A complete parametric study of stacked rectangular microstrip patches printed on non-magnetic isotropic substrate is performed. The numerical results are obtained by applying the method of moments to the electric field integral equations. Detailed closed-form expressions of Green’s functions are presented. The new results found indicate that, the lower resonant frequency is mainly determined by the patch etched on the thicker layer. The layer having the higher permittivity defines which resonance is mainly determined by the bottom patch, either the upper resonance if the upper layer has the higher permittivity, or the lower resonance in opposite case. All these results offer better understanding and thus a better control of the dual-band operating of the microstrip antenna. Therefore, a proper choice of the antenna parameters becomes possible in order to obtain the desired functional characteristics.

A complete parametric study of stacked rectangular microstrip patches printed on non-magnetic isotropic substrate is performed. The numerical results are obtained by applying the method of moments to the electric field integral equations. Detailed closed-form expressions of Green’s functions are presented. The new results found indicate that, the lower resonant frequency is mainly determined by the patch etched on the thicker layer. The layer having the higher permittivity defines which resonance is mainly determined by the bottom patch, either the upper resonance if the upper layer has the higher permittivity, or the lower resonance in opposite case. All these results offer better understanding and thus a better control of the dual-band operating of the microstrip antenna. Therefore, a proper choice of the antenna parameters becomes possible in order to obtain the desired functional characteristics.

In this paper, we study the postural behaviour of two categories of people: Post-CVA subjects suffering from cerebrovascular accident syndromes and healthy individuals under several levels of anterior–posterior and medial–lateral sinusoidal disturbances (0.1–0.5 Hz). These perturbations were produced from an omnidirectional platform called Isiskate. Afterwards, we have quantified seventy postural parameters, they were combined of linear stabilometric parameters and non-linear time dependent stochastic parameters using stabilogram diffusion analysis and some spectral attributes using power spectral density. The aim of our analysis is to reduce data dimensionality using principal component analysis (PCA). Furthermore, we proposed a new PCA-related criterion named: criterion of contribution in order to evaluate the contribution of every variable in the resulted system structure, and thus to eliminate the redundant postural characteristics. Afterwards, we highlighted some interesting distinctive parameters. The selected parameters were used thereafter in comparison between the studied groups. Finally, we created a classification model using support vector machines to distinguish stroke patients. Our proposed techniques help in understanding the human postural dynamics and facilitate the diagnosis of pathologies related to equilibrium which can be used to improve the rehabilitation services.

In this paper, we study the postural behaviour of two categories of people: Post-CVA subjects suffering from cerebrovascular accident syndromes and healthy individuals under several levels of anterior–posterior and medial–lateral sinusoidal disturbances (0.1–0.5 Hz). These perturbations were produced from an omnidirectional platform called Isiskate. Afterwards, we have quantified seventy postural parameters, they were combined of linear stabilometric parameters and non-linear time dependent stochastic parameters using stabilogram diffusion analysis and some spectral attributes using power spectral density. The aim of our analysis is to reduce data dimensionality using principal component analysis (PCA). Furthermore, we proposed a new PCA-related criterion named: criterion of contribution in order to evaluate the contribution of every variable in the resulted system structure, and thus to eliminate the redundant postural characteristics. Afterwards, we highlighted some interesting distinctive parameters. The selected parameters were used thereafter in comparison between the studied groups. Finally, we created a classification model using support vector machines to distinguish stroke patients. Our proposed techniques help in understanding the human postural dynamics and facilitate the diagnosis of pathologies related to equilibrium which can be used to improve the rehabilitation services.

In this paper, we study the postural behaviour of two categories of people: Post-CVA subjects suffering from cerebrovascular accident syndromes and healthy individuals under several levels of anterior–posterior and medial–lateral sinusoidal disturbances (0.1–0.5 Hz). These perturbations were produced from an omnidirectional platform called Isiskate. Afterwards, we have quantified seventy postural parameters, they were combined of linear stabilometric parameters and non-linear time dependent stochastic parameters using stabilogram diffusion analysis and some spectral attributes using power spectral density. The aim of our analysis is to reduce data dimensionality using principal component analysis (PCA). Furthermore, we proposed a new PCA-related criterion named: criterion of contribution in order to evaluate the contribution of every variable in the resulted system structure, and thus to eliminate the redundant postural characteristics. Afterwards, we highlighted some interesting distinctive parameters. The selected parameters were used thereafter in comparison between the studied groups. Finally, we created a classification model using support vector machines to distinguish stroke patients. Our proposed techniques help in understanding the human postural dynamics and facilitate the diagnosis of pathologies related to equilibrium which can be used to improve the rehabilitation services.

