Miracle-dz/UniFAR-FTUs huggingface dataset:
Common-mode EMI Noise Modeling and Reduction using Balance Technique for AC-DC-AC Traction Systems with Paralleled Power Modules

This paper proposes a common-mode (CM) noise suppression technique with the Wheatstone bridge balance circuit and a decoupling inductor in AC-DC-AC traction system with paralleled power modules. Since the EMI noise propagation paths in AC-DC-AC traction system with parallel power modules are complicated, a general CM equivalent circuit for above system is established in this paper. The EMI model is verified through experiment and simulation comparisons. Based on the understanding of the propagating mechanism of the CM noise in the whole system, the interactions between the rectifier subsystem and inverter subsystem are analyzed. The CM noise suppression in above system is often achieved by the EMI filters with trial and error method. In order to reduce the passive components' size and improve the noise attenuation capabilities, a Wheatstone balance circuit with a decoupling inductor technique is proposed to reduce the generated CM noise.
Management of sensory-motor activity in mobile robots

Consideration is given to the management of conflicting demands on the use of the motor units of the robot from the active sensors and manipulatory processes. An operating-system-like facility is introduced for managing the conflicting motor requests produced by multiple active sensing and manipulation tasks. A proposed implementation of this sensory-motor management facility based on the input-output-timed-automata (IOTA) abstraction is introduced. The IOTA abstraction is general enough to allow the enforcement of temporal constraints and to permit the specification and modification of task priorities based on the goals and current state of the robot. The IOTA-based sensory-motor operating system acts as a scheduler for various motor requests submitted by the active sensor and manipulation systems. The sensory-motor system is more general than the subsumption architecture of R. Brooks (1986) and can implement in a straightforward fashion alteration of priorities. <<ETX>>
A Study on the Voltage-Clamping caused by Dynamic Avalanche at Over-stress Turn-Off of GCTs

Dynamic avalanche is a key factor leading to the power device failure. By the device simulation, it is found that when the gate commutated thyristor (GCT) is turned off at a high supply voltage or high stray inductance, the anode-cathode voltage is clamped at certain value and a destructive stationary filament appears. Its mechanism is explained in detail. Additionally, the SOA limited by the voltage clamping is depicted, which implies the shrink of the SOA with the increase of the emitter efficiency of anode.
Performance Comparison between Several Underwater Navigation Algorithms for Autonomous Underwater Vehicle

Performing and robust navigation systems for Autonomous Underwater Vehicles (AUVs) play a critical role in scientific and industrial missions (e.g. exploration and surveillance of archaeological sites, reconnaissance and patrolling for military operations, Oil & Gas operations). The quality of the navigation algorithm for the estimation of the AUV navigation state affects the performance of the overall system strongly. Underwater Navigation methods can be divided into three main classes, Kalman filter-based, particle filter-based and graph-based, the advantages and disadvantages of each class are overviewed. In this paper, the authors present a performance comparison between three underwater navigation algorithms based on extend Kalman filter (EKF), particle filter (PF), incremental smoothing and mapping (iSAM). These approaches have been currently tested offline running on the experimental data collected with the Sailfish AUV during different missions on the bridge of Jiaozhou Bay and Menlou Reservoir. Different navigation algorithms have been tested by experimental data. The research's outcome has shown the advantage and disadvantage of these underwater navigation algorithms.
An Optimized Control Scheme for Reducing Conduction and Switching Losses in Dual Active Bridge Converters

An optimized switching control strategy to reduce the conduction and switching losses of the dual active bridge converter is presented in this paper. The control strategy can simultaneously reduce the root mean square value and average absolute value of the leakage inductor current, which are closely relevant to the conduction and switching losses of the semiconductor devices and high-frequency transformers. The optimization is conducted by regulating two manipulated variables on the basis of achieving zero-voltage switching for all switches in a wide voltage range as well as effectively reducing the power losses. An experimental prototype was implemented to validate the theoretical analysis and the feasibility of the proposed method. The experimental results revealed that the converter power losses can effectively be reduced and the overall system efficiency can be improved using the proposed control strategy.
Epidemiological Survey of Neurological Diseases in a Tribal Population Cluster in Gujarat

