Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal design of a low cost 20kW 99.1% efficiency active ZCS isolated dc-dc converter

The paper presents the optimal design of an innovative very high efficiency isolated dc-dc power converter topology. In terms of efficiency and ease to control, it overperforms resonant dc-dc converters from the literature. High efficiency and low cost are obtained by operating low cost IGBT without switching losses with a power factor close to optimal. It is particularly well suited to be employed as module to make low and medium voltage isolated ac/dc converters or fast DC chargers. A variant of the topology allows bidirectional power flow, which enables the efficient and cost effective integration of renewable energies and energy storage into the medium voltage grid. Used as a solid state transformer, it allows higher efficiency than the classical ac distribution transformer and the authors consider it as an enabler for hybrid ac-dc and dc grids.
Routing with Renewable Energy Management in Wireless Sensor Networks

In Wireless Sensor Networks (WSNs), the power consumption is an important aspect when designing routing protocols. When compared to other components of a sensor node, the power required by radio transmitters is responsible for most of the consumption. One way to optimize the energy consumption is by using energy-aware protocols. Such protocols take into consideration the residual energy information (i.e., remaining battery power) when making decisions, providing energy efficiency through the careful management of energy consumption. In this work, we go further and propose a new routing protocol that uses not only the residual energy information but also the available renewable energy information from renewable energy sources such as solar cells. We then present the REBORN (Renewable Energy-Based Routing) algorithm, an energy-aware geographic routing algorithm, capable of managing both the residual and the available energy. Our results clearly show the advantages and the efficiency achieved by our REBORN algorithm when compared to other proposed energy-aware approaches.
Handling User Cold-Start Problem for Group Recommender System Using Social Behaviour Wise Group Detection Method

With the accessibility to information, users often face the problem of selecting one item (a product or a service) from a huge search space. This problem is known as information overload. Therefore to help them in searching items on internet we propose a recommender system which recommends items on social networking site considering group members opinion. An important issue for the RS that has greatly captured the attention of researchers is the new user cold-star problem, which occurs when there is a new user that has been registered to the system and no prior rating of this user is found in the rating table. In this paper, items will be recommended to the group of user having similar interest and liking. Thus, the proposed system implements the advanced recommendation model in which users will satisfy in multiple ways. Recommendation will be done in two ways, individual recommendation and group recommendation. Individual recommendation contain preference wise recommendation and group recommendation contain similar profile wise and social behavior wise recommendation. So, both individual as well as group recommendation will be there. So for group recommendation, we propose two automatic group detection method i.e. similar profile wise and social behavior wise. Social behavior wise group detection method is used to avoid the cold-start problem, which also reduce the overhead as well as increase the accuracy. The experimental results indicate that social behavior wise group detection method achieves better accuracy and computation time than the relevant methods. In any case user will get the recommendation as per his likings.
Detailed Design Procedures for Low-Speed, Small-Scale, PMSG Direct-Driven by Wind Turbines

This paper is dedicated to demonstrate step by step procedures used to design a permanent magnet synchronous generator (PMSG) for small-scale, low speed applications. The main target of this work is the generator directly connected to the prime mover and in the fractional or few kilowatts range. A linear lumped-element-based model is presented, which is used for basic analysis and design. Then, a proposed complete design procedure - asserted with equations, tables, design limits and practical recommendations - are detailed. Also, a flowchart is developed to be later used as a Matlab M-file code for PMSG design with specific requirements. The design procedures are then validated using different techniques including: a) Finite Element Method (FEM) using Maxwell software, through different case studies, b) results comparison with different available generators from both research work and commercial one, and c) experimental results obtained from actual prototype machine implemented by the authors. Such comparisons have validated the proposed procedures as a contributed step-by-step simple and reliable design tool for such cluster of PMSGs.
The Loss Characteristics of PSFB ZVS DC-DC Converter Applied to the Auxiliary Power System

In this paper, the operation control and loss characteristics of a PSFB (Phase-Shifted Full-Bridge) ZVS DC/DC converter applied to auxiliary power system has been investigated. The working characteristics, device losses and system efficiency of the PSFB (Phase-Shifted Full-Bridge) circuit topology for 1500Vdc power supply using 3300V Si IGBT are studied. One type of ISOP (Input-Series Output-Parallel) double bridge topology using 1700V SiC MOSFET is proposed. The improved input voltage sharing control method is used to meet the requirements of the supply voltage and system capacity and it also improves the system’s rapidity and stability. The 1700V Si IGBT and the 1700V SiC MOSFET used in ISOP PSFB converter are compared on the control, losses and efficiency. Simulation and experiment results show that the application of SiC devices exerts a positive effect on the volume reducing, weight decreasing and efficiency increasing.
Extended EMF-based Simple IPMSM Sensorless Vector Control Using Compensated Current Controller

