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This paper describes the control system for a dispersion interferometer based on a CO2 laser developed by the Budker Institute of Nuclear Physics (Novosibirsk, Russia) for the Globus-M2 tokamak (Ioffe Institute, St. Petersburg, Russia). The basis of this system is the programmable controller ADAM-5510E/TCP with a set of analog and digital input/output modules and specially developed software that allows monitoring and control of the operation and parameters of interferometer elements. During the year of the dispersion interferometer operation as a standard diagnostic at the Globus-M2 tokamak, the control system showed good levels of reliability and sustainability. [ABSTRACT FROM AUTHOR]

In this article, power quality disturbances, such as voltage and current unbalances, series and shunt faults, are monitored in three-phase synchronous machines. Because the imbalances affect machine efficiency and service life, it is essential to figure out whether the three-phase voltages/currents are balanced or unbalanced. An integrated detection algorithm is proposed to detect the unbalanced voltages/currents and various abnormal conditions precisely and quickly, which is based on the coherence estimator. Most existing detection methods require more than one cycle time to determine the contingency conditions, while the proposed technique detects these situations in a fast and discrete protection system. The suggested scheme acquires instantaneous measurements of the three-phase voltages and currents taken at the synchronous machine terminals in order to calculate fifteen coherence coefficients that are utilized to detect and assess any unbalance or trouble accurately and swiftly. A new proposal for imbalance and disturbance indicators based on the coherence estimators is developed in this study. Multiple test cases have been conducted to validate the proposed algorithm capabilities using a real power system, which includes a motor-generator set, a three-phase load and measurement transformers. The experimental results have been revealed that the relay reliability and accuracy percentages have been found to be 98.28% and 98.52%, respectively. The quantitative findings of the imbalance and disturbance assessment are recorded. [ABSTRACT FROM AUTHOR]

India is experiencing rapid expansion in renewable energy resources as a result of economic challenges posed by rising oil prices and natural concerns. Since the early 2000s, solar photovoltaic (PV) adoption has accelerated exponentially. By 2015, global installed capacity will exceed 222GW. By 2050, it is anticipated to reach 4500GW. Solar photovoltaic panels on polycrystalline roofs have an efficiency of 22.7%. The cancer tropics travel through eight states in India, where summer temperatures range between 40 and 50 degrees Celsius, reducing the efficiency of solar panels. As a result, efficient Maximum Power Point Training (MPPT) controllers are required to close this gap. The experimental test was conducted in Ghaziabad at latitude 28.6692 (N) and longitude 77.4538 (W) (E). The solar photovoltaic simulator was created with LabVIEW software. The effect of temperature, irradiance, series resistance, shunt resistance, and ideal factor fluctuations on the performance of a solar panel has been investigated. The simulated findings are validated against an experimental setup to ensure the accuracy and reliability of the results using NI myRIO and LabVIEW. [ABSTRACT FROM AUTHOR]

Conventional baseband processing techniques for communication must be adapted to the specificities of terahertz channels. Currently, there is limited research on channel coding applicable to terahertz bands, particularly in terms of performing real-time tests that differentiate them from offline processing. This paper presents a test platform for a 300 GHz wireless communication system based on the PXIe platform. The experiment utilizes a high-performance, low-complexity serial scheduling approach with the Minimum Sum-Log Likelihood Ratio Belief Propagation (MS-LLR-BP) soft decision decoding algorithm to test point-to-point real-time line-of-sight communication for low-density parity-check (LDPC) code communication systems. The results indicate that the implementation of LDPC coding in QPSK terahertz wireless transmission systems results in a performance enhancement of approximately 25–55% in bit error rate (BER), demonstrating the excellent performance of LDPC codes against terahertz channel fading. This highlights their potential in future ultra-high-speed communication systems. [ABSTRACT FROM AUTHOR]

Robots are increasingly present in everyday life, replacing human involvement in various domains. In situations involving danger or life-threatening conditions, it is safer to deploy robots instead of humans. However, there are still numerous applications where human intervention remains indispensable. The strategy to control a robot can be developed based on intelligent adaptive programmed algorithms or by harnessing the physiological signals of the robot operator, such as body movements, brain EEG, and muscle EMG which is a more intuitive approach. This study focuses on creating a control platform for a 3-finger gripper, utilizing Electromyography (EMG) signals derived from the operator’s forearm muscles. The developed platform consisted of a Robotiq three-finger gripper, a Delsys Trigno wireless EMG, as well as an NI CompactRIO data acquisition platform. The control process was developed using NI LabVIEW software, which extracts, processes, and analyzes the EMG signals, which are subsequently transformed into control signals to operate the robotic gripper in real-time. The system operates by transmitting the EMG signals from the operator's forearm muscles to the robotic gripper once they surpass a user-defined threshold. To evaluate the system's performance, a comprehensive set of regressive tests was conducted on the forearm muscles of three different operators based on four distinct case scenarios. Despite of the gripper’s structural design weakness to perform pinching, however, the results demonstrated an impressive average success rate of 95% for tasks involving the opening and closing of the gripper to perform grasping. This success rate was consistent across scenarios that included alterations to the scissor configuration of the gripper. [ABSTRACT FROM AUTHOR]

