Miracle-dz/UniFAR-FTUs huggingface dataset:
Electromagnetic torque prediction and harmonic reduction of interior permanent magnet synchronous motor for electric vehicles using an analytical method

Interior permanent magnet synchronous motors (IPMSMs) have been widely used as drive machines in electric vehicles (EVs) due to their high torque density. However, the torque ripple of IPMSMs will result in severe noise and vibration. This paper proposes a new analytical method for electromagnetic torque prediction and harmonic reduction of IPMSM. On the basis of dq theory, an analytical model of electromagnetic torque is firstly established by taking the permanent magnet flux harmonics and the cross-coupling effect into consideration. And the specific sources and orders of torque harmonics are also determined. Then, the torque-angle characteristics are further studied. In particular, the permanent magnet (PM) torque and the reluctance torque are separated and quantitatively analyzed via the proposed analytical model. Finally, a theoretical method of reducing the specific order torque harmonic by PM shifting is derived and proposed from the perspective of avoiding resonance. The accuracy and effectiveness of the proposed analytical method are verified by finite-element analysis. The results show that the proposed analytical model is accurate enough to predict the electromagnetic torque performance of IPMSM. Moreover, the electromagnetic torque harmonics with specific orders can be effectively reduced by shifting the PM to an appropriate angle.
What Is "Synthesis" And Who Needs A Symposium On It?

This symposium is a result of the author's observation over the better part of the last decade that workers in each of the fields of optics, electro-optics, acoustics, and electromagnetics have been solving very similar problems with little awareness of what is being done outside their field. Many of the tools and quite a few of the important results have been reinvented independently in each of these fields. There are excellent and fundamental reasons for this. The purpose of this introductory paper is to attempt to convey a bit of philosophy wrapped around some very fundamental Physics about the field of synthesis and its interdisciplinary aspects. This paper presents two basic ideas: 1. Synthesis is a problem that is different and distinct from analysis, and should be treated as such. 2. Most electromagnetic and acoustic synthesis problems ultimately deal with physics that can be expressed mathematically in the same form.
Development of a floating element wall shear transducer

Abstract : A highly linear passive floating element wall shear transducer has been developed which uses a sensitive frequency modulation technique to measure a capacitance change proportional to the displacement of the floating element for small deflections. The floating element is 4mm square surrounded by a gap nominally 0.18mm and protrudes into the boundary layer 9 micrometer. Scaled on inner parameters, each side of the sensing head measures about 290, the mean gap width is 13, and the element protrusion is 0.7. The transducer was tested in a turbulent boundary layer on a flat plate at momentum thickness Reynolds numbers of 3140, 3500, and 3760 and the results compared to wall shear stress estimates obtained from the law of the wall. The transducer was found to predict the steady mean wall shear stress within the limits of experimental uncertainty in all cases; transducer measurements of mean wall shear stress for momentum thickness Reynolds numbers of 3140 and 3500 were within 2 percent of the actual value. Transducer measurement of the unsteady mean wall shear stress was severely limited by a mechanical resonance in the transducer at 63 Hz. The operating principles and general characteristics of the transducer are discussed, its performance is evaluated, and recommendations are made concerning future work.
Virtual prototyping to design better corporate buildings

For new generations of decision-makers virtual worlds will be a normal part of their lives due to the gaming and filming industries. Their future needs for visualisation, serious gaming, and decision-making in support of new technologies will emerge and grow, and will finally be fulfilled. This development will be especially useful in the context of social architecture for organizations. Virtual reality (VR) allows examination of such models holistically as well as on the decomposed lower levels. With virtual worlds hard calculable facts and algorithms are as important as soft complex systems and the meaning of spaces. VR gives science a reliable escape from the scientific flatlands that are generally presented on paper or screen. Building 3D of social architecture for organizations, as well as 4D for a profound debate about possible future states of these organizations will advance our understanding of the decisions that are successful in this specific context.
Drug resistance, rather than low tenofovir levels in blood or urine, is associated with tenofovir, emtricitabine and efavirenz (TEE) failure in resource-limited settings.

