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Forecasting demand for trends in their introduction phase plays an important role in strategic planning for product manufacturers. Lack of sufficient historical data in the early stages of a trend makes it difficult for standard time series and statistical methods to do a robust forecast. In this paper, we have proposed a novel approach to forecast the demand of emerging trends. Our methodology involved using Dynamic Time Warping (DTW), a pattern matching algorithm to identify similar trends for historical matching time frames, and used as leading indicators in a regression model to forecast demand. The forecast accuracy of these models was found to be significantly better when compared with popular forecasting methods like Autoregressive Integrated Moving Average (ARIMA), Prophet, and Long Short-Term Memory (LSTM). We have taken the Food and Beverage industry as an example application area to explain our methodology.

Ferrite Assisted Reluctance Synchronous (FA-RelSyn) Motor is establishing itself as a potential alternative compared to the conventional Induction Motor based variable speed drives, owing to its improved torque performance, wide range of speed of operation and high efficiency. Also, the inexpensiveness compared to its rare earth magnet counterparts (Permanent Magnet Motors) makes it a possible choice for Electric Vehicle (EV) application. This work is intended to analyze the performance of FA-RelSyn Motor for EV application using Finite Element Analysis (FEA). The design process involves Electromagnetic analysis along with co-simulation using PSIM for drive implementation, Thermal and Vibration analysis as per New European Drive Cycle requirements.

With continuous monitoring and sensing, millions of Internet of Things sensors all over the world generate tremendous amounts of data every minute. As a result, recent studies start to raise the question as whether to send all the sensing data directly to the cloud (i.e., direct transmission), or to preprocess such data at the network edge and only send necessary data to the cloud (i.e., preprocessing at the edge). Anomaly detection is particularly useful as an edge mining technique to reduce the transmission overhead in such a context when the frequently monitored activities contain only a sparse set of anomalies. This paper analyzes the potential overhead-savings of machine learning based anomaly detection models on the edge in three different IoT scenarios. Our experimental results prove that by choosing the appropriate anomaly detection models, we are able to effectively reduce the total amount of transmission energy as well as minimize required cloud storage. We prove that Random Forest, Multilayer Perceptron, and Discriminant Analysis models can viably save time and energy on the edge device during data transmission. K-Nearest Neighbors, although reliable in terms of prediction accuracy, demands exorbitant overhead and results in net time and energy loss on the edge device. In addition to presenting our model results for the different IoT scenarios, we provide guidelines for potential model selections through analysis of involved tradeoffs such as training overhead, prediction overhead, and classification accuracy.

This work deals with the performance analysis of segmented rotor Switched Reluctance Motor (SRM) for cooling fan application. The configuration has the merits of improved average torque and efficiency in comparison with the conventional SRM. In order to highlight the structural characteristics of the configuration, vibration analysis has been carried out to estimate the natural frequency of vibration. Transient analysis has been performed to predict the displacement due to electromagnetic forces. The results reveal that while the segmented rotor configuration exhibits superior electromagnetic characteristics the displacement due to magnetic forces is high.

The most powerful active phased array MST radar (AAMSTR) having 360° beam agility, modularity, multi-channel capability and built-in scalability has been realised at NARL, Gadanki, India (13.45°N, 79.18°E). Several latest technologies has been implanted in the radar development, such as placing state-of-the-art high power solid state Transmit-Receive modules (TRM) near antenna elements to minimize cable losses, complex distributed control signal system to each TRM through optical fiber, flexible antenna array configuration to support upto a maximum of 64 channels with direct digital receiver system for Spaced Antenna (SA) and Interferometry/ Imaging applications. The system has been validated for its scientific usage in a variety of experimental modes, like Doppler beam swinging (DBS) and Velocity-Azimuth-Display (VAD) modes in the troposphere. The initial results are found to be very encouraging. The multi-receiver capability has been tested with different array apertures and base lengths for interferometry and spaced antenna experiments. The improved detectability and high resolution capabilities with built-in flexibilities caters the present and future scientific requirements of the atmospheric research community. In this paper, we present the system configuration with multi-channel facility, validation of products, new capabilities and the first results obtained using the Active Phased Array MST Radar.

