Miracle-dz/UniFAR-FTUs huggingface dataset:
True RMS voltmeter calibration by reference square waveform signal and algorithm for measurement and processing of results

An approach for calibrating of the AC voltage of True RMS voltmeters is proposed, using reference square waveform signals instead of the traditionally used harmonic (sinusoidal) signal. A computer-based automation system and an algorithm for calibration of True RMS voltmeters have been implemented.The algorithm performs the sequence of operations for control of the reference calibrator Metrix CX1651 and the calibrated True RMS voltmeter PICOTEST M3500A, setting reference voltage values from the calibrator, performing multiple measurements at the calibration point, extracting measured results and extracting the measured results to obtain an estimate of the actual value of the measured voltage values and an estimate of the extended uncertainty at the calibration point. Based on the results of calibrations, the two approaches were analyzed and compared, which proved their equivalence.
EFFECT OF THERMAL GRADIENT ON VIBRATION OF NON- HOMOGENEOUS SQUARE PLATE WITH EXPONENTIALLY VARYING THICKNESS

Vibrations of plate and plate type structures made up of composite materials have a significant role in various industrial mechanical structures, aerospace industries and other engineering applications. The main aim of the present paper is to study the two dimensional thermal effect on the vibration of non-homogeneous square plate of variable thickness having clamped boundary. It is assumed that temperature varies bi-parabolic i.e. parabolic in x-direction & parabolic in y-direction and thickness is considered to vary exponentially in x direction. Also, density is taken as the function of “x” due to non-homogeneity present in the plate’s material. Rayleigh Ritz technique is used to calculate the natural frequency for both the modes of vibration for the various values of taper parameter, non-homogeneity constant and thermal gradient. All the calculations are carried out for an alloy of Aluminum, Duralumin, by using mathematica.
Three-dimensional kinematic and dynamic analysis of the crawl tumble turn performance: the expertise effect

1.66 ^ 0.05 1.76 ^ 0.04 ,0.0001 VOut (m/s) 1.68 ^ 0.12 2.01 ^ 0.19 ,0.001 A (years) 15.9 ^ 1.3 21.9 ^ 4.1 ,0.001 AT (s) 1.23 ^ 0.08 1.10 ^ 0.07 0.001 BM (kg) 55.2 ^ 5.6 63.5 ^ 5.9 0.004 VG (m/s) 2.31 ^ 0.22 2.55 ^ 0.15 0.011 V1mR (m/s) 21.57 ^ 0.13 21.73 ^ 0.13 0.013 UD (m) 2.29 ^ 0.33 2.62 ^ 0.35 0.046 Notes: Variables ranked by increasing p-value. Only variables for which p , 0.05 were reported.
Analysis of the Effects of Smoking Desire and Self-Efficacy on Nicotine Use Levels During the Covid-19 Pandemic Period Using Machine Learning Techniques

In March 2020, when the first COVID-19 case was reported in Turkey, some regulations as minimum physical contact, staying at home, closed schools, and unstable working systems became a part of our lives. With these accusatory changes in lifestyle, it has become difficult for people to cope with this period. In this study, the effect of self-efficacy and desire to smoke on nicotine addiction during the COVID-19 pandemic was analyzed and classified by machine learning methods. Among the classification algorithms used, classification was made with a random forest classifier with an accuracy of 71.4%.
AlN MEMS Resonator with High Quality Factor

This paper reports a novel design on the notched supports coupled to the end of tethers to enhance the quality factor (Q factor) of the Lamb wave Aluminum Nitride (AlN) micro-electro-mechanical systems (MEMS) resonators. The anchor loss was reduced with the optimal notched support. Compared with the conventional flat-edge resonators, the Q factors of the fabricated resonators were improved by 1.42 times and 1.20 times at frequencies of 664 MHz and 839 MHz, respectively. This proposed approach can be adapted to various piezoelectric resonators which suffered from severe anchor loss induced by conventional tether designs.
Let's consider Moore's law in its entirety

