Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Structural Optimization Design of Dual-stator Permanent Magnet Motor Using Meshless Technology

In order to overcome the drawbacks of finite element analysis (FEA), including the strong dependence on mesh quality and high computational cost. This research proposed a meshless method for the structural topology optimization of a dual-stator permanent magnet motor. Firstly, taking the Gauss node density distribution as the reference variable and the minimization of model weight as the objective function, the mathematical simulation of the topology optimization subjected considering the displacement constraints is proposed based on the Shepard interpolation approach. Secondly, electromagnetic forces are mapped into the initial three-dimensional structural model for harmonic response analysis employing FEA and the conventional meshless method, respectively. Thirdly, parametric modeling of the motor structure was carried out to determine the optimal design scheme. Finally, compared with FEA calculation results and experimental test results, it can be found that the proposed method can not only guarantee the calculation accuracy, but also reduce the calculation time significantly.
Research on CNN-BiLSTM Power Load Forecasting Based on VMD Algorithm

Electricity load forecasting contributes to the efficient operation of the grid system and plays a vital role in the proper scheduling of energy markets Power load data is affected by its own nonlinearity and a variety of factors, making the forecasting accuracy low. In this paper, we propose a combined prediction method based on the Variational mode decomposition (VMD) of convolutional-bidirectional long- and short-term memory network (CNN-BiLSTM). The raw load data are first decomposed into low-frequency components, mid-frequency components and high-frequency components by VMD, and the input different modal components are feature extracted by the CNN-BiLSTM network, and finally the prediction results of each modal component are reconstructed to obtain the prediction results. The experimental results show that the prediction effect of this method is better than the traditional model, which significantly improves the accuracy and effectiveness of the power load prediction model.
A Hierarchical Optimization Method of Industrial Rectifier Transformer Loss Considering Winding Impedance Matching

Rectifier transformer operating in high current environment suffers from poor power quality and high loss. In order to reduce transformer loss and improve optimization accuracy, this article proposes a hierarchical optimization method considering winding impedance matching for inductive filtering transformer structure design. Firstly, based on the winding arrangement of the inductive filtering transformer, the impedance matching condition and its optimization feasibility are analyzed. Then, combined with the Sobol algorithm, the sensitivity analysis on transformer design parameters is carried out, and the hierarchical optimization model is established. Experimental results show that the hierarchical optimization model successfully provides a global feasible solution by minimizing total loss while effectively improves the accuracy of optimization.
Compensating the biodiversity impacts of land use: toward ecologically equal exchange in the North-South context

xvi Zusammenfassung . xx
Research on LCLC Resonant Converter with Wide Output Voltage Range

To address the problem of narrow output voltage range in DC-DC converters, this paper proposes a high-gain LCLC resonant converter. The proposed resonant converter parallels an LC branch on the primary side of the transformer to replace the excitation inductance of the transformer, and adds a switch to the full-bridge rectification network, making the secondary side possible to switch from full bridge rectification to voltage doubling rectification, expanding the voltage gain range. In contrast to current solutions, this configuration offers notable benefits such as superior efficiency and an extensive range of gain. To achieve a broad spectrum of voltage outputs in the converter, a combination of frequency conversion and phase shifting is employed as a hybrid control strategy. Within this control approach, we delve into the operational procedures, the scope of voltage regulation, and the soft switching conditions of the converter for a comprehensive analysis. Finally, simulation was conducted in MATLAB/Simulink environment to verify the feasibility of the topology structure and control strategy.
Multi-scale contextual information convolutional neural network for structures detection in high-resolution remote sensing image

Structures in high-resolution remote sensing images exhibit multi-scale characteristics. The detection network designed for large-scale objects directly applied to multi-scale structures such as wind turbines and transmission towers does not yield satisfactory results. To solve this problem, this paper proposes a structures detection network using multi-scale context information. Firstly, the VGG network is employed to generate multi-scale feature maps. Medium-sized feature maps are selected, because them contain more information about structures. To strengthen the location information of structures, Convolutional Block Attention Module is used in branches. Then, the feature maps at different scales are contacted together in the channel dimension to integrate multi-scale information. And small size feature maps are not conducive to the detection of structures, so the size of feature maps are increased through deconvolution. Finally, the network can be enhanced the learning of location information by Location Enhance Module. Then, the feature maps are input into RPN network to get the suggested region. The results show that this network has higher accuracy in structure detection compared with Faster Rcnn in remote sensing images.
Current Decomposition in Loop Distribution Network