Transport Layer Security (TLS) is the de-facto protocol for secure communication in Internet of Things (IoT) applications. However, the processing and energy demands of this protocol are two essential parameters that must be taken into account with respect to the resource-constraint nature of IoT devices. In this paper, we study the resource consumption of the TLS handshake using a testbed in which an IoT board (Cypress CYW43907) communicates with a Raspberry Pi server over an 802.11 wireless link. Although TLS supports a wide-array of encryption algorithms, we focus on the performance of TLS using three of the most popular and robust cipher suites. Our experiments show that ciphers using Elliptic Curve Diffie Hellman (ECDHE) key exchange are considerably more efficient than ciphers using Diffie Hellman (DHE). Furthermore, ECDSA signature verification consumes more time and energy than RSA signature verification given ECDHE key exchange. The studies of this paper help IoT designers choose an appropriate TLS cipher suite based on application demands, computational capabilities, and available energy resources.

In current scenario, power system utility faces the enormous power demand, due to that, deregulation concept has been emerged. This work depicts the Automatic Generation Control (AGC) of two area interconnected (thermal-thermal) deregulated power system using fuzzy logic controller. AGC is a system, for adjusting the power output and change in frequency of a generator in the power plants, in response to changes in the sudden load. The controller aims to adjust the power output at the nominal values. Due to lack of control performance with nonlinearities in the conventional PID controller, in this work consider as an intelligent controller such as Fuzzy Logic Controller is proposed. Fuzzy logic controller is used to restore the frequency and tie line power to its nominal value with minimum computational effort in the shortest possible time as well as handling the system nonlinearities. The Generator Rate Constraint (GRC) is also considered for the test system.

The use of Synchronous Reluctance (SynRel) Motor Drives in various applications are gaining importance in recent times, as result of its very high efficiency. It can be visualized as a real alternative in comparison with typical variable frequency electric drives due to the features such as presence of rotor with high thermal stability and easy serviceability. Research has been steered globally and several remarkable developments have been put forward in the literature. An effort is made to provide a detailed overview of the technology status and developments in SynRel drives reviewing the aspects of modeling, optimization, thermal analysis and vibration analysis.

In the current scenario, power consumption, speed, size and heat dissipation are the huge challenge in the semiconductor industries. When the size of the single computing element is reduced then the speed can be improved and also if the power dissipation is reduced then the heat dissipation will be less. The possible solution for these two problems is the Reversible Logic and Quantum Cellular Automata (QCA). The Reversible Logic is considered to be the promising technology to the future Quantum computer technologies. The Reversible Logic gates prune the power dissipation to a larger extent. In this paper Novel Reversible Gates are proposed with Reversibility and Universality. The Arithmetic and Logic Unit (ALU) is designed with the proposed Reversible Gates in Reversible Logic. The designed Arithmetic and Logic unit is evaluated in QCA with the required specifications. The Arithmetic and Logic Unit is designed by setting the control inputs for each unit. The parameters taken into account are Quantum Cost (QC), Garbage Outputs (GO), Constant Inputs (CI), Area, Number of Cells and Simulation Time. The proposed ALU adopting Novel gates finds utilization in low power applications. Also it can be used as the module in the Quantum computers due to its reduced Quantum Cost and Garbage outputs. The Proposed design extends its applications over Quantum Computing, Optical Computing, Nanotechnology and DNA mapping.

In Power system, as the load changes the terminal voltage of the generator will also change. Automatic voltage regulator plays a major role in maintaining the constancy of the voltage. Automatic voltage regulator regulates the voltage with the help of controller to maintain the voltage stability of the power system. Two degree of Freedom Controller optimized by Particle Swarm Optimization will help to adjust the exciter voltage to ensure stable and efficient response due to transient changes in load. The controller used is robust over wide range of operating conditions and it is simple in its structure and easy to implement. The gains of the controller is optimized by the Particle Swarm Optimization to achieve a better dynamic performance, to reject the disturbance due to load and to improve the robustness with respect to parameter uncertainties which may be caused due to load variation, aging of the equipment, dielectric losses etc.