Vector control of an interior permanent magnet synchronous motor (IPMSM) without the magnetic pole position sensor has been studied. Especially, the extended electromotive force (EMF) based method is one of the famous systems. We proposed a simple method which estimates the magnetic pole position using the output voltage of the d-axis PI current controller without using disturbance observer. In this paper, we develop the early proposed method by introducing a new non-interference control. By the results of simulation and experiment, we have improved the magnetic pole position error in the rotor speed ramp responses.
Designing for Friendship: Modeling Properties of Play, In-Game Social Capital, and Psychological Well-being

Players are increasingly viewing games as a social medium to form and enact friendships; however, we currently have little empirically-informed understanding of how to design games that satisfy the social needs of players. We investigate how in-game friendships develop, and how they affect well-being. We deployed an online survey (N= 234) measuring the properties of games and social capital that participants experience within their gaming community, alongside indicators of the social aspects of their psychological wellbeing (loneliness, need satisfaction of relatedness). First, our findings highlight two strong predictors of in-game social capital: interdependence and toxicity, whereas cooperation appears to be less crucial than common wisdom suggests. Second, we demonstrate how in-game social capital is associated with reduced feelings of loneliness and increased satisfaction of relatedness. Our findings suggest that social capital in games is strongly and positively related to players' psychological well-being. The present study informs both the design of social games as well as our theoretical understanding of in-game relationships.
Implicit Entity Linking Through Ad-Hoc Retrieval

The systematic linking of explicitly-observed phrases within a document to entities of a knowledge base has already been explored in a process known as entity linking. The objective of this paper, however, is to identify and entity link those entities that are not mentioned but are implied within a document, more specifically within a tweet. This process is referred to as implicit entity linking. Unlike prior work that build a representation for each entity based on its related content in the knowledge base, we propose to perform implicit entity linking by determining how a tweet is related to user-generated content posted online and as such indirectly perform entity linking. We formulate this problem as an ad-hoc document retrieval process where the input query is the tweet, which needs to be implicitly linked and the document space is the set of user-generated content related to the entities of the knowledge base. We systematically compare our work with the state-of-the-art baseline and show that our method is able to provide statistically significant improvements.
Miniaturized Filters Based on SIW Quasi-Lumped Elements

The modeling and design procedure of in-line bandpass filters based on quasi-lumped SIW resonators is presented in this paper. A shunt parallel resonator is implemented by a gap-isolated rectangular patch shorted to ground by means of a via hole. The structure is then embedded into post-wall SIW line, and the proposed resonator can be modeled at circuital level as a quasi-lumped section of a vertically integrated shorted stripline including a capacitive loading at one end. A 3- pole filter centered at 10 GHz with 7% FBW is designed showing very low losses and a huge degree of miniaturization.
Detection of Broken Rotor Bars Faults in Inverter-Fed Induction Motors

This paper proposes a method for classification of broken rotor bars of three-phase induction motors driven with three different models of frequency inverters by using the amplitude of the stator current signal in the time domain. To assess the effectiveness of the method under evaluation in this work, classification accuracy of four different learning machine techniques were compared: Fuzzy ARTMAP network; Support Vector Machine; k-Nearest Neighbour and Multilayer Perceptron Network. Moreover, this paper presents the comparison of an analogue and a digital filter to the line current signal provided by the motor. Results obtained from 2293 experimental tests are presented to validate this comparative study, considering a wide range of speed and load conditions.
A Multi-answer Multi-task Framework for Real-world Machine Reading Comprehension

The task of machine reading comprehension (MRC) has evolved from answering simple questions from well-edited text to answering real questions from users out of web data. In the real-world setting, full-body text from multiple relevant documents in the top search results are provided as context for questions from user queries, including not only questions with a single, short, and factual answer, but also questions about reasons, procedures, and opinions. In this case, multiple answers could be equally valid for a single question and each answer may occur multiple times in the context, which should be taken into consideration when we build MRC system. We propose a multi-answer multi-task framework, in which different loss functions are used for multiple reference answers. Minimum Risk Training is applied to solve the multi-occurrence problem of a single answer. Combined with a simple heuristic passage extraction strategy for overlong documents, our model increases the ROUGE-L score on the DuReader dataset from 44.18, the previous state-of-the-art, to 51.09.
A Matrix based Isolated Bidirectional AC-DC Converter with LCL type Input Filter for Energy Storage Application

