• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.101-113
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• 1995

The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

• Radiation Oncology Journal
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• v.17 no.2
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• pp.113-119
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• 1999

Purpose : To evaluate possible acute toxicity and early response of concurrent radiation therapy and low dose daily cisplatin as a radiosensitizer in patients with locally advanced uterine cervical carcinomas. Materials and Method : From December 1996 to January 1999, 38 previously untreated Patients with locally advanced squamous cell carcinoma of the uterine cervix (from stage IIB to stage IIIB) were treated at Inha University Hospital. All patients underwent standard pretreatment staging Procedures after the initial evaluation by gynecologists and radiation oncologists. Sixteen Patients with huge cervical mass (>4 cm) were submitted to the group treated with concurrent radiation therapy and low dose daily cisplatin while the remainder was treated with radiation therapy alone. Radiation therapy consisted of 4500 cGy external beam irradiation to whole pelvis (midline block after 3000 cGy), 900$\~$1000 cGy boost to involved parametrium, and high dose-rate intracavitary brachytherapy (a total dose of 3000$\~$3500 cGy/500 cGy per fraction to point A, twice per week). In the group treated with low dose cisplatin concurrently, 10 mg of daily intravenous cisplatin was given from the 1st day of radiation therapy to the 20th day of radiation therapy. Acute toxicity was measured according to expanded common toxicity criteria of the NCI (C) Clinical Trials. Early response data were analyzed at minimum 4 weeks' follow-up after completion of the treatment protocol. Results: Hematolgic toxici쇼 was more prominent in patients treated with radiation therapy and cisplatin. Six of 16 patients (37.5$\~$) treated with radiation therapy and cisplatin and one of 22 patients (4.5$\~$) treated with radiation therapy alone experienced grade 3 leukopenia. In Fisher's exact test, there was statistically significant difference between two groups regarding leukopenia (P=0.030). There was no apparent difference in the frequency of gastrointestinal and genitourinary toxicity between two groups (P=0.066). Three of 16 patients (18.7$\~$) treated with radiation therapy and cisplatin and two of 22 patients (9.1$\~$) treated with radiation therapy alone experienced more than 5 kg weight loss during the treatment. There was no statistically significant difference on weight loss between two groups (P=0.63). Two patients on each group were not evaluable for the early response because of incomplete treatment. The complete response rate at four weeks' follow-up was 80$\~$(16/20) for the radiation therapy alone group and 78$\~$ (11/14) for the radiation therapy and cisplatin group. There was no statistically significant difference in early response between two treatment groups (P=0.126). Conclusion : This study led to the conclusion that the hematologic toxicity from the treatment with concurrent radiation therapy and low dose daily cisplatin seems to be more prominent than that from the treatment of radiation therapy alone. There was no grade 4 hematologic toxicity or mortality in both groups. The hematologic toxicity in both treatment groups seems to be well managable modically. Since the risk factors were not balanced between two treatment groups, the direct comparison of early response of both groups was not possible. However, preliminary results regarding early response for patients with bulky cervical tumor mass treated with radiation therapy and low dose daily cisplatin was encouraging. Longer follow-up is necessary to evaluate the survival data. A phase III study is needed to evaluate the efficacy of concurrent daily low dose cisplatin with radiation therapy in bulky cervical cancer.

• Applied Biological Chemistry
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• v.8
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• pp.87-93
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• 1967

1) For the micro-analysis of mercury in plant materials, the method of Furutani was shown to be the simplest and most efficient way and the recovery of the assay was about 98%. 2) When the rice grain was soaked in 1/1000 diluted solution of organo-mercury fungicide for 8 hours at the end of March, the amounts of mercury residues in the brown rice and unhulled rice were 8.8 to $9.5\;{\mu}g/g$ seeds and 10.1 to $10.7\;{\mu}g/g$ seeds, respectively. 3) By washing the treated rice seeds with running water for three days, tile residual mercury concentration was reduced to 1/4 to 1/5; thus the mercury residues were 1.86 to $1.92\;{\mu}g/g$ for brown rice and 1.96 to $2.93\;{\mu}g/g$ for unhulled rice. 4) The residual mercury was present more in the unhulled rice than in the brown rice, either before or after washing of the treated seeds. 5) Among the different rice varieties, no difference was observed in mercury residues by seed treatment and washing.

