Verify System Performance Research Articles

Prototype‐Based Collaborative Learning in UAV‐Assisted Edge Computing Networks

ABSTRACTContextThe rise of artificial intelligence of things (AloT) has enabled smart cities and industries, and UAV‐assisted edge computing networks are an important technology to support the above scenarios. UAV‐assisted refers to leveraging UAVs as a dynamic, flexible infrastructure to assist edge network data processing and communication tasks. Multiple UAVs can use their own resources, and collaborate edge servers to train artificial intelligence (Al) models.ObjectiveCompared with cloud‐based collaborative computing scenarios, UAV‐assisted edge collaborative learning can reduce training and inference delays and improve user satisfaction. However, UAV‐assisted edge networks scenario brings new challenges in terms of transmission burden and energy consumption.MethodThis paper proposes a prototype‐based joint optimization and training software system. The system consists of an optimization module and a training module. The optimization module first models an optimization problem including energy consumption and prototype error. Then it solves the optimization problem by problem transformation and plans the location of each UAV given the objects' position. After UAVs fly to the designated area and complete data collection, UAVs and the edge server train a model according to the proposed prototype‐based collaborative training module. Our training module enables multiple UAVs and an edge server to collaboratively train a model by lightweight prototype transmission and prototype aggregation. We also prove the convergence of the proposed collaborative training method.ResultsResults show our method reduces prototype error and energy consumption by at least 12.31% and improves model accuracy by 3.62% with a little communication burden.ConclusionFinally, we verify system performance through experiments.

For a clinical application of optical triangulation to assess respiratory rate using an RGB camera and a line laser

This paper presents a non-contact and unrestrained respiration monitoring system based on the optical triangulation technique. The proposed system consists of a red-green-blue (RGB) camera and a line laser installed to face the frontal thorax of a human body. The underlying idea of the work is that the camera and line laser are mounted in opposite directions, unlike other research. By applying the proposed image processing algorithm to the camera image, laser coordinates are extracted and converted to world coordinates using the optical triangulation method. These converted world coordinates represent the height of the thorax of a person. The respiratory rate is measured by analyzing changes of the thorax surface depth. To verify system performance, the camera and the line laser are installed on the head and foot sides of a bed, respectively, facing toward the center of the bed. Twenty healthy volunteers were enrolled and underwent measurement for 100s. Evaluation results show that the optical triangulation-based image processing method demonstrates non-inferior performance to a commercial patient monitoring system with a root-mean-squared error of 0.30rpm and a maximum error of 1rpm (p>0.05\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p > 0.05$$\\end{document}), which implies the proposed non-contact system can be a useful alternative to the conventional healthcare method.

Implementation of battery storage system in a solar PV-based EV charging station

Commercial production of solar-powered battery charging stations for electric vehicles has recently started largely as a result of the growing popularity of electric vehicle (EV) technology as well as the falling cost of photovoltaic (PV) systems. The rise in popularity of EVs may be attributed to both the progression of technology and rising awareness of environmental issues. In this work, a 400V DC bus voltage-based EV charging station is designed which is powered by both a PV system and a utility grid. Also, battery energy storage units are used to overcome the unpredictable behavior of the environment. An Energy management algorithm (EMA) has been presented to balance the power flow among PV, EVs, BESS, grid, and residential load. A sharing coefficient-based power sharing is done between the grid and battery to reduce the stress from the battery units. Then, a multi-step constant current charging method is used to charge the EVs in the charging station to maintain the proper state of charge (SOC) of EV batteries. During this study, different operating conditions are considered according to available PV power and load to validate the power management scheme in the EV charging station. The model is run using MATLAB simulation and opal-RT simulation. The obtained results have been demonstrated with an explanation and system performance verification.

