Miracle-dz/UniFAR-FTUs huggingface dataset:
The Virtual Wheel Concept for the Singularity-Free Kinematics and Dynamics Modeling and Control of Pseudo-Omnidirectional Vehicles

Pseudo-omnidirectional vehicles (POV) are equipped with several center steered and driven standard wheels, and exhibit high maneuverability and positioning accuracy. Yet this class of mobile systems is rarely considered. Despite their simple setup, the mathematical modeling is challenging. Moreover all models presented so far suffer from artificial singularities (due to a particular parameterization), which is often tackled with switching strategies. This is a critical issue as the model is the basis for simulation, motion planning, control, and design. In this letter, a novel modeling concept is introduced which is singularity-free and does not rely on a switching strategy. Its application to kinematics and dynamics modeling of general POV is presented. Closed form solutions for the traction forces and drive torques are presented. These solutions account for the practically relevant situation of non-exactly aligned wheels. This model serves as basis for optimal path planning and model-based control. Simulations are reported showing the robustness and applicability of the concept.
Performance Enhancement of PV System Configurations Under Partial Shading Conditions Using MS Method

The study of this work is to highlight the key metrics of various topologies in terms of output power, Fill Factor (FF), Mismatch Losses (ML) and efficiency. The idea behind this work is to analyze and obtain the performance of different topologies under various shading patterns. The major problem which comes across the path of Photovoltaic (PV) system performance is partial shading. The solution to this problem is to reconfigure the panels to achieve better results under shading conditions. For this, different configurations such as Series Parallel (SP), Total Cross Tied (TCT), Physical Relocation of Module with Fixed Electrical Connections (PRM-FEC), SuDoKu and Magic Square (MS) has been discussed, analyzed and compared using MATLAB/SIMULINK. Simulation approach is used to describe the working and evaluation of all configurations. By the results obtained, it is clearly visible that MS method have achieved largest output power of 2877 W, highest efficieny of 10.24 %, FF is 0.481 and lowest ML of 772 W among all the configurations under Long Narrow (LnN) pattern.
Scalable Designs for Reinforcement Learning-Based Wide-Area Damping Control

This article discusses how techniques from reinforcement learning (RL) can be exploited to transition to a model-free and scalable wide-area oscillation damping control of power grids. We present two control architectures with distinct features. Performing full-dimensional RL control designs for any practical grid would require an unacceptably long learning time and result in a dense communication architecture. Our designs avoid the curse of dimensionality by employing ideas from model reduction. The first design exploits time-scale separation in the generator electro-mechanical dynamics arising from coherent clustering, and learns a controller using both electro-mechanical and non-electro-mechanical states while compensating for the error in incorporating the latter through the RL loop. The second design presents an output-feedback approach enabled by a neuro-adaptive observer using measurements of only the generator frequencies. The controller exhibits an adaptive behavior that updates the control gains whenever there is a notable change in the loads. Theoretical guarantees for closed-loop stability and performance are provided for both designs. Numerical simulations are shown for the IEEE 68-bus power system model.
Research on Performance Evaluation of Autonomous Underwater Vehicle’ Path Planning in Complex Scenes

Aiming at the problems of lack of operation for path guidance in complex scene, difficulty in quantifying evaluation index of path planning, and over idealization of evaluation results, this paper analyzes the common working conditions faced by autonomous underwater vehicle in complex scene, establishes a complete quantitative evaluation index model, uses analytic hierarchy process (AHP) to weight the index, and proposes an improved cloud-gravity-center evaluation method, the expert evaluation method transforms the fixed comment set of cloud model into the quantitative score of path planning’ effectiveness in complex scenarios, and improves the A* algorithm based on the energy cost of yawing in the evaluation index model, based on the complex scene, the effectiveness evaluation of the path before and after the improvement of A* algorithm is carried out. The simulation results show that the method is practical in unstructured scene, and the analysis of evaluation results can effectively guide path planning for task of autonomous underwater vehicle, and has high application value.
Identity Division Multiplexing Based Location Preserve in 5G