Gordon Moore's predictions refer, in addition to the resolution at which we can make the devices, also to the size of the chips and to the "circuit cleverness". Considering Moore's law in all its aspects offers a more complex perspective on the current evolution of the field of integrated circuits. Computers, as a General-Purpose Technology, tend to be replaced by various types of accelerators. A possible solution that we present is based on parallelism supported by the recursive abstract model that we propose starting from the model of partially recursive functions of Stephen Kleene.
GSK-RL: Adaptive Gaining-sharing Knowledge algorithm using Reinforcement Learning

Meta-heuristics and nature inspired algorithms have been prominent solvers for highly complex, nonlinear and hard optimization problems. The Gaining-Sharing Knowledge algorithm (GSK) is a recently proposed nature-inspired algorithm, inspired by human and their tendency towards growth and gaining and sharing knowledge with others. The GSK algorithm have been applied to different optimization problems and proved robustness compared to other nature-inspired algorithms. The GSK algorithm has two main control parameters kfand kr which controls how much individuals gain and share knowledge with their common society and circles or what they inherit from their parents. GSK has no control parameter adaptation scheme, the kf and kr are fixed for all individuals. In this paper we introduce an adaptation technique for the GSK algorithm by learning those parameters during search procedure of the algorithm. The new algorithm is dubbed as GSK-RL. The parameter controller in GSK-RL is a neural network trained using actor critic methods for reinforcement learning. The GSK-RL is compared against original GSK algorithm with its default parameters on CEC 2017 test suite functions for dimensions 10 and 30. The GSK-RL performed well on 10 dimensional problems but the performance started to degrade on 30 dimensional problems and it showed unstable behaviour on some functions that the controller has never been trained on before. This paper concludes that neither the state of the search algorithm as described for the RL model nor the reward function has a critical role in designing an RL-based controller for parameters of the GSK, however the training functions and the collected trajectories are the most important factor in designing such a controller.
Reliability of Unmanned Aerial Vehicles for the groups size estimation of Grampus griseus (Cuvier, 1812) in the Gulf of Taranto (Northern Ionian Sea, Central-eastern Mediterranean Sea)

In the last decade, Unmanned Aerial Vehicles (UAVs) were applied in monitoring studies addressing to marine and terrestrial wildlife for their multiple advantages. Due to their operational flexibility and low cost, UAVs have been applied in studies aimed at studying behavior, estimating group size and abundance of species as well as at measuring the individuals through photogrammetry methods. In this work, numerical estimates of group size of Risso’s dolphin sighted in the Gulf of Taranto from UAVs video-analysis were compared from those recorded by MMO on board of a research vessel. Data were collected from April 2018 to September 2020 for a total of 109:58 minutes of recording. Aerial shots together traditional survey methods allowed a more thorough analysis of the number of individuals observed, offering a better estimates overview, with the possibility of viewing videos several times and taking screenshots. Using UAVs could provide more accurate estimates on Risso’s dolphin population. In conclusion, given the efficiency such systems found in this work, the use of UAV could be instrumental in broadening perspectives on marine mammal studies.
Enhanced Image Quality Assessment Based on Halftoning Metrics

The digital halftoning is widely adopted in printing applications to obtain a high-quality printing output with optimal ink usage. The technique comprises of transforming a continuous tone grayscale image into its approximate binary image. On the other hand, image quality assessment deals with estimating the perceptual quality of the degraded image. The paper deals with exploitation of ordered dithering technique of the halftoning, to improve the performance of the existing image quality indices. The widely used full reference image quality metrics such as Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) are considered for this paper. The main objective aims to improvise the correlation coefficient between the widely used IQM and Human Visual System (HVS). Moreover, the computation demand of the existing indices is also reduced significantly. The well-known LIVE image quality database is used to validate the performance of the proposed approach. To perform correlation analysis, Pearson, Spearman and Kendall correlation coefficients are used. From experimental analysis, it can be validated that the proposed IQM performs with improved accuracy and less computational demand.
AIoT-based Audio Recognition System for Smart Home Applications