• Restorative Dentistry and Endodontics
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• v.32 no.2
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• pp.138-150
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• 2007

The purpose of this study was to evaluate the difference of surface roughness of composite resin according to composite resin type, polishing methods, and use of resin sealant. Two hundred rectangular specimens, sized $8{\times}3{\times}2mm$, were made of Micro-new (Bisco, Inc., Schaumburg, IL, U.S.A) and Filtek Supreme (3M ESPE Dental Products, St. Paul, MN, U.S.A.), and divided into two groups; Micronew-M group, Filtek Supreme-S group. Specimens for each composite group were subdivided into five groups by finishing and polishing instruments used; M1 & S1(polyester strip), M2 & S2 (Sof-Lex disc), M3 & S3 (Enhance disc and polishing paste), M4 & S4(Astropol) and M5 & S5 (finishing bur), Polished groups were added letter B after the application of resin surface sealant (Biscover), eg, M1B and S1B. After specimens were stored with distilled water for 24hr, average surface roughness (Ra) was taken using a surface roughness tester. Representative specimens of each group were examined by FE-SEM (S-4700: Hitachi High Technologies Co., Tokyo, Japan). The data were analysed using paired t-test, ANOVA and Duncan's tests at the 0.05 probability level. The results of this study were as follows ; 1. The lowest Ra was achieved in all groups using polyester strip and the highest Ra was achieved in M5, S5 and M5B groups using finishing bur. On FE-SEM, M1 and S1 groups provided the smoothest surfaces, M5 and S5 groups were presented the roughest surfaces and voids by debonding of filler on the polished specimens. 2. There was no significant difference in Ra between Micronew and Filtek Supreme before the application of resin sealant, but Micronew was smoother than Filek Supreme after the application of resin sealant. 3. There was significant corelation between Ra of type of composite resin and polishing methods before the application of resin sealant (p=0.000), but no significant interaction between them after the application of resin sealant. On FE-SEM, most of composite resin surfaces were smooth after the application of resin sealant on the polished specimens. 4. Compared with before and after the application of resin sealant in group treated in the same composite and polishing methods, Ra of M4B and M5B was statistically lower than that of M4 and M5, and S5B was lower than that of S5, respectively (p<0.05). In conclusion, surface roughness by polishing instruments was different according to type of composite resin. Overall, polyester strip produced the smoothest surface, but finishing bur produced the roughest surface. Application of resin sealant provided the smooth surfaces in specimens polished with Enhance, Astropol and finishing bur, but not provided them in specimens polished with Sof-Lex disc.

• The Journal of Korean Academy of Prosthodontics
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• v.46 no.2
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• pp.148-156
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• 2008

Statement of problems: Self-etch adhesives exhibit some clinical benefits such as ease of manipulation and reduced technique-sensitivity. Nevertheless, some concern remains regarding the bonding effectiveness of self-etch adhesives to enamel, in particular when so-called 'mild' self-etch adhesives are employed. This study compared the microtensile bond strengths to ground enamel of the two-step self-etch adhesive Clearfil SE Bond (Kuraray) to the three-step etch-and- rinse adhesive Scotchbond Multi-Purpose (3M ESPE) and the one-step self-etch adhesive iBond (Heraeus Kulzer). Purpose: The purpose of this study was to determine the effect of a preceding phosphoric acid conditioning step on the bonding effectiveness of a two-step self-etch adhesive to ground enamel. Material and methods: The two-step self-etch adhesive Clearfil SE Bond non-etch group, Clearfil SE Bond etch group with prior 35% phosphoric acid etching, and the one-step self-etch adhesive iBond group were used as experimental groups. The three-step etch-and-rinse adhesive Scotchbond Multi-Purpose was used as a control group. The facial surfaces of bovine incisors were divided in four equal parts cruciformly, and randomly distributed into each group. The facial surface of each incisor was ground with 800-grit silicon carbide paper. Each adhesive group was applied according to the manufacturer's instructions to ground enamel, after which the surface was built up using Light-Core (Bisco). After storage in distilled water at $37^{\circ}C$ for 1 week, the restored teeth were sectioned into enamel beams approximately 0.8*0.8mm in cross section using a low speed precision diamond saw (TOPMET Metsaw-LS). After storage in distilled water at $37^{\circ}C$ for 1 month, 3 months, microtensile bond strength evaluations were performed using microspecimens. The microtensile bond strength (MPa) was derived by dividing the imposed force (N) at time of fracture by the bond area ($mm^2$). The mode of failure at the interface was determined with a microscope (Microscope-B nocular, Nikon). The data of microtensile bond strength were statistically analyzed using a one-way ANOVA, followed by Least Significant Difference Post Hoc Test at a significance level of 5%. Results: The mean microtensile bond strength after 1 month of storage showed no statistically significant difference between all adhesive groups (P>0.05). After 3 months of storage, adhesion to ground enamel of iBond was not significantly different from Clearfil SE Bond etch (P>>0.05), while Clearfil SE Bond non-etch and Scotchbond Multi-Purpose demonstrated significantly lower bond strengths (P<0.05), with no significant differences between the two adhesives. Conclusion: In this study the microtensile bond strength to ground enamel of two-step self-etch adhesive Clearfil SE Bond was not significantly different from three-step etch-and-rinse adhesive Scotchbond Multi-Purpose, and prior etching with 35% phosphoric acid significantly increased the bonding effectiveness of Clearfil SE Bond to enamel at 3 months.