Implementation of Simple Additive Weighting to Decide a Fund Proposal

One of Indonesian micro financial services is Baitul Maal Wat Tamwil (BMT) provides services such as savings, financing and zakat activities. Financing service determine qualifying status based on consideration of customer files before carried out in company discussions. This decision support system aims to provide officers to decide whether or not to admit funding. The research used Simple Additive Weighting (SAW) by finding the prejudiced sum of the performance ratings for each alternative from all criteria. The method used 7 criteria including income, outstanding loans, amount of financing, collateral, nature/environment, track record of financing and monthly expenses. Customers were declared acceptable if they had a preference value above the minimum limit of 16.1. The BMT officer can adjust the minimum limit value according to customer performance. To develop the system used waterfall method and to verify system performance used a black box test which shows the results that the system works according to its function and the validity test results obtained 100% accurate. It means the system is ready and suitable for use. The existence of this decision support system is able to assist officers in making decisions to qualify for financing objectively.

Considerations for determining the performance of ultraviolet light emitting diode fluid disinfection systems.

The International Ultraviolet Association (IUVA) Task Force was formed to develop guidelines regarding testing and reporting on performance of UV LED water disinfection systems. The goal was to provide clarity in a guidance document on measuring system performance across the global UV LED water disinfection system market. A review of current performance measurement protocols for mercury lamp based systems shows that the common elements of UV LED system performance measurement protocols should be as follows: specified standard for the amount of pathogen reduction required, the requirement that the validation testing be conducted by a competent facility, and that the system be continually monitored by UV sensors while in use to verify system performance unless pathogen reduction is not claimed. UV LEDs have selectable peak wavelengths, as opposed to mercury lamps that have fixed emission wavelength values. As a result of this difference, the following changes to protocols used to test mercury lamp systems are recommended. First, the use of disinfection benchmarks other than 254 nm dose, such as direct inactivation values, dose benchmarks referenced to 254 nm, and/or dose benchmarks at the UV LED emission wavelength that give the same inactivation as the original 254 nm UV dose benchmark. Second, the use of 254 nm UV water transmittance values as a placeholder, rather than an assumed correct value, for systems under test with LED wavelengths >250 nm and water transmittance values ≥87%. More research is needed for lower wavelengths and UVTs. Third, the recommendation that germicidal response UV sensors be used in UV LED based systems to ensure that the validated disinfection is delivered. Finally, additional LED-specific considerations were also noted. UV LEDs are also instant-on devices, making them ideal light sources for systems operated intermittently. Performance testing of systems operated intermittently should include a test to insure that pathogens do not migrate past the UV LEDs while the LEDs are off. UV LED devices have recognized protocols for determining the lifetime of the devices, as well as for measuring other device properties. Caution should be exercised in using these lifetime values for devices in UV disinfection systems, since the thermal environment of the devices may be different for protocol testing and disinfection system operation. PRACTITIONER POINTS: Validation of UVC LED fluid disinfection is necessary for point of use, point of entry, and municipal applications. The emission spectrum properties, considerations and measurements for output over lifetime, and unique system design considerations of UVC LEDs as light sources are factors that must be considered when evaluating fluid disinfection performance. The instant-on operation, system geometry, validation benchmarks, system sensing, water transmittance, and fouling must also be considered for UVC LED devices when evaluating fluid disinfection performance.

Customer churn prediction using machine-learning techniques in the case of commercial bank of Ethiopia

The number of service providers is increasing rapidly in every business. These days, there is plenty of options for customers in the banking sector when choosing where to put their money. As a result, customer churn and engagement have become one of the top issues for most of the banks. In this paper, a method to predict customer churn in a Bank using machine learning techniques, which is a branch of artificial intelligence, is proposed. The research promotes the exploration of the likelihood of churn by analyzing customer behavior. random forest (RF), logistic regression (LR), gradient boosting classifier (GBC), extreme gradient boosting classifier (EGBC), and light gradient boosting machine classifier (LGBCMC) are used in this study. Also, some feature selection methods have also been done to find the more relevant features and verify system performance. The experimentation was conducted on the churn modeling dataset from Kaggle. The results are compared to find an appropriate model with higher precision and predictability. As a result, using the Random Forest model after oversampling is better than other models in terms of accuracy. The experimental result shows that the Light Gradient Boosting Machine classifier outperformed with an accuracy of 98%, a precision of 97%, and a recall of 100%, with an AUC of 99% than other proposed supervised machine learning algorithms with balanced datasets across all evaluation metrics.

Development of sub-mirror radius of curvature automatic test system for IACT

The Image Air shower Cherenkov Telescope (IACT) is one powerful instrument to study gamma ray astronomy. Generally the reflection system of IACT is assembled by multiple small sub-mirrors. It is time-consuming and costly to measure the sub-mirrors for the traditional manual method. In order to solve the problem, we design and develop an automatic system to measure the radius of curvature (ROC) of spherical sub-mirrors. A foam aluminum sample spherical mirror is tested to verify system performance. The repeated measurement error of the system ROC is 5.68 mm with the step 5 mm, and the minimum spot size repeated measurement error is 0.04 mm. The results indicate that the accuracy and stability of the system are excellent. Two mirrors with different ROC are measured. The ROC of the aluminum foam structure mirror is 16100.30 ± 5.59 mm, and the minimum spot size is 3.37 ± 0.04 mm. The ROC of a glass mirror is 5810.00 ± 1.42 mm with the step 1 mm and a minimum spot size of 1.92 ± 0.02 mm. The results indicate that the system is suitable for measuring mirrors with different ROCs and the measurement results are effective and reliable. It is vital to note that the measurement is fast and unattended, the single measurement time is less than 5 minutes and the total time is less than 15 minutes.

Sensitivity Analysis of Transient Critical Heat Flux by RIA Under High-Pressure Flow Boiling Conditions in TRTL

A reactivity-initiated accident (RIA) is a design-basis accident under which critical heat flux (CHF) is likely to be exceeded. The operational margin for RIAs is currently determined using steady-state CHF lookup tables, which provide conservative estimates relative to transient CHF phenomena. The Transient Reactor Test Loop (TRTL) facility at Oregon State University is capable of performing out-of-pile rapid heating experiments representative of a RIA at conditions representative of a pressurized water reactor (PWR). To further our understanding of and ability to predict transient CHF under PWR conditions, we performed a sensitivity analysis on a RELAP5-3D model of the TRTL facility coupled to the RAVEN code framework to define a proposed experimental test matrix to be performed at the TRTL facility. We then implemented a flow boiling CHF correlation into RELAP5-3D and performed a secondary sensitivity analysis inspecting the impact of the built-in RELAP5-3D CHF and heat transfer multipliers on both the prediction of CHF and key safety parameters, such as peak cladding temperature and heat flux. The results show that the multiplier with the highest influence toward the prediction of CHF occurrence and the safety parameters is the transient CHF multiplier. Operational performance envelopes have been developed for each of the test matrix cases and will be used for validation once the experiments are performed. The TRTL facility is currently performing shakedown testing to verify system performance prior to proceeding with the experimental campaign. Restart testing results include pump curve restart testing, pressure tests, and heater rod thermocouple transients.

Churn Prediction using Various Machine Learning Algorithms

In the era of big data, customer churn is a big problem faced by banks in the increasingly competitive market. The number of service providers are being increased very rapidly in every business. In these days, there is no shortage of options for customers in the banking sector when choosing where to put their money. In this paper, a method to predicts the customer churn in a Bank, using machine learning techniques, which is a branch of artificial intelligence is proposed. The research promotes the exploration of the likelihood of churn by analyzing customer behaviour. The KNN, SVM, Decision Tree, and Random Forest classifiers are used in this study. Also, some feature selection methods have been done to find the more relevant features and to verify system performance. The experimentation was conducted on the churn modelling dataset from Kaggle. The result gives us that in which algorithm the customer will stay or exits according to the data.

A control approach for power quality improvement of a large-scale grid connected PV system at standard test conditions

In this paper two stage grid connected photovoltaic system (GCPVS) is simulated in MATLAB/Simulink software with control strategy based on voltage source converter (VSC) which is operated to supply active power and filter the harmonics currents at common coupling point (CCP). The developed control scheme is applied to a large- capacity system of 1 MW and the parameters of the system components are attuned to achieve harmonics level in accordance with the IEEE standard 519. In presented system, power electronic converters, boost converter and inverter, are interfaced between photovoltaic generation unite and grid. To maximize power delivery by photovoltaic system, perturb and observation algorithm based maximum power point tracking technique (MPPT) is used for boost converter control. For the inverter control, VSC based strategy including reference frame transformation, phase lock loop interface, PI controllers and PWM technique is applied. The system performance was evaluated for power and voltage control at standard test conditions (STC) and relevant IEEE standard has been considered for its validation. Moreover, harmonics level for voltage and current signals at CCP is monitored by Fast Fourier transformation (FFT) analysis. Simulation results are presented to verify system performance for selected parameters.

Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM

AbstractThis paper presents the genetic algorithm (GA) and particle swarm optimization (PSO) based frequency regulation for a wind‐based microgrid (MG) using reactive power balance loop. MG, operating from squirrel cage induction generator (SCIG), is employed for exporting the electrical power from wind turbines, and it needs reactive power which may be imported from the grid. Additional reactive power is also required from the grid for the load, directly coupled with such a distributed generator (DG) plant. However, guidelines issued by electric authorities encourage MGs to arrange their own reactive power because such reactive power procurement is defined as a local area problem for power system studies. Despite the higher cost of compensation, static synchronous compensator (STATCOM) is a fast‐acting FACTs device for attending to these reactive power mismatches. Reactive power control can be achieved by controlling reactive current through the STATCOM. This can be achieved with modification in current controller scheme of STATCOM. STATCOM current controller is designed with reactive power load balance for the proposed microgrid in this paper. Further, gain values of the PI controller, required in the STATCOM model, are selected first with classical methods. In this classical method, iterative procedures which are based on integral square error (ISE), integral absolute error (IAE), and integral square of time error (ISTE) criteria are developed using MATLAB programs. System performances are further investigated with GA and PSO based control techniques and their acceptability over classical methods is diagnosed. Results in terms of converter frequency deviation show how the frequency remains under the operating boundaries as allowed by IEEE standards 1159:1995 and 1250:2011 for integrating renewable‐based microgrid with grid. Real and reactive power management and load current total harmonic distortions verify the STATCOM performance in MG. The results are further validated with the help of recent papers in which frequency regulation is investigated for almost similar power system models. The compendium for this work is as following: (i) modelling of wind generator‐based microgrid using MATLAB simulink library, (ii) designing of STATCOM current controller with PI controller, (iii) gain constants estimation using classical, GA and PSO algorithm through a developed m codes and their interfacing with proposed simulink model, (v) dynamic frequency responses for proposed grid connected microgrid during starting and load perturbations, (vi) verification of system performance with the help of obtained real and reactive power management between STATCOM and grid, and (vii) validation of results with available literature.

Ultrasound-Based Smart Corrosion Monitoring System for Offshore Wind Turbines

The ultrasound technique is a well-known non-destructive and efficient testing method for on-line corrosion monitoring. Wall thickness loss rate is the major parameter that defines the corrosion process in this approach. This paper presents a smart corrosion monitoring system for offshore wind turbines based on the ultrasound pulse-echo technique. The solution is first developed as an ultrasound testbed with the aim of upgrading it into a low-cost and low-power miniaturized system to be deployed inside offshore wind turbines. This paper discusses different important stages of the presented monitoring system as design methodology, the precision of the measurements, and system performance verification. The obtained results during the testing of a variety of samples show meaningful information about the thickness loss due to corrosion. Furthermore, the developed system allows us to measure the Time-of-Flight (ToF) with high precision on steel samples of different thicknesses and on coated steel samples using the offshore standard coating NORSOK 7A.

Development of a System Suitability Test for Two-Dimensional Liquid Chromatography

Verifying system performance is important when using chromatographic instrumentation for analyzing both known and unknown samples. Typically, system suitability tests (SSTs) are used to verify performance, which involves running an established method and comparing the results to pre-established acceptance criteria. As two-dimensional liquid chromatography (2D-LC) becomes used more widely and in regulated laboratory environments, development and implementation of SSTs will be critical for successful routine use of the 2D-LC technique.

A Dynamically Reconfigurable ECG Analog Front-End With a 2.5× Data-Dependent Power Reduction.

This paper presents a reconfigurable electrocardiogram (ECG) analog front-end (AFE) exploiting bio-signals' inherent low activity and quasi-periodicity to reduce power consumption. This is realized by an agile, on-the-fly dynamic noise-power trade-off performed over specific cardiac cycle regions guided by a least mean squares (LMS)-based adaptive predictor leading to ∼2.5× data-dependent power savings. Implemented in 65 nm CMOS, the AFE has tunable performance exhibiting an input-referred noise ranging from 2.38 - 3.64 μVrms while consuming 307 - 769 nW from a 0.8 V supply. A comprehensive system performance verification was performed using ECG records from standard databases to establish the feasibility of the proposed predictor-based approach for power savings without compromising the system's anomaly detection capability or ability to extract pristine ECG features.

RETRACTED ARTICLE: Agricultural business and product marketing effected by using big data analysis in smart agriculture

This article has been retracted from publication in the Taylor & Francis journal, Acta Agriculturae Scandinavica, Section B — Soil & Plant Science. Following publication, concerns were raised by multiple third-parties around the content of the special issue and the decision-making process. Following an investigation by the Taylor & Francis Publishing Ethics & Integrity team in full cooperation with the Editor-in-Chief, it was confirmed that this article included in Special Issue titled “ Envisage Computer Modelling and Statistics for Agriculture”, guest edited by Gunasekaran Manogaran was not peer-reviewed appropriately, in line with the Journal's peer review standards and policy. As the stringency of the peer review process is core to the integrity of the publication process, the Editor and Publisher have decided to retract all of the articles within the above-named Special Issue. The journal has not confirmed if the authors were aware of this compromised peer review process. The journal is committed to correcting the scientific record and will fully cooperate with any institutional investigations into this matter. The authors have been informed of this decision. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines.

Research on Channel Optimization of Ads-B Aviation Target Surveillance Radar Based on Improved Filtering Algorithm

In order to improve the surveillance effect of the aviation target surveillance radar, this paper improves the traditional filtering algorithm and builds the channel optimization system of the ADS-B aviation target surveillance radar based on the improved filtering algorithm. Moreover, this paper uses algorithm improvement to ensure the positive definite or semipositive definiteness of the state covariance and uses the root mean square volume Kalman filter to avoid the filter divergence or tracking interruption caused by the nonpositive definiteness of the matrix; the filtering principle of the interactive multimodel is to use multiple filters for parallel processing and achieve the adaptive adjustment algorithm residual error by adjusting the one-step prediction covariance in the adjustment algorithm. In addition, this paper combines the actual needs to construct a system functional structure to optimize the channel of the ADS-B aviation target surveillance radar and uses software engineering methods to model and analyze the requirements. Finally, this paper designs experiments to verify system performance. The research results show that the performance of the system constructed in this paper meets actual needs.

Multi-user accessible indoor infrared optical wireless communication systems employing VIPA-based 2D optical beam-steering technique.

Infrared optical wireless communication system can achieve ultrahigh capacity and high privacy data transmission. However, for using narrow infrared laser beam as carrier to transmit signal, the high-speed data transmission can only be achieved by point-to-point connection. With the rapid number increasement of consumer electronic devices, such connection method puts a heavy burden on the number of transmitters. Thus, the transmitting end with the point-to-multipoint capability or multi-user accessibility is required. In this paper, we present a multi-user accessible indoor infrared optical wireless communication system employing passive diffractive optics based on a virtually imaged phased array (VIPA). Multiple beams can be generated in a point-to-multipoint scheme by using VIPA-based beam-steering antenna (BSA). On the other hand, by tuning wavelength of laser source, fast 2D steering of multiple beams with the same steering trajectory is supported, which can be used for user ends with changing locations. In the experiment, 5 beams are generated by utilizing only one transmitter. All five beams can realize 12.5 Gb/s on-off-keying (OOK) data rate transmission. Free-space optical wireless transmission at 3.6-m communication distance is demonstrated for system performance verification and evaluation. a total 3.44°×7.9° scanning field of view of five beams is achieved.

Standalone electric vehicle charging station using an isolated bidirectional converter with snubber

AbstractThe rise of green technologies in transportation requires electric vehicles (EV) as a prominent solution for reducing greenhouse gas emissions. An off‐grid EV charging station plays a significant role in remote regions leading to increased use of EVs. Solar energy promises to be the best solution due to its abundance and simple installation. As solar energy is not constant over a 24‐hour period, there is a need for an energy storage unit (ESU) along with a photovoltaic array. In this paper, we present an efficient design approach that uses a fast‐charging station with a maximum power point tracking boost converter, a bidirectional DC‐DC converter with a snubber circuit, and ESU. The power electronic converters with an active snubber and two capacitive‐diode snubbers act as the energy sources that interface with the ESU. The snubber circuits achieve near zero voltage switching and zero current switching for the converter, thus improving overall efficiency. ESU meets the energy demand for EVs when there is insufficient generated solar energy. On the other hand, during the excess generation of solar energy, ESU utilizes this energy to develop an optimal power management system. This results in a green, reliable, and efficient off‐grid EV charging station. The proposed method is validated using the MATLAB/Simulink environment to verify system performance.

Industry 4.0: Hand Recognition on Assembly Supervision Process

In the assembly industry, the process of assembling components is very important in order to produce a quality product. Assembly of components should be carried out sequentially based on the standards set by the company. For companies that still operate the assembly process manually by employee, sometimes errors occur in the assembly process, which can affect the quality of production. In order to be carried out the assembly process according to the procedure, a system is needed that can detect employee hands when carrying out the assembly process automatically. This study proposes an artificial intelligence-based real-time employee hand detection system. This system will be the basis for the development of an automatic industrial product assembly process to welcome the Industry 4.0. To verify system performance, several experiments were carried out, such as; detecting the right and left hands of employees and detecting hands when using accessories or not. From the experimental results it can be concluded that the system is able to detect the right and left hands of employees well with the resulting FPS average of 15.4.

Development of grid‐interactive inverter utilising induction motor driven photovoltaic water pumping system

The stand-alone solar photovoltaic water pumping system (SPVWPS) remains idle for a significant period of time, when irrigation is not required and when sun is not available. Due to this large idle period, the effective utilisation of SPVWPS assets, i.e. solar photovoltaic array, power electronics converter, and motor, is poor. This study presents an approach to increase the effective utilisation of SPVWPS under the aforementioned idle period. It is proposed to interface the grid with SPVWPS without adding extra power electronic interface. An innovative integrated photovoltaic inverter is constructed using existing SPVWPS components. The inverter enables the transfer of active power and exchange of reactive power with the grid during an idle period of SPVWPS. The three legs of the voltage source inverter (VSI) are interleaved with motor windings. The VSI switches are controlled with synchronous pulse width modulation to force a cophasal current in the motor windings. This accompanies a net motor torque to zero under grid-interactive operation. Hence, the three-phase VSI operates as a single-phase grid synchronise converter, and the motor windings are used as filter inductance. The control system is presented to establish grid-interactive functionality. A prototype is developed to verify system performance. The control system is implemented using the ARM Cortex-M4 microcontroller.