• Journal of Venture Innovation
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• v.4 no.2
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• pp.97-108
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• 2021

Labor contracts appear in form as an exchange relationship between labor products and wages, but since they transcend the level of simple barter, they can be economically identified as "trading" and can be identified as "rental." From a legal point of view, a legal device that legally supports and imposes binding force on commodity exchange relations is a contract. Such a labor contract led to a relationship in which wages were received and a certain amount of time was placed under the direction and supervision of the employer as a counter benefit to the receipt of wages. Since working hours are subordinate hours with one's labor under the disposition authority of the employer, long hours of work can be done for the health and safety of workers and furthermore, it can be an act that violates the value to enjoy as a human being. The reduction of working hours needs to be shortened in terms of productivity and enjoyment of workers' culture so that they can expand and reproduce, but users' corporate management labor and production activities should also be compatible compared to those pursued by capitalist countries. Working hours can be seen as individual time and time in society as a whole, and long hours of work at the individual level are reduced, which is undesirable at the individual level, but an increase in products due to an increase in production time at the social level can help social development. It is necessary to consider working hours in terms of finding the balance between these individual and social levels. If the regulation method of working hours was to regulate the total amount of working hours, flexibility and elasticity of working hours are a qualitative regulation method that allows companies to flexibly allocate and organize working hours within a certain range of up to 52 hours per week. Accordingly, it is necessary to shorten working hours, but expand and implement the flexible working hours system according to the situation of the company. To this end, it is necessary to flexibly operate the flexible working hours system, which is currently limited to six months, handle the selective working hours by agreement between employers and workers, and expand the target work of discretionary working hours according to the development of information and communication technology and new types based on the 4th industrial revolution.

• Journal of Venture Innovation
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• v.6 no.4
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• pp.99-111
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• 2023

This study aims to confirm that consumers' satisfaction with online shopping websites has changed to a phenomenon different from the past. In other words, in a situation where the use of e-commerce is expanding worldwide after the pandemic and various types of commerce such as mobile commerce and social commerce are formed, the consumer's information processing and decision-making process are meaningful in examining the behavior that has been changed based on the perceived motivation level of consumers by the new environment according to the consumption value and personal characteristics perceived by the consumer. In other words, the purpose of this study was to investigate the effect of consumption value and need for cognition on the satisfaction toward online websites as a mediating role in the trust of the website. As a result of testing Hypothesis 1, not only the hedonic value of the consumer for the website but also the utilitarian value had a positive influence on the satisfaction toward the website, and in particular, the utilitarian value showed a relatively greater influence than the hedonic value. However, the negative relationship between the need for cognition and satisfaction was found to be at a significant level under one-sided verification. In Hypothesis 2, only the utilitarian value among the consumption values of 2-1 showed a positive effect on satisfaction through a mediating role of trust. It was confirmed that the utilitarian value among the consumption values was an important factor in the satisfaction toward the website. The significance of this study is that, unlike previous research results, not only consumption value based on senses and emotions but also utilitarian value has a greater influence. Therefore, utilitarian value and need for cognition have a stronger influence on satisfaction if they play a mediating role based on the trust of the website used by consumers. These findings reflect the current market trend of online consumption, and they are helpful in the management and strategy of online websites based on consumer behavior understanding and major factors.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.523-541
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• 2023

