. The last step evaluates the alternative models in view of model accuracy and selects the best model. For the experiments, we used clickstream data which represents 5 demographics and 16,962,705 online activities for 5,000 Internet users. IBM SPSS Modeler 17.0 was used for our prediction process, and the 5-fold cross validation was conducted to enhance the reliability of our experiments. As the experimental results, we can verify that there are a specific data mining method well-suited for each demographic variable. For example, age prediction is best performed when using the decision tree based dimension reduction and neural network whereas the prediction of gender and marital status is the most accurate by applying SVM without dimension reduction. We conclude that the online behaviors of the Internet users, captured from the clickstream data analysis, could be well used to predict their demographics, thereby being utilized to the digital marketing.

• Progress in Medical Physics
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• v.17 no.4
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• pp.212-223
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• 2006

Positional accuracy of the on-board imager (OBI) isocenter with gantry rotation was presented in this paper. Three different type of automatic evaluation methods of discrepancies between therapeutic and OBI isocenter using digital image processing techniques as well as a procedure stated in the customer acceptance procedure (CAP) were applied to check OBI isocenter migration trends. Two kinds of kV x-ray image set obtained at OBI source angle of $0^{\circ},\;90^{\circ},\;180^{\circ},\;270^{\circ}$ and every $10^{\circ}$ and raw projection data for cone-beam CT reconstruction were used for each evaluation method. Efficiencies of the methods were also estimated. If a user needs to obtain an isocenter variation map with full gantry rotation, a method taking OBI image for every $10^{\circ}$ and fitting with 5th order polynomial was appropriate. However for a mere quality assurance (QA) purpose of OBI isocenter accuracy, it was adequate to use only four OBI Images taken at the OBI source angle of $0^{\circ},\;90^{\circ},\;180^{\circ}\;and\;270^{\circ}$. Maximal discrepancy was 0.44 mm which was observed between the OBI source angle of $90^{\circ}\;and\;180^{\circ}$ OBI isocenter accuracy was maintained below 0.5 mm for a year. Proposed QA program may be helpful to Implement a reasonable routine QA of the OBI isocenter accuracy without great efforts.

• Journal of Distribution Research
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• v.15 no.3
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• pp.111-137
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• 2010

