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Research on the Measures and Driving Force behind the Three Major Works of Daesoon Jinrihoe in North Korea in Case of the Respective Types of Unification on the Korean Peninsula (한반도 통일 유형별 북한지역의 대순진리회 3대 중요사업 추진 여건과 방안 연구)

  • Park, Young-taek
    • Journal of the Daesoon Academy of Sciences
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    • v.39
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    • pp.137-174
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    • 2021
  • The main theme of this paper centers on how to promote Three Major Works of Daesoon Jinrihoe, charity aid, social welfare, and education projects, during the unification period. Determining the best methods of promotion is crucial because the Three Major Works must be carried out after unification, and the works must remain based on the practice of the philosophy of Haewon-sangsaeng (the Resolution of Grievances for Mutual Beneficence). The idea of Haewon-sangsaeng is in line with the preface of the U.N. Charter and the aim of world peace. North Korean residents are suffering from starvation under their devastated economy, which is certain to face a crisis of materialistic deficiency during reunification. In this study, the peaceful unification of Germany, unification under a period of sudden changes in Yemen, and the militarized unification of Vietnam were taken as case studies to diagnose and analyze the conditions which would affect the implementation of the Three Major Works. These three styles of unification commonly required a considerable budget and other forms of support to carry out the Three Major Works. Especially if unification were to occur after a period of sudden changes, this would require solutions to issues of food, shelter, and medical support due to the loss of numerous lives and the destruction of infrastructure. On the other hand, the UNHCR model was analyzed to determine the implications of expanding mental well prepared and sufficiently qualified professionals, reorganizing standard organizations within complex situations, task direction, preparing sufficient relief goods, budgeting, securing bases in border areas with North Korea, and establishing networks for sponsorship. Based on this, eight detailed tasks in the field of system construction could be used by the operators of the Three Major Works to prepare for unification. Additionally, nine tasks for review were presented in consideration of the timing of unification and the current situation between South and North Korea. In conclusion, in the event of unification, the Three Major Works should not be neglected during the transition period. The manual "Three Major Works during the Unification Period" should include strategic points on organizational formation and mission implementation, forward base and base operation, security and logistics preparation, public relations and external cooperation, safety measures, and transportation and contact systems.

A Study on Major Safety Problems and Improvement Measures of Personal Mobility (개인형 이동장치의 안전 주요 문제점 및 개선방안 연구)

  • Kang, Seung Shik;Kang, Seong Kyung
    • Journal of the Society of Disaster Information
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    • v.18 no.1
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    • pp.202-217
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    • 2022
  • Purpose: The recent increased use of Personal Mobility (PM) has been accompanied by a rise in the annual number of accidents. Accordingly, the safety requirements for PM use are being strengthened, but the laws/systems, infrastructure, and management systems remain insufficient for fostering a safe environment. Therefore, this study comprehensively searches the main problems and improvement methods through a review of previous studies that are related to PM. Then the priorities according to the importance of the improvement methods are presented through the Delphi survey. Method: The research method is mainly composed of a literature study and an expert survey (Delphi survey). Prior research and improvement cases (local governments, government departments, companies, etc.) are reviewed to derive problems and improvements, and a problem/improvement classification table is created based on keywords. Based on the classification contents, an expert survey is conducted to derive a priority improvement plan. Result: The PM-related problems were in 'non-compliance with traffic laws, lack of knowledge, inexperienced operation, and lack of safety awareness' in relation to human factors, and 'device characteristics, road-drivable space, road facilities, parking facilities' in relation to physical factors. 'Management/supervision, product management, user management, education/training' as administrative factors and legal factors are divided into 'absence/sufficiency of law, confusion/duplication, reduced effectiveness'. Improvement tasks related to this include 'PM education/public relations, parking/return, road improvement, PM registration/management, insurance, safety standards, traffic standards, PM device safety, PM supplementary facilities, enforcement/management, dedicated organization, service providers, management system, and related laws/institutional improvement', and 42 detailed tasks are derived for these 14 core tasks. The results for the importance evaluation of detailed tasks show that the tasks with a high overall average for the evaluation items of cost, time, effect, urgency, and feasibility were 'strengthening crackdown/instruction activities, education publicity/campaign, truancy PM management, and clarification of traffic rules'. Conclusion: The PM market is experiencing gradual growth based on shared services and a safe environment for PM use must be ensured along with industrial revitalization. In this respect, this study seeks out the major problems and improvement plans related to PM from a comprehensive point of view and prioritizes the necessary improvement measures. Therefore, it can serve as a basis of data for future policy establishment. In the future, in-depth data supplementation will be required for each key improvement area for practical policy application.

Utilizing the Idle Railway Sites: A Proposal for the Location of Solar Power Plants Using Cluster Analysis (철도 유휴부지 활용방안: 군집분석을 활용한 태양광발전 입지 제안)

  • Eunkyung Kang;Seonuk Yang;Jiyoon Kwon;Sung-Byung Yang
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.79-105
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    • 2023
  • Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.