Nowadays the detection of fabric defects is an active research topic to detect and resolve the difficulties faced in processing fabric in printing and knitting in textile industries. The traditional approach of visual screening of human fabrics is exceedingly time consuming and it is not reliable as it is much susceptible to human errors. There are two major issues in defect inspection like defect identification and classification in fabric. Automatic identification of defects is quite important in the current scenario. For enhancing the quality of the fabric, this paper proposes a Texture Defect Detection (TDD) algorithm. This TDD algorithm utilizes pre-processing for the extraction of luminance plane and Discrete wavelet frame decomposition for dividing the image into several subbands with same resolution as input image. Statistical features are extracted using Gray Level Co-occurrence Matrix and these features are applied to Support Vector Machine for classifying the defective images. This improves the quality of texture segmentation and classification of visible defects. The experimental setup is done with the fabric conveyor and three high resolution industrial cameras acA4600-7gc for covering the entire width of the fabric while running. This TDD algorithm is developed under LabVIEW platform. Textile Texture Database (TILDA) multi-class dataset is used for testing the proposed algorithm. This algorithm is tested for 4 different classes of fabric defects including 2800 defective and 400 non defective fabric images. The success rate of detection of fabric defect is 96.56% with the images from the database. The validation results with real time fabric images show 97% of accuracy in the detection of defects in fabric images. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite System (GNSS) receivers perform many important signal-processing operations, among which signal acquisition is of great importance. The acquisition provides a coarse estimate of the code delay and Doppler frequency values of the received signal, which plays an important role in synchronizing the local code with the received signal. Depending on the application domain, GNSS signals may be affected by indoor and urban channel conditions, interference, and jamming. Since the GNSS signal has to travel thousands of kilometers to reach the receiver antenna and then the receiver circuitry, the received signal becomes weak and degraded. One way to deal with such situations is the implementation of an advanced signal-processing algorithm in the receiver capable of giving appropriate warnings or improving the receiver's performance. In this paper, we propose a method based on wavelet denoising that helps improve receiver acquisition sensitivity, thus stepping up the accuracy of the receiver. The proposed method uses wavelet transform (WT) to divide the wavelet space, with improved de-correlation capability resulting in improved signal acquisition. This method is implemented on a Navigation with Indian Constellation (NavIC) receiver built on a LabVIEW-based software platform. Real-time experiments showed that the proposed method could improve the acquisition and receiver performance by 49–52% under the degraded signal environment. [ABSTRACT FROM AUTHOR]

Epilepsy is a neurological disorder characterized by abnormal brain activity, resulting in seizures, periods of unusual behavior, and, in severe cases, loss of consciousness. If epilepsy is detected early, it may reduce the patient's health risk significantly. Sometimes people's lives could be saved. There are numerous methods for detecting epileptic activity in brainwaves. One such method is through LabVIEW, a graphical programming software. The peak detection method, implemented in LabVIEW, can be used to detect epileptic activity. Because it reduces erroneous detection, this method is more efficient than manual detection. This research demonstrates epileptic activity by detecting peaks in an EEG database that contains both epileptic and non-epileptic EEG waves from online websites such as the Child Mind Institute and pre-processed EEG datasets. A total of 150 EEG waves were examined, with 25 displaying epileptiform abnormalities and the remaining 125 being completely normal. This method was found to be 97.33% accurate in detecting epileptic activity in the brain. [ABSTRACT FROM AUTHOR]

Industry 4.0 standards have been widely adopted by most industries, encompassing remote monitoring for workplace safety, logistics, asset monitoring, quality management, and product monitoring. Real-time data, including images, must be transmitted for effective remote monitoring. However, due to cybersecurity concerns, the data must be encrypted before being sent over the internet. To address this, a real-time smart camera-based encryption method using chaos is proposed in this work. The encryption logic is created using LabVIEW and integrated into the smart camera. The four-step encryption process includes pixel shuffling, confusion, Improved logistic mapping, and diffusion. Encryption keys are generated using the user’s passcode to set the initial parameters of the logistic mapping for generating key sequences. The resulting encrypted frames are diffused with index key streams to further enhance security. The proposed method has undergone security and performance analyses, demonstrating robustness against various vulnerabilities and minimal computational time. This makes it suitable for real-time encryption scenarios in Industry 4.0. [ABSTRACT FROM AUTHOR]

In this study, elastic waves generated from a SKD11 (HV670) steel specimen under various corrosive solutions were investigated. The frequency characteristics of the waves, as well as how hydrogen aggregation and crack propagation affected these characteristics, were studied using time-frequency analysis conducted in LabVIEW. The waves detected were either in a low frequency band, below 40 kHz, or in a high frequency band, above 60 kHz. The low frequency waves below 40 kHz were caused by hydrogen aggregation and corrosion, while the high frequency waves above 60 kHz were caused by crack initiation and propagation due to HAC. Inspection by SEM confirmed that the grains and cracks were caused by HAC via hydrogen embrittlement. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks are often to perform autonomous sensing and controlling the real world objects through the sensor nodes across the globe. Since these sensor nodes are operated by the energy of the battery that has been performed a vital role in deploying a sensor network. Hence, the battery power needs to be minimized to prolong network lifetime for healthcare applications. The monitored data transmission is very important to process in building wireless sensor networks. In order to provide efficient data transmission wireless technology standards are followed as IEEE 802.15.4 standards that provide desirable communication between end to end with optimal routes using the proposed Energy Optimization Algorithm. The proposed algorithm has been improved the data packet transmission efficiency up to 25% and also helps to prolong the life time of Wireless Sensor Networks in order to achieve the efficient data transmission for health care monitoring. [ABSTRACT FROM AUTHOR]

In this paper, the ultra-high acceleration macro-micro motion platform flexible positioning platform is taken as the research object. First, the finite element modal analysis is performed using the finite element technique, and the natural frequencies and mode shapes of the flexible positioning platform are obtained. Then, using the response surface optimization design method, the low-order natural frequency of the flexible positioning platform is increased, and its mass is decreased. Finally, the experimental modal analysis of the flexible positioning platform is carried out, and the experimental modal parameters of the flexible positioning platform are calculated. The experimental results are basically consistent with the finite element analysis results, which verify the accuracy of the finite element modal analysis. The research results are of great significance to the development of the ultra-high acceleration macro-micro motion platform. [ABSTRACT FROM AUTHOR]

To test electric devices such as household appliances, electric vehicle and other loads, there is need for emulators instead of real devices, which decreases the cost of testing. This paper presents a dynamically programmable load emulator that imitates the current–time characteristic of different types of the loads. The exact mathematical model of various types of electric loads is firstly extracted. These mathematical models are implemented by LabVIEW software. A non-ideal buck converter is used for the hardware part of the emulator, which is controlled by LabVIEW. The proposed emulator can mimic the types of loads given by LabVIEW software with great accuracy and is an example of an actual load simulator with good approximation. Manufacturers or laboratories of electric equipment can use the proposed emulator to perform their tests instead of using the actual device. This reduces the cost of tests and speeds them up so that all types of electric loads can be modeled with an emulator. In addition, because a simple power electronic converter structure is used, the proposed emulator has low complexity and low manufacturing cost. Simulation and laboratory results prove the efficiency of this emulator in making models of different types of loads. [ABSTRACT FROM AUTHOR]