• Journal of Distribution Research
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• v.15 no.3
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• pp.1-34
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• 2010

Introduction The purpose of this research is to develop overall model which involves the effect of ongoing support services by franchisor on franchisee's relationship quality(trust, satisfaction, and commitment) and business performance(financial and non-financial performance), and to investigate the relationships among trust, satisfaction, commitment, financial and non-financial performance. This study also suggests franchise business or franchise system should be based on long-term orientation between franchisor and franchisee rather than short-term orientation, or transactional relationship, and proposes the most effective way of providing on-going support services by franchisor with franchisee thru symbiotic relationship among franchisor and franchisee Research Model and Hypothesis The research model as Figure 1 shows the variables on-going support services which affect the relationship quality between franchisor and franchisee such as trust, satisfaction, and commitment, and also analyze the effects of relationship quality on business performance including financial and non-financial performance We established 12 hypotheses to test as follows; Relationship between on-going support services and trust H1: On-going support services factors (product category & price, logistics service, promotion, information providing & problem solving capability, supervisor's support, and education & training support) have positive effect on franchisee's trust. Relationship between on-going support services and satisfaction H2: On-going support services factors (product category & price, logistics service, promotion, information providing & problem solving capability, supervisor's support, and education & training support) have positive effect on franchisee's satisfaction. Relationship between on-going support services and commitment H3: On-going support services factors (product category & price, logistics service, promotion, information providing & problem solving capability, supervisor's support, and education & training support) have positive effect on franchisee's commitment. Relationship among relationship quality: trust, satisfaction, and commitment H4: Franchisee's trust has positive effect on franchisee's satisfaction. H5: Franchisee's trust has positive effect on franchisee's commitment. H6: Franchisee's satisfaction has positive effect on franchisee's commitment. Relationship between relationship quality and business performance H7: Franchisee's trust has positive effect on franchisee's financial performance. H8: Franchisee's trust has positive effect on franchisee's non-financial performance. H9: Franchisee's satisfaction has positive effect on franchisee's financial performance. H10: Franchisee's satisfaction has positive effect on franchisee's non-financial performance. H11: Franchisee's commitment has positive effect on franchisee's financial performance. H12: Franchisee's commitment has positive effect on franchisee's non-financial performance. Method The on-going support services were defined as an organized system of continuous supporting services by franchisor for the purpose of satisfying the expectation of franchisee based on long-term orientation and classified into six constructs such as product category & price, logistics service, promotion, providing information & problem solving capability, supervisor's support, and education & training support. The six constructs were measured agreement using a 7-point Likert-type scale (1 = strongly disagree to 7 = strongly agree)as follows. The product category & price was measured by four items: menu variety, price of food material provided by franchisor, and support for developing new menu. The logistics service was measured by six items: distribution system of franchisor, return policy for provided food materials, timeliness, inventory control level of franchisor, accuracy of order, and flexibility of emergency order. The promotion was measured by five items: differentiated promotion activities, brand image of franchisor, promotion effect such as customer increase, long-term plan of promotion, and micro-marketing concept in promotion. The providing information & problem solving capability was measured by information providing of new products, information of competitors, information of cost reduction, and efforts for solving problems in franchisee's operations. The supervisor's support was measured by supervisor operations, frequency of visiting franchisee, support by data analysis, processing the suggestions by franchisee, diagnosis and solutions for the franchisee's operations, and support for increasing sales in franchisee. Finally, the of education & training support was measured by recipe training by specialist, service training for store people, systemized training program, and tax & human resources support services. Analysis and results The data were analyzed using Amos. Figure 2 and Table 1 present the result of the structural equation model. Implications The results of this research are as follows: Firstly, the factors of product category, information providing and problem solving capacity influence only franchisee's satisfaction and commitment. Secondly, logistic services and supervising factors influence only trust and satisfaction. Thirdly, continuing education and training factors influence only franchisee's trust and commitment. Fourthly, sales promotion factor influences all the relationship quality representing trust, satisfaction, and commitment. Fifthly, regarding relationship among relationship quality, trust positively influences satisfaction, however, does not directly influence commitment, but satisfaction positively affects commitment. Therefore, satisfaction plays a mediating role between trust and commitment. Sixthly, trust positively influence only financial performance, and satisfaction and commitment influence positively both financial and non-financial performance.