In this paper, we design an audio recognition system to detect events of lighters sound, which names Audio Recognition System (ARS). ARS is composed of AIOT device (i.e. Raspberry Pi), deep-learning-based analytics, and real-time alarming advisory (e.g. Line Notify). We conduct experiments with 8,000 observations. The result shows ARS achieves 97% accuracy in a quiet place and 94% accuracy in a noisy environment.
Artificial Intelligence Based Algorithms for Driver Distraction Detection: A Review

World Health Organization gave a report global road safety. Road accidents have turned to be more dangerous and they became the eighth most important reason for death. Out of this one fifth of them are caused due to the negligence of the driver. We discuss about the different types of algorithms which are more efficient based on the features that are detected by the algorithms. Comparison of algorithms is done to know the algorithms which work well for the specific set features detection. In driver distraction, there are many features like pupil diameter, hands location, head location etc., which are needed to be detected and predict the type of distraction. Each algorithm uses different kind of Artificial Intelligence models and does the predictions based on the features.
Compact CPW-fed monopole antenna for 5 GHz wireless application

A compact and simple coplanar waveguide (CPW)-fed monopole antenna for 5 GHz wireless communication is proposed. By properly adjusting the lengths of both the monopole strip and the inverted L-shaped ground, the designed antenna, with, including ground plane, only 9/spl times/9.5 mm/sup 2/, can operate at the desired 5.2 or 5.8 GHz band. The electromagnetic coupling effect between the radiating strip and the ground on excitation of the resonant mode has been studied. Prototypes of the proposed antenna have been constructed and experimentally studied. Measured results show a -10 dB impedance bandwidth and an average antenna gain of 400 MHz and >6 dBi, respectively.
Miniaturized 90 degree hybrid coupler using high dielectric substrate for QPSK modulator

This paper describes miniaturized 90 degree hybrid coupler using edge-coupled microstriplines. A high dielectric constant substrate (K=38) and high-density coupled-line configuration are adopted to realize small chip size. A conventional meandered coupled-line type and a new spiral coupled-line type were discussed for a high-density configuration. A bandwidth from 1.8 GHz to 3.6 GHz with /spl plusmn/0.5 dB power dividing balance and 90/spl plusmn/3 degrees phase difference were achieved with a chip size of 1.5/spl times/1.5 mm.
Microfluidic device with integrated temperature control unit for hydrogel actuation

A microfluidic device, with a temperature control unit to study the behaviour of temperature sensitive hydrogel, has been designed, simulated and fabricated. The system consists of a PDMS (polydimethylsiloxane) microchannel sealed on a Pyrex substrate with microfabricated titanium electrodes for heating and sensing elements. A thermal insulating layer in-between the electrodes and the substrate was found to increase the heat transfer to the fluid and decrease the lateral heat propagation. The temperature profile and the heat distribution in the system were investigated using the commercial software package CFD-ACE+. The device was electrically and thermally characterised. Such a system, biocompatible and re-usable, could be a potential candidate for biomedical applications such as DNA amplification and protein synthesis.
Collaborative discovery and enrichment of business process models using a semantification approach

Business process discovery (BPD) is a crucial step for analyzing an enterprise’s current business. Challenges in business process discovery include the complexity of the enterprise and the interactions among its units and stakeholders; the inaccuracy and incompleteness of available business information and business modelling languages; and the dynamic of businesses in the enterprise. In this paper we present a collaborative solution for BPD grounded in the concepts introduced by DEMO business transaction patterns theory and in a well-known Business Process Management methodology. BPD derives the process happy-flow concerning the most usual situations. Additionally, a happy-flow enrichment allows adding variability to the model, namely the declinations, rejections, and revocations. The solution was developed and deployed in an industrial environment offering a full BPMN model that could be executable targeting a BPMN compatible engine. It helps to create agreements between every participant in process discovery and deliver more complete BPMN models in an efficient and systematic way. This collaborative solution was tested using a real proof of concept in the context of banking. In order to assess the performance of the system a batch of experiments was conducted. Comparing this solution with related work we found no other work containing similar features to ours.
Charge pump power-factor-correction technologies. I. Concept and principle