The International Maritime Organization and environmental protection agencies have formulated relevant treaties to control SOX emissions from ships for air pollution; however, the current technology application has not achieved effective online detection. To adapt to the future trend of development, this research develops a marine diesel SOX online detection system based on LabVIEW. This paper first discusses the principle of SOX detection, then designs the overall scheme of marine diesel engine SOX online detection system based on LabVIEW, and finally develops the hardware and software of the detection system. The detection system includes two parts: hardware and software. The hardware is mainly composed of a gas pretreatment module, a SOX sensor module, a USB CAN analysis module and PC and so on. Two types of software are developed: the USB CAN analysis module software and the upper computer software based on LabVIEW. With the help of USB CAN analysis module software, the problem that SOX sensor module cannot communicate with PC directly by USB interface is solved effectively. The SOX online detection system of marine diesel engine based on LabVIEW reduces the development cost and cycle, and its upper computer interface is intuitive and easy to operate. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) is a technique of Electrophysiology used in a wide variety of scientific studies and applications. Inadequately, many commercial devices that are available and used worldwide for EEG monitoring are expensive that costs up to thousands of dollars. Over the past few years, because of advancements in technology, different cost-effective EEG recording devices have been made. One such device is a non-invasive single electrode commercial EEG headset called MindWave 002 (MW2), created by NeuroSky Inc that cost less than 100 USD. This work contributes in four distinct ways, first, how mental states such as a focused and relaxed can be identified based on EEG signals recorded by inexpensive MW2 is demonstrated for accurate information extraction. Second, MW2 is considered because apart from cost, the user's comfort level is enhanced due to non-invasive operation, low power consumption, portable small size, and a minimal number of detecting locations of MW2. Third, 2 situations were created to stimulate focus and relaxation states. Prior to analysis, the acquired brain signals were pre-processed to discard artefacts and noise, and band-pass filtering was performed for delta, theta, alpha, beta, and gamma wave extraction. Fourth, analysis of the shapes and nature of extracted waves was performed with power spectral density (PSD), mean amplitude values, and other parameters in LabVIEW. Finally, with comprehensive experiments, the mean values of the focused and relaxed signal EEG signals were found to be 30.23 µV and 15.330 µV respectively. Similarly, average PSD values showed an increase in theta wave value and a decrease in beta wave value related to the focus and relaxed state, respectively. We also analyzed the involuntary and intentional number of blinks recorded by the MW2 device. Our study can be used to check mental health wellness and could provide psychological treatment effects by training the mind to quickly enter a relaxed state and improve the person's ability to focus. In addition, this study can open new avenues for neurofeedback and brain control applications. [ABSTRACT FROM AUTHOR]

Automatic modulation classification finds its application in many military and civil areas. It is an integral part of cognitive radio and software defined radio technologies. In this paper, LabVIEW based Field Programmable Gate Array (FPGA) implementation of modulation classification algorithm is proposed. Any modulation scheme among BPSK, QPSK, 8PSK, 8QAM, 16QAM and 4ASK is classified by alteration of oversampling factor and further error minimization between extracted constellation and ideal constellation of considered modulation schemes. Study results reveal that the developed method detects the above mentioned modulation schemes reliably above 12 dB SNR in Additive White Gaussian Noise (AWGN) channel. Comparative analysis of the proposed method with existing methods based on higher order statistics, mel-frequency ceptral coefficients and naive based modulation classification shows an overall improvement in classification accuracy. [ABSTRACT FROM AUTHOR]

Nowadays for the privacy and security of secret data, information like audio, signature, thumb, voice, and fingerprints are the most emerging parameters and hence its authentication has received more attention due to its need for different applications. This paper develops innovative and efficient forensic software and hardware-based audio-video crypto -steganalysis model to enhance robustness and imperceptibility. All the existing diamond encoding (DE) approaches are always used to conceal one secret bit to create a diamond shape with objectionable manipulation error and hence, it is not a perfect solution for the security of hidden secret data, embedding capacity (EC), imperceptibility, and robustness. To overcome these limits, the proposed approach integrates all kinds of secret data such as Text, Image, Mp3,.Wav, Voice with many bits vertically and horizontally using the Adaptive Pixel Block Mapping Diamond Encoding Technique (APBMDET). It is used to generate a New Diamond Characteristic Value (NDCV) function which is equal to log2(4s2 + 4s + 5) - ary notations. Moreover, to enhance the security of hidden data, robustness, and imperceptibility, the forensic authentication technique and various types of attacks are applied to stego video. It is observed that original and stego audio-video does not deviate from each other. The obtained theoretical analysis and experimental results through LabVIEW and Field Programmable Gate Array (FPGA) show the effectiveness of the proposed novel technique which is used to maintain a very good recovery of both original and secret data without any distortion with larger data conceal capacity as compared to any existing techniques. [ABSTRACT FROM AUTHOR]

In order to meet the needs of operation and management of multiple stepping motors in the current Internet of things environment, this paper designed the software and hardware of the stepping motor drive management system under the control of a single-chip microcomputer based on LabVIEW, which is a graphical programming platform developed by National Instruments Corporation of the United States, and tested and verified the functions of the system. The software part of the system transmitted data between the host computer and the driver terminal based on a service cloud platform called Easy-Control, realizing the network real-time online management operation function. In the hardware design, the existing functions of the STM32F407ZGT6 single-chip microcomputer were combined with the the design of the special driver chip LV8726TA to simplify the circuit design of hardware to increase system stability. The comparison demonstrated that the software and hardware of the system were developed on the LabVIEW platform, which had the advantages of high efficiency, short development cycle, low cost, and convenient function expansion. This work provides a scheme for the design and implementation of similar systems. [ABSTRACT FROM AUTHOR]

Modern industrial products require high precision and material strength. These have a greater effect on a die and so there is accelerating die failure during mass production. Die failure damages product accuracy so it must be detected in real time. This study develops a system that detects die failure directly from the servo press machine itself. The servo motor torque data and punch time data and press slide position data are used to detect the failure status of the die and punch. SUS304 and SAE1065 steel sheets were used as test pieces. The failure mode and the effect of failure on feedback data are studied to determine the feasibility of the detection mechanism. The results show that the punch time and the torque vary with the failure mode and failure grades. For SUS304 sheets, after 1000 cycles of artificial wear, the maximum torque is 9% greater than that for a punch that is not worn. For SAE1065 sheets, the torque is 4.4% greater for the same degree of punch failure. The punch time respectively increases by 26 ms and 22 ms for SUS304 and SAE1065. Using these results, a LabVIEW DAQ module with a servo stamping machine is used to construct an online wear detection system. The LabVIEW program is tested. The test results on the LabVIEW front panel agree well with previous results. This study shows that punch/die failure can be detected accurately using this real-time failure detection system. [ABSTRACT FROM AUTHOR]