Background: There are few community-based neuroepidemiological studies based in tribal communities. This cross-sectional community-based study explored the prevalence rates of neurological disorders in the tribal region of Kaparada in Gujarat. Methodology: A two-stage methodology was used. Door-to-door surveys were conducted in the villages of Moti Vahiyal, Arnai, and Chavshala in Kaparada taluka in the Valsad district. Trained volunteers administered a questionnaire that assessed demographic details and common neurological symptoms in children and adults. Data were obtained from 8217 individuals from 1464 households using the questionnaire in stage 1. A number of 615 individuals reported at least one symptom. In stage 2, a team of neurologists conducted a medical camp to assess those “screened in” for neurological disorders. Results: The crude prevalence rate for neurological disorders in general was found to be 2592.19/100,000. The prevalence rates for lower motor neuron diseases were highest (1010.1), and the rates of epilepsy, movement disorders, stroke, vertigo, headaches, upper motor neuron diseases, and mental and behavioral disorders were found to be 255.6, 133.9, 109.53, 170.38, 511.4, 109.53, and 292.08/100,000, respectively. Age- and sex-specific rates and patterns varied for different disorders. Conclusion: The prevalence rates of most disorders were found to be lower than those reported elsewhere, but age and sex prevalence patterns were similar to existing research. Challenges in conducting such a study in a remote population are discussed.
High Precision Antenna Far-Field Measurement System Based on Pulse Trigger and Closed Loop Control Technology

This paper introduces a kind of high-precision far-field measurement system for antennas, which is based on pulse trigger and closed-loop control technology. The schematic structure and measurement principle of the system is described. In addition, communication methods, precision control and program design are introduced also. All instruments in this system are controlled by program through LAN bus, achieving automatic and remote measurement. Positioning accuracy of this system is less than 0.008°, which is much better than the current industrial standard 0.03°. The good performance and stability of the system are verified through testing and evaluation, indicating the validity of the proposed measurement method and system design strategies.
Spatial-Aware Deep Recommender System

Location recommendation systems are becoming more and more present in our life. In this paper, we propose a novel recommendation model, S-DEEPREC, that utilizes neural networks to jointly learn the locations preferences of users and incorporate the geographical constraints in their preferences. S-DEEPREC utilizes a feed forward neural network to learn the latent factors of users and locations and the interaction between them. Further, we utilize a feed forward neural network with a softmax layer to incorporate geographical constraints in latent factors of locations. We evaluate S-DEEPREC on one of the largest check-in datasets and compare it with existing factorization based recommendation models. The results show that S-DEEPREC performs 10 times better than state-of-the-art recommendation model.
Interactive 3D Building Modeling and Semantic Labeling from VGI Image Data

3D buildings in LoD3 (with façade objects) with semantic information are of great importance for many applications. In this paper, an interactive approach is proposed for 3D building models in LoD3 by using VGI image data. Similar to JSOM, an interactive platform is developed to acquire a façade model with detailed geometries and semantics. Techniques of feature extraction are incorporated in the software, so that a façade can be modeled by only sketching the boundary of the façade and one or two façade objects from one VGI image. The feedbacks of the current Beta version depict that the software is user friendly and can generate 3D façade while labelling façade objects by very few interactive input.
Unscented Kalman Filter Based Single Beacon Underwater Localization with Unknown Effective Sound Velocity