The development of a semi-autonomous intimation system to parents about the presence of their child in school or college campus is the objective of this Project. If a student bunked his/her class or abducted from school or college, their parents might know that after 6pm only. Here we proposed a new solution to send quick intimation to their parents about the presence of students through school or college bus at 9.30am. By this we can track the children and save them early if any mischief is happening. For this we are using an RFID reader, GPS tracker and GSM module along with an Arduino mega 2560 and its software. RFID readers can read the RFID tags of the students. GSM system is used to send their presence to their parents through SMS. To achieve this, a passive or active tracking device with GPS is used. Passive devices store GPS location, speed and time. Once the vehicle returns to a predestined point, the device is removed and the data downloaded to a computer for evaluation. By this we can get arrival and departure locations of the students. Active devices also collect the same information, but usually transmit the data in near-real-time via cellular or satellite networks to a computer or data center for evaluation. It is used to track the location of a vehicle from organizing itself. This electronic document is a “live” template and already defines the components of your paper [title, text, heads, etc.] in its style sheet.

Renewable energy resources such as wind and solar are more widely used for power generation. Photovoltaic panels are used to convert solar energy into electrical energy. Solar energy can be used for both stand alone and grid side applications. Grid tied systems are connected to electrical grid and allow residents of building to use solar energy. The photovoltaic system consists of PV panels connected through DC-DC converter and DC-AC inverter to the grid. The IV and PV characteristics of PV panels are used to determine the MPP. The MPPT algorithm used for tracking maximum power is incremental conductance algorithm. In addition to operate at the international standards, three phase PWM inverter with PI controller is used. This paper deals with the grid interaction of 10kW panel and the study of real power flow from the source to the utility grid.

Luo Converters which use voltage lift technique to provide high gain is a topic of research interest. They are used in motor drives, telecom, automotive applications and as radar and electronic warfare in military. In this work, mixed signal behaviour of constant frequency controlled PWM Ultra Lift Luo Converter is analyzed. The closed loop transfer function is derived using Perturbation theory, Sample-Hold theory and Modified Pade Approximation method. To get the margin of stability accurately, Slope Compensation is used. The expressions of the control current of the inner current loop of Converter with and without slope compensation are derived. Finally the controller is designed using PSIM 9.0 and SMARTCTRL 1.0 software and stability is analysed.

The photovoltaic (PV) energy and its conversion into electrical energy has a raising importance in the renewable energy marketplace. It is essential to harvest the maximum power from the PV arrays since they have very low conversion efficiency. This process requires the power electronic converter as the power conditioning device. The quasi Z-source inverter is chosen as power conditioning device because of its capability of boosting and DC to AC conversion in single stage. An improved incremental conductance maximum power point tracking algorithm is developed with the aim to prevent the bewilderedness during rapidly changing solar irradiation. This algorithm controls the shoot-through duty cycle of the inverter to attain the maximum power point of the PV array. A novel modified space vector pulse width modulation technique with four shoot-through states is proposed for the inverter to control the inverter. Simulation and experimental results are provided to establish the performance of the proposed system. The comparison with the conventional algorithm is also presented.

This paper outlines performance prediction of 6/3 Switched Reluctance Motor (SRM) with flux reversal free stator. The performance analysis of the motor is done under both electrical and mechanical aspects. In electrical regards, the electromagnetic analysis is done in static and dynamic conditions. This predicts the flux path, flux distribution and elimination of flux reversal in the stator, which act as the main concern with the vibration that leads to acoustic noise. The mechanical traits, simulates the motor in both structural and thermal aspects. The vibration analysis is done in modal as 2D and 3D for predicting the natural frequency of motor while the thermal analysis predicts the temperature rise in the motor.

Quantum Cellular Automata (QCA) is a promising future to the CMOS technology with ultra operating speed and low power consumption. The realization of QCA with Reversible Logic is the Green Computing. A router is the key component in the internet core for transmitting data packets. Being the technology beyond CMOS, the work has been proposed to design a Router in QCA. In addition to that, crossing in Router architecture is done in Multilayer with reversible logic. This proposed architecture guarantees efficient data routing in Router. Also it provides reduced cell area, high operating speed, and minimum complexity.

A new IEEE 1451.4 standard for a smart transducer interface defines the concept for adding self-identification technology to traditional analog sensors and actuators. Numerous manufacturers' offers 1451.4 sensors, which are often called TEDS sensors. Tools for the development of these sensors are not yet widely available. In this work, a tool for development of smart sensor fully compliant with the IEEE1451.4 standard is developed. Mixed-mode interface with auto detection of One-wire memory device has been developed by the use of Amicus Board which has PIC 18F25K20 microcontroller. To demonstrate the functionality and efficiency of developed tool, bridge sensor (load cell) is implemented and also analog temperature sensor is converted to smart transducer for Industrial automation. Details of sensor implementation and test results are presented. To validate, a smart transducer controller is made and tested.

