Miracle-dz/UniFAR-FTUs huggingface dataset:
Rational Neural Networks for Approximating Graph Convolution Operator on Jump Discontinuities

For node level graph encoding, a recent important state-of-art method is the graph convolutional networks (GCN), which nicely integrate local vertex features and graph topology in the spectral domain. However, current studies suffer from several drawbacks: (1) graph CNNs rely on Chebyshev polynomial approximation which results in oscillatory approximation at jump discontinuities; (2) Increasing the order of Chebyshev polynomial can reduce the oscillations issue, but also incurs unaffordable computational cost; (3) Chebyshev polynomials require degree Ω(poly(1/ε)) to approximate a jump signal such as |x|, while rational function only needs O(poly log(1/ε)). However, it is non-trivial to apply rational approximation without increasing computational complexity due to the denominator. In this paper, the superiority of rational approximation is exploited for graph signal recovering. RatioanlNet is proposed to integrate rational function and neural networks. We show that the rational function of eigenvalues can be rewritten as a function of graph Laplacian, which can avoid multiplication by the eigenvector matrix. Focusing on the analysis of approximation on graph convolution operation, a graph signal regression task is formulated. Under graph signal regression task, its time complexity can be significantly reduced by graph Fourier transform. To overcome the local minimum problem of neural networks model, a relaxed Remez algorithm is utilized to initialize the weight parameters. Convergence rate of RatioanlNet and polynomial based methods on a jump signal is analyzed for a theoretical guarantee. The extensive experimental results demonstrated that our approach could effectively characterize the jump discontinuities, outperforming competing methods by a substantial margin on both synthetic and real-world graphs.
Local Balancing of Low-Voltage Networks by Utilizing Distributed Flexibilities as Part of the InterFlex Field Trial

The growing share of Distributed Generators (DG) brings with it a fundamental change in dispatchability and location of the overall power generation portfolio. A significant share of DGs are renewable-based and connected to the distribution system, replacing the conventional generators placed at high voltage levels. With this fundamental shift in the power system, more active approaches to distribution system operation are required. In this paper the authors propose a model to utilize distributed flexibilities to locally balance power generation and demand, minimizing the power exchange between low and medium voltage levels. The proposed model is applied to several low voltage networks in the German distribution system. Simulation results show that the proposed model decreases the peak load in tested LV networks by 2.6-12.5 %, and leads to an overall flattening of the load profile.
Online Reliability Assessment of Distribution Feeder Considering Time Sequential Load Transfer Procedure

An online reliability evaluation method for distribution network considering time sequential load transfer procedure is presented in this paper. The method, which takes the medium voltage distribution feeder as the evaluation object, assesses the worst outage risk in real time under the extreme fault condition. In order to simulate the load restoration procedure after fault, an optimization model of the load transfer strategy is set up aiming at minimizing total energy loss. The power variation in load transfer periods as well as the continuous back-up power supply ability is considered in the model, and a multi period heuristic search algorithm is applied to solve it efficiently. The effectiveness and feasibility of the proposed method is verified by case study, and the results can provide references for distribution system operators in distribution network.
Voltage-Based Load Control for Frequency Support Provision by HVDC Systems

In the last years, the electrical grid has seen a deep change in the power production share between conventional generators, such as coal and gas turbines, to renewable ones, like wind and photovoltaic power plants. These resources are characterized by a power electronics-based interface to the grid. However, these resources do not offer any rotational inertia to the grid, that, in case of large disturbances, can suffer of large frequency deviation. Several strategies have been proposed in literature for damping the frequency deviation, mostly involving HVDC systems. The HVDC can request active power to the DC-connected AC areas in order to provide the needed energy to damp the frequency variation. However, all these strategies do not investigate the impact of the power variation on the frequency in the other DC-connected AC areas, that may result large if these system's inertia is low. This paper proposes a control strategy for minimizing the impact of the power request in these DC-connected AC areas varying the power consumption of near voltage-sensitive loads by means of a controlled voltage variation. As demonstrated in this work, the controlled voltage variation is able to reduce the frequency swing in these AC areas, matching the power variation request for frequency support with the power variation achieved from the voltage-sensitive loads.
Benefits of Morphosyntactic Features on English-Arabic Statistical Machine Translation