An isolated three-phase AC-DC converter is proposed in this paper for integrating energy storage element such as battery to the utility grid. The proposed topology uses a matrix based AC-AC converter for three-phase to single-phase conversion, facilitates the use of high frequency transformer for galvanic isolation and provides the necessary turns ratio for matching the required voltages on both sides and full bridge controlled rectifier section for AC-DC conversion. Space Vector Modulation (SVM) based switching technique has been implemented for the matrix based converter for superior input power quality and improved power conversion efficiency and Sinusoidal Pulse Width Modulation (SPWM) has been used for the full bridge controlled rectifier. A T-shaped LCL input filter is developed to provide low pass filtering effect. Also, the filter provides an inductance dominance, providing current source characteristics, hence only a capacitive output filter is used. Simulation was carried out in Powersim (PSIM) simulation software. Variation of voltage gain for SVM and SPWM modulation indices is also presented. The converter is able to generate a charging voltage as well as three-phase sinusoidal voltage with THD of 3%. A closed loop control is developed for matrix type AC-AC converter part. The control is able to perform bidirectional operation of the system.
Motor Insulation Aging Diagnosis with Pre-Installed Current Sensors for Inverter Control

In order to avoid a sudden failure of equipment, online diagnosis technique of motors is desired. To develop an insulation aging diagnosis technology using pre-installed current sensor, waveform of pre-installed current sensors is recorded for several insulation aging conditions. Initial and late insulation aging conditions are simulated by connecting the several capacitors to the motor. By comparing the Lissajous figure of each insulation aging state, it was revealed that the Lissajous figure became thicker as the insulation aging states progressed. Local Subspace Classifier was applied as a method to calculate the degree of abnormality of the changes of Lissajous figure and confirmed that LSC was able to detect the rise in abnormality degree due to progression of insulation aging.
Improved Harmonics Elimination for Standalone Brushless Doubly-Fed Induction Generator with Nonlinear Loads

This paper proposes an improved harmonics elimination method for standalone brushless doubly-fed induction generator (BDFIG) feeding nonlinear loads. To avoid degrading the performance of power generation systems, the caused 5th and 7th voltage harmonics must be eliminated. Meanwhile, a proportional-integral plus resonator in the positive fundamental reference frame has been employed to promise the zero steady error of the control winding current, which contains both de and ac components. The control scheme is developed in the machine-side converter for the voltage harmonics elimination of the power winding. Experimental results with 30 kVA BDFIG are presented to verify the proposed control method.
A Fast Open-Circuit Fault Diagnosis Scheme for Modular Multilevel Converters with Model Predictive Control

Fault diagnosis is a crucial way to increase the reliability of modular multilevel converters (MMCs) which consist of a large number of submodules (SMs). This paper proposes a fast fault detection and isolation (FDI) method to identify single open-circuit faults for MMCs with model predictive control (MPC). The proposed FDI method is simply implemented by comparing the applied arm voltage obtained in the former control cycle and the estimated arm voltage calculated by the load and circulating current models. No additional transducer or measurement is required. Experimental results show that an open-circuit fault in the MMC can be accurately detected and isolated in a very short time.
Machine Learning to Data Management: A Round Trip

With the emergence of machine learning (ML) techniques in database research, ML has already proved a tremendous potential to dramatically impact the foundations, algorithms, and models of several data management tasks, such as error detection, data cleaning, data integration, and query inference. Part of the data preparation, standardization, and cleaning processes, such as data matching and deduplication for instance, could be automated by making a ML model "learn" and predict the matches routinely. Data integration can also benefit from ML as the data to be integrated can be sampled and used to design the data integration algorithms. After the initial manual work to setup the labels, ML models can start learning from the new incoming data that are being submitted for standardization, integration, and cleaning. The more data supplied to the model, the better the ML algorithm can perform and deliver accurate results. Therefore, ML is more scalable compared to traditional and time-consuming approaches. Nevertheless, many ML algorithms require an out-of-the-box tuning and their parameters and scope are often not adapted to the problem at hand. To make an example, in cleaning and integration processes, the window sizes of values used for the ML models cannot be arbitrarily chosen and require an adaptation of the learning parameters. This tutorial will survey the recent trend of applying machine learning solutions to improve data management tasks and establish new paradigms to sharpen data error detection, cleaning, and integration at the data instance level, as well as at schema, system, and user levels.
How to represent a word and predict it, too: Improving tied architectures for language modelling

Recent state-of-the-art neural language models share the representations of words given by the input and output mappings. We propose a simple modification to these architectures that decouples the hidden state from the word embedding prediction. Our architecture leads to comparable or better results compared to previous tied models and models without tying, with a much smaller number of parameters. We also extend our proposal to word2vec models, showing that tying is appropriate for general word prediction tasks.
Discovering Influence Hierarchy Based on Frequent Social Interactions

