Advances in Communication, Devices and Networking

In this paper, modelling of thermoelectric and conduction mechanism of multilayer graphene nanoribbon (GNR) has performed taking various temperatures. The coordination of various elements H–H–H, C–C–H was calculated using radial distribution function. The current–voltage curves GRN were estimated with variation of temperatures from 4 to 3400 K. To evaluate the conduction mechanism and conductance with different applied voltage dI/dV versus voltage has been performed with varying of temperature. Moreover, the thermoelectric coefficient of GRN with different energy at different temperature has been estimated.

In this paper, a technique for temperature stabilization of pulsed IMPATT oscillator has been described. The different electrical parameters of the designed oscillator at W band are studied at extended ambient temperature. Variation of oscillation frequency over extended temperature is determined by the intersection point of negative of device reactance $$ \left| {X_{{\text{D}}} } \right| $$XD and circuit reactance $$ \left| {X_{{\text{C}}} } \right| $$XC. The analysis matches closely with the experimental results obtained. It is shown that the output frequency of the oscillator can be stabilized by changing the slope and amplitude of the biasing current pulse. A control circuit with integrated temperature sensor is designed for varying the current pulse amplitude dynamically over extended temperature. The designed IMPATT oscillator with integrated control circuit shows stabilization of oscillation frequency along with the considerable improvement in variation of peak power and chirp bandwidth over extended temperature.

Tailor-made heterostructural nanoform based on multiple low-dimensional frameworks not only offers manifold functionalities also bestows several novel interface phenomena. From the broad usage window of heterostructures, photocatalysis is very significant nowadays. In this work, we have realized oxide-based hybrid comprising 1D TiO₂–ZnO nanoform on flexible carbon cloth via facile chemical approach. Successful presentation of the hybrid over foldable platform was established via FESEM which discloses its typical morphology. To attain a clear insight of the elemental composition EDX analysis and elemental mapping of the hybrid was also carried out. Catalytic activity of the synthesized samples under UV light illumination was inspected taking Rhodamine B as the model contaminant where the heterostructure exhibited much-improved performance as compared to the individual structural building block. Prolonged separation time of the photogenerated charge carriers in heterostructure ensures enhanced photocatalytic activity. Such work on morphology-induced catalytic performance enhancement will inspire the researchers toward creative designing of different photocatalyst comprising other multifunctional oxides.

The amplification of super-Gaussian pulses in a system of bit rate 40 Gb/s with duty cycle 0.5 by traveling-wave semiconductor optical amplifier (TW-SOA) is investigated. The carrier wavelength of the super-Gaussian pulse is 1550 nm. Simulative results related to pulse broadening due to nonlinear self-phase modulation (SPM) phenomenon are analyzed and compared. This paper analyses the issues of super-Gaussian pulse and spectrum distortion in semiconductor optical amplifiers (SOA). It is shown that the amplified super-Gaussian pulse shapes and their spectra are depended on the length of SOA and compared the results with the published work.

This paper presents the design of a current-starved VCO using pseudo-NMOS topology. The proposed design has better phase noise, lower power consumption as compared to traditional CSVCOs and the number of components are also less (8 MOSFETs are reduced). The proposed design consists of five inverter stages, and pseudo-NMOS topology is used to replace the current sourcing PMOS blocks, thereby reducing power consumption to 155.7 μW for fundamental frequency of 1.8 GHz. The simulation results depict that the proposed CSVCO has better phase noise and lower power consumption as compared to other ring VCO topologies. The circuit performance is validated in Cadence Spectre using 180 nm CMOS technology at a supply of 1.8 V. The analysis also shows that for this CSVCO, the phase noise is (−103.73 dBc/Hz) @1 MHz offset frequency and (−124.97 dBc/Hz) @10 MHz offset frequency.

Adders are the integral part of arithmetic logic units in digital system. Performance of the adder circuits decides the performance of those circuit and systems. Full adders are designed either in conventional approach or hybrid approach. In conventional approach, only one logic style is used, whereas in hybrid approach, two or more logic styles are used. A performance analysis between conventional and hybrid 1-bit full adder circuits is presented in this paper. In conventional design, complementary metal–oxide–semiconductor (CMOS) full adder, complementary pass logic (CPL) full adder, and transmission gate full adder (TGA) are the most popular. In this paper, CMOS full adder and CPL full adder are reported. The hybrid adder reported in this paper is designed using CMOS logic and transmission gate (TG) logic. The circuits are implemented using Cadence virtuoso tools with 180 nm United Microelectronics Company (UMC) technology. From the pre-layout simulation, performance metrics such as power, speed, and power delay products were computed. Performance of each of the circuits in terms of power, speed, power delay product (PDP), and area requirements in terms of transistor counts for the design is then compared.

Recent IC technology emphases on the fabrication of ICs as more area optimization and low-power practices. Among all the arithmetic operations, the most heavily used one is multiplication that measures more frequently in signal processing applications. Multiplication is a very hardware-focused subject, and we as customers are mostly worried with getting low power, smaller area, and higher speed. The most important concern in classic multiplication mostly realized by shifting and adding is to accelerate fundamental multi-operand addition of partial products. In this literature, the Booth multiplier implementation is presented with different adder architectures like ripple carry adder and carry look ahead adder and carry select adder. The time delay, area, and power have been investigated for different adders.

This paper presents an analysis of structural, electronic, and optical properties of pristine anatase titanium dioxide (TiO₂) using orthogonalized linear combinations of atomic orbitals (OLCAO) basis set under the framework of density functional theory (DFT). The lattice constants such as a and c, band diagram, density of states (DOS) have also been studied. The band gap shows indirect nature around the fermi level in anatase TiO₂. Density of states shows a contribution of Ti_3d and O_2p orbitals in conduction and valence band regions. From the analysis of optical properties, it is seen that the anatase TiO₂ supports the interband indirect transition from O_2p in valence region to Ti_3d in the conduction region. All the optical properties are discussed in detail under the energy range of 0–16 eV. Further, we have compared the results with previous works as well as with the experimental results. We found that DFT-based simulation results are approximation to the experimental results.

This present work encompasses the analytical modeling of a front high-K gate stack dual-material tri-gate SON MOSFET. By solving the three-dimensional Poisson’s equation, the expression for surface potential of the proposed device is obtained. In addition, the electric field of the device is also calculated. The results obtained are compared with the model’s single-metal counterpart. The extent of agreement between the analytical results and simulated results obtained from a 3-D device simulator, namely Atlas, Silvaco, is quite good that validates our proposed model.

In this paper, Pd modified and unmodified ZnO thin film sensors were prepared by sol-gel process for detection of hydrogen (H₂) gas. Spin-coating (1200 rpm, duration 10 s) method was used to deposit the sol on above the SiO₂/p-Si substrate. The surface morphology was analyzed by field emission scanning electron microscopy (FESEM). The gas sensing characteristic was measured by 50–250 °C operating temperature and 100–3000 ppm H₂ gas concentration. Maximum sensitivity was found 74% at operating temperature 150 °C for 1000 ppm of H2 gas concentration. Stability of Pd modified and unmodified ZnO thin film sensors has been measured at operating temperature 150 °C. Pd modified ZnO thin film sensor with Ag contact was found highest sensitivity compared to the unmodified ZnO thin film sensor with Ag contact.

In most of digital signal processing application, processing elements like adders form the basic building blocks of filtering and analysis of signals. CMOS-based adder circuits suffer from several problems like leakage current and threshold voltage variations. In this paper, a novel design of an adiabatic FinFET-based low-power processing element using complementary energy path adiabatic logic (CEPAL) in 32 nm technology is proposed. The proposed processing elements are CEPAL–FinFET-based adiabatic half adder and full adder. FinFET-based circuits are designed for deep submicron VLSI designs in signal and image applications. The FinFET design has low power consumption when combined with adiabatic design which improves scalability and design flexibility. The proposed FinFET–CEPAL-based adders show a considerable power reduction and low energy consumption with favorable performance improvement. Extensive circuit simulation has been carried out with HSPICE using predictive technology model in 32 nm FinFET technology. The analytical results validate that the proposed design exhibits the energy saving compared to standard bulk CMOS design.

This paper presents an explicit 2D analytical surface potential modeling of Triple Metal Front Gate Stack DG MOSFET with Graded Channel (GC-TMDG MOSFET) to explore the dual benefits of gate and channel engineering techniques. The surface potential profile of the proposed model is derived by solving 2D Poisson’s equation with suitable boundary conditions and also compared with graded channel DG MOSFET and Triple Material DG MOSFET to establish the superiority of our structure. In addition to this, lateral electric field closer to drain end is examined to substantiate the immunity of the device to hot carrier effect. For validation of analytical model, all the results are compared with 2D ATLAS device simulator data.

