Purpose: The purpose of this study is to evaluate the usefulness of Surface-Guided Patient Setup by comparing the patient positioning accuracy when image-guided radiation therapy was used for Markerless patients(unmarked on the skin) using Surface-Guided Patient Setup and Marker patients(marked on the skin) using Laser-Based Patient Setup. Materials And Methods: The position error during IGRT was compared between a Markerless patient initially set up with SGPS using an optical surface scanning system using three cameras and a Marker patient initially set up with LBPS that aligns the laser with the marker drawn on the patient's skin. Both SGPS and LBPS were performed on 20 prostate cancer patients and 10 Stereotactic Radiation Surgery patients, respectively, and SGPS was performed on an additional 60 breast cancer patients. All were performed IGRT using CBCT or OBI. Position error of 6 degrees of freedom was obtained using Auto-Matching System, and comparison and analysis were performed using Offline-Review in the treatment planning system. Result: The difference between the root mean square (RMS) of SGPS and LBPS in prostate cancer patients was Vrt -0.02cm, Log -0.02cm, Lat 0.01cm, Pit -0.01°, Rol -0.01°, Rtn -0.01°, SRS patients was Vrt 0.02cm, Log -0.05cm, Lat 0.00cm, Pit -0.30°, Rol -0.15°, Rtn -0.33°. there was no significant difference between the two regions. According to the IGRT standard of breast cancer patients, RMS was Vrt 0.26, Log 0.21, Lat 0.15, Pit 0.81, Rol 0.49, Rtn 0.59. Conclusion:. As a result of this study, the position error value of SGPS compared to LBPS did not show a significant difference between prostate cancer patients and SRS patients. In the case of additionally performed SGPS breast cancer patients, the position error value was not large based on IGRT. Therefore, it is considered that it will be useful to replace LBPS with SGPS, which has the great advantage of not requiring patient skin marking..
On the purpose to suggest an advanced scheme in assessing the domestic wheat quality, this paper reviewed the inspection systems of wheat in major wheat producing countries as well as the quality criteria which are being used in wheat grading and classification. Most wheat producing countries are adopting both classifications of class and grade to provide an objective evaluation and an official certification to their wheat. There are two main purposes in the wheat classification. The first objectives of classification is to match the wheat with market requirements to maximize market opportunities and returns to growers. The second is to ensure that payments to glowers aye made on the basis of the quality and condition of the grain delivered. Wheat classes has been assigned based on the combination of cultivation area, seed-coat color, kernel and varietal characteristics that are distinctive. Most reputable wheat marketers also employ a similar approach, whereby varieties of a particular type are grouped together, designed by seed coat colour, grain hardness, physical dough properties, and sometimes more precise specification such as starch quality, all of which are genetically inherited characteristics. This classification in simplistic terms is the categorization of a wheat variety into a commercial type or style of wheat that is recognizable for its end use capabilities. All varieties registered in a class are required to have a similar end-use performance that the shipment be consistent in processing quality, cargo to cargo and year to year, Grain inspectors have historically determined wheat classes according to visual kernel characteristics associated with traditional wheat varieties. As well, any new wheat variety must not conflict with the visual distinguishability rule that is used to separate wheats of different classes. Some varieties may possess characteristics of two or more classes. Therefore, knowledge of distinct varietal characteristics is necessary in making class determinations. The grading system sets maximum tolerance levels for a range of characteristics that ensure functionality and freedom from deleterious factors. Tests for the grading of wheat include such factors as plumpness, soundness, cleanliness, purity of type and general condition. Plumpness is measured by test weight. Soundness is indicated by the absence or presence of musty, sour or commercially objectionable foreign odors and by the percentage of damaged kernels that ave present in the wheat. Cleanliness is measured by determining the presence of foreign material after dockage has been removed. Purity of class is measured by classification of wheats in the test sample and by limitation for admixtures of different classes of wheat. Moisture does not influence the numerical grade. However, it is determined on all shipments and reported on the official certificate. U.S. wheat is divided into eight classes based on color, kernel Hardness and varietal characteristics. The classes are Durum, Hard Red Spring, Hard Red Winter, Soft Red Winter, Hard White, soft White, Unclassed and Mixed. Among them, Hard Red Spring wheat, Durum wheat, and Soft White wheat are further divided into three subclasses, respectively. Each class or subclass is divided into five U.S. numerical grades and U.S. Sample grade. Special grades are provided to emphasize special qualities or conditions affecting the value of wheat and are added to and made a part of the grade designation. Canadian wheat is also divided into fourteen classes based on cultivation area, color, kernel hardness and varietal characteristics. The classes have 2-5 numerical grades, a feed grade and sample grades depending on class and grading tolerance. The Canadian grading system is based mainly on visual evaluation, and it works based on the kernel visual distinguishability concept. The Australian wheat is classified based on geographical and quality differentiation. The wheat grown in Australia is predominantly white grained. There are commonly up to 20 different segregations of wheat in a given season. Each variety grown is assigned a category and a growing areas. The state governments in Australia, in cooperation with the Australian Wheat Board(AWB), issue receival standards and dockage schedules annually that list grade specifications and tolerances for Australian wheat. AWB is managing "Golden Rewards" which is designed to provide pricing accuracy and market signals for Australia's grain growers. Continuous payment scales for protein content from 6 to 16% and screenings levels from 0 to 10% based on varietal classification are presented by the Golden Rewards, and the active payment scales and prices can change with market movements.movements.
