MEASUREMENT SCIENCE REVIEW            Volume 23     

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No. 1

No. 2 No. 3 No. 4 No. 5 No. 6  

       Measurement of Physical Quantities



Turgut Özseven, Zübeyir Şükrü Özkorucu:

Optimization of Support Vector Machines for Prediction of Parkinson’s Disease


As in all fields, technological developments have started to be used in the field of medical diagnosis, and computer-aided diagnosis systems have started to assist physicians in their diagnosis. The success of computer-aided diagnosis methods depends on the method used; dataset, pre-processing, post-processing, etc. differ according to the processes. In this study, parameter optimization of support vector machines was performed with four different methods currently used in the literature to assist the physician in diagnosis. The success of each method was tested on two different Parkinson's datasets and the results were compared within themselves and with the literature. According to the results obtained, the highest accuracy rates vary depending on the dataset and optimization method. While Improved Chaotic Particle Swarm Optimization achieved high success in the first dataset, Bat Algorithm achieved higher success in the other dataset. While the successful results obtained are better than some studies in the literature, they are at a level that can compete with some studies.



Siquan Zhang:

Investigation of Flux Transfer along Ferrite Core of Probe Coil for Eddy Current Nondestructive Evaluation


A probe coil with a T-core above a layered conductor with surface hole is investigated for magnetic flux transfer along the ferrite core and enhancement of eddy currents in conductor. The cylindrical coordinate system is adopted and an artificial boundary is added to the solution domain with radius b, and the general formula for calculating the impedance of the T-core coil is derived using the truncated region eigenfunction expansion (TREE) method. For four special cases with different probe configurations, coil impedance changes due to the layered conductor and defect are calculated with Mathematica software over a frequency change ranging from 100 Hz to 20 kHz. The analytical results are in good agreement with those obtained by the finite element method and experimental measurements. The results show that under the same lift-off height and excitation frequency, the impedance change caused by the conductor or defect in the coil of long core column is greater than that of the short core column coil. It indicates that the probe coil with a long core column can transfer magnetic flux to the conductor, thereby enhancing eddy currents in the conductor.



Kiril Demerdziev, Vladimir Dimchev:

Reactive Power and Energy Instrument’s Performance in Non-Sinusoidal Conditions Regarding Different Power Theories


It is important to conduct the examination of reactive power and energy instruments in normal operating conditions, due to their place in the regulated trade of electrical energy. The challenge arises when the normal operating conditions encompass non-sinusoidal voltages and currents, for two main reasons: the fact that the term reactive power/energy is not unambiguously defined in case of harmonically polluted environment and the fact that the measurement algorithm implemented in the meter is usually not explicitly presented by the producer. Different algorithms provide the same result in case of sinusoidal signals, while in case of harmonics the instrument’s performance may vary significantly, when different power theories are adopted. In the paper, a commercially available reactive energy electricity meter is tested with harmonically distorted voltage and current signals, and an analysis of its output is performed from the perspective of the implemented measuring algorithm, which is not known a priori. The tests encompass alteration of different waveform parameters and the instrument’s output is analyzed from the perspective of several reactive power theories. The conclusion of the analysis results in the meter’s performance feature illustration in correlation with different harmonic parameters and different reference conditions.



Mehmet Eren, Ramazan Gürsel Hoşbaş:

Testing the Performance of the Video Camera to Monitor the Vertical Movements of the Structure via a Specially Designed Steel Beam Apparatus


This article focuses on a specially designed steel beam testing apparatus to determine the dynamics of the structure using data obtained from different sensor systems. The analysis of these different sensor systems is performed by processing data recorded by the Global Navigation Satellite System (GNSS), vision based measurement (video camera), and accelerometer surveys. To perform this analysis, the accelerometer and GNSS receiver are installed at the steel beam’s mid-span position. The high-contrast artificial target attached to the accelerometer is recorded by a video camera to monitor the structural dynamics. Steel beam experiments show that it is compatible with the accelerometer, which is predicted as a reference sensor in detecting motion with an amplitude of 10 mm and above in the vertical direction with GNSS and determining the structural frequency by spectral analysis. On the other hand, we concluded that the video camera can be used to determine the structural dynamics in SHM because its results were compatible with the reference data even if the amplitude was too small.



Hao Yang, Yufeng Lai, Xuanqi Liu, Houshi Jiang, Jiansheng Yang:

Equivalence Ratio Modelling of Premixed Propane Flame by Multiple Linear Regression Using Flame Color and Spatial Characteristics


Equivalence ratio (Φ) is one of the most important parameters in combustion diagnostics. In previous studies, flame color characteristics have been widely applied to model the Φ of premixed hydrocarbon flames. The flame spatial characteristics also change with the varying Φ. In this paper, a high-speed color camera was employed to capture the premixed propane flame images under different Φ conditions (Φ = 0.93 to 1.53). Then, the relationship between the spatial characteristics and the Φ variation was investigated. The area and height of propane premixed flames perform a strong sensitive response to the Φ variation. Based on the research above, the Φ measurement models were constructed using color and spatial characteristics. A comparison was made between the color characteristics (Color-Φ) model and the color-spatial characteristics (Multi-dimensional-Φ) model. Both models were applied to a set of color images of a premixed propane flame, and the result indicates that the Multi-dimensional-Φ model performs with higher accuracy.



