Abstract: The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system. The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.
Abstract: Truck-involved crashes have higher crash severity than non-truck-involved crashes. There have been many studies about the frequency of crashes and the development of severity models, but those studies only analyzed the relationship between observed variables. To identify why more people are injured or killed when trucks are involved in the crash, we must examine to quantify the complex causal relationship between severity of the crash and risk factors by adopting the latent factors of crashes. The aim of this study was to develop a structural equation or model based on truck-involved and non-truck-involved crashes, including five latent variables, i.e. a crash factor, environmental factor, road factor, driver’s factor, and severity factor. To clarify the unique characteristics of truck-involved crashes compared to non-truck-involved crashes, a confirmatory analysis method was used. To develop the model, we extracted crash data from 10,083 crashes on Korean freeways from 2008 through 2014. The results showed that the most significant variable affecting the severity of a crash is the crash factor, which can be expressed by the location, cause, and type of the crash. For non-truck-involved crashes, the crash and environment factors increase severity of the crash; conversely, the road and driver factors tend to reduce severity of the crash. For truck-involved crashes, the driver factor has a significant effect on severity of the crash although its effect is slightly less than the crash factor. The multiple group analysis employed to analyze the differences between the heterogeneous groups of drivers.
Abstract: Mobile augmented reality (MAR) tracking targets from the surroundings and aids operators for interactive data and procedures visualization, potential equipment and system understandably. Operators remotely communicate and coordinate with each other for the continuous tasks, information and data exchange between control room and work-site. In the routine work, distributed control system (DCS) monitoring and work-site manipulation require operators interact in real-time manners. The critical question is the improvement of user experience in cooperative works through applying Augmented Reality in the traditional industrial field. The purpose of this exploratory study is to find the cognitive model for the multiple task performance by MAR. In particular, the focus will be on the comparison between different tasks and environment factors which influence information processing. Three experiments use interface and interaction design, the content of start-up, maintenance and stop embedded in the mobile application. With the evaluation criteria of time demands and human errors, and analysis of the mental process and the behavior action during the multiple tasks, heuristic evaluation was used to find the operators performance with different situation factors, and record the information processing in recognition, interpretation, judgment and reasoning. The research will find the functional properties of MAR and constrain the development of the cognitive model. Conclusions can be drawn that suggest MAR is easy to use and useful for operators in the remote collaborative works.
Abstract: The purpose of this research was to identify factors
that influenced the success of e-commerce implementation within
SMEs businesses. In order to achieve the objectives of this research,
the researcher collected data from random firms in Thailand, both the
users and those who are not using the e-commerce. The data was
comprised of the results of 310 questionnaires, as well as 10
interviews with owner/managers of businesses who are currently
using e-commerce successfully. The data were analyzed by using
descriptive statistics, which included frequency, percentages, mean,
and the standard deviation of pertinent factors. Independent t-test and
one-way ANOVA test were also used. The findings of this research
revealed that 50% of all the firms surveyed had e-commerce website,
whereas, over 20% of all firms surveyed had developing an ecommerce
strategy. The result findings also indicate that
organizational factors, technological factors and environment factors
as significant factors effecting success of e-commerce
implementation in SMEs. From the hypotheses testing, the findings
revealed that the different level of support use ecommerce by
owner/manager had different success in e-commerce implementation.
Moreover, the difference in e-commerce management approach
affected the success in terms of higher total sales for the business or
higher number of retained or returning customers.
Abstract: This research aimed to study form of traffic distribution and environmental factors of road that affect traffic accidents in Dusit District, only areas responsible of Samsen Police Station. Data used in this analysis is the secondary data of traffic accident case from year 2011. Observed area units are 15 traffic lines that are under responsible of Samsen Police Station. Technique and method used are the Cartographic Method, the Correlation Analysis, and the Multiple Regression Analysis. The results of form of traffic accidents show that, the Samsen Road area had most traffic accidents (24.29%), second was Rachvithi Road(18.10%), third was Sukhothai Road (15.71%), fourth was Rachasrima Road (12.38%), and fifth was Amnuaysongkram Road(7.62%). The result from Dusit District, onlyareasresponsibleofSamsen police station, has suggested that the scale of accidents have high positive correlation with statistic significant at level 0.05 and the frequency of travel (r=0.857). Traffic intersection point (r=0.763)and traffic control equipments (r=0.713) are relevant factors respectively. By using the Multiple Regression Analysis, travel frequency is the only one that has considerable influences on traffic accidents in Dusit district only Samsen Police Station area. Also, a factor in frequency of travel can explain the change in traffic accidents scale to 73.40 (R2 = 0.734). By using the Multiple regression summation from analysis was Ŷ=-7.977+0.044X6
Abstract: This contribution examines the relationship between the family environment and the level of young pupils’ scholastic success. It comments on the partial results of a research probe carried out in the year 2012 on a sample of 412 Czech Republic primary school pupils of the fourth, fifth and sixths forms within the Project IGA 43 201 15 0004 01. The key links of this project were monitored in relation to the highest education level achieved by the learners´ parents, as well as to the type of family it is (in particular its ability to function), to component factors specific to the family climate (their willingness to share information, communication, parental control) and, finally, to the number of children in the family as an important socialization constituent.
Abstract: In social network analysis the mean nodal degree and
density of the graph can be considered as a measure of the activity of
all actors in the network and this is an important property of a graph
and for making comparisons among networks. Since subjects in a
family or organization are subject to common environment factors, it
is prime interest to study the association between responses.
Therefore, we study the distribution of the mean nodal degree and
density of the graph under correlated binary units. The cross product
ratio is used to capture the intra-units association among subjects.
Computer program and an application are given to show the benefits
of the method.
Abstract: The aim of this paper is to examine factors related to system environment (namely, system quality and vendor support) that influences ERP implementation success in Iranian companies. Implementation success is identified using user satisfaction and organizational impact perspective. The study adopts the survey questionnaire approach to collect empirical data. The questionnaire was distributed to ERP users and a total of 384 responses were used for analysis. The results illustrated that both system quality and vendor support have significant effect on ERP implementation success. This implies that companies must ensure they source for the best available system and a vendor that is dependable, reliable and trustworthy.
Abstract: Macrobenthos distribution along the coastal waters of
Penang National Park was studid to estimate the effect of different
environmental parameters at three stations, during six sampling
months, from June 2010 to April 2011. The aim of this survey was to
investigate different environment stress over soft bottom polychaete
community along Teluk Ketapang and Pantai Acheh (Penang
National Park) over a year period. Variations in the polychaete
community were evaluated using univariate and multivariate
methods. A total of 604 individuals were examined which was
grouped into 23 families. Family Nereidae was the most abundant
(22.68%), followed by Spionidae (22.02%), Hesionidae (12.58%),
Nephtylidae (9.27%) and Orbiniidae (8.61%). It is noticeable that
good results can only be obtained on the basis of good taxonomic
resolution. The maximum Shannon-Wiener diversity (H'=2.16) was
recorded at distance 200m and 1200m (August 2010) in Teluk
Ketapang and lowest value of diversity was found at distance 1200m
(December 2010) in Teluk Ketapang.