Decarbonizing the vitality area and diminishing carbon discharges to confine environmental change are the primary worries of twenty-first century. Renewable energy and efficiency interventions, supported by rapid electrification, will provide more than 90% of the reducing C O 2 emissions planned by 2050. By 2050, the transition to renewable energy will also increase the world's gross domestic product by 2.5% and the number of jobs by 0.2%.Conventional Poly crystalline roof top solar PV has an efficiency of 22.7%. Tropic of cancer passes through eight states of India, The temperature in summers varies from 40 to 50 ∘ C which results in decrease in efficiency of solar panel. So we require efficient MPPT controllers to overcome this gap. In Ghaziabad, the experimental test is performed with latitude of 28, 6692 (N) and longitude 77, 4538 (E). Solar PV simulator is designed using LabVIEW software. Effect of variations of temperature, irradiations, series resistance and shunt resistance on solar panel has been studied. Simulated results are tested using experimental setup with the help of arduino interfaced LabVIEW. [ABSTRACT FROM AUTHOR]

In this study, a new measurement system was developed to determine failures and to define the level of failure that may occur in bearings and rotor bearings or in foot of motor in single phase capacitor start motor. In the system, the vibratory operation of the motor is provided by connecting different screws on the motor's rotor mounted flywheel or by gradually removing the nut bolts of motor foot. The VB3 vibration sensor outputs were recorded to the computer with LabVIEW program at 1 ms intervals for one minute. The changing characteristics of sensor output for each experiment had more than one frequency component; therefore, Fast Fourier Transform (FFT) was performed for determining such components. When the obtained FFT graphs were analyzed, it was determined that the vibrations had harmonics of 50 Hz and its multiples; and it was observed that the frequency and amplitude values of first 5 harmonics could be used for determining the presence, type and level of failure but there was a nonlinear relation between each other. Therefore, 2 different artificial neural networks (ANN) customized separately were developed for determining the type and rate of the failure of motor. 80%, 10% and 10% of available data were reserved for training, testing and verification, respectively, and the ANN was trained. Accuracy degree for the ANN in the estimations following the training stage was calculated as R = 0.97–0.98. Furthermore, the results of ANN were compared with the results obtained using Sequential Minimal Optimization, Naive Bayes (NB) and J48 algorithms; and it was determined that the accuracy degree of ANN was higher. After this, a program was developed in MATLAB in order to work 2 ANNs with highest success together. Lastly, a system consisting of Raspberry Pi and a 7″ LCD screen, similar to the multimedia system in cars, was created to use at industrial applications. [ABSTRACT FROM AUTHOR]

In order to reduce the complexity of software and hardware design in multi-channel eddy current testing, a multi-channel real-time eddy current testing system based on lock-in amplifier technology and self- balancing technology is designed. The system uses graphical programming language platform (LabVIEW), Myrio1900 data acquisition control card and lock-in amplifier as key components. The lock-in amplifier adopts the lock-in technology to detect the amplitude and phase of the weak eddy current signal. The Myrio1900 card outputs multiple analog switch control signals and collects the amplitude component of the weak eddy current signal. The LabVIEW platform uses self-balancing technology to eliminate the imbalance of the bridge itself. The detection system realizes the real-time and reliable display of the amplitude and XY components of the 6-channel eddy current signal. Experimental results show that the designed system has a detection width of 56.00 mm at one time, and can detect artificial grooves with a covering layer of 2.90 mm. The artificial grooves have a width of 1.00 mm, a depth of 1.00 mm and a length of 50.00 mm. The system design process described in the article can be used as a reference for equipment developers and can also be used for educational purposes. [ABSTRACT FROM AUTHOR]

High Conservation Value Forests or botanical parks are critical forested areas that need to be appropriately managed and protected against fire, as they contain large concentrations of biodiversity-which includes endangered or threatened species–which are very sensitive to fire outbreaks. Thus, early detection and rapid responses are so important in combating and containing fire in these areas. As such, a lot of innovative methods are used for the containment and combating of fire. This paper proposes a stand-alone program called FireLocator created by LabVIEW that can detect in real-time the geolocation and behavior of fires by superposition of detection areas through state-of-the-art multispectral infrared detectors using wireless transmitters and mathematical modeling algorithms at a very early stage with maximum spatial resolution. In this context, four alternative models for the optimum positions of detectors in pilot control area are analyzed with Analytic Hierarchy Process (AHP) method. Experimental results demonstrated that preferred alternative model for FireLocator program has the highest percentage with 38.22% based on the AHP algorithm that validates the model used in this study. Moreover, FireLocator outperformed other fire monitoring systems and provided high spatial resolution (up to 3 m) which assisted in determining fire behavior and the geolocation of the fire in a minimum pilot area of ~ 3598.9 square meters. [ABSTRACT FROM AUTHOR]

The recognition of human daily living activities within a house represents an efficient tool to model its power consumption and is also a good indicator for monitoring the health status of the inhabitants. The problematic of activities recognition in smart homes has been extensively addressed in several studies. In this paper, we present an original interactive tool developed under LabVIEW environment with a graphical user interface allowing the modeling of the daily living activities, based on a machine learning Hidden Markov Model. After an overview of the advantage for the consideration of this model in current human activities, we examine how the associated scientific problematic can find an interest and a solution by the integration of machine learning tools. Thus, the application based on a Hidden Markov model approach, is presented and evaluated using two sets of experimental data from literature. Comparing with results obtained by other daily living activities recognition methods, we point out the very satisfactory recognition performance of the Hidden Markov Model and the likelihood of our development associated to a user-friendly graphical interface. This work opens the way to applications dedicated to the supervision of human daily living activities and / or to the management of the electrical consumption within a smart home equipped with non-intrusive sensors. [ABSTRACT FROM AUTHOR]