Arabic is a Semitic language that arouses great interest in the field of machine translation. Given the large differences between morphology and grammar of Arabic and English, a statistical approach based on parallel corpus is privileged in the machine translation area. The statistical machine translation system's (SMT) quality is highly related to the preprocessing and post-processing steps of the English-Arabic parallel corpus used in the training phase. We present in this study a new alignment approach based on parallel corpus to involve some morphosyntactic information (stem, lemma and POS tags) for each word in this corpus. To evaluate our approach, we used the phrase-based statistical machine translation (PBSMT) system and then we tested it on the English-Arabic United Nations (UN) parallel corpus. The results obtained in the tests we carried out showed that this approach contributed to a significant improvement of the word alignment quality and consequently increase the BLEU score value of the translation.
Hand segmentation under different viewpoints by combination of Mask R-CNN with tracking

This paper presents a new method for hand segmentation from images and video. The method based mainly on an advanced technique for instance segmentation (Mask RCNN) which has been shown very efficient in segmentation task on COCO dataset. However, Mask R-CNN has some limitations. It works on still images, so cannot explore temporal information of the object of interest such as dynamic hand gestures. Second Mask R-CNN usually fails to detect object suffered from motion blur at low resolution as hand. Our proposed method improves Mask R-CNN by integrating a Mean Shift tracker that tracks hands in consecutive frames and removes false alarms. We have also trained another model of Mask R-CNN on cropped regions extended from hand centers to obtain a better accuracy of segmentation. We have evaluated both methods on a self-constructed multi-view dataset of hand gestures and show how robust these methods are to view point changes. Experimental results showed that our method achieved better performance than the original Mask R-CNN under different viewpoints.
Manfaa Freelancer Application

Nowadays, mobile commerce and the freelancer ecosystem are two evolved technologies. These technologies facilitate communication between freelancers and clients in the supply-driven and demand-driven crowdsourcing human services marketplace. Manfaa is an application considered as customer-to-customer mobile commerce and freelancer ecosystem applications. It will be developed on an Android platform and will be available over the Internet. The Manfaa application aims to enable users to get what they need exactly from the right person. It is going to help users in different aspects at reasonable prices. Additionally, it will accelerate the process of getting the work done.
Modelling and characterization of a microhotplate

Microhotplates are devices based on semiconductor technology and designed to increase fast the temperature in a specific and small region. We report in the next sections how we characterized the steady state and transient behaviour of our microhotplate [1], derived a calibrated multiphysics finite element model for it and built knowledge about the device based on experimental and simulated data. Along this process, we found a peculiar temperature drop in our device, which we suspect to be the effect of humidity and vapour created around the heater. Our ambition here is to expose the series of experiments and simulation that led us to this conjecture, that if correct, it could give us valuable information for improving design of microhotplates.
Modular Multilevel Converter for Multifunctional Battery Management System of Electric Vehicle

Modular multilevel converter (MMC) has become a promising technology for medium/high voltage high power applications. Electric vehicles on the other hand, have a large number of series connected battery cells to enhance the output voltage to drive the connected motor. This paper applies the concept of modular multilevel converter for low power electric vehicle applications where, the batteries of the EV help in exchanging power with the motor. The batteries can discharge when feeding power to the motor and get charged when the motor runs into regenerative mode. Multi-carrier PWM technique is employed to generate the multilevel voltage waveforms and sorting technique is used to balance the battery voltages. Simulation study has been done in MATLAB/SIMULINK platform and it is observed that the voltages and State-of-Charge (SOC) of batteries are well maintained.
Efficient Background-Noise-Reduced Single-Mode Waveguides Platform for On-Chip Integrated Photonics

In this paper, we propose a modified platform for on-chip integrated photonics. The platform allows one to efficiently connect a tapered optical fiber or fiber lens to an on-chip waveguide with high alignment precision and to mechanically fix the fiber on the chip to prevent defocusing, lateral shift, and angular detuning during device operation. The metal screen of the connector—made of gold—prevents any penetration of the background radiation into the optical circuit, something which is not possible to achieve in all the cases using tapers or grating couplers. We performed impedance-matching analysis based on transmission line theory and numerically optimized the platform, allowing us to achieve a tapered fiber mode to on-chip waveguide mode transformation efficiency as high as 96% (−0.177 dB) at wavelengths of 785 and 1550 nm. The platform bandwidth (transformation efficiency ≥80%) is 151 nm. At the same time, transformation efficiency is stable (reduction less than 1%) in an offset range of ±2 nm—enough for modern on-chip and off-chip coherent light sources. The horizontal and vertical lateral alignment tolerances for the platform are 700 and 600 nm, respectively, at a transformation efficiency ≥80% while the longitudinal alignment tolerance is approximately 70 nm. Due to the relatively high lateral and longitudinal tolerances, it is possible to produce the platform at high efficiency using existing fabrication nanotechnologies. We believe that this platform accelerates the realization of fully on-chip Raman spectroscopes and may be of practical importance in other on-chip integrated photonic devices.
Heterogeneous Routing: A Methodology for PPA Tradeoff in Network-On-Chips