Bing-yi Miao, Xian-cheng Wang, Jun-hua Chen, Chu-hua Jiang, Meng-yao Qu:

A Novel Non-Contact Measurement Method of Ball Screw Thread Profile Detection Based on Machine Vision


The transmission accuracy of the ball screw depends on the processing quality of the thread profile. Traditional detection method of thread profile is complicated and inefficient. When shooting the thread profile of the ball screw in the normal section, the camera axis must be tilted to the lead angle, and adjustment errors are easily introduced from both the front view and the top view. When shooting in the axial section, the spiral lines block each other, so the actual thread profile cannot be captured for detection. In order to solve the above problems, a thread profile detection method is proposed: the theoretical equation of the ball screw thread profile in the axial section is derived based on the theoretical thread profile in the normal section, and the theoretical equation of the thread profile projection curve in the axial section is solved based on helix analysis, and the differential equation between them is obtained; then, the theoretical correction value of the thread profile projection curve is obtained by Linear Search to find the boundary value; the actual thread profile in both axial section and normal section is finally obtained with the theoretical correction value, which can support accurate measurement and detection of the key parameters of the thread profile. Experiments show that the proposed method can effectively improve the accuracy of the ball screw thread profile detection.




No. 2  



Shumaila Ihtisham, Sadaf Manzoor, Alamgir Khalil, Sareer Badshah4,Muhammad Ijaz, Hadia Atta:

Modeling Extreme Values with Alpha Power Inverse Pareto Distribution


The study focuses on the development of a new probability distribution with applications to extreme values. The distribution is proposed by incorporating an additional parameter into the inverse Pareto distribution using the α-Power Transformation. Various properties of the new distribution are derived. The paper also explores the estimation of the parameters by the Maximum Likelihood Estimation (MLE) technique. Simulations are performed to evaluate the performance of the MLEs. In addition, two real data sets with extreme values are used to evaluate the efficacy of the proposed model. It is concluded that the proposed model performs well in the case of extreme values compared to the existing distributions.



Mikulas Bittera, Jozef Hallon, Imrich Szolik, Rene Hartansky:

Alternative Approach Leading to Reduction in Measurement Instrument Uncertainty of EMI Measurement


Even in the field of electromagnetic compatibility, low measurement uncertainty means high measurement quality. Although there are standardized procedures for obtaining the uncertainty of such a measurement, which facilitate uncertainty estimation, modern approaches show further reduction possibilities. The paper presents an alternative approach to reducing measurement instrument uncertainty in the case of electromagnetic interference measurement based on many years of our experience and a large number of measurements in this field. In the paper, two different methods of uncertainty reduction are described. The first method is based on a detailed analysis of the sources of uncertainty and the subsequent division of the analyzed frequency band into more subranges. Another method uses the choice of the antenna factor, which also contains information about the test site where the measurement is carried out. In this way, despite a lengthy analysis, it is relatively easy to achieve a measurement instrument uncertainty that is below the maximum measurement uncertainty given by the CISPR standard.



Meng-ting Xu, Hong-xi Wang, Ya-xiao Wang, Hui-hui Tian:

Design and Experimental Study of a Probe for Crankshaft Full-automatic Measuring Machine


The Crankshaft Full-automatic Measuring Machine (CFMM) features high accuracy, high efficiency and complete measurement parameters, and represents the forefront of a geometric crankshaft accuracy measuring instrument. One of its core technologies is the high-precision radial following the crankshaft connecting rod journal measurement. In this paper, an independent probe design scheme combining the flexible dual-complex parallel four-bar guide mechanism and double displacement sensors based on the contact measurement method was proposed. It was suitable for the measurement of precision parts with eccentric characteristics such as crankshaft and camshaft measurement. Taking the spring as the flexible part, the probe prototype's optimization design, processing and assembly were completed, the test device was built, and the system accuracy was calibrated under various positions and feed quantities of the probe. The results revealed that the expanded measurement uncertainty after double-sensor compensation was enhanced from 1.53 μm in single-sensor measurement to 0.44 μm, satisfying the high-precision requirements of engineering measurement accuracy and reducing the measurement cost.



