From the 1990s, urban policy in Algeria underwent significant upheavals, including authoritarian management, which was replaced by participatory management. Following the example of Algerian cities, the city of Batna adheres with this new vision, hence the implementation of a partnership program that involves various stakeholders including the citizen. The latter is present within multiple associations. The objective of this work is to highlight the activism of neighborhood associations as a representative element of civil society and their determining role in the management of different situations. To report on this issue, a field survey was conducted in the form of semi-directive interviews addressed to the three local actors: associations, citizens and elected officials.

Introduction. Budget constraints in a world ravenous for electrical power have led utility companies to operate generating stations with full power and sometimes at the limit of stability. In such drastic conditions the occurrence of any contingency or disturbance may lead to a critical situation starting with poorly damped oscillations followed by loss of synchronism and power system instability. In the past decades, the utilization of supplementary excitation control signals for improving power system stability has received much attention. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp low-frequency oscillations caused by load disturbances or short-circuit faults.

Problem. Adaptive power system stabilizers have been proposed to adequately deal with a wide range of operating conditions, but they suffer from the major drawback of requiring parameter model identification, state observation and on-line feedback gain computation. Power systems are nonlinear systems, with configurations and parameters that fluctuate with time that which require a fully nonlinear model and an adaptive control scheme for a practical operating environment. A new nonlinear adaptive fuzzy approach based on synergetic control theory which has been developed for nonlinear power system stabilizers to overcome above mentioned problems.

Aim. Synergetic control theory has been successfully applied in the design of power system stabilizers is a most promising robust control technique relying on the same principle of invariance found in sliding mode control, but without its chattering drawback. In most of its applications, synergetic control law was designed based on an asymptotic stability analysis and the system trajectories evolve to a specified attractor reaching the equilibrium in an infinite time. In this paper an indirect finite time adaptive fuzzy synergetic power system stabilizer for damping local and inter-area modes of oscillations for power systems is presented. 

Methodology. The proposed controller design is based on an adaptive fuzzy control combining a synergetic control theory with a finite-time attractor and Lyapunov synthesis. Enhancing existing adaptive fuzzy synergetic power system stabilizer, where fuzzy systems are used to approximate unknown system dynamics and robust synergetic control for only providing asymptotic stability of the closed-loop system, the proposed technique procures finite time convergence property in the derivation of the continuous synergetic control law. Analytical proofs for finite time convergence are presented confirming that the proposed adaptive scheme can guarantee that system signals are bounded and finite time stability obtained. 

Results. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results are compared to those obtained with a conventional adaptive fuzzy synergetic controller.

Introduction. Budget constraints in a world ravenous for electrical power have led utility companies to operate generating stations with full power and sometimes at the limit of stability. In such drastic conditions the occurrence of any contingency or disturbance may lead to a critical situation starting with poorly damped oscillations followed by loss of synchronism and power system instability. In the past decades, the utilization of supplementary excitation control signals for improving power system stability has received much attention. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp low-frequency oscillations caused by load disturbances or short-circuit faults.

Problem. Adaptive power system stabilizers have been proposed to adequately deal with a wide range of operating conditions, but they suffer from the major drawback of requiring parameter model identification, state observation and on-line feedback gain computation. Power systems are nonlinear systems, with configurations and parameters that fluctuate with time that which require a fully nonlinear model and an adaptive control scheme for a practical operating environment. A new nonlinear adaptive fuzzy approach based on synergetic control theory which has been developed for nonlinear power system stabilizers to overcome above mentioned problems.

Aim. Synergetic control theory has been successfully applied in the design of power system stabilizers is a most promising robust control technique relying on the same principle of invariance found in sliding mode control, but without its chattering drawback. In most of its applications, synergetic control law was designed based on an asymptotic stability analysis and the system trajectories evolve to a specified attractor reaching the equilibrium in an infinite time. In this paper an indirect finite time adaptive fuzzy synergetic power system stabilizer for damping local and inter-area modes of oscillations for power systems is presented. 

Methodology. The proposed controller design is based on an adaptive fuzzy control combining a synergetic control theory with a finite-time attractor and Lyapunov synthesis. Enhancing existing adaptive fuzzy synergetic power system stabilizer, where fuzzy systems are used to approximate unknown system dynamics and robust synergetic control for only providing asymptotic stability of the closed-loop system, the proposed technique procures finite time convergence property in the derivation of the continuous synergetic control law. Analytical proofs for finite time convergence are presented confirming that the proposed adaptive scheme can guarantee that system signals are bounded and finite time stability obtained. 

