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The Internet of Things (IoT) has witnessed remarkable growth, leading to the emergence of numerous applications and services. However, energy efficiency remains a critical concern in IoT networks due to the resource-constrained nature of many IoT devices. Energy-efficient routing protocols play a pivotal role in mitigating this challenge, optimizing energy consumption, and extending the operational lifetime of IoT deployments. This survey paper aims to provide a holistic understanding of the state-of-the-art approaches, their characteristics, strengths, limitations, and performance metrics. The survey encompasses a wide range of energy-efficient routing protocols proposed in the literature, including traditional routing protocols adapted for IoT scenarios and protocols specifically tailored for energy optimization. We discuss the impact of different network characteristics on the performance of energy-efficient routing protocols, such as network size, node density, mobility, and heterogeneity. Through this systematic survey, we aim to provide researchers, engineers, and practitioners with a comprehensive overview of energy-efficient routing protocols for IoT networks. The survey findings can serve as a valuable reference for protocol selection, performance evaluation, and the development of novel energy-efficient routing strategies in future IoT deployments. [ABSTRACT FROM AUTHOR]

It also reports simulation-based comparison study with other optimization algorithms such as particle swarm optimization, differential evolution, and whale optimization algorithm. The experiment results of the algorithm in the form of precision are compared with conventional algorithms to draw conclusions about the efficacy of the proposed algorithm. In the paper titled "Analysis of Amplitude Scintillation and Positioning Error of IRNSS/GPS/SBAS Receiver for Heavy Rainy Days", the authors examine the characteristics of amplitude scintillation on an IRNSS/SBAS/GPS receiver with all seven satellites of the Indian Regional Navigation Satellite System (IRNSS) at the low-altitude station IITRAM, Ahmedabad, on days with heavy rain. In the paper "Model Order Reduction Based Power System Stabilizer Design Using Improved Whale Optimization Algorithm", the authors present an optimization technique I viz i . improved whale optimization for designing a power system stabilizer using model-order reduction for a modified single machine infinite bus system. [Extracted from the article]

The paper on "Moving Average Filter-PLL-Based Voltage and Frequency Control of Standalone WECS" a phase locked loop (PLL) is presented to solve the issue of fast and accurate estimation of system frequency during distorted voltage in a wind energy conversion system. The algorithms are the particle swarm optimization, genetic algorithm, imperialist competitive algorithm and selfish herd optimization. The next paper titled "Effective Control of Voltage and Frequency in Microgrid Using Adjustment of PID Coefficients by Metaheuristic Algorithms" presents four evolutionary algorithms to optimize a PID controller's coefficients for use in frequency and voltage control of a microgrid. The paper presents study of performance evaluation of the algorithm for diseases in apple trees and rice crop and compares the performance with other techniques to make inferences about the efficacy of the algorithm. [Extracted from the article]

This study investigated technologies related to a smart-card display and its wireless charging system, where the wireless receiver in the smart card receives not only the data but also the power required for the display circuitry. The goal of this research was to achieve the required energy transfer during the extremely short reading time when a person swipes his or her smart card. This paper describes the design considerations and the analysis procedures of the transmitter and receiver pair for an electronic paper (E-paper) display. A series of magnetic simulations as well as experimental tests were conducted to investigate the various design factors. The design considerations included the shape and effect of using ferromagnetic cores, the component design for frequency tuning, the geometric arrangements, and the number of turns of the coils. A novel design for power transmission is then proposed using a ferromagnetic core to enhance its energy efficiency. In experiments the transmitter unit provided 250 mW of power to the transmitter antenna. The resultant transmission efficiency (S21) was −5.1 dB over a distance of 4.3 mm. Experimental results show that the smart card receives 220 mW, representing a high transmission efficiency of 88%. [ABSTRACT FROM PUBLISHER]

In this paper, we present the MU (multi-user) MIMO (multiple-input & multiple-output) system which is capable to serve the maximum number of users without additional bandwidth or power budget. MIMO systems maximize the channel capability as per the DPC scheme (Dirty Paper Coding). According to DPC, several antennas distributed over the base station are used for serving multiple users simultaneously. Nevertheless, DPC is a comprehensive search algorithm employing sequences of encoded user data for transmitting information to multiple users. Due to increased user density and subsequent transmit antennas in the MU-MIMO system, the exhaustive search (i.e. DPC) becomes cumbersome with the expanded search space domain. This search task would not be completed within a coherence time frame of the packet data communication system. The required objective is to consider this as a cost function for optimization to maximize the realizable sum-rate (throughput) of the MU-MIMO systems. This paper illuminates the joint antenna and user scheduling (JAAU) process with binary artificial bee colony (binary ABC) accomplishing nearly 98–99% of system throughput with the suggestively decreased figure in computation complexity and run time. Binary ABC is observed to have the global optimum value swiftly within the stipulated packet time frame of next-generation wireless data communications. Moreover, binary ABC achieves an appreciable system capacity for MU-MIMO systems as compared with DPC (which attains the maximum system throughput with the highest complexity). These findings are corroborated with exhaustive simulation results presented in this article. [ABSTRACT FROM AUTHOR]

By figuring out the best numbers for the inductor, capacitor, and duty cycle of the boost converter, this method makes it possible to match the PV system to the configuration of the DC/AC converter. The suggested numerical antenna model shows good agreement with the performance of the built antenna prototype within the human muscle-mimicking liquid phantom. This paper "Multi -objective Naked Mole -Rat Algorithm for UWB Antenna Design", introduces a novel multi-objective naked mole-rat (MONMR) algorithm for the optimization of two printed monopole patch antenna structures for ultrawideband (UWB) applications. In "Improved Switched-Capacitor Switched-Inductor Z-source Inverter for Increasing Boost Factor and Decreasing Voltage Capacitors Stress", the authors uses a switched-inductor Z-source inverter to improve a switched-capacitor inductor ZSI. [Extracted from the article]

