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In this study, performance of different wind turbines is compared with using QBlade software. Normally wind turbines are categorized as Horizontal Axis Wind Turbine (HAWT) and Vertical axis wind turbine (VAWT) which in this paper Darrieus type as a VAWT is discussed with HAWT. The airfoil selected for this study is NACA 0012 and from simulations it can be resulted how adding blades influence efficiency in wind turbines. In terms of using wind turbines, number of blades is one of the important parameters. QBlade contains the XFOIL airfoil analysis functionalities which makes a software a single tool that comprises all functionality needed for the design and simulation of vertical and horizontal axis wind turbines. The benefits of the proper airfoil design optimal is increasing the efficiency of wind turbines and maximization of the power produced.

This article presents an ambience intelligence application for smart home systems for efficient use of electricity, enhance comfort zone, independence of living and security. The system integrates smart home occupant's identification, sensors-actuators deployment, a gateway Hub, machine learning, and cloud computing components to realize the objectives of smart living. A Mobile phone MAC-address based occupant identification and machine learning algorithms are proposed to address the multiple smart home occupant problems and an instant user control versus rule-based control conflicts. Results show that machine learning algorithm could learn the ambience preferences of multiple occupants when trained on a large enough dataset. The proposed system can implement ambient intelligence applications in smart home.

This paper covers the design aspects of a new multi-channel electrode for the acquisition of surface electromyography signals from a selected muscle. The new multi-channel electrode has 11 pins where the monopolar signals produced will be configured in a software either as Linear array or Laplacian configuration. The design specification of the pre-amplifier ideally was to have a voltage gain of 500 with bandpass filtering of 5 Hz-1 kHz. The final design of the pre-amplifier circuit using an INA 118 instrumentation amplifier was built and tested to give values for voltage gain of 484 with bandpass filtering of 6.8 Hz-1.02 kHz. The software configuration that gives clearer and more defined signals in terms of motor unit action potentials for future signal processing is the Laplacian rather than Linear array.

Conventional collection of surface electromyography signals requires the surface electrodes, amplifier and data acquisition card to all be wired together, restricting the movement of the test subject. With the advancement of wireless technology such as Bluetooth and XBee with ZigBee, the wire link between the electrodes and computer storing the data can be removed. Using Bluetooth configuration will require new circuitry of an analogue-to-digital convertor with a microcontroller to a Bluetooth module with the wireless link to an USB Bluetooth modem dongle. The XBee configuration will also require an analogue-to-digital convertor with a microcontroller to a XBee transceiver for the wireless link to an USB XBee dongle transceiver. XBee with ZigBee configuration will allow multichannel collection of signals as a wireless sensor network.

The data collection of surface electromyography signals has required the sensor, amplifier and data acquisition card to be all wired together restricting the movement of the subject being tested. With the advancement of wireless technology such as Bluetooth, IEEE 802.15.4 and ZigBee the wire link between the amplifier and computer analysing and storing the data can be removed. Using Bluetooth will require new circuitry of a microcontroller with an analogue-digital convertor, a RS232 serial link, transceiver and a USB dongle transceiver for the wireless link. The IEEE 802.15.4 will require a single chip microcontroller to perform the analogue-digital convertor and also a transceiver for the wireless link to an USB dongle transceiver. ZigBee will build on the IEEE 802.15.4 configuration to allow multichannel collection of signals as a wireless sensor network.