Results. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results are compared to those obtained with a conventional adaptive fuzzy synergetic controller.

Introduction. Budget constraints in a world ravenous for electrical power have led utility companies to operate generating stations with full power and sometimes at the limit of stability. In such drastic conditions the occurrence of any contingency or disturbance may lead to a critical situation starting with poorly damped oscillations followed by loss of synchronism and power system instability. In the past decades, the utilization of supplementary excitation control signals for improving power system stability has received much attention. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp low-frequency oscillations caused by load disturbances or short-circuit faults.

Problem. Adaptive power system stabilizers have been proposed to adequately deal with a wide range of operating conditions, but they suffer from the major drawback of requiring parameter model identification, state observation and on-line feedback gain computation. Power systems are nonlinear systems, with configurations and parameters that fluctuate with time that which require a fully nonlinear model and an adaptive control scheme for a practical operating environment. A new nonlinear adaptive fuzzy approach based on synergetic control theory which has been developed for nonlinear power system stabilizers to overcome above mentioned problems.

Aim. Synergetic control theory has been successfully applied in the design of power system stabilizers is a most promising robust control technique relying on the same principle of invariance found in sliding mode control, but without its chattering drawback. In most of its applications, synergetic control law was designed based on an asymptotic stability analysis and the system trajectories evolve to a specified attractor reaching the equilibrium in an infinite time. In this paper an indirect finite time adaptive fuzzy synergetic power system stabilizer for damping local and inter-area modes of oscillations for power systems is presented. 

Methodology. The proposed controller design is based on an adaptive fuzzy control combining a synergetic control theory with a finite-time attractor and Lyapunov synthesis. Enhancing existing adaptive fuzzy synergetic power system stabilizer, where fuzzy systems are used to approximate unknown system dynamics and robust synergetic control for only providing asymptotic stability of the closed-loop system, the proposed technique procures finite time convergence property in the derivation of the continuous synergetic control law. Analytical proofs for finite time convergence are presented confirming that the proposed adaptive scheme can guarantee that system signals are bounded and finite time stability obtained. 

Results. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results are compared to those obtained with a conventional adaptive fuzzy synergetic controller.

Introduction. Budget constraints in a world ravenous for electrical power have led utility companies to operate generating stations with full power and sometimes at the limit of stability. In such drastic conditions the occurrence of any contingency or disturbance may lead to a critical situation starting with poorly damped oscillations followed by loss of synchronism and power system instability. In the past decades, the utilization of supplementary excitation control signals for improving power system stability has received much attention. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp low-frequency oscillations caused by load disturbances or short-circuit faults.

Problem. Adaptive power system stabilizers have been proposed to adequately deal with a wide range of operating conditions, but they suffer from the major drawback of requiring parameter model identification, state observation and on-line feedback gain computation. Power systems are nonlinear systems, with configurations and parameters that fluctuate with time that which require a fully nonlinear model and an adaptive control scheme for a practical operating environment. A new nonlinear adaptive fuzzy approach based on synergetic control theory which has been developed for nonlinear power system stabilizers to overcome above mentioned problems.

Aim. Synergetic control theory has been successfully applied in the design of power system stabilizers is a most promising robust control technique relying on the same principle of invariance found in sliding mode control, but without its chattering drawback. In most of its applications, synergetic control law was designed based on an asymptotic stability analysis and the system trajectories evolve to a specified attractor reaching the equilibrium in an infinite time. In this paper an indirect finite time adaptive fuzzy synergetic power system stabilizer for damping local and inter-area modes of oscillations for power systems is presented. 

Methodology. The proposed controller design is based on an adaptive fuzzy control combining a synergetic control theory with a finite-time attractor and Lyapunov synthesis. Enhancing existing adaptive fuzzy synergetic power system stabilizer, where fuzzy systems are used to approximate unknown system dynamics and robust synergetic control for only providing asymptotic stability of the closed-loop system, the proposed technique procures finite time convergence property in the derivation of the continuous synergetic control law. Analytical proofs for finite time convergence are presented confirming that the proposed adaptive scheme can guarantee that system signals are bounded and finite time stability obtained. 

Results. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results are compared to those obtained with a conventional adaptive fuzzy synergetic controller.

Introduction. Constant increases in power consumption by both industrial and individual users may cause depletion of fossil fuels and environmental pollution, and hence there is a growing interest in clean and renewable energy resources. Photovoltaic power generation systems are playing an important role as a clean power electricity source in meeting future electricity demands.