With the wide application of laser technology in laser processing and photoelectric detection, the measurement and display of the laser beam polarization has become an extremely important prerequisite. In this paper, we realize the laser polarization measurement tool based on the virtual instrument LabVIEW software platform. The set-up is designated to measure the Stokes parameters for an arbitrarily polarized beam, using the rotating waveplate method provided by the stepper motor, drive circuit, photodetector, and computer processing of the digitized electrical signal in the PCI expansion card. The Poincare sphere is used for the interpretation of the state of polarization (SOP) and degree of polarization (DOP). The working wavelength range is declared to be 400 – 1100 nm, the accuracy of DOP, azimuth measurement, and ellipticity are ±2%, 0.4°, and 0.4°, respectively. [ABSTRACT FROM AUTHOR]

In this paper, we propose a measurement system based on single autocorrelation technology and combined with LabVIEW software platform to realize the real-time online measurement of the femtosecond-laser pulse width. The system uses an experimental device based on the Mach–Zehnder interferometer, where the second-harmonic signal of femtosecond laser is obtained by the nonlinear effect of light and nonlinear material; the linear grayscale conversion, median filtering, and threshold segmentation are also applied to the second-harmonic signal. The image centroid, autocorrelation curve, and femtosecond-laser pulse width are obtained, using LabVIEW software. In the experiment, a seed laser source with a central wavelength of 800 nm is used as a test object, and the pulse width is measured to be equal to 261 fs. [ABSTRACT FROM AUTHOR]

Bio-impedance is the manner in which a person's body opposes the applied alternating current in a unique manner. Acquired bio-impedance data is being used for diagnosis of critical diseases condition of various systems in human body. Electrode placement on body surface to sense impedance signal for various systems is unique format for each system. This paper first part focus on design of electrical bio-impedance based acquisition system with patient identification and later part deals with visualizing, analyzing and prediction of disease condition using software tools. Impedance data from 100 patients were acquired using designed system made with surface electrodes, signal generator with variable frequency and amplitude, Microcontroller board to process acquired data. Obtained impedance values at low frequencies are a good source of cardiac related information. Data obtained from bio impedance based multi-parameter monitoring system was visualized and analyzed for the prediction of age and disease condition. The validity of this system was made using intelligent diagnosis system based on IBM SPSS computational algorithms. [ABSTRACT FROM AUTHOR]

Research in vision systems applied to manufacturing processes has increased during the last years. Nevertheless, accurate positioning systems frequently require costly investments. This article presents a new algorithm developed in LabVIEW for controlling a novel positioning system that processes images to obtain the position, which could be implemented in micromachining. With this aim, the method uses the analysis of the LEDs shown in an image projected on an LCD screen to perform an accurate positioning. The ultimate goal of this method is to get the coordinates of the images shown on the screen in order to know the movement made by the system and, in this way, be able to compensate the error. The experimental results and related analysis developed proved the accuracy and consistency in dissimilar situations. In addition, once implemented the algorithm proposed in a closed loop program, a positioning system is achieved where the error is always convergent. [ABSTRACT FROM AUTHOR]

In this paper, a new four-dimensional (4D) chaotic system which contains an active flux-controlled memristor characterized with a smooth continuous cubic nonlinearity is introduced. The objective is to obtain a 4D chaotic system which contains quadratic terms by using the memristor model which is designed as a new cubic emulator. A new chaotic circuit equation is obtained by using this emulator. The chaotic behavior of the system is observed both theoretically and graphically. The fundamental dynamics of the chaotic system are examined by using equilibrium points, phase portraits, Lyapunov exponents and bifurcation diagrams. The proportional–integral–derivative (PID) control design obtained using optimization algorithms is presented for memristor-based chaotic system. Firefly algorithm and genetic algorithm are used in PID control design for obtaining optimal PID controller gains that provides optimization between master and slave circuits. To verify system performance, this proposed PID-based chaotic circuit is used to communicate communication systems. Experimental results of this system are obtained and presented in real time. [ABSTRACT FROM AUTHOR]

The excessive Neutral-to-Earth-Voltage (NTEV) could lead to the unnecessary losses and safety hazard issue to the electrical consumer. Hence, it is a paramount need to mitigate the excessive NTEV from occurring in the system. In order to mitigate the excessive NTEV, it is very crucial to identify the source of this problem so that the proper mitigation technique can be deployed. One of the identifying approaches is by classifying the type of signal which is associated to excessive NTEV. In this paper, the propose classification technique is using Statistical-based S-transform and one-versus-one SVM (OVO-SVM) via the LabVIEW platform. In this case, the MathScript Node is utilized as an interactive interface in.m file commands with LabVIEW platform. As for SVM, different types of kernel function such as linear, gaussian, sigmoid, and polynomial have been used for performance evaluation comparison. The finding from this work indicates that OVO-SVM learning tool using Gaussian technique produced the highest classification of accuracy result. [ABSTRACT FROM AUTHOR]

Managing plastic waste is an important point of concern these days. The aim of this paper is to present the concept of reverse vending machine which is proposed to serve as a solution to the problem of pollution caused due to plastic items especially plastic bottles, which are commonly used for storing cold drink, fruit juices etc. The concept of reverse vending machine is an approach towards green engineering technology. The reverse vending machine is an integration of sensorics, LabVIEW programming along with data acquisition and pneumatics technology. This machine is a low-cost automatic machine, which crushes the plastic bottle to a reduced size, thereby, requiring less storage space for final disposal. The crushed plastic bottle consumes less energy, when it undergoes recycling process. The present article also focuses on the concept of cash-from-trash, where recycled plastic can be used to produce useful products and help in reducing greenhouse gas emissions and pollution. [ABSTRACT FROM AUTHOR]

To provide future engineers with first-hand working knowledge on the thermal behavior of materials (such as polymers, metals, ceramics and even organic substances like foodstuffs or pharmaceuticals), it is necessary to design learning experiences that develop both transferable and disciplinary skills. This can be achieved by walking them through a thorough and comprehensive process that includes the fundamental scientific concepts and elements of experimental methodology, data acquisition and analysis. With this objective in mind, we designed a program at our institution in which students and faculty are involved in the construction of portable thermal characterization devices, an activity that provides fitting scenarios for developing different of cognitive and analytical competencies and experimental skills. Through their involvement in this research-based learning, students come to understand the thermal characterization of materials. In addition, they develop data-acquisition skills, learn graphic programming and how to construct equipment for the characterization of materials. The students can achieve different levels of expertise depending on their roles and involvement with the use and development of instrumentation for evaluating the thermal properties of materials. The students who participated in the learning process of thermal analysis were able to change roles—they may have started as trainees and then went on to become either tutors or designers of instruments used for thermal characterization. [ABSTRACT FROM AUTHOR]

