bluuebunny/crossref_metadata_2025 huggingface dataset:
Technical Performance Comparison of Horizontal and Vertical Ground-Source Heat Pump Systems
Authors: Gao Wu , Masum Shakil , Jiang Liangliang
Published: September 2023

The configurations of ground heat exchangers (GHEs) play a significant role in the efficiency and sustainability of ground-source heat pump (GSHP) systems. However, there is a knowledge gap in understanding the performance differences between the horizontal and vertical GSHP systems in the same project under various heating and cooling demands. In this study, a technical performance comparison between GSHP systems coupled with horizontal ground loops and vertical boreholes under three scenarios of heating-to-cooling ratios (6 : 1, 2.4 : 1, and 1 : 1) was conducted. The simulations were based on a coupled thermal–hydraulic model for unsaturated soils that takes into account realistic ground surface boundary, GHE boundary, and the dynamics of heat pump efficiency. The GHEs were designed based on an experimental site located on the campus of a UK university. Results showed significant differences in the development of fluid temperatures and coefficient of performance (COP) of heat pumps between the horizontal and vertical GSHP systems due to the differences in the soil profiles and temperature boundaries. Both the fluid temperatures and heat pump COPs in the horizontal GSHP system reached a steady annual cycle after 2 years regardless of the heating-to-cooling ratios. For the vertical system, a general downward trend in the fluid temperatures and the COP of the heat pump in the heating mode can be found when a heating-to-cooling ratio was 6 : 1 or 2.4 : 1, while an overall upward trend in the fluid temperatures and the COP of the heat pump in the heating mode can be noted in the case of 1 : 1 heating-to-cooling ratio. Additionally, the heat pump operating in the cooling mode was off most of the time when a heating-to-cooling ratio was 6 : 1 or 2.4 : 1, while a declining trend in the COP of the heat pump in the cooling mode was exhibited in the case of a heating-to-cooling ratio of 1 : 1. The technical comparison reveals that the heating-to-cooling ratios would significantly affect the efficiency and sustainability of both GSHP systems.
Varying the energisation condition to mitigate sympathetic inrush current
Authors: Nadhirah Nurul Fatin , Halim Hana Abdull , Mukhtar Nurhakimah Mohd , Zali Samila Mat
Published: September 2023

Transformers are generally easy to access and can contribute significantly to entire power system. When a transformer is turned on for the first time, it produces a magnetising inrush current which acts as a starting current. Energisation of transformer has a substantial impact on inrush current and transformer that are connected in parallel. Sympathetic inrush current is a phenomenon that appears when a transformer is switched-on in network whereas the other transformers that was earlier energised. Besides, when sympathetic inrush phenomena occur, the peak and period fluctuate significantly. In this paper, the transformers will be energised in three different ways and each condition will be explored in depth. The operation time of the transformer’s energisation whether it is energised simultaneously or at different times are tested and analysed in terms of their characteristics. It is performed using power system computer aided design (PSCAD) software, starting with a develop model of the energisation and then generate the outcomes. The results of the simulation demonstrate that energising the transformer in different ways can give different effect on the sympathetic inrush current, as well as the variables that affect it and methods for reducing it.
Improving the efficiency of photovoltaic cells embedded in floating buoys
Authors: Nazerian Vahdat , Asadollahi Hossein , Sutikno Tole
Published: September 2023

Solar cells are used to power floating buoys, which is one of their applications. Floating buoys are devices that are placed on the sea and ocean surfaces to provide various information to the floats. Because these cells are subjected to varying environmental conditions, modeling and simulating photovoltaic cells enables us to install cells with higher efficiency and performance in them. The parameters of the single diode model are examined in this article so that the I-V, P-V diagrams, and characteristics of the cadmium telluride (CdTe) photovoltaic cell designed with three layers (CdTe, CdS, and SnOx) can be extracted using A solar cell capacitance simulator (SCAPS) software, and we obtain the parameters of the single diode model using the ant colony optimization (ACO) algorithm. In this paper, the objective function is root mean square error (RMSE), and the best value obtained after 30 runs is 5.2217×10-5 in 2.46 seconds per iteration, indicating a good agreement between the simulated model and the real model and outperforms many other algorithms that have been developed thus far. The above optimization with 200 iterations, a population of 30, and 84 points was completed on a server with 32 gigabytes of random-access memory (RAM) and 30 processing cores.
Fault localization on power cables using time delay estimation of partial discharge signals
Authors: Fern Chin Kui , Yii Chai Chang , Bakar Asfarina Abu , Saad Ismail , Tze Kin Kenneth Teo , Ikhsan Megat Hasnan Megat Muhammad , Mohamad Nur Aqilah
Published: September 2023