 Problem. All photovoltaic systems have two problems; the first one being the very low electric-power generation efficiency, especially under low-irradiation states; the second resides in the interdependence of the amount of the electric power generated by solar arrays and the ever changing weather conditions. Load mismatch can occur under these weather varying conditions such that maximum power is not extracted and delivered to the load. This issue constitutes the so-called maximum power point tracking problem. 

Aim. Many methods have been developed to determine the maximum power point under all conditions. There are various methods, in most of them based on the well-known principle of perturb and observe. In this method, the operating point oscillates at a certain amplitude, no matter whether the maximum power point is reached or not. That is, this oscillation remains even in the steady state after reaching the maximum power point, which leads to power loss. This is an essential drawback of the previous method. In this paper, a cascade sliding mode maximum power point tracking control for a photovoltaic system is proposed to overcome above mentioned problems. 

Methodology. The photovoltaic system is mainly composed of a solar array, DC/DC boost converter, cascade sliding mode controller, and an output load. Two sliding mode control design strategies are joined to construct the proposed controller. The primary sliding mode algorithm is designed for maximum power point searching, i.e., to track the output reference voltage of the solar array. This voltage is used to manipulate the setpoint of the secondary sliding mode controller, which is used via the DC-DC boost converter to achieve maximum power output. 

Results. This novel approach provides a good transient response, a low tracking error and a very fast reaction against the solar radiation and photovoltaic cell temperature variations. The simulation results demonstrate the effectiveness of the proposed approach in the presence of environmental disturbances.

Introduction. Constant increases in power consumption by both industrial and individual users may cause depletion of fossil fuels and environmental pollution, and hence there is a growing interest in clean and renewable energy resources. Photovoltaic power generation systems are playing an important role as a clean power electricity source in meeting future electricity demands.

 Problem. All photovoltaic systems have two problems; the first one being the very low electric-power generation efficiency, especially under low-irradiation states; the second resides in the interdependence of the amount of the electric power generated by solar arrays and the ever changing weather conditions. Load mismatch can occur under these weather varying conditions such that maximum power is not extracted and delivered to the load. This issue constitutes the so-called maximum power point tracking problem. 

Aim. Many methods have been developed to determine the maximum power point under all conditions. There are various methods, in most of them based on the well-known principle of perturb and observe. In this method, the operating point oscillates at a certain amplitude, no matter whether the maximum power point is reached or not. That is, this oscillation remains even in the steady state after reaching the maximum power point, which leads to power loss. This is an essential drawback of the previous method. In this paper, a cascade sliding mode maximum power point tracking control for a photovoltaic system is proposed to overcome above mentioned problems. 

Methodology. The photovoltaic system is mainly composed of a solar array, DC/DC boost converter, cascade sliding mode controller, and an output load. Two sliding mode control design strategies are joined to construct the proposed controller. The primary sliding mode algorithm is designed for maximum power point searching, i.e., to track the output reference voltage of the solar array. This voltage is used to manipulate the setpoint of the secondary sliding mode controller, which is used via the DC-DC boost converter to achieve maximum power output. 

Results. This novel approach provides a good transient response, a low tracking error and a very fast reaction against the solar radiation and photovoltaic cell temperature variations. The simulation results demonstrate the effectiveness of the proposed approach in the presence of environmental disturbances.

Introduction. Constant increases in power consumption by both industrial and individual users may cause depletion of fossil fuels and environmental pollution, and hence there is a growing interest in clean and renewable energy resources. Photovoltaic power generation systems are playing an important role as a clean power electricity source in meeting future electricity demands.

 Problem. All photovoltaic systems have two problems; the first one being the very low electric-power generation efficiency, especially under low-irradiation states; the second resides in the interdependence of the amount of the electric power generated by solar arrays and the ever changing weather conditions. Load mismatch can occur under these weather varying conditions such that maximum power is not extracted and delivered to the load. This issue constitutes the so-called maximum power point tracking problem. 

Aim. Many methods have been developed to determine the maximum power point under all conditions. There are various methods, in most of them based on the well-known principle of perturb and observe. In this method, the operating point oscillates at a certain amplitude, no matter whether the maximum power point is reached or not. That is, this oscillation remains even in the steady state after reaching the maximum power point, which leads to power loss. This is an essential drawback of the previous method. In this paper, a cascade sliding mode maximum power point tracking control for a photovoltaic system is proposed to overcome above mentioned problems. 

