Adina Astilean

Near real-time monitoring of the ionosphere using dual frequency GPS data in a Kalman filter approach

The ionosphere is an important source of errors for the GPS signals that travel through the ionosphere on their way to the ground-based receivers by introducing a frequency dependent path delay proportional to the total electron content (TEC) along the signal path. For dual-frequency GPS receivers, the ionospheric effects can be accounted for by taking advantage of the dispersive nature of the ionosphere in the microwave region of the electromagnetic spectrum, while for the single frequency GPS receivers the ionospheric effects can be minimized by modeling them using, for example, empirical or physics-based ionospheric models. On the other hand, the errors imposed by the ionosphere on the GPS signals can provide important temporal and spatial information about the electron density distribution in the ionosphere. Besides the ionospheric errors, there are some other sources of errors that can affect the GPS signals, such as the satellite and receiver instrumental biases, carrier phase ambiguities, multipath effects, clock errors, orbital errors, tropospheric errors, but which can be compensated for, estimated, or neglected depending on the particular application. In this paper, we are only concerned with the ionospheric effects on the GPS signals, and describe a Kalman filter-based algorithm for near real-time estimation of the line-of-sight and vertical ionospheric TEC and of the combined satellite and receiver instrumental biases, using data from dual-frequency GPS receivers.

E-health decision support system for differential diagnosis

A new experimental system, capable to use the combined facilities offered by mobile communications, cloud computing and artificial intelligence, to assist the professional formation and specialization of medical staff and to offer up to date information for differential diagnosis, is proposed. To demonstrate the feasibility of the proposed approach, a proof-of-concept system was developed. An application in which two expert systems are used for the differential diagnosis of hypertension is presented. These systems aim to facilitate the diagnosis process of primary, endocrine and renal hypertension. A Naive Bayes Classifier and a Fuzzy Inference System were designed and implemented in order to differentiate the presented types of hypertension. The application was designed based on the client-server architecture, using Cloud Computing techniques and Android programming. The system take as inputs the preliminary medical information and investigation results that are sent from the Android client and outputs the precise risk of having a certain type of hypertension.

Acoustic noise pollution monitoring in an urban environment using a VANET network

The main objective of this work is the development of a Vehicle Ad Hoc NETwork (VANET) to collect data from GPS equipped mobile phones used as noise detectors. In this system, sensor nodes perioadically transmit acoustic noise levels to neighboring cars, data packets being shared and temporary stored by participating VANET nodes and ultimately forwarded to a collector node connected to the Internet, providing public real-time data. A routing technique called MP-OLSR that takes into account the spatially separation between the multiple paths is used, for better transmission reliability and congestion avoidance as well as for control message overhead minimization.

Fingerprint recognition distributed system

The paper proposes a distributed identification and verification system which integrates fingerprint recognition and Global Positioning System methods. The system is composed of a number of mobile fingerprinting terminals which communicate with data processing units using GSM\GPRS technology. The motivation for integrating GPS technology in an identification system is to add a supplementary security level by granting access based on area localization. In order to further increase the system security a cryptographic module is used to encrypt / decrypt messages passed between the distributed components. The system architecture is presented and main modules are described.

Train Traffic Control Based on Distributed Resource Allocation

Abstract The railway traffic is characterized as a large and dynamic system with uncertain properties related to resource loading, train arrivals and failures. Despite these uncertainties, the control system is expected to guarantee that all the trains behave according to their timelines. The current approach solves the railway traffic control problem using the resource allocation. The trains are considered tasks with specified temporal behaviors that have to fulfill their deadlines. The solutions based on open loop, closed loop with independent, coordinated and heterarchical controllers are defined and compared. The control signals are implemented and verified using time Petri nets. Some algorithms for control system implementation are given. The method evaluations are performed using the meter functions: utility, utilization, reservation and efficiency. The results obtained through simulations show that the proposed distributed controllers solve adequately the control problems and can be used for large scale implementation.

Formal Analysis of an Urban Road Traffic Model

The paper proposes a method based on timed automata to validate different road traffic control scenarios. In order to estimate the current traffic state, a strategy in which a special attention was given to information collected from the streets converging to main crossroads was elaborated. Then, the up to dated information was used by a complex road traffic model to improve the traffic flow. The validation and verification of the road traffic model was realized using UPPAAL model-checker. A representative area of Cluj Napoca city center was modeled and simulated in order to determine the right parameters for traffic control. The proposed model, validated in UPPAAL, can be extended to any road structure for analysis purposes.

Complex automation system of a low power hydroplant

Based on the new latest generation programmable automata possibilities, this work presents the main aspects of implementing them, to achieve a complex automation system of a small power hydro plant (SAC-HmP). This work presents the SAC-HmP model and the results of the system implemented at C.H.E.M.P. Budac 1 and C.H.E.M.P. Bolovanu (Bistrita hydrographic basin).

Ant routing protocol in a ZigBee ad hoc sensors network for radiation level monitoring

A low cost ad-hoc sensors network for the monitoring of the radiation level of contaminated and risk areas is proposed in the presented paper. An experimental system which collects and sends radiation level data from a mining area to a server was implemented. The presented approach is based on the detecting of the gamma radiation levels using ZigBee sensors which become active only when a level of radiation is exceeded and are suitable to detect and transmit data to the nearby network nodes only on demand, reducing the power consumption. To solve the routing problem in the ad-hoc network, a solution based on Ant algorithm was chosen.

Multiagent technology for an Urban Road Traffic Advisor

This paper proposes generic multi-agent system architecture for an urban driving advisory system. This architecture is described as composed of basic role-oriented processes communicating though primitive interaction protocols. The architecture is aimed to provide an enabling communications framework upon which multi-agent system models can be organized and built to be used for an simulation of an urban map and to estimate the traffic behavior (to provide information about the best routes). The paper presents a hierarchical routing strategy for an urban driving advisory system (UDAS), based on agent technology. UDAS assists the drivers to get the desired destination taking into account the current situation of traffic characteristics. It gives the estimated arrival time and the corresponding distance between a start and an arrival point. The necessary information is obtained from traffic and records of previous traffic behavior (used as statistic information and to characterized the traffic, for example the traffic is jammed on an area if we have a street or an intersection blocked and the neighbor streets or intersections are full). The drivers could consult the advisory system using a variety of devices like mobile phones. The information given by the advisory system has the form of predefined short messages

Design and Testing in Laboratory Environment of the Embedded Microsystem ECAM

The paper presents an embedded control and acquisition microsystem for advanced industrial applications, where small size, small power consumption and reliability play an important role. The embedded system was designed, realised and tested in laboratory environment based on experiments involving remote control. In order to test the platform, a real small transportation and sorting installation, connected with the simulated cyclic production of a manufacturing cell were utilised. The application was implemented using two main programs: A Java program that simulates the flexible manufacturing system and the LabVIEW programs (VIs) destined to the wireless acquisition of signals from sensors and to command the actuator of conveyer. The VIs were loaded from a PC with Windows operating system and LabVIEW real time in order to accomplish the acquisition of the output signals from sensors and to transmit commands to the actuator. The two programs communicate using TCP protocol