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A new 4-D hyperchaotic two-wing system with three quadratic nonlinearities is proposed in this paper. The dynamical properties of the new hyperchaotic system are described in terms of phase portraits, Lyapunov exponents, Kaplan-Yorke dimension, symmetry, dissipativity, etc. Also, a detailed dynamical bifurcation analysis of the hyperchaotic system has been studied using bifurcation diagrams. As an engineering application, an electronic circuit realization of the new hyperchaotic two-wing system is developed in MultiSIM, which confirms the feasibility of the theoretical hyperchaotic two-wing system.

A 3-D new two-scroll chaotic attractor with three quadratic nonlinearities is investigated in this paper. First, the qualitative and dynamical properties of the new two-scroll chaotic system are described in terms of phase portraits, equilibrium points, Lyapunov exponents, Kaplan-Yorke dimension, dissipativity, etc. We show that the new two-scroll dissipative chaotic system has three unstable equilibrium points. As an engineering application, global chaos control of the new two-scroll chaotic system with unknown system parameters is designed via adaptive feedback control and Lyapunov stability theory. Furthermore, an electronic circuit realization of the new chaotic attractor is presented in detail to confirm the feasibility of the theoretical chaotic two-scroll attractor model.

A 3-D novel double-convection chaotic system with three nonlinearities is proposed in this research work. The dynamical properties of the new chaotic system are described in terms of phase portraits, Lyapunov exponents, Kaplan-Yorke dimension, dissipativity, stability analysis of equilibria, etc. Adaptive control and synchronization of the new chaotic system with unknown parameters are achieved via nonlinear controllers and the results are established using Lyapunov stability theory. Furthermore, an electronic circuit realization of the new 3-D novel chaotic system is presented in detail. Finally, the circuit experimental results of the 3-D novel chaotic attractor show agreement with the numerical simulations.

In this paper describe an implementation of speech recognition to pick and place an object using Robot Arm. To get the feature extraction of speech signal used Mel-Frequency Cepstrum Coefficients (MFCC) method and to learn the database of speech recognition used Support Vector Machine (SVM) method, the algorithm based on Python 2.7. The data learning which used to SVM process are 12 features, then the system tested using trained and not trained data show the best agreement to identifying the speech recognition. The speech recognition system has been implemented for control the 5 DoF Robot Arm based Arduino microcontroller to doing task pick and place the object.

To performing Sholat, Muslims around the world are required to pay attention to the requirements of Sholat, such as; determining the direction of the Qibla (Kaaba) and the time of Sholat. In this research will be made a real time Qibla Finder and Sholat Times named Q-Bot Ver3 to help Muslims find a Qibla direction and Time of Sholat anywhere. This Qibla Finder and Sholat Times are developed with robotic technology based on Digital Compass, GPS and Microcontroller. To determine the Qibla direction and Sholat times, latitude and longitude data form GPS module processed used spherical triangle trigonometry method, while the compass module used to show the Qibla direction. Moreover, this system has a buzzer which can sound if the device facing to the Qibla. This system is reliable and accurate in determining the Qibla Finder and Sholat Times. Thus, the advantage of the system is can correct the Qibla of Masjid and can help blind people to facing Qibla around the world.

In this paper, we design and investigate a biological signal detection of eye movements (Electrooculogram). To detect a signal of Electrooculogram (EOG) used 4 instrument amplifier process; differential instrumentation amplifier, High Pass Filter (HPF) with 3 stage filters, Low Pass Filter (LPF) with 3 stage filters and Level Shifter circuit. The total of amplifying is 1000 times of gain, with frequency range 0.5-30 Hz. IC OP-Amp OP07 was used for all amplifying process. EOG signal will be read as analog input for Arduino microprocessor, and will interfaced with serial communication to PC Monitor using Processing® software. The result of this research show a differences value of eye movements. Differences signal of EOG have been applied to navigation control of the mobile robot. In this research, all communication process using Bluetooth HC-05.