This paper proposes a routing algorithm design methodology based on real network traffic analysis. The method aims at large-scaled network on chip in which load differs among different areas or routing nodes. By applying different routing algorithms on different nodes, the area and/or power consumption can be saved only at the cost of minor performance loss. Experimental results show that by replacing routing nodes using NoP routing algorithm with nodes using XY routing algorithm, up to 10% of routing nodes can be simplified into much less power/area costing nodes, saving at least 2 % of area overhead, only at the cost of 5% of performance loss.
Optimal Power Flow Analysis of Power System for Petrochemical Enterprises Based on the Interior Point Method and PSASP

The electricity consumption accounts for about 20% to 30% of total energy consumption in a petrochemical enterprise. The optimal power flow analysis can guide electricity workers to optimize the operation mode of the enterprise power network, reduce the power loss and improve the power, which can save the energy and costs of the enterprise maximized. It can also provide scientific basis for decision making to workers considering the economy of power supply grid during making network planning in order to develop a rational power network planning.
A Systematic Review on Vehicle Identification and Classification Techniques

Vehicle detection and classification from a moving platform is an important factor in Intelligent Transportation System (ITS). Vehicle identification and classification provide input to traffic control measures and traffic management systems. Vehicle identification and classification in congested traffic and busy roads is still facing challenges due to a number of factors like different types of vehicles, the vehicle with almost similar features having different class etc. Improving Transportation System in big cities is facing more challenges due to a number factor like traffic congestion, lane problems. This review paper is on vehicle detection and classification to address the work done in this field and feature demands of classification and identification of vehicles.
A Cross-Age Face Recognition Approach Using Fog Computing Architecture for User Authentication on Mobile Devices

Mobile commerce security needs quality services where mobile devices respond in real-time and traditional cloud computing approach uses a centralized architecture does not support these systems with such time dependency well. Thus, this study proposes a cross-age face-recognition model with MobileNets to determine the identity of a user in the situation of aging appearance change on a fog computing architecture. Especially, this study uses a face-recognition technique based on a distributed concept. In this concept, MobileNet-based face recognition system effectively performs cross-age face recognition for identity authentication with the enhanced facial features of the users locally. Overall, the MobileNet model reaches acceptable prediction accuracy with lower latency in face recognition process compared with that of the existing CNNs schemes.
Optimal Placement of Sectionalizing Switch Considering Switch Malfunction Probability

Sectionalizing switches (SSs) are often presumed to function fully reliable. However, SSs are exposed to have some malfunctions, whereby undermining their ability to improve service reliability. This paper presents a model to integrate SS malfunction probability into SS placement problem. The model aims to minimize the total SSs costs as well as customers interruption cost. The proposed model is formulated in mixed integer programing, which can be easily solved via several available solvers and gain global optimal solution. The proposed model indicates the extent to which the placement problem is affected by uncertainty associated with SSs functionality, and how not considering SSs malfunction overestimates their benefits. The effectiveness of the proposed method is demonstrated through various case studies and sensitivity analyses. Moreover, the applicability of the proposed model in practice is examined by applying it on a real-life distribution system.
Transmission Performance of 112-Gb/s PDM-PAM4 Signal over Unrepeatered Raman-amplified Link

We propose a cost-effective unrepeatered optical transmission system by utilizing PDM-PAM4 signal and Stokes vector receiver. At rate up to 112-Gb/s per carrier, the results show that the optimum signal launch power is ~4-dB lower for WDM channels transmission than single carrier over 200 km unrepeatered link, and the reach distance for WDM transmission is ~10% shorter than single carrier transmission at 7% FEC threshold.
Seek Control of Hard Disk Drives Using Model Following Control: An Improved Result

This paper treats seek control of hard disk drives. This system has unstable zeros and resonant terms in high frequency region, and the output shows a big overshoot when we apply a traditional Model Following Control scheme. To reduce the overshoot and the settling time, an improved configuration of Model Following Control scheme is proposed. Moreover, outer feedback to make the peak of the control input small.
Summarizing Graphs at Multiple Scales: New Trends

Recent advances in computing resources have made it possible to collect enormous amounts of interconnected data, such as social media interactions, web activity, knowledge bases, product and service