Miracle-dz/UniFAR-FTUs huggingface dataset:
Rapid Prototyping Design for In-Wheel Motor Controller

Based on the study of the Matlab rapid prototyping technology, the rapid prototyping design approach is presented, which is widely applicable to all kinds of microcontroller. Through the modification of the system target file, the automatic code generation function of the Matlab could support more microcontrollers. The rapid prototyping of in-wheel motor controller is designed through this approach. Then the embedded C codes are generated according to the vector control algorithm model which is validated by simulation, and the rapid prototyping of in-wheel motor controller is achieved. The proposed approach is validated through the comparison to hand-written code.
Testing for a unit root in the presence of a nonlinear trend: The case of Australian Reel Exchange Rate

In this paper, we examine stationarity of the Australian real exchange rate (RER). For this purpose, we modify the test of Kapetanios et. al. [Testing for a unit root in the nonlinear STAR framework. Journal of Econometrics 112 (2003) 359-379] to allow for a nonlinear trend function in the data generating process. Using bootstrap techniques, we show that the null hypothesis of unit root can be rejected, providing evidence in favour of PPP proposition for the Australian RER.
Long-Term Performance of Ultrasonic Transducers Used for Energy and Data Transmission

In this work, we present experimental results on the long-term performance of ultrasonic transducers elements. For aeronautic applications these devices are targeted for the wireless transmission of energy and data to and from sensor elements placed inside of hermetically sealed metal envelopes, typically used e.g. for hydraulic accumulators, oxygen bottles, fuel tanks etc. By exciting the transmitter piezo in resonance, acoustic waves are generated traveling through the metallic body and are reconverted to electrical energy on the receiving side. Commercially available cylindrically shaped piezoelectric elements have been selected in order to build up an energy and data transmission system. In a test arrangement for preevaluation purposes both piezoelectric elements are arranged on opposite sides of a metal wall, fixed by using an electrically conductive epoxy and exposed to ambient temperatures up to of 100 deg C. Furthermore, a concept is presented how to integrate the complete system in a compact way in a hydraulic accumulator.
Directed Connectivity Analysis in People with Spinal Cord Injury during Attempted Arm and Hand Movements

⎯ We investigated the cortical connectivity patterns that arise in subjects with spinal cord injury (SCI) during attempted hand and arm movements using multivariate autoregressive (MVAR) models and electroencephalographic (EEG) signals. The MVAR models were fitted using multiple trials from multiple subjects in order to capture general connectivity characteristics during different type of attempted movements. Based on the results we detected two main sources of information: the somatosensory and the primary motor area. Changes in directional connectivity between different regions before and after cue onset were found to be informative in terms of the type of movement attempted by the SCI participants. Keywords⎯ multivariate autoregressive model, directed coherence, EEG, spinal cord injury, attempted movement
Theory of angle estimation using a multiarm spiral antenna

An analysis of angle estimation using a single aperture, multimode spiral is presented. It is demonstrated that in addition to the classical Comparison method, modern parameter estimation techniques such as Multiple Signal Classification (MUSIC) and MLM (Maximum Likelihood Method) can be applied to multimode antenna technology for angle estimation. These techniques, coupled with the advent of digital receivers make possible the elimination of the mode-forming network. Results of computer simulations show that these new approaches give lower bias and variance, and also extend coverage toward boresight compared with the traditional Comparison method.
Effect of interacted deterioration parameters on service life of concrete structures in cold environments

The workshop was held at VTT as part of the Finnish project “Effect of interacted deterioration parameters on service life of concrete structures in cold environments”. The 3-year project began in 2008 and is funded by Tekes. The goal of the workshop was to share results and experiences on current concrete durability research, especially with regard to correlation of accelerated laboratory tests with real-time field exposure sites. Presentations were given on topics of frost resistance, abrasion, chloride ingress and existing field station data. International researchers were invited to share their expertise and collaboration ideas for future partnerships.
An experimental study of rough surface scattering and its effects on communication coherence

The paper addresses some reflection and scattering phenomena for a model telemetry channel with a periodically fluctuating surface. Limitations on the extent of surface fluctuations are derived from the reflection and scattering area, Rayleigh parameter and shadow function. These results are related to the observed pulsed response of the surface. Finally the effect of the scattering process on communication coherence is briefly discussed. <<ETX>>
Experimental determination of magnetic saturation and hysteresis characteristics in power transformers with the WVAV method