Precise localization of partial discharge (PD) sources on power cables is vital to prevent power line failures that can lead to significant economic losses for electrical suppliers. This study proposes four methods to estimate the time delay of PD signals under electromagnetic interference, including white Gaussian noise (WGN) and discrete sinusoidal interference (DSI), using denoised PD signals with signal-to-noise ratios ranging from 10.6 to -7.02 dB. The maximum peak detection (MPD) and cross-correlation (CC) approaches, as well as two new techniques, interpolation cross-correlation (ICC) and envelope cross-correlation (ECC), are evaluated for their effectiveness in PD source localization. The researchers employ the time difference of arrival (TDoA) algorithm to compute PD location using the double-end PD location algorithm, where the PD location precision serves as an indicator of the accuracy of the time delay estimation methods. The study concludes that CC and ICC are the most suitable methods for estimating the time delay of PD signals in the PD location algorithm, as they exhibit the lowest error rates. These results suggest that CC and ICC can be used effectively for precise PD source localization under electromagnetic interference on power cables.
Measurement of energy poverty in the Colombian Caribbean region: a comparative analysis
Authors: Bayona-Velásquez Etna , Núñez-Alvarez José Ricardo , Pirela-Ríos Ana , Marín-Giraldo Ever
Published: September 2023

This research work is directed to analyze the level of energy poverty and its consequences on the quality of life of the population of the Colombian Caribbean region, by doing a comparison of the results obtained in that area with data regarding the population of Bogotá, capital of Colombia, and of the rest of the country. The method of meeting absolute energy needs was used to determine the energy poverty index at households (EPH). Results obtained indicate that EPH exceeds 60% in urban areas, and 96% in rural zones, where it was also evidenced a clear link between energy poverty and school dropout.
Development of spiral square coils for magnetic labelling detection in microfluidic systems
Authors: Feddag Abdelhadi , Mekkakia-Maaza Nasr-Eddine , Lakhdari Abdelghani
Published: September 2023

Due to the development of microfluidic systems biomedical microelectromechanical systems (BioMEMS) for magnetic labelling detection by magnetic microbeads circling in microfluidic channels, we used the magnetic field created by microcoils. The magnetic field associated with the electric current, but with negatively affects if its value increases too much. Handling bio-species in the microfluidic chip requires that the temperature maintained to keep the cells to prevent their destruction. In this paper we have described the spiral square coil design of different structures to produce an effective magnetic flux density. The simulation of the magnetic flux density is carried out with the help of the COMSOL software. We have presented an optimization of the geometric parameters of the microcoil for a better performance and a miniaturization of the structure with copper wire section S=25 µm2 and inter-wire space a=5 µm. We have also developed this microcoil by adding a ferromagnetic core to the inner center, the results obtained in this work shown that the magnetic flux density increases around 1.07 times in Bx and 1.45 times in Bz. This new approach in designing a microcoil allows to obtaining a fast trapping of the microbeads and a highly sensitive biological element detection and avoiding increase heat ratio in microfluidic systems.
Optimal inverter-based distributed generation in ULP Way Halim considering harmonic distortion
Authors: Sofyan Sofyan , Faraby Muhira Dzar , Akhmad Satriani Said , Gaffar Ahmad , Fitriati Andi , Elviralita Yoan , Muchtar Akhyar
Published: September 2023

Integration of distributed generation (DG) based on the use of new renewable energy is considered to be able to increase the capability of the electric power distribution system. However, the use of inverter-based DG is not optimal, it can worsen the condition of the system, especially in terms of the spread of harmonic distortion which can damage the equipment. This is due to the inverter-based DG technology, apart from supplying electrical energy, DG also injects harmonic currents from existing semiconductor components. This research discusses optimization placement of inverter-based DG using the multi objective particle swarm optimization (MOPSO) method which was tested on the Unit Layanan Pelaksana (ULP) Way Halim 88-bus radial distribution system based on MALTAB 2020b to increase the efficiency of the electrical system by reducing losses and %THDv. The inverter-based DG placed on 24 bus points with a capacity of 690 kW can reduce losses by up to 12.74 kW or 14.96% and all %THDv values for each bus are below 5%.
Optimal placement of battery energy storage system considering penetration of distributed generations
Authors: Nguyen Thuan Thanh , Nguyen Hoai Phong , Duong Thanh Long
Published: September 2023

This paper proposes the optimal problem of location and power of the battery-energy-storage-system (BESS) on the distribution system (DS) considering different penetration levels of distributed generations (DGs). The objective is to minimize electricity cost of the DS in a typical day considering the power limit of DG fed to the DS. Growth optimizer (GO) is first applied to search the BESS’s location and power for each interval of the day. The considered problem and GO method are evaluated on the 18-node DS with two penetrations levels of photovoltaic system and wind turbine. The results demonstrate that the optimal BESS placement significantly reduces electricity cost. Furthermore, the optimal BESS location and power also help to reduce the cut capacity of DGs as their power greater than the load demand. The compared results between GO and particle swarm optimization (PSO) method have shown that GO reaches the better performance than PSO in term the optimal solution and the statistical results. Thus, GO is an effective approach for the BESS placement problem.
Dynamic voltage restorer quality improvement analysis using particle swarm optimization and artificial neural networks for voltage sag mitigation
Authors: Siregar Yulianta , Muhammad Maulaya , Arief Yanuar Zulardiansyah , Mubarakah Naemah , Soeharwinto Soeharwinto , Dinzi Riswan
Published: September 2023