This paper describes the GaAs MESFET-based S-band (2–3 GHZ) SPDT switch with TTL driver (TTL control). TTL control voltage is needed to select the RF path. At 2–3 GHZ, simulated insertion loss is lower than 0.8 dB and isolation is better than 36 dB. Simulated input return loss is better than 17.5 dB and output return loss is better than 18 dB. For improvement of isolation, extra path is added. When we add extra path then isolation is increased. Simulated improved isolation is better than 43 dB and insertion loss is lower than 0.98 dB. Simulated input and output return losses are better than 14 dB.

In this paper, first time a three-dimensional analytical model of dual-metal triple-gate silicon-on-nothing tunneling field effect transistor (DMTG SON TFET) is presented. This model is derived by solving the 3D Poisson’s equation. Simulation of 3D device lowered the need of parameter fittings. In addition, two different metals form a barrier over the channel region, which restricts reverse tunneling of carrier from drain to source. Choice of two different metals increases the on current and decreases the off current, thus improving the on–off current ratio of this proposed device. The electric field and the surface potential are obtained by solving the 3D Poisson’s equation with proper boundary condition and the drain current is modeled by using the Kane’s model also. The performance comparison of the proposed structure is done with the single-metal SON TFET and double-metal SOI TFET. The 3D analytical results are simulated using SILVACO ATLAS for this structure.

Over the last few decades, researchers have invested enormous research effort into inorganic/organic solar cells like dye-sensitized solar cells (DSSCs) due to its cost-effectiveness and simple fabrication process, over the conventional photovoltaic solar cells made of different materials like Si, Ge, GaAs, GaInPh. In 2012, the solid-state perovskite materials are organic–inorganic metal trihalide materials, having chemical formula ABX3 and having specific crystal structure as calcium titanium oxide (CaTiO₃) revolutionized as the light-harvesting, absorbing materials. In past couple of years, perovskite solar cells have shown significant improvement in terms of efficiency and crossed the 20% efficiency level. There has been a consistent approach among researchers to explore different materials as electron transport layer of the perovskite solar cells to improve the performance of the solar cells. The most common perovskite material used in solar cell is methyl ammonium lead iodide (CH₃NH₃PbI₃) along with top and bottom layer of HTO and ETO. In this work, the toxic material lead iodide (PbI₃) is replaced with tin oxide (SnI₃), and this perovskite material CH₃NH₃SnI₃ introduced with an ETO layer of ZnO has achieved a significant efficiency of 22.90%. In this work, zinc oxide (ZnO) layer is proposed as the electron transport layer for lead-free CH₃NH₃SnI₃-based perovskite solar cells. The proposed structure is “metal contact/spiro-MeOTAD/CH₃NH₃SnI₃/ZnO/TCO/metal contact,” and the structure is modeled using SCAPS simulating tool.

Most desirable part of the electrical machines is insulation. This paper exploits properties of mustard oil which could be the better solution in oil-cooled transformer than traditional petroleum-based mineral oils, as it exhibits better properties of flash point, fire point, and breakdown voltage. Moreover, mustard oil is non-inflammable and non-toxic in nature. Since last century, petroleum-based mineral oil is used as liquid insulating and cooling medium. Besides their good insulating and cooling properties, some environmental factors are also related to them. With the consideration of environmental factors, many researchers are intending to evolve new insulating medium having better properties to replace these presently used mineral oils. This paper mainly emphasizes on the investigation of breakdown strength of mustard oil. The breakdown test is conducted based on Indian standard (IS 6792:1992).

One of the serious challenges that the power sector is experiencing today is unit commitment. The problem becomes more severe when renewable energy is integrated with the convention power station. In the present scenario, renewable energy alone is inadequate to achieve the demand for power. Thus, operating renewable energy coherently with the conventional power station is a major complication. The demanded power must be fulfilled by the generation scheduling under the constraint of irregularities of renewable energy that can be economically availed. Application of GA can be an important tool for solving the problems of unit commitment. Like quadratic programming which is a conventional tool for mathematical optimization, the solution of GA can be reformed by applying its output as initial feasible. With the application of GA, the solution is improved under the constraint of integrating renewable energy with conventional resources.

There has been phenomenal expansion in Indian power sector since independence. The first 765 kV transmission line was commissioned in 2007 in the Western part of India. It is expected that in coming years, India will be requiring a huge demand of large power stations for bulk power flow. Keeping that in mind, large substations are designed for further augmentation. This paper provides a comprehensive power flow study of a 765 kV interconnected bus system based on the standard parameters of the 800 kV (with 765 kV as the nominal voltage) class transmission system of India. This type of analysis is very useful for solving different power flow problems of an extra high-voltage (EHV) transmission system. The scope of the work is limited to air-insulated substations only. The software analysis is done on MiPower environment for real-time analysis.

The Internet communications are being developed to a great extent. With this development, an enormous amount of data is being generated. However, this data is not always secured. Intruders are always trying to misuse this data and gain unauthorized access, and hence, network security is also being compromised. An Intrusion Detection System (IDS) provides an efficient way to handle this. In this paper, an efficient IDS has been proposed which uses the NSL-KDD dataset which is a high-dimensional dataset. The dataset contains a large number of records, labeled as attack or normal. Correlation-based Feature Selection (CFS) method is chosen to select relevant and important features from the dataset for reducing the overall runtime of the proposed model, and a Deep Neural Network (DNN) classifier is used to examine if a record is normal or an attack. We tested our model using model validation and also compared the results with other existing models.

In this paper, a Ku-band bandpass filter with wide upper stopband characteristics is presented. The bandpass filter is implemented with a stub-loaded resonator (SLR). The resonator is designed to incorporate two resonating modes in the passband. Due to the presence of higher-order harmonics, the stopband is restricted to 25 GHz. To extend the stopband, the stepped-impedance stub (SIS) is connected at the input and output port. The proposed SIS stub has broad stopband characteristics, which extend the stopband up to 40.0 GHz. The proposed filter is analysed and simulated using a 3D EM solver. Simulated response agrees well with the analytical procedures.

Big data technology sustainability is contingent on the availability of interconnections of large-scale, ultra-high-speed, densely integrated big data heterogeneous server platforms. For highly densified servers to be attainable, semiconductor technologies upon which these servers are predicated must further be miniaturized. It is recently not uncommon to implement band gap reduction engineering of SiGe HBT in a bid to attain highly densified integrated circuit for large-scale servers. Unfortunately, the parasitic effects become significant, in particular as these integrated circuits are targeted for high frequency of operations due to the interconnection links between the chip and the transceivers. Insertion loss |S₂₁| becomes considerable, and both the signal level as well as noise figure depreciate substantially as a result. In this work, therefore, we investigate the extent of parasitic effect to wit performance degradation, and further to optimize the parasitics for performance enhancement.

A reconfigurable defected ground structure (DGS) resonator based on coplanar waveguide (CPW) technology is being proposed. The reconfigurable resonator leads to generate multiple stopbands at arbitrary frequencies. Basically, the design is based on slot defect which is thereby created on the ground plane. Here, two different states of diode configuration are being proposed, and in particular state, multiple transmission zeros are achieved in the 0–12 GHz frequency range. To identify the transmission zeros, the slotline design equations are used. Moreover, the conventional circuit parameter extraction method is used to extract the equivalent circuit diagram of each state.

Environmental pollution and scarce resources have led us to think of new alternatives. Even though we have plenty of alternatives like solar energy, hydro energy, bio gas, still wind energy plays an important role. It is said that if all the places in the world with wind energy potential is utilized, it will fulfill the total energy requirements of the world. Keeping it in mind, we focused on the wind energy potential for power generation in the Northeastern cities of India such as Gangtok, Tarey Bhir, Zunheboto, Bomdila, Dibrugarh, Udaipur, Ukhrul, Serchhip, and William Nagar. The wind speed data were collected over the period of 22 years (January 1983 to December 2004) from the RETScreen climate database at an altitude of 10 m from the ground. The wind speed data were subjected to two parameters: Weibull distribution with the scale (c) and shape (k) being the parameters along with other statistical techniques for assessment of wind energy potential. We found that wind speed varies between 1.94 and 7.15 m/s at different places in northeastern cities. The Weibull parameters k and c lie between 4.81–11.95 and 2.53–6.12. Also, the wind power density which is the quantitative measure of the wind energy available at any location varies from 10.2 to 186.76 W/m2. The result based on the Weibull analysis indicates that only Gangtok, Tarey Bhir, Bomdila, and Dibrugarh can be used for electricity generation on a large scale at 10 m height above the ground, whereas other places can be used to extract energy from low-speed wind at a height greater than 10 m.