Liping Tian, Lingbin Shen, Yanhua Xue, Lin Chen, Ping Chen, Jinshou Tian, Wei Zhao:

3-D Imaging Lidar Based on Miniaturized Streak Tube


Streak Tube Imaging Lidar (STIL), with advantages of non-scanning working mode, small distortion, high image framing rate, high resolution in low contrast environment, compact structure, easy miniaturization and high reliability, has a wide range of applications in military, aerospace, space confrontation, attack and defense, and marine law enforcement. This article introduces the principle of single-slit and multi-slit streak tube imaging lidar. It also introduces a single-slit general streak camera that can be used for imaging lidar. In addition, a multi-slit miniaturized streak tube with a single-lens focusing system with a total length of about 200 mm has been designed. The results of the 3D electromagnetic simulation show that the effective photocathode area of this streak tube reaches 36 mm × 36 mm, the temporal resolution is better than 50 ps, the dynamic spatial resolution can reach 12 lp/mm, and the whole photocathode can accommodate at least 19 slits in the effective detection range. The streak tube has a meshless structure, which is highly reliable. The streak tube can be used to increase the field of view of the imaging lidar system, improve the reliability, and achieve system miniaturization.



Khairun Nisa’ Minhad, Araf Farayez, Mamun Bin Ibne Reaz, Mohammad Arif Sobhan Bhuiyan, Siti Balqis Samdin, Mahdi H. Miraz:

Early Diagnosis of Dementia Patients by SPADE Activity Prediction Algorithm


Dementia is not a specific disease, but a general term for age-related decline or loss of memory, cognitive abilities including problem solving and decision-making, and one’s own language, which significantly interfere with daily life. Researchers around the world have developed ways to automate the diagnosis of dementia through the use of machine learning and data mining approaches. The aim of this research project is to design and develop a day-to-day activity prediction algorithm in order to accurately identify and differentiate the dementia affected patients from the healthy subjects, to ensure early diagnosis of dementia development. This research advocates a novel algorithm called ‘Sequence Prediction via All Discoverable Episodes (SPADE)’ as a statistical tool to map activities of daily life (ADLs) in different groups of people in order to develop a unique parameter for precise diagnosis. The results of our experiment demonstrated a significant difference (i.e. 11 %) in the sequence prediction peak accuracy between the healthy subjects and the residents with dementia.

SPADE demonstrated an adequate accuracy (i.e. 80 % on average), with an improvement of about 12 % compared to the performance of M-SPEED in inferring future occurrences of activities. It is thus evident that the algorithms for activity predictions show promise for early detection of dementia symptoms without the use of any expensive clinical procedure.



L. Nurel Özdinç Polat, Şükrü Özen:

Evaluation of Physiological Effect of Audiological Test based on Galvanic Skin Response


The aim of this study was to determine the physiological effects of the audiological test procedure on individuals and the changes in Galvanic Skin Response (GSR). GSR data from 39 volunteers at rest and during the audiological testing were analyzed and the effects of the audiological testing procedure were evaluated. It was observed that the audiological test showed significant differences according to the resting status in terms of mean value, mean power, Root Mean Square (RMS), Kurtosis, and Skewness. The results obtained in the study show that these differences in GSR can be evaluated according to the physiological effect reflections of the emotional changes created on individuals by the audiological test.




No. 3  




Peng Chen, Xin Su, Ting’ao Shen, Ling Mou:

A Parameter Estimation Algorithm for Damped Real-value Sinusoid in Noise


In order to improve the parameter estimation performance of damped real-value sinusoid in noise, a novel algorithm with high accuracy and computational efficiency is proposed, which combines the characteristics of good anti-interference, small computation of frequency-domain methods and high parameter estimation accuracy of time-domain methods. Firstly, the Discrete Fourier Transform algorithm (DFT) and two points spectrum interpolation algorithm of frequency-domain methods are used to improve the noise immunity. Then, the linear prediction property and enhancement filter of time-domain methods are used to increase the parameter estimation accuracy. In addition, the parameters estimation performance of the proposed algorithm is verified by computational complexity analysis and testing experiments, and the practical application effectiveness of the proposed algorithm is demonstrated on the Coriolis Mass Flowmeter experimental platform. The experimental results indicate that the proposed one effectively improves real time performance, and the parameter estimation accuracy is better than those of the existing excellent algorithms.



Lijun Meng, Xin Tan, Quanquan Yu:

Study on Time-frequency Imaging of Ultrasonic Detection with Phase Shifted Fiber Bragg Grating Sensing


The influence of the wavelength difference between the laser source and the phase-shifted fiber Bragg grating on the intensity of the power demodulation system based on an adjustable laser source was studied experimentally, and the optimum of the output laser wavelength was determined. Then, the research on time-frequency imaging damage identification based on smooth pseudo-Wigner-Ville distribution was carried out. The Time of Flight of the acoustic wave signal was calculated and time compensation was made according to the Wigner-Ville distribution and the Lamb wave dispersion curve. The ultrasonic waves before and after damage were measured with spatially arranged PS-FBGs. The difference signals were processed in a window,  and then the time-frequency energy of the normalized difference signal was imaged to assess the damage detection and location. Although the mode and group velocity of ultrasound measured by each fiber grating were different, the accurate location and identification of artificial damage in an aluminum alloy plate was realized by using only three phase-shifted fiber Bragg gratings and a smooth Wigner time-frequency imaging method.