This paper proposes a Smart Electric Bus (e-Bus) Battery SUbstitution Scheme called SBUS in a cloud-based e-Bus system for the efficient battery replacement during e-Bus services. A smart e-Bus system using cloud-based management is considered as an alternative public transportation system. The battery of an e-Bus often needs to replaced, which can be one of the reasons for vehicle traffic congestion. When the battery of an e-Bus was not enough to run itself on its service route, it needs to replace its battery during the running. By this reason, road traffic congestion can be caused by this routine battery exchange. In order to solve this problem, SBUS is proposed to reduce road traffic congestion. To our knowledge, this paper presents the first attempt to investigate how to effectively assign an appropriate e-Bus station for battery replacement e-Bus station for battery replacement to each e-Bus to reduce road traffic congestion. As a result, the proposed scheme can assign an appropriate e-Bus station for battery replacement to each e-Bus to reduce road traffic congestion. To show the effectiveness of the proposed SBUS, we compare it with baseline schemes through simulation. The results of the experiment show that SBUS is more efficient than the baseline schemes in terms of the shorter average waiting time for battery replacement and the shorter end-to-end travel delay for e-Bus services. [ABSTRACT FROM AUTHOR]

The authors of the paper titled "Towards Neuro-Fuzzy Compensated PID Control of Lower Extremity Exoskeleton System for Passive Gait Rehabilitation" designed a neuro-fuzzy compensated PID control for passive gait rehabilitation using a lower extremity exoskeleton system. In the paper "A Comparative Survey of Convex Combination of Adaptive Filters", the authors evaluate the convex combination of adaptive filters, which are mostly based on the least mean square (LMS) algorithm, the affine projection (AP) algorithm, and the recursive least mean square (RLS) algorithm. The paper "A Novel Weighted Superposition Attraction Algorithm-based Optimization Approach for State of Charge and Power Management of an Islanded System with Battery and Super Capacitor-based Hybrid Energy Storage System" proposes a Hybrid Energy Storage System (HESS) employing a Battery and a Super Capacitor (SC). The authors of the paper titled "Computer-Aided Detection and Diagnosis of Thyroid Nodules Using Machine and Deep Learning Classification Algorithms" propose a computer-assisted method for detecting and segmenting tumour regions in ultrasound thyroid images using machine and deep learning classification algorithms. [Extracted from the article]

In this paper, the radiating element of a patch antenna for energy harvesting application was fabricated using the graphene ink-based screen printed method. Wax-coated paper and polyester were investigated as flexible substrates to mount the graphene radiating element. FR4, the typical material used in electronic circuitry was also considered as a substrate for comparison. The performance of the antenna was measured by using the standard method of Vector network analyzer. Simulation of the antenna performance was carried out using a material-based software tool, COMSOL Multiphysics and the simulated results have been compared with prototyped results. The proposed design is targeted at 2.45 GHz wireless energy harvesting applications. An experimental trial of replacing conventional copper mechanism with state of art material is studied for its performance. [ABSTRACT FROM AUTHOR]

The paper provides an equivalent circuit model and parametric analysis of the filter characteristics along with circuit simulation studies. The paper titled "A Miniaturized Band-Reject Filter Using Metamaterial Structures on Silicon Substrate for X-Band Application" gives the design of a band-reject filter in the X-band based on series connected complementary split ring resonators. The paper reports the electrostatic analysis of GNR and compares the delay of the radial point interpolation method (RPIM) with other analysis method I viz. i reproducing kernel particle method (RKPM). [Extracted from the article]

The next paper "Qualitative Analysis of Stable Reduced Order Models for Interval Systems Using Mixed Methods", considers the problem of representing complex higher order systems by approximate lower order stable systems. The method is studied on a test system and compared with other neural network architectures to bring out the efficacy of the proposed architecture. The system comparisons are shown in terms of the step response and frequency response (magnitude and phase) of respective transfer functions of original system and different model order reduction methods. [Extracted from the article]

Wavelet transform and wavelet packet transform methods are studied for this purpose and fault disturbance detection in micro-grids. The next paper titled "Joint Throughput Optimization for Multichannel Multiradio Multirate Wireless Network with Network Coding", presents a network coding method to improve network throughput. These are two important performance parameters of a wireless sensor network that are considered together for optimization in this paper. [Extracted from the article]

In this paper, a compact low-profile dual-band 2 × 2 wide band wearable slot antenna (smart watch) for the frequency spectrum of 3.4–3.6 GHz (LTE Band 42) is proposed. For smart watch applications, the antenna should be as small as possible and it should be resonating at the forthcoming 5G technology. Hence, two resonant modes are achieved for each antenna by etching the T-shaped monopole slot in the ground plane of size 40 × 40 mm2, and each slot is coupled fed by the L-shaped tuned stub which is printed on the 0.8 mm-thick FR4 substrate. The proposed antenna is fabricated and its performance is experimentally measured. The measured antenna parameters agree well with the simulated results. The reflection co-efficient and transmission co-efficient of the Multi Input Multi Output (MIMO) antenna are well below −10 dB throughout the band of operation. The efficiency of the MIMO antenna is achieved up to 81% with the overall gain of about 2.4 dB. To validate the proposed MIMO performance, the envelope correlation co-efficient between the antenna elements is calculated. In this paper, the effect of the proposed antenna in the human hand is also studied and discussed along with the specific absorption rate. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive review of the feature extraction techniques for character recognition (CR) which will be helpful for the new researchers to understand the insight into the developments of the current research in the field of CR. Feature extraction plays a major role in the performance of the CR. The characteristics of the feature extraction techniques have to be independent of the scalable font characteristics such as type, size, style, tilt, rotation and should be able to describe the complex, distorted, broken characters effectively. A feature vector should be simple, reliable, complete, and compact to recognize any input character with high accuracy similar to human perception. A lot of research has been done on feature extraction techniques for optical CR for the past few decades. Most of the existing CR methods from the literature will work successfully for one or two fonts and they have used the combination of existing features to improve the accuracy. Therefore, we feel there is still scope to work on feature extraction techniques for the recognition of multilingual characters. [ABSTRACT FROM AUTHOR]