Methodology. The photovoltaic system is mainly composed of a solar array, DC/DC boost converter, cascade sliding mode controller, and an output load. Two sliding mode control design strategies are joined to construct the proposed controller. The primary sliding mode algorithm is designed for maximum power point searching, i.e., to track the output reference voltage of the solar array. This voltage is used to manipulate the setpoint of the secondary sliding mode controller, which is used via the DC-DC boost converter to achieve maximum power output. 

Results. This novel approach provides a good transient response, a low tracking error and a very fast reaction against the solar radiation and photovoltaic cell temperature variations. The simulation results demonstrate the effectiveness of the proposed approach in the presence of environmental disturbances.

Introduction. Constant increases in power consumption by both industrial and individual users may cause depletion of fossil fuels and environmental pollution, and hence there is a growing interest in clean and renewable energy resources. Photovoltaic power generation systems are playing an important role as a clean power electricity source in meeting future electricity demands.

 Problem. All photovoltaic systems have two problems; the first one being the very low electric-power generation efficiency, especially under low-irradiation states; the second resides in the interdependence of the amount of the electric power generated by solar arrays and the ever changing weather conditions. Load mismatch can occur under these weather varying conditions such that maximum power is not extracted and delivered to the load. This issue constitutes the so-called maximum power point tracking problem. 

Aim. Many methods have been developed to determine the maximum power point under all conditions. There are various methods, in most of them based on the well-known principle of perturb and observe. In this method, the operating point oscillates at a certain amplitude, no matter whether the maximum power point is reached or not. That is, this oscillation remains even in the steady state after reaching the maximum power point, which leads to power loss. This is an essential drawback of the previous method. In this paper, a cascade sliding mode maximum power point tracking control for a photovoltaic system is proposed to overcome above mentioned problems. 

Methodology. The photovoltaic system is mainly composed of a solar array, DC/DC boost converter, cascade sliding mode controller, and an output load. Two sliding mode control design strategies are joined to construct the proposed controller. The primary sliding mode algorithm is designed for maximum power point searching, i.e., to track the output reference voltage of the solar array. This voltage is used to manipulate the setpoint of the secondary sliding mode controller, which is used via the DC-DC boost converter to achieve maximum power output. 

Results. This novel approach provides a good transient response, a low tracking error and a very fast reaction against the solar radiation and photovoltaic cell temperature variations. The simulation results demonstrate the effectiveness of the proposed approach in the presence of environmental disturbances.

This paper deals with the design and optimization of a 1.2 MVA medium-voltage (MV) power electronic traction transformer (PETT) for an AC 15 kV/16.7 Hz railway grid, in which a simple two-stage multi-cell PETT topology consisting of a bidirectional 170 kW, 2.5 kV AC rms to 6 kV DC power factor corrected (PFC) converter stage followed by a bidirectional isolated 46 kHz, 6 kV to 1.5 kV series resonant DC/DC converter for each cell is presented. This paper presents a methodology that maximizes the converter"s efficiency and minimizes the converter"s size and weight. Accordingly, the first stage employs 10 kV SiC MOSFETs based on the integrated Triangular Current Mode (iTCM). The second stage uses 10 kV SiC MOSFETs on the MV-side, 3.3 kV SiC MOSFETs on the LV-side, and a medium frequency (MF) MV transformer operating at 46 kHz. MF transformers offer a way to reduce weight and improve energy efficiency, particularly in electric multiple-unit applications. The MF MV transformer requires power electronic converters, which invert and rectify the voltages and currents at the desired operating frequency. The development of high voltage SiC MOSFETs, which can be used instead of Si IGBTs in PETT topologies, increases the operating frequency without reducing the converter"s efficiency. The designed MV PETT achieves 98.95% efficiency and 0.76 kVA/kg power density.

This paper deals with the design and optimization of a 1.2 MVA medium-voltage (MV) power electronic traction transformer (PETT) for an AC 15 kV/16.7 Hz railway grid, in which a simple two-stage multi-cell PETT topology consisting of a bidirectional 170 kW, 2.5 kV AC rms to 6 kV DC power factor corrected (PFC) converter stage followed by a bidirectional isolated 46 kHz, 6 kV to 1.5 kV series resonant DC/DC converter for each cell is presented. This paper presents a methodology that maximizes the converter"s efficiency and minimizes the converter"s size and weight. Accordingly, the first stage employs 10 kV SiC MOSFETs based on the integrated Triangular Current Mode (iTCM). The second stage uses 10 kV SiC MOSFETs on the MV-side, 3.3 kV SiC MOSFETs on the LV-side, and a medium frequency (MF) MV transformer operating at 46 kHz. MF transformers offer a way to reduce weight and improve energy efficiency, particularly in electric multiple-unit applications. The MF MV transformer requires power electronic converters, which invert and rectify the voltages and currents at the desired operating frequency. The development of high voltage SiC MOSFETs, which can be used instead of Si IGBTs in PETT topologies, increases the operating frequency without reducing the converter"s efficiency. The designed MV PETT achieves 98.95% efficiency and 0.76 kVA/kg power density.