The extended Kalman filter (EKF) is the most widely applied state estimation algorithm for single beacon underwater localization systems. However, since the assumptions of local linearity are often violated during underwater surveys, the EKF is difficult to tune and often gives unreliable estimates. Compared with the EKF, the unscented Kalman filter (UKF) can achieve improved estimation performance for nonlinear systems, while its computational efforts is the same order of magnitude as the EKF. This paper investigates the estimator performance and computational complexity while implementing the UKF based on a novel single beacon localization model with unknown effective sound velocity. Furthermore, the estimator performance while using the iterated EKF, which is an alternative way to reduce the linearization error of the EKF, is also investigated. In addition, the Rauch-Tung-Striebel (RTS) smoother is applied for postprocessing. Through numerical examples of using simulated data, both the filter and RTS smoother results show that while implementing the UKF, the localization accuracy, as well as the estimation of effective sound velocity, can be improved.
Online Informative Path Planning Using Sparse Gaussian Processes

Estimating the environmental fields for large survey areas is a difficult task, primarily because of the field's spatio-temporal nature. A good approach in performing this task is to do adaptive sampling using robots. In such a scenario, robots have limited time to collect data before the field varies significantly. In this paper, we suggest an algorithm, AdaPP, to perform this task of data collection within a constraint on sampling time and provide an approximation of the environmental field. We test our performance against conventional sampling paths and show that we are able to obtain a good approximation of the field within the stipulated time.
Cloud Infrastructure and Monitoring System for Real Estate Registration

Cloud computing has become a prime approach for providing reliable and scalable computing infrastructure for a variety of geographical information applications. This paper reports a cloud infrastructure and monitoring system built for supporting the real estate registration in Yunnan province. Such as system includes the fundamental cloud platform and functionalities as well as the real-time monitoring of underline cloud computing resources including physical and virtual resources. Both programmable Application Programmable Interface (API) and Graphical User Interface (GUI) are provided to users for exploring and developing applications atop the infrastructure. These features provided concrete support to the real estate registration applications. Details of the functionality, modules, deployment, and integration of the system is provided in this paper. While supporting the real estate registration of Yunnan province, the system also sets an example for establishing the future cloud platform for natural resource management in China and many other countries.
Modeling and Control of Two dc-dc Convertes Used in a Resonant Dual Active Bridge

The need for controlling the energy more efficiently has motivated the development of more compact, modular and efficient power converters such as the Dual Active Bridge (DAB). This dc-dc converter has been suggested as an important part of several power conditioning systems, such as the Solid-State Transformer (SST) to control the power flow between two power sources. Several topologies have been suggested to operate more efficiently the DAB as the switching frequency increases. An accurate representation of the DAB is required in order to design the control strategy that regulated the power flow. In this paper two DAB topologies, named: phase-controlled CLLC (Capacitor-Inductor-Inductor-Capacitor) and CLC (Capacitor Inductor Capacitor) Resonant Dual Active Bridge (RDAB), are studied and compared. Extensive time-domain simulations are carry out in order to compare and validate the functionality of each model under different operating conditions.
A Novel Slotted Cavity-Backed Patch Antenna for Dual-Band UHF Applications

A novel slotted cavity-backed patch antenna with defected ground structure (DGS) is proposed in this paper. This slotted cavity-backed antenna is composed of a square patch with a metal square-loop as radiator, a cross-shaped slotted square patch as defected ground structure (DGS) and a metal backed-cavity. Both of the square patch and metal square-loop have four square slots. Simulated results shows that the impedance bandwidth with a return loss better than l0dB is 6MHz at 420MHz and the impedance bandwidth is MHz at 480MHz. The antenna exhibits stable radiation pattern over the operation frequency band. The profile and size of the proposed RHCP antenna are 1.0mm (0.00lλ0) and $\mathbf{77mm\times 77 mm(0.12\lambda_0}\times 0.12\lambda_0)$, both of which are extremely small.
Applying the Kasai to Weather Prediction

The Kasai is an algorithm for processing data series. It organizes the incoming data series as a set of rules and these rules are used to predict the next item in the data series. In this paper, we analyze the ability of Kasai to make reliable predictions. We apply Kasai to predict weather using Weather Underground data and compare Kasai’s performance with standard Weka machine learning algorithms on the same dataset.
A Survey of Recommender Systems Based on Deep Learning