Real-time communications (RTC) wireless multi-channel data acquisition systems provide promising remote interactive solutions. This paper develops and implements wireless octet channels for data detection and processing. Data analysis and suitable control action are accomplished by using an Arduino UNO controller interfaced with the National Instruments (NI) LabVIEW virtual engineering toolset. A simple graphical user interface has been developed and implemented. Sensors for humidity, pulse, temperature and motion are used for reading the environmental parameters. The system can accommodate measurements of eight individual parameters at different reading speeds. In addition, high-accuracy data measurements can be obtained by using the mean values technique for the three sensors in cases such as temperature and humidity. An efficient storage technique for dated and timed data can be optimized to cancel all successive repeated measurements. Whenever the environmental parameters have been changed the system will store only the updated changes, thus providing an accurate enough description of the sensor output as well as significant reduction in required memory. Quad flags are implemented as the actuators triggering signals. The acquired data can be remotely monitored via either smartphones or computers located in the WI-FI local area network coverage area. [ABSTRACT FROM AUTHOR]

Automobile exhaust has become one of the important factors that affect atmosphere environment and cause environmental pollution. Therefore, it is necessary to do a good job of automobile exhaust detection. However, existing surveillance systems for such a poisonous gas still have some drawbacks like a limited network function, wiring complexity, a small signal coverage, poor compatibility. To overcome above disadvantages, this paper presents a master–slave wireless network monitoring system by integrating ZigBee and GSM technologies. The detected gas status from the Remote Detection Unit can be transmitted to Master Monitoring Station via self-organizing ZigBee network. The Master Monitoring Station connected with the Monitoring Server is to process the data received and thus send mobile phone real-time alarm information via GSM module. Simultaneously, the Monitoring Server can display the gas status and record it in the database online. Also, it can adjust gas warning level according to the temperature and humility of environment. Experimental results show that the proposed system is feasible in terms of stability reliability, self-organizing and wide area range, achieving the expected design goals in data acquisition and transmission, especially in simplifying equipment installation and wiring, improving system mobility and portability and remote monitoring. [ABSTRACT FROM AUTHOR]

In general, fault diagnosis and classification is concerned about monitoring a system, identifying the fault occurrence and pinpointing the exact fault location. Fault diagnosis and fault-tolerant systems are crucial for modern electrical and electronic system safety. Inverters are most frequently used DC-AC power converters. DC-AC three-phase inverter faults are very common to occur and need an effective and robust fault diagnosis system for protection and isolation. A new fault detection and classification technique is introduced in this paper. Feature extraction system considers three-phase voltage pattern plot in 3D, and the neural network are used to pinpoint the fault location. The testing process is conducted under simulation and physical environment to confirm its expediency. Proposed technique and experimental results are discussed in detail. Simulation experiment followed by practical implementation on SPWM three-phase inverter is included with results to ensure the system accuracy and reliability. [ABSTRACT FROM AUTHOR]

Miniaturized and "smart" sensors are required for research in biology, physiology, and biomechanics, and they have extremely important clinical applications for diagnostics and minimally invasive surgery. Fiber optic sensors have been proven to provide advantages compared to conventional sensors and high potential for biomechanical and biomedical applications. They are small, easy to operate, minimally invasive with low risk, more accurate, and inexpensive. This paper reports the design and modeling of a fiber optic force sensor that is capable of measuring compliance for a contact force of up to 1 N. The main objective of this study is to design and model a fiber optic sensor capable of measuring the total force applied on an object. A polydimethylsiloxane (PDMS) elastomer film with a thickness of 1.2 mm is placed between an optical fiber tip and an object, and it is used for measuring the force applied on a rigid element. The compliance of the fiber optic force sensor is measured by recording the response of PDMS elastomer films under different load conditions. We use finite element modeling results as a basis for comparing experimental data. The agreement between theoretical predictions and experimental data is reasonable and within an acceptable range. [ABSTRACT FROM AUTHOR]

Fuzzy logic controllers are readily customizable in natural language terms and can effectively deal with nonlinearities and uncertainties in control systems. This paper presents an intelligent and automated fuzzy control procedure for the refrigerant charging of refrigerators. The elements that affect the experimental charging and the optimization of the performance of refrigerators are fuzzified and used in an inference model. The objective is to represent the intelligent behavior of a human tester and ultimately make the developed model available for the use in an automated data acquisition, monitoring, and decision-making system. The proposed system is capable of determining the needed amount of refrigerant in the shortest possible time. The system automates the refrigerant charging and performance testing of parallel units. The system is built using data acquisition systems from National Instruments and programmed under LabVIEW. The developed fuzzy models, and their testing results, are evaluated according to their compatibility with the principles that govern the intelligent behavior of human experts when performing the refrigerant-charging process. In addition, comparisons of the fuzzy models with classical inference models are presented. The obtained results confirm that the proposed fuzzy controllers outperform traditional crisp controllers and provide major test time and energy savings. The paper includes thorough discussions, analysis, and evaluation. [ABSTRACT FROM AUTHOR]

The high-speed data acquisition equipment which is based on NI and LabVIEW software was used to establish the acoustic emission (AE) signal collection platform, and adopted wavelet analysis method to extract the weak of AE signal waveform from noise, aiming at the localization of AE source on plywood surface. The signal cross-correlation analysis method is used to determine the time difference between the AE signals and the different sensors,so that further calculates the average propagation speed of AE signal on the plywood surface. A kind of AE signal source localization method which is based on the cross-correlation method was proposed according to the principle of geometric positioning, and verified by means of the testing experiment which selected the lead break to simulate AE source. This paper has shown that wavelet analysis can effectively extract AE signal waveform, and the localization method based on cross-correlation principle can precisely calibrate the position of AE signal source. [ABSTRACT FROM AUTHOR]