Charge pump power-factor-correction (CPPFC) technologies, including voltage-source (VS) CPPFC, current-source (CS) CPPFC, and continuous input current (CIC) CPPFC, are presented in this paper. The charge pump concept for achieving PFC and its unity power factor conditions are derived and analyzed, The developed CPPFC techniques use a capacitor to achieve PFC function.
Wideband, high-gain, variable time-delay techniques for array antennae

The purpose of this paper is to present two improved techniques for obtaining a wideband, high-gain, non-dispersive, variable time-delay device to steer array antennae. The first time-delay technique utilizes two wideband helix structures separated by a cylindrical drift tube to obtain a variable delay of 20 ns or more with a gain of 20 to 30 dB. An electron beam passes through the two helices and drift region. Signal energy coupled on to the beam at the input helix is decoupled at the output helix. A variable delay is obtained by controlling the beam velocity through the drift region by varying the drift tube potential. Gain variation is minimized by maintaining constant beam velocity through the helices. The gain of the device is proportional to output helix length. The second method for obtaining a variable time-delay is realized by switching different time-delay elements into the signal path. Such a technique is controlled digitally and is referred to as a digital delay line. In this technique each switch is replaced by a wideband amplifier. It is the bandwidth of these amplifiers that determines the system bandwidth (200 to 800 Mc/s). Each bit is capable of producing 12 dB gain. The amplifiers can be easily gated on or off.
Objective speech intelligibility measurement on the basis of natural speech in combination with perceptual modeling

The relation between subjective and objective speech intelligibility measurements is researched. For a large series of speech degradations, noise, linear and nonlinear distortions (speech codecs), intelligibility tests were carried out using short CVC words. In the subjective domain the percentage correctly identified words is taken as the intelligibility score for a certain type of degradation. In the objective domain ITU-T Recommendation P.862 is used as the starting point to develop a perceptual model that allows predicting the perceived intelligibility of a speech fragment.
Robotic Grasping Strategies Based on Classification of Orientation State of Objects

Robotic grasping has been studied for years, but still has lots of room for improvement due to its requirement of sufficient robustness to achieve a high success rate. This paper proposes grasping strategies that produce reliable grasping poses without human labeling. All the training and testing processes are performed in a simulation environment. We then further evaluate the quality of the grasping strategy produced by the system. High success rate result shows its potential of application in industrial production lines, helping the robot arms perform high-quality grasping with picking or similar tasks.
An analogue model of the memristor

The paper presents a working electrical scheme modeling the memristor. The scheme allows experimenting with the model under various testing signals. The user can use it to verify the theoretical presumptions about the memristor properties. Examples of several typical measurements are shown. Copyright © 2010 John Wiley & Sons, Ltd.
Impact of Investor Sentiment on Stock Returns Using Fine-tune BERT

In this study, we explore the impact of investor sentiment on stock returns. We fine-tune the BERT language model to capture investor sentiment from messages posted on the social media platform StockTwits. Apple Inc. (AAPL) stock is selected in this investigation because it has more significance in statistics based on its tremendous messages on StockTwits. A linear regression model is constructed to analyze the relationship between investor sentiment and stock returns. The experimental results show that there is a positive correlation between stock returns and investor sentiment. The investor sentiment can impact the Apple Inc. stock return.
A study on the variation of effective CTE of printed circuit boards through a validated comparison between strain gages and Moire/spl acute/ interferometry

