Miracle-dz/UniFAR-FTUs huggingface dataset:
Electric Arc Furnace Power Quality Analysis Based on a Stochastic Arc Model

Electric arc furnaces (EAF) are commonly used in steel industry. Unfortunately, nonlinear characteristic of the arc furnace and its stochastic behavior bring about many problems, e.g. voltage flicker and waveform distortions. The AC furnaces are usually modelled using combined models which divide the phenomenon taking place in real objects into a deterministic and a stochastic or chaotic parts. The former can be expressed by a nonlinear differential equations. The paper goal was to take advantage of the earlier results, i.e. a closed form of the solution to one of the most popular nonlinear differential equations used for the AC electric arc modelling, and start research towards a complete EAC model which covers not only the deterministic but also the time-varying nature of the arc waveforms. Such a model can be helpful, among others, in solution to power quality problems in EAF supplying networks. Theoretical considerations have been illustrated by some examples and the results have been compared with measurements.
Application of Iterative Machine Learning for Output Tracking With Magnetic Soft Actuators

This paper presents experimental results of output tracking for soft magnetic actuators using iterative machine learning (IML) to estimate the model and its uncertainty. A challenge is that parameters of dynamic-response models of such soft actuators are sensitive to the operating point. To overcome this challenge and improve the tracking performance, a complex-valued Gaussian process regression (CGPR) is used to estimate a system inverse model; additionally, the CGPR approach provides an uncertainty measure, which is used to design the frequency-dependent iteration gain to ensure convergence. This approach leads to convergence even when data near resonance (where models tend to be sensitive) is not available. Moreover, a method to improve the model estimation is proposed, in which the initial training signal is augmented with additional frequency content to increase the input and output signal size compared to the noise. Using this augmented approach, the IML approach results in a <inline-formula> <tex-math notation="LaTeX">${\text{95}\%}$</tex-math></inline-formula> reduction in the maximum tracking error compared to using the dc gain alone. The final maximum tracking error is <inline-formula><tex-math notation="LaTeX"> ${\text{1.8}\%}$</tex-math></inline-formula>, which is near the sensor resolution limit.
Aldosterone and Mineralocorticoid Receptor System in Cardiovascular Physiology and Pathophysiology

The mineralocorticoid hormone aldosterone (Aldo) has been intensively studied for its ability to influence both the physiology and pathophysiology of the cardiovascular system. Indeed, although research on Aldo actions for decades has mainly focused on its effects in the kidney, several lines of evidence have now demonstrated that this hormone exerts disparate extrarenal adverse effects, especially in the circulatory system. Accordingly, in the last lusters, a number of studies in preclinical models (in vitro and in vivo) and in humans have established that Aldo, following the interaction with its receptor—the mineralocorticoid receptor (MR)—is able to activate specific intracellular genomic and nongenomic pathways, thus regulating the homeostasis of the cardiovascular system. Importantly, through this mechanism of action, this hormone becomes a crucial regulator of the function and growth of different types of cells, including fibroblasts, cardiomyocytes, and vascular cells. For this main reason, it is plausible that when Aldo is present at high levels in the blood, it profoundly modifies the physiology of these cells, therefore being at the foundation of several cardiovascular disorders, such as heart failure (HF). On these grounds, in this review, we will provide an updated account on the current knowledge concerning Aldo activity in the cardiovascular system and the most recent preclinical studies and clinical trials designed to test better approaches able to counter the hyperactivity of the Aldo/MR signaling pathway in the setting of cardiovascular diseases.
Research on Four-Wheeled Indoor Mobile Robot SLAM Based on RBPF Algorithm

Simultaneous localization and mapping (SLAM) of mobile robots in indoor unknown environments is one of the focuses of present robot researching. In order to realize indoor mapping, it proposes to that the four-wheeled mobile robot equipped with laser radar implements SLAM with RBPF algorithm. It can locate the robot in the process of indoor movement, and then the laser radar scans out the position obstacles and updates in real time, achieving the indoor mapping. The experiments are showing that the method proposed here can construct accurate map relatively and achieve the desired results.
Implementing a Neural Processor for Accelerating Deep Learning