Purpose: Protoporphyrin (PpIX) fluorescence allows discrimination of tumor and normal brain tissue during neurosurgery. A handheld fluorescence (HHF) probe can be used for spectroscopic measurement of 5-ALA-induced PpIX to enable objective detection compared to visual evaluation of fluorescence. However, current technology requires that the surgeon either views the measured values on a screen or employs an assistant to verbally relay the values. An auditory feedback system was developed and evaluated for communicating measured fluorescence intensity values directly to the surgeon. Methods: The auditory display was programmed to map the values measured by the HHF probe to the playback of tones that represented three fluorescence intensity ranges and one error signal. Ten persons with no previous knowledge of the application took part in a laboratory evaluation. After a brief training period, participants performed measurements on a tray of 96 wells of liquid fluorescence phantom and verbally stated the perceived measurement values for each well. The latency and accuracy of the participants' verbal responses were recorded. The long-term memorization of sound function was evaluated in a second set of 10 participants 2-3 and 7-12 days after training. Results: The participants identified the played tone accurately for 98% of measurements after training. The median response time to verbally identify the played tones was 2 pulses. No correlation was found between the latency and accuracy of the responses, and no significant correlation with the musical proficiency of the participants was observed on the function responses. Responses for the memory test were 100% accurate. Conclusion: The employed auditory display was shown to be intuitive, easy to learn and remember, fast to recognize, and accurate in providing users with measurements of fluorescence intensity or error signal. The results of this work establish a basis for implementing and further evaluating auditory displays in clinical scenarios involving fluorescence guidance and other areas for which categorized auditory display could be useful. [ABSTRACT FROM AUTHOR]

The objective of the paper is to represent the real-time framework in multiprocessor environment task scheduling process by examining the novel algorithm advanced PSO. The advanced PSO algorithm has the metaphor as the basis to facilitate social interaction, which makes a search on space by making adjustments to the trajectories of individual vectors, referred to 'particles' as they are considered as the points that move within the multidimensional search space. This algorithm will reduce the turn-around time, burst time and waiting time for multiprocessor task scheduling, when compared to existing algorithm like first come first served algorithm, shortest job first algorithm and round robin scheduling algorithm. This proposed algorithm is developed and making hardware for tank level water control for single input single output tank system and two input two output tank system. LABVIEW software is used to implement the real-time algorithm in hardware and software. The time taken for searching best position for particles will be executed and compare with all algorithms using bar chart will be given in result. [ABSTRACT FROM AUTHOR]

Thermal metrology laboratory at the National Institute of Standards (NIS-Egypt) has been working for the last four years to realize the International Temperature Scale 1990 in low-temperature ranges. It is required to develop a temperature controlling system to regulate the temperature precisely. Two mathematical algorithm techniques are considered to stabilize the temperature of an evacuated copper cylinder that is located inside an isolated calorimeter, and the normal PI and modified fractional PI controls have been designed and developed based on Laboratory Virtual Instrument for Engineering Workbench (LabVIEW) software. The new improved fractional PI controlling mechanism has showed stability better than 3 ± 1 mK in temperature and 45 ± 1 min in time performances. The estimated uncertainty related to the measurements has been improved up to ±0.32 mK. [ABSTRACT FROM AUTHOR]

A LabVIEW-based software for the control of the fully automated multi-sequential flow injection analysis Lab-on-Valve (MSFIA-LOV) platform AutoRAD performing radiochemical analysis is described. The analytical platform interfaces an Arduino-based device triggering multiple detectors providing a flexible and fit for purpose choice of detection systems. The different analytical devices are interfaced to the PC running LabVIEWVI software using USB and RS232 interfaces, both for sending commands and receiving confirmation or error responses. The AUTORAD platform has been successfully applied for the chemical separation and determination of Sr, an important fission product pertinent to nuclear waste. [ABSTRACT FROM AUTHOR]

Recently, the development of confidentiality and authenticity ensured by image encryption has been one of the key advancements in the field of secured wireless communication. The proposed work focuses on providing confusion, diffusion and permutation inherently in the system. The input grayscale image is shuffled by employing the Henon algorithm and subsequently separated into 8 bit planes. With the aid of a secret key of 256 bits, chaotic sequences are generated for each bit plane. Later, the logistic map is adapted on the chaotic sequences to obtain the scrambled image. Furthermore, this image is shuffled with Zaslavskii and Hilbert Space Filling Curve algorithms, which establishes the confusion stage. To incorporate the diffusion stage, a self-invertible matrix is generated by a latin square image cipher and a secret key. This matrix and the scrambled image underwent the Hill cipher to build the encrypted image followed by a row-column transformation to ensure multifold security. The proposed compound activities of encryption are successfully implemented on the laboratory virtual instrumentation engineering workbench 2013 platform. Noticeably, the established processes of image encryption are tested in the universal software radio peripheral environment and transceived via an additive white Gaussian noise (AWGN) channel. More specifically, the influence of natural and unnatural (cropping attack) noise on the characteristics of the encrypted image while sharing through AWGN channel has been investigated. Security analysis is performed by computing the unified average changing intensity, number of pixels change rate, correlation value, large key space to defy brute force attack, strong key sensitivity and uniform gray value distribution on encryption. [ABSTRACT FROM AUTHOR]

In this paper, bit error performance evaluation of chaotic sequences is presented. Performance of chaotic sequences is evaluated on multiple access spread spectrum system model for USRP software defined radio. LabVIEW is used to perform numerical simulations and bit error rate analysis. Chaotic sequences of different lengths are generated using one-dimensional, two-dimensional, and three-dimensional maps. It is expected that sequences generated from complex maps will have better multiple access performance. Performance of chaotic sequences is evaluated against orthogonal sequences in multiple access scenario. Using Golay figure of merit and Pearson correlation coefficient, analysis of correlation properties and a comparison is performed on orthogonal and chaotic sequences for correlation properties comparison. The results show that chaotic sequences from two-dimensional maps have lower bit error rate than orthogonal and other chaotic sequences. Comparison of correlation properties shows that sequences with a low figure of merit and low Pearson coefficient have lower bit error rate. Those results can be used to generate chaotic sequences with desired correlation properties. [ABSTRACT FROM AUTHOR]