Protection of the user is the one of primary points within the coming of 5G portable communications. Area protection has recently been broadly tended to within the writing as crucial tricky issues for the client security. The area protection has moreover been tended to in realeases in versatile eras guidelines. In LTE release 13, the proposal is to utilize pseudonyms such as Cell Radio Network Temporary Identifiers (C-RNTI) rather than permanent identity for protecting area security. The point of this paper is to assess the 3GPP security design and propose a protection capability for protecting area security of the 5G design. The proposed strategy is based on presenting modern variable nom de plumes that can supplant the settled Cell- Radio Network Temporary Identifier (C-RNTI) and in cruel times keep up the compatibility with the standard. The proposed arrangement employments an Identity-Division Multiplexing (IDM) strategy to guarantee the unlinkability and untraceability of the client and to avoid aggressors from following or distinguish clients through C-RNTI personalities. The plot gives secure and viable area administration regarding the security of client security in 5G. The conspire is formally confirmed of satisfactory ensure of user’s area security assurance by utilizing ProVerif.
Machine Learning Migration for Efficient Near-Data Processing

Machine Learning (ML) rises as a highly useful tool to analyze the vast amount of data generated in every field of science nowadays. Simultaneously, data movement inside computer systems gains more focus due to its high impact on time and energy consumption. In this context, the Near-Data Processing (NDP) architectures emerged as a prominent solution to increasing data by drastically reducing the required amount of data movement. For NDP, we see three main approaches, Application-Specific Integrated Circuits (ASICs), full Central Processing Units (CPUs) and Graphics Processing Units (GPUs), or vector units integration. However, previous work considered only ASICs, CPUs and GPUs when executing ML algorithms inside the memory. In this paper, we present an approach to execute ML algorithms near-data, using a general-purpose vector architecture and applying near-data parallelism to kernels from KNN, MLP, and CNN algorithms. To facilitate this process, we also present an NDP intrinsics library to ease the evaluation and debugging tasks. Our results show speedups up to $10\times$ for KNN, $11\times$ for MLP, and $3\times$ for convolution when processing near-data compared to a high-performance x86 baseline.
Upgrade and Commissioning of the SULTAN Facility to Host Quench Experiments on HTS High Current Conductors

High Temperature Superconductors (HTS) are promising materials for future fusion magnets. One of HTS conductors' main issues is the quench protection: the quench develops much slower than in LTS, delaying the quench detection by voltage monitoring and causing a massive temperature increase before detection. The Swiss Plasma Center (SPC), with the support of EUROFusion, has upgraded the SULTAN facility to test large current conductors during the whole quench evolution. The 100 kA superconducting transformer has been replaced by an 18 kA direct power supply, which allows sustaining the operating current in the sample during a quench. Five HTS conductors have been manufactured at SPC: they are sub-size of the HTS high-current cables designed by the group for an HTS high current high field cable proposed for EU-DEMO Central Solenoid (CS) hybrid magnet. Every conductor has a specific feature. The aim is to compare the quench behavior of the five conductors “parametrically”. The commissioning of the upgraded facility and the preliminary results of the measurements are presented in this work.
Leader-following consensus of nonlinear multi-agent systems based on position and velocity estimations

In this paper, leader-following consensus problem of nonlinear multi-agent systems is studied. In order to obtain control law in multi-agent systems, usually agents’ information should be exactly known, which may not be available in real applications. In this work, a method is proposed to estimate the position and velocity of agents with arbitrary initial conditions of followers and leaders. Then, the estimations are used to obtain a consensus control law. At first, a single integrator nonlinear multi-agent system with a leader is considered, and a consensus law is proposed using followers’ position estimations. Then, for a double integrator nonlinear system, a controller is obtained based on position and velocity estimations. Several simulations are performed to validate the proposed method.
Spontaneous Enhancement of Power Conversion Efficiency in SnO2-Based Dye-Sensitized Solar Cells