This study was aimed at investigating important factors influencing career success among regular workers. The current researcher scrutinized the degree to which variables and factors affect the career success and occupational turnover rates of the research participants. At the same tune, two hypothetical path models established by the researcher were examined using linear multiple regression methods and the LISREL. After examining the differences among the factors of career success, a comparison was made between the disabled worker group and the non-disabled worker group. A questionnaire using the 5-point Likert scale was distributed to a group of 374 workers with disabilities and 463 workers without disabilities. For the data analysis purpose, the structural equation model, factor analysis, correlation analysis, and multiple regression analysis were carried out. The results of this study ran be summarized as follows. First, the results of factor analysis showed important categories of conceptual themes of career success. The initial conceptual factor model did not accord with the empirical one. A three-factorial model revealed categories of personal, family, and organizational factor respectively. The personal factor was composed of the self-esteem and self-efficiency. The family factor was consisted of the multi-roles stress and the number of children. Finally, the organizational factor was composed of the capacity for utilizing resources, networking, and the frequency of mentoring. In addition, the total 10 sub areas of career success were divided by two important aspects; the subjective career success and the objective career success. Second, both research participant groups seemed to be influenced by their occupational types. However, all predictive variables excluding the wage rate and the average length of work years had significant impact on job success for the disabled work group, while all the variables excluding the frequency of advice and length of working years had significant impact on job success for the non-disabled worker group. Third, the turnover rate was significantly influenced by the age and the experience of turnover of the research participants. However, the number of co-workers was the strongest predictive variable for the worker group with disabilities, but the occupation choice variable for the worker group without disabilities. For the disabled worker group, the turnover rate was differently influenced by the type of occupation, the length of working years, while multi-role stress and the average working years at the time of turnover for the worker group without disabilities. Fifth, as a result of verifying the hypothetical path model, it showed that the first model was somewhat proper and could predict the career success on both research participant groups. In the second model, the Chi-square, the degree of freedom ((
This study investigated consumer intention to use a location-based mobile shopping service (LBMSS) that integrates cognitive and affective responses. Information relevancy was integrated into pleasure-arousal-dominance (PAD) emotional state model in the present study as a conceptual framework. The results of an online survey of 335 mobile phone users in the U.S. indicated the positive effects of arousal and information relevancy on pleasure. In addition, there was a significant relationship between pleasure and intention to use a LBMSS. However, the relationship between dominance and pleasure was not statistically significant. The results of the present study provides insight to retailers and marketers as to what factors they need to consider to implement location-based mobile shopping services to improve their business performance. Extended Abstract : Location aware technology has expanded the marketer's reach by reducing space and time between a consumer's receipt of advertising and purchase, offering real-time information and coupons to consumers in purchasing situations (Dickenger and Kleijnen, 2008; Malhotra and Malhotra, 2009). LBMSS increases the relevancy of SMS marketing by linking advertisements to a user's location (Bamba and Barnes, 2007; Malhotra and Malhotra, 2009). This study investigated consumer intention to use a location-based mobile shopping service (LBMSS) that integrates cognitive and affective response. The purpose of the study was to examine the relationship among information relevancy and affective variables and their effects on intention to use LBMSS. Thus, information relevancy was integrated into pleasure-arousal-dominance (PAD) model and generated the following hypotheses. Hypothesis 1. There will be a positive influence of arousal concerning LBMSS on pleasure in regard to LBMSS. Hypothesis 2. There will be a positive