Automated computer-aided soft computing methods are presently used to detect the tumor regions in brain images. In this paper, the tumor cells are detected in the brain Magnetic Resonance Imaging (MRI) using the Extended Linear Boosting (ELB) classification method as one type of soft computing process. This paper proposes an effective brain tumor detection and segmentation method using the ELB classification method. The Curvelet transform is applied on the source brain MRI image to convert the spatial domain pixels into multi-resolution pixel. The spectral and linear discriminate features are computed from the Curvelet transformed coefficient matrix. The dimensionality of the computed features is reduced using the PCA method and the optimized features are then classified using the ELB classification method. The performance evaluation metrics, sensitivity, specificity, accuracy and detection rate, are used in this paper to evaluate the performance of the proposed brain tumor detection and segmentation system. [ABSTRACT FROM AUTHOR]

Engineering efforts also involve optimization methods when solution is not explicit. In many cases the implementation of an idea requires engineering choices to be made, that reflect the need to optimize/ minimization in terms of design choices, software implementation or choices at the algorithmic or architectural levels. The papers listed later reflect the use of numerical optimization based approaches, while the earlier ones show how optimization might enter into more complex design choices, such as into problem representations or at the architecture level. [Extracted from the article]

The current communication deals with the investigation of sucrose concentration in aqueous solution using copper-based metamaterial structure at a wavelength of 1550 nm. In this article, 5×5 air holes are engraved on a copper-based metamaterial structure, which contains the different concentration of sucrose in aqueous solution. Further, the present structure manipulates with finite difference time domain (FDTD) technique to compute the sucrose concentration. Moreover, different losses (absorption loss, dispersion loss, propagation loss, and polarization loss) are measured for the same. Nevertheless, similar type of papers have been published, the present paper has a couple of benefits including the method of computation (FDTD) and the output variation (linear ship) with the concentration. Apart from this, the present research shows the error bar, which deals with an accurate measurement. Again a mathematical model is also obtained, which gives the relationship between the sucrose concentration and the output intensity. Further, output results declared that transmitted intensity varies linearly with the concentration of sucrose. Lastly, a feeble error in the commutation proclaims an accurate investigation of sucrose in their aqueous solution with the help of a photonic structure. [ABSTRACT FROM AUTHOR]

Glaucoma is a critical retinal disorder due to high intraocular pressure (IOP) within the eye. It causes irreversible damage of the optical nerve head (ONH). The available glaucoma detection methods using decomposition techniques with gray images or only green channel images are less accurate. In this paper, a more accurate method for glaucoma detection using image channels (ICs) and discrete wavelet transform (DWT) from fundus images is proposed. Firstly, input images are resized then red channel (RC), green channel (GC), blue channel (BC), and gray scale (Gs) images are extracted. Secondly, these four types of images are enhanced and decomposed separately into sub band images (SBIs) using second level (SL) DWT. Thirdly, most useful features are extracted from each of DWT SBIs. Fourthly, extracted features from each of RC, GC, BC, and Gs images are concatenated and normalized. Finally, robust features are selected and fed to the least square support vector machine (LS-SVM) classifier. The obtained glaucoma detection accuracy of the proposed method is 84.95% which is more than the existing methods using the same image database. The proposed method may become suitable for ophthalmologists to detect glaucoma with better accuracy. [ABSTRACT FROM AUTHOR]

This paper presents an efficient method to improve the far-field radiation pattern of concentric circular antenna array (CCAA) design using two stochastic optimization algorithms known as social spider algorithm (SSA) and modified social spider algorithm (MSSA). Low side lobe level (SLL) plays a crucial role in reducing the interference with the other frequency components along the entire side lobes of the far-field radiation pattern. SSA and MSAA are the state-of-the-art evolutionary optimization techniques which are applied here to determine the optimal current amplitude and the inter-element distance between two consecutive antennae of the 3-ring CCAA. In this paper, the optimal results achieved by using SSA, MSSA for (4, 6, 8) elements and (8, 10, 12) elements 3-ring CCAAs, with and without centre elements are reported. The results achieved by employing SSA and MSSA show a considerable improvement in SLL reduction as compared to the uniform and the other array patterns reported in the state-of-the-art literature. [ABSTRACT FROM AUTHOR]

This paper peruses the Doppler-bearing passive target tracking (DBT), a task that is subject to the nonlinear measurement equations. These measurement equations form the target tracking a nontrivial duty. In order to defeat these problems, many studies have reported various nonlinear estimation techniques, such as sigma-point Kalman filters. These types of filters have demonstrated superior performances for nonlinear system parameter estimation. Consequently, the main contribution of this paper is to improve the performance of the sigma-point Kalman filters. Thereafter, this paper introduces a transformed unscented simplex cubature Kalman filter, in which adaptation techniques are utilized to reduce the dependency of the proposed filter performance on the priori statistical information of the process and measurement noises. Moreover, the proposed filter is initialized by the range-parameterised Unscented Kalman filter. The Cramér–Rao lower bound (CRLB) determines the best accessible accuracy of estimators, which is utilized in this paper to accredit the performance of the proposed filter. The validity and feasibility of the proposed filter are confirmed by Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