The choice of the appropriate metallizing layer for high-temperature thermoelectric (TE) materials is a tricky task and poses varied challenges to researchers. In this work, a n type TiAl metallizing layer (90% Ti with 10% Al by weight with a copper foil) is proposed for a $$\hbox {Yb}_{0.2}\hbox {Co}_{4}\hbox {Sb}_{12}$$ skutterudite (SK) TE material coupled with a standard ' p type' SK base of $$\hbox {Nd}_{0.45}\hbox {Ce}_{0.45}\hbox {Fe}_{3.5}\hbox {Co}_{0.5}\hbox {Sb}_{12}$$ with a 60:12:28% Fe:Ni:Cr metallizing layer. The n type and p type nanostructured SK powders are sintered at high temperatures and pressures in a DC hot press from which a TE device is assembled using diced, polished and property characterized TE legs (high figure of merit zT of 1.4 for n type and 1.2 for p type, respectively). The device is evaluated for functional degradation with repeated cycling to 500°C hot side (HS) and 50°C cold side (CS) temperatures in a specially designed high-vacuum test rig with key TE properties like peak power, open circuit voltage, and material internal resistance continuously recorded over each cycle. The device shows stable performance with <7% drop in TE harvested power over ~2500 thermal cycles. With the industry benchmark for evaluating TE device performance being around 1000 thermal cycles (<10% drop in TE power over time), the study indicates stable performance of the n type TiAl metallizing layer over the device lifetime. [ABSTRACT FROM AUTHOR]

In this paper, a digital vector impedance half-bridge meter based on virtual instruments is designed, implemented and tested. Here, not only the accuracy of the magnitude of the impedance is considered but, more importantly, its phase measurement accuracy. The meter utilizes a four-voltmeter method which is a basic modification of the well-known three-voltmeter method. The half-bridge is constructed with commercially available data acquisition (DAQ) board in the form of peripheral control interconnect cards incorporated in personal computers. The DAQ board is used only to acquire the voltages instead of using four separate voltmeters, while the excitation signal is produced by an integrated circuit signal generator. The main error in this method arises from the error in measuring the voltage values. Since the resolution of the DAQ board used here is 16 bits; expect that absolute errors due to A/D conversion will be around 0.305 mV for ±10 V range. Detailed error analysis of the method is included in the context of the paper. It is found that the errors in the impedance magnitude is fairly small and relatively less sensitive on the resolution of the voltmeters because of the relative measurements in the half bridge with a precise reference resistance. The original three voltmeter vector impedance meter has relatively large error in the phase especially in the small phase angles. To decrease the phase error to an acceptable range, one has to increase the resolution of the voltmeter appreciably, which makes them expensive. The other solution to reduce the error in the phase angle with less cost is to add a fourth voltmeter which acquires directly the small phase angles. In this case, it is found that, a much lower resolution voltmeter can be utilized while achieving an acceptable measurement accuracy of the impedance. [ABSTRACT FROM AUTHOR]

We propose an integrated curriculum to establish essential abilities of computer programming for the freshmen of a physics department. The implementation of the graphical-based interfaces from Scratch to LabVIEW then to LabVIEW for Arduino in the curriculum 'Computer-Assisted Instrumentation in the Design of Physics Laboratories' brings rigorous algorithm and syntax protocols together with imagination, communication, scientific applications and experimental innovation. The effectiveness of the curriculum was evaluated via statistical analysis of questionnaires, interview responses, the increase in student numbers majoring in physics, and performance in a competition. The results provide quantitative support that the curriculum remove huge barriers to programming which occur in text-based environments, helped students gain knowledge of programming and instrumentation, and increased the students' confidence and motivation to learn physics and computer languages. [ABSTRACT FROM AUTHOR]

This paper illustrates the wavelet-based feature extraction for emotion assessment using electroencephalogram (EEG) signal through graphical coding design. Two-dimensional (valence-arousal) emotion model was studied. Different emotions (happy, joy, melancholy, and disgust) were studied for assessment. These emotions were stimulated by video clips. EEG signals obtained from four subjects were decomposed into five frequency bands (gamma, beta, alpha, theta, and delta) using 'db5' wavelet function. Relative features were calculated to obtain further information. Impact of the emotions according to valence value was observed to be optimal on power spectral density of gamma band. The main objective of this work is not only to investigate the influence of the emotions on different frequency bands but also to overcome the difficulties in the text-based program. This work offers an alternative approach for emotion evaluation through EEG processing. There are a number of methods for emotion recognition such as wavelet transform-based, Fourier transform-based, and Hilbert-Huang transform-based methods. However, the majority of these methods have been applied with the text-based programming languages. In this study, we proposed and implemented an experimental feature extraction with graphics-based language, which provides great convenience in bioelectrical signal processing. [ABSTRACT FROM AUTHOR]

This paper relates to development of a novel generic transceiver module for software defined radio (SDR) built using graphical user interface language LabVIEW. The main advantage of the module is that it is built entirely on the user input interface where the users get the flexibility to change any parameters according to their needs and the generic module supports there digital modulation schemes with two forward error correction coding techniques where the user has the flexibility to decide about the same. The SDR module has been fully implemented and it has the ability to navigate over a wide range of frequencies with programmable channel bandwidth and modulation characteristics. The module has been tested on real time data, text and image transmissions using the test jig for Wi-Fi module. With the help of the Wi-Fi hardware test jig it has been proved that the signal transmitted has been recovered with very low probability of error at the destination. A plot between bit error rate (BER) and the signal to noise ratio shows that a low BER has been achieved using this design. The novelty of this design is that the module auto identifies the best available digital multistate modulation scheme i.e. M-ary quadrature amplitude modulation, M-ary frequency-shift keying, M-ary phase-shift keying for the selected input. [ABSTRACT FROM AUTHOR]

This paper focus on discussion and design of the LabVIEW-based radiation monitoring system of the Experimental Advanced Superconducting Tokamak (EAST). This monitoring system based on LabVIEW software can get and monitor the environment's real-time nuclear radiation around EAST. EAST is a fully superconducting Tokamak, it has played an important role of nuclear fusion research and plasma physics experiments. During EAST's pulse discharge, there will be some radiation produced in the EAST's hall and environment, so radiation monitoring and control are necessary. Firstly this paper reviews EAST and radiation. Then this paper briefly presents the structure of the monitoring system. Thirdly, the design of the monitoring system based on LabVIEW is presented. The LabVIEW-based radiation monitoring system mainly includes: the definition of serial port, the definition of data request, the definition of data rewrite, the definition of data cutting, the definition of data saving and displaying. This monitoring system can work well. [ABSTRACT FROM AUTHOR]