The project involves the design and development of a neural processor architecture for accelerating deep learning. Several companies are investing in hardware acceleration as the interest in deep learning is growing. A neural network is a combination of neurons that apply weights to a set of inputs and evaluate the output based on a nonlinear function. Deep neural nets have several such nodes and evaluating the state of each of these nodes is a very compute intensive task. Currently a combination of CPUs and GPUs are used for training/inference of these neural nets, but these processors are not designated for such heavy workloads. Hence there is a need for designing a specialized hardware this application.
Phase I Monitoring of Spatial Surface Data from 3D Printing

ABSTRACT In recent years, 3D printing gets more and more popular in manufacturing industries. Quality control of 3D printing products thus becomes an important research problem. However, this problem is challenging due to the facts that (i) the surface of a product from 3D printing can have arbitrary shape, even when the 3D printing process is in-control, (ii) surface observations of the product obtained from a laser scanner may not have regularly spaced locations, and (iii) the overall geometric positions of 3D printing products might be all different, making proper comparison among different products difficult. In this article, we propose a Phase I control chart for monitoring products from 3D printing that addresses all these challenges. Numerical studies show that it works well in practice.
We still trust in Google, but less than 10 years ago: an eye-tracking study

Introduction. The purpose of this study is to replicate a study from 2007, which found that student users trust in Google's ability to rank results more than in their own relevance judgements. Method. In a between-subjects experiment using eye-tracking methodology, participants (n=25) worked on search tasks where the results ranking on search engine results pages had been manipulated. Analysis. The data were analysed using descriptive statistics, analysis of variance (ANOVA), t-tests and mixed model analyses with the statistical program SPSS. Results. This study confirms major results from the study we replicated, but finds one important difference: although the viewing behaviour was influenced more by the position than by the relevance of a snippet, the crucial factor for a result to be clicked was the relevance and not its position on the results page. Conclusions. The subjects of our experiment displayed an emancipated search behaviour while choosing relevant snippets even in lower positions. This means that, despite the fact that students were influenced by the position of a result, they made choices on the basis of relevance.
A High Efficiency Multi-Receiver Wireless Power Transfer System with Unanimous Power Reception at a Certain Angle

This paper presents a high efficiency magnetically coupled resonant wireless power transfer(MCR-WPT) system which can achieve uniform power distribution for five receivers that are at different positions and an angle with the horizontal plane. Both the receiver and transfer coils utilize a single coil structure. This paper analyzes the change of the coupling coefficient with the variation of angle of the non-axial receiver coil. In order to make the non-axial receiver gets the maximum power, it is necessary to adjust the coupling coefficient to the maximum by deflecting the receiver an angle. A prototype is fabricated and tested. The simulation and test results are in good agreement. The overall system efficiency reaches 89.16%, and the five receivers can receive almost the same power.
Melon Crack Identification and Classification Using k-Means Clustering for Quality Inspection

The main objective of this work is to propose a method, for the identification of crack in melon, using the colour images, and classify into cracked and non-cracked ones, and giving the dominant colours of the surface. The melon is segmented, and its cracked part is identified using k-means clustering based segmentation algorithm. Colour images of melons, with differently shaped cracks, are taken as input dataset for employing the proposed algorithm. Colour components in the image of melon are used for segmentation. k-means clustering based approach is an iterative process that is used to cluster images of melon into k clusters. Pixels are clustered after transformation into L*a*b* colour space taking as an input a* and b* channels, and images are produced to identify the cracked part. A cluster containing the cracked part was found by the value of the centroid. Additionally, the melon’s surface dominant colours are obtained for the main peel colour representation. The experimental study shows the effectiveness of proposed method on the applied dataset of melon’s images provided by Vilmorin & Company.
A Signal and Offset T&H Frontend for Spinning Hall Sensors with Ping-Pong and Chopping Techniques