The time series obtained during different fault events in an inverter-based microgrid are known to be inherently nonlinear, non-stationary and exhibits multifractal, chaotic behavior. This paper proposes a novel feature extraction and fault detection methodology based on multifractal detrended fluctuation analysis (MFDFA). The limitations of single-scale detrended fluctuation analysis and its susceptibility to interfere with the background noises are overcome in MFDFA which characterizes the multi-scaling nonlinear behavior of load signals during faults. The shape and distribution of the multifractal spectrum along with Hurst exponent are extracted from MFDFA analysis for pattern recognition and classification of different fault events. The efficacy of multifractal features in fault detection and localization with artificial neural network (ANN)-based classifier validates the adequacy of the proposed model.

Nowadays, solar photovoltaic (PV) systems are rapid growing energy resources in the world. Solar PV system depends upon the solar irradiation and temperature. Number of maximum power point tracking (MPPT) techniques can be used to extract the maximum power. During bad weather condition or partial shading condition, conventional MPPTs are unable to recognize the maximum power point (MPP). Consequently, these algorithms cannot be utilized as a part of PV framework to concentrate maximum accessible power. For this, particle swarm optimization (PSO) is utilized to reinstate particles to scan for the new maximum power point (MPP). A detailed simulation is done in the MATLAB/Simulink. PSO system gives various focal points, it has a speedier following velocity, it can likewise build up the MPP for any ecological varieties including partial shading condition, and also it is easy to develop.

This paper presents autonomous operation of microgrid by using modeling and small-signal analysis. State space technique is very good for finding the system small-signal stability. When microgrid having a number of generating units then it is very simple and time saving technique for solving system stability. In my microgrid model there are two micro generating sources and for checking System stability we are using the state space matrix and calculate the Eigen values and find the individual and combined DGs stability. These analyses Eigen values define the system stability and dynamics under the variation of controller and system parameters. And also verify the results with time domain simulation in MATLAB.

Wind energy is one of the best alternatives for the fossil fuels in the field of electricity generation. They have many advantages, when compared to the fossil fuels, such as it is available naturally, does not have harmful effect on the environment and will not be get depleted with the passage of time. Besides all these advantages of the wind energy, when the wind is used for the generation of electrical energy, there are lot of issues related to wind like fluctuations in wind speed which cause major problems in power generation. Variation in wind speed can also cause power fluctuation, which will cause discomfort at the consumer level. Many developing nations have now moved towards wind energy to meet their growing energy demands. The problem of power output variation of wind farms can be optimized by various optimization techniques like particle swarm optimization, genetic algorithm and artificial neural network. In this study, the technique of artificial neural network is being used for the optimization of wind power. In the neural network toolbox, the optimum value for wind power is first determined individually for three different input variables (wind speed, tip-to-speed ratio and coefficient of power) and then the final optimum values are determined by using all these parameters as input variables at the same time.

The paper proposes cost analysis of hybrid power system design using homer both grid-tied and off-grid mode of hydropower plant operative everywhere in the nation. Wind power systems are used to make system efficient and reliable. Hybrid energy system is used to decrease dependency on convention or renewable energy sources. Models of electric non-conventional (HOMER) are equated along with the operative and economical parameter with hydropower system parameter, and wind parameter with cost-effective approach is presented.

This paper investigates the study of stability for a 100 kW solar photovoltaic (SPV) grid-connected system using distributed static compensator (D-STATCOM) control. The proposed D-STATCOM control works as compensating reactive power source, which decreases the voltage variation on the distribution side of the proposed system. In addition, an isolated DC–DC converter has been implemented in conjunction with three-phase DC–AC voltage source converter (VSC) in double-stage grid-connected system operating at unity power factor. Especially, an integral regulator (IR) type of incremental conductance (IC)–maximum power point tracking (MPPT) technique has been applied, which controls the output voltage of SPV array and derives the maximum power from SPV array under changing atmospheric circumstances. Furthermore, the proposed MPPT technique has been proven highly converging in tracking of maximum power and keeps a steady DC link supply by altering the index of the converter. For the duration of the faulted conditions at grid side, the resulting balanced waveforms at point of common coupling (PCC) have been obtained. Additionally, harmonic study carried demonstrates the role of D-STATCOM in the reduction of harmonics and DC offset at utility side providing a stable steady state and transient response. In order to authorize the proposed system, the MATLAB simulations have been performed to show the usefulness of D-STATCOM control in proposed double-stage SPV grid-connected system.

Energy supply should be diverse and sustainable, and it needs to be utilized more effectively. It is necessary for promoting human’s quality of life with the economic development of energy resources. Microgrid works with renewable energy sources such as biomass, solar, wind and waste-to-energy. The microgrid can be disconnected from the main supply itself and connected to the load in order to supply power to the load when power failures occur. The goal of this paper is to provide a review on microgrid management system using technologies and its applications. Paper also includes different techniques like optimal control technique, best power management using optimization technique and function of battery-based energy storage element in microgrid for power management system.

This paper presents a significantly efficient nature-motivated moth flame optimization (MFO) algorithm to solve the convex economic load dispatch (ELD) problems of the power system. The ELD focuses on the effective scheduling of the power-generating units so as to fulfil the total load demand and to satisfy the various constraints of the generating units as well as power network limitations. The aim of the proposed work is to reduce the quadratic cost function of the generating unit and hence obtain the minimum cost of generation so as to maintain the economy of the generation plant. The obtained better positions of moths around the flames describe about the best solutions obtained as so far for the proposed work of the ELD problems. This paper performs test on convex cost function of 18 unit system so as to validate the efficiency, reliability and robustness of the proposed methodology.

Images captured by synthetic aperture radar (SAR) are generally corrupted with noises. SAR images are commonly affected by speckle noise and impulse noise. Noise filtering techniques must remove noises and simultaneously preserve valuable information present in the images. This article presents a noise filtering techniques based on soft computing. The proposed filters are implemented in two phases: In the first phase, the presence of noise in a particular pixel is detected by using fuzzy logic, and in the second phase, noisy pixels are filtered by using Self-Organizing Map (SOM). From our experiment, it is found that the proposed SOM filter reduces both speckle and impulse noise and also preserves the information present in the image. The proposed SOM filter is comparatively evaluated with various filters based on peak signal-to-noise ratio and edge-preserving factor.

A corporate network-fed quasi-lumped resonator antenna array is presented. A new class of patch antennas comprising of an interdigital capacitor in parallel with a straight strip inductor is employed as radiators, whereas an optimized corporate feed network is designed to couple excitation power to the radiating elements. The proposed radiating elements rely on the long but folded capacitance occurring between the interdigit gap, thus ensuring the miniaturization of the passives. The feed network has also been optimized for compactness and power propagation efficiency with minimum transmission losses. An 8 × 1 and an 8 × 2 are prototyped and investigated using the finite integration technique numerical code. The resulting design is litographically etched on a Roger duroid microwave laminate and subsequently measured. Findings indicate that the resulting design is compact in terms of estate area occupancy and demonstrates reasonable radiation efficiency.

Driver fatigue leading to drowsy driving is a severe traffic safety problem and is widely believed to be one of the largest contributors to fatalities and severe injuries on the road at present. Nodding off for just three seconds or less while driving can prove fatal. Drowsy driving slows reaction times, reduces vigilance, impairs information processing and creates un-mindfulness. We have developed a detection system for drivers under drowsiness, using non-invasive sensors. The system uses brain–computer interface (BCI) to determine the mental attention level of the driver following a complex recursive algorithm. In order to reduce false alarms in such detection system, we have incorporated two additional sensors in it. Infrared (IR) trans-receiver system emits an infrared signal to the eyes and another infrared photoresistor measures the reflected wave. The reflectivity of the open eye is grossly different from closed eye owing to the structure and presence of tear film in the eye. The microcontroller continuously compares and detects the difference in eye-blinking patterns of a normal person and that of a driver under drowsiness. The sleeping driver has certainly less or no eye blinking, which will be detected online and immediately without any time lag to prevent accident. Finally, a 3-axis compass sensor placed on the steering wheel will detect further the angular movement of the steering wheel of the vehicle. The driver under drowsiness will show an irregularity in eye-blinking pattern together with an abnormality in steering movement. On coincidence of all the three sensors, in order to reduce any false alarm, the driver will be alerted with a blinking LED placed within his/her view angle. If the driver does not respond and the statistics do not come back to normal, the software would prompt to apply emergency brakes automatically and simultaneously it would send SMS/email to the concerned authorities. The vehicle may also be fitted with additional blinking lights visible to other drivers too, to alert them on the road.