In this paper, the experimental determination of the magnetic saturation and hysteresis characteristics of power transformers having a multilimb magnetic core with the wattmeter-voltmeter-amperimeter-voltmeter (WVAV) method is described in detail. An analysis is presented for the experimental curves obtained in terms of the material properties, iron-core dimensions and geometry, winding connections and the WVAV method of measurement used. Potential applications of the determination of experimental saturation and hysteresis curves are on electromagnetic transient studies and harmonic and power quality analysis of power systems.
Synchronous machine steady-state stability analysis using an artificial neural network

In the developed artificial neural network, those system variables which play an important role in steady-state stability, such as generator outputs and power system stabilizer parameters, are used as the inputs. The output of the neural net provides the information on steady-state stability. Once the connection weights of the neural network have been learned using a set of training data derived offline, the neural net can be applied to analyze the steady-state stability of the system in real-time situations where the operating conditions change with time. To demonstrate the effectiveness of the proposed neural net, steady-state stability analysis is performed on a synchronous generator connected to a large power system. It is found that the proposed neural net requires much less training time than the multilayer feedforward network with back-propagation-momentum learning algorithm. It is also concluded from test results that correct stability assessment can be achieved by the neural network. >
Effect of channel spacing in an optical two-channel DPSK transmission system with optical amplifiers

In a two-channel 560 Mbit/s DPSK system with optical broadband amplifiers the effect of channel spacing is investigated. The main crosstalk mechanism is independent of the amplifiers. It is caused by the spectral overlap of the two channels. No additional crosstalk due to four-wave mixing in the amplifier is found.
Demand chain management in a global enterprise-information management view

The strategy and role of Information Management as an enabler and contributor to successful business strategy is discussed. Global Demand Chain Management is used as an example. Basic principlesand differences of Supply Chain Management and Demand Chain Management are explained, focusing on the perspective of Information Management. Key drivers and criteria for Information Management system design are outlined. The gaps of current application software platforms are discussed.
Sensitivity analysis and optimization of thin-film thermoelectric coolers

The cooling performance of a thermoelectric (TE) material is dependent on the figure-of-merit (ZT = S2σT/κ), where S is the Seebeck coefficient, σ and κ are the electrical and thermal conductivities, respectively. The standard definition of ZT assigns equal importance to power factor (S2σ) and thermal conductivity. In this paper, we analyze the relative importance of each thermoelectric parameter on the cooling performance using the mathematical framework of sensitivity analysis. In addition, the impact of the electrical/thermal contact parasitics on bulk and superlattice Bi2Te3 is also investigated. In the presence of significant contact parasitics, we find that the carrier concentration that results in best cooling is lower than that of the highest ZT. We also establish the level of contact parasitics that are needed such that their impact on TE cooling is negligible.
Wildfire and drying legacies and stream invertebrate assemblages

Climate change is engendering droughts and wildfires in many ecosystems, especially those in Mediterranean climates. Yet, there is little information on the long-term responses of stream invertebrates in Mediterranean climates to wildfire, particularly during and after extreme drought. To examine the effects of drought and wildfire on stream invertebrate assemblages, we sampled stream reaches in southern California with surface water in 2016, at the end of a 5-y drought, and stream reaches in 2017, after flows resumed or increased, including sites within (burned), outside (unburned), and downstream of footprints for fires occurring 8 to 10 y ago. Spatial and temporal variation in invertebrate assemblages were attributed to hydrological regimes, including stream drying during the drought, but there were few fire-legacy effects. At the end of the drought, invertebrate assemblages occupying remaining standing water with high solute, temperature, and benthic organic matter levels were dominated by tolerant, lentic taxa. After flows returned in spring 2017, all sites, including those that were dry in 2016, were dominated by quick-colonizing riffle taxa. Invertebrate densities increased into the subsequent summer at the same time that flows declined and temperatures and conductivities increased; however, sensitive cool-water taxa were more abundant at perennial, shaded sites, whereas tolerant, warm-water taxa were more abundant at shallow, open sites that had dried the year before. We observed negative relationships between riparian burning extent vs canopy cover (weak) and coarse particulate organic matter levels (strong); however, invertebrate assemblage structure was similar in basins that did and did not burn. Although invertebrate populations were severely reduced at 1 site whose basin had burned the year before, invertebrate assemblages had largely recovered after 10 post-fire y, and fire-legacy effects were dwarfed by hydrological variation, particularly stream drying during the drought. Our data also suggest the importance of protecting water supplies and riparian vegetation for perennial, shaded headwater reaches, which provide refuges from drought and wildfire for native biodiversity.
Osteoporosis Preventive Behavior Among Female Healthcare Students in Da Nang, Vietnam