Power quality is one of the problems in power systems, caused by increased nonlinear loads and short circuit faults. Short circuits often occur in power systems and generally cause voltage sags that can damage sensitive loads. Dynamic voltage restorer (DVR) is an efficient and flexible solution for overcoming voltage sag problems. The control system on the DVR plays an important role in improving the quality of voltage injection applied to the network. DVR control systems based on particle swarm optimization (PSO) and artificial neural networks (ANN) were proposed in this study to assess better controllers applied to DVRs. In this study, a simulation of voltage sag due to a 3-phase short-circuit fault was carried out based on a load of 70% of the total load and a fault location point of 75% of the feeder’s length. The simulation was carried out on the SB 02 Sibolga feeder. Modeling and simulation results are carried out with MATLAB-Simulink. The simulation results show that DVR-PSO and DVR-ANN successfully recover voltage sag by supplying voltage at each phase. Based on the results of the analysis shows that DVR-ANN outperforms DVR-PSO in quality and voltage injection into the network.
Single-phase binary phase-shift keying, quadrature phase shift keying demodulators using an XOR gate as a phase detector
Authors: Kaewmunee Apinut , Khumsat Phanumas
Published: September 2023

A single-phase/single-loop multiple-phase-shift-keying (m-PSK) demodulator is described. The demodulator relies on a linear range of an exclusive-OR (XOR) gate employed as a phase detector. The phase controller takes the average output from the XOR gate and performs a sub-ranging/re-scaling operation to provide an input signal to a voltage-controlled oscillator (VCO). The demodulator is truly modular which theoretically can be extended for an m-PSK signal. The proposed single-phase binary-/quadrature-PSK (BPSK/QPSK) demodulators have been implemented with low-cost discrete components. The core of the phase controller simply relies on number of stages of a full-wave rectifier and a linear amplifier built from well-known op-amp-based negative feedback circuits. The demodulator prototypes operate from a single supply of 5 V. At a carrier frequency of 100 kHz, both the BPSK and QPSK demodulators achieved the maximum symbol rate of 20 ksymbol/s respectively. At these symbol rates, the BPSK and QPSK demodulators deliver symbol-error rates less than 2×10-10 and 7×10-10.
A 1.8 V 25 Mbps CMOS single-phase, phase-locked loop-based BPSK, QPSK demodulator
Authors: Chaichomnan Chutpipat , Khumsat Phanumas
Published: September 2023

A single-phase binary/quadrature phase-shift keying (BPSK/QPSK) demodulator basing on a phase-locked loop (PLL) is described. The demodulator relies on a linear characteristic a rising-edge RESET/SET flip-flop (RSFF) employed as a phase detector. The phase controller takes the average output from the RSFF and performs a sub-ranging/re-scaling operation to provide an input signal to a voltage-controlled oscillator (VCO). The demodulator is truly modular which theoretically can be extended for a multiple-PSK (m-PSK) signal. Symbol-error rate analysis has also been extensively carried out. The proposed BPSK and QPSK demodulators have been fabricated in a 0.18-mm digital complementary metal–oxide–semiconductor (CMOS) process where they operate from a single supply of 1.8 V. At a carrier frequency of 60 MHz, the BPSK and QPSK demodulators achieved maximum symbol rates of 25 and 12.5 Msymb/s while consuming 0.68 and 0.79 mW, respectively. At these maximum symbol rates, the BPSK and QPSK demodulators deliver symbol-error rates less than 7.9×10-10 and 9.8×10-10, respectively where their corresponding energy per bit figures were at 27.2 and 31.7 pJ.
A survey of scan-capture power reduction techniques
Authors: Sontakke Vijay , Dickhoff John
Published: September 2023

With the advent of sub-nanometer geometries, integrated circuits (ICs) are required to be checked for newer defects. While scan-based architectures help detect these defects using newer fault models, test data inflation happens, increasing test time and test cost. An automatic test pattern generator (ATPG) exercise’s multiple fault sites simultaneously to reduce test data which causes elevated switching activity during the capture cycle. The switching activity results in an IR drop exceeding the devices under test (DUT) specification. An increase in IR-drop leads to failure of the patterns and may cause good DUTs to fail the test. The problem is severe during at-speed scan testing, which uses a functional rated clock with a high frequency for the capture operation. Researchers have proposed several techniques to reduce capture power. They used various methods, including the reduction of switching activity. This paper reviews the recently proposed techniques. The principle, algorithm, and architecture used in them are discussed, along with key advantages and limitations. In addition, it provides a classification of the techniques based on the method used and its application. The goal is to present a survey of the techniques and prepare a platform for future development in capture power reduction during scan testing.
Improvement of the linear quadratic regulator control applied to a DC-DC boost converter driving a permanent magnet direct current motor
Authors: Bouchahed Adel , Assabaa Mohamed , Draidi Abdellah , Makhloufi Fateh , Belhani Ahmed
Published: September 2023