Power conversion efficiency (PCE) of SnO2-based dye-sensitized solar cells (DSSCs) is reported to increase slowly over a period of days after their fabrication. Thus far, underlying processes involved in this slowly increasing phenomenon of PCE are not understood. In this article, we investigate the spontaneous enhancement of PCE in SnO2-based DSSCs and the underlying mechanism by using the X-ray diffraction, the X-ray photoelectron spectra (XPS), electrochemical impedance spectrum, and first-principles calculations. The Sn 3d and O 1s binding energy are observed to shift toward low binding energy over time by the XPS measurements, and the ratio of O/Sn on the surface of SnO2 increases from 1.9 to 2.1 implying the adsorption of oxygen atom on the surface of SnO2. Our first-principles calculation results confirm that a shift-up in the conduction band minimum of SnO2 owing to its adsorption of oxygen atom. We, therefore, attribute the slowly increasing phenomenon of PCE to oxygen adsorption effect on the surface of SnO2. This article gives a comprehensive understanding of the surface oxidation effect on the PCE enhancement in DSSCs and provides an effective way to fabricate DSSCs based on oxide semiconductors with good performance and long-time stability.
Experimental Study of Parylene Based Capacitive Humidity Sensor for Integrated Thermal Comfort Sensing Application

In this letter, we report the temperature effect and noise characterization of the Parylene-based capacitive humidity sensor which can be used for integrated CMOS compatible thermal comfort sensing. The sensor is comprised of a pair of interdigitated Pt electrodes deposited on a silicon substrate and a parylene hygroscopic layer coated on the electrodes using room temperature chemical vapor deposition process. The sensor was characterized at different relative humidity (RH) values and working temperatures in a testing setup. The capacitance of the sensor increases with the RH due to the absorption of water molecules on the surface of the sensing film. The capacitance of the sensor also increases with temperature, which is due to the stronger thermal movement of the molecules that helps increase the polarization at increased temperature levels. Besides, a readout circuit was done on a printed circuit board using capacitance to voltage converter for the sensor. The sensor achieved a maximum sensitivity of 76.2 mV/%RH and response and recovery times of about 31.5 and 29.2 s, respectively. Besides, the sensor shows a noise level of 1.399 mV rms within 25 Hz bandwidth in the output voltage response. The experimental results also indicated a resolution of about 0.072–2% within the ASHRAE standard approved RH range (25–95%) for the fabricated sensor.
Analysis and Comparison of Various Islanding Detection Schemes for DC Microgrids

Islanding detection is a critical issue in the case of AC and DC microgrids (MGs). If the islanding detection technique fails, it may lead to instability in the system. This can affect the load side devices as well as consumers. Many methods have been proposed to detect islanding on AC MGs. Nowadays, the researchers focus on DC MGs islanding detection schemes (IDSs) as the number of converters in DC MGs is reduced significantly. This also leads to reduce total conversion losses to achieve improved efficiency. A current injection-based active islanding detection scheme (IDS) is proposed to detect islanding in DC MGs. This paper compares three passive IDSs, namely under/over voltage (UOV), change in impedance (CII), and rate of change of power (ROCOP) based passive IDSs with the proposed current injection-based active IDS. The performance of these techniques is compared in terms of detection time and the effectiveness during different non-islanding cases. The performance and effectiveness of the proposed IDSs are verified and compared with the help of hardware set up and dSPACE DS1104 controller.
Multi-Task Deep Network for Semantic Segmentation of Building in Very High Resolution Imagery