Recently, telesurgery, as a branch of telemedicine, is growing at great speed. In telesurgery, a remote surgeon can communicate with operating room through communication networks in order to perform remote operation. Because human life is at stake in telesurgery, it is necessary to implement appropriate Traffic Engineering (TE) techniques to manage and route telesurgical data traffics over communication networks. Implementing proper TE technique can increase Quality of Experience (QoE) for the remote surgeon, and as a result, it increases the accuracy and performance of telesurgery. In recent years, the advent of Software Defined Network (SDN) has facilitated network providers to develop efficient TE methods to guarantee QoE for their customer applications. In this paper, a novel multi-objective TE technique called SMOTE is proposed to guarantee QoE for telesurgery applications over SDN. The goal of this paper is to enable a network administrator to provide a satisfactory remote operation by providing QoE for the remote surgeon. The objectives, which are considered in our proposed method, are the minimization of end-to-end delay and packet loss. SMOTE uses Non-dominated Sorting Genetic Algorithm (NSGA-II) a well-known multi-objective algorithm, to solve the optimization model for calculating optimal routes between the remote surgeon and the operating room. We conducted comprehensive simulations to evaluate the performance of SMOTE in terms of QoE. Simulation results confirmed that SMOTE guarantees QoE in telesurgery. [ABSTRACT FROM AUTHOR]

The segmentation of Glioma tumor regions in brain Magnetic Resonance Imaging (MRI) image, using Convolutional Neural Networks (CNN) classification method, is proposed in this paper. The adaptive histogram equalization method is applied on the brain MRI image for enhancing the abnormal pixels with respect to surrounding pixels. This enhanced brain image is transformed into multidirectional scaling image using Gabor transform. Then, features are extracted from this multidirectional scaling image and then these features are trained and classified using CNN deep learning algorithm in order to differentiate the Glioma from normal brain MRI image. Finally, the tumor regions are segmented using morphological operations. The proposed Glioma brain tumor segmentation method using CNN classification approach obtains 96.9% of sensitivity, 99.3% of specificity and 99.2% of accuracy. [ABSTRACT FROM AUTHOR]

Several metamaterial antenna configurations have been proposed in the literature for gain and bandwidth enhancement. However, these antennas are rarely used in commercial applications due to complexity in their design and fabrication process. In this paper, different configurations of electromagnetically coupled microstrip antennas and arrays are proposed as an alternative antenna design for gain and bandwidth enhancement. A comparison is made between the configurations proposed in this paper and the metamaterial configurations reported in the literature. The proposed configurations have better gain and bandwidth than the metamaterial configurations within the smaller volume. [ABSTRACT FROM AUTHOR]

Simulation and emulation of electric motor faults are particularly useful to study, test, and evaluate the motor condition monitoring products based on the motor current signature and vibration analysis. Many researchers have proposed and developed several DAQ & computer-based simulation tools. This paper aims to develop a system to simulate and emulate the maximum types of faults which can occur in a three-phase induction motor. In this paper, an embedded system based induction motor fault simulator and the emulator is proposed and developed. The focus of this paper is to model the induction motor faults mathematically based on the motor current signature and vibration frequency spectrum, which are theoretically derived and proved by the early generation researchers and engineers. The novelty of the proposed approach is a cost-effective, portable, and handy tool for field evaluation of the motor condition monitoring products. This paper presents the hardware and software development for making a stand-alone motor faults simulator and emulator. The system employs a powerful high-end and powerful embedded system INTEL ATOM Minnow Board, which is built around E3826, Dual Core, and 1.46 GHz processor. A dedicated 4-channel Direct Digital Synthesizer (DDS) with 12-bit resolution along with software generates all three-phase induction motor faults for both MCSA and vibration analysis. The simulated and emulated faults signals are compared and evaluated against the Standards with the help of a digital storage oscilloscope. [ABSTRACT FROM AUTHOR]

In general, a 5G new radio network is defined by three primary utilization situations, namely upgraded versatile broadband, ultra-reliable, and low latency interchanges of information, as well as huge machine-type correspondences. These utilizations require improved throughput, inertness, dependability contrasted, and a 4G framework. As a coding plan for information, 5G Turbo codes attain high throughput, a variable code rate, and length, and crossover programmed rehash with good error-detecting capability. The execution boundaries of 5G advancements are normal and are tens and thousands of times better compared with 4G. In this paper, the evaluations of puncturing and non-puncturing for turbo code depending on the minimization of penetrating of efficient pieces are discussed. It also provides penetrating of equality pieces considering additive white Gaussian noise (AWGN) Channel with 16 quadrature amplitude modulation (QAM) to attain high spectral efficiency. In addition to this, the super encoder encodes the separated progression with a code speed of 1/3. The code block association progressively connects the yields from the super encoder. The sign mapper employed in this paper adjusts the progression using a 16-QAM balance. Also, the mapper takes effective pieces, one uniformity bit from the upper encoder, and the deinterleaved equity bit from the base encoder. The Orthogonal frequency-division multiplexing (OFDM) mapper parts into more modest equivalent channels, named subcarriers and the information is sent on these equivalent channels at a reduced rate. [ABSTRACT FROM AUTHOR]

Mission-critical IT systems are utilizing closed source software (CSS) mainly due to reasons related to "quality assurance" and "continued support" despite much better benefits of using Open Source Software (OSS). OSS permits users to access source code for assessment, amendment, and redistribution, which offers low dependency on a vendor without license or maintenance cost. This paper investigates and analyzes OSS adoption factors for "critical IT infrastructure" by conducting a comprehensive review of the relevant literature. Furthermore, this paper proposes a framework that can help the critical IT industry to have increased confidence in OSS. The proposed framework utilizes the organizing logic of the Technology, Organization, and Environment (TOE) framework, recommends factors that were recognized by critically scrutinizing the studies found in the available literature. To validate the framework, a questionnaire-based survey was conducted targeting IT experts in critical sectors. The data integrity of survey results was analyzed using Cronbach's alpha. Framework factors were validated statistically using one sample T-test. The outcome indicated that the factors were statistically significant as the p-value was less than 0.05 for all the factors. [ABSTRACT FROM AUTHOR]

