Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study on The Factors Affecting The Continuous Use of E-Government Services - Focused on Privacy and Security Concerns-

In this study, we conducted a survey of those who have used E-Government Services (civil servants, employees of public institutions, and the public) to empirically identify the factors affecting the continuous use intention E-Government Services, and conducted an empirical analysis using SPSS and Smart PLS with 284 valid samples except for dual, error and poor answers. Based on the success model of the information system (IS access model), we set independent variables which were divided into quality factors (service quality, system quality, information quality) and risk factors (personal information and security), and perceived ease of use and reliability, which are the main variables based on the technology acceptance model (TAM) that best describes the parameter group, were established as useful parameters. In addition, we design the research model by setting user satisfaction and the continuous use intention as dependent variables, conducted the study about how affecting factors influence to the acceptance factors through 14 hypotheses.The study found that 12 from 14 hypotheses were adopted and 2 were rejected. Looking at the results derived, it was analyzed that, firstly, 3 quality factors all affect perceived ease of use in relation to the quality of service, system quality, information quality which are perceived ease of use of E-Government Services. Second, in relation to the quality of service quality, system quality, information quality and perceived usefulness which are the quality factors of E-Government Services, the quality of service and information quality affect perceived usefulness, but system quality does not affect perceived usefulness. Third, it was analyzed that both factors influence reliability in the relationship between Privacy and security and trust which are risk factors. Fourth, the relationship between perceived ease of use and perceived usefulness has shown that perceived ease of use does not affect perceived usefulness. Finally, the relationship between user value factors (perceptual usability, perceived usefulness and trust) and user satisfaction and the continuous use intention was analyzed that user value factors affect user satisfaction while user satisfaction affects the continuous use intention. This study can be meaningful in that it theoretically presented the factors influencing the continued acceptance of e-government services through precedent research, presented the variables and measurement items verified through the empirical analysis process, and verified the causal relationship between the variables. The e-government service can contribute to the implementation of e-government in line with the era of the 4th Industrial Revolution by using it as a reference to the establishment of policies to improve the quality of people's lives and provide convenient services to the people.
Differential Power Processing based Photovoltaic Power Systems: A Review

The internal and external mismatches experienced on photovoltaic (PV) cells will reduce the actual output power. Compared with the full power processing (FPP) architecture, differential power processing (DPP) architectures achieve high system reliable and efficiency by processing a fraction of total power when maintaining the operation of distributed local maximum power point (MPP). This paper presents a comprehensive review of different DPP architectures in terms of the connection, power converter topologies, and MPPT control. The conclusion was drawn based on the literature review and evaluation.
Composite Fuzzy and Current Reference based Peak Power Tracking for Micro Wind Turbine

Power characteristics of a wind turbine follows the hill-shape according to the speed of the wind supplied. Tracking maximum power point is more complex as compared to PV-MPPT techniques, the reason being high intermittence than solar power. The perturb and observe MPPT algorithm is applicable to wind turbines as well, the advantage of which is the lesser switching stress on the controlled semiconductor switch. The disadvantages of this conventional method include the delay to reach maximum power point as compared to the newly developing soft computing based tracking methods, which can have better peak seeking speed and better global search capabilities, but will cause higher switching stress on the switching device. This paper presents a composite control algorithm for wind energy conversion system, where fast behaviour of fuzzy-logic based control to achieve peak power point and lesser switching stress given by current reference based control, are combined to form one single system.
A Literature Survey of Optimization Techniques for Satellite Image Segmentation

The satellite image segmentation is a key area for current research and numerous work has been done for exploration of this area. The nature inspired optimization algorithms are very promising with image segmentation techniques to provide a platform for processing of satellite images. In this paper a literature review of different nature based optimization algorithms such as modified artificial bee colony (MABC) algorithm, ABC algorithm, particle swarm optimization (PSO), Darwinian PSO, genetic algorithm (GA), Wind driven optimization (WDO) and cuckoo search(CS) using different objective functions has been discussed to find the optimized multilevel thresholds. These nature influenced optimization methods and their performances are compared using different objective functions for optimal multilevel thresholding. The comparative study shows that the MABC algorithm and different variants of CS algorithm are very strong and accurate in results generating using image segmentation. Both methods search multilevel thresholds very efficiently and correctly, and in MABC an improved bee’s search solution are used and in CS the cuckoo search solution are used.
An Unscented Rao-Blackwellised Particle Filter for Prognostics and Remaining Useful Life Estimation of Battery