As accessibility to 3D printers increases, there is a growing frequency of exposure to chemicals associated with 3D printing. However, research on the toxicity and harmfulness of chemicals generated by 3D printing is insufficient, and the performance of toxicity prediction using in silico techniques is limited due to missing molecular structure data. In this study, quantitative structure-activity relationship (QSAR) model based on data-centric AI approach was developed to predict the toxicity of new 3D printing materials by imputing missing values in molecular descriptors. First, MissForest algorithm was utilized to impute missing values in molecular descriptors of hazardous 3D printing materials. Then, based on four different machine learning models (decision tree, random forest, XGBoost, SVM), a machine learning (ML)-based QSAR model was developed to predict the bioconcentration factor (Log BCF), octanol-air partition coefficient (Log Koa), and partition coefficient (Log P). Furthermore, the reliability of the data-centric QSAR model was validated through the Tree-SHAP (SHapley Additive exPlanations) method, which is one of explainable artificial intelligence (XAI) techniques. The proposed imputation method based on the MissForest enlarged approximately 2.5 times more molecular structure data compared to the existing data. Based on the imputed dataset of molecular descriptor, the developed data-centric QSAR model achieved approximately 73%, 76% and 92% of prediction performance for Log BCF, Log Koa, and Log P, respectively. Lastly, Tree-SHAP analysis demonstrated that the data-centric-based QSAR model achieved high prediction performance for toxicity information by identifying key molecular descriptors highly correlated with toxicity indices. Therefore, the proposed QSAR model based on the data-centric XAI approach can be extended to predict the toxicity of potential pollutants in emerging printing chemicals, chemical process, semiconductor or display process.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.31-43
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• 2022

Startups are recognized as the vitality of the economy, and countries are competing to attract competitive overseas entrepreneurs and startups to their own startup ecosystem. In this global trend, entrepreneurs cross the border without hesitation, expecting abundant available resources and a startup friendly environment. Despite the increasing frequency of start-up migration between countries, studies related to this are very rare. Therefore, this study has chosen the cross-border migration of startups between countries as a research topic, and those who have been involved in the cross-border entrepreneurial migration to South Korea as a research sample. This study consists of two stages. The first research stage hires a Delphi method to collect expert opinions and find major factors related to the global startup migration. Drawing on the prior literature on the regional startup ecosystem at the national level, this stage is to conduct expert interviews in order to discover underlying factors and subfactors important for global migration of startups. The second stage measures the importance of the factors and subfactors using the AHP model. The priorities of factors and factors were identified hiring the overseas entrepreneurs who moved to Korea as the AHP survey samples. The results of this study suggest some interesting implications. First, a group of entrepreneurs with nomadic tendencies was found in the trend of global migration of entrepreneurs. They had already started their own businesses with the same business ideas in multiple countries before settling down in Korea. Second, important unique factors and subfactors in the context of global start-up migration were identified. A good example is the government's support package, including start-up visas. Third, it was possible to know the priority of the factors and subfactors that influence the global migration of startups This study is meaningful in that it preemptively conducted exploratory research focusing on a relatively new phenomenon of global startup migration, which recently catches attention in the global startup ecosystem. At the same time, it has a limitation in that it is difficult to generalize the meanings found in this study because the research was conducted based on the case of South Korea

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.44-62
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• 2024

The development of online funeral services and social issues of eco-friendly funeral culture have raised awareness of the new need for online funeral culture. There have been several attempts to revitalize online funeral services in domestic institutions and companies, but the effect is weak. The purpose of this study is to propose a design that can improve the accessibility and usability of online memorial services by analyzing the usability problem factors through a First Time User Experience analysis of the online memorial platform. Therefore, in this study, in order to identify the problem factors of the online memorial platform, a literature review on the UX, OOBE, and FTUE theories was conducted. The subject of the study was the app 'Memorial'. Before analyzing the First-Time User-Experience, IA was compared and analyzed with other similar services to understand the characteristics of the UX service of the app 'Memorial', which is the subject of the study. In addition, tasks corresponding to the Unpack-Setup/Configure-First Use stage were performed on 10 subjects who had no experience using the online memorial platform. The experimental process was expressed as the UX Curve to identify factors that caused negative experiences. As a result, the major problem factors included unnecessary UI elements, the need for sensitive personal information at the membership stage, and lack of immersion in the service. The improvements included strengthening community functions to facilitate the sharing of emotions and promote smooth communication between users. We proposed UI/UX service developments that enhanced the app by incorporating these insights. In order to verify the effectiveness, serviceability, and value of the developed prototype, an interview with a expert was conducted. The interviewes consisted of three service design experts. This study was conducted to contribute to the quality improvement and activation of the recently emerging online funeral services. The study is significant as it aims to understand the current status of these services and identify the factors necessary to improve service accessibility and usability. Subsequent studies require in-depth user verification of how much the proposed improvement plan affects the actual user experience.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.345-363
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• 2023