The designed microstrip patch antenna has a planner structure and operates in industrial, scientific and medical (ISM) band. The operating centre frequency of ISM band is 2.45 GHz. The final structure has been achieved after three iterations. Cross-type fractal with a superstrate layer is introduced here. The superstrate layer is used in all the iterations. When a superstrate is used on a microstrip antenna, the antenna properties like its radiation efficiency, gain, return loss, VSWR, resonant frequency and bandwidth are changed which may alter the antenna performance. The antenna structures are simulated in IE3D platform. A comparison of return loss, bandwidth, gain, directivity, VSWR, radiation pattern and overall area of the patch is also presented in this paper.

In radar domain, digital beamforming radar is evolving as a promising radar technology as compared to conventional pulse-Doppler radar. The design of PD radar and DBF radar is done by keeping all the design parameters same, and its performance is compared in this work. Needless to say that PD radar uses only analog systems but DBF radar uses digital systems. DBF radar’s performance is high, as compared to PD radar because of the use of digital techniques and MIMO antennas. The difference in signal to clutter ratio is 5.23 dB, i.e., SNR of DBF radar is three times greater than PD radar. The only limitation of DBF radar is being the hardware complexity, due to the use of multiple transceivers at each element of an antenna array, resulting in increased cost, size, weight, and power of the overall system.

Millimeter wave frequency modulation continuous wave (FMCW) waveform is very popular for its range and velocity detection for vehicular applications. However, it has false target detection problem in multiple target scenarios. This paper presents a double FMCW waveform for target detection in multi-target situations. This approach is considered to reduce the false target detection and to solve the ambiguity problem. Then Range–Doppler under different conditions is tested and shown in this paper.

Design and analysis of Circular Microstrip Patch Antenna (CMPA) using slots etched on patch for multiband applications is presented in this paper. Lightweight, low cost, plain configuration, and multiband functionality are the advantages and serve many applications like satellite communication, air traffic control, and radar communications. The substrate used is FR4 epoxy which has relative permittivity of 4.4. Introduction of slots increases resonant frequencies and bandwidth which make antenna serve multiple applications. The design is simulated using Ansoft HFSS software, and return loss, gain, VSWR, radiation pattern, and field distributions are studied.

The proposed design of antenna is the powerful textile antenna used to increase bandwidth efficiently. The proposed antenna has various applications like satellite communication, defense system, medical applications, and air traffic control. The proposed antenna acquires multiple frequency bands with bandwidth coverage percentage, first band from 2.81 to 3.692 GHz with 27.44%, second band from 4.556 to 5.618 GHz with 20.88%, third band with from 6.446 to 7.67 GHz with 17.35%, fourth band from 8.948 to 11.288 GHz with 23.13%, and lastly, fifth band from 12.134 to 17.606 GHz with 36.80%. The textile as the dielectric has many advantages as easy to wear, low material cost, easy availability, and high flexibility. The studied results of the proposed antenna show highly negative return loss, high directivity, radiation pattern, gain, and high efficiency.

In this article, the proposed textile antenna has been studied with better results, high directivity, high gain, good return loss and multiple bands are obtained for wide range of applications in S-band with multiple bands. The substrate material of the proposed antenna is a jean which is a flexible material, the patch and partial ground plane are of copper. There is a modification in proposed textile antenna design with the same size but better return loss and multiple bands. The simulations of the proposed antenna were carried using CST Microwave Studio software.

This chapter presents a dumb-bell shape microstrip patch antenna mainly used for wireless local area network application. The simulated result shows that the presented antenna has dual bandwidth of 49.60 and 10.05% covering the frequency range from 1.629 to 2.705 GHz and 3.411 to 3.772 GHz. In the end, the general investigation of the reflection coefficient, gain and efficiency of the anticipated antenna has been studied.

This article explains the application of artificial neural network for the judgment of bandwidth of microstrip antenna. The algorithms of radial basis function (RBF) are used to make the neural network model. The training and testing data of the neural network are procured by analyzing the microstrip patch antenna by IE3D software. The results procured from ANN are tallied with IE3D and are quite reasonable. The operating frequency range of the antenna varies from 1.879 to 2.896 GHz. The results acquired from IE3D and those acquired from ANN are highly correlated.

In this article, the algorithms of MLPFFBP-ANN are used to make the neural network model and for the judgment of bandwidth of microstrip antenna. The training and testing data of the neural network are procured by analyzing the microstrip patch antenna by IE3D software. The results obtained by using MLPFFBP-ANN are tallied with IE3D and are quite reasonable. The operating frequency range of the antenna varies from 1.66 to 2.53 GHz. The results acquired from IE3D and ANN are highly correlated.

The expressions for performance parameters of selection combining (SC) diversity receiver with L-branch over one wave diffused wave (OWDP) fading channel has been found out. The cumulative distribution function (cdf) of the signal-to-noise ratio (SNR) output has been obtained. Using the obtained cdf equation, the probability distribution function (pdf) of received SNR of the system over OWDP fading channel has been evaluated. The pdf obtained has been employed to evaluate the performance measurement namely for different coherent and non-coherent modulations. The outcomes obtained for the fading parameter K and the total number of branch L have been analyzed. The obtained outcomes are verified through Monte Carlo Simulation.

The major concern in free-space optical communication is atmospheric turbulence which may significantly degrade the performance depending upon the level of turbulence. The use of spatial time diversity can mitigate the effects of fading caused by atmospheric turbulence. The simulation results show the application of space-time block coding in intensity modulation and direct detection system to improve the bit error rate performance. The improvement in terms of coding gain is maximum when the turbulence level is high.

A fiber optic sensor has been reported for use in measurement of refractive index (RI) of transparent liquids. The sensing principle of the sensor is based on the effect of the RI of the liquid present between two misaligned optical fibers on coupling of light between them. In the proposed sensor, the displaced fiber ends are suitably intruded inside a liquid chamber, and optical power coupled from input fiber to the output fiber is observed w.r.t. change in RI of liquid sample, that is, introduced inside the liquid chamber. From experimental observations, the sensor can detect RI change up to resolution of 10−4.

We report a fiber optic sensor to measure the level of free chlorine present in chlorinated water. The sensor is made of an optical fiber that has been suitably bent in the form of U-shape. The sensor produces its sensing action when the U-shape probe is dipped inside liquid samples. Sensing principle of the sensor is based on absorption of fiber optic evanescent light wave by surrounding liquid medium. Experimental observations have shown that sensitivity increases with decrease in wavelength of excitation light source. We found that resolution of the sensor varies from 2.7 to 5.5 mg/L at 430 nm wavelength. The proposed sensor has the potential to be a low-cost alternative device for measuring free chlorine level of chlorinated drinking water very precisely and accurately.

Low phase noise is an important parameter, which determines the overall performance of the pulsed radar receivers in terms of range, Doppler and also operational robustness. Poor local oscillator (LO) phase noise causes reduction in the IF signal power as well as deterioration in phase noise. Considerable efforts are made to improve the LO phase noise. However, there is always an uncertainty as to how much phase noise should be tolerable and at the cost of what amount of performance. In this paper, a method is being proposed to ascertain the minimum tolerable phase noise or threshold LO phase noise and the impairments in performance thereof. It has also been shown that beyond a certain value, the improvement in performance vis-a-vis the cost and complexity is negligible.

Mobile applications are gaining substantial interests in recent years in large-scale wireless sensor networks (WSN). To achieve uninterrupted functioning of WSN, it is essential to initiate handover from current wireless node to another suitable node. A proactive distance handover algorithm for WSN is presented in this work. The algorithm is successfully validated considering the case studies of different mobility pattern.

A few researches have been conducted in the past decades for analyzing speech signal. For efficient study on the nature of the actual production of speech, the effect of vocal tract response and excitation source should be taken separately. However, this task is practically problematic since the components forming speech are not linearly combined. This paper presents homomorphic analysis and a method for nonlinear filtering of vowels in Khasi dialect has been proposed. A log-spectrum of each of the eight vowels was obtained. The first three formants frequencies of each vowel from four different Khasi speaking speakers were calculated.

