Time Series Forecasting of the Austrian Traded Index (ATX) Using Artificial Neural Network Model

This paper analyses the Austrian Traded Index (ATX) of the Vienna Stock Exchange (Wiener Börse) in the period from 2009 to 2017, using the method of the artificial neural network (ANN). Sampling data are taken from the web page of the Wiener Börse and filtered on weekly basis to comply with weekly seasonality in eight years range. The aim is to construct several AAN models that meet certain criteria and evaluate them on the holdout subsample. Furthermore, the goal is to find the best model that can predict new upcoming yet unseen data with high accuracy. A data frame for testing forecasting performance is one month, a quartile, a half year, and one year period for which last year of the data sample is retained (August, 2016- August 2017). Using various criteria and different parameters, the total of thirty networks were built and tested and top five networks were analysed in more details. Results confirm high accuracy of using method of artificial neural networks, which is consistent to studies conducted on similar cases. Correlation of top three selected networks by validation subsample is over 0,9. The mean absolute percentage errors (MAPE) for the best selected network are 1,76% (month); 2,11% (quartile); 2,21% (half-year); 2,13% (year). Once again, ANN method has proven to be a powerful forecasting tool

Low Power Strain Gage Measurement with Wireless Network Access

This paper describes a measurement system for industry applications where the weight has to be monitored in a flexible way. The measurement system can be used to build several kinds of weight cell applications in which the low power sensor is battery powered and able to communicate with a master unit through a wireless network. The system requirements are described and all blocks derived from these requirements are presented. The implementation of the wireless network includes a peer-to-peer connection between multiple measurement units with the master unit by using just one communication channel

Initial Study on the State of the Art Solutions for the Simulation of the Thermoregulatory Sweating Conditions

The paper presents an initial study and basic research of the state of the art systems and solutions for the simulation of the thermoregulatory sweating conditions. The simulation of the thermoregulatory sweating conditions has been treated by many researchers, and has become over the years a major area of interest for many industries (e.g. textile, protective garments, aeronautics, automotive industries and sports). The objective of this paper is to reflect and analyse the existing literature, for this purpose. Three existing systems and two thermoregulatory models will be characterized and critically discussed. The findings support the methodology for future applied scientific research (PhD thesis), which will use existing scientific knowledge to develop a practical application using suitable technology

Initial Study on the State of the Art Solutions for the Simulation of the Thermoregulatory Sweating Conditions

The paper presents an initial study and basic research of the state of the art systems and solutions for the simulation of the thermoregulatory sweating conditions. The simulation of the thermoregulatory sweating conditions has been treated by many researchers, and has become over the years a major area of interest for many industries (e.g. textile, protective garments, aeronautics, automotive industries and sports). The objective of this paper is to reflect and analyse the existing literature, for this purpose. Three existing systems and two thermoregulatory models will be characterized and critically discussed. The findings support the methodology for future applied scientific research (PhD thesis), which will use existing scientific knowledge to develop a practical application using suitable technology

TASKRADAR: TASK VISUALISATION AND MONITORING WITHIN AUTOMOTIVE PRODUCT DEVELOPMENT LIFECYCLE USING SEMANTIC TECHNOLOGIES

Project management within the automotive production in specific departments is still done separately and does not interact with engineering process. Our work aims on providing flexible data insights on collaboration tasks within such environments. We apply semantic technologies RDF, OWL and SPARQL with a specific domain related ontology PROTARES (PROject TAsks RESources) to interlink, describe and query domain knowledge. As proof of concept we are introducing an experimental visualisation interface called TaskRadar. Our application resides on domain ontology and allows knowledge based browsing and visualisation of tasks in development process. With this example we want to show, how semantically driven customized views can support monitoring and reflection as well as decision-making within the early phases of the automotive product lifecycle

Student Performance on an E-Learning Platform: Mixed Method Approach

E-learning is considered a leading application of digital technologies in educational systems. The aim of the paper is to explore the utilization and impact of digital technologies on an e-learning platform. For this purpose, research was conducted at the Moodle learning management system. Data from the e-learning platform were empirically evaluated in order to find key indicators of student performance in different courses. Student success with the e-learning system was evaluated using a mixed-method: Social Network Analysis, K-Means Clustering, and Multiple Linear Regression. The research was conducted at the University of Novi Sad, Faculty of Technical Sciences, Serbia. The results indicate a significant relationship between the performance of students and the use of digital educational resources from the e-learning platform

Sweat glands module with integrated sensors designed for Additive Manufacturing

Lead by the results of our previous work, in which we designed the sweat glands prototype according to AM (Advanced Manufacturing) requirements, in this study we aimed to integrate the previously manufactured channels into a stereolithography (SLA)-manufactured module, in order to avoid support structures inside the channels and the model cavities. That was achieved by distributing the channels in the manner which approximates the sweat glands distribution on an equivalent real body part and to be able toadjust the sweat quantity, to the estimated sweat rates found in the literature. The manufactured module has integrated humidity and temperature sensors, which will allow an accurate quantitative assessmentof the thermoregulation of the individual modules and the sweat glands prototype as a whole