The genus Desmodesmus (Chodat) S.S. An, T. Friedl & E. Hegewald is ubiquitous in freshwater ecosystems, such as rivers, ponds, and wetlands. The actual species diversity and distribution of the genus is unknown because of morphological plasticity affected by habitats. Currently, 38 Desmodesmus species have been reported in Korea most of which transferred from the genus Scenedesmus recently, however, no phylogenetic relationships have been studied yet. Despite the challenges in analyzing relationships among Desmodesmus species through the morphology, ecology, and original description, this study focused on examining species-level relationships using the FBCC culture strains isolated from Korea. A total of 299 sequences (66 of 18S rRNA, 47 of atpB, 67 of petA, 52 of rbcL, and 67 of tufA) were newly determined and used for phylogenetic analysis. Four plastid genes tend to have higher variation than 18S rRNA in the variable sites and P-distance. From the combined phylogeny, the Desmodesmus included six clades such as Clade-1: D. pseudoserratus and D. serratus, Clade-2: D. communis, D. dispar, D. maximus, D. pannonicus, unidentified Desmodesmus sp., Clade-3: D. bicaudatus and D. intermedius, Clade-4: D. microspina, D. multivariablis, D. pleiomorphus, D. subspicatus, Clade-5: D. abundans, D. kissii, and D. spinosus, and Clade-6: D. armatus, D. armatus var. longispina, D. opoliensis, unidentified Desmodesmus spp. The new sequence data from FBCC strains will be used to identify species and study the molecular ecology of scenedesmacean green algae in freshwater ecosystems. The phylogenetic information from this study will expand our understanding of Desmodesmus species diversity in Korea.

• Journal of Christian Education in Korea
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• v.78
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• pp.57-85
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• 2024

Purpose of the study: In order to utilize artificial intelligence-generated AI in educational ministry, this study analyzes the concept of artificial intelligence and generative AI and the educational theological aspects of educational ministry to find ways to efficiently utilize artificial intelligence ChatGPT in educational ministry. Contents and methods of the study: The contents of this study are. First, the contents of this study were analyzed by dividing the concepts of artificial intelligence and generative AI into the concept of artificial intelligence, types of artificial intelligence, and generative language model AI ChatGPT. Second, the educational theological analysis of educational ministry was divided into the concept of educational ministry, the goals of educational ministry, the content of educational ministry, and the direction of educational ministry in the era of artificial intelligence. Third, the plan to use artificial intelligence ChatGPT in educational ministry is to provide tools for writing sermon manuscripts, preparation tools for worship and prayer, and church education, focusing on the five functions of the early church community. It was analyzed by dividing it into tools for teaching, tools for teaching materials for believers, and tools for serving and volunteering. Conclusion and Recommendation: The conclusion of this study is that, first, when writing sermon manuscripts through artificial intelligence ChatGPT, high-quality sermon manuscripts can be written through the preacher's spirituality, faith, and insight. Second, through artificial intelligence ChatGPT, you can efficiently design and plan worship services and prepare services that serve the congregation objectively through various scenarios. Third, by using artificial intelligence ChatGPT in church education, it can be used while maintaining a complementary relationship with teachers through collaboration with human and artificial intelligence teachers. Fourth, through artificial intelligence ChatGPT, we provide a program that allows members of the church community to share spiritual fellowship, a plan to meet the needs of church members and strengthen interdependence, and an attitude of actively welcoming new people and respecting diversity. It provides useful materials that can play an important role in giving, loving, serving, and growing together in the love of Christ. Lastly, through artificial intelligence ChatGPT, we are seeking ways to provide various information about volunteer activities, learning support for children and youth in the community, mentoring-related programs, and playing a leading role in forming a village community in the local community.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.

• 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.