INTRODUCTION The high cost of viral load (VL) testing limits its use for antiretroviral treatment (ART) adherence support. A low-cost lateral flow urine tenofovir (TFV) rapid assay predicts PrEP breakthroughs but has not yet been investigated in HIV treatment. We therefore evaluated its utility in a pilot cross-sectional study of TFV-containing ART recipients at increased risk of virologic failure. METHODS Participants who had a treatment interruption ≥30 days or had ≥1 episode of viremia (VL≥400 copies/mL) in the previous year were recruited from a public health setting in Cape Town, South Africa. Self-reported adherence data were collected, the urine TFV assay performed, and concurrent TFV-diphosphate (DP) analysed in dried blood spots. VL testing was done concurrently and, if viremic, genotypic HIV drug resistance testing performed. RESULTS Of 48 participants, 18 (37.5%) had virologic failure (VL>400 copies/mL) at the time of the study including 16 of 39 receiving efavirenz (EFV), 2 of 6 receiving protease inhibitors (PI) and 0 of 3 receiving dolutegravir (DTG). Resistance testing succeeded in 17/18, of which 14 had significant mutations compromising ≥2 agents of the current EFV-based regimen. Of these 14, all had detected urine TFV. Urine TFV was undetectable in 2 out of 3 without regimen-relevant resistance; p=0.02. CONCLUSION In participants on EFV-based regimens returning to care, virologic failure was largely due to viral resistance, where detectable urine TFV had 100% sensitivity (14/14 participants) in predicting resistance. Conversely, when undetectable, the urine-based assay could be used to preclude participants with poor adherence from undergoing costly HIV drug resistance testing.
Multi-sensor management for passive target tracking in an anti-submarine warfare scenario

The Multi-Sensor Fusion Management (MSFM) algorithm positions multiple, bearings-only, passive sensors in a two-dimensional plane to optimise the fused probability of detection using a simple decision fusion method. Used iteratively, the MSFM algorithm allows a manoeuvring target to be passively tracked in the presence of clutter and missing measurements. The algorithm also incorporates prior knowledge of the physical constraints of the scenario, the targets initial position and its manoeuvring capabilities. In the MSFM algorithm the probability distribution of the target location is modelled using a non-parametric approach. The logarithm of the fused detection probability is used as a criterion function in the optimisation of the sensor positions, for which a straightforward gradient ascent approach is used. Following the placement optimisation, the sensors are deployed and the individual sensor detections combined using a logical OR fusion rule. The target location distribution can then be updated using the method of sampling, importance re-sampling (SIR). An extension to the MSFM algorithm is used which allows the reduction of the total number of sensors deployed. The MSFM algorithm has been implemented for a simulated, but operationally plausible, anti-submarine warfare scenario. In this scenario a single submarine passing through a channel is tracked by sonobuoys which are deployed by a Maritime Patrol Aircraft. When compared with a model of traditional methods for sonobuoy placement, the MSFM algorithm is found to reduce the time to submarine location by over a factor of three and the number of sonobuoys required by over a factor of four.
Optimization of sugar level to develop healthy goat milk shrikhand

The present study was conducted to optimize the sugar level for preparation of goat milk shrikhand, which is the demand of present day health conscious consumer. Goat milk shrikhand was prepared with three different levels of sugar i.e. 20% (S1), 25% (S2) and 30% (S3) and evaluated for various physicochemical properties and sensory attributes. pH values and moisture content decreased significantly ( P< 0.05) whereas titratable acidity, ash content and brix values increased significantly ( P< 0.05) with increased sugar content in goat milk shrikhand. Textural parameters i.e. consistency, cohesiveness and work of cohesiveness values were significantly ( P< 0.05) higher in S2 and S3 than S1. There was no significant difference in colour parameters among the treatments. The scores of all sensory attributes increased significantly ( P< 0.05) with increased sugar content and S3 had significantly ( P< 0.05) higher flavour, sweetness, mouth coating and overall acceptability scores than S1 and S2. Therefore, S3- goat milk shrikhand prepared with 30% sugar content was found as the best treatment.
H ∞ asynchronous synchronisation control for Markovian coupled delayed neural networks with missing information