A spun Hall sensor with continuous-time chopping and ping-pong sampling techniques for fast overcurrent detection application is presented in this paper. The proposed background track-and-hold ping-pong comparator continuously tracks the input Hall signal while cancels the Hall offset and the amplifier offset without shorting the input amplifier. In addition to the spinning-current technique, a system chopping and a chopped 6-bit DAC with temperature coefficient (TC) correction guarantee an overcurrent threshold drift of 1.06A (0.7% of the typical full-scale range 150A) from −50°C to 125°C.
Optimal Design of an Ultra-Premium-Efficiency PMA-Synchronous Reluctance Motor With the Winding Method and Stator Parameters to Reduce Flux Leakage and Minimize Torque Pulsations

In this paper, the optimal design for a permanent magnet-assisted synchronous reluctance motor (PMA-SynRM) is proposed in terms of efficiency, maximum torque, and minimum torque pulsations. Design variables, objective functions, and constraints are selected for this optimal design, which is divided into two steps. Step I utilizes the pole/slot combination of the PMA-SynRM and winding methods. The chosen 4-pole/36-slot model with distributed winding maximizes the rated efficiency. In Step II, the optimal design of the stator parameters is obtained using the response surface method and the precise torque and torque ripple are calculated using the finite-element analysis (FEA). The proposed stator slot openings are minimized to minimize the air-gap flux leakage, and consequently, realize a smooth electromagnetic torque. Finally, a few FEA results are validated by experimental results.
DSO and Aggregator Sharing Concept for Distributed Battery Storage System

Increase in electricity demand, mostly due to integration of new technologies electrifying heat and transport, as well as increasing share of distributed generation, create new challenges for distribution system operator (DSO) in terms of reliability and quality of power supply. This is particularly manifested during daily extremes, suggesting there is insufficient capacity of the distribution grid. To avoid expensive and unnecessary investments in new cables and transformers (since events that require network reinforcement are short and rare), the DSO can define a methodology for implementation of so called non-grid solutions. This paper analyses a concept in which the DSO signs a contract with the aggregator of flexible resources, offering incentives, such as reduced network fee, for using battery storage when necessary. Since the aggregator is looking for a feasible business case due to high investment cost of storage, the incentives given by the DSO provide a cost-effective investment for the aggregator. The aggregator uses battery storage to minimize the cost of purchasing electricity on the market while the DSO is utilizing it to postpone network reinforcement. The problem is cast as a bilevel problem where the operation of the distribution grid is modelled by Second-Order-Cone-Programming (SOCP) relaxation of optimal power flows bidding for the right to use aggregator's battery for preventing violating networks technical constraints. Over a set of scenarios, we demonstrate how coordinated usage of battery storage can postpone network reinforcement while ensuring secure power supply, as well as bring additional cost benefits for the aggregator.
Beam Walking to Assess Dynamic Balance in Health and Disease: A Protocol for the “BEAM” Multicenter Observational Study

Background: Dynamic balance keeps the vertical projection of the center of mass within the base of support while walking. Dynamic balance tests are used to predict the risks of falls and eventual falls. The psychometric properties of most dynamic balance tests are unsatisfactory and do not comprise an actual loss of balance while walking. Objectives: Using beam walking distance as a measure of dynamic balance, the BEAM consortium will determine the psychometric properties, lifespan and patient reference values, the relationship with selected “dynamic balance tests,” and the accuracy of beam walking distance to predict falls. Methods: This cross-sectional observational study will examine healthy adults in 7 decades (n = 432) at 4 centers. Center 5 will examine patients (n = 100) diagnosed with Parkinson’s disease, multiple sclerosis, stroke, and balance disorders. In test 1, all participants will be measured for demographics, medical history, muscle strength, gait, static balance, dynamic balance using beam walking under single (beam walking only) and dual task conditions (beam walking while concurrently performing an arithmetic task), and several cognitive functions. Patients and healthy participants age 50 years or older will be additionally measured for fear of falling, history of falls, miniBESTest, functional reach on a force platform, timed up and go, and reactive balance. All participants age 50 years or older will be recalled to report fear of falling and fall history 6 and 12 months after test 1. In test 2, seven to ten days after test 1, healthy young adults and age 50 years or older (n = 40) will be retested for reliability of beam walking performance. Conclusion: We expect to find that beam walking performance vis-à-vis the traditionally used balance outcomes predicts more accurately fall risks and falls. Clinical Trial Registration Number: NCT03532984.
Symbol Timing and Carrier Frequency Recovery Based on Entropy Minimization

