Security is a very important aspect of a smart system as one of the core smart city components. That is why the concept of smart cities must pay special attention to the security of the individual Internet of Things (IoT) components that make up smart cities. For an IoT system to operate smoothly, all participants in the communication must permit the system to collect information about them - e.g., on the street by various sensors, at home by various devices, such as mobile devices, etc. Such a large set of data collected about the citizens in a smart city is a major security issue.

Abstract
Any rotating object with variable velocity about a fixed point generates centrifugal and tangential accelerations that are the components of the inertial forces. The known textbooks of engineering mechanics contain chapters for the acceleration of a rotating object that is presented by not accurate mathematical processing. Such a mathematical model for the acceleration of the rotating object yields the incorrect result that leads an unjustified increase in the size of the mechanical component of machines. In engineering, rotating components of machines is a subject of exact computing of inertial forces which non-observance reflects on the reliability of their work. This work considers an analysis of the acceleration of a rotating object at a fixed point and presents the precise mathematical model for its acceleration.

Keywords: Radial and Tangential Acceleration; Rotating Object; Fixed Point

Abstract
The space flights of the astronauts discovered a new physical phenomenon that is recurrence inversions of the rotating objects at the condition of weightlessness. This physical effect is an object of stare studying by scientific researchers of the entire world. They published only a dozen manuscripts with approximated and numerical models and assumptions because of complex problems. The analytical approaches of the new gyroscope theory enabled the description of the physics of the phenomenon of the rotating object in the weightless conditions of space flights. On the rotating object, at the free flight, are acting the inertial forces generated by its circular motions around the earth and its rotating mass.

Keywords: Inertial toque; Gyroscope theory; Mathematical model; Inversion

Abstract
The present paper aims to design an active vehicle system suspension by modification passive suspension into consideration the chassis is flexible to provide us the actual suspension image to make the best performance of the car and ride comfort. Creation of a State-Space half-car Model from a Finite Element, Model achieved by use MATLAB and Controlled by (LQR) Problems with its parameters Q and R which used in the determination of optimal car suspension systems design. The challenge is minimizing the chassis deflection; displacement and reduce the acceleration of suspension vibration. It is shown in our result that the model response to the Q and R-value is positive.

Keywords: Finite Element method; Beam equation; alf car vehicle; Simply supported beam

Abstract
A DeepGen network is proposed for voice conversion, which is the process of modification of a speech utterance by a source orator to that of a target orator, preserving the linguistic contents. Automatic dubbing is an application of speech processing which facilitates the modelling of the large variability of pitch. The proposed DeepGen network automizes voice conversion by taking blocks of consecutive frame-wise linguistic and fundamental frequency features. This block-wise approach models temporal dependencies within the features of the input block. Voice conversion, which is also called as voice cloning has always required significant amount of recorded speech but the proposed DeepGen network intends to convert one voice to another using a relatively smaller set of speech samples by bootstrapping samples from a larger speech dataset. The proposed generative model is a variant of the convolutional generative model with encoder and decoder blocks that bring into line the hidden structures of the
feature spaces from the source and target voices on a two-stage training process. An attractive and efficient voice conversion is thus obtained in the real-world scenario using the proposed DeepGen network. The novelty of the work lies in the induction of a deep learning generative network for cloning voice in Tamil language.

Keywords: DeepGen network; Voice Conversion; Generative Network; Convolutional generative model; Feature spaces