A Study on Human-Robot Interaction Trends Using BERTopic (BERTopic을 활용한 인간-로봇 상호작용 동향 연구)

  • Jeonghun Kim;Kee-Young Kwahk
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.185-209
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    • 2023
  • With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.

A Study on the Linkage and Development of the BRM Based National Tasks and the Policy Information Contents (BRM기반 국정과제와 정책정보콘텐츠 연계 및 구축방안에 관한 연구)

  • Younghee, Noh;Inho, Chang;Hyojung, Sim;Woojung, Kwak
    • Journal of the Korean Society for information Management
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    • v.39 no.4
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    • pp.191-213
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    • 2022
  • With a view to providing a high-quality policy information service beyond the existing national task service of the national policy information portal (POINT) of the National Library of Korea Sejong, it would be necessary to effectively provide the policy data needed for the implementation of the new national tasks. Accordingly, in this study, an attempt has been made to find a way to connect and develop the BRM-based national tasks and the policy information contents. Towards this end, first, the types of national tasks and the contents of each field and area of the government function's classification system were analyzed, with a focus placed on the 120 national tasks of the new administration. Furthermore, by comparing and analyzing the national tasks of the previous administration and the current information, the contents ought to be reflected for the development of contents related to the national tasks identified. Second, the method for linking and collecting the policy information was sought based on the analysis of the current status of policy information and the national information portal. As a result of the study, first, examining the 1st stage BRM of the national tasks, it turned out that there were 21 tasks for social welfare, 14 for unification and diplomacy, 17 for small and medium-sized businesses in industry and trade, 12 for general public administration, 8 for the economy, taxation and finance, 6 for culture, sports and tourism, science and technology, and education each, 5 for communication, public order and safety each, 4 for health, transportation and logistics, and environment each, 3 for agriculture and forestry, 2 for national defense and regional development each, and 1 for maritime and fisheries each, among others. As for the new administration, it is apparent that science technology and IT are important, and hence, it is necessary to consider such when developing the information services for the core national tasks. Second, to link the database with external organizations, it would be necessary to form a linked operation council, link and collect the information on the national tasks, and link and provide the national task-related information for the POINTs.

Analysis of Tourism Popularity Using T-map Search andSome Trend Data: Focusing on Chuncheon-city, Gangwon-province (T맵 검색지와 썸트랜드 데이터를 이용한 관광인기도분석: 강원도 춘천을 중심으로)

  • TaeWoo Kim;JaeHee Cho
    • Journal of Service Research and Studies
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    • v.12 no.1
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    • pp.25-35
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    • 2022
  • Covid-19, of which the first patient in Korea occurred in January 2020, has affected various fields. Of these, the tourism sector might havebeen hit the hardest. In particular, since tourism-based industrial structure forms the basis of the region, Gangwon-province, and the tourism industry is the main source of income for small businesses and small enterprises, the damage is great. To check the situation and extent of such damage, targeting the Chuncheon region, where public access is the most convenient among the Gangwon regions, one-day tours are possible using public transportation from Seoul and the metropolitan area, with a general image that low expense tourism is recognized as possible, this study conducted empirical analysis through data analysis. For this, the general status of the region was checked based on the visitor data of Chuncheon city provided by the tourist information system, and to check the levels ofinterest in 2019, before Covid-19, and in 2020, after Covid-19, by comparing keywords collected from the web service sometrend of Vibe Company Inc., a company specializing in keyword collection, with SK Telecom's T-map search site data, which in parallel provides in-vehicle navigation service and communication service, this study analyzed the general regional image of Chuncheon-city. In addition, by comparing data from two years by developing a tourism popularity index applying keywords and T-map search site data, this study examined how much the Covid-19 situation affected the level of interest of visitors to the Chuncheon area leading to actual visits using a data analysis approach. According to the results of big data analysis applying the tourism popularity index after designing the data mart, this study confirmed that the effect of the Covid-19 situation on tourism popularity in Chuncheon-city, Gangwon-provincewas not significant, and confirmed the image of tourist destinations based on the regional characteristics of the region. It is hoped that the results of this research and analysis can be used as useful reference data for tourism economic policy making.