Loop distribution network attracts growing attentions for its various benefits. A basic problem of this configuration is to formulate the crucial factors that determine the power flow. While related theoretical framework is deficient. This paper formulates the branch currents in single loop distribution network, and decomposes each branch current into a superposition of 2–5 current components, which are the concrete representations of the various factors (e.g., the node current distribution, the loop network configuration, the primary power flow and the power electronic devices). The proposed method can serve as a theoretical framework for some specific problems of a single loop distribution network. For instance, this paper draws two conclusions extra as follows: 1) there is no coupling between the two kinds of line losses generated respectively by the transporting current and the interior current; 2) the arrangement of a single series compensation maybe fail to guarantee an economic branch current distribution.
Investigation of Losses in Regenerative Testing for a 240-kW Sectored Dual-Three-Phase PMSM

Regenerative testing (RT) as an indirect test method is increasingly attractive in high-power multiple three-phase motor applications since no additional mechanical load is needed. However, the RT may bring additional losses, which cause an abnormal temperature rise in the motor. This paper investigates the losses under RT conditions for a 240-kW sectored dual-three-phase surface permanent magnet synchronous motor (SPMSM). First, the distorted air-gap magnetic field generated by the phase difference between the currents of each set of windings under RT conditions is analyzed. Then the resulting additional losses are calculated, which shows that the losses of the permanent magnets (PMs) are the main additional losses under RT conditions. Finally, the validity of the analysis is demonstrated by the comparison of the calculated losses and the experimental results.
Estimation of 2D-DOA for Multiple Frequency Hopping Signals Based on Blind Source Separation

In order to realize two-dimensional direction of arrival (DOA) estimation of multiple frequency hopping signals, a two-dimensional DOA estimation algorithm based on underdetermined blind source separation is proposed. Firstly, multiple frequency hopping signals are received through L-shaped array antenna, and STFT&WVD combined time-frequency method is used for time-frequency transformation operation to improve time-frequency resolution and cross term suppression ability of time-frequency map. Then, single time-frequency source points are detected by using azimuth angle difference of each source's frequency hopping signals. Finally, improved K-means clustering algorithm is used to complete time-frequency single source point and frequency hopping rate clustering of each source's frequency hopping signals, The mixed matrix is calculated according to the hopping frequency and the corresponding time-frequency single source point, so as to realize the azimuth and pitch angle estimation. The simulation results show that under the condition of low signal-to-noise ratio, the algorithm has high precision of two-dimensional DOA estimation, good robustness and certain anti noise ability.
Research on credit-risk models via machine-learning algorithms and logistic regression for predicting CBA consumer behaviour

Start with the pre-screening of a possible application and continuing through the account's administration during its life and potential write-off, risk assessment techniques are used to handle things a borrower's account. Typically, a logistic regression model is used to estimate how risky it is to lend money to a credit applicant. However, researchers have also looked at a variety of other classifiers, and while early results indicate that support vector machines are the most accurate, practical implementation of these results from the lab may be hampered by issues with data quality. With a regression-based R2 values of forecasted/realized tardiness of 85%, this article generates out-of-sample predictions that greatly increase the categorization rates of credit-card holder defaults and delinquencies. We estimate the cost reductions to range from 6% to 25% of total losses using conservative estimates for the costs and benefits of reducing credit lines based on machine-learning projections.
Rotor Spherical Region Location of Permanent Magnet Spherical Motor Based on Improved Random Forest

Real-time acquisition of rotor position information is a prerequisite for closed-loop control of spherical motors. The Hall effect sensor array based on the quadrature triangle model can locate the rotor position in the spherical intervals. Increasing the number of sensors can make the spherical area more precise, and thus the positioning accuracy is improved, but it is limited by the installation space and hardware circuit complexity. Therefore, without increasing the number of sensors, this paper introduces a Random Forests (RF) algorithm to improve the accuracy of identification. Based on the results of spherical interval identification, the RF algorithm can reduce the amount of data by one or two orders of magnitude. By combining these two methods, the speed of interval recognition and the high accuracy of machine learning algorithms are fully utilized. To reduce the interference of bad data and improve the data processing capability, an Improved Random Forests (IRF) algorithm is proposed. Finally, the proposed algorithm is experimentally validated. The maximum positioning error is only 0.6°, which is a low-cost and high-precision spherical motor position recognition solution.
CLLLC resonant converter compound control for optical storage system