This paper deals with the design and optimization of a 1.2 MVA medium-voltage (MV) power electronic traction transformer (PETT) for an AC 15 kV/16.7 Hz railway grid, in which a simple two-stage multi-cell PETT topology consisting of a bidirectional 170 kW, 2.5 kV AC rms to 6 kV DC power factor corrected (PFC) converter stage followed by a bidirectional isolated 46 kHz, 6 kV to 1.5 kV series resonant DC/DC converter for each cell is presented. This paper presents a methodology that maximizes the converter"s efficiency and minimizes the converter"s size and weight. Accordingly, the first stage employs 10 kV SiC MOSFETs based on the integrated Triangular Current Mode (iTCM). The second stage uses 10 kV SiC MOSFETs on the MV-side, 3.3 kV SiC MOSFETs on the LV-side, and a medium frequency (MF) MV transformer operating at 46 kHz. MF transformers offer a way to reduce weight and improve energy efficiency, particularly in electric multiple-unit applications. The MF MV transformer requires power electronic converters, which invert and rectify the voltages and currents at the desired operating frequency. The development of high voltage SiC MOSFETs, which can be used instead of Si IGBTs in PETT topologies, increases the operating frequency without reducing the converter"s efficiency. The designed MV PETT achieves 98.95% efficiency and 0.76 kVA/kg power density.

This work proposes a new modeling framework based on combining graded band-gap (GBG) engineering and metaheuristic optimization to improve the Cd-Free ZnMgO/CIGS solar cell performances. Analytical and numerical calculations are carried out to assess the influence of band-gap profiles of both buffer and active layers on the electronic and optical properties of the studied solar cell. This investigation shows a great improvement of solar cell efficiency by increasing the optoelectronic figures of merit through tuning and optimizing the band-gap profiles and the conduction band offset at the ZnMgO/CIGS interface. Moreover, metaheuristic-based optimization models are developed to optimize the GBG profiles and enhance the optical and electrical performances of the solar cell. In this context, we recorded very satisfactory results, where the optimized design with GBG paradigm offers a high efficiency of 31.88% compared to 23.35% provided by the conventional CdS/CIGS solar cell. Therefore, this study provides a new strategy in enhancing the efficiency of thin-film solar cells by exploiting the graded band-gap engineering combined with metaheuristic optimization approach.

This work proposes a new modeling framework based on combining graded band-gap (GBG) engineering and metaheuristic optimization to improve the Cd-Free ZnMgO/CIGS solar cell performances. Analytical and numerical calculations are carried out to assess the influence of band-gap profiles of both buffer and active layers on the electronic and optical properties of the studied solar cell. This investigation shows a great improvement of solar cell efficiency by increasing the optoelectronic figures of merit through tuning and optimizing the band-gap profiles and the conduction band offset at the ZnMgO/CIGS interface. Moreover, metaheuristic-based optimization models are developed to optimize the GBG profiles and enhance the optical and electrical performances of the solar cell. In this context, we recorded very satisfactory results, where the optimized design with GBG paradigm offers a high efficiency of 31.88% compared to 23.35% provided by the conventional CdS/CIGS solar cell. Therefore, this study provides a new strategy in enhancing the efficiency of thin-film solar cells by exploiting the graded band-gap engineering combined with metaheuristic optimization approach.

This work proposes a new modeling framework based on combining graded band-gap (GBG) engineering and metaheuristic optimization to improve the Cd-Free ZnMgO/CIGS solar cell performances. Analytical and numerical calculations are carried out to assess the influence of band-gap profiles of both buffer and active layers on the electronic and optical properties of the studied solar cell. This investigation shows a great improvement of solar cell efficiency by increasing the optoelectronic figures of merit through tuning and optimizing the band-gap profiles and the conduction band offset at the ZnMgO/CIGS interface. Moreover, metaheuristic-based optimization models are developed to optimize the GBG profiles and enhance the optical and electrical performances of the solar cell. In this context, we recorded very satisfactory results, where the optimized design with GBG paradigm offers a high efficiency of 31.88% compared to 23.35% provided by the conventional CdS/CIGS solar cell. Therefore, this study provides a new strategy in enhancing the efficiency of thin-film solar cells by exploiting the graded band-gap engineering combined with metaheuristic optimization approach.