In this paper, an algorithm for prognostics and remaining useful life estimation of battery with an improvement in terms of variances of parameter estimation compared to particle filter is proposed. The algorithm inherits the Rao-Blackwellised particle filtering concept in that the hidden state parameters are arranged into continuous and approximately discrete states which are estimated by an unscented Kalman filter and a particle filter respectively. Simulation results are provided for performance comparison in terms of accuracy in parameter and remaining useful life (RUL) estimations and 90% prediction intervals (PI) in prognoses of the proposed algorithm and the generic particle filter in a battery prognostics system.
OCAE: Organization-Controlled Autoencoder for Unsupervised Speech Emotion Analysis

One of the severe obstacles to speech emotion analysis is the lack of reasonable labelled speech signal. Thus, an important issue to be considered is applying an unsupervised method to generate a representation in low dimension to analyze emotions. Such a representation coming from data needs to be stable and meaningful, just like the 2D or 3D representation of emotions elaborated by psychology. In this paper, we propose a fully unsupervised approach, called Organization-Controlled AutoEncoder (OCAE), combining autoencoder with PCA to build an emotional representation. We utilize the result of PCA on speech features to control the organization of the data in the latent space of autoencoder, through adding an organization loss to the classical objective function. Indeed, PCA can keep the organization of the data, whereas autoencoder leads to better discrimination of the data. By combining both, we can take advantage of each method. The results on Emo-DB and SEMAINE database show that our representation generated in an unsupervised manner is meaningful and stable.
Automatic labeling of traffic sound recordings using autoencoder-derived features

An approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted into a 2-dimensional form of Mel-cepstrogram. Next, the sequence of mel-cepstrograms is processed by the autoencoder neural network, which assigns a unique embedding to each of processed mel-cepstrograms. The embeddings may be treated as features which can be fed on the input of other machine learning-based classifiers. In our research, we prepared such an autoencoder and compared it with a standard solution of parameterization consisting of averaging MFCC throughout all the analyzed frames. Both types of features were then treated as an input for selected types classifiers. It was found, that parameters derived by the autoencoder neural network may be useful for improving the performance of classifiers in case of problematic classes such as detection of single and multiple vehicles passes.
Voltage Controlled PFC Based Interleaved Synchronous Buck Converter BLDC motor

In this work power factor improvement and harmonic minimization for the interleaved synchronous buck converter connected through the nonlinear load is proposed. The interleaved converter supplied with 240V and reaches 12V as output. The converter output always connected with variable distorting loads caused by nonlinear element present in the circuit, causes lower power factor with more induced harmonics. Linear PLL can be programmed to synchronize with the reference clock signal to point out for proper switching operation of the MOSFET to get desired output. The VCPFC controller designed using MATLAB Simulink with controlled power factor and reduced harmonics. Controller output waveforms are examined and analyzed with other controller performances. The converter is rated with 2mA, 1mH, and $1000\mu \mathrm{F}$ values. The chopper is tested for different resistive loads and inductive loads.
Study on the Effect of the Intake Port Configuration on the In-cylinder of Small Engine

The airflow in the engine cylinder is known to greatly affect the performance of the engine. Therefore, the main objective of this study is to evaluate the flow characteristics of the in-cylinder small engine to see the effect of the intake port configuration at equivalent rated engine speed using simulation model under various intake valve lift conditions. Geometry engine created using CAD software, then exported and analyzed using CONVERGE. The turbulence model is observed using a modified model (RNG) k-ɛ. The pressure boundary conditions are used to determine the pressure fluid at the intake and exhaust port. The result shows that the change combination of the intake port give effect to swirl ratio value. The helical intake port with same direction have the highest swirl ratio during intake and compression stroke around thirteen times compare to the original model in valve lift maximum. The change combination of the intake port also give effect to the tumble ratio where the maximum tumble ratio occurs at the helical port with same direction where the maximum increase at 460 °CA around 83 % and the minimum tumble ratio occurs at helical port with opposite direction where the maximum decrease at 460 °CA around 83 %. The change combination of the intake port also give effect to increase the turbulent kinetic energy where the maximum increase around 300 % for model with same direction and 240 % for model with opposite direction and length scale also increase 35 % for model with same direction and 40 % for model with opposite direction. Finally, it is concluding that the analysis carried in this work is useful in predicting the flow and in-turn optimizing combustion chamber of the engine.
Design and Evaluation of a Novel Microprocessor-Controlled Prosthetic Knee