Increasing availability of multiple responses and requirement of thorough analysis demand efficient modeling to derive a feasible support system which can make the analysis less-onerous, time-consuming, error-prone. Further, it is an indispensable provision to develop compact health monitoring devices, utility, and reliability of which rely on efficiency of program embedded that can manage the jobs without intervention of clinicians. In this article, a feature-level fusion framework is addressed using discriminant correlation analysis to effectively classify electroencephalogram (EEG) templates. Experiment on EEG data set shows that proposed method is efficacious and promising in terms of accuracy in comparison to the state-of-the-art methods.

With the advent of Internet of Things (IoT) and the advanced intelligent transportation systems (ITS), the concept of integration of data with technology and simultaneous sensing and communication is essential. These application areas would be driven by road safety and vehicular infotainment. The challenges in this regard are simultaneous vehicle-to-vehicle (V2V) sensing and communication. Here we have proposed the development of an OFDM UWB system whereby the UWB radar is sensing the object and the communication information is embedded in the transmitted UWB pulses. The radar receiver detects the target as well as estimates its range and velocity within the coherent processing interval. A realistic multipath fading channel is used with two moving targets.

The Digital Video Broadcasting Satellite to handheld (DVB-SH-A) employs Orthogonal Frequency Division Multiplexing (OFDM) that suffers from high Peak to Average Power Ratio (PAPR). Carrier Interferometry (CI) spreading codes is an efficient method that reduces PAPR with less computational complexity and without degrading BER performance. Therefore, CI-OFDM is proposed in place of OFDM for the existing DVB-SH-A. The fixed-point design of 1024-point CI-OFDM baseband transceiver using QPSK scheme is designed using Xilinx System Generator (XSG) and Verilog HDL with signed representation. Oversampling method is employed to approximate the baseband PAPR. Also, the behavior of CI-OFDM is validated on fixed-point AWGN channel. The fixed-point performance parameters like BER and PAPR are compared with MATLAB simulations.

In recent times, Wi-Fi (802.11 ac) is gaining popularity as it supports multistation WLAN and high throughput. Dielectric resonator antennas find many useful applications because of their low weight, low profile, low loss, conformability, and easy realization. In this paper, an aperture-coupled elliptically polarized rectangular dielectric resonator antenna is presented. Elliptical polarization is utilized to enhance the impedance bandwidth and gain in WLAN recommended band. The antenna is seen to be elliptically polarized with maximum gain of 7.50 dB and impedance bandwidth 550 MHz.

In recent times, Wi-Fi b/g (802.1 b/g) has been profoundly accepted due to the desire for increased data rates and minimal costs. It promotes the industrial, scientific, and medical (ISM) applications. Dielectric resonator antenna has been widely preferred for the various applications due to their low weight, low profile, conformability, easy and cheap realization. In this paper, an aperture-fed rectangular glass paperweight dielectric resonator antenna has been proposed. This antenna serves a great advantage because of its low cost, as glass material is utilized as radiator. The antenna seems to support near omnidirectional pattern providing a widespread impedance bandwidth of 1960 MHz.

The paper depicts a systematic procedure using pitch tracking and pitch smoothing methods-based statistical approach for exploring the singers’ melody of voice for a set of songs of poet Rabindranath Tagore sung by different renowned singers. The medium category (Mudara) of songs started with vowel ‘aa’ has been incorporated in the data set of songs. Index of melody has been estimated numerically based on semitones of different singers for a particular duration of the first vocal phrase. The value of probability of significance calculated by one-way ANOVA has been considered for the comparative study of the index of melody of the singers of particular song, and the results show the significant difference among the singers of same song of Tagore.

This paper presents an optimal fuzzy system for image contrast enhancement using differential evolution. The algorithm uses different fuzzification functions for underexposed and overexposed regions of the image. After fuzzification, both of these regions namely underexposed and overexposed are modified using a fuzzy intensification (FINT) operator and power-law, respectively. The fuzzy values are defuzzified using inverse of the membership functions to get enhanced image. An objective function based on histograms of the input and enhanced image is formulated and used in differential evolution algorithm to get the optimized enhancement. The evaluation of the proposed algorithm is evaluated visually as well as quantitatively. The comparison with existing algorithms establishes the supremacy of the proposed algorithm.

Optical character recognition is an important field of research with widespread applications. Researchers have endeavored to replicate the human ability to read printed text, and extensive research has been carried out. In this paper, we recognize optical characters using a recently proposed classifier minimum complexity machine (MCM). To aid in performance analysis, with existing classifiers we have compared the results obtained from MCM with results from support vector machine (SVM) and k-nearest neighbor (k-NN). A common dataset for testing and training was used throughout to determine the accuracy and time taken for testing. Principal component analysis has been used to obtain a reduced set of features prior to the training and testing process. An analysis of the effect of the number of components on the accuracy of minimum complexity machine, support vector machine, and k-nearest neighbor has been provided as well. It was noted that minimum complexity machine has given accuracy comparable to that of the existing classifier though the time taken for testing was substantially reduced.

Risk analysis is one of the most important components of any financial decision and has been a subject of extensive research. We present here a comparative analysis of different methods to calculate value at risk (VaR) in the Indian Market. The models that have been explored are filtered historical simulations, Monte Carlo, historical simulation, and variance–covariance. The implementation was carried out in MATLAB, and the stock indices of NIFTY 50 and BSE SENSEX were used as a representative of the Indian Stock Market. The results obtained were first compared on the basis of time taken to calculate the risk incurred using six different datasets. They were also compared on the basis of whether the actual losses were within the calculated VaRs. A theoretical comparison on the various methods was also performed.

Field programmable gate array (FPGA) provides an attractive platform for realization of different logical functions and hardware components frequently used in digital signal processing (DSP) applications. These platforms present new challenges for logic and hardware designers, particularly for the module that involves the mapping of desired functionality onto the underlying prefabricated reconfigurable hardware resources. A fundamental aspect of the DSP is filtering. Digital filters having finite duration of impulse responses are referred to as finite impulse response (FIR) filters. This paper mainly emphasizes on the design and implementation of FIR filters of different forms in FPGA. The proposed design algorithm of FIR is modeled in VHDL followed by verification and synthesis using the XST tool. The performance of FIR is analyzed using the timing diagrams, HDL synthesis report, and device utilization summary. This work also incorporates hardware co-simulation of the system with real filter analysis.

Nowadays, advanced driver assistance system (ADAS) is one of the utmost emerging matters of intelligent transportation system (ITS). Many sensors, with their own advantages and limitations, are available in market, to be implanted in the vehicle to provide guidance to the driver. Such guidance enables the action of vehicle by providing drivers advanced control and better driving experience. But the choice of sensors among the available sensors is an important issue that needs to be addressed. This paper presents a method, considering multiple constraints, to provide ranking of those sensors to be used to design a robust, reliable, and cost-effective ADAS.

This paper presents evaluation results of support vector machine (SVM) classifiers with radial basis function (RBF) kernel in offline signature verification. We have used two data sets of offline signatures and extracted 15 (fifteen) features from each signature sample of the data sets. The best feature subsets of the data sets were selected using filter and wrapper methods. For both the data sets, SVM classifiers with RBF kernel were designed with every selected feature sets individually. Classifiers were optimized, and their performances were evaluated using 10-fold cross-validation. Another classifier was designed using both the data sets combined to test the generalizability of the classifier across two different signatures.

This paper describes a study on prosodic feature-based automatic language classification system for four Indian languages from Northeastern India. However, the number of languages may be increased. The present system can classify the selected Indian languages into two broad groups of tonal and non-tonal languages, based on the possibility of use of lexical tone in them. The lexical tonality in a language is measured by the speed and level of pitch variations in utterances. These parameters are applied as the inputs to a Naive Bayes classifier to complete the design of the system. Here three Indian languages and one dialect, namely Manipuri, Assamese, and Bengali languages and Kakching dialect of Manipuri language, have been used. All these languages are from the Northeastern part of India and are selected since no language classification or identification work is reported for these languages so far. The experimental results reveal that the present system is able to classify the Indian languages into broad groups of tonal and non-tonal languages for a relatively less amount of training data being in use.

The rapid pace at which data traffic is increasing day by day in wireless networks is a matter of concern. Thus, developing reliable solution that can handle this ever-growing data traffic is vital. 5G-based cellular networks have several distinct benefits. First and foremost, it will be able to deliver services similar to a fiber-based broadband network. This is a significant performance improvement over previous radio access technology. In this work, FBMC-based 5G front-end Femtocell has been introduced. This introduction has helped to improve the performance of existing LTE-based 4G JIO radio access. The designed model and proposed infrastructure help to achieve a very high data throughput of the order of 1 Gbs per second and good signal strength with reduced BER.

