In these recent years Wireless Sensor Networks (WSN) has been widely used in many types of applications such as environment monitoring or asset tracking. In these applications, each sensor node may collect different types of data with different levels of importance. Each type of traffic requires a different treatment from the network to meet the objective of QoS (Quality of Service). We argue that the sensor networks should be willing to spend more resources in disseminating packets that carry more important information. In this paper we propose a new protocol with differentiated services for WSNs called Diff-HEEP. The proposed protocol is an enhancement of HEEP protocol that can provide requested quality of service for high priority real time classes and distinguish high priority real time traffic from the low priority non-real time traffic, and input traffic streams are then served based on their priorities.

In these recent years Wireless Sensor Networks (WSN) has been widely used in many types of applications such as environment monitoring or asset tracking. In these applications, each sensor node may collect different types of data with different levels of importance. Each type of traffic requires a different treatment from the network to meet the objective of QoS (Quality of Service). We argue that the sensor networks should be willing to spend more resources in disseminating packets that carry more important information. In this paper we propose a new protocol with differentiated services for WSNs called Diff-HEEP. The proposed protocol is an enhancement of HEEP protocol that can provide requested quality of service for high priority real time classes and distinguish high priority real time traffic from the low priority non-real time traffic, and input traffic streams are then served based on their priorities.

The control of voltage and reactive power is a major issue in power systems control and operation. Because of the topological differences between distribution and transmission systems, different strategies have evolved. Flexible AC Transmission Systems (FACTS) controllers, such as the Thyristor Controlled Voltage Regulator (TCVR), employ the latest technology of power electronic switching devices in electric power transmission systems to control voltage and improve voltage regulation. This paper presents an impact study of using TCVR on the fault current calculations in case of a ground fault. The case study is a high voltage transmission line in the Algerian power network. The analysis is based on symmetrical components method which includes symmetrical components of current and voltage as well as the transmission line currents and line voltages, without and with TCVR in the presence of fault resistance. In this research work, the obtained simulation results match the presented theoretical analysis.

The control of voltage and reactive power is a major issue in power systems control and operation. Because of the topological differences between distribution and transmission systems, different strategies have evolved. Flexible AC Transmission Systems (FACTS) controllers, such as the Thyristor Controlled Voltage Regulator (TCVR), employ the latest technology of power electronic switching devices in electric power transmission systems to control voltage and improve voltage regulation. This paper presents an impact study of using TCVR on the fault current calculations in case of a ground fault. The case study is a high voltage transmission line in the Algerian power network. The analysis is based on symmetrical components method which includes symmetrical components of current and voltage as well as the transmission line currents and line voltages, without and with TCVR in the presence of fault resistance. In this research work, the obtained simulation results match the presented theoretical analysis.

The control of voltage and reactive power is a major issue in power systems control and operation. Because of the topological differences between distribution and transmission systems, different strategies have evolved. Flexible AC Transmission Systems (FACTS) controllers, such as the Thyristor Controlled Voltage Regulator (TCVR), employ the latest technology of power electronic switching devices in electric power transmission systems to control voltage and improve voltage regulation. This paper presents an impact study of using TCVR on the fault current calculations in case of a ground fault. The case study is a high voltage transmission line in the Algerian power network. The analysis is based on symmetrical components method which includes symmetrical components of current and voltage as well as the transmission line currents and line voltages, without and with TCVR in the presence of fault resistance. In this research work, the obtained simulation results match the presented theoretical analysis.

Although the risk graph method, described by the IEC 61508 standard is widely used for the determination of Safety Integrity Levels for the Safety Instrumented Functions (SIF) which performed by Safety Instrumented Systems (SIS). This technique has limits regarding the linguistic interpretation of the parameters of the risk analyzed. In addition, the calibration of the risk graph method as defined at the IEC61511 standard consists to use discrete intervals include also a problem of uncertainty in the calculation of Safety Integrity Levels. The purpose of this work is to improve of conventional risk graph in order to ensure a better implementation of safety instrumented systems (SIS). The proposed model based on fuzzy rules, considers the parameters defining the risk graph as inputs of a fuzzy inference systems and the Safety Integrity Level (SIL) as unique output. In order to validate the proposed model, a case study on an industrial system is carried out. The obtained results show a particular interest of fuzzy graph risk for estimating the appropriate Safety Integrity Level than that given by the risk graph conventional.

Although the risk graph method, described by the IEC 61508 standard is widely used for the determination of Safety Integrity Levels for the Safety Instrumented Functions (SIF) which performed by Safety Instrumented Systems (SIS). This technique has limits regarding the linguistic interpretation of the parameters of the risk analyzed. In addition, the calibration of the risk graph method as defined at the IEC61511 standard consists to use discrete intervals include also a problem of uncertainty in the calculation of Safety Integrity Levels. The purpose of this work is to improve of conventional risk graph in order to ensure a better implementation of safety instrumented systems (SIS). The proposed model based on fuzzy rules, considers the parameters defining the risk graph as inputs of a fuzzy inference systems and the Safety Integrity Level (SIL) as unique output. In order to validate the proposed model, a case study on an industrial system is carried out. The obtained results show a particular interest of fuzzy graph risk for estimating the appropriate Safety Integrity Level than that given by the risk graph conventional.

Although the risk graph method, described by the IEC 61508 standard is widely used for the determination of Safety Integrity Levels for the Safety Instrumented Functions (SIF) which performed by Safety Instrumented Systems (SIS). This technique has limits regarding the linguistic interpretation of the parameters of the risk analyzed. In addition, the calibration of the risk graph method as defined at the IEC61511 standard consists to use discrete intervals include also a problem of uncertainty in the calculation of Safety Integrity Levels. The purpose of this work is to improve of conventional risk graph in order to ensure a better implementation of safety instrumented systems (SIS). The proposed model based on fuzzy rules, considers the parameters defining the risk graph as inputs of a fuzzy inference systems and the Safety Integrity Level (SIL) as unique output. In order to validate the proposed model, a case study on an industrial system is carried out. The obtained results show a particular interest of fuzzy graph risk for estimating the appropriate Safety Integrity Level than that given by the risk graph conventional.

Although the risk graph method, described by the IEC 61508 standard is widely used for the determination of Safety Integrity Levels for the Safety Instrumented Functions (SIF) which performed by Safety Instrumented Systems (SIS). This technique has limits regarding the linguistic interpretation of the parameters of the risk analyzed. In addition, the calibration of the risk graph method as defined at the IEC61511 standard consists to use discrete intervals include also a problem of uncertainty in the calculation of Safety Integrity Levels. The purpose of this work is to improve of conventional risk graph in order to ensure a better implementation of safety instrumented systems (SIS). The proposed model based on fuzzy rules, considers the parameters defining the risk graph as inputs of a fuzzy inference systems and the Safety Integrity Level (SIL) as unique output. In order to validate the proposed model, a case study on an industrial system is carried out. The obtained results show a particular interest of fuzzy graph risk for estimating the appropriate Safety Integrity Level than that given by the risk graph conventional.

This paper presents a comparison between the two diagnosis approaches of linear closed-loop systems; sequential approach and integrated approach. An application of these two approaches for a DC motor will be introduced at the end to have the advantage and inconvenient one and the other for electrical entertainment.

This paper presents a comparison between the two diagnosis approaches of linear closed-loop systems; sequential approach and integrated approach. An application of these two approaches for a DC motor will be introduced at the end to have the advantage and inconvenient one and the other for electrical entertainment.