influence of dominance in LBMSS on pleasure in regard to LBMSS. Hypothesis 3. There will be a positive influence of information relevancy on pleasure in regard to LBMSS. Hypothesis 4. There will be a positive influence of pleasure about LBMSS on intention to use LBMSS. E-mail invitations were sent out to a randomly selected sample of three thousand consumers who are older than 18 years old and mobile phone owners, acquired from an independent marketing research company. An online survey technique was employed utilizing Dillman's (2000) online survey method and follow-ups. A total of 335 valid responses were used for the data analysis in the present study. Before the respondents answer any of the questions, they were told to read a document describing LBMSS. The document included definitions and examples of LBMSS provided by various service providers. After that, they were exposed to a scenario describing the participant as taking a saturday shopping trip to a mall and then receiving a short message from the mall. The short message included new product information and coupons for same day use at participating stores. They then completed a questionnaire containing various questions. To assess arousal, dominance, and pleasure, we adapted and modified scales used in the previous studies in the context of location-based mobile shopping service, each of the five items from Mehrabian and Russell (1974). A total of 15 items were measured on a seven-point bipolar scale. To measure information relevancy, four items were borrowed from Mason et al. (1995). Intention to use LBMSS was captured using two items developed by Blackwell, and Miniard (1995) and one items developed by the authors. Data analyses were conducted using SPSS 19.0 and LISREL 8.72. A total of usable 335 data were obtained after deleting the incomplete responses, which results in a response rate of 11.20%. A little over half of the respondents were male (53.9%) and approximately 60% of respondents were married (57.4%). The mean age of the sample was 29.44 years with a range from 19 to 60 years. In terms of the ethnicity there were European Americans (54.5%), Hispanic American (5.3%), African-American (3.6%), and Asian American (2.9%), respectively. The respondents were highly educated; close to 62.5% of participants in the study reported holding a college degree or its equivalent and 14.5% of the participants had graduate degree. The sample represents all income categories: less than $24,999 (10.8%), $25,000-$49,999 (28.34%), $50,000-$74,999 (13.8%), and $75,000 or more (10.23%). The respondents of the study indicated that they were employed in many occupations. Responses came from all 42 states in the U.S. To identify the dimensions of research constructs, Exploratory Factor Analysis (EFA) using a varimax rotation was conducted. As indicated in table 1, these dimensions: arousal, dominance, relevancy, pleasure, and intention to use, suggested by the EFA, explained 82.29% of the total variance with factor loadings ranged from .74 to .89. As a next step, CFA was conducted to validate the dimensions that were identified from the exploratory factor analysis and to further refine the scale. Table 1 exhibits the results of measurement model analysis and revealed a chi-square of 202.13 with degree-of-freedom of 89 (p =.002), GFI of .93, AGFI = .89, CFI of .99, NFI of .98, which indicates of the evidence of a good model fit to the data (Bagozzi and Yi, 1998; Hair et al., 1998). As table 1 shows, reliability was estimated with Cronbach's alpha and composite reliability (CR) for all multi-item scales. All the values met evidence of satisfactory reliability in multi-item measure for alpha (>.91) and CR (>.80). In addition, we tested the convergent validity of the measure using average variance extracted (AVE) by following recommendations from Fornell and Larcker (1981). The AVE values for the model constructs ranged from .74 through .85, which are higher than the threshold suggested by Fornell and Larcker (1981). To examine discriminant validity of the measure, we again followed the recommendations from Fornell and Larcker (1981). The shared variances between constructs were smaller than the AVE of the research constructs and confirm discriminant validity of the measure. The causal model testing was conducted using LISREL 8.72 with a maximum-likelihood estimation method. Table 2 shows the results of the hypotheses testing. The results for the conceptual model revealed good overall fit for the proposed model. Chi-square was 342.00 (df = 92, p =.000), NFI was .97, NNFI was .97, GFI was .89, AGFI was .83, and RMSEA was .08. All paths in the proposed model received significant statistical support except H2. The paths from arousal to pleasure (H1: