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The Ikhwan Shop provides goods and cellphone repair services, but the system that runs in the shop records incoming and outgoing goods, and the results of repair services are still done by writing in a hand-written shop logbook. Therefore, a management system, an application designed to cover all activities running in the store, is needed. The activities are selling pulses, snacks, office stationery, receiving damaged cellphone repairs, and serving consignment of supplier goods. The system is equipped with a calculation of net and gross income and data collection related to employee salaries. After managers, cashiers, and technicians tested and implemented the system, it was concluded that it followed the business processes running at the Ikhwan shop. The system testing results with Blackbox show that all system functions can run well, so management activities run more effectively and efficiently. [ABSTRACT FROM AUTHOR]

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The primary aim of the present study is to explore the use, advantages and potential of two advanced data acquisition techniques – 3D scanning and digital image correlation (DIC), in the testing of metallic structures. 3D scanning is a novel method for capturing the full outer geometry of an object. It is being increasingly used in experimental studies for the determination of dimensional parameters and the characterisation of local and global imperfections, examples of which are given and discussed. Digital image correlation (DIC) is a rapidly evolving technology for the full‐field measurement of the displacements and strains over a surface. A brief introduction to DIC and its workflow is firstly provided. Example applications of DIC in various scales of experiments, including material tests, structural element tests and full‐scale structural system tests, are subsequently discussed. These new‐generation data acquisition techniques enable structural researchers to gain a deeper insight into the behaviour of metallic structures in experimental research. [ABSTRACT FROM AUTHOR]

This article presents a low-cost and flexible software solution for acoustic startle response (ASR) test that can be used with a Spike2-based interface. ASR is a reflexive response to an unexpected, loud acoustic stimulus, and prepulse inhibition (PPI) is a phenomenon in which the startle response is reduced when preceded by a weak prestimulus of the same modality. Measuring PPI is important because changes in PPI have been observed in patients with various psychiatric and neurological disorders. Commercial ASR testing systems are expensive, and their closed source code affects their transparency and result reproducibility. The proposed software is easy to install and use. The Spike2 script is customizable and supports a wide range of PPI protocols. As an example of PPI recording, the article presents data obtained in female rats, both wild-type (WT) and dopamine transporter knockout (DAT-KO), showing the same tendency as the data obtained in males, with ASR on a single pulse higher than ASR on prepulse+pulse, and PPI reduced in DAT-KO rats compared to WT. [ABSTRACT FROM AUTHOR]

Kitchen waste has the characteristics of complex components and differences in texture characteristics in rural areas. A control system based on PLC was designed for the screw press pretreatment with automatic pressure regulation of screw press, equipment cleaning, abnormal feeding handling, working condition monitoring, key data collection and other functions. The system could control the screw press device to treat kitchen waste automatically and realize solid-liquid separation and solid reduction. The screw press control system was tested under the conditions of 0-32 ℃ in different seasons all year round. The results show that the control system can realize automatic running according to the system logic requirements. The system can control the device to steady state within 240 s and keep the control accuracy within 5 percent of the setting value. The drive motor operates stably within 38%-50% of the rated current, and the control system can well match the screw device for kitchen waste pretreatment. [ABSTRACT FROM AUTHOR]

Solar photovoltaic (SPV) has become an inalienable part of the power system due to its numerous advantages over conventional energy sources. However, SPVs can be subjected to various kinds of faults which can degrade the overall performance of the system. Machine learning (ML) techniques may be useful to identify faults occurring in photovoltaic (PV) systems. In this paper, an ML technique called random under-sampling boosting (RUSBoost) has been applied to detect the different types of faults occurring on the DC side of the PV system. A test system of 4.8 kWp has been designed in MATLAB/Simulink environment for data acquisition of different operating conditions. Commonly used performance parameters have been used as features for the ML model. Thereafter, RUSBoost has been trained using features acquired from the test system. The work also investigates the optimum number of features required for fast and accurate detection of PV array faults. It has been found that, training the model with the current ratio, voltage ratio, power ratio, and array efficiency gives the best result with 99.6% training accuracy and 2.78 s of training time. The performance of RUSBoost is further compared to popular AdaBoost and bagged tree ensemble classifier algorithm to establish the efficacy of the applied ML technique. [ABSTRACT FROM AUTHOR]

Digital twin technology is a key technology to realize cyber-physical system. Owing to the problems of low visual monitoring of the blade-rotor test rig and poor equipment monitoring capabilities, this paper proposes a framework based on the digital twin technology. The digital-twin based architecture and major function implementation have been carried out form five dimensions, i.e. Physical layer, Virtual layer, Data layer, Application layer and User layer. Three key technologies utilized to create the system including underlying equipment real-time communication, virtual space building and virtual reality interaction have been demonstrated in this paper. Based on RS-485 and other communication protocols, the data acquisition of the underlying devices have been successfully implemented, and then the real-time data reading has been achieved. Finally, the rationality of the system has been validated by taking the blade-rotor test rig as the application object, which provides a reference for the monitoring and evaluation of equipment involved in manufacturing and experiment. [ABSTRACT FROM AUTHOR]

In order to improve the agility of college students, this paper designs a distributed agility training system. The system includes an upper computer and nine lower computers, in which the lower computer realizes the functions of data acquisition and communication with the upper computer and calculates the reaction time. The Android-based system software was installed in the upper computer to complete the functions of network connection, setting training times and showing the exercise time. In order to test the effectiveness of the equipment, nine university students were invited to complete agility training over 8 weeks with the help of agility training equipment in preparatory, enhancement and special stages. A t-test (Student's t test) was conducted on the test results at different positions on the front and middle and back areas of the court before and after the training. The results show that the agility of the experimental objects was significantly improved after training, from the midpoint to any point at the front, middle and back court (p < 0.01). This shows that using equipment designed to develop agility for long-term training can promote the sensitive quality in badminton learners. [ABSTRACT FROM AUTHOR]

Geotechnical centrifugal model testing is an important means to study complex geotechnical engineering problems, which has been widely concerned by scholars at home and abroad. The TPEI -200g·t geotechnical centrifuge model testing system was fully completed in 2021. The maximum centrifugal acceleration is 200g, the maximum load is 2t, and the effective radius is 4 m. The data acquisition system adopts American NI module, which is a dynamic and static integrated data acquisition system with 128 channels, which can collect data of soil pressure, pore pressure, strain, displacement, acceleration, etc. The system is equipped with a variety of equipment, such as centrifuge manipulator, shaking table, filling robot, water level fluctuation robot, etc., which can dynamically simulate a variety of practical working conditions, such as inserting and pulling piles, digging holes, vibration, filling, water level lifting and so on, and meet the needs of geotechnical tests in most cases. The testing system is based on providing technical services and support for major engineering projects, and provides a high-level research platform for the transportation industry. [ABSTRACT FROM AUTHOR]

University students' physical health test is an important part of university physical education. The data obtained by the physical health test play an extremely important role in the field of students' physical health research. This paper clarifies the current situation of data collection of the physical health test for college students by sorting out the development status and trend of the physical health test system in China. To further ensure the accuracy and validity of the physical health test data, this article puts forward the corresponding optimization measures for the data collection link of the existing physical health testing system given the problems existing in the implementation of university students' physical health tests. Optimization measures are as follows: (1) add a test data collection type for test video collection; (2) optimize the authentication process to increase face recognition; and (3) enhance posttest test data management by stamping time. [ABSTRACT FROM AUTHOR]

Electrochemical impedance spectroscopy (EIS) is a widely used technique for characterizing electrochemical systems. The term "electrochemical impedance spectroscopy" actually has a twofold meaning: it is both a measurement technique to determine impedance spectra and an analysis tool for extracting information about an electrochemical system. Contrary to some opinions, the design of valid EIS measurements is not trivial in practice, as systems under test also have to meet certain requirements to ensure the validity of the measured data. One of the most serious and underestimated problems is that many electrochemical systems (including biological, reacting, and corroding systems) are intrinsically non-stationary and are affected by time-dependent phenomena. This study provides an overview and guidance on some of the methodologies proposed in the literature to address problems related to impedance measurements in time-varying (non-stationary) systems. Selected techniques for the determination of "true" impedance spectra in non-stationary systems are briefly reviewed. To better understand the theoretical background of the different approaches, basic principles of the measuring methods and the fundamentals of data collection, validation, and correction are also discussed. [ABSTRACT FROM AUTHOR]