In this paper, we study the postural behaviour of two categories of people: Post-CVA subjects suffering from cerebrovascular accident syndromes and healthy individuals under several levels of anterior–posterior and medial–lateral sinusoidal disturbances (0.1–0.5 Hz). These perturbations were produced from an omnidirectional platform called Isiskate. Afterwards, we have quantified seventy postural parameters, they were combined of linear stabilometric parameters and non-linear time dependent stochastic parameters using stabilogram diffusion analysis and some spectral attributes using power spectral density. The aim of our analysis is to reduce data dimensionality using principal component analysis (PCA). Furthermore, we proposed a new PCA-related criterion named: criterion of contribution in order to evaluate the contribution of every variable in the resulted system structure, and thus to eliminate the redundant postural characteristics. Afterwards, we highlighted some interesting distinctive parameters. The selected parameters were used thereafter in comparison between the studied groups. Finally, we created a classification model using support vector machines to distinguish stroke patients. Our proposed techniques help in understanding the human postural dynamics and facilitate the diagnosis of pathologies related to equilibrium which can be used to improve the rehabilitation services.

This paper presents a new approach in the field of trajectory tracking for nonholonomic mobile robot in presence of disturbances. The proposed control design is constructed by a kinematic controller, based on PD sliding surface using fuzzy sliding mode for the angular and linear velocities disturbances, in order to tend asymptotically the robot posture error to zero. Thereafter a dynamic controller is presented using as a sliding surface design, a fast terminal function (FTF) whose parameters are generated by a genetic algorithm in order to converge the velocity errors to zero in finite time and guarantee the asymptotic stability of the system using a Lyapunov candidate. The elaborated simulation works in the case of different trajectories confirm the robustness of the proposed approach.

This paper presents a new approach in the field of trajectory tracking for nonholonomic mobile robot in presence of disturbances. The proposed control design is constructed by a kinematic controller, based on PD sliding surface using fuzzy sliding mode for the angular and linear velocities disturbances, in order to tend asymptotically the robot posture error to zero. Thereafter a dynamic controller is presented using as a sliding surface design, a fast terminal function (FTF) whose parameters are generated by a genetic algorithm in order to converge the velocity errors to zero in finite time and guarantee the asymptotic stability of the system using a Lyapunov candidate. The elaborated simulation works in the case of different trajectories confirm the robustness of the proposed approach.

This paper presents a new approach in the field of trajectory tracking for nonholonomic mobile robot in presence of disturbances. The proposed control design is constructed by a kinematic controller, based on PD sliding surface using fuzzy sliding mode for the angular and linear velocities disturbances, in order to tend asymptotically the robot posture error to zero. Thereafter a dynamic controller is presented using as a sliding surface design, a fast terminal function (FTF) whose parameters are generated by a genetic algorithm in order to converge the velocity errors to zero in finite time and guarantee the asymptotic stability of the system using a Lyapunov candidate. The elaborated simulation works in the case of different trajectories confirm the robustness of the proposed approach.

In this paper, a new Graphene nanoribbon (GNR) based Ge-phototransistor is proposed and investigated numerically by self-consistently solving the Schrödinger equation and Poisson equation using non-equilibrium Green’s function (NEGF) formalism. An overall performance metrics comparison between both the conventional Si-based phototransistor and the proposed design is performed. It is found that the proposed GNR Ge-phototransistor provides better electrical and optical performances compared to the conventional counterpart. Moreover, using GNR material as a channel can improve the device performance not only enables a high Ion/Ioff ratio, but also allows achieving a superior sensitivity for ultra-low optical powers. It is also revealed that the responsivity of the investigated design can be increased by reducing the GNR channel length. This underlines the outstanding capability of the proposed design for bridging the gap between modern nanoelectronic and nanophotonic technologies. In addition, the proposed GNR-based Ge-phototransistor can achieve an acceptable detectivity for very weak optical power intensities, in the order of some Femto-Watts, which leads to reduce the total power consumption associated with optical links. Therefore, the proposed GNR phototransistor pinpoints a new path toward achieving an ultrasensitive photoreceiver with low power consumption, which makes it potential alternative for chip-level Infrared communication and nano-optoelectronic applications.