This paper introduces a new high-performance narrowband Hybrid Beamformation (HBF) system for upcoming mmWave-based 5G system. HBF system overcomes the pitfall of narrowband Analog only Beamformation and narrowband Digital only Beamformation. Next-generation 5G communication system will be taking the advantage of millimeter wave (mmWave) frequencies band that inherits signal fading and immense propagation loss. The move toward the mmWave spectrum facilitates the use of shorter wavelength. This facilitation makes possible for small antennas to focus its radiated signals into narrow beam to compensate for signal fading and path loss. An enhanced version of antenna gain with much focused antenna beam with HPBW of almost 11° with gain of 23.45 dB has been obtained in this paper. Assuming that both BS and MS have prior knowledge of the narrowband mmWave channel, we were able to achieve very low BER of almost zero when good signal strength was maintained after Beamformation.

Event detection, in simple terms, means detection of the incidences occurring around us satisfying the threshold condition of some predefined criteria. In present scenario, event detection is gaining importance because of its versatility regarding predefined criteria, threshold conditions and its widespread applications. Many works have been done in this area. In the present paper, our goal is to detect the accidents occurring on the streets, roads and highways. For this, we have done the correlation analysis of optical flow and exhaustive simulation has been performed to show its effectiveness. The results based on optical flow of frames and its correlation show that the event is detected more accurately compared to the results obtained due to correlation only. Also, an exhaustive study has been performed on various accidental scenarios and it has been observed that the proposed method accurately identifies the accidental scenario in every case, be it any kind of traffic (more dense or less).

Wireless freedom, smaller size, faster speed, smarter world: the next advancement is here, i.e., 5G. Recently, the world is going crazy over the latest technology, i.e., 4G (LTE/LTE-Advanced networks). Also in India, Reliance Jio 4G network has gained immense popularity. Already research has started in the coming next generation, i.e., 5G with an aim of increasing data rate from 10 to 100 times, reducing energy consumption by 10 times, increasing 100 times more connected devices, and also to reduce the latency. Hence, 5G network will be able to support machine to machine communication efficiently. That will make the 5G network capable of monitoring and controlling millions of devices and will provide the enormous data collection and distribution requirements of Internet of Things, i.e., IoT. Here, in this paper, a comparative analysis of BER performance of LTE-Advanced system and 5G system has been done, once with big date, i.e., wideband and then with control signals, i.e., narrowband, as for implementing IoT, big data is needed to support massive devices with high speed and narrowband is needed for controlling purpose. We are concerned about BER performance as BER is an important parameter for system performance analysis. SystemVue 2016.08 software has been used for experimental purpose. Also, MATLAB 2015 has been used.

Imaging modalities are noninvasive, fast, and accurate in the diagnosis of different anatomical disorders. As such, there is a pertinent requirement for segmentation of the organs to give proper visual information on the morphological and pathological changes. The aim of the proposed work is to implement the automatic liver segmentation from the CT images, using active contour segmentation technique. The localization and detection of liver tumor will be easier for radiologist with the extraction of the liver from other adjoining organs. In this paper, we are discussing the different techniques employed for liver segmentation and our present ongoing study is based on 2D and 3D liver segmentation with its future implementation.

Work toward the fifth generation of mobile networks has gained a huge momentum recently. As 5G research projects have already started or are about to start, and 5G activities in standardization bodies, in particular 3GPP, have already been scheduled, it is important to start also the work on the security architecture, in order to ensure that security is built into 5G networks right from the start. Important steps will be the clarification of the security requirements, the review of existing security architectures, in particular, the LTE security architecture, and finally the selection of the 5G security measures in tight interworking with the design of the general 5G network architecture. In this paper, we go one step in this direction and hope to promote the overall work toward a sound 5G security architecture.

Global Navigation Satellite System (GNSS) is used to obtain user’s position, velocity and time (PVT) information. A scheme of using a low-cost, single-frequency multi-constellation GNSS hardware has been proposed here which can be used for several applications. The realization of the concept utilizes output data from a GNSS module in National Marine Electronics Association (NMEA) format that may be used by microcontroller and auxiliary hardware for location tracking, time synchronization or stamping and atmospheric monitoring purposes. The use of multi-GNSS is expected to provide enhanced capability of the generic system.

This research is based on vision-based hand gesture recognition. The gesture of hands can convey important information and can be applied as a useful means for man–machine interaction. One of the primary steps of hand gesture recognition is identifying the number and coordinates of the fingers visible in the image or video frame. This work proposes a simple but effective way for locating the coordinates of the images by using Hough transform. First the prospective fingertips are detected by circular Hough transform. Next the coordinates of the fingertips are cross-verified by searching for the long Hough lines in the vicinity of the fingertip coordinates. The long Hough lines will indicate the fingers.

In mobile ad hoc networks (MANETs), routing protocols are commonly used to manage the routes. Because of mobility of nodes, there is a need to reconfigure routes dynamically. These protocols normally suffer from various deficiencies such as high routing overhead and constrained adaptability. In MANETs, mobility pattern directly influences the performance of routing protocol because communication link failures between nodes are associated with the network topology. The performance of routing protocol depends on number of sent control packets, which in turn affects the energy consumption of whole network. This study investigates ad hoc on-demand distance vector (AODV) Perkins et al. (Ad hoc on-demand distance vector (AODV) routing, 2003 [1]) routing protocol under various network configurations and utilizing different mobility models, e.g., random waypoint (RWP), linear, Gauss–Markov, and mass mobility. All simulations have been done using OMNET++ IDE (https://omnetpp.org/documentation/ [2]). The execution is resolved on the premise of an aggregate number of sent control packets with varying node density, mobility, and different mobility types.

Sensing of soil nutrient content has become an integral part of soil fertility management system. Fertilizers have been in use for enhancing soil fertility since nineteenth century, but accurately applying fertilizers based on the amount required for a particular site or type of soil/crop has always remained a challenge. Moreover, standard laboratory analyses are very time-consuming and expensive. In this work, we developed a simple sensing system employing six LEDs (380, 475, 510, 570, 650, and 840 nm) and corresponding photodetector array for obtaining the diffused reflectance from five successive positions (separated by 72°). Based on this reflectance data obtained from the sensing system, unique soil spectral signatures were obtained and analyzed statistically. Two mathematical models, transformed multilinear regression model named as SSRC and exponential regression model named as ERMIR, were developed for rapid non-destructive estimation of soil nitrogen based on diffuse reflectance spectroscopy using Vis-NIR sensing. Both the models’ performances were analyzed based on the three statistical parameters R2, RMSE, and SEE. The R2 values obtained were almost near to 1, and the RMSE and SEE values were satisfactory. The repeatability and stability of the sensing system was also checked and found to be very satisfactory.

New technology trend has been initiated worldwide for the exploration of IoT using 4G and 5G mobile communications, cloud RAN, and extended coverage beyond the coverage area of mobile network. Motivated by the above trends, ECE Department, SMIT has started to build one test bed for IoT using 5G. At first, some recent papers are reviewed toward practical perspective on IoT in 5G network issues related to (i) latency critical IoT applications in 5G, (ii) efficient IoT gateway over 5G wireless, and (iii) efficient 5G small cell planning with eMBMS for optimal demand response in smart grids. This paper will discuss the detailed development efforts to achieve the IoT test bed. Efforts are rendered to make the test bed as a high-end research facility, industrial consultancy, and support toward 5G-enabled wireless IoT.

Face recognition plays vital role in many of the biometric as well as other scientific applications. Face needs to be detected prior to recognition, and many researchers introduced methods for face detection along with unique features. These methods have been used in constrained and unconstrained environment. But it is difficult to tackle challenges such as occlusion, pose variation, illumination order to detect faces in unconstrained environment. Here in this paper, we are going to extract facial curves as features which will be further used for face detection. We have extracted lower facial features such as chin curves, lips curves, and ear curves by obtaining face contours using edge detection techniques in images and video frames from YouTube Faces Database. By matching majority of features, it is possible to detect face in unconstrained environment.

This paper emphasizes on the beamforming techniques used in today’s systems. Multiple beamforming techniques such as the Minimum Variance Distortionless Response (MVDR) and Linear Constraint Minimum Variance (LCMV), to name a few, are used to improve the capacity and data rates of various systems such as cellular system. Both mentioned techniques are based on the received weight vector of the desired signal. This paper presents the mathematical difference as well as the power difference between LCMV and MVDR beamforming techniques.