State-estimation plays a vital role to monitor, observe and understand the combined heat and electric network. In this paper, a hybrid framework is presented to accurately estimate the system states of electric distribution network and heat network, using the limited non-redundant measurements obtained from supervisory control and data acquisition and advanced metering infrastructure systems. The presented hybrid framework involves two steps, namely, the state-forecasting and the state-estimation. The state-forecasting uses a deep neural network to forecast the system states at every fifteen minutes interval, while these forecasted states are further used by the hybrid estimator, which uses a robust extended Kalman filter to estimate the system states with help of both datasets corresponding to supervisory control and data acquisition and advanced metering infrastructure systems, at hourly interval. The proposed framework does not completely rely on the system model at different instants. The effectiveness of the method is validated through thorough comparisons with simulation studies carried out using the Barry Island test system, United Kingdom. Satisfactory performance is observed even with the presence of bad data in the measurements. • A framework to estimate states of electric and heat networks with SCADA and AMI data • A method of forecasting the CHEN states using only a limited SCADA dataset • A robust Kalman filter for accurate estimation under gross errors in data. • Test results that validate the method on Barry Island CHEN system. • Comparative results over the state-of-art WLS and ANN based estimators. [ABSTRACT FROM AUTHOR]

English teaching plays an extremely important role in college education. It cannot just improve students’ English level, but also help students adapt to the increasingly open and complex society. Besides, it is an important foundation for students to further go to the world and integrate in the world development trend. Although English teaching has received attention of various colleges and universities, there are still many problems in college English teaching, and the teaching effect is not obvious. To make teaching conform to the rapid development of the new education environment and make teaching practice more fitted with the standard of modern education, teaching mode reform for college English is imperative. Based on the teaching idea of “assessment for learning”, the teaching management system was designed in this study, including three steps: teaching intelligence system, assessment and test system, and information feedback system. Meanwhile, interactive teaching approach was combined to plan the interactive teaching process of college English course, including the process of proposing and solving questions, independent thinking and cooperative learning module, and leaning achievement exchange activity. In the end, assessment-for-learning teaching mode was used to collect the data of four dimensions (degree of learning engagement, completion degree of English learning content, degree of English learning interaction, and English learning effect) and the learning performance evaluation system supported by big data was established. The experimental results show that the teaching mode in this study could effectively improve students’ learning performance and enhance their actual English application ability. [ABSTRACT FROM AUTHOR]

Each year in the United States, influenza causes illness in 9.2 to 35.6 million individuals and is responsible for 12,000 to 56,000 deaths. The U.S. Centers for Disease Control and Prevention (CDC) tracks influenza activity through a national surveillance network. These data are only available after a delay of 1 to 2 weeks, and thus influenza epidemiologists and transmission modelers have explored the use of other data sources to produce more timely estimates and predictions of influenza activity. We evaluated whether data collected from a national commercial network of influenza diagnostic machines could produce valid estimates of the current burden and help to predict influenza trends in the United States. Quidel Corporation provided us with de-identified influenza test results transmitted in real-time from a national network of influenza test machines called the Influenza Test System (ITS). We used this ITS dataset to estimate and predict influenza-like illness (ILI) activity in the United States over the 2015-2016 and 2016-2017 influenza seasons. First, we developed linear logistic models on national and regional geographic scales that accurately estimated two CDC influenza metrics: the proportion of influenza test results that are positive and the proportion of physician visits that are ILI-related. We then used our estimated ILI-related proportion of physician visits in transmission models to produce improved predictions of influenza trends in the United States at both the regional and national scale. These findings suggest that ITS can be leveraged to improve "nowcasts" and short-term forecasts of U.S. influenza activity. Author summary: The United States Centers for Disease Control and Prevention (CDC) tracks influenza activity through a national surveillance system. However, the CDC influenza surveillance data are subject to a 1 to 2 week reporting delay, which limits how such information can be used to assess the current burden of disease and to make timely projections of the trajectory of the epidemic. Researchers have previously used indirect signals of influenza activity such as Google search queries for influenza-related terms or Twitter posts to develop more timely estimates of influenza burden and improved model-based forecasts. However, these indirect signals are subject to behavioral changes not related to influenza activity, and thus may provide inaccurate estimates and projections. We used a new real-time data source with high geographic resolution that is directly related to influenza activity: influenza test results provided through a national network of commercial influenza diagnostic test machines. We used these influenza test results to accurately estimate the current burden of influenza and improve real-time model projections of influenza burden in the United States. [ABSTRACT FROM AUTHOR]

This paper presents a measurement-based method to determine distributed energy resource (DER) active- and reactive-power setpoints that minimize bus voltage deviations from prescribed reference values, bus active- and reactive-power deviations from desired setpoints, as well as cost of DER outputs. Central to the proposed method is the estimation of a linear sensitivity model from synchronized voltage and power-injection data collected from distribution-level phasor measurement units installed at only a subset of buses in the distribution system. As new measurements become available, the linear sensitivity model is updated via the recursive weighted partial least-squares estimation method. The estimated sensitivity model is then embedded as an equality constraint in a convex quadratic optimization problem, which can be solved via, e.g., the alternating direction method of multipliers. Numerical simulations involving the IEEE 33-bus distribution test system illustrate key benefits of the proposed method, including (i) eliminating the need for an accurate offline system model, (ii) adapting to online network-topology and operating-point changes, and (iii) being robust against delays potentially attributed to communication, computation, and actuation. Additional numerical simulations involving larger test systems demonstrate computational scalability. [ABSTRACT FROM AUTHOR]