In this paper, we introduce a novel problem of discovering influence hierarchy to organize influential users in a social network into different levels according to their potential of spreading influence. We present a novel approach of discovering influence hierarchy utilizing the temporal aspect and flow direction of interactions among users. The influence hierarchy has the potential to visualize the information flow of the network and identify different roles such as creators, information disseminators, emerging leaders and active followers. It is highly applicable in several domains such as sociology, marketing, political science and disaster management.
Real-Time CPU-Based Virtual View Synthesis

This paper presents the fast virtual view synthesis method for free navigation purposes. Presented method was implemented on CPU in order to allow free navigation for even cheap personal computers with integrated graphic cards. The described synthesis technique is based on the hybrid view synthesis, combining advantages of forward-type and backward-type synthesis. It allows to synthesize high resolution sequences in the real time, allowing the viewer to freely navigate around the scene, e.g. volleyball playfield. Three implementations were developed and tested: single-threaded, vectorized and multithreaded implementation.
Test Setup with a Permanent Magnet Synchronous Machine for Efficiency Maps of an Electric Vehicle

This paper presents activities connected with the realization and putting into service of a 100 kW frequency controlled permanent magnet synchronous machine (PMSM). Electromagnetic interference problems, mechanical problems and theirs solution is presented. The tuning and functionality of the control algorithm is described and the results of the experiments are presented. The test setup is used to verify efficiency map calculation and measurement for an electric vehicle drive system.
Relationship Between Shyness and Generalized Pathological Internet Use Among Chinese School Students: The Serial Mediating Roles of Loneliness, Depression, and Self-Esteem

The present study aimed to explore the mediating effects of loneliness, depression, and self-esteem on the association between shyness and generalized pathological Internet use (GPIU). A total of 5215 school students completed questionnaires regarding shyness, loneliness, depression, self-esteem, and GPIU (aged 11–23 years old, M = 16.19, SD = 3.10). The self-reported scores for GPIU, shyness, loneliness, depression, and self-esteem were tested in students from elementary schools to universities. The results of a variance analysis indicated that senior high school students had the greatest prevalence of GPIU of all the study stages. With the study stages resolved, the results of a structural equation model revealed that: (a) shyness positively predicted GPIU; (b) shyness/loneliness/depression predicted GPIU through self-esteem; (c) shyness predicted GPIU through loneliness/depression → self-esteem; and (d) shyness predicted GPIU through loneliness → depression → self-esteem. In conclusion, these results provided significant implications for preventing or reducing GPIU in Chinese school students.
Compressing 3D-CNNs for Hardware-Efficient Object Classification in Video Streams

This paper presents a set of methods for effective compression of 3D-CNN deep learning architectures with a particular focus on embedded platforms. Deep learning models are massive regarding the number of parameters, especially in video processing. Such memory consumption poses a challenge when it comes to efficient deployment to embedded devices. The authors applied a series of quantization and pruning techniques and showed that it is possible to significantly reduce an 80M-parameters-large deep learning model with a negligible (approx. 1 perc.) decrease in accuracy.
New Design of High Output Equivalent 4-pole Universal Motor

This paper presents a new design of a high output equivalent 4-pole, 2-brush universal motor. Equivalent four poles mean that two poles with field coils are the same poles by changing the connection of two field coils of a 2-pole universal motor and two auxiliary poles without field coils are opposite poles. The 4-pole, 2-brush motor is designed by changing the number of armature slots and the connection of armature coils at the same time. A conventional 2-pole universal motor has been used for the comparison of the motor performance and commutation, where the maximum outer length of a stator is the same with that of the equivalent 4-pole motor. The output of the equivalent 4-pole motor versus the rated voltage and speed was higher than that of the conventional 2-pole motor. The commutation of the equivalent 4-pole universal motor was better than that of the conventional 2-pole motor.
Una segregazione paradossale e multi-scalare: il caso del quartiere ZEN di Palermo

L’articolo affronta la questione della segregazione nel quartiere ZEN di Palermo (Sicilia). L’impianto teorico dialoga con la letteratura anglosassone, ma ne prende le distanze nel tentativo di individuare alcune specificita locali del caso. L’obiettivo e duplice: intanto indentificare alcuni “movimenti geostorici” che hanno caratterizzato il quartiere, collegando a ciascuno di questi una fase del processo segregativo; inoltre, rappresentare la segregazione del quartiere in forma cartografica, mediante l’uso di alcuni ideogrammi e mappe mentali.