Energy storage is one of the ways to absorb renewable energy and reduce its fluctuation. CLLLC resonant converter is used in optical power generation energy storage system in this paper. In this paper, the voltage-current double-loop control strategy of the battery current inner ring is adopted, and the compound control combining frequency conversion control and phase shift control is adopted to enable the converter to provide channels for charging and discharging energy storage batteries. Within the entire input range, the switch tubes can achieve both zero voltage switching (ZVS) and zero current switching (ZCS). This paper analyzed the working state and characteristics of the converter under two control schemes. Finally, using MATLAB/ Simulink simulation platform to verify the accuracy of theoretical analysis and the validity of the control method.
Trade and growth: a simple model with not-so-simple implications

We present a simple dynamic model of international trade and growth. Our equations linking exogenous and endogenous variables do not resemble those estimated by the empirical literature: Ours are not linear, despite the fact that our model is linear, they do not include variables used in this literature and include variables that have never been used in this literature.
Implementation And Evaluation of Gamiﬁcation Elements In An E-learning Platform For Engineering Education

E-learning and online courses are widely used today, with different platforms being available for the user. When implementing and evaluating such a platform relevant research is required, therefore a pre-study was conducted. The pre-study showed that the platforms used at Linköpings University have a variety of available platform of which the teachers can use, however, some of there lack the features and it is therefore common for teachers to use more than one platform for a course. The goal of the thesis has been to answer the research question and to do so a platform was implemented, with focus on the gamiﬁcation elements. The thesis answered the research question through the implementation of the platform and the user test. The user test was held on the target audience. The participants of the user test were faced with a short course on the developed platform. The test results show that the combination of gamiﬁcation elements used motivated the participants towards the presented course and the assignments within it. During the user test a questionnaire, based on Intrinsic Motivation Inventory , was used. The result from this showed that the platform and its gamiﬁcation elements increased the enjoyment, interest, perceived competence and effort towards the course.
Equity Incentives, Audit Opinions, and Annual Report’s tone: An Analysis Based on Text Information

This paper takes the listed companies in 2011-2021 as the initial sample to study the impact of equity incentive on the annual report’s tone, and uses the management expense rate and audit opinion as moderating variables to study the role of equity incentive in the annual report’s tone. Research has found that when companies implement a certain degree of equity incentives, the tone of their annual reports is more positive. Further research has found that the effect of equity incentives on the tone of annual reports is influenced by the management expense ratio and audit opinions. Combining the implementation of equity incentives for executives with the annual report information of the company helps to deeply explore the macro overview of the company's corporate behavior under the implementation of incentives for executives on its current and future development, providing a new perspective for understanding the decision-making and planning of listed companies.
Into the Third Dimension: Architecture Exploration Tools for 3D Reconfigurable Acceleration Devices

Recent chip integration processes enable 3D stacking of multiple active dice in the same package, offering higher logic density, lower power consumption, and significant die-to-die bandwidth. Field-programmable gate arrays (FPGAs) can benefit from 3D chip integration either by stacking multiple homogeneous FPGA fabrics to increase logic capacity or by integrating with other heterogeneous application-specific integrated circuits (ASICs). This opens up a myriad of research questions and interrelated design choices. However, we lack the tools necessary to model these 3D reconfigurable devices and quantitatively explore their vast design space. In this work, we enhance existing FPGA architecture exploration tools and build new ones to address this gap, with a cross-stack focus on circuit-level fabric modeling, 3D integration considerations, system-level architecture, and computer-aided design (CAD) tools. We extend the RAD-Gen framework by integrating an upgraded version of the COFFE automatic transistor sizing tool that supports 7 nm FinFETs with a more accurate, metal-aware area model for newer process technologies. We also implement new tools in RAD-Gen for modeling the inter-die connections and power distribution networks of 3D architectures. In addition, we introduce a new version of the Versatile Place & Route (VPR) tool that can model 3D devices, with enhancements to its architecture description language and its placement and routing engines. Finally, we showcase the capabilities of our enhanced tools by modeling and evaluating both homogeneous and heterogeneous 3D reconfigurable devices.
Logical and Complexity-theoretic Aspects of Models of Computation with Restricted Access to Arrays