In an electrical Power system, the current drawn by power converter devices from the line is distorted resulting in a higher Harmonic Distortion and low Power Factor (PF). Hence, there is a continuous need for power factor improvement and reduction of line current harmonics. Here, an Active Power factor Correction method is proposed to improve the PF and to regulate the Output Voltage of a Single Phase AC to DC Boost Converter. Small signal modeling of single-phase full bridge rectifier and its modes of operations are discussed. The inner Voltage loop is controlled by PID controller and sliding mode control is used for controlling the Outer current loop. An overall comparison is made for various voltages and loads. Output voltage tracking is also analyzed. The main aim of the proposed work is to maintain the power factor above 0.95 and to reduce the total harmonic distortion below 5%. Simulation is carried out using MATLAB software.

The circuits like Logic gates, Adders, Multipliers are the basic building block of the digital circuits. These combinational circuits can be designed by using the concepts of the reversible logic. The reversible logic is either a physically reversible or logically reversible. In this paper the combinational circuits are logically reversible. One of the applications of the reversible logic is Quantum Cellular Automata (QCA). QCA has attracted feature of extremely small feature size (at the molecular or even atomic scale) and its ultra-low power consumption, making it one candidate for replacing CMOS technology. Thus the design and realization of the Basic Logic gates and Combinational circuits like ripple carry adder, serial adder, multiplexer are done by using the concept of Quantum Cellular Automata. Also, the area and cost of the QCA system is reduced with the help of Coplanar architecture arrangement of cells. The paper is organized as follows; the section one gives the overall introduction about QCA, Clocking of QCA and Wires in QCA. Section two gives information about the basic logic gates. In Section three, design and Simulation of Combinational circuits like half adder, full adder, ripple carry adders and multipliers are discussed. At last the Comparison of Quantum cost of the above designs due to Coplanar architecture was elaborated.

Brushless dc (BLDC) motor drives have gained significant attention due to their merits such as high efficiency, high dynamic response, high reliability etc. From the literatures, it is understood that there has been remarkable developments evolved in application of the feedback controllers for both the BLDC motor drive's speed and current loops. The recent investigation and innovations in the pulse width modulation (PWM) methods are not encompassed in BLDC drives. The conventional PWM results mechanical vibration and acoustic noise, and limit the application scope the BLDC drives. This is due to the incapability of deterministic PWM in spreading the harmonic power. This paper presents random pulse width modulation (RPWM) for BLDC motor drive with better harmonic power distribution. The randomness is introduced in carrier wave by toggling between triangular wave (+fc) and its inverted form (-fc). The performance of the proposed RPWM is validated by using MATLAB software and results such as harmonic spread factor (HSF), total harmonic distortion (THD), and acoustic noise spectrum are presented. The comparison of results with the conventional PWM demonstrates the superiority of the proposed PWM.

This paper describes Artificial Neural Network (ANN) based speed and current controller design for Permanent Magnet Synchronous Motor (PMSM).The neural network controllers are designed to translate the speed and current errors into respective driving voltage signals to the input of PMSM. A multilayer feed forward neural network is trained using Back propagation learning algorithm to estimate the driving voltage input of PMSM. To analyze the performance of neural controller, the overall system is simulated under various operating conditions. The simulation results compared with conventional P-I controller for different conditions highlight the performance of the proposed controller in steady state and transient conditions.

This paper depicts an enhanced Particle Swarm Optimization (PSO) algorithm for Brushless DC Motor (BLDC) design. The algorithm is applied to shape optimization of a 120 W BLDC motor using a multiobjective optimization problem. While the objectives are maximization of average torque and minimization of cogging torque in the BLDC motor, magnet length, air gap and stator slot opening are considered as the design variables. The results obtained using the PSO algorithm indicate that it is capable of giving better design solutions when compared and investigated with those obtained from Genetic Algorithm (GA) and Finite Element Analysis (FEA) based simulation. The results also demonstrate that the proposed algorithm is more effective and outperforms GA in terms of solution quality, accuracy, constraint handling and computational time.