This paper first studies asynchronous synchronisation control problem for Markovian coupled neural networks with missing information. As information exchanges among neural networks, which can help achieving synchronisation, are conducted via a generally unprotected communication network with limited bandwidth, nodes' state information and the synchronised state information may not be available to node i, and a Bernoulli process is used to model this phenomenon. Furthermore, considering that the amount of information needs to be transmitted is decided by the coupling relationship, missing information rate is assumed to be node- and coupling dependent. By introducing another nonhomogeneous Markov chain with transition probability matrix depending on coupling mode, the asynchronous synchronisation controller is designed, which can describe complex asynchronous switch phenomenon between system and controller modes and covers mode-dependent controller and mode-independent one as two special cases. Three sufficient conditions respectively guaranteeing the global synchronisation and the global synchronisation of the addressed networks are obtained, and then the asynchronous synchronisation controller design method is proposed. Finally, an illustrative example with results demonstrating the effectiveness of the given controller design approach is provided.
DETERMINING RELATIVE IMPORTANCE OF HUMAN GUT MICROBIOTA, AGE, GENDER AND LIFESTYLE PATTERN AS A PREDICTOR FOR BMI USING LOGMPIE DATA

We use the ‘Relative Abundance Table’ and ‘LogMPIE Study Metadata’ from the “Landscape of Gut Microbiome - Pan-India Exploration”, or LogMPIE dataset to find out the relative importance of human gut microbiota abundance (specifically genus), age, gender, and lifestyle pattern as a predictor for BMI (Body Mass Index). The LogMPIE data is taken from 1004 subjects and 993 unique microorganisms are reported along with BMI, age, and physical activity. We use Random Forest Regressor to find out the relative importance of the above-mentioned features (microorganism genus abundance, age, gender, and lifestyle pattern) in predicting the BMI of a subject. The objective here is not the prediction of BMI using the features but to find out the relative importance of these features as much as these affect the BMI.
Modulation of Gamma Spectral Amplitude and Connectivity During Reaching Predicts Peak Velocity and Movement Duration

Voluntary movements are accompanied by increased oscillatory activity or synchronization in the gamma range (> 25.5 Hz) within the sensorimotor system. Despite the extensive literature about movement-related gamma synchronization, the specific role of gamma oscillations for movement control is still debated. In this study, we characterized movement-related gamma oscillatory dynamics and its relationship with movement characteristics based on 256-channels EEG recordings in 64 healthy subjects while performing fast and uncorrected reaching movements to targets located at three distances. We found that movement-related gamma synchronization occurred during both movement planning and execution, albeit with different gamma peak frequencies and topographies. Also, the amplitude of gamma synchronization in both planning and execution increased with target distance. Additional analysis of phase coherence revealed a gamma-coordinated long-range network involving occipital, frontal and central regions during movement execution. Gamma synchronization amplitude and phase coherence pattern reliably predicted peak velocity amplitude and timing, thus suggesting that cortical gamma oscillations play a significant role in the selection of appropriate kinematic parameters during planning and in their implementation during movement execution.
Optically fed microwave system using laser diodes with enhanced modulation bandwidth

The authors present the idea of using a laser diode with enhanced modulation characteristics to generate microwave optical signals for radio-over-fibre systems. By employing strong external light injection into a laser diode, the bandwidth improvement is shown experimentally, and by using a simulation package, we then demonstrate how the bandwidth improvement greatly enhances the overall performance of an optically fed microwave system based on direct modulation of a laser diode.
The Relationship among Manufacture Procedure, Manufacture Result and Customers Loyalty in Supply Chains