In this paper, a new Graphene nanoribbon (GNR) based Ge-phototransistor is proposed and investigated numerically by self-consistently solving the Schrödinger equation and Poisson equation using non-equilibrium Green’s function (NEGF) formalism. An overall performance metrics comparison between both the conventional Si-based phototransistor and the proposed design is performed. It is found that the proposed GNR Ge-phototransistor provides better electrical and optical performances compared to the conventional counterpart. Moreover, using GNR material as a channel can improve the device performance not only enables a high Ion/Ioff ratio, but also allows achieving a superior sensitivity for ultra-low optical powers. It is also revealed that the responsivity of the investigated design can be increased by reducing the GNR channel length. This underlines the outstanding capability of the proposed design for bridging the gap between modern nanoelectronic and nanophotonic technologies. In addition, the proposed GNR-based Ge-phototransistor can achieve an acceptable detectivity for very weak optical power intensities, in the order of some Femto-Watts, which leads to reduce the total power consumption associated with optical links. Therefore, the proposed GNR phototransistor pinpoints a new path toward achieving an ultrasensitive photoreceiver with low power consumption, which makes it potential alternative for chip-level Infrared communication and nano-optoelectronic applications.

In this paper, a new Graphene nanoribbon (GNR) based Ge-phototransistor is proposed and investigated numerically by self-consistently solving the Schrödinger equation and Poisson equation using non-equilibrium Green’s function (NEGF) formalism. An overall performance metrics comparison between both the conventional Si-based phototransistor and the proposed design is performed. It is found that the proposed GNR Ge-phototransistor provides better electrical and optical performances compared to the conventional counterpart. Moreover, using GNR material as a channel can improve the device performance not only enables a high Ion/Ioff ratio, but also allows achieving a superior sensitivity for ultra-low optical powers. It is also revealed that the responsivity of the investigated design can be increased by reducing the GNR channel length. This underlines the outstanding capability of the proposed design for bridging the gap between modern nanoelectronic and nanophotonic technologies. In addition, the proposed GNR-based Ge-phototransistor can achieve an acceptable detectivity for very weak optical power intensities, in the order of some Femto-Watts, which leads to reduce the total power consumption associated with optical links. Therefore, the proposed GNR phototransistor pinpoints a new path toward achieving an ultrasensitive photoreceiver with low power consumption, which makes it potential alternative for chip-level Infrared communication and nano-optoelectronic applications.

In this paper, a new Graphene nanoribbon (GNR) based Ge-phototransistor is proposed and investigated numerically by self-consistently solving the Schrödinger equation and Poisson equation using non-equilibrium Green’s function (NEGF) formalism. An overall performance metrics comparison between both the conventional Si-based phototransistor and the proposed design is performed. It is found that the proposed GNR Ge-phototransistor provides better electrical and optical performances compared to the conventional counterpart. Moreover, using GNR material as a channel can improve the device performance not only enables a high Ion/Ioff ratio, but also allows achieving a superior sensitivity for ultra-low optical powers. It is also revealed that the responsivity of the investigated design can be increased by reducing the GNR channel length. This underlines the outstanding capability of the proposed design for bridging the gap between modern nanoelectronic and nanophotonic technologies. In addition, the proposed GNR-based Ge-phototransistor can achieve an acceptable detectivity for very weak optical power intensities, in the order of some Femto-Watts, which leads to reduce the total power consumption associated with optical links. Therefore, the proposed GNR phototransistor pinpoints a new path toward achieving an ultrasensitive photoreceiver with low power consumption, which makes it potential alternative for chip-level Infrared communication and nano-optoelectronic applications.