This paper proposes a computer-aided methodology for detecting and segmenting the tumor regions in ultrasound thyroid images using machine and deep learning algorithms. This proposed tumor detection methodology uses Kirsch's edge detector for enhancing the edge region pixels in thyroid image and then Dual Tree Contourlet Transform (DTCT) was applied on the enhanced image for obtaining the coefficients. Then, features are computed from this transformed thyroid image and these features are trained and classified using the Co-Active Adaptive Neuro Expert System (CANFES) classifier. Then, the morphological segmentation method is applied on the abnormal thyroid image to segment the tumor regions. Finally, the Convolutional Neural Network (CNN) algorithm is applied on the segmented tumor regions for diagnosing them into mild, moderate and severe. [ABSTRACT FROM AUTHOR]

The number of DGs located at distribution site, which uses renewable energy sources, forms a Micro-grid system. The problem of using DG with the utility is unplanned islanding. This paper has focused on passive islanding detection method (IDM) which is easy for implementation, cheaper and proficient. The suggested method tried to eradicate the disadvantage of passive conventional IDM. Low impedance grid always immersed small deviation of inverter output in the grid-connected mode, but whenever the grid is disconnected (i.e. in islanding condition) this stability effect of the grid is absent, which is picked up for islanding detection in the proposed method. In this paper, voltage ripple-based passive IDM is evaluated and tested under various operating conditions. The proposed method is easily working on condition like generated power and load power are the same and it was found that technique is robust, without NDZ and can detect islanding within 0.3 sec. Also the proposed method is able to differentiate islanding and non-islanding scenarios, which is helpful to stop unnecessary malfunctioning of DGs. [ABSTRACT FROM AUTHOR]

This paper aims to obtain the overall equations of the yearly, seasonal, monthly and daily optimum tilt angles worldwide. So, the daily optimum tilt angle variations are examined for 337 locations in the northern hemisphere and 247 locations in the southern hemisphere, and it is shown that the daily optimum tilt angle changes in cosine form over a year. Then, the daily optimum tilt angle is estimated using a cosine function. The daily optimum tilt angle is independent of the longitude and can be estimated using a function that depends on the latitude and the number of days. The resulting model can be used to calculate the optimum tilt angles in desired intervals. In order to verify the validity of the results, the results of the proposed model are compared with the results of the other papers. It is shown that the presented model can calculate the optimum tilt angles with acceptable accuracy in the southern and northern hemispheres. [ABSTRACT FROM AUTHOR]

The GTEM cell is a new version of the modified transmission line, operated at very high-frequency test equipment for EMI or EMC measurement. The equipment is designed for an electromagnetic compatibility, immunity and radiated emissions test. In this paper, GTEM is designed using ANSYS HFSS 13.0 and fabricated for 1 to 3.9 GHz frequency. This paper focuses mainly on the novel validation test for the manufactured GTEM cell characterization without using costly Vector Network Analyzer. The novel test set up comprises of GTEM cell, transmitter and the receiver is designed and tuned at 2.4 GHz. Using this set up field uniformity is checked for fabricated GTEM ranges within +/− 6dB. This makes a compact and cost-effective novel test validation set up for the designed, developed and manufactured GTEM for 1 to 3.9 GHz. [ABSTRACT FROM AUTHOR]

In this paper, critical analysis of performance comparison of various optimization techniques for a MRPID (Multi Resolution Proportional Integral Derivative) thermal system controller is presented. This controller controls the uncertainty or mismatch between real and reference temperature. Wavelet coefficients of error between the two temperatures and their corresponding gains are added to produce a control signal for the thermal system. The main purpose of the proposed method is to optimize the tuning parameters of a wavelet-based MRPID controller to regulate the switching pulse of the thermal system. Modeling and simulations are carried out using MATLAB/Simulink@2015. Figures-of-merit such as disturbance rejection, system stability and transient response are also compared using various techniques like Particle swarm optimization (PSO)-MRPID, Genetic Algorithm (GA)-MRPID (existing techniques), Firefly-MRPID controllers and Elephant herding optimization (EHO) based Recurrent neural network (RNN)-MRPID algorithm. Firefly-MRPID and EHO with RNN-based MRPID are proposed for determining unique (best) operating conditions of the thermal system in this paper. [ABSTRACT FROM AUTHOR]

The load-frequency control is a matter of interest in power system operation as it addresses the problem of controlling the system in response to the disturbances. A well-known solution to this problem is feedback stabilization through Linear Quadratic Regulator. The observability condition has to be satisfied for the implementation of LQR, but for certain cases of multi-source power systems this criteria fails. Also, to obtain the desired response, proper selection of the weighting matricesQand R for LQR controller is inevitable. On a trial and error based choice of these matrices, the classical optimal controller may fail to achieve an optimum set point tracking, due to the absence of an integral control action. In this paper, a balanced reduction technique is proposed to obtain a minimal realization of the unobservable system, which makes the optimal control design possible for the control of change in frequency. Thus the paper also applies PID output feedback controller designed through LQR. The impact of reduction for minimal realization and the LQR based PID controller in the frequency stabilization of the considered systems are highlighted in this paper through pertinent cases. [ABSTRACT FROM AUTHOR]

One of the most challenging events for distance relays is a transient phenomenon known as power swing, which can have damaging results to the system. The occurrence of power swing can cause the impedance trajectory to enter protective zones of distance relays that may lead them to the wrong operation. Malfunction of distance relays can create instability in power systems, and a large blackout may occur in these networks. The purpose of this paper is to introduce a new method based on using the mean value of sampled data from the current signal to recognize power swing from simultaneous faults. This method has been tested using DIgSILENT and MATLAB software on a two-bus network with parallel lines. The obtained results demonstrate that the proposed scheme is capable of detecting various types of power swings, including both unstable and stable power swing. The presented method in this paper also has an accurate operation to detect simultaneous symmetric faults. Besides, this method is planned for a protection system with a central controller using the IEC-61850 standard. [ABSTRACT FROM AUTHOR]