The effective coefficient of thermal expansion (CTE) of printed circuit boards (PCBs) have a great deal of influence on the reliability of solder joints in microelectronic packages. In this paper we carryout a systematic characterization of nineteen circuit board samples using strain gages, further validated by moire/spl acute/ interferometry, to understand the impact of CTE variation on the reliability of solder joints. It is shown that the measured effective coefficient of thermal expansion varied in a wide range by as much as 5 PPM about the commonly used value of 17 PPM. This is shown to cause a significant reliability impact for a representative plastic ball grid array package assembly. The comparison between strain gage and moire/spl acute/ interferometry showed good overall correlation, but differed from each other by as much as 2.73 parts per million (PPM). The possible sources of error in each technique are identified and discussed.
Multi-trophic species interactions in a marine bioremediation model assessment

Through the diversification of multitrophic communities it is possible to obtain in mariculture stable and sustainable systems useful for biomass production. This study on the synergistic interactions between the sponge Sarcotragus spinosulus (Porifera, Dictyoceratida), the macroalga Chaetomorpha linum (Chlorophyta, Cladophorales) and the European sea bass Dicentrarchus labrax (Chordata, Actinopterygii), provides the basis for the development and optimization of a lab-scale multi-trophic model for biomasses production and bioremediation.
Effect of Monotonic Filtering on Graph Collection Dynamics

Distributed data collection is a fundamental task in open systems. In such networks, data is aggregated across a network to produce a single aggregated result at a source device. Though self-stabilizing, algorithms performing data collection can produce large overestimates of aggregates in the transient phase. For example, in [1] we demonstrated that in a line graph, a switch of sources after initial stabilization may produce overestimates that are quadratic in the network diameter. We also proposed monotonic filtering as a strategy for removing such large overestimates. Monotonic filtering prevents the transfer of data from device $A$ to device $B$ unless the distance estimate at $A$ is more than that at $B$ at the previous iteration. For a line graph, [1] shows that monotonic filtering prevents quadratic overestimates. This paper analyzes monotonic filtering for an arbitrary graph topology, showing that for an $N$ device network, the largest overestimate after switching sources is at most $2N$.
Hyperparameter Optimization for SOC Estimation by LSTM with Internal Resistance

State of charge (SOC) is an important indicator to describe battery performance. However, most of the training input data for SOC estimation using deep learning algorithm do not consider the battery internal resistance. In this paper, a method for SOC estimation of lithium-ion batteries based on the LSTM neural network is proposed, and the battery voltage, current, temperature and internal resistance are taken as the training input data of the LSTM model. When the correlation function is determined, the influence of different hyperparameters of the LSTM model with battery internal resistance as the training data on the SOC estimation results is analyzed and compared to determine the optimal setting of the hyperparameters of the model. The experimental results show that the model with the battery resistance as the training input data has higher accuracy. On this basis, the LSTM model with appropriate hyperparameters has the advantages of high accuracy and fast convergence in SOC estimation.
A 131 dBΩ 146 MHz Transimpedance Amplifier for 20 MHz Capacitive MEMS Beam Resonator1

This paper proposes an ultra-high-gain wideband transimpedance amplifier (TIA) for a 20 MHz capacitive MEMS beam resonator. The TIA consists of a common-gate amplifier, a wideband Cherry-Hooper amplifier, and buffers. The common-gate amplifier uses a self-biased inverter to expand the bandwidth. The output transistors in the Cherry-Hooper amplifier are tunable to combat the process variation. The output buffer employs a small load resistor to guarantee wideband and sets switches to cut off the parasitic from the test buffer. Implemented in the 0.35 μm CMOS process, the TIA shows a simulated gain of 131 dBΩ, a bandwidth of 146 MHz, and an input-referred current noise of 16.3 pA/√Hz. The proposed TIA works well with the resonator, and oscillation builds up within 50 μs with a swing of 2.9 Vp-p. The simulated phase noise is -108.6 dBc/Hz at 10 kHz offset and -112.4 dBc/Hz at 100 kHz. The power consumption is 15 mW under 3.3 V supply. This work provides a reference for V/UHF resonator driving and voltage-controlled MEMS oscillators.