Mathuvanesan Chokkalingam, Chinnadurai Murugaiyan:

Free-Space Optical Communication with an Optimized Lipschitz Exponent for Biosignal Telemetry


Healthcare monitoring is a rapidly developing network in the field of advanced medical treatment. The network combines the ideology of wireless communication, signal processing, medical information and real-time processing units to support the medical monitoring system. The proposed work focuses on the development of a Free-Space Optical (FSO) system to transmit the biosignals from a remote distance to the physician. Generally, the data transmitted over the FSO system is affected by various atmospheric conditions such as air medium, O2, and H2O molecules. To tackle these problems, the Biosignals  Electrocardiogram (ECG) and Electroencephalogram (EEG) are processed in the Optimized Lipschitz Exponent (OLE) Function before transmission over the FSO medium. In this novel technique, the OLE function measures the informative data from the biosignals by calculating the local regularities and singularity. This collects the most informative signals and transmits them in the signal over the FSO medium. This particular hybridization helps to transmit the required data without distortion. The bit error rate of 10-9 is obtained, which satisfies the healthcare monitoring condition. The result section shows that the proposed model has minimum losses compared to the original signal.



Peter Andris, Ivan Frollo, Jiří Přibil, Daniel Gogola, Tomáš Dermek:

Conversion of the Bruker Minispec Instrumentation into the Static Magnetic Field Standard


The static magnetic field standard is part of many scientific experiments aimed at measuring the magnetic field. Often this device has to be built by oneself, if there is no possibility to buy it off the shelf. One possibility is also to convert a suitable device into a static magnetic field standard. Such a method is also described in this article. When the first experiments showed that the key parts could not be obtained under the existing conditions, it was decided to convert Bruker's Minispec into a static magnetic field standard. Such a standard will not be completely universal, but it will accommodate many experiments, and the experience may help in the future when a more perfect standard is built. This article describes the design of the apparatus, briefly describing all the equipment, which includes many parts of the original device. The parts specific to the new construction are described in more detail. An alternative solution for frequency deviation calculation using a software quadrature detector, tested only in the form of a computer simulation, is also described.  



Tomáš Húlan, Igor Štubňa, Omar Al-Shantir, Anton Trník:

The Apparatus for Thermomechanical Analysis of Clay-based Ceramics Regression Using Flame Color and Spatial Characteristics


A dynamic thermomechanical analysis (D-TMA) apparatus is described for measuring the resonant frequency of the flexural vibration and the internal damping of the sample using the impulse excitation technique (IET). Since the measurement is conducted at temperatures up to 1250 °C, an electromagnetic impulser is used for excitation. The free vibrations are registered by an electret microphone, stored and then converted into a frequency spectrum using the fast Fourier transform, from which the resonant frequency can be found. The furnace is built from refractory porous alumina bricks and alumina fiber pads. The heating elements are four SiC rods connected to a temperature controller. The temperature is measured with a Pt-PtRh10 thermocouple in close proximity to the sample.



Alexander Budimir, Slobodan Tabaković, Milan Zeljković:

The Influence of the Movement Method on the Results of Machine Tool Positioning Accuracy Analysis


The improvement of machine tools, and therefore, of industrial production, requires high accuracy of machining while adapting to the different dimensions of the workpieces and to the machines themselves. As a result, the improvement of testing procedures and the analysis of positioning accuracy results represent an important research task in modern manufacturing engineering. The paper presents the results of the research carried out with the aim of determining the influence of the choice of parameters for standardized testing of positioning accuracy on the measurement results with reference to the characteristics of the machines from the point of view of the size of the workspace and the machines themselves. In this way, it is possible to choose the appropriate test parameters of the machine tools depending on their geometrical characteristics and test conditions and within the existing standards.




No. 4  



Emre Sayin, Rahman Bitirgen, Ismail Bayezit:

Attitude Control and Parameter Optimization:

A Study on Hubble Space Telescope


In this work, we build a satellite attitude Proportional-Integral-Derivative (PID) controlled system by using the Hubble Space Telescope (HST) parameters as a reference and tune its controller parameters using various tuning methods. First, we give the equations for the motion of a satellite. We elaborate the control structure as controller, actuator, dynamics and kinematics subsystems and construct an external disturbance model. We use a reaction wheel assembly used in the HST with the same configuration as the actuator. We evaluate the performance of the linearization by comparing it with the nonlinear model output. By working on the linearized model, we tune the PID controller parameters using two different methods: "Model-Based Root Locus Tuning” and "Genetic Algorithm Based Tuning". First, we obtain the controller parameters by manipulating the poles on the root locus plot of the linearized system. In addition, we use genetic algorithms to find the optimized controller values of the system. Finally, we compare the performances of the two methods based on their cost function values and find that the Genetic Algorithm-based tuned parameters are more fruitful in terms of the cost function value than the parameters obtained by the Root Locus-based tuning. However, it is found that the Root Locus-based tuning performs better in disturbance rejection.