Building extraction from very high resolution (VHR) imagery plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. The automatic generation of buildings from satellite images presents a considerable challenge due to the complexity of building shapes. Compared with the traditional building extraction approaches, deep learning networks have shown outstanding performance in this task by using both high-level and low-level feature maps. Recently, many deep networks derived from U-Net has been extensively used in various buildings segmentation tasks. However, in most of the cases, U-net produce coarse and non-smooth segmentations with lots of discontinuities. To improve and refine the performance of U-Net network, we propose a deep end-to-end network, which use a single encoder and two parallel decoders along with performing the mask predictions also perform distance map estimation. The distance map aid in ensuring smoothness in the segmentation predictions. We also propose a new joint loss function for the proposed architecture. Experimental results based on public international society for photogrammetry and remote sensing (ISPRS) datasets with only (RGB) images demonstrated that the proposed framework can significantly improve the quality of building segmentation.
Design of Box Culvert in Iraqi Highways Considering Catchment Areas

In Iraq, the infrastructures are developing rapidly, so it is necessary to consider the hydrology of the developed catchment before constructing any drainage facilities such as culvert to prevent traffic disruption during rain. In this study, sizing of box culvert for highways in Iraq is proposed using rational method for determination of peak runoff from small catchment (less than 3 km2). Rainfall depth was used to derive the intensity duration frequency curve, and then the rainfall intensity was found. However, soil conservation service curve number (SCS-CN) was used in the estimation of peak runoff from catchment with size ranging from 3 to less than 30 km2 using the soil classification and the curve number. HY-8 computer software was used for sizing square and circular sections. Circular sections were also calculated. The appropriate sizes for square sections in large basins are 3 m to 4 m and 2 m to 2.9 m for more than 114 m3/s and 32 m3/s respectively, but for circular sections, diameters were 4.1m, from 3 m to 3.8 m and from 2.5 m to 2.9 m under flow rates more than 160 m3/s, 68 m3/s and 25 m3/s respectively. However, for small basins, square sections sizes were 3m to 3.1m and 2 m to 2.7 m for flow rates more than 23 m3/s and 8 m3/s respectively. Diameters for circular sections were 3 m to 3.2 m and 2 m to 2.9 m under flow rates 23 m3/ s and 8 m3/s respectively.
Contagion of fear: Is the impact of COVID‐19 on sovereign risk really indiscriminate?

Abstract This paper investigates the impact of infectious diseases on the evolution of sovereign credit default swap (CDS) spreads for a panel of 77 countries. Using annual data over 2004–2020, we find that infectious‐disease outbreaks have no discernible effect on CDS spreads, after controlling for macroeconomic and institutional factors. However, a granular analysis using high‐frequency data indicates that the COVID‐19 pandemic has had a significant impact on CDS spreads. This adverse effect appears to be more pronounced in advanced economies, which may reflect the greater severity of the pandemic and depth of the economic crisis in these countries, at least during the initial stage of the outbreak, as well as underreporting in developing countries due to differences in testing availability and institutional capacity. While more stringent containment measures help lower sovereign CDS spreads, the fiscal burden of these efforts could undermine credit worthiness and eventually push the cost of borrowing higher.
The Scenario of Wikipedia Usage as a supporting source for under-resource language researches

Atualmente, a Wikipedia se tornou a maior e mais importante coleção de dados abertos na Web. Também houve um aumento significativo no uso de artigos da Wikipedia como referência em artigos científicos e relatórios de pesquisa. Neste artigo, revisamos projetos de pesquisa no campo da technologia da informação que mais se beneficiaram com o surgimento da Wikipedia. Em Seguida, descrevemos o cenário de uso da Wikipedia no desenvolvimento do silabificador javanês e sistema de identificação de Idioma. Também descrevemos a participação da comunidade Javanêsa de Wikipedia na anotação dos caracteres Javanêses.
First record of late Campanian paleoceanographic and paleoclimatic changes, Arabian Platform, Mazidag-Mardin area, SE Turkey

