Carptahian Journal of Electronic and Computer Engineering

4

Authors: I. Orha, S. Oniga

The aim of this paper is to present the implementation of an activity recognition system based on a data acquisition system with inertial sensors. One of the requirement of data acquisition systems used in human activity recognition is their level of acceptability or their level of obstruction [2, 4]. Starting from this important requirement, we designed a few wearable data acquisition systems using inertial sensors. The idea from which we started, takes into account the need to obtain more complete information about the studied human subject, in complex activities recognition systems. In our experiment we used inertial sensor built into so called “9DOF inertial module”. Our systems contain, on the wearable side, a maximum of three inertial sensors, a microcontroller module, and a communication module which can be one of the three solutions. For data reception, on the fixed part of the system, we have a communication module corresponding to the one on wearable parts and a microcontroller module connected to a PC through a serial port. For activity recognition, data files are transferred to a PC, and data is processed in Matlab using artificial neural networks as classifier. The networks have been configured according to the number of sensors that acquired data and the number of activities that we want to recognize.

4

Authors: Mihaela Osaci, Adela Berdie, Iulia Andrea, Iohana Varadi

The paper presents a monitoring solution for flow measurement through Web Dynpro ABAP interface. The use of integrated software systems in companies currently represents an essential condition for providing higher and more reliable access to information resources. The SAP Netweaver, a multilingual & multitasking system based on the three-tier client-server technology, is one of the mostly used integrated platforms implemented in companies.

4

Authors: Ján Tóth, Ľuboš Ovseník, Ján Turán

This paper deals with advanced Free Space Optics communication technology. Two FSO nodes are needed in order to make a connection. Laser diodes are used as light sources. Simple OOK modulation is involved in this technology. FSO system offers multiple advantages indeed. However, a direct visibility is required in order to set up a communication link. This fact yields perhaps the most significant weakness of this technology. Obviously, there is no a chance to fight the weather phenomena like fog, heavy rain, dust and many other particles which are naturally present in the atmosphere. That’s why there is a key task to find a suitable solution to keep FSO link working with high reliability and availability. It turns out that it’s necessary to have knowledge about weather situation when FSO link operates (liquid water content - LWC, geographical location, particle size distribution, average particle diameter, temperature, humidity, wind conditions, pressure and many other variable weather parameters. It’s obvious that having most of mentioned parameter’s values stored in database (implicitly in charts) would be really beneficial. This paper presents some of mentioned indicators continuously gathered from several sensors located close to one of FSO nodes.

6

Authors: Moloud Abdar

Statistics from the World Health Organization (WHO) shows that heart disease is one of the leading causes of mortality all over the world. Because of the importance of heart disease, in recent years, many studies have been conducted on this disease using data mining. The main objective of this study is to find a better decision tree algorithm and then use the algorithm for extracting rules in predicting heart disease. Cleveland data, including 303 records are used for this study. These data include 13 features and we have categorized them into five classes. In this paper, C5.0 algorithm with a accuracy value of 85.33% has a better performance compared to the rest of the algorithms used in this study. Considering the rules created by this algorithm, the attributes of Trestbps, Restecg, Thalach, Slope, Oldpeak, and CP were extracted as the most influential causes in predicting heart disease.