Miroslav Gutten, Daniel Korenciak, Martin Karman, Peter Brncal, Matej Kucera, Tomasz N. Koltunowicz, Maciej Sulowicz:

Combination of Non-contact and Contact Measuring Methods for Analyzing Structural Conditions of Dry Transformers


The article describes the non-contact and contact analysis of 1-MVA dry power transformers with epoxy-resin insulation using an acoustic camera and frequency analyzer with automatic sweeping for low-middle frequency areas. Power transformers are most commonly used for construction component (core, windings, taps) analysis. The electrical, non-rotating machine generates electromagnetic and acoustic emissions that can be used to analyze dry transformers during their operation. Non-contact online diagnostic methods have many advantages over offline methods because it is not necessary to shut down the transformer, and also, the condition and behavior of the machine are analyzed during its normal operation. The article presents the analysis and comparison of structural parts of the distribution dry transformers of the same type and power. The problem of insufficient or incorrect clamp-screw connection was identified using the SFRA (Sweep Frequency Response Analysis) method.



Ľuboš Kučera, Tomáš Gajdošík, Igor Gajdáč, Lukáš Pompáš, Lukáš Smetanka, Viktor Witkovský, Gejza Wimmer:

Design and Construction of Metrological Equipment for Torque Sensors with a Carbon-based Measuring Arm


The paper presents a comprehensive design of metrological equipment for torque sensor verification and calibration , detailing the process from conception to construction and highlighting the specifics of the structural design to meet metrological requirements. The measuring device's functionality and the individual structural components are described, as is the methodology for creating a complete product. The paper addresses the crucial issue of measurement uncertainty and the required accuracy, achieved through the construction of a special measuring arm made of carbon material. FEM analyses of the carbon arm are presented and compared with the required metrological accuracies. In addition, we discuss the different properties of various carbon structures in Pre-preg materials used in the construction of the measuring arm and present the results of measurements on such carbon materials. This paper provides a comprehensive insight into the design and construction of metrological equipment for torque sensors, with a focus on its compliance with metrological requirements. The proposed device aims to establish the foundations for primary metrology of torque in Slovakia and has potential applications in a wide range of industries.



Supakorn Harnsoongnoen, Benjaporn Buranrat:

Glucose Concentration Monitoring Using Microstrip Spurline Sensor


This article reports a microstrip spurline sensor for monitoring of glucose concentration. The microstrip spurline sensor is a low-cost and easy-to-fabricate device that uses printed circuit board (PCB) technology. It consists of a combination of four spurlines and transmission lines. The four spurlines are used to reject unwanted frequencies, while the transmission lines allow the desired frequencies to pass through. The resonance frequency (Fr) and reflection coefficient (S11) were recorded through meticulous simulations and experiments, within the frequency range of 1.5 GHz to 4 GHz. Additionally, the sensor was employed to detect changes in glucose concentration, ranging from 0 mg/dL to 150 mg/dL. The findings of this study indicate that the antenna-based sensor proposed in this research can effectively measure glucose levels across the diabetes range, from hypoglycemia to normoglycemia and hyperglycemia, with a high degree of sensitivity of 7.82x10-3 dB/(mg/dL) and 233.33 kHz/(mg/dL).



Jozef Jakubík, Mary Phuong, Martina Chvosteková, Anna Krakovská:

Against the Flow of Time with Multi-output Models


Recent work has paid close attention to the first principle of Granger causality about the cause preceding the effect. In this context, the question may arise as to whether the detected direction of causality will also be reversed after the time reversal of unidirectionally coupled data. It has been shown recently that in the case of unidirectionally causally connected autoregressive (AR) processes X→Y, after time reversal of data, the opposite causal direction Y→X is indeed detected, although typically as part of the bidirectional X↔Y link. As we argue here, the answer is different when the measured data does not come from AR processes, but rather from linked deterministic systems. If the goal is the usual forward data analysis, cross-mapping-like approaches correctly detect X→Y, while Granger’s causality-like approaches, which should not be used for deterministic time series, detect causal independence X⫫Y. The results of the backward causal analysis depend on the predictability of the reversed data. Unlike AR processes, observables from deterministic dynamical systems, even complex nonlinear ones, are well predicted forwards while backward predictions can sometimes seem difficult (notably when the time-reversal of a function leads to one-to-many relations). To address this problem, here we propose an approach based on models that provide multiple candidate predictions for the target, combined with a loss function that takes into account only the best candidate. The resulting good forward and backward predictability supports the view that with unidirectionally causally linked deterministic dynamical systems X→Y, the same link is expected to be detected both before and after the time-reversal.