In recent years, deep learning’s revolutionary advances in speech recognition, image analysis, and natural language processing have gained significant attention. Deep learning technology has become a hotspot research field in the artificial intelligence and has been applied into recommender system. In contrast to traditional recommendation models, deep learning is able to effectively capture the non-linear and non-trivial user-item relationships and enables the codification of more complex abstractions as data representations in the higher layers. In this paper, we provide a comprehensive review of the related research contents of deep learning-based recommender systems. First, we introduce the basic terminologies and the background concepts of recommender systems and deep learning technology. Second, we describe the main current research on deep learning-based recommender systems. Third, we provide the possible research directions of deep learning-based recommender systems in the future. Finally, concludes this paper.
Conducted EMC Modeling for EV Drives Considering Switching Dynamics and Frequency Dispersion

This paper provides a modelling method for conducted EMC in EV drive systems with a special emphasis on some non-ideal effects. It is found that the switching dynamics of a power device can be represented as a low-pass multiplier on the spectrum of EMC sources, and the dispersion effect in inductors, capacitors and cables change the frequency response of the conduction path; all of which have impacts on the EMC filter design and can be modelled via two-port networks in the frequency domain.
An Adaptive Partition Method for Handling Skew in Spark Applications

In the parallel computing framework of Hadoop/Spark, data skew is a common problem resulting in performance degradation, such as prolonging of the entire execution time and idle resources. What lies behind this issue is partition imbalance, which causes significant differences in the amount of data processed by each reduce task. This paper proposes a key reassigning and splitting partition algorithm (SKRSP) to handle skew, which considers both the partition balance of the intermediate data and the partition balance after shuffle operator. We design two partition algorithms for different applications: the range-based key splitting partition method (KSRP) for sort operation and hash-based key reassigning partition method (KRHP) for the other operations. We implement SKRSP in Spark 2.2. 0 and evaluate its performance through three benchmarks exhibiting significant data skew: Sort, Join, and PageRank. The experimental results verify that our algorithm not only can achieve a better partition balance but also reduce the execution time of reduce tasks effectively.
Optimal motion planning of autonomous vehicles in three dimensional terrains

A method is presented for optimally planning the motions of autonomous vehicles, considering vehicle dynamics, terrain topography, obstacles, and surface mobility. The terrain is represented by a smooth cubic B patch, and the geometric path consists of a two dimensional B spline curve mapped to the three-dimensional surface. The path is optimized with a parameter optimization procedure, using motion time as the cost function. The optimal motion time along the path is computed by transforming the constraints between the vehicle and ground to limits on vehicle speeds. The optimal speeds which minimize motion time are then obtained below the velocity limits, using the maximum acceleration of deceleration at all times. Examples are presented which demonstrate the method for a simple dynamic model of a vehicle moving on mountainous terrain. <<ETX>>
Genetic resistance of eight native Egyptian chicken breeds having chicken B-cell marker 6 gene post-challenge with field strain of Marek’s disease-induced tumor virus

