The Journal of Informational Technology and Applications (JITA) is a scientific journal with an international reach. Its primary goal is to share new ideas, knowledge, and experiences that contribute the development of an information society based on knowledge.Our vision is to become a leading journal that publishes groundbreaking research that advances scientific progress. We invite you to collaborate by submitting original research works related to emerging issues in your field that align with our editorial policies.The journal is published twice a year, in June and December. The deadline for the June issue is April 15th; for the December issue, it is October 15th. After a blind review and evaluation process, authors will be notified of the publishing decision.
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Road Traffic Accidents (RTAs) are a major public concern, resulting in an estimated 1.2 million deaths and 50 million injuries worldwide each year. In the developing world, RTAs are among the leading cause of death and injury. Most of the analysis of road accident uses data mining techniques which provide productive results. The analysis of the accident locations can help in identifying certain road accident features that make a road accident to occur frequently in the locations. Association rule mining is one of the popular data mining techniques that identify the correlation in various attributes of road accident. Data analysis has the capability to identify different reasons behind road accidents. In the existing system, k-means algorithm is applied to group the accident locations into three clusters. Then the association rule mining is used to characterize the locations. Most state of the art traffic management and information systems focus on data analysis and very few have been done in the sense of classification. So, the proposed system uses classification technique to predict the severity of the accident which will bring out the factors behind road accidents that occurred and a predictive model is constructed using fuzzy logic to predict the location wise accident frequency.
The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.
The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.
bum@apeiron-edu.eu
+387 (0)51 247 972
Pan European University APEIRON Banja Luka BUM Pere Krece 13, P.O.Box 51 78102 Banja Luka, Republic of Srpska Bosnia and Hercegovina
© 2024 Paneuropean University Apeiron All Rights Reserved
bum@apeiron-edu.eu
+387 (0)51 247 972
Pan European University APEIRON Banja Luka BUM Pere Krece 13, P.O.Box 51 78102 Banja Luka, Republic of Srpska Bosnia and Hercegovina
© 2024 Paneuropean University Apeiron All Rights Reserved
Pan European University APEIRON Banja Luka BUM Pere Krece 13, P.O.Box 51 78102 Banja Luka, Republic of Srpska Bosnia and Hercegovina
bum@apeiron-edu.eu
+387 (0)51 247 972
© 2024 Paneuropean University Apeiron All Rights Reserved