We study a class of program schemes, NPSB, in which, aside from basic assignments, non-deterministic guessing and while loops, we have access to arrays; but where these arrays are binary write-once in that they are initialized to ‘zero’ and can only ever be set to ‘one’. We show, amongst other results, that: NPSB can be realized as a vectorized Lindstrom logic; there are problems accepted by program schemes of NPSB that are not definable in the bounded-variable infinitary logic L∞ωω; all problems accepted by the program schemes of NPSB have asymptotic probability 1 and on ordered structures, NPSB captures the complexity class LNP. We give equivalences (on the class of all finite structures) of the complexity-theoretic question ‘Does NP equal PSPACE? ’, where the logics and classes of program schemes involved in the equivalent statements define or accept only problems with asymptotic probability 0 or 1 and so do not cover many computationally trivial problems. The class of program schemes NPSB is actually the union of an infinite hierarchy of classes of program schemes. Finally, when we amend the semantics of our program schemes slightly, we find that the classes of the resulting hierarchy capture the complexity classes Σpi (where i≥2) of the Polynomial Hierarchy PH.
New Prairie Press New Prairie Press

This study explores how spirituality in workplaces is contextualized in South Korean startups. With the unprecedented development of technology, new small-sized ventures, so-called startups have emerged as the major drivers in today’s global market (Schwab, 2017). The disruptive changes that startup creates in the market imply the growing needs of both organizations and individuals to be more adaptive to the given changes. Backing up these trends, an increasing amount of new consumers’ needs is fulfilled through innovative breakthrough, possibly only temporarily, at the expense of tremendous stress that individual employees at startups suffer from. Nonetheless, to survive through the volatile market, secure the competitive edge of the fast-paced industry as well as to create an inclusive work environment, numerous startups emphasized entrepreneurial orientation as well as team spirit. Here, entrepreneurial orientation means the ideation and implementation of new ideas as well as the exploration of new business opportunities. Additionally, team spirit refers to team members' attached feelings to commit themselves to their team's shared goal. The emphasis on the spiritual dimension of entrepreneurship and teamwork aligns with the "spiritual movement”(Ashmos and Duchon, 2000). Based on the paradigm shift in organization science, which leads to the empowerment of individuals by prioritizing employee's work-life balance, spirituality in workplaces has gained much attention in the early 2000s. This movement aims to make the workplace more inclusive so that spirituality enhances individual employees' well-being, highlights their self-existential meaning in workplaces, and deepens the understanding of interconnectivity with others (Karakas, 2010; Houghton, Neck and Krishnakumar, 2016). Despite the debate over defining spirituality, a plethora of empirical studies have substantiated the positive effect of spirituality at workplaces, especially regarding the link between spirituality and performance/productivity (Giacalone and Jurkiewicz, 2003; Duchon and Plowman, 2005; Rego, Cunha, Souto, 2007; Petchsawang and Duchon, 2012). As the efforts that South Korean startups have exhibited to link this ‘spirit’ discourse to their productivity aligns with the aforementioned spiritual movement in workplaces, this study is designed to seek an answer to the fundamental question around this matter; does the emphasis on ‘spirit’ positively influence the perceived productivity in South Korean Startups? To corroborate this link, this study explores the mediating effect of team spirit in the relationship between entrepreneurial orientation and the team's performance towards the South Korean startups. Based on the analysis of 240 responses from 66 startup teams, this study concludes that team spirit fully mediates the positive association between entrepreneurial orientation and team productivity. The conclusion also suggests the organizational development strategy to build a more inclusive workplace for startup employees.
Design for Cloud Learning Platform Integrated Office Management to Support the Adjustment of the Industrial World During the Covid-19 Pandemic

The role of organizations, businesses, and governments in achieving their goals is largely determined by the roles and functions of services and the implementation of activities through an office. The work environment during the COVID-19 pandemic experienced changes to employees in a company or organization. The impact of this is that during the Covid-19 pandemic the implementation of work from home for employees is expected to be able to maintain performance, this is evident from parts of the office such as archives, documents, and finance which are still not standardized and have significant shortcomings. not in accordance with the needs of the industrial world. Based on this context, the research team initiated the development of an office administration simulation system based on cloud integrated learning which is present as an innovation that directly answers the needs in the field based on simulator applications. This application was developed using the method design thinking process, with several stages, namely empathize, define, ideate, prototype, and test. The results of the development carried out include several features such as the homepage, levels, regions, office practicum role playing, evaluation, learning management system, and features virtual office. After the media has been developed, the media is validated by material experts with the criteria for the presentation aspect of the simulation with an average score of 5 with very appropriate and effective criteria. After that, media expert validation was carried out with media presentation aspects with an average of 4.7 with appropriate and effective criteria.