The present study examines the relationships between manufacture procedures, manufacture results and customers loyalty. And investigates key drivers that establish maintain customers loyalty. The survey instrument the form of a questionnaire to the function managers of manufacturing firms in Taiwan. These firms are listed in the Business Weekly (Taiwans leading business magazine) as the top manufacturing firms of 2013. There is analysis of confirmatory factor in 410 questionnaires were conducted. LISREL with structural equation modeling (SEM) was used to test and analyze the hypothesized relationships of the research model. This study empirically demonstrates the importance of the Manufacture procedure and Manufacture Results dimensions of manufacture quality on Customers Loyalty behavior. Both Manufacture Procedure and Manufacture Results quality are important determinants of Customers Loyalty.
Optimization of Renewable Energy Efficiency using HOMER

Hybrid Optimization Model for Electrical Renewable (HOMER), is a micro power optimization model, that simplifies the task of evaluating designs of both off-grid and grid-connected power systems for a variety of applications. The HOMER Hybrid Optimization Modeling Software is used for designing and analyzing hybrid power systems, which contain a mix of conventional generators, cogeneration, wind turbines, solar photovoltaic, hydropower, batteries, fuel cells, hydropower, biomass and other inputs. This paper investigates the energy efficiency of renewable energy system considering an isolated AC diesel generator. A model system consisting of a PV, three batteries and a converter system was considered. HOMER was able to calculate the best option that would give the best energy efficiency. Also, a further investigation was carried out considering two cases with two different load profiles to show that the load profiles affects the responses of the renewable energy system and the cash flow summary of some of the system equipments.
A study of the pedestrian impact kinematics using finite element dummy models: the corridors and dimensional analysis scaling of upper-body trajectories

Pedestrian–vehicle impact experiments using cadavers have shown that factors such as vehicle shape and pedestrian anthropometry can influence pedestrian kinematics and injury mechanisms. Although a parametric study examining these factors could elucidate the complex relationships that govern pedestrian kinematics, it would be impractical with cadaver tests because of the relative expense involved in performing numerous experiments on subjects with varying anthropometry. On the other hand, finite element modelling represents a more feasible approach because numerous experiments can be conducted for a fraction of the expense. The current study examined the relationship between pedestrian anthropometry and front shape of a mid-size sedan using a PAM-CRASH model of the 50th-percentile male (50th M) Polar-II pedestrian dummy extensively validated against experimental data. To evaluate the influence of pedestrian anthropometry on response kinematics, scaled dummy models were developed on the basis of the weight and height of the 5th-percentile female (5th F), 50th-percentile female (50th F) and 95th-percentile male (95th M). Simulations of the 5th F, 50th F, 50th M, and 95th M Polar-II finite element models struck at 40 km/h by a mid-size sedan were used to generate trajectories of the head, upper thorax, mid-thorax and pelvis. In an effort to assess the validity of scaling techniques when interpreting trajectory data from vehicle–pedestrian crashes, the trajectories of the 5th F, 50th F and 95th M model were scaled to the 50th M and compared with those generated by the 50th M model. The results demonstrated non-linear behaviour of dummy kinematics that could not be accounted for with traditional dimensional analysis scaling techniques.
Effects of wind generation intermittency and volatility on power system transient stability

The transient stability analysis incorporating wind power intermittency and volatility is studied in this study. The wind turbines with doubly fed induction generator (DFIG) and direct-driven permanent magnet synchronous generator (PMSG) are considered, respectively, during analysis. In modelling of DFIG and PMSG, the default GE wind turbine model and the Western Electricity Coordinating Council generic wind turbine model are employed, respectively. Based on the Jensen model, which is applied to describe the wake effect in a wind farm located on flat terrain, an equivalent simplified model of a wind farm is established regarding wind farm layout. On the basis of the built wind farm model, the Monte Carlo simulation technique combined with two evaluation indices, namely angle-based margin index and critical clearing time (CCT) is applied on the IEEE 10-generator-39-bus test system and a real-sized China-Jiangxi power grid as a benchmark to exploit and explore the effects of wind power intermittency and volatility on power system transient stability. The frequency distributions of transient stability evaluation index, CCT, probability of system transient instability and the range of wind speeds causing system transient instability are simulated. In addition, the influence of wake effect on transient stability is discussed as well.
PhaseAnti: An Anti-Interference WiFi-Based Activity Recognition System Using Interference-Independent Phase Component