Motion detection plays a primary vital part in the process of extraction of information regarding the moving objects and utilizes the stabilization in functional areas, such as tracking, classification, recognition etc. In this paper, we propose an extended view and precise approach to motion detection for the automatic video surveillance system. This method accomplishes a complete detection of any moving object by involving substantial modules such as Background subtraction method, Dynamic Optimization threshold method to gain a vivid picture of the moving object, Morphological filtering is introduced to eliminate the noise and hence Background disturbance problem is solved. Then the paper presents tracking and cropping of the detected moving object. The visual inspection analysis of this method of Detecting, Tracking and Cropping of moving object has gained a better result.

Quasi-Z-source inverters are educed with additional advantages of continuous current from source, lower switch stress and smaller component ratings in addition to buck/boost capability, inversion and single stage conversion of the basic topology of Z-source inverters. This work proposes a novel topology of cascaded quasi-Z-source multilevel inverter. The working and switching states of the proposed topology are explained. Modified multi-carrier bipolar PWM techniques are explicated for the proposed inverter. A five level quasi-Z-source inverter is designed, modeled and the simulation results are obtained. The total harmonic distortion and individual harmonic contribution in each pulse width modulation techniques are performed.

Switched Reluctance Motors (SRMs) have evolved to represent interesting solutions for variable speed drive applications, due to their low cost and high dynamic performance capabilities. On the other hand, a number of less positive characteristics, such as their nonlinear behavior, and the existence of a significant torque ripple in the output also accompanied by audible noise, make the control problem associated with their operation a challenging task. These things limited their deployment in practical applications. The motivation of the present work is to simplify the control of SRM using Neural Network based control, to cut down the complexity and cost so that it can be accepted as a viable variable speed drive in general and a preferred drive for industrial and domestic applications This paper deals with the neural network based control for 8/6 pole Switched Reluctance Motor. Here, the neural network based controller, which is used to obtain the optimum turn on and turn off angles to minimize the torque ripple and speed ripple. The machine is modeled and simulated using Matlab / Simulink environment. The output response shows good dynamic behavior of the system.

This paper proposes a novel method of reactive power management and pricing in the background of re-structured electricity market. Financial compensation for reactive power support provided by the generators is considered in this paper. Those generators which have re-scheduled its real power generation to provide more reactive power are eligible for payment. The system operator has to find the optimum re-scheduling and minimum payment. This procedure is illustrated using 6 bus system and IEEE 30 bus system. The results show that cost of reactive power is optimum for the given conditions.

This paper investigates the performance of Dynamic Voltage Restorer for compensating different voltage sag levels with various faults and to reduce the Total Harmonic Distortion during the mitigation process. The DVR is implemented with three phase voltage source inverter and is connected at the point of common coupling in order to regulate the load side voltage. The compensation is based on PI and Mamdani Fuzzy Controller. Extensive simulation studies under different magnitude of sag for faults on load side for balanced and unbalanced conditions are conducted using fault generator. Simulation result analysis reveals that DVR performs perfectly with PI and Fuzzy control approach. In addition, capability and performance of DVR for various energy storage capacities and injection transformer rating are also analyzed. The performance of these controllers are validated with simulation results using Matlab/Simulink.

This paper presents an approach for online evaluation of loadability limit of Pool Model with Thyristor Controlled Series Compensator (TCSC) for various load patterns using Back Propagation Neural Network (BPNN) with optimal feature set. Differential Evolution (DE) algorithm is employed to find out optimal location and control of TCSC. This approach uses AC load flow equations with constraints on real and reactive power generations, transmission line flows, magnitude of bus voltages and TCSC settings. The input parameters are real and reactive power loads at all buses. The BPNN is trained through off-line simulation using DE algorithm and tested with new load patterns. The optimal feature set for training BPNN is obtained by a wrapper model of feature selection called Sequential Forward Selection (SFS). Simulations are performed on 39 bus New England test system. The performance of the proposed model is compared with unified BPNN trained with full feature set. The selection of optimal features with SFS has significantly reduced the training time of BPNN with minimal Mean Squared Error (MSE) for the evaluation of loadability limit of pool model with TCSC.

Biometric watermarking refers to the process of incorporating the handwritten signatures or fingerprints in watermarking technology. In this paper, we present a novel statistical attack invariant watermarking scheme to embed an offline handwritten signature invisibly in the host as a notice of genuine ownership. The scheme employs Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) with Least Significant Bit (LSB) encoding for watermark insertion, which is to be known as DCT-SVD scheme. Experimental results confirm that DCT-SVD scheme is robust to statistical attacks even in the presence of deliberate distortions.