The basic purpose of this study is to investigate perceived quality and service personal value affecting the result of long-term relationship between service buyers and suppliers. This research presented a constructive model(perceived quality affecting the service personal value and the moderate effect of NFC) in the on off line and then propose the research model base on prior researches and studies about relationships among components of service. Data were gathered from respondents who visit at the education service market. For this study, Data were analyzed by AMOS 7.0. We integrate the literature on services marketing with researches on personal values and perceived quality. The SERPVAL scale presented here allows for the creation of a common ground for assessing service personal values, giving a clear understanding of the key value dimensions behind service choice and usage. It will lead to a focus of future research in services marketing, extending knowledge in the field and stimulating further empirical research on service personal values. At the managerial level, as a tool the SERPVAL scale should allow practitioners to evaluate and improve the value of a service, and consequently, to define strategies and actions to address services for customers based on their fundamental personal values. Through qualitative and empirical research, we find that the service quality construct conforms to the structure of a second-order factor model that ties service quality perceptions to distinct and actionable dimensions: outcome, interaction, and environmental quality. In turn, each has two subdimensions that define the basis of service quality perceptions. The authors further suggest that for each of these subdimensions to contribute to improved service quality perceptions, the quality received by consumers must be perceived to be reliable, responsive, and empathetic. Although the service personal value may be found in researches that explore individual values and their consequences for consumer behavior, there is no established operationalization of a SERPVAL scale. The inexistence of an established scale, duly adapted in order to understand and analyze personal values behind services usage, exposes the need of a measurement scale with such a purpose. This need has to be rooted, however, in a conceptualization of the construct being scaled. Service personal values can be defined as a customer's overall assessment of the use of a service based on the perception of what is achieved in terms of his own personal values. As consumer behaviors serve to show an individual's values, the use of a service can also be a way to fulfill and demonstrate consumers'personal values. In this sense, a service can provide more to the customer than its concrete and abstract attributes at both the attribute and the quality levels, and more than its functional consequences at the value level. Both values and services literatures agree, that personal value is the highest-level concept, followed by instrumental values, attitudes and finally by product attributes. Purchasing behaviors are agreed to be the end result of these concepts' interaction, with personal values taking a major role in the final decision process. From both consumers' and practitioners' perspectives, values are extremely relevant, as they are desirable goals that serve as guiding principles in people's lives. While building on previous research, we propose to assess service personal values through three broad groups of individual dimensions; at the self-oriented level, we use (1) service value to peaceful life (SVPL) and, at the social-oriented level, we use (2) service value to social recognition (SVSR), and (3) service value to social integration (SVSI). Service value to peaceful life is our first dimension. This dimension emerged as a combination of values coming from the RVS scale, a scale built specifically to assess general individual values. If a service promotes a pleasurable life, brings or improves tranquility, safety and harmony, then its user recognizes the value of this service. Generally, this service can improve the user's pleasure of life, since it protects or defends the consumer from threats to life or pressures on it. While building upon both the LOV scale, a scale built specifically to assess consumer values, and the RVS scale for individual values, we develop the other two dimensions: SVSR and SVSI. The roles of social recognition and social integration to improve service personal value have been seriously neglected. Social recognition derives its outcome utility from its predictive utility. When applying this underlying belief to our second dimension, SVSR, we assume that people use a service while taking into consideration the content of what is delivered. Individuals consider whether the service aids in gaining respect from others, social recognition and status, as well as whether it allows achieving a more fulfilled and stimulating life, which might then be revealed to others. People also tend to engage in behavior that receives social recognition and to avoid behavior that leads to social disapproval, and this contributes to an individual's social integration. This leads us to the third dimension, SVSI, which is based on the fact that if the consumer perceives that a service strengthens friendships, provides the possibility of becoming more integrated in the group, or promotes better relationships at the social, professional or family levels, then the service will contribute to social integration, and naturally the individual will recognize personal value in the service. Most of the research in business values deals with individual values. However, to our knowledge, no study has dealt with assessing overall personal values as well as their dimensions in a service context. Our final results show that the scales adapted from the Schwartz list were excluded. A possible explanation is that although Schwartz builds on Rokeach work in order to explore individual values, its dimensions might be especially focused on analyzing societal values. As we are looking for individual dimensions, this might explain why the values inspired by the Schwartz list were excluded from the model. The hierarchical structure of the final scale presented in this paper also presents theoretical implications. Although we cannot claim to definitively capture the dimensions of service personal values, we believe that we come close to capturing these overall evaluations because the second-order factor extracts the underlying commonality among dimensions. In addition to obtaining respondents' evaluations of the dimensions, the second-order factor model captures the common variance among these dimensions, reflecting the respondents' overall assessment of service personal values. Towards this fact, we expect that the service personal values conceptualization and measurement scale presented here contributes to both business values literature and the service marketing field, allowing for the delineation of strategies for adding value to services. This new scale also presents managerial implications. The SERPVAL dimensions give some guidance on how to better pursue a highly service-oriented business strategy. Indeed, the SERPVAL scale can be used for benchmarking purposes, as this scale can be used to identify whether or not a firms' marketing strategies are consistent with consumers' expectations. Managerial assessment of the personal values of a service might be extremely important because it allows managers to better understand what customers want or value. Thus, this scale allows us to identify what services are really valuable to the final consumer; providing knowledge for making choices regarding which services to include. Traditional approaches have focused their attention on service attributes (as quality) and service consequences(as service value), but personal values may be an important set of variables to be considered in understanding what attracts consumers to a certain service. By using the SERPVAL scale to assess the personal values associated with a services usage, managers may better understand the reasons behind services' usage, so that they may handle them more efficiently. While testing nomological validity, our empirical findings demonstrate that the three SERPVAL dimensions are positively and significantly associated with satisfaction. Additionally, while service value to social integration is related only with loyalty, service value to peaceful life is associated with both loyalty and repurchase intent. It is also interesting and surprising that service value to social recognition appears not to be significantly linked with loyalty and repurchase intent. A possible explanation is that no mobile service provider has yet emerged in the market as a luxury provider. All of the Portuguese providers are still trying to capture market share by means of low-end pricing. This research has implications for consumers as well. As more companies seek to build relationships with their customers, consumers are easily able to examine whether these relationships provide real value or not to their own lives. The selection of a strategy for a particular service depends on its customers' personal values. Being highly customer-oriented means having a strong commitment to customers, trying to create customer value and understanding customer needs. Enhancing service distinctiveness in order to provide a peaceful life, increase social recognition and gain a better social integration are all possible strategies that companies may pursue, but the one to pursue depends on the outstanding personal values held by the service customers. Data were gathered from 284 respondents in the korean discount store and online shopping mall market. This research proposed 3 hypotheses on 6 latent variables and tested through structural equation modeling. 6 alternative measurements were compared through statistical significance test of the 6 paths of research model and the overall fitting level of structural equation model. and the result was successful. and Perceived quality more positively influences service personal value when NFC is high than when no NFC is low in the off-line market. The results of the study indicate that service quality is properly modeled as an antecedent of service personal value. We consider the research and managerial implications of the study and its limitations. In sum, by knowing the dimensions a consumer takes into account when choosing a service, a better understanding of purchasing behaviors may be realized, guiding managers toward customers expectations. By defining strategies and actions that address potential problems with the service personal values, managers might ultimately influence their firm's performance. we expect to contribute to both business values and service marketing literatures through the development of the service personal value. At a time when marketing researchers are challenged to provide research with practical implications, it is also believed that this framework may be used by managers to pursue service-oriented business strategies while taking into consideration what customers value.