Ammonia Decomposition over Ni Catalysts Supported on Zeolites for Clean Hydrogen Production (청정수소 생산을 위한 암모니아 분해 반응에서 Ni/Zeolite 촉매의 반응활성에 관한 연구)

  • Jiyu Kim;Kyoung Deok Kim;Unho Jung;Yongha Park;Ki Bong Lee;Kee Young Koo
    • Journal of the Korean Institute of Gas
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    • v.27 no.3
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    • pp.19-26
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    • 2023
  • Hydrogen, a clean energy source free of COx emissions, is poised to replace fossil fuels, with its usage on the rise. Despite its high energy content per unit mass, hydrogen faces limitations in storage and transportation due to its low storage density and challenges in long-term storage. In contrast, ammonia offers a high storage capacity per unit volume and is relatively easy to liquefy, making it an attractive option for storing and transporting large volumes of hydrogen. While NH3 decomposition is an endothermic reaction, achieving excellent low-temperature catalytic activity is essential for process efficiency and cost-effectiveness. The study examined the effects of different zeolite types (5A, NaY, ZSM5) on NH3 decomposition activity, considering differences in pore structure, cations, and Si/Al-ratio. Notably, the 5A zeolite facilitated the high dispersion of Ni across the surface, inside pores, and within the structure. Its low Si/Al ratio contributed to abundant acidity, enhancing ammonia adsorption. Additionally, the presence of Na and Ca cations in the support created medium basic sites that improved N2 desorption rates. As a result, among the prepared catalysts, the 15 wt%Ni/5A catalyst exhibited the highest NH3 conversion and a high H2 formation rate of 23.5 mmol/gcat·min (30,000 mL/gcat·h, 600 ℃). This performance was attributed to the strong metal-support interaction and the enhancement of N2 desorption rates through the presence of medium basic sites.

Analysis and Implication on the International Regulations related to Unmanned Aircraft -with emphasis on ICAO, U.S.A., Germany, Australia- (세계 무인항공기 운용 관련 규제 분석과 시사점 - ICAO, 미국, 독일, 호주를 중심으로 -)

  • Kim, Dong-Uk;Kim, Ji-Hoon;Kim, Sung-Mi;Kwon, Ky-Beom
    • The Korean Journal of Air & Space Law and Policy
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    • v.32 no.1
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    • pp.225-285
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    • 2017
  • In regard to the regulations related to the RPA(Remotely Piloted Aircraft), which is sometimes called in other countries as UA(Unmanned Aircraft), ICAO stipulates the regulations in the 'RPAS manual (2015)' in detail based on the 'Chicago Convention' in 1944, and enacts provisions for the Rules of UAS or RPAS. Other contries stipulates them such as the Federal Airline Rules (14 CFR), Public Law (112-95) in the United States, the Air Transport Act, Air Transport Order, Air Transport Authorization Order (through revision in "Regulations to operating Rules on unmanned aerial System") based on EASA Regulation (EC) No.216/2008 in the case of unmanned aircaft under 150kg in Germany, and Civil Aviation Act (CAA 1998), Civil Aviation Act 101 (CASR Part 101) in Australia. Commonly, these laws exclude the model aircraft for leisure purpose and require pilots on the ground, not onboard aricraft, capable of controlling RPA. The laws also require that all managements necessary to operate RPA and pilots safely and efficiently under the structure of the unmanned aircraft system within the scope of the regulations. Each country classifies the RPA as an aircraft less than 25kg. Australia and Germany further break down the RPA at a lower weight. ICAO stipulates all general aviation operations, including commercial operation, in accordance with Annex 6 of the Chicago Convention, and it also applies to RPAs operations. However, passenger transportation using RPAs is excluded. If the operational scope of the RPAs includes the airspace of another country, the special permission of the relevant country shall be required 7 days before the flight date with detail flight plan submitted. In accordance with Federal Aviation Regulation 107 in the United States, a small non-leisure RPA may be operated within line-of-sight of a responsible navigator or observer during the day in the speed range up to 161 km/hr (87 knots) and to the height up to 122 m (400 ft) from surface or water. RPA must yield flight path to other aircraft, and is prohibited to load dangerous materials or to operate more than two RPAs at the same time. In Germany, the regulations on UAS except for leisure and sports provide duty to avoidance of airborne collisions and other provisions related to ground safety and individual privacy. Although commercial UAS of 5 kg or less can be freely operated without approval by relaxing the existing regulatory requirements, all the UAS regardless of the weight must be operated below an altitude of 100 meters with continuous monitoring and pilot control. Australia was the first country to regulate unmanned aircraft in 2001, and its regulations have impacts on the unmanned aircraft laws of ICAO, FAA, and EASA. In order to improve the utiliity of unmanned aircraft which is considered to be low risk, the regulation conditions were relaxed through the revision in 2016 by adding the concept "Excluded RPA". In the case of excluded RPA, it can be operated without special permission even for commercial purpose. Furthermore, disscussions on a new standard manual is being conducted for further flexibility of the current regulations.

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DEVELOPMENT OF STATEWIDE TRUCK TRAFFIC FORECASTING METHOD BY USING LIMITED O-D SURVEY DATA (한정된 O-D조사자료를 이용한 주 전체의 트럭교통예측방법 개발)

  • 박만배
    • 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.

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Influence analysis of Internet buzz to corporate performance : Individual stock price prediction using sentiment analysis of online news (온라인 언급이 기업 성과에 미치는 영향 분석 : 뉴스 감성분석을 통한 기업별 주가 예측)

  • Jeong, Ji Seon;Kim, Dong Sung;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.37-51
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    • 2015
  • Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.