The accuracy of power system state estimation (PSSE), its robustness against bad data and the speed of its algorithm are crucial to economic and secure system operation. On the other hand, observability and redundancy considerations mandate PSSE to take advantage of traditional supervisory control and data acquisition (SCADA) measurements along with available phasor measurement unit (PMU) measurements. This set of hybrid PMU/SCADA inputs has traditionally made the problem formulation non-linear, and hence time-consuming to solve due to the iterative process of solution. This study addresses the foregoing challenges by proposing a novel linear least-absolute-value (LAV) estimation, without the need for an initial guess of the system state. The linearity of the proposed PSSE formulation is guaranteed regardless of whether PMU-only, SCADA-only or hybrid SCADA/PMU measurements are utilised. This facilitates the fast and non-iterative solution of the LAV estimation of system state based on linear programming. The LAV estimator outperforms the weighted-least-squares estimator in dealing with erroneous measurements, by automatically rejecting bad data of any size. An extensive number of simulation studies carried out on test systems of different sizes confirm the superiorities of the proposed method in comparison with other existing PSSE methods. [ABSTRACT FROM AUTHOR]

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Air-lock-entrapped phenomenon is easy to occur in the process of water filling and air exhaustion of the undulating pipeline. A test loop system for the simulation of the entrapped air movement with a wide range of inclination angle( 0° ～ 30°) was designed and constructed in view of the lack of research on formation and evolution characteristics of air-lock and the unclear flow mechanism of gas-liquid two-phase coupling. The test system includes a water supply subsystem, a test piping subsystem, an inclination-angle adjustment subsystem, a drainage subsystem, a camera subsystem and a data measurement and acquisition subsystem. The test results on the loop show that it can be used for in-depth study of gas-liquid two-phase flow characteristics during the formation and development of the entrapped airlock. [ABSTRACT FROM AUTHOR]

The work presented in this paper focuses on fiber brag grating (FBG) sensor data acquisition and measurements. A brief overview of the technology and of fiber bragg grating is presented as a basis of understanding of the experimental work. Hardware of the test system is presented in detail with its characteristics. Three distinct FBG sensors are presented, namely, temperature, strain and humidity. The experimental section tests these three sensors and a few observations are made about the testing implementation. [ABSTRACT FROM AUTHOR]

An indirect method based on timestamp analysis is developed to estimate the deadtime of a data acquisition (DAQ) system as a function of data size (deadtime function). The performance of two types of time-to-digital converter (TDC) modules, the CAEN V1190 and the AMSC AMT-TDC, are studied by applying the proposed method to a test DAQ system built with the TDC modules. With the aid of this method, the DAQ system of the SAMURAI spectrometer at the RIKEN radioactive isotope beam factory (RIBF) is optimized. Through the optimization, the minimum deadtime of one event decreases from about 170 μ s to about 45 μ s. • Deadtime is represented as a function of data size (deadtime function). • A method is developed to evaluate the deadtime function from experimental data. • Deadtime functions of subsystems of a compound DAQ system can be extracted. • Deadtime of SAMURAI DAQ is shortened with the aid of the proposed method. [ABSTRACT FROM AUTHOR]

• Drawbacks of linear-based stability assessment techniques are discussed. • A data-driven scheme is proposed to monitor the stability of SST-based microgrids. • The proposed approach is verified using NI PXIe real-time processor. • Associated parameters are modified in real-time leading to more accurate results. In this paper, a data-driven based Real-time Stability Metric (RSM) is proposed to evaluate the stability in Solid State Transformer (SST)-based modern distribution systems based on nonlinear time series analysis. This approach brings two main advantages to the analysis. First, the time series dataset is obtained from the terminal measurement; therefore, linearization is not necessarily needed as opposed to linear approaches. Second, fast dynamics in the system can be captured by an appropriate time resolution in data acquisition and it facilitates the proposed stability analysis capable in real-time. In this study, three Solid State Transformers are considered in a microgrid as the test system. Stability is evaluated by real-time determination of Lyapunov exponents through a real-time processor coordinated with the microgrid. [ABSTRACT FROM AUTHOR]