Quadrotors are one of the Unmanned Aerial Vehicles (UAVs) that have many applications in the aerospace industries which require a high level of accuracy and innovation in control and stability. In this paper, a hybrid control structure is proposed for this system. The sliding mode controller (SMC) is the foundation of this control structure. This controller, despite its high stability capability for nonlinear systems, has two weaknesses: chattering phenomenon and high vulnerability to noise. The proposed solution is to incorporate the SMC and the Fuzzy intelligent controller because of its high flexibility against the changes in the system model conditions. The new Fuzzy-SMC resolves the SMC weaknesses significantly, but it is not optimized due to a lack of access to the system model expert information. In order to optimize the Fuzzy-SMC, it is necessary to have accurate structural information and specification of the system model which are not available for this case. The final proposed solution is to synthesize the Genetic Algorithm (GA) with the Fuzzy-SMC. In GA performance, each Fuzzy rule is regarded as a chromosome and at each stage, the best of chromosomes, containing the fastest responding, are passed on to the next generation as the elite. The rest combine to create the next generation by using combination and mutation methods. Thus, the Fuzzy-SMC operates based on optimized Fuzzy rules. The results of the simulation in MATLAB software clearly show that the state of quadrotor reaches the desired value and location at the appropriate time. [ABSTRACT FROM AUTHOR]

Constant switching frequency (CSF) is an important objective to be achieved by any control strategy deployed on a Voltage Source Inverter (VSI) so that the filter design will be easier. Though the invent of Multi-Level Inverters (MLI's), the Two-Level Inverters (TLI's) are widely used when it comes to current control strategies. In this paper, a new hysteresis current control strategy is proposed for a TLI in order to achieve nearly CSF. In this method, the constant switching frequency is achieved by creating a Variable Band (VB), which varies according to the switching frequency average of the pole voltage. The proposed control strategy creates VB's such that it mimics the Continuous Space Vector Pulse Width Modulation (CSVPWM) and also the Bus-Clamping Pulse Width Modulation - 60° and 30° (BCPWM60 - BCPWM30). The paper also analyses the proposed control strategy under different criteria such as current THD, dynamic performance and parameter variation. This performance of the proposed strategy is simulated using MATLAB Simulink platform and experimentally validated on a 2.2 kW, three phase, Induction Motor (IM) using dSPACE-1103 kit. [ABSTRACT FROM AUTHOR]

Generally, more Internet of Things (IoT) based sensor networks are used for transportation and traffic signals in a smart city. The need of IoT based networks are increasing day by day. The main issue of IoT networks is poor energy optimization. Offering energy optimization in the IoT will present a number of difficulties. The researchers try to extend the network lifetime by reducing energy consumption. Clustering is a good solution to reduce the consumption of energy in a network. In IoT along wireless sensor networks (WSNs), a cluster is a group of nodes. Using these clusters, Cluster Head (CH) is formed. CH collects information from other nodes and is connected to the Base Station (BS). In this paper, Cluster head selection using a Multi-Dilation Convolutional Neural Network optimized with Balancing Composite Motion Optimization (BCMO) is proposed. The major goal of this work is to increase the normalized energy and optimize the weight, temperature, delay, distance between all nodes, and weight. In this paper, the Multi-Dilation Convolutional Neural Network optimized with Balancing Composite Motion optimization is proposed for energy optimization (CHS-MDCNN-BCMO-IoTN). The efficiency of the proposed CHS-MDCNN-BCMO-IoTN approach is compared with other existing methods in terms of normalized energy, load, temperature, and number of cluster head formations. This CHS-MDCNN-BCMO-IoTN method attains 31.45%, 30.98% and 27.24% highest number of alive nodes, 26.16%, 27.23% and 33.62% lower number of dead nodes when compared with existing methods. [ABSTRACT FROM AUTHOR]

Increasing size of web leads to relevant information extraction by traditional and last query expansion methods not to be efficient and encounter an essential challenge. Therefore, to improve query expansion, in this paper, a novel hybrid method called HQEBSKG is introduced. In the first part, a new and efficient technique is proposed based on semantic knowledgebase to expand users' queries. In the following part, a useful method based on semantic relations between words is also suggested for query expansion. In the current work, to achieve the semantic relations, FarsNet and WordNet ontologies are used simultaneously to enrich knowledge resources. The experimental results show performance improvement. [ABSTRACT FROM AUTHOR]

Controlling of voltage and frequency in the microgrid is a challenging issue and many controllers are suggested for this purpose. Proportional-Integral-Derivative (PID) controller is simple and efficient when its coefficients are optimally adjusted. Recently, evolutionary algorithms are used to optimally adjust the PID coefficients. In this paper, four evolutionary algorithms, particle swarm optimization, genetic algorithm, imperialist competitive algorithm and selfish herd optimization, are applied to set the PID controller coefficients and tested in the frequency and voltage control of the microgrid. Settling time, overshoot and stability margin are three main factors in the control response of PID which are considered for generating the fitness function to be optimized in terms of the PID coefficients. The proposed microgrid includes inverter-based distributed generators and different loads. Load change and different faults may cause the degradation of frequency and voltage where using of the PID controller leads to better control of these parameters. Simulation results show the efficiency of all four algorithms where particle swarm optimization performance is better than other three algorithms. Experimental results also verify the simulation results discussed in the paper. [ABSTRACT FROM AUTHOR]