Background: Osteoporosis prevention at young ages is crucial to diminish the risk of the disease and its complication in later years of life. Having good osteoporosis knowledge and positive health belief may lead to better preventive behavior which then contributes to build and maintain bone health throughout life. Objective: To investigate knowledge, health belief, and behavior of osteoporosis prevention among female healthcare students. Methods: The descriptive cross-sectional study was conducted in a public medical university in Da Nang of Vietnam. Four hundred participants were selected by applying the multistage sampling technique. Data were collected from May 2020 to June 2020 through the questionnaire that consists of 4 parts including the demographic data form, the osteoporosis knowledge assessment tool, the osteoporosis health belief scale, and the exercise and calcium behaviors scale. Data were analyzed using descriptive statistics and Pearson correlation test. Results: Participants had poor osteoporosis knowledge (mean [SD], 37.8 [16.0]; range, 0 - 75) and low preventive behavior (mean [SD], 5.7 [3.5]; range, 0 - 25). Osteoporosis health belief was found at a moderate level with a mean (SD) of 126.7 (12.9) (range, 84 - 187). There were positive significant correlations between knowledge and health belief, knowledge and behavior of osteoporosis prevention (P < .05). Conclusions: Osteoporosis preventive behavior of female healthcare students was low. Osteoporosis education programs should be developed for female healthcare students to improve their knowledge and health belief that would then lead to their better preventive behavior.
Efficient spatial designs using Hausdorff distances and Bayesian optimization

An iterative Bayesian optimization technique is presented to find spatial designs of data that carry much information. We use the decision theoretic notion of value of information as the design criterion. Gaussian process surrogate models enable fast calculations of expected improvement for a large number of designs, while the full‐scale value of information evaluations are only done for the most promising designs. The Hausdorff distance is used to model the similarity between designs in the surrogate Gaussian process covariance representation, and this allows the suggested algorithm to learn across different designs. We study properties of the Bayesian optimization design algorithm in a synthetic example and real‐world examples from forest conservation and petroleum drilling operations. In the synthetic example we consider a model where the exact solution is available and we run the algorithm under different versions of this example and compare it with existing approaches such as sequential selection and an exchange algorithm.
Fifty Ways to Lose Your Data (and How to Avoid Them)

There probably are not 50 ways to lose your data, but there are a bunch. Of course, if we all backed up our data before working with it, there wouldn’t be a problem. However, that’s not always a practical solution, especially if your data sets are large. By being aware of coding syntax that can lead to data destruction, you can avoid finding yourself with a data set containing 0 observations. The techniques in this paper can help anyone from the novice to the experienced user prevent disasters. If you’ve never had this problem, these techniques will allow you to continue to be quite proud of yourself.
The Future of Chemically Enhanced Primary Treatment: Evolution Not Revolution

Summary of CEPT development. Overall, the reader should conclude from this reviewthat the CEPT technology has been well developed after at least 35 years of basic andapplied research at bench-, pilot- and field-scale. There is a wealth of research andpractical experience to draw upon. In addition to the cited references, recent designmanuals and textbooks do a good job of presenting design approaches for CEPT (e.g.,Bouker et al, 1987, Sedlack, 1992, and WEF and ASCE, 1998). CEPT in Hong Kong Two of the discussers were involved as treatment technology consultants advising theHonk Kong based firm conducting the independent review of Stage II of the StrategicSewage Disposal Scheme for the Hong Kong government. This occurred at the sametime as Professor Harleman’s first involvement as an International Review Panelmember. The reports of the two groups are bound in the same volume and should beconsidered together (Pypun, 1995 and Yi et al., 1995). Harleman and Murcott are in error when they assert that Professor Harleman wasinstrumental in arguing that the conventional primary treatment planned for Stonecutter’sIsland in Stage I of the plan should be replaced with CEPT. In fact, the consultant(Montgomery Watson) had planned on CEPT using low lime (pH 9.7) treatment for thefirst stage of construction.Harleman and Murcott are correct that it was the panel’s recommendation to increase thesurface overflow rate of the primary sedimentation tanks and that low dose iron should beused, however the iron was to replace lime as a coagulant. It should be noted that theindependent consultants (Pypun, 1995) had previously concluded under Option 9 for
OPTICAL MEMS TECHNOLOGIES FOR ELECTRICALLY TUNABLE MULTI-SPECTRAL SHORT-WAVE INFRARED SENSORS AND ARRAYS

Optical MEMS technology combined with broadband infrared sensor technology is used to realize wavelength-tunable infrared sensors. This paper describes the ongoing research into one such sensor design based on an electrically tunable Fabry-Perot cavity. Theory, measured results and future research directions are presented and discussed for the single-sensor design currently being developed, in the context of the intended application of this technology; the development of lightweight, portable and robust multi-spectral imaging systems.
SIMAD: Secure Intelligent Method for IoT-Fog Environments Attacks Detection

