In this paper, novel virtual instrumentation based systems for real-time collision-free path planning and tracking control of mobile robots are proposed. The developed virtual instruments are computationally simple and efficient in comparison to other approaches, which act as a new soft-computing platform to implement a biologically-inspired neural network. This neural network is topologically arranged with only local lateral connections among neurons. The dynamics of each neuron is described by a shunting equation with both excitatory and inhibitory connections. The neural network requires no off-line training or on-line learning, which is capable of planning a comfortable trajectory to the target without suffering from neither the too close nor the too far problems. LabVIEW is chosen as the software platform to build the proposed virtual instrumentation systems, as it is one of the most important industrial platforms. We take the initiative to develop the first neuro-dynamic application in LabVIEW. The developed virtual instruments could be easily used as educational and research tools for studying various robot path planning and tracking situations that could be easily understood and analyzed step by step. The effectiveness and efficiency of the developed virtual instruments are demonstrated through simulation and comparison studies.

Granisetron Hydrochloride is a 5-hydroxytryptamine 3 (5-HT3) receptor antagonist used for the prevention and treatment of nausea and vomiting associated with cancer chemotherapy. Based on the hydrophilicity of this drug (pka=9.4) it is unlikely that passive diffusion across the skin could deliver therapeutic amounts from a large sized patch. This study was conducted to evaluate the feasibility of in vitro transdermal delivery of granisetron using electroporation across full thickness hairless rat skin. A 2 4-1 fractional factorial design was used to determine the most important variables affecting the transdermal delivery of granisetron using electroporation. The variables studied and respective levels investigated were drug concentration (10, 20 mg/ml), voltage (155, 310 volt), pulse duration (12, 24 ms) and number of pulses (100, 200 pulses). Permeation profiles were used for the representation of data, where Q: the cumulative amount permeated per cm 2 (µg/cm 2) was plotted against time (min). The selected dependent variable (response) was Q120 which is the cumulative amount permeated per cm 2 after 2 hours. Design-expert version 7.0.0 was used for the statistical evaluation. The results of the analysis of variance (ANOVA) revealed that Q120 was significantly affected by the voltage, pulse duration and number of pulses. The drug concentration had a non significant effect on Q120. A reduced polynomial regression equation which expresses the influence of process parameters on the response was obtained to enable navigation of the experimental space.

Recently, Sustainable energy has appeared recently as one of the most efficient sources of electrical energy. Solar energy, which converts direct sun rays into electrical energy, is one of the most basic kind of renewable energy. Maximum power extraction in the presence of changing environmental conditions is one of the problems of solar energy transformation. The Weather conditions affectthe voltage, current, and consequently the maximum power extracted from PV panels. To raise the efficiency and reducing the tracking time of the system, it requests to work for PV panels at a Maximum Power Point (MPP). Under any environmental conditions, there is a different MPP. Solar irradiation, temperature, and load all affect the PV panel's output power. The control of a Photovoltaic system using fuzzy logic, intelligent Maximum Power Point Tracking (MPPT) is proposed in this study. Fuzzy MPPT systems have a rapid response to the changes in the environmental conditions and do not move with changes in circuit parameters. In this research, we compare different examples of membership functions like Triangular, PIShaped, and Gaussian combination with different roles. Simulation results show that the Pi-shaped membership function has the best performance compared to other types. Fuzzy MPPT controller based on PI-shaped membership function is designed and implemented using low-cost hardware. Experimental results confirmed the validity of the proposed MPPT system.

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