Aim: The aim of this work was to detect chicken B-cell marker 6 (ChB6) gene in some native breeds in Egypt and find the relationship between founded genes in these different breeds to determine the resistance of native Egyptian breeds of chicken to Marek’s disease (MD). Materials and Methods: A total of 14 different chicken breeds (30 each) including ten native breeds in addition to SPF Lohmann, High Line, Bovans, and Roodiland were used. Blood samples were collected for the detection of (ChB6) by polymerase chain reaction (PCR) assay and sequenced to determine the presence or absence of ChB6 gene. Experimental infection was done using local field isolated MD virus (MDV) of 11 (1 day old) unvaccinated chick breeds having no maternal antibodies against MDV. Ten breeds of them carry ChB6 gene, eight breeds were native, and the rest two breeds were SPF Lohmann and High Line in addition to a group of ChB6 gene-lacking breed (Bovans) were infected. Spleen samples were collected from all infected breeds at 20th, 25th, 30th, 35th, and 40th weeks post-infection and tested by PCR assay for the detection of MDV. Furthermore, at 40th week post-infection, tumorized spleen sample of Bovans breed was collected and prepared for examination by transmission electron microscope (TEM) to confirm the presence of MDV. Results: Our results revealed the positivity of 10 out of 14 breeds (Gimmizah, Sinai, Dandarawi, Fayoumi, Golden Montazah, Matrouh, Beheri, Dokki, SPF Lohmann, and High Line) to the presence of ChB6 gene and resistance to MDV infection, while the Bovans, Mandarah, Inshas and Roodiland breeds lack the ChB6 gene and are susceptible to MDV infection. The collected spleen samples revealed negative for the presence of challenged MDV by PCR in 10 breeds (Gimmizah, Sinai, Dandarawi, Fayoumi, Golden Montazah, Matrouh, Beheri, Dokki, SPF Lohmann, and High Line) and positive for Bovans breed. TEM is used to confirm MDV infection in Bovans group which demonstrated tumors. Conclusion: The study confirms the relationship between the presence of ChB6 gene in our native breeds and the absence of tumors.
Gateway Entry Vector Library of Wolbachia pipientis Candidate Effectors from Strain wMel

Wolbachia pipientis is an intracellular symbiont that modifies host biology using a type IV secretion system to inject bacterial effectors into the host cytoplasm. We utilized a bioinformatics approach to predict Wolbachia effectors and cloned the candidates into an entry vector, which can be utilized for subsequent analyses. ABSTRACT Wolbachia pipientis is an intracellular symbiont that modifies host biology using a type IV secretion system to inject bacterial effectors into the host cytoplasm. We utilized a bioinformatics approach to predict Wolbachia effectors and cloned the candidates into an entry vector, which can be utilized for subsequent analyses.
Numerical Evaluation of AC Loss in NbTi/YBCO Composite Slab under Parallel Field

This paper describes the numerical results of AC loss of LTS/HTS composite superconducting slab, made of NbTi and YBCO conductors by welding together, under external AC magnetic field. The hysteresis loss characteristics of the LTS/HTS composite slab including the losses of its LTS and HTS parts are also discussed under parallel oscillating field.
Diseño e Implementación de un Sistema de Control para un Electrolizador Alcalino

Nowadays, there are important efforts in order to reduce the carbon emissions originated for the human activities. Carbon emissions produced for internal combustion motors used in vehicles is one the main pollutant sources. An option in order to reduce this carbon emission is by means the use of hydrogen mixed with gasoline, this strategy allows obtain the same mechanical power in the motor with a less gasoline volume. Alkaline electrolyzers are a simple and cheap option to obtain hydrogen in order to be used mixed with fossil fuels in internal combustion motors. In this work a control system for a 100 W alkaline electrolyzer is designed. Experimental results obtained demonstrated a 92% efficiency of the power stage designed.
An Efficient Reference Modulation Based Control Strategy for Active Hybrid Energy Management of EVs

In the hybrid energy storage system of electric vehicles (EVs), supercapacitors (SCs) are configured to supplement high frequency power loads to reduce battery strains. Continuous supply and quick response to power load through bidirectional power control is of great importance to attain power balance and keep the stability of bus voltage. In this paper, we propose a reference modulation based power management strategy to tackle this problem. Specifically, an adaptive SCs reference current regulation is designed to maintain sustainable power supply for SCs. A discrete lead compensator based reference smoothing control technique is integrated in to bottom layer control in order for quick transient response to stochastic power demand. With the designed SCs current regulation and reference smoothing technique, we aim to reduce the fluctuation of bus voltage. US06 driving cycles are applied in simulation and experiment to verify the effectiveness of the proposed approach.