The emphasis on studying fractional-order controller has gradually been increasing in the area of control theory. The elementary component of a fractional-order controller is the fractional-order operator $$ s^{\beta } \left( {0 < \beta < 1} \right) $$sβ0<β<1, which can either be a fractional differentiator or be a fractional integrator. The discretization of $$ s^{\beta } $$sβ is central for digital realization of the fractional-order controller. In this paper, a half-order fractional differentiator is approximated to a rational transfer function by using Oustaloup approximation. The approximated continuous-time transfer function is then discretized to obtain the corresponding transfer functions in the complex $$ z $$z-domain and complex delta-domain. Finally, the frequency responses obtained from two discretized transfer functions of two different complex domains are compared for simulation studies with the help of MATLAB software.

This paper presents the speed control of an Induction Motor (IM) using rule-based fuzzy logic controller and simulated with the help of MATLAB Simulink and later tested with its hardware model. Because of low maintenance and robustness, IM has much application in industries. Here, the scalar control method is employed for controlling the speed of an IM where the stator voltage and the frequency to the system are changed proportionately by keeping v/f ratio constant Krishnan (Electric Motor Drives—Modeling, Analysis and Control. Prentice-Hall, Upper Saddle River, 2001 [1]). The inputs to the fuzzy logic controller (FLC) are speed error (e) and change in speed error (Δe) and output to the controller is the change of control (ωsl) which is actually the frequency correction at the output. These inputs are processed according to the user-defined rule, and output is corrected and provides the required signal to control the speed of PWM inverter-fed IM. It was observed that fuzzy logic controller avoids complexity to the system design and it also avoids the mathematical computations compared to other controller design. Using fuzzy logic controller for closed loop v/f control scheme gives superior way of controlling the speed of IM by maintaining a constant maximum torque.

This investigation deals with the introduction of a noble dynamic fuzzy model reference adaptive control scheme. In this work, we propose a new model of MRAC using fuzzy control for the speed control of DC Motor. The starting of our work is done with the general comprehensive designing of MRAC for first-order process along with the second-order process using MIT Rule. After that, the description regarding our proposed model is given. For the evaluation of the performance of the controller, fuzzy-based MRAC is applied on DC Motor. The simulation results are compared with other controllers showing that the reaching time and tracking can be extensively reduced.

Identification of objects in digital images is an important part in computer vision. Edges have high probability being the border of an object, so edge detection is very crucial in image processing. The accurate detection of edges in an image reduces the processing requirement by filtering our insignificant data, while preserving important structure in an image. In this paper, various image edge detection techniques are analyzed and presented, further the paper proposed edge detection technique based on fuzzy logic. In this paper, MATLAB software along with its pre-defined functions has been utilized for the development of such fuzzy logic-based edge detection technique, and it is compared with other existing edge detection techniques.

This paper presents a three-stage control system to feed a squirrel-cage induction motor (SCIM) from stand-alone PV systems, through cascaded two-level inverters and an open-winding transformer. The main objective of this system is to extract the effective PV power, while maintaining the DC link voltage in presence of the load torque and solar irradiance variation. The DC link voltage controller is developing the reference speed for the speed controller, followed by current controller. The speed and current controllers are developed through rotor flux-oriented vector control. The SVPWM modulation technique is used to supply the desired voltage vector to the SCIM for good dynamic response. The MATLAB/Simulink simulation results are showing the worth of this proposed control strategy at considered operational conditions.

In the present work, the performance of a Wind Turbine (WT) with doubly fed induction generator (DFIG) interfaced with power grid is investigated. Proportional-Integral (P-I) controllers have been considered for controlling the system, and the small signal stability model of the system has been considered for designing the controller. Gain settings of P-I controllers of WT with DFIG are optimized using Flower Pollination Algorithm (FPA). Analysis reveals that the P-I controllers with optimized gains for WT for DFIG system improve the dynamic responses significantly. Sensitivity analysis has been performed by changing WT and DFIG parameters, and results reveal that FPA-optimized P-I controller gains obtained for nominal values of these are quite robust and need not be changed.

Robot manipulators have become a major component in the manufacturing sectors which are utilized in several applications such as grinding, welding, assembling, and mechanical handling due to quite efficient accuracy, speed, and repeatability. These applications require proper path planning, proper generation of trajectory, and most importantly a control design. This work deals with the problem of modeling and control of a two-link robot manipulator which is a classical and simple example of robot followed in understanding the fundamentals of robotic manipulator. Since, the closed form solutions are not available so we use numerical solution. Due to these uncertainties and nonlinear behavior, it is a very difficult task to control the motion of the robotic arm at the accurate position. Here, we are focused on designing and implementation of PID controller to control the motion of the robot arm. MATLAB has been used to carry out simulation after derivation of necessary equations.

In the present work, the application of thyristor-controlled series capacitor (TCSC) is investigated for damping oscillation of single-machine infinite bus (SMIB) power system. The analysis is performed by considering proportional–integral–differential (P-I-D) controller for TCSC, and gain settings of the P-I-D controller of TCSC are optimized using Krill Herd Algorithm (KHA) for different values of generator active power and terminal voltage. The optimized values of gains of P-I-D controller are used for training the multilayered feedforward artificial neural network (ANN)-based controller for real-time tuning. Dynamic performances considering TCSC equipped with ANN-based P-I-D controller and the P-I-D controller optimized with KHA are compared, and it is seen that ANN-based P-I-D controller for TCSC performs well under different operating conditions.

Over the decades, a number of methodologies have been introduced to meliorate the resistive sensor measurement protocol for complete knowledge of the phenomenon of interest. Nonetheless, such setting requires high degree of circuit components that result high level of errors (i.e., nonlinear) and thereby, its minimization for effective design is an open question. This article presents a technique that utilizes direct resistive circuit with microcontroller ($$ \mu C $$μC), followed by subsequent estimation of curve-fitting models (CFMs) to curtail the errors involved and implementation in $$ \mu C $$μC to update real-time data. Further, the study exploited the effectiveness of various employed CFMs in this context. The significant aftermaths with suitable choice of CFM and subsequent comparison with the state-of-the-art approaches manifest the efficacy of the adopted scheme.

PID controllers are still very popular in process industries due to their simple design and easy tuning. Model-free tuning relations are relatively preferred compared to model-based tuning relations as identification of the true model for industrial processes is not an easy task. Ziegler-Nichols (ZN) setting is one of the most widely accepted model-free tuning guidelines. However, for higher-order processes, it provides undesired oscillations during set point change and load variation. Fixed set point weighting (FSPW) and variable set point weighting (VSPW) techniques are reported to restrict the oscillations during set point tracking only. Recently, reported dynamic set point weighting (DSPW) is capable to provide an overall improvement during set point change as well as load varying conditions. But to achieve further performance enhancement of a PID controller, a simple fuzzy rule-based set point weighting (FRSPW) technique is reported here for under-damped second-order processes. Superiority of the proposed FRSPW-based PID controller is established through quantitative estimation of various performance indices and, moreover, its adequate robustness is also observed in presence of considerable perturbation of process parameters.

This paper presents a fault localization technique based on wavelet packet decomposition (WPD) and radial basis function neural network (RBFNN) for a hybrid transmission line consisting of an overhead line and an underground cable fed from both ends. The transmission line is simulated in Electromagnetic transients program (EMTP) and only fault currents are recorded at local end of the transmission line. Third-level WPD with mother wavelet db1 is utilized to calculate wavelet packet energies of fault current at each node. The normalized values of these features are fed to the RBF neural network to estimate fault location on both overhead section and an underground cable. The algorithm is fast as only half cycle post-fault data are sufficient and need not identify the fault sections (overhead line or underground cable) for estimating fault location. The accuracy of fault localization is very high irrespective of fault resistances, fault inception angles (FIA), and fault types at different locations on the hybrid transmission line.

This paper proposes design of adaptive calibration technique to eliminate the interference of noise in pressure measurement. Proposed paper objective is to design a signal-conditioning technique that measures the pressure accurately, even with variations in environmental parameters like humidity and temperature. Output of the capacitance pressure sensor is converted to voltage using the data conversion circuits. Distributed blackboard data fusion framework is used for creating an adaptive calibration technique to measure pressure accurately without interference of environmental parameters like temperature and humidity. Results of the proposed measurement technique are analyzed to evaluate the performance of proposed technique. Obtained results evidence the effective implementation of proposed calibration technique.