Transfemoral amputees demand a mechatronic lower limb prosthesis as technical substitute for restoring their gait functions. Prosthetic knee is the key component of a transfemoral prosthesis. The performance of the prosthetic knee determines the walking ability of the transfemoral amputee. This study proposed a novel microprocessor-controlled prosthetic knee with hydraulic damper and evaluated the performance of the prosthetic knee by function simulation and evaluation platform. The prosthetic knee with electrical-controlled hydraulic cylinder that could modulate knee flexion and extension damping properties independently and continuously by single motor was designed. Gait phase identification system based on knee angle sensor, inertial measurement units mounted on thigh connector and shank and force transducer embedded in shank was proposed. Gait phase identification and damping control strategy were determined by typical gait events during walking. Speed adaption and gait symmetry tests were conducted with a customized gait simulator to evaluate the performance of the proposed microprocessor-controlled prosthetic knee. The angle trajectories of the prosthetic knee were similar under a range of walking speeds. While the symmetry index values indicated that the stance phase was more asymmetry than swing phase, the peak swing flexion knee angles were consistently controlled between 60–70 degrees under different speeds. The knee angle symmetry was observed in different speeds during swing phase. It is suggested that the proposed microprocessor-controlled prosthetic knee could meet the fundamental demands of walking with smooth angular transition across different walking speeds.
Automatic Detection of Regular Geometrical Shapes in Photograph using Machine Learning Approach

We propose a model for automatic detection of regular geometrical shapes in a photograph. The proposed framework uses a machine learning approach to detect shapes based on geometrical features. The geometrical shapes are elements of compositions in a photograph. Usually, the regular shapes play a very important role in photo aesthetic analysis. They provide a good amount of aesthetic score to photographs. The developed model is a multi-class classifier using Random Forest based on 9 distinct geometrical features, which can detect and classify the regular shapes into ‘Circle’, ‘Rectangle’, ‘Square’, and ‘Triangle’. We test our model on a ground truth dataset containing 250 images. The experimental result shows that the proposed model gives the accuracy up to 96%, which outperforms the current state-of-the-art. Its application to the problem of aesthetic score evaluation of photographs, and online guidance to amateur photographers to improve their photography skill.
A Probability-Based Multimetric Routing Protocol for Vehicular Ad Hoc Networks in Urban Scenarios

Vehicular Ad hoc Networks have received considerable attention in recent years and are considered as one of the most promising ad-hoc network technologies for intelligent transport systems. Vehicular Ad hoc Networks have special requirements and unique characteristics (e.g., special mobility patterns, short life links, rapid topology changes) which make the design of suitable routing protocols, a challenge. Consequently, an efficient routing protocol that fits with VANETs’ requirements and characteristics is a crucial task to obtain a good performance in terms of average percentage of packet losses and average end-to-end packet delay. To attain this goal, we propose a novel probabilistic multimetric routing protocol (ProMRP) that is specially designed for VANETs. ProMRP estimates the probability for each neighbor of the node currently carrying the packet, to successfully deliver a packet to destination. This probability is computed based on four designed metrics: distance to destination, node’s position, available bandwidth and nodes’ density. Furthermore, an improved version of ProMRP called EProMRP is also proposed. EProMRP includes an algorithm that accurately estimates the current position of nodes in the moment of sending the packet instead of using the last updated position obtained from the previous beacon message. Simulations are carried out in a realistic urban scenario using OMNeT++/VEINS/SUMO, including real maps from the OpenStreetMaps platform. Simulation results show a better performance of ProMRP and EProMRP compared to recent similar proposals found in the literature in terms of packet losses and end-to-end packet delay, for different vehicles’ densities.
Effect of Optical and Structural Parameters of Thermal Barrier Coatings of the Combustion Chamber on Working Processes of a Diesel