Kavitha G., Deny J.:

Single and Multi-Point Non-Orthogonal Multiple Access based Power Adaptive Design for Improving Bit Error Ratio


In the framework of next-generation communication systems, Non-Orthogonal Multiple Access (NOMA) has attracted considerable interest. The fundamental advantage is that it has greater spectrum utilization than its orthogonal equivalents. This proposed work integrates Single-Input Single-Output NOMA (SISO) with Coordinated Multi-Point (CoMP). It uses both systems based on Quadrature Phase-Shift Keying (QPSK). A power-tolerant NOMA reduces the system's vulnerability to erroneous power allocation by adaptively modifying each user's signal power. The transmitted data is used to modify the power in the Power-Adaptive NOMA (PANOMA). PANOMA helps improve the Bit Error ratio and also improves the computational complexity. The Bit Error Rate (BER) and the lower limit capacity efficiency across Rayleigh fading channels are determined in precise closure representations of more than two consumer situations to measure its capability. The proposed method PA-CoMP-NOMA improves the Bit Error ratio in both systems. It improves the average BER among all users. Compared to its orthogonal cousin, NOMA has higher spectral efficiency. Nevertheless, our proposed method retains this feature as well as superior BER performance, although its spectral effectiveness is lower than that of the classic sum-rate based power NOMA.




No. 5  



Luka Ponorac, Ivan Blagojević:

Experimental Validation of a High-Speed Tracked Vehicle Powertrain Simulation Model


High-speed tracked vehicles have complex powertrains that, in addition to power transfer and transformation, also perform the functions of vehicle steering and braking systems, as well as power supply system for various subsystems on the vehicle. Analyzing the power balance of a tracked vehicle, especially in specific moving scenarios such as the turning process, is of great importance for understanding the power requirements and workload of the powertrain components and their optimization. A simulation model was developed, based on the construction parameters of an experimentally tested high-speed tracked vehicle to reduce the time and material resources required for experimental testing. Both the simulation and experimental tests were conducted using the same input parameters and driving conditions for different vehicle turning scenarios. Simulation and experimental test results are compared to verify the accuracy of the simulation model. The analysis of the obtained results shows that the average value of the relative rpm error is about 5%, the average value of the relative torque error is about 7%, while the average value of the relative power error is about 6.5%.



Cigdem Deniz, Ozlem Kocahan, Bengu Altunan1, Aysun Unal:

Novel Approach to Investigate the Effect of High-Dose Methylprednisolone on Erythrocyte Morphology: White Light Diffraction Microscopy


The present study focuses on quantitative phase imaging of erythrocytes with the aim to evaluate the effects of high-dose methylprednisolone (HDMP) on erythrocytes in vivo under physiological conditions in human blood samples. Samples from ten patients, prescribed to be treated with 1000 mg/day intravenous methylprednisolone for 5 days, were analyzed by white light diffraction phase microscopy (WDPM) for quantitative imaging. WDPM, an optical measurement technique, enables single shot measurement and low speckle noise using white light. Quantitative phase imaging performed with this experimental setup allowed the determination of erythrocyte morphology with 9 different parameters. In vivo quantitative analysis of erythrocytes by WDPM, which is a simple and reliable method, shows that HDMP treatment has no significant effect on erythrocyte morphology. With the developing technology, interdisciplinary studies on individuals under treatment should play an important role in elucidating the interaction between steroids and erythrocytes



Zheng-yang Sun, Hong-xi Wang, Hui-hui Tian, Bing Liu:

Docking Pose Measurement Method for Large Components Based on Draw-Wire Displacement Sensors


A method for measuring the docking pose of large components based on the draw-wire displacement sensor is proposed. In this method, coordinate systems and measurement points are established on the docking surfaces of fixed and moving components. The draw-wire displacement sensor is used to measure the distances between these measurement points. A mathematical model based on the distances between the measurement points is established, and the three-sphere rendezvous positioning principle is optimized to obtain the spatial positions of the measurement points. Consequently, the pose deviations of the fixed and moving components in all six degrees of freedom (6DOF) are determined. A simulation analysis of the measurement uncertainty of the obtained pose deviations is performed, resulting in a composite standard uncertainty obtained from the measurement standard uncertainties of different sensors. The simulation results show that the composite standard uncertainty is most affected in the x-axis translation direction and least affected in the x-axis rotation direction. With this method, only the distances between the measurement points need to be measured to determine the corresponding pose relationships. The cost of the equipment is low, and it is not easily affected by external factors such as the environment.



Jiří Přibil, Anna Přibilová, Ivan Frollo:

Analysis of Heart Pulse Transmission Parameters Determined from Multi-Channel PPG Signals Acquired by a Wearable Optical Sensor


The article describes the development and testing of a special prototype wearable device consisting of three optical photoplethysmography (PPG) sensors. The functionality of the developed triple PPG sensor was tested under normal laboratory conditions and in a running magnetic resonance imaging (MRI) scanner working with a low magnetic field. The results of the first measurements under normal laboratory conditions show that the obtained mutual positions of systolic/diastolic blood pressure values and heart pulse transmission parameters determined from the PPG waves can be fitted by a line segment with a sufficiently high slope. Measurement experiments inside the open-air MRI tomograph show the practical influence of vibrations and acoustic noise on the cardiac system of the examined persons, which was confirmed by a slight increase in the heart pulse rate and changes in pulse transmission time and pulse wave velocity. We plan to perform further measurements inside the whole-bodyMRI device producing more intensive vibrations and noise with expected higher stress impact on an exposed person.