Discrete logarithm problem, popularly known as DLP has been the heart of many Public Key Infrastructures that are being used today. DLP belongs to the category of hard problems. Many ideas have been proposed to solve DLP. The best-known methods are Number Field Sieve (NFS) class algorithms. The Function Field Sieve (FFS) algorithm is one of the NFS class algorithms to solve DLP in an extension field, i.e. Galois field GF (2 n). This FFS involves three phases such as Function Sieving, Filtering, and Linear Algebra. Linear Algebra phase involves solving huge sparse matrices/system of linear equations. The most popular methods to solve sparse matrices are Lanczos and Wiedemann method. Recently, Wiedemann method got attention to solve the linear system of equations such as Ax = 0. This paper studies Wiedemann algorithm to solve A X ≡ 0 m o d 2 n − 1 based on the factors of 2 n − 1 ; since the DLP is defined over GF (2 n). The different cases considered in this paper are (1) 2 n − 1 is a prime of size less than n bits, (2) 2 n − 1 is a composite number with one factor of size more than n bits, and (3) 2 n − 1 is a composite number with more than one factors of n bits. The naive Wiedemann is considered in case 1, paralleled version of Joux and Pierrot ["Nearly sparse linear algebra and application to discrete logarithms computation," preprint Contemporary Developments in Finite Fields and Applications, 2016.] is considered in case 2 and the client-server model along with the paralleled version of Wiedemann for case 3. Algorithms for all the three cases of solving A X ≡ 0 m o d 2 n − 1 are designed, analysed, experimented, and tested under the conditions based on density and size of matrices. The experiments are carried out on the matrices obtained from filtering step of FFS. The results are analysed and reported. From the results, it is shown that the communication cost between master and the slaves is to be considered and minimum density in the matrix is to be maintained in the previous step of linear algebra of FFS, i.e. filtering step to avoid trivial solutions. The configuration of the system used for experiments is 64 bit Intel (R) Xeon (R) CPU E5-2650 v3 @ 2.30 GHz with 40 cores and Intel(R) Core i7-6500U CPU @ 2.50 GHz. [ABSTRACT FROM AUTHOR]

This paper proposes a hierarchical error recovery method for the hybrid mobile broadcast/communication networks. The mobile broadcast network (e.g., DVB-T/H, T-DMB) transmits the base forward error correction (FEC) and the multimedia content at the same time for the error recovery. However, the occurrence of errors is different due to the receiving environment of the individual mobile broadcast network, and not all the base FECs can recover errors. The server retransmits the enhanced-FEC (E-FEC) to a terminal through the individual mobile communication network and a terminal can try to recover the packet with errors which the base FEC cannot recover. If there are more retransmitted source data to a user, the overhead of a user and the communication network will increase because the individual mobile communication is a subscription-based network. Therefore, this paper proposes a hierarchical error recovery method, and the E-FEC with higher channel coding rate than base FEC is generated and transmitted. The proposed method in this paper transmits only the redundancy data for the error recovery when errors occur, and reduces the resource by 50%–80% compared with the retransmission of the source. If the source bit rate is 800 kbps, for instance, the packet error ratio is 10%, and if a user watches a broadcast content for one hour, the amount of retransmitted data is 80 kbps × 3600 = 36 MBytes, but that of the proposed method in this paper is 7.2–18 MBytes. [ABSTRACT FROM AUTHOR]

Public key cryptography is based on two popular mathematical hard problems namely the integer factorization and discrete logarithm problem. Number Field Sieve (NFS) and Function Field Sieve (FFS) are the most efficient and widely used algorithms to solve integer factorization and discrete logarithm problems. The main phases of these algorithms are polynomial selection, relation collection and linear algebra. Among these steps, relation collection and linear algebra are the most computationally costly. The filtering step is used in between relation collection and linear algebra step, which employs several strategies to reduce the coefficient matrix size and makes the matrix suitable for linear algebra, so that linear algebra takes comparatively lesser time. This paper presents a complete framework for the filtering step in the NFS class of algorithms. In this paper, the filtering step is considered as two main sub-phases. The two phases are namely matrix construction and matrix reduction. In the first sub-phase, the relations collected from the relation collection step are structured to represent in a matrix form. The main goal of this phase is to construct a relation from the smooth elements obtained in the relation collection phase along with the other necessary inputs with respect to NFS class of algorithms. The second sub-phase deals with matrix reduction in which various strategies such as duplicate removal, singleton removal, clique removal and merge are applied to reduce the overall matrix size preserving the sparsity at the same time. Algorithms for the first and second phases are designed and analyzed in the paper. The experiments are conducted on the relations collected from standard tool CADO-NFS and the results are reported. From the results, it is shown that the filter map structure presented in the current work for matrix representation helps to improve the overall performance of filtering module. Specifically, the method to handle duplicates in the matrix instead of the traditional method improves the duplicate removal module of filtering. Additionally, an optimized clique removal method of filtering which is introduced in the present work further improves the performance of filtering. [ABSTRACT FROM AUTHOR]

A fractional-order proportional integral derivative (FOPID)controller has replaced the classical PID controller used in industries for process control application. FOPID is less sensitive to the change of control parameters than PID Controller, due to which better results are obtained. The FOPID provides a robust and stable system for a higher-order system as of iso- damping property. This study aims to find a stable and controlled structure by tuning the FOPID controller with the Particle Swarm Optimization (PSO) algorithm, fuzzy-based logic approach, and Adaptive Neuro-fuzzy inference system (ANFIS). The tuning of FOPID is done to overcome deficits of PID controller using the different types of optimization method to overcome large overshoot and large settling time. This paper presented useful techniques based on PSO, fuzzy logic, and ANFIS to optimize FOPID controlled high-performance drilling machines. On the analysis and comparisons of simulation findings, it is observed that the FOPID-PSO approach provides better performance over the Ziegler-Nichols (ZN)-FOPID and the above-mentioned intelligent techniques in terms of less settling time (ts=0.823sec.) & optimized peak overshoot (Mp=2.44%) for the mentioned target. [ABSTRACT FROM AUTHOR]