This paper presents a new entropy minimization criterion for both symbol timing and carrier frequency recovery for wireless receivers. Synchronization is achieved by minimizing the entropy estimated from the eye diagram and the constellation diagram. Key implementation details are addressed toward the realization of entropy-based synchronization algorithms. In addition, the performance is evaluated in controlled conditions. It is shown that, as an alternative to the maximum likelihood criterion, entropy minimization has great potential and offers certain advantages for synchronization in wireless communication, particularly for pulse shaping filters with small excess bandwidth, as well as in multipath fading channels.
Electromagnetic Prospecting for Underground Structure by a 2.5-D Frequency-Domain Algorithm

In this work, we present a novel 2.5-D frequency-domain algorithm using mixed spectral element method with the divergence-free constraint to solve the EM prospecting problem, and show its application to the marine controlled-source electromagnetic (MCSEM) systems. Because the divergence-free constraint is explicitly enforced (unlike the conventional spectral element method), the charge conservation is honored in the governing equation. The stability of the solution is ensured, making the system matrix well-conditioned even at low frequencies. Numerical experiments show that the proposed method is well suited for solving low-frequency MCSEM problems by an iterative method.
Adaptive Trajectory Tracking Controller for an Armoured Vehicle: Hardware-in-the-Ioop Simulation

This paper presents a hardware-in-the-loop (HiL) simulation study of an adaptive trajectory following strategy consists of a knowledge-based adaptive mechanism, to automatically guide an armoured vehicle along a desired path. To model the armoured vehicle, a 7 Degree-of-Freedoms (DoF) mathematical model was used. Next, a geometric controller was developed based on Stanley controller. A knowledge database was built using Particle Swarm Optimisation (PSO) algorithm to optimise set of controller parameters depending on various combinations of vehicle speed and heading error. An adaptive mechanism was developed to automatically adjust controller parameters based on this knowledge. The controller was implemented through HiL simulations and evaluated against the original Stanley Controller. Trajectory following performance was evaluated and it was proven that the adaptive controller managed to guide the armoured vehicle successfully along the roads with 87% lateral error reductions on HiL compared to the simulations. It was also shown that the proposed adaptive controller managed to produce correctional steering actions that is suitable for the steering actuator to generate.
Method of successive dichotomizations: An improved method for estimating measures of latent variables from rating scale data

The most commonly used models for estimating measures of latent variables from polytomous rating scale data are the Andrich rating scale model and the Samejima graded response model. The Andrich model has the undesirable property of estimating disordered rating category thresholds, and users of the model are advised to manipulate data to force thresholds to come out ordered. The Samejima model estimates ordered thresholds, but has the undesirable property of estimating person measures on a non-invariant scale—the scale depends on which items a person rates and makes comparisons across people difficult. We derive the rating scale model logically implied by the generally agreed upon definition of rating scale—a real line partitioned by ordered thresholds into ordered intervals called rating categories—and show that it estimates ordered thresholds as well as person and item measures on an invariant scale. The derived model turns out to be a special case of the Samejima model, but with no item discrimination parameter and with common thresholds across items. All parameters in our model are estimated using a fast and efficient method called the Method of Successive Dichotomizations, which applies the dichotomous Rasch model as many times as there are thresholds and demonstrates that the derived model is a polytomous Rasch model that estimates ordered thresholds. We tested both the Method of Successive Dichotomizations and the Andrich model against simulated rating scale data and found that the estimated parameters of our model were nearly perfectly correlated with the true values, while estimated thresholds of the Andrich model became negatively correlated with the true values as the number of rating categories increased. Our method also estimates parameters on a scale that remains invariant to the number of rating categories, in contrast to the Andrich model.
Cost-Effectiveness Analysis for the Treatment of Hyperphosphatemia in Predialysis Patients: Calcium-Based versus Noncalcium-Based Phosphate Binders