The paper describes the bulk mean thermodynamic parameters of the combustion space in the diesel engine cylinder during the whole operating cycle adjusted consideration the features of heat transfer between the working fluid and the combustion chamber wall made of (or coated) thermal barrier materials using semitransparent ceramics. The novelty of this study is a simulation of convective and radiant heat exchange by the forming gas atmosphere and the generating soot microparticle cloud near heat insulated walls with a temperature regime determined by the significant influence of the optical parameters of thermal barrier materials or coatings. The total thermal radiant flux within the IR long and short wavelength range was modeled as a part of the convective-radiant heat flux. The temperature regime of insulation material (with a transparency band up to $\sim 3-4 \mu m$) was mainly determined by exposure of penetrating radiation component (~ 1-2 $\mu m)$ primarily from red-hot soot particles. For the first time, the model developed by the authors suggests the study of convective and radiant processes in different locations within the chamber due to the temperature regime of the exposed semitransparent thermal barrier coatings with subsurface (internal) radiant thermal source with the power which is independently determined by its microstructure and optical parameters. The proposed physical model based on the independent impact of the long and short wavelength components allowed the authors to modify the traditional semi-empirical approximation of by including (for example, in the Annand formula) the real value without any correlating constants. The remaining additive radiant part used for solving a nonlinear problem of radiant-conductive heat transfer within the wall with TBC to determine its specified surface temperature Tw for further iterative and cyclic calculations depending on the angular rotation rate of the engine crankshaft.
A Method of Parameter Estimation and Suppression for Smeared Spectrum Jamming

We address the problem of suppressing smeared spectrum (SMSP) jamming from the received mixed signal of radar. In order to come up with a novel suppression algorithm based on parameter estimation, we resort to the time-frequency analysis of jamming signal. The short-time Fourier transform (STFT) of jamming signal is derived. Based on the fact that the jamming-to-target ratio (JSR) is always positive, the estimation methods for different parameters of SMSP jamming are given. The jamming signal is reconstructed and then suppressed by subtracting it from the mixed signal. The estimated performance of this method is verified by Monte Carlo simulation, and the results indicate the effectiveness of the proposed method.
Investigating Deep CNNs Models Applied in Kinship Verification through Facial Images

The kinship verification through facial images is ana ctive research topic due to its potential applications. In this paper, we propose an approach which takes two images as input then give kinship result (kinship / No-kinship) as an output. our approach based on the deep learning model (ResNet) for the feature extraction step, alongside with our proposed pair feature representation function and RankFeatures (Ttest) for feature selection to reduce the number of features finally we use the SVM classifier for the decision of kinship verification. The approach contains three steps which are: (1) face preprocessing, (2) deep features extraction and pair features representation (3) Classification. Experiments are conducted on five public databases. The experimental results show that our approach is comparable with existed approaches.
Energy Optimization on a Wind Power System Operating at Variable Wind Speeds

In the present paper we analyze the operation of a wind power system at maximum power, at rapid variations in wind speed over time. Measuring wind speed and mechanical angular velocity determines the mathematical model of the wind turbine, optimal mechanical angular velocity, mathematical model of the synchronous generator with permanent magnets and dependence on the wind speed of the optimal mechanical angular velocity. It brings the wind power system to the optimal area by changing the load to the generator. The simulations are based on solving the differential momentum of the kinetic momentum, determining the variation in time of the mechanical angular velocity at a certain load of the generator and calculating the power at the wind turbine and the synchronous generator so that the generator load is in the optimal area and stable. The functioning of the wind power system in GALBIORI - Dobrogea area (Romania) is analyzed. Finally, we present the algorithm for calculating the power at the generator, knowing the value of the optimal mechanical angular velocity.
Substantiation of Band Limits for Measuring Acoustic Signals of Partial Discharges in High-Voltage Power Transformers

Analysis of characteristics of partial discharges is an effective method of evaluating the current technical condition of high-voltage equipment. An acoustic method of measuring partial discharges in high-voltage power transformers allows not only to identify insulation faults, but also to locate their position. When performing an acoustic method using external sensors, it is necessary to determine a frequency band, where the measurement of acoustic signals is especially effective. The article provides a study of an impedance mathematical model that takes into account the primary acoustic properties of an oil-filled transformer as a multilayer object. We obtained values of dependence of the acoustic signal transmittance on the frequency. On the basis of the conducted studies, we identified the band limits recommended for practical measurements, development of monitoring systems, and troubleshooting of high-voltage power transformers.
An Improved Single Phase Asymmetric Reduced Device Count Multilevel Inverter

This paper proposes a new single phase multilevel inverter structure based on an improved fundamental module that utilizes two dc voltage sources and five switches. The functioning of the fundamental module in both symmetric and asymmetric modes is explained in detail. The generalized structure based on the proposed fundamental module and the equations employed to find out the magnitudes of the dc sources are also derived. Nine level and forty nine level inverters are developed and the proposed structures are validated adequately through simulations. The metrics of the proposed reduced device count structure is compared with that of the recently proposed similar structure with regard to the amount of switches, sources and level to switch ratio to demonstrate the precedence of the proposed structure.