Internet of things (IoT) is a network of objects linked to cyberspace. It increases rapidly and reaches all around, not only limited to smartphone or home appliances but employed in factories, business, and health care because it enhances efficiency, reduces cost, and saves lives. Think a world where billions of objects can feel, convey, and share information, and all interlinked over public or private Internet protocol (IP) networks. These interrelated things have data usually gathered, tested, and conformed to initiate an exercise, allowing a wealth of understanding for designing, managing, and judgment making. This is the world of the Internet of things (IoT). The Internet of things (IoT) is the upcoming trend of creation that assures to be better and makes our everyday life optimal, smarter, which is based on having intelligence devices and smart things operating at same time. Using Internet protocol (IP) facility, things can now be linked to the Internet, so permitting them to be understood, guided, and managed at every time and at every place. IoT is used in number of fields including designing smart city, connected vehicle, etc. This paper presents a review on IoT and depicts key challenges on the same field.

Big data management is today treated as one of the important tools that deal large but related data sets. Complex data and traditional data processing are also very much important and valuable for solid and healthy big data management. Big data is useful, and today, it is implemented in most of the organizations as well as sectors. Healthcare, education, banking and finance, information foundations, business houses, etc., are most important and valuable place where big data is used. Due to the importance of Big Data and Analytics it is today treated as an important academic field international even in India also few universities have offered programs on the field. It is important and valuable for the creation of business and strategies of IT. In this paper, bachelors and masters engineering program details (other than Science & Management Concentration) are studied and provided which are available in Indian universities based on study. Paper is also highlighted regarding possible academic programs in Indian scenario based on Indian need and International degrees available.

With the aid of Cloud Computing, virtualization for several devices has become possible. It is quite essential for its effective and efficient utilization. With connectedness through Internet and similar technologies, centralization of such information technology services has become possible to great extent. It is an important tool for development of environment having remote access to different domains of business, socio-economical and scientific initiatives. The attributes of service science provided are common in many contexts. Cloud Computing is available on different platforms, mainly private, public and hybrid. Cloud Computing is also related to the Big Data and Data Technologies. As an academic program, Cloud Computing is not so popular and available; but there is a potentiality to offer Cloud Computing and allied subjects in India and other developing countries.

Wireless sensor networks (WSNs) contain a collection of sensor nodes. These nodes are linked with one another and have low computational power. Wireless sensor network is used for sending messages, data, and other important information over a wireless link for military purpose, environmental monitoring, Health checkups for patents, habitat monitoring, target tracking, and disaster management. Security is most important concept in WSN while sending such important message over wireless link. This permit attacker to penetrate the network and carried out various possible attacks with the purpose of stealing or editing actual data/information. In this paper, discussions are made on different techniques available to avoid and detect wormhole attack.

Traffic within a data center can sometime lead to congestion due to imbalance of distribution of traffic. In this paper, a software-defined networking (SDN) approach to traffic engineering within a data center is described. A video traffic distribution scheme is designed based on SDN, to improve network availability by means of multipath thus achieving load balancing. In this paper, queue bandwidth allocation (QBA) algorithm is proposed which allocates bandwidth to video traffic and other classes of traffic. QBA uses the concept of queue in OpenFlow (OF) 1.3 ([1] and McKeown et al. in ACM SIGCOMM Comput Commun Rev [2]) which guarantees quality of service (QoS) by reserving bandwidth on each queue for each class of traffic based on the priority of each class of traffic which is discussed in Sect. 3. Finally, simulations are performed to show that our proposal is significant in achieving load balancing to solve the queue congestion problem as well as allocate bandwidth to each queue using QBA.

An aggregate signature is a short digital signature which is the output of aggregation process. The signature aggregation is done on k signatures of k distinct messages from k distinct users. As the produced signature size is shorter, so it will be efficient to use the schemes in low-bandwidth communication environment. In this paper, we proposed two identity-based aggregate signature schemes from bilinear pairing operations. The proposed schemes are secure against existential forgery under adaptively chosen message and identity attack in the random oracle model based on the assumption of intractability of the computational Diffie–Hellman problem (CDHP). The efficiency analysis of the proposed identity-based aggregate signature schemes with other established identity-based aggregate signature schemes is also done in this paper.

Intrusion and intrusive activities have become a bottleneck for both Internet and Intranet users. An intrusion detection system tries to take care of such activities by constantly monitoring the user systems. Although there are two basic approaches in intrusion detection, i.e., misuse detection system and anomaly detection system, respectively, however, recent research works emphasize on hybrid approach which tries to gather the advantage of both misuse and anomaly-based systems. The proposed research work is based on such a hybrid system which uses misuse detection system for known types of intrusions and anomaly detection system for novel attacks. Frequency episode extraction method is specifically used for misuse-based detection and chi-square test is used for anomaly-based detection. Experiments show that the hybrid intrusion detection system is able to consider the real-time traffic of a network as well as the standard available data set for detecting the efficiency of the system. The proposed system learns and trains itself by detecting known attacks from misuse detection system and novel attacks from anomaly detection system, thereby improving the true positive rates and diminishing false negative rates consequently.

The tremendous growth in the rate of urbanization in the past few decades has in turn increased the need for a stable and sustainable urban development plan. Solid waste collection is a very complex process that involves efficient management of the entire system, starting from the collection to the dumping of wastes, hygienically. This paper describes the real-time monitoring and management of waste collection system, thus, enabling us to be excused from collecting semi-empty bins. Furthermore, the incoming data can be effective to determine the minimum number of vehicles associated or bins to distribute. This paper hence gains insights into the status of waste in a city and therefore contributes to a cost-efficient, eco-friendly and more systematic way of waste collection.

The size of computer network is rapidly growing, and the new generation Internet needs more improvement to keep data transfer faster in the network. As the Internet users are increasing, the network traffic also parallelly increasing, so high attention is required to keep faster data transfer. For this reason, network monitoring secures the data and the management of network traffic is very essential task in the field of computer network. User data information is transferred through user datagram protocol (UDP) or transmission control protocol (TCP) via various nodes that present in the network. UDP is datagram-oriented protocol, i.e., it carries the datagram or packet from source node to destination node. To monitor the packet or datagram, packet sniffing is widely used; that is, a method of capturing the datagram to analyze the network log traffic occurs in a network during communication between various nodes that exist in the network. This paper provides a well-developed method to monitor and analyze the network traffic using UDP that removes the existing deficiency of traditional existing tool used for analyzing network traffic.

Drainage hydrographical network is one of the most salient features used for hydrological analysis, geomorphology, Earth science, terrain analysis and still is a research topic in the field of GIS. A drainage network generally extracted from toposheet processing, raster image processing, and the new advanced satellite image processing. The classification of the drainage network plays a very important role for geographers, geologists, hydrologists, biologist, and other scientists as it reveals the idea of the size and strength of specific stream within drainage networks. Recent freely available satellite images provide the digital elevation data over the earth surface is very important for faster extraction of drainage network.

In this paper, we present a digital pen for handwritten digits recognition based on acceleration in three-dimensional spaces. The digital pen consists of a triaxial accelerometer, an 8-bit microcontroller, and a RF transmission module. MATLAB GUI is used for signal preprocessing, noise rejection, and acceleration equivalent voltage to image conversion. Accelerometer generates signals due to the hand movement and transmits the data wirelessly to PC to detect the trajectory. Then, the trajectory is converted to image.

This paper presents a comparative study between particle swarm optimization and particle swarm optimization time-varying acceleration coefficients (TVAC) algorithm-based methodology for solving load flow in electrical power systems. Load flow study provides the system status in steady state and is required by several functions performed in power system control rooms.

In this project, we propose advanced hi-tech wireless notice board. Notice board is a primary thing in any institutions, organization, hospital, or public utility places. For passing any notice, we use papers. If we observe, lots of papers are being wasted due to this notices so we need to save papers in order to make an eco-friendly system. We are trying to develop a digital notice board which can overcome these problems. With this notice board, we can send our notice anytime without wasting any resource and can make our communication more efficient. We can handle proposed notice board with less errors and maintenance. We can replace normal notice board with digital notice board anywhere like institutions, organization, hospital, or public utility places and can update the notice anytime. For this, we used Raspberry Pi for wireless communication. Here we can change the news or notice or timetable which can be displayed on notice board. Raspberry Pi will act as server, and there will be multiple clients connected to the server, and these clients are connected with LCD. Here server and clients are connected via router for wireless communication. For displaying information, we need to approach server and from server, we can send our information to particular client or multiple clients and clients will be displaying that particular information. The goal of this paper is to provide the access to notices and articles quickly as compared to manual notice board. We can update text messages using centralized database anytime. The address is assigned to each receiver and information is displayed from the main server at the reception.