This article discusses a new robust control technique that enables the DC-DC boost converter driving a permanent magnet direct current (PMDC) motor to operate in high static and dynamic performances. The new technique is based on the design of a both linear quadratic regulator (LQR) and linear quadratic regulator-proportional integral (LQR-PI) type controllers, which have the advantage of eliminating oscillations, overshoots and fluctuations on different characteristics in steady-state system operation. In order to increase the output voltage, the LQR regulator is combined with a first-order system represented in the form of a closed-loop transfer function, the latter raising the output voltage to 24 volts, this voltage is enough to drive the permanent magnet direct current motor. The contribution of this paper is the creation of a robust control system represented in the form of a hybrid corrector able to regulate steady-state and transient disturbances and oscillations as well as to increase DC-DC boost converter output voltage for the PMDC motor to operate at rated voltage. The results of the three control techniques are validated by MATLAB Simulink.
Capacitor current analysis of a three-level neutral point clamped converter under unbalanced loading conditions
Authors: Thahab Riyadh Toman , Al-Mhana Tahani Hamodi , Thahab Ahmed Toman
Published: September 2023

A neutral point clamped (NPC) converter is considered a forefront in industrial applications. Supplying a typically balanced stand-alone load is one of those applications. However, the loading may become unbalanced which can impact the capacitors’ current and voltage ripple. In this work, an approach is proposed that analyze the capacitor current under unbalanced loading. The proposed method is based on a combination of two-dimensional Fourier series and symmetrical components. Since, two-dimensional Fourier series sectorize the spectrum into harmonics that are either defined by multiples of, fundamental, carrier or both frequencies, the method derives the Fourier coefficients for each sector, corresponding to a sequence current. Therefore, based on the presented approach, each harmonic amplitude in the spectrum sector is defined by three Fourier coefficients reflecting zero, positive and negative sequence current. The capacitor current spectrum is obtained by vector summing sequence coefficients. The method is tested on unbalanced load conditions with (out) a ground path. Results verify feasibility of the proposed method in deriving Fourier coefficients of capacitor currents that accurately reflects the loading status of the NPC. This is vital for converter design in terms of proper sizing of DC capacitor and can help in avoiding components failure.
Virtual environment for assistant mobile robot
Authors: Herrera Jorge Jaramillo , Jimenez-Moreno Robinson , Martinez Baquero Javier Eduardo
Published: September 2023

This paper shows the development of a virtual environment for a mobile robotic system with the ability to recognize basic voice commands, which are oriented to the recognition of a valid command of bring or take an object from a specific destination in residential spaces. The recognition of the voice command and the objects with which the robot will assist the user, is performed by a machine vision system based on the capture of the scene, where the robot is located. In relation to each captured image, a convolutional network based on regions is used with transfer learning, to identify the objects of interest. For human-robot interaction through voice, a convolutional neural network (CNN) of 6 convolution layers is used, oriented to recognize the commands to carry and bring specific objects inside the residential virtual environment. The use of convolutional networks allowed the adequate recognition of words and objects, which by means of the associated robot kinematics give rise to the execution of carry/bring commands, obtaining a navigation algorithm that operates successfully, where the manipulation of the objects exceeded 90%. Allowing the robot to move in the virtual environment even with the obstruction of objects in the navigation path.<
A robust super twisting fractional-order sliding mode-based control of vehicle longitudinal dynamic subjected to a constant actuator fault
Authors: Abzi Imane , Kabbaj Mohammed Nabil , Benbrahim Mohammed
Published: September 2023

This paper deals with the design and analysis of a super twisting fractional-order sliding mode controller (ST-FOSMC) to adjust the vehicle longitudinal dynamic when braking. While vehicle loading, road types, and modeling uncertainties are time-varying parameters, the control law must be robust against these disturbances. Also, the aging of the brake plate may introduce a difference between the control output and the actuator response that should be considered. The proposed control strategy has been used to enable the anti-lock braking system (ABS) to track the desired wheel slip value despite the presence of disturbances and constant actuator fault. The design of this controller is presented and the system stability is guaranteed by applying the Lyapunov theory. We carried out a simulation example that makes a comparison between our controller and the one based on the fractional-order sliding mode control to investigate which one of them outperforms the other. The results exhibit the superiority of the super twisting fractional order controller over the traditional fractional-order sliding mode controller during the braking phase.
Low-cost colorimetric setup for concentration measurement of manganese ions based on optical absorbance
Authors: Maidan Dali Mohd Rumaizan , Ali Nurul Hidayah , Mohamad Robi Fatin Izyani , Osman Mohamed Syazwan , Abd Rahman Mohamad Faizal
Published: September 2023