Hariguru TM., Srinivasan S.:

The Effect of Differential Pressure and Permanent Pressure Loss on Multi-Hole Orifice Plate


The widely used orifice plate falls under restricted type flow devices, has the highest differential pressure and permanent pressure drop in the ensemble. The objective is to curtail the permanent pressure drop and maintain the differential pressure across the orifice plate, and thereby, the power required to pump the liquid is retrenched. So, three-hole, four-hole and five-hole orifice plates with an identical area to that of the single-hole orifice plate were designed and experiments were carried out. It is observed that the experimental results almost matched with the simulation data. In comparing the performance, the four-hole orifice plate yielded a higher differential pressure and higher-pressure loss. In contrast, the five-hole orifice yielded lower differential pressure and higher-pressure loss compared to the single-hole orifice plate. In case of three-hole orifice plate it performed better than the single-hole orifice with reduced pressure loss and higher differential pressure. It was also found that the power consumed by the pump for pumping was lower for three-hole, four-hole and five-hole orifice plates compared to the single-hole orifice plate. Thus, the three-hole orifice plate performs better than a single-hole orifice plate in terms of higher differential pressure, reduced permanent pressure loss and lower power consumption of the pump.



Tomáš Tvrdík, Ľubomír Melicherčík, Katarína Šebeková, Jakub Szabó, Marianna Maková, Daniel Gogola, Svatava Kašparová:

In vivo Volumetric, DTI and 1H MRS Rat Brain Protocol for Monitoring Early Neurodegeneration and Efficacy of the Used Therapy


The aim of our study was to develop a multimodal experimental protocol for in vivo imaging and metabolic parameters (MRI, DTI and 1H MRS) in an animal model of neurodegeneration. We have successfully developed the protocol for simultaneous DTI/MRI/1H MRS measurement to ensure unaltered conditions for repeatable non-invasive experiments. In this experiment, diffusion tensor imaging, spectroscopic and volumetric "bio-markers" were generated in the brain for the D-galactose model of "age-related dementia". The hippocampal relative volume, taurine and myo-inositol relative concentrations were found to be significant predictors contributing to the differences between the groups of rats treated with D-galactose in simulated "neurodegeneration", even in response to the applied Huperzine A therapy.




No. 6  



S. Rajalakshmi, Ibrahim AlMohimeed, Mohamed Yacin Sikkandar, S. Sabarunisha Begum:

Optimal Deep Learning-Based Recognition Model for EEG Enabled Brain-Computer Interfaces Using Motor-Imagery


Brain-Computer Interfaces (BCIs) facilitate the translation of brain activity into actionable commands and act as a crucial link between the human brain and the external environment. Electroencephalography (EEG)-based BCIs, which focus on motor imagery, have emerged as an important area of study in this domain. They are used in neurorehabilitation, neuroprosthetics, and gaming, among other applications. Optimal Deep Learning-Based Recognition for EEG Signal Motor Imagery (ODLR-EEGSM) is a novel approach presented in this article that aims to improve the recognition of motor imagery from EEG signals. The proposed method includes several crucial stages to improve the precision and effectiveness of EEG-based motor imagery recognition. The pre-processing phase starts with the Variation Mode Decomposition (VMD) technique, which is used to improve EEG signals. The EEG signals are decomposed into different oscillatory modes by VMD, laying the groundwork for subsequent feature extraction. Feature extraction is a crucial component of the ODLR-EEGSM method. In this study, we use Stacked Sparse Auto Encoder (SSAE) models to identify significant patterns in the pre-processed EEG data. Our approach is based on the classification model using Deep Wavelet Neural Network (DWNN) optimized with Chaotic Dragonfly Algorithm (CDFA). CDFA optimizes the weight and bias values of the DWNN, significantly improving the classification accuracy of motor imagery. To evaluate the efficacy of the ODLR-EEGSM method, we use benchmark datasets to perform rigorous performance validation. The results show that our approach outperforms current methods in the classification of EEG motor imagery, confirming its promising performance. This study has the potential to make brain-computer interface applications in various fields more accurate and efficient, and pave the way for brain-controlled interactions with external systems and devices.