The main contribution of this paper is inspired by the question "Can six-phase doubly-fed induction generator (6-Φ-DFIG) work in unhealthy (with one or more phases open-circuited) conditions or not?". The conventional DFIG cannot work under open-phase conditions, while the novel 6-Φ-DFIG can operate with one or more phases open-circuited. This paper addresses the mathematical and simulation-based modelling of the novel 6-Φ-DFIG operation under open-phase faults. Moreover, the advantages of the novel 6-Φ-DFIG are also illustrated in this paper. Simulation results validate the mathematical modelling of the novel 6-Φ-DFIG due to an open phase for the post-fault conditions. To the best of the authors' knowledge, the proposed novel 6-Φ-DFIG has never been modelled and simulated for open-phase conditions anywhere in the world. [ABSTRACT FROM AUTHOR]

In this paper, the concept of one switched-inductor Z-source inverter is extended to improved switched-capacitor inductor ZSI. In the proposed inverter, capacitors are used instead of the side diodes of the one switched inductor Z-source inverter. The proposed inverter improved voltage gain and boost factor compared to the switched-inductor Z-source inverter and the switched-inductor quasi Z-source inverter. The improved switched-inductor-capacitor Z-source inverter reduces the stress to capacitor voltage. The proposed inverter in this paper can be extended up to the n cascade, thus achieving a higher boost factor of a low duty cycle. The performance of the proposed structure at different operating modes is investigated, and the voltage equations are calculated. The analysis, derivation of the stress of switches voltage, the stress of capacitors voltage, the stress of diode voltage, the stress of inductor current, the gain of voltage, and the boost factor of the proposed inverters are carried out are compared with the similar inverters. To confirm the performance of the proposed converter, a laboratory sample of converters is made, in which, with V d c = 60 output for the improved switched-capacitor-inductor ZSI of converter, the DC-link (Vi) voltage is 200 with boost factor 1.67, which confirms the relationships obtained from the proposed converters. [ABSTRACT FROM AUTHOR]

Artificial Intelligence has changed our outlook towards the whole world, and it is regularly used to better understand all the data and information that surround us in our everyday lives. One such application of Artificial Intelligence in a real-world scenario is the extraction of data from various images and interpreting them in different ways. This includes applications like object detection, image segmentation, image restoration, etc. While every technique has its own area of application, image segmentation has a variety of applications extending from the complex medical field to regular pattern identification. The aim of this paper is to research about several FCNN-based semantic segmentation techniques to develop a deep learning model that is able to segment tumours in brain MRI images to a high degree of precision and accuracy. The aim is to try several different architectures and experiments with several loss functions to improve the accuracy of our model and obtain the best model for our classification including newer loss functions like dice loss function, hierarchical dice loss function cross entropy, etc. [ABSTRACT FROM AUTHOR]

A hardware-based memory-efficient sequence alignment architecture is described in this paper. This paper expresses a comprehensive blueprint of the hardware implementation of compact sequence alignment for pair-wise global alignment technique to achieve high-throughput processing. This architecture uses SRAM and only a small amount of digital logic circuitry to perform elementary operations of sequence alignment in real time. Additionally, this alignment engine does not require any preprocessing operations like in most of the existing alignment approaches do. Furthermore, it does not call for any sort of comparison mechanism for preparing final sequence alignment by the alignment co-processor. The entire architecture is simulated and synthesized in FPGA board for numerous cases considering dissimilar pseudo-randomly generated sequence pairs with variable sequence lengths ranging from 16 to 2048 nucleotides. The proposed design exhibits compact alignment of the sequences that leads to the identification of close similarity between the sequences under test. Moreover, the proposed alignment engine takes significantly less amount of time, ≈64–95% less time, and ≈85–99% less amount of memory space than existing alignment approaches. The overall system performance is studied with respect to Millions Alignments Per Second (MAPS) and exhibits ≈55–75% more sequence alignments of same set of DNA sequences in a stipulated time compared to existing schemes. [ABSTRACT FROM AUTHOR]

In this paper, a novel approach for condition and performance monitoring of induction motor through estimated motor losses is proposed and explained. The novelty in the proposed approach is minimal non-intrusive measurements and does not require disconnection of motors from the load. In many systems, the losses measured directly or indirectly in a motor are of the lump sum in nature. The main advantage of the system prescribed in this paper gives losses in the segregated form, which is directly used to assess the internal condition of the motor. This approach will assess the condition of induction motors for internal faults such as stator faults, rotor faults, core faults, bearings faults, etc. The equivalent circuit parameters and motor losses are estimated using the developed Genetic Algorithm (GA). The estimated motor loss data are compared with the NEMA & IE Standards and if any deviation found will be reported as faults. The reported information is linked to the developed fuzzy algorithm to identify the faults exactly along with its severity level. The proposed approach was tested and evaluated with the help of LT motors ranging from 5 to 200 HP in real-time from a selected industry. [ABSTRACT FROM AUTHOR]

The power optimization is one of the biggest challenging issues for designing of VLSI circuits within the advanced technology. The reversible logic is one among the best approaches for low power application. This logic has wide applications in the communication, nanotechnology, digital signal processing, computer graphics, optical computing, etc. In this paper, some proposed reversible magnitude comparator has been designed using the prevailing reversible gates and implemented using gate diffusion input (GDI) technique. The design methodologies are also proposed for the designing of N-bit comparator. The main objective of this paper is to design and implementation of reversible magnitude comparator using some proposed methods and compares them with the existing circuits in terms of constant input, garbage output, number of reversible gates, and quantum cost. The transistor implementations of the proposed comparators are done by the combination of CMOS and GDI technique in EDA Tanner tools. After the design and analysis of proposed comparators it has been found that the proposed-2 logic based 4-bit comparator has lowest quantum cost which is equal to 38 and the proposed-3 logic based 4-bit comparator has lowest constant input and garbage output which is equal to 8 and 13. [ABSTRACT FROM AUTHOR]