This study presents a cost-effective setup for measuring the concentration of Mn2+ ions using colorimetry. The current method involves a calibration curve created with expensive and large commercial laboratory-based instruments, limiting its use in financially constrained situations. To address this issue, the study proposes a low-cost setup consisting of a light-emitting diode and photodiode that utilizes colorimetric and absorbance effects for Mn2+ concentration measurement. Mn2+ colorimetric samples were prepared using the 1-(2-pyridylazo)-2-naphthol (PAN) method with concentrations ranging from 0.2 to 1.0 mg/L. The samples were tested using the proposed setup, followed by a spectrophotometry test to determine the optimal configuration for the setup. The validity of the setup was confirmed by measuring the voltage and calculating the optical absorbance, which exhibited a good correlation with the concentration, consistent with the initial expectation. The correlation coefficient for voltage and absorbance against Mn2+ concentration was found to be 0.9976 and 0.9987, respectively, indicating good linearity and suitability as a calibration curve for Mn2+ detection and measurement. Consequently, the study’s objectives were successfully achieved, and the proposed setup is considered a viable platform for more complex applications, such as real-time monitoring activities.
Two-link lower limb exoskeleton model control enhancement using computed torque
Authors: Parikesit Elang , Maneetham Dechrit
Published: September 2023

Robotic technology has recently been used to help stroke patients with gait and balance rehabilitation. Rehabilitation robots such as gait trainers are designed to assist patients in systematic, repetitive training sessions to speed up their recovery from injuries. Several control algorithms are commonly used on exoskeletons, such as proportional, integral and derivative (PID) as linear control. However, linear control has several disadvantages when applied to the exoskeleton, which has the problem of uncertainties such as load and stiffness variations of the patient’s lower limb. To improve the lower limb exoskeleton for the gait trainer, the computed torque controller (CTC) is introduced as a control approach in this study. When the dynamic properties of the system are only partially known, the computed torque controller is an essential nonlinear controller. A mathematical model forms the foundation of this controller. The suggested control approach’s effectiveness is evaluated using a model or scaled-down variation of the method. The performance of the suggested calculated torque control technique is then evaluated and contrasted with that of the PID controller. Because of this, the PID controller’s steady-state error in the downward direction can reach 5.6%, but the CTC can lower it to 2.125%.
A novel visual tracking scheme for unstructured indoor environments
Authors: Martinez Fredy , Montiel Holman , Martinez Fernando
Published: September 2023

In the ever-expanding sphere of assistive robotics, the pressing need for advanced methods capable of accurately tracking individuals within unstructured indoor settings has been magnified. This research endeavours to devise a realtime visual tracking mechanism that encapsulates high performance attributes while maintaining minimal computational requirements. Inspired by the neural processes of the human brain’s visual information handling, our innovative algorithm employs a pattern image, serving as an ephemeral memory, which facilitates the identification of motion within images. This tracking paradigm was subjected to rigorous testing on a Nao humanoid robot, demonstrating noteworthy outcomes in controlled laboratory conditions. The algorithm exhibited a remarkably low false detection rate, less than 4%, and target losses were recorded in merely 12% of instances, thus attesting to its successful operation. Moreover, the algorithm’s capacity to accurately estimate the direct distance to the target further substantiated its high efficacy. These compelling findings serve as a substantial contribution to assistive robotics. The proficient visual tracking methodology proposed herein holds the potential to markedly amplify the competencies of robots operating in dynamic, unstructured indoor settings, and set the foundation for a higher degree of complex interactive tasks.
Homogenous and interoperable signaling computer interlocking through IEC 61499 standard
Authors: Abourahim Ikram , Eleuldj Mohsine , Amghar Mustapha
Published: September 2023

The technological evolution of signaling systems has created a dependency from infrastructure managers to suppliers and industrials dominating the market. Indeed, for each deployed computer interlocking, the modification of field equipment is required to allow an adaptation with the new interlocking in terms of communication protocols and logical interface. In addition, to ensure safe traffic of trains, the communication of railway signaling data is necessary between interlockings. However, delayed deployments from one station to another make the establishment of communication channels costly and difficult, or even impossible, since each supplier keeps confidential its communication protocols and usually opts for interfacing based on wired logic. This paper presents our approach to a homogeneous architecture of interlocking meeting modularity requirements, interoperability, and logical interfacing between interlockings. This approach relies on a classification of internal functions of the computer interlocking, a distribution of the execution of those functions and making useful information available for interfaces between adjacent interlockings through the IEC 61499 standard coupled with service-oriented architecture (SOA).
Skin cancer classifier based on convolution residual neural network
Authors: Ajel Ahmed R. , Al-Dujaili Ayad Qasim , Hadi Zaid G. , Humaidi Amjad Jaleel
Published: September 2023