Prabakaran J., Selvaraj P.:

An Approach to Recognise Lung Diseases Using Segmentation and Classification


Lung cancer is one of the most common causes of death in people worldwide. One of the key procedures for early detection of cancer is segmentation or analysis and classification or assessment of lung images. Radiotherapists have to invest a lot of effort into the manual segmentation of medical images. To solve this issue, early-stage lung cancer is detected using Computed Tomography (CT) scan images. The proposed system for diagnosing lung cancer is divided into two main components: the first part is an analyser component built on the upper layer of the U-shaped Network Transformer (UNT), and the second component is an assessment component built on the upper layer of the self-supervised network, which is used to categorise the output segmentation component as benign or cancerous. The proposed method provides a powerful tool for the early detection and treatment of lung cancer by combining CT scan data with 2D input. Numerous experiments are conducted to improve the analysis and evaluation of the findings. Using the public dataset, both test and training experiments were conducted. New state-of-the-art performances were achieved with experimental results: an analyser accuracy of 96.9% and an assessment accuracy of 96.98%. The proposed approach provides.




Ondřej Klempíř, David Příhoda, Radim Krupička:

Evaluating the Performance of wav2vec Embedding for Parkinson's Disease Detection


Speech is one of the most serious manifestations of Parkinson's disease (PD). Sophisticated language/speech models have already demonstrated impressive performance on a variety of tasks, including classification. By analysing large amounts of data from a given setting, these models can identify patterns that would be difficult for clinicians to detect. We focus on evaluating the performance of a large self-supervised speech representation model, wav2vec, for PD classification. Based on the computed wav2vec embedding for each available speech signal, we calculated two sets of 512 derived features, wav2vec-sum and wav2vec-mean. Unlike traditional signal processing methods, this approach can learn a suitable representation of the signal directly from the data without requiring manual or hand-crafted feature extraction. Using an ensemble random forest classifier, we evaluated the embedding-based features on three different healthy vs. PD datasets (participants rhythmically repeat syllables /pa/, Italian dataset and English dataset). The obtained results showed that the wav2vec signal representation was accurate, with a minimum area under the receiver operating characteristic curve (AUROC) of 0.77 for the /pa/ task and the best AUROC of 0.98 for the Italian speech classification. The findings highlight the potential of the generalisability of the wav2vec features and the performance of these features in the cross-database scenarios.



Lianfu Han, Ming Chen, Xingbin Liu, Changfeng Fu:

New Measurement Method of Oil-Water Two-Phase Flow with High Water Holdup and Low Rate by Phase State Regulation


Flow rate and holdup are two essential parameters to describe oil-water two-phase flow. The distribution of oil-water two-phase flow in the pipeline is very uneven, and there is a significant slippage between the phases. This makes it difficult to measure these two flow parameters. In this paper, a new measurement method of flow rate and holdup based on phase state regulation is proposed. The oil-water two-phase flow is adjusted to oil or water single-phase flow according to the time sequence by the phase state regulation, and the oil-water phase interface is measured with a conductance sensor. A wavelet transform based phase inflection point detection model is proposed to detect the oil-water phase change point. The experimental results show that the maximum measurement error of the flow rate of water is 3.73%, the maximum measurement error of the flow rate of oil is 3.68%, and the flow rate measurement repeatability is 0.0002. The accuracy of the measurement holdup is better than 3.23%, and the repeatability of the measurement holdup is 0.0003. The prototype designed based on this method has two advantages. One is that it is small in size, the other is that it does not depend on the accuracy of the sensor. Therefore, it can be widely used in oilfield ground measurement.




Michal Ulvr:

An Experimental Setup for Power Loss Measurement up to 1 kHz using an Epstein Frame at CMI


This paper describes an experimental setup used at the Czech Metrology Institute (CMI) to measure the specific power loss of oriented and non-oriented electrical steel sheets up to 1 kHz using an Epstein frame. Special attention is given to a) a description of the hardware that is used, b) a description of the feedback control and measurement software, and c) an analysis of the sources of uncertainty and validation. Calibration expanded uncertainty of (0.5 up to 1.6)% for k = 2 can be achieved with this setup.



Chaitanya B., Manjunathachari K.:

Modified Micro strip Feed Hybrid Rectangular Dielectric Resonator Antenna for Wireless Tri-Band Applications


This article reports the Modified Micro strip Feed Hybrid Rectangular Dielectric Resonator Antenna (RDRA). The proposed structure has a ground plane with a plus-shaped slot on the FR4 substrate of height 1.6 mm with 38 mm x 35 mm as it dimensions. The proposed Dielectric resonator antenna is made of the material with 10 as its dielectric constant, and the dimension of the DR is 19 x 20 x 18 mm3. The DR is attached with the modified micro strip feed with an octagonal ring throughout the plus shape slot in the ground. The proposed structure operates from 2.60 GHz - 2.74 GHz, 3.12 GHz - 3.37 GHz, and 4.25 GHz - 4.37 GHz. The resonant frequency of the final proposed RDRA is 2.68 GHz, 3.26 GHz, and 4.31 GHz, which covers the WLAN, WIMAX, and Wireless Avionics Intra-Communications (WAIC) applications, respectively. The entire structure is simulated using the CST microwave studio. The simulated are comply with the measured results and both are presented. The compact size, stable radiation pattern, along with reasonable gain, makes this antenna suitable for the proposed applications.







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