: The Internet of Thing IoT paradigm has emerged in numerous domains and it has achieved an exponential progress. Nevertheless, alongside this advancement, IoT networks are facing an ever-increasing rate of security risks because of the continuous and rapid changes in network environments. In order to overcome these security challenges, the fog system has delivered a powerful environment that provides additional resources for a more improved data security. However, because of the emerging of various breaches, several attacks are ceaselessly emerging in IoT and Fog environment. Consequently, the new emerging applications in IoT-Fog environment still require novel, distributed, and intelligent security models, controls, and decisions. In addition, the ever-evolving hacking techniques and methods and the expanded risks surfaces have demonstrated the importance of attacks detection systems. This proves that even advanced solutions face difficulties in discovering and recognizing these small variations of attacks. In fact, to address the above problems, Artificial Intelligence (AI) methods could be applied on the millions of terabytes of collected information to enhance and optimize the processes of IoT and fog systems. In this respect, this research is designed to adopt a new security scheme supported by an advanced machine learning algorithm to ensure an intelligent distributed attacks detection and a monitoring process that detects malicious attacks and updates threats signature databases in IoT-Fog environments. We evaluated the performance of our distributed approach with the applicationof certain machine learning mechanisms. The experiments show that the proposed scheme, applied with the Random Forest (RF) is more efficient and provides better accuracy (99.50%), better scalability, and lower false alert rates. In this regard, the distribution character of our method brings about faster detection and better learning.
Design of a novel intelligent damping controller for unified power flow controller in power system connected offshore power applications

This study proposes a unified power flow controller-based oscillation damping controller for use with a permanent magnet synchronous generator-based offshore power farm. A novel intelligent damping controller (NIDC) was used to increase the stability of power control and improves the performance, where the proposed NIDC consists of the adaptive critic network, the functional link-based Elman neural network (FLENN), the genetic ant colony optimisation algorithm (GACO) and proportional–integral-derivative (PID) linear damping controller. The PID damping controller analyses complex eigenvalues based on the theory of modern control. The node connecting weights of the FLENN and critic network are trained online. A GACO approach is developed to adjust the learning rates and thus improve the learning ability. The proposed NIDC can achieve better damping characteristics, and the internal power fluctuations can also be effectively alleviated.
An Investigation of Fundamental Frequency Limitations for HF/VHF Power Conversion

By Chucheng Xiao W.G. Odendaal, Chairman The volume reduction in power converters over the past several decades can chiefly be attributed to increases in switching frequency. It is to be expected that the trends towards miniaturization will maintain steady pressure to keep this pace of increasing switching frequencies of power converters. However certain fundamental limits in high frequency power conversion are being reached as frequencies are being pushed deeper into the megahertz range, inhibiting substantial further increases. The work reported in this dissertation is intended to systematically investigate the fundamental frequency limitations, identify some of the solutions for HF/VHF power conversion and to provide guidelines and tools to optimize the performance of power converters by maximizing frequency. A number of multi-megahertz power converters are examined to evaluate the present status and future trend of HF/VHF power conversion. An interesting trend between power level and frequency is observed. A general limitation about the power level and frequency, independent of design details, is derived from the physics of the semiconductor devices, which determines the upper bound of the power levels as frequency increases. A 250 MHz DC-DC power converter (derived from the Class E power amplifier) is analyzed and demonstrated with discrete components, which again verifies the trend between power level and frequency. The power losses in the semiconductor devices are discussed, and optimization criteria for minimizing the power losses of the devices, are discussed. By relating the power losses to the semiconductor materials’ properties, a
Analytical calculation of air-gap magnetic field distribution and instantaneous characteristics of brushless DC motors

This paper derives the relative air-gap-specific permeance distribution function by Schwarz-Christoffel transformation, considering the effect of slotting. Neglecting the iron saturation, and employing the analytical algorithm for partial differential equations, efficient and effective analytical calculations of no-load air-gap magnetic field distribution, armature field distribution, and phase electromotive force (EMF), are demonstrated, considering the stator slots. Subsequently, based on the main circuit topology of a brushless DC motor (BLDCM), the field-circuit coupling model is constructed for the motor, and then the phase current waveforms and load air-gap magnetic field distribution at any time are determined. Consequently, the instantaneous electromagnetic torque is computed, which underpins the quantitative analysis of torque ripple and the pulsation induced by commutation. Hence, the present work paves the way to precise prediction of the motor's performance and acoustic noise. It is a powerful tool for the design of surface permanent magnet brushless DC motors.