Accurate automatic classification of skin lesion images is a great challenge as the image features are very close in these images. Convolution neural networks (CNN) promise to provide a potential classifier for skin lesions. This work will present dermatologist-level classification of skin cancer by using residual network (ResNet-50) as a deep learning convolutional neural network (DLCNN) that maps images to class labels. It presents a classifier with a single CNN to automatically recognize benign and malignant skin images. The network inputs are only disease labels and image pixels. About 320 clinical images of the different diseases have been used to train CNN. The model performance has been tested with untrained images from the two labels. This model identifies the most common skin cancers and can be updated with a new unlimited number of images. The DLCNN trained by the ResNet-50 model showed good classification of the benign and malignant skin categories. The ResNet-50 as a DLCNN has verified a significant recognition rate of more than 97% on the testing images, which proves that the benign and malignant lesion skin images are properly classified.
Mixed H2/H∞ robust controllers in aircraft control problem
Authors: Satybaldina Dana , Dabayeva Aida , Kissikova Nurgul , Uskenbayeva Gulzhan , Shukirova Aliya
Published: September 2023

A leading cause of accidents during the landing phase of a flight lies in a considerable altitude loss by an aircraft as a result of the impact of a microburst of wind. One of the significant factors focuses primarily on the need to simultaneously satisfy various requirements regarding conditions of environmental disturbances and a wide range of systemic changes. The paper presents an algorithm for synthesizing an optimal controller that solves the mixed H2/H∞ control problem for the stabilization of aircraft in glide-path landing mode in the presence of uncertainty. Firstly, the principles of multi-criteria optimization are presented, and the mixed H2/H∞ problem is interpreted as the synthesis of a system with optimal quadratic performance, subject to its readiness to operate with the worst disturbance. Then, the ensuing section expounds upon the mathematical depiction of the vertical trajectory of aircraft, duly considering the perturbations imposed by wind phenomena. Subsequently, the effectiveness of mixed H2/H∞ control is confirmed compared to autonomous H2 or H∞ regulators through simulation outcomes acquired from the created system. Optimization based on a hybrid (mixed) criterion allowed combining the strengths of locally optimal systems based only on H2 or H∞ theory.
Thai culture image classification with transfer learning
Authors: Rattaphun Munlika , Songsri-in Kritaphat
Published: September 2023

Classifying images of Thai culture is important for a variety of applications, such as tourism, education, and cultural preservation. However, building a Machine learning model from scratch to classify Thai cultural images can be challenging due to the limited availability of annotated data. In this study, we investigate the use of transfer learning for the task of image classification on a dataset of Thai cultural images. We utilize three popular convolutional neural network models, namely MobileNet, EfficientNet, and residual network (ResNet) as baseline pre-trained models. Their performances were evaluated when they were trained from random initialization, used as a feature extractor, and fully fine-tuned. The results showed that all three models performed better in terms of accuracy and training time when they were used as a feature extractor, with EfficientNet achieving the highest accuracy of 95.87% while maintaining the training time of 24 ms/iteration. To better understand the reasoning behind the predictions made by the models, we deployed the gradient-weighted class activation mapping (Grad-CAM) visualization technique to generate heatmaps that the models attend to when making predictions. Both our quantitative and qualitative experiments demonstrated that transfer learning is an effective approach to image classification on Thai cultural images.
An enhanced fletcher-reeves-like conjugate gradient methods for image restoration
Authors: Hassan Basim A. , Jabbar Hawraz N. , Laylani Yoksal A. , Rahman Moghrabi Issam Abdul , Alissa Ali Joma
Published: September 2023

Noise is an unavoidable aspect of modern camera technology, causing a decline in the overall visual quality of the images. Efforts are underway to diminish noise without compromising essential image features like edges, corners, and other intricate structures. Numerous techniques have already been suggested by many researchers for noise reduction, each with its unique set of benefits and drawbacks. Denoising images is a basic challenge in image processing. We describe a two-phase approach for removing impulse noise in this study. The adaptive median filter (AMF) for salt-and-pepper noise identifies noise candidates in the first phase. The second step minimizes an edge-preserving regularization function using a novel hybrid conjugate gradient approach. To generate the new improved search direction, the new algorithm takes advantage of two well-known successful conjugate gradient techniques. The descent property and global convergence are proven for the new methods. The obtained numerical results reveal that, when applied to image restoration, the new algorithms are superior to the classical fletcher reeves (FR) method in the same domain in terms of maintaining image quality and efficiency.
Image reconstruction through compressive sampling matching pursuit and curvelet transform
Authors: Seetharamaswamy Shashi Kiran , Veeranna Suresh Kaggere
Published: September 2023

An interesting area of research is image reconstruction, which uses algorithms and techniques to transform a degraded image into a good one. The quality of the reconstructed image plays a vital role in the field of image processing. Compressive Sampling is an innovative and rapidly growing method for reconstructing signals. It is extensively used in image reconstruction. The literature uses a variety of matching pursuits for image reconstruction. In this paper, we propose a modified method named compressive sampling matching pursuit (CoSaMP) for image reconstruction that promises to sample sparse signals from far fewer observations than the signal’s dimension. The main advantage of CoSaMP is that it has an excellent theoretical guarantee for convergence. The proposed technique combines CoSaMP with curvelet transform for better reconstruction of image. Experiments are carried out to evaluate the proposed technique on different test images. The results indicate that qualitative and quantitative performance is better compared to existing methods.
A brief study on rice diseases recognition and image classification: fusion deep belief network and S-particle swarm optimization algorithm
Authors: Jayaram Miryabbelli , Kalpana Gudikandhula , Borra Subba Reddy , Bhavani Battu Durga
Published: September 2023