This work proposes a new modeling framework based on combining graded band-gap (GBG) engineering and metaheuristic optimization to improve the Cd-Free ZnMgO/CIGS solar cell performances. Analytical and numerical calculations are carried out to assess the influence of band-gap profiles of both buffer and active layers on the electronic and optical properties of the studied solar cell. This investigation shows a great improvement of solar cell efficiency by increasing the optoelectronic figures of merit through tuning and optimizing the band-gap profiles and the conduction band offset at the ZnMgO/CIGS interface. Moreover, metaheuristic-based optimization models are developed to optimize the GBG profiles and enhance the optical and electrical performances of the solar cell. In this context, we recorded very satisfactory results, where the optimized design with GBG paradigm offers a high efficiency of 31.88% compared to 23.35% provided by the conventional CdS/CIGS solar cell. Therefore, this study provides a new strategy in enhancing the efficiency of thin-film solar cells by exploiting the graded band-gap engineering combined with metaheuristic optimization approach.

Iris texture is one of the most secure biometric characteristics used for person recognition, where the most significant step in the iris identification process is effective features extraction. Deep Convolutional Neural network models have been achieved massive success in the features extraction field in recent years, but several of these models have tens to hundreds of millions of parameters, which affect the computational time and resources. A lot of systems proposed in the iris recognition field extract features from normalized iris images after applying many pre-processing steps. These steps affect the quality and computational efficiency of these systems; also, occlusion, reflections, blur, and illumination variation affect the quality of features extracted. This paper proposed a new robust approach for iris recognition that locates the iris region based on the YOLOv4-tiny, then it extracts features without using iris images’ pre-processing, which is a delicate task. In addition, we have proposed an effective model that accelerated the feature extraction process by reducing the architecture of the Inception-v3 model. The obtained results on four benchmark datasets validate the robustness of our approach, where we achieved average accuracy rates of 99.91%, 99.60%, 99.91%, and 99.19% on the IITD, CASIA-Iris-V1, CASIA-Iris-Interval, and CASIA-Iris-Thousand datasets, respectively.

Iris texture is one of the most secure biometric characteristics used for person recognition, where the most significant step in the iris identification process is effective features extraction. Deep Convolutional Neural network models have been achieved massive success in the features extraction field in recent years, but several of these models have tens to hundreds of millions of parameters, which affect the computational time and resources. A lot of systems proposed in the iris recognition field extract features from normalized iris images after applying many pre-processing steps. These steps affect the quality and computational efficiency of these systems; also, occlusion, reflections, blur, and illumination variation affect the quality of features extracted. This paper proposed a new robust approach for iris recognition that locates the iris region based on the YOLOv4-tiny, then it extracts features without using iris images’ pre-processing, which is a delicate task. In addition, we have proposed an effective model that accelerated the feature extraction process by reducing the architecture of the Inception-v3 model. The obtained results on four benchmark datasets validate the robustness of our approach, where we achieved average accuracy rates of 99.91%, 99.60%, 99.91%, and 99.19% on the IITD, CASIA-Iris-V1, CASIA-Iris-Interval, and CASIA-Iris-Thousand datasets, respectively.

Thisarticleconcernstheinverse problem of the recoveryof unknown potential coefficient for the Schrödinger equation, in a bounded domain of Rn with non-homogeneous Neumann boundary condition from a time-dependent Dirich let boundary measurement. We prove uniqueness and Lipschitz stability for this inverse problem under certain convexity hypothesis on the geometry of the spatial domain and under weak regularity requirements on the data. The proof is based on aCarleman estimate in [12] for Schrödinger equations and its resulting implication, a continuous observability inequality. Mathematics Subject Classification. 35R30, 35Q40, 49K20.

Thisarticleconcernstheinverse problem of the recoveryof unknown potential coefficient for the Schrödinger equation, in a bounded domain of Rn with non-homogeneous Neumann boundary condition from a time-dependent Dirich let boundary measurement. We prove uniqueness and Lipschitz stability for this inverse problem under certain convexity hypothesis on the geometry of the spatial domain and under weak regularity requirements on the data. The proof is based on aCarleman estimate in [12] for Schrödinger equations and its resulting implication, a continuous observability inequality. Mathematics Subject Classification. 35R30, 35Q40, 49K20.