Abstract: The geomembrane play vital role in environmental protection by its characteristics of anti-infiltration, draining water and reinforcement. In order to promote automation test level about geomembrane, test system on waterpower about geomembrane is designed. Computer sends commands to driver card PCI-1020, using PCI-1020 card control stepper motor driver and stepper motor to apply pressure to sample, simultaneity, the sensor''s signals were sent to PCI-1711 acquisition card for A / D conversion, then, PCI-1711 send data into computer. This article discuss the system''s overall design, the hardware structure, software design, and process of data acquisition in detail. Software is designed by VB. Experiment results show that the test system possesses the advantages of high-speed data acquisition and high-accuracy. [Copyright &y& Elsevier]

Background: After stroke, sustained hand rehabilitation training is required for continuous improvement and maintenance of distal function.Methods: In this paper, we present a system designed and implemented in our lab: the Home based Virtual Rehabilitation System (HoVRS). Fifteen subjects with chronic stroke were recruited to test the feasibility of the system as well as to refine the design and training protocol to prepare for a future efficacy study. HoVRS was placed in subjects' homes, and subjects were asked to use the system at least 15 min every weekday for 3 months (12 weeks) with limited technical support and remote clinical monitoring.Results: All subjects completed the study without any adverse events. Subjects on average spent 13.5 h using the system. Clinical and kinematic data were collected pre and post study in the subject's home. Subjects demonstrated a mean increase of 5.2 (SEM = 0.69) on the Upper Extremity Fugl-Meyer Assessment (UEFMA). They also demonstrated improvements in six measurements of hand kinematics. In addition, a combination of these kinematic measures was able to predict a substantial portion of the variability in the subjects' UEFMA score.Conclusion: Persons with chronic stroke were able to use the system safely and productively with minimal supervision resulting in measurable improvements in upper extremity function. [ABSTRACT FROM AUTHOR]

This study presents the phasor measurement unit (PMU) placement strategy in the presence of false data injection attacks which is one of the most serious security threats against power grid. It is focused on applications related to supervisory control and data acquisition (SCADA) systems where measurement data can be easily corrupted by adversaries without getting caught by the system. To safeguard power grids against malicious attacks, procedures have been proposed to facilitate the placement of secure PMUs to defend against false data injection attacks in a highly cost-effective way. It has formulated a method of identifying measurements that are vulnerable to false data injection attacks. It was discovered that a weak power grid can be transformed into a robust power grid by adding a few PMUs at vulnerable locations. Simulations on the IEEE standard test systems demonstrate the benefits of the proposed procedure. [ABSTRACT FROM AUTHOR]

Due to the risk of failure of LED luminaries induced by the driver power, performance testing is especially important to driver power in some critical industries production and acceptance of work. A test system of LED driver based on LabVIEW is proposed to detect multiple physical parameters, including input voltage, output current, driver power efficiency, peak factor of current ripple and total harmonic distortion etc. The component selection of the system was investigated and the framework of the proposed system was presented. The hardware of this system mainly consists of signal conditioning modules, data acquisition card, test cables and computer. The software is designed by LabVIEW to realize the calculation, display and analysis of the collected data. The experimental results show that the system can realize the test of LED driver, and real-time grade determination of the test results according to relevant standards or the exact level specified by client. In addition, the system has simple structure and high expansibility, which is convenient for early use and later maintenance. The stability and bias was carried out to evaluate the proposed system by Minitab software, which ensured the measurement accuracy. [ABSTRACT FROM AUTHOR]

A single calorimeter station for the Muon g − 2 experiment at Fermilab includes the following subsystems: a 54-element array of PbF 2 Cherenkov crystals read out by large-area SiPMs, bias and slow-control electronics, a suite of 800 MSPS waveform digitizers, a clock and control distribution network, a gain calibration and monitoring system, and a GPU-based front-end which is read out through a MIDAS data acquisition environment. The entire system performance was evaluated using 2.5–5 GeV electrons at the End Station Test Beam at SLAC. This paper includes a description of the individual subsystems and the results of measurements of the energy response and resolution, energy-scale stability, timing resolution, and spatial uniformity. All measured performances meet or exceed the g − 2 experimental requirements. Based on the success of the tests, the complete production of the required 24 calorimeter stations has been made and installation into the main experiment is complete. Furthermore, the calorimeter response measurements reported here informed the design of the reconstruction algorithms that are now employed in the running g − 2 experiment. [ABSTRACT FROM AUTHOR]