In the regions of southern Andhra Pradesh, rice brown spot, rice blast, and rice sheath blight have emerged as the most prevalent diseases. The goal of this research is to increase the precision and effectiveness of disease diagnosis by proposing a framework for the automated recognition and classification of rice diseases. Therefore, this work proposes a hybrid approach with multiple stages. Initially, the region of interest (ROI) is extracted from the dataset and test images. Then, the multiple features are extracted, such as color-moment-based features, grey-level cooccurrence matrix (GLCM)-based texture, and shape features. Then, the S-particle swarm optimization (SPSO) model selects the best features from the extracted features. Moreover, the deep belief network (DBN) model trained by SPSO is based on optimal features, which classify the different types of rice diseases. The SPSO algorithm also optimized the losses generated in the DBN model. The suggested model achieves a hit rate of 94.85% and an accuracy of 97.48% with the 10-fold cross-validation approach. The traditional machine learning (ML) model is significantly less accurate than the area under the receiver operating characteristic curve (AUC), which has an accuracy of 97.48%.
Generalized recursive algorithm for fetal electrocardiogram isolation from non-invasive maternal electrocardiogram
Authors: Kaoula Ikram , Guessoum Abderrezak , Kazed Boualem
Published: September 2023

Non-invasive maternal electrocardiogram recording is the least unpleasant method to record a weak fetal electrocardiogram signal. The importance of this recording lies in the fact that it reveals crucial information about the fetal health state, especially during the last four weeks of pregnancy. This paper will be concerned with a new adaptive algorithm, namely the generalized recursive algorithm, to isolate and get the fetal electrocardiogram from the abdominal maternal electrocardiogram. This is achieved using a non-invasive method for bi-channel maternal electrocardiogram recordings i.e., with the thoracic maternal electrocardiogram as a reference signal, and the abdominal maternal electrocardiogram as a primary signal. Prior to this procedure, the discrete wavelet transform (DWT) method is applied to the abdominal electrocardiogram signal to clean it from any additive noise and the baseline wandering that is generally present on the raw recordings. The proposed new adaptive filter is shown to deliver improved characteristics through simulations. These simulations were performed on both synthetic and actual signals. This work was compared with the normalized least mean square algorithm.
A survey on passive digital video forgery detection techniques
Authors: Jegaveerapandian Liba Manopriya , Rani Arockia Jansi , Periyaswamy Prakash , Velusamy Sakthivel
Published: September 2023

Digital media devices such as smartphones, cameras, and notebooks are becoming increasingly popular. Through digital platforms such as Facebook, WhatsApp, Twitter, and others, people share digital images, videos, and audio in large quantities. Especially in a crime scene investigation, digital evidence plays a crucial role in a courtroom. Manipulating video content with high-quality software tools is easier, which helps fabricate video content more efficiently. It is therefore necessary to develop an authenticating method for detecting and verifying manipulated videos. The objective of this paper is to provide a comprehensive review of the passive methods for detecting video forgeries. This survey has the primary goal of studying and analyzing the existing passive techniques for detecting video forgeries. First, an overview of the basic information needed to understand video forgery detection is presented. Later, it provides an in-depth understanding of the techniques used in the spatial, temporal, and spatio-temporal domain analysis of videos, datasets used, and their limitations are reviewed. In the following sections, standard benchmark video forgery datasets and the generalized architecture for passive video forgery detection techniques are discussed in more depth. Finally, identifying loopholes in existing surveys so detecting forged videos much more effectively in the future are discussed.
A comparative study of steganography using watermarking and modifications pixels versus least significant bit
Authors: Caballero Hector , Muñoz Vianney , Ramos-Corchado Marco A.
Published: September 2023

This article presents a steganography proposal based on embedding data expressed in base 10 by directly replacing the pixel values from images red, green blue (RGB) with a novel compression technique based on watermarks. The method considers a manipulation of the object to be embedded through a data compression triple process via LZ77 and base 64, watermark from low-quality images, embedded via discrete wavelet transformation-singular value decomposition (DWT-SVD), message embedded by watermark is recovered with data loss calculated, the watermark image and lost data is compressed again using LZ77 and base 64 to generate the final message. The final message is embedded in portable network graphic (PNG) images taken from the Microsoft common objects in context (COCO), ImageNet and uncompressed color image database (UCID) datasets, through a filtering process pixel of the images, where the selected pixels expressed in base 10, and the final message data is embedded by replacing units’ position of each pixel. In experimentation results an average of 40 dB in peak signal noise to ratio (PSNR) and 0.98 in the similarity structural index metric (SSIM) evaluation were obtained, and evasion steganalysis rates of up to 93% for stego-images, the data embedded average is 3.2 bpp.
Generative adversarial deep learning in images using Nash equilibrium game theory
Authors: Fatima Syeda Imrana , Garapati Yugandhar
Published: September 2023