Background Hyperphosphatemia in chronic kidney disease (CKD) patients is often treated with calcium carbonate (CaCO3) despite the fact that CaCO3 is associated with increased calcium load and potentially increased cardiovascular risk. Alternative treatments with noncalcium-based phosphate binders do not increase the calcium load but are more costly. This study analyzes the cost-effectiveness of sevelamer versus CaCO3 for the treatment of hyperphosphatemia in stage III-V predialysis CKD patients in Malaysia. Methods A Markov decision model was adapted to simulate a hypothetical cohort of CKD patients requiring treatment for hyperphosphatemia. Survival was estimated by using efficacy data from the INDEPENDENT-CKD clinical trial. Cost data was obtained from Malaysian studies while health state utilities were derived from literature. Analysis was performed over lifetime duration from the perspective of the Ministry of Health Malaysia with 2013 as reference year. Results In the base case analysis, sevelamer treatment gained 6.37 life years (5.27 QALY) compared to 4.25 life years (3.54 QALY) with CaCO3. At 3% discount, lifetime costs were RM159,901 ($48,750) and RM77,139 ($23,518) on sevelamer and CaCO3, respectively. Incremental cost-effectiveness (ICER) of sevelamer versus CaCO3 was RM47,679 ($14,536) per QALY, which is less than the WHO threshold of three times GDP per capita (RM99,395) per QALY. Sensitivity analyses, both using scenario sensitivity analysis and probabilistic sensitivity analysis, showed the result to be robust. Conclusions Our study finds that sevelamer is potentially cost-effective compared to CaCO3, for the treatment of hyperphosphatemia in predialysis CKD III-V. We propose that sevelamer should be an option in the treatment of Malaysian predialysis patients with hyperphosphatemia, particularly those with high calcium load.
Non-linear relationships between the BMI and physical fitness in Polish adolescents

Abstract Background: Comparisons of physical fitness in normal weight and overweight/obese youth generally highlight the negative consequences of an elevated BMI. In contrast, several studies of children and adolescents highlight the importance of variation in indicators of physical fitness across the full spectrum of BMIs from low through high. Aim: The purpose of the study was to evaluate relationships between specific physical fitness items and the BMI among youth. Subjects and methods: Height, weight and six physical fitness tests were measured in 1239 males and 903 females, aged 13–16 years; BMI (kg/m2) was calculated. Fitness tests were compared by weight status using sex-specific MANCOVAs, controlling for age. Sex-specific quadratic regressions of each fitness item on the BMI were also calculated. Results: The sprint, standing long jump and shuttle run indicated better performances in normal than in thin and overweight/obese boys; the latter groups did not differ. Thin and normal weight boys performed better than overweight/obese boys in sit-ups and distance run. Among girls, sit-ups differed as follows: normal > thin > overweight/obese. Thin and normal weight girls performed better than overweight/obese girls in the jump, distance run and shuttle run. Normal weight girls were faster in the sprint than the overweight/obese. The quadratic regressions indicated significant non-linear relationships between the BMI and all fitness items among boys and in four items among girls. Conclusion: Performances on fitness tests varied with weight status. Relationships between performances and the BMI were curvilinear except for the distance run and flexibility in girls.