<abstract xmlns="http://www.w3.org/1999/xhtml">

Research into lowering the temperature during the production and installation of hot asphalt has been going on for a long time. In addition to developing appropriate recipes, it is important to gain experience, particularly in asphalt paving technology, since in addition to the behavior of the different asphalt mixtures during their compaction, external factors such as the location of the project and weather conditions also play an important role. The testing of the low-temperature asphalt on the federal highway B 169 was carried out successfully. Due to the high pre-compaction by the paver screed, the required compaction values were achieved on the binder course with 4 rolling passes and on the surface course with 3 rolling passes. The viscosity-changing additives and the selected rolling technology had a positive influence on the results. However, precise measurement results for compaction could not be achieved using the PQI probe.
</abstract>

Paving Low-Temperature Asphalt on the B 169 Highway Near Heyda

<abstract xmlns="http://www.w3.org/1999/xhtml">

The purpose of this article is to illustrate the intuitively understood links between the social and economic characteristics of an area and the waste production at a given location. These relationships have been investigated using statistical data from thirteen regions in the Czech Republic between 2019 and 2021. In order to evaluate the data, freely available tools such as Python 3.8.16 and a number of its libraries, e.g. matplotlib, plotly, sklearn, numpy and others, have been used.
</abstract>

Comparison of Waste Production in Regions of the Czech Republic in 2019-2021

<abstract xmlns="http://www.w3.org/1999/xhtml">

Ensuring public safety on our roads is a top priority, and the prevalence of road accidents is a major concern. Fortunately, advances in machine learning allow us to use data to predict and prevent such incidents. Our study delves into the development and implementation of machine learning techniques for predicting road accidents, using rich datasets from Catalonia and Toronto Fatal Collision. Our comprehensive research reveals that ensemble learning methods outperform other models in most prediction tasks, while Decision Tree and K-NN exhibit poor performance. Additionally, our findings highlight the complexity involved in predicting various aspects of crashes, as the Stacking Regressor shows variability in its performance across different target variables. Overall, our study provides valuable insights that can significantly contribute to ongoing efforts to reduce accidents and their consequences by enabling more accurate predictions.
</abstract>

Batna 2 University, Faculty of Technology

Laboratory of Automation and Manufacturing, Industrial Engineering Department

University of Putra Malaysia, Faculty of Engineering

Department of Chemical and Environmental Engineering, Safety Engineering Interest Group

Department of Construction, Installations and Structures

Machine Learning Techniques for Fatal Accident Prediction

Volume 30 (2024): Issue 1 (March 2024)

Volume 29 (2023): Issue 3 (December 2023) Social Sciences

Volume 29 (2023): Issue 2 (June 2023) Science of Economics

Volume 29 (2023): Issue 1 (March 2023)

ACC JOURNAL

The ACC JOURNAL is an international scientific journal that came into existence in 2009. The Technical University of Liberec publishes it Four universities (Technical University of Liberec, Czechia; Technical University Dresden – International Institute Zittau, Germany; University of Applied Sciences Zittau/Görlitz, Germany; Wroclaw University of Economics and Business, Poland) have joined in the Academic Coordination Centre Nisa (ACC) participate in its production. There are usually three issues per year. The ACC JOURNAL is a periodical publishing original reviewed scientific papers, scientific studies, papers presented at conferences and summaries of findings of research projects. The first issue contains contributions focused on natural sciences and technology, the second one is focused on the science of economics and the third one on social sciences. ACC JOURNAL is a reviewed one. It is built upon the tradition of the “Scientific Treaties” published between 1995 and 2008. The journal is registered in international databases: INDEX COPERNICUS INTERNATIONAL, ERIH PLUS, ROAD Directory of Open Access Scholarly Resources and DOAJ Directory of Open Access Journals. Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process. 

ACC JOURNAL

Volume 30 (2024): Issue 1 (March 2024)

Paving Low-Temperature Asphalt on the B 169 Highway Near Heyda

Comparison of Waste Production in Regions of the Czech Republic in 2019-2021

Machine Learning Techniques for Fatal Accident Prediction

Wyszukiwanie

Wszystkie tomy i zeszyty w tym czasopiśmie