Driven by a wide range of essential applications, significant achievements have recently been made to explore WiFi-based Human Activity Recognition (HAR) techniques that utilize the information collected by commercial off-the-shelf (COTS) WiFi infrastructures to infer human activities without the need for the subject to carry any devices. Although existing WiFi-based HAR systems achieve satisfactory performance in some instances, they are faced with a severe challenge that the impacts of ubiquitous Co-channel Interference (CCI) on WiFi signals are inevitable. This downgrades the performance of these HAR systems significantly. To address this challenge, we propose PhaseAnti in this paper, a novel WiFi-based HAR system to exploit the CCI-independent phase component, Nonlinear Phase Error Variation (NLPEV), of WiFi Channel State Information (CSI) to cope with the negative effects of CCI. The stability of NLPEV data and the sensibility of this component to motions are rigorously analyzed. Furthermore, validated by extensive properly designed experiments, this phase component across subcarriers is invariant under various CCI scenarios while sufficiently distinct for different motions. Therefore, the NLPEV data can be used and processed effectively to perform HAR in CCI scenarios. Extensive experiments with various daily activities in different indoor rooms demonstrate the superior effectiveness and generalizability of the proposed PhaseAnti system under various CCI scenarios. Specifically, PhaseAnti achieves a <inline-formula><tex-math notation="LaTeX">$ 96.5\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>96</mml:mn><mml:mo>. </mml:mo><mml:mn>5</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="liu-ieq1-3127721.gif"/></alternatives></inline-formula> recognition accuracy rate (RAR) on average in different CCI scenarios, which can improve up to a <inline-formula><tex-math notation="LaTeX">$ 16.7\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>16</mml:mn><mml:mo>. </mml:mo><mml:mn>7</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="liu-ieq2-3127721.gif"/></alternatives></inline-formula> RAR compared with the amplitude component in the presence of CCI. Furthermore, the recognition speed is 10.3 × faster than the state-of-the-art solution.
Design and Control of a Novel Leg-Arm Multiplexing Mobile Operational Hexapod Robot

A novel legged robot with 6 limbs driven by 20 proprioceptive motors, named SDUHex, is proposed in this letter. The limbs located at the middle of the robot can work as manipulators or locomotors. The topology design of the multi-mode robot is introduced and the kinematics and dynamics of the robot leg is analysed. A hierarchical optimized whole body controller with virtual model active compliance, called VM-WBC, is proposed. This control method unified the foot locomotion and arm operation. The terrain adaptation strategy is proposed to improve the non-flat terrain passability. A series of locomotion and operation experiments are carried out on SDUHex to test the designed robot and control method. Robust locomotion of the robot is verified by lateral impact recovery and slope terrain adaptation experiments. Arm operation of the robot including single-arm pushing and dual-arm picking are experimented to highlight the novel multiplexing function of the robot limbs.
A Forecasting Model of RBF Neural Network Based on Particle Swarm Optimization

In order to improve the precision of gas emission forecasting,this paper proposes a new forecasting model based on Particle Swarm Optimization (PSO). PSO is a novel random optimization method which has extensive capability of global optimization.In the model, PSO is used to optimize the weight,width and center of RBF neural network and the optimal model is applied to forecast gas emission.The diversified factors analysised with grey correlation,MATLAB is employed to implement the model for gas emission forecasting.The simulation results show that the gas emission model optimized by PSO is more accurate than the traditional RBF model．