A generative adversarial learning (GAL) algorithm is presented to overcome the manipulations that take place in adversarial data and to result in a secured convolutional neural network (CNN). The main objective of the generative algorithm is to make some changes to initial data with positive and negative class labels in testing, hence the CNN results in misclassified data. An adversarial algorithm is used to manipulate the input data that represents the boundaries of learner’s decision-making process. The algorithm generates adversarial modifications to the test dataset using a multiplayer stochastic game approach, without learning how to manipulate the data during training. Then the manipulated data is passed through a CNN for evaluation. The multi-player game consists of an interaction between adversaries which generates manipulations and retrains the model by the learner. The Nash equilibrium game theory (NEGT) is applied to Canadian Institute for Advance Research (CIFAR) dataset. This was done to produce a secure CNN output that is more robust to adversarial data manipulations. The experimental results show that proposed NEGT-GAL achieved a grater mean value of 7.92 and takes less wall clock time of 25,243 sec. Therefore, the proposed NEGT-GAL outperforms the compared existing methods and achieves greater performance.
An efficient reconfigurable code rate cooperative low-density parity check codes for gigabits wide code encoder/decoder operations
Authors: Venkatesh Divyashree Yamadur , Mallikarjunaiah Komala , Srikantaswamy Mallikarjunaswamy
Published: September 2023

In recent days, extensive digital communication process has been performed. Due to this phenomenon, a proper maintenance of authentication, communication without any overhead such as signal attenuation code rate fluctuations during digital communication process can be minimized and optimized by adopting parallel encoder and decoder operations. To overcome the above-mentioned drawbacks by using proposed reconfigurable code rate cooperative (RCRC) and low-density parity check (LDPC) method. The proposed RCRC-LDPC is capable to operate over gigabits/sec data and it effectively performs linear encoding, dual diagonal form, widens the range of code rate and optimal degree distribution of LDPC mother code. The proposed method optimize the transmission rate and it is capable to operate on 0.98 code rate. It is the highest upper bounded code rate as compared to the existing methods. The proposed method optimizes the transmission rate and is capable to operate on a 0.98 code rate. It is the highest upper bounded code rate as compared to the existing methods. the proposed method's implementation has been carried out using MATLAB and as per the simulation result, the proposed method is capable of reaching a throughput efficiency greater than 8.2 (1.9) gigabits per second with a clock frequency of 160 MHz.
Optimal coding unit decision for early termination in high efficiency video coding using enhanced whale optimization algorithm
Authors: Krishnegowda Suhas Shankarnahalli , Periapandi Hosanna Princye
Published: September 2023

Video compression is an emerging research topic in the field of block based video encoders. Due to the growth of video coding technologies, high efficiency video coding (HEVC) delivers superior coding performance. With the increased encoding complexity, the HEVC enhances the rate-distortion (RD) performance. In the video compression, the out-sized coding units (CUs) have higher encoding complexity. Therefore, the computational encoding cost and complexity remain vital concerns, which need to be considered as an optimization task. In this manuscript, an enhanced whale optimization algorithm (EWOA) is implemented to reduce the computational time and complexity of the HEVC. In the EWOA, a cosine function is incorporated with the controlling parameter A and two correlation factors are included in the WOA for controlling the position of whales and regulating the movement of search mechanism during the optimization and search processes. The bit streams in the Luma-coding tree block are selected using EWOA that defines the CU neighbors and is used in the HEVC. The results indicate that the EWOA achieves best bit rate (BR), time saving, and peak signal to noise ratio (PSNR). The EWOA showed 0.006-0.012 dB higher PSNR than the existing models in the real-time videos.
Design and characterization of a circularly polarized microstrip-line-fed slot array antenna for S-band applications
Authors: Das Debprosad , Hossain Md. Farhad , Hossain Md. Azad
Published: September 2023

A 2×2 slot array antenna fed by microstrip line for circular polarization operated in the S band frequency range is designed in this paper. Single cross slot with single port feed as well as dual port feed is taken into consideration for realizing circular polarization and combining these two processes, the slot array is designed with single feed for circular polarization. The antennas are designed on a Teflon glass fiber substrate of thickness 0.8 mm. The slot array dimension is 120×142×1.636 mm3. Smith chart of single cross slot antenna with single feed as well as dual feed has a dip at 2.69 and 2.53 GHz respectively indicate the capability of realizing circular polarization in the S band frequency range. The return loss of the slot array antenna is -58 dB shows good input impedance matching of the antenna. A dip in the smith chart of the slot array shows circular polarization near 2.4 GHz ensuring wireless applications as well. Axial ratio is found to be less than 1 dB in the resonance frequency. The impedance bandwidth percentage of the slot array antenna is 12.24%. The simulation is done by using keysight advanced design system (ADS) software.