The sedimentology, geochemistry and paleontology of the pelagic upper Campanian Maastrichtian Bozova Formation in the "Mazidag" (Mazıdağı) Mardin area, SE Turkey, reveal paleoceanographic and paleoecological changes for the first time. A 119.25 m-thick composite stratigraphic section is characterized by alternating marls, clayey limestones, shales, and black shales; no coarse siliciclastic admixture or turbidite intercalations were recorded in the section. Biostratigraphic data indicate the presence of the Radotruncana calcarata Zone, and the UC15de/UC16 nannofossil zones. Stable isotope and elemental geochemical analyses have been carried out in the studied section. The isotope curves display similar patterns compared to reference curves from European and Chinese basins in the same interval. The prominent negative carbon isotope excursion determined in the upper interval can be correlated with the Late Campanian Event. Proxy elements display generally two relative rising trends in productivity from the lower part and the middle part of the succession. The lower part of the section records relatively more dysoxic/anoxic conditions and coincides with common black shale beds. The presence of both diverse planktonic foraminifera and calcareous nannofossils in the studied interval indicates a fully marine, warm-water, low-latitude Tethysian oceanic environment. In addition, the plant fossils derived from the nearby land mass indicate that a tropical humid climate was similar to that in northeast Australia. Therefore, warm water, tropical humid atmospheric conditions developed in the studied area causing the rise in productivity, precipitation and transportation of plant debris into offshore environments.
A New Set Covering Controller Placement Problem Model for Large Scale SDNs

Software Defined Network (SDN) is an emerging architecture that can overcome the challenges facing traditional networks. SDN enables administrator/operator to build a simpler and manageable network. New SDN paradigms are encouraged to deploy multiple (rather than centralized) controllers to monitor the entire network. The controller placement problem is one of the key issues in SDN that affect all its aspects including scalability, convergence time, fault tolerance, and node to controller latency. Many researchers focus on solving this problem by trying to optimize the location of an arbitrary number of controllers. The related works in this area get less attention to two following important issues: i) Bidirectional end-to-end latency between the switch and its controller instead of propagation latency and ii) finding the minimal number of controllers, which is a prerequisite for locating them. In this paper, we propose a Set Covering Controller Placement Problem Model (SCCPPM) in order to find the least number of required controllers with respect to carrier-grade latency requirement. The proposed model is carried out on a set of 124 graphs from the Internet Topology Zoo and solve them with IBM ILOG CPLEX Optimization package. Our results indicate that the number of required controllers for high resilient network is dependent on topology and network size. Moreover, to achieve carrier-grade requirement, 86% of topologies must have more than one controller.
Investigation and Comparative Study of 12/16 C-core and Conventional Radial Flux Switched Reluctance Motor under Coil Fault Conditions . (Dept. E)

HE major driving force in the development of electrical vehicles for urban transport is the environmental and economic issues. Traction motor selection is a key component of EV. With rapid transportation transition, it increases substantial awareness of the parameters used in the selection of motors. Switched Reluctance (SR) motors are currently used in a variety of applications in the sectors of EV, electrical aircraft, renewable energy, domestic appliances, and wind turbines [1,2]. Because of SRM provides simple structure, robustness, high starting torque, fault tolerance, high speed operation and low manufacturing costs [3-
Factors Affecting Smartphone Purchase Intention of Consumers in Nepal

The main aim of this research paper is to identify the factors that influence smartphone purchase intention in the Nepalese market. The study identifies how the brand personality, attribute factors, and the price factor influence the purchase intention of a smartphone. The paper puts the emphasis on how the consumer preference functions in the selection of the smartphone and which factor plays the more significant role in smartphone purchase intention. This research paper has used primary data and a 7-point Likert scale survey questionnaire. The primary data has been collected through a structured survey questionnaire by using convenient sampling technique from 294 smartphone users in the Kathmandu Valley. Descriptive statistics, Correlation Analysis and Structural Equation Modeling (SEM) have been carried out to analyze the primary data using the SPSS AMOS 24. Brand personality, attribute factor, and product price were taken as independent variables to identify the impact on purchase intention. The result of the regression path analysis showed that brand personality has no significant effect on purchase intention in the purchasing of smartphone. It is also found that the product attributes and product price have a significant influence on consumer purchase intention of a smartphone in Nepal.