International Journal of Engineering and Applied Physic

    Detection of Fake News Using Machine Learning

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    For some past recent years, largely since people started obtaining quick access to social media, fake news have became a serious downside and are spreading a lot of and quicker than the true news. As incontestable by the widespread effects of the big onset of fake news, humans are incapable of detecting whether the news is genuine or fake. With this, efforts have been made to research the method of fake news detection. The most popular and well-liked of such efforts is “blacklists” of sources and authors that don't seem to be trustworthy. Whereas these tools area helpful, so as to form a more complete end to end resolution, we also account for tougher cases wherever reliable sources and authors unharnessed false news. The motive of this project is to form a tool for investigation the language patterns that characterize wrong and right news through machine learning. The results of this project represent the flexibility for machine learning to be helpful during this task. We have made a model that detects several instinctive indicator of right and wrong news

    Static bending analysis of two-directional functionally graded beam using simple Timoshenko beam elements

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    This article presents the static bending of two-directional functionally graded (FG) beam by using simple Timoshenko beam elements. The Matlab code developed based on the finite element formulation is validated by solving two-directional FG beam problems under distributed load and two boundary conditions. Numerical results which are in terms of maximum normalized transverse deflections are compared with the analytical solutions and the results from previous studies. Besides, the shapes of transverse deflection and rotation along the length of beams are also depicted in this article to provide specific views about the static behavior of proposed structure

    Arduino implementation of MPPT with P and O algorithm in photovoltaic systems

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    Maximum Power Point Tracking (MPPT) method frequently used in photovoltaic systems to maximize photovoltaic power generation Generator (PVG). The principle of these technologies is making PVG reach the maximum power point (MPP), depending on environmental factors such as solar irradiance and ambient temperature, ensure the best power transfer between PVG and load. In this article, we present the implementation of a MPPT command using the Arduino nano. The proposed MPPT command is based on Perturbation and Observation Algorithm (P&O). The PV system is simulated and studied using ISIS Proteus software. Results show that the algorithm shows good results in time response and oscillations

    Study and design the circuit for piezoelectric vibration energy harvester to charge a datalogger

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    The studies presented in this paper focus on the recovery of vibrational energy using a piezoelectric beam. The device implemented in this work is quite far from industrial realities, but it has the advantage of being easily reproducible and inexpensive. In a first step we will design a circuit for mechanical Energy Harvesting. In practice these systems recover the little energy from ambient vibrations in order to power low consumption electrical systems (typically from a few ?W to mW). After comparison with a basic recovery system (diode bridge) examined both experimentally and by simulation, the model is used on a more efficient recovery system. This study focuses on non-linear circuit topologies, and the improvement of the recovered power compared to the standard technique (STD) To charge a datalogger. The simulation results of this system evaluate an improvement of 325% compared to the standard system

    Sales Prediction of a Pharmaceutical Distribution Company

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    The study aims to find an appropriate model to extract insights from the sales of a Pharmaceutical Distribution Company (PDC) and make it available in an interactive and readable manner for the company. In PDCs, it is highly important to obtain a good approximation of the medicine needs, due to the short shelf life of many medicines and the need to control stock levels. The presented method is a combination of analysis and interactive visualization tools along with prediction. In this paper, we explore the use of Support Vector Regression algorithm for the sales prediction of individual products. The proposed model helps to present the sales data in a better way such that understanding the trends and seasonality becomes easier for the PDCs. The dataset has information of hourly, daily, weekly and monthly sales of the drugs and hence the end results also give us a likely classified understanding of the sales. The study of the results obtained, suggest that the proposed model may be considered appropriate for product sales prediction

    Measurement the effects of temperature and fiber orientation on vibration of functionally graded beam

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    This paper concerned with analytical approach to study the thermal vibration of fiber orientation functionally graded (FOFG) beam, that fibers`oriented angles are variable and graded in the thickness direction of the beam. Uniform thermal distribution considered in the entire beam and properties of fiber orientation functionally graded (FOFG) beam considered as the temperature-dependent element. Symmetrical, asymmetrical, and classical distribution types for the mode of fiber angle presented in the thickness direction of the beam continuously. Equilibrium Equations derived from first- order shear deformation theory and Hamilton principle. Simply supported boundary condition is considered for both edges of the beam.Eneralized differential quadrature method usedto solve the system of coupled differential Equations. To study accuracy of the present analysis, a compression carried out with a known data. The results shows that different parameters such as thickness to radius ratio, effect of temperature variations, model of fibers angle variations and power-law index affected on the natural frequencies

    Selection of material through "Thermal-Stress" analysis on Fusion 360 for a brake rotor

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    The braking systems are used for reducing speed or halting the vehicle. The brake rotors experience high frictional forces causing their wear and tear; kinetic energy is converted into heat energy which increases the temperature of the rotor. If an appropriate amount of heat is not dissipated it can deteriorate the quality of the rotor. This paper aims to determine better material from the traditionally used Grey Cast Iron. Heat dissipation, deformation and safety factor are determined by the physical and thermal properties of the material. To select the best material, ‘Thermal-Stress’ analysis is performed on Fusion 360 as a brake rotor experiences not only high torque but also high temperature at the same time. The results are conferred based on the various criteria discussed in the paper such as material properties, the temperature generated and FEA. The tests lead to Ti-6Al-4V (Ti Grade 5) as the best material

    Adjustable Radio Technology Using BPSK Modulation

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    This research paper proposes a technique called a radio gating, called an RF gating, which consists of a symbolic change of the active time radio (ATR) on the RF foreground. This technique is particularly suitable for adapting the receiver's energy consumption to performance requirements without changing its architecture. In the specific case of binary turn-key signalling, the effect of this method on the Bit Error Rate (BER) performance is studied (BPSK).In existing it Minimum shift keying signalling will used in RF Power gating technique, it will have, low efficiency, and more bit error rate. In this paper to modified the Minimum shift keying technique to Binary shift keying technique. Finally this work is implemented in VHDL, and synthesized with Xilinx FPGA Vertex-5, and shown the area, power and delay variations

    Uncertainty Principles for the Dunkl-Bessel type transform

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    The Dunkl-Bessel type transform satisfies some uncertainty principles similar to the Euclidean Fourier transform. A generalization of Beurling’s theorem, Gelfand-Shilov theorem, Cowling-Price’s theorem and Morgan’s theorem are obtained for the Dunkl-Bessel type transform

    Shape Classification Via Contour Matching Using the Perpendicular Distance Functions

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    We developed a novel shape descriptor for object recognition, matching, registration and analysis of two-dimensional (2-D) binary shape silhouettes. In this method, we compute the perpendicular distance from each point on the object contour to the line passing through the fixed point. The fixed point is the centre of gravity of a shape. As a geometrically invariant feature, we measure the perpendicular distance function for each line that satisfies the centre of gravity of an object and one of the points on the shape contour. In the matching stage, we used principal component analysis concerning the moments of the perpendicular distance function. This method gives an excellent discriminative power, which is demonstrated by excellent retrieval performance that has been experimented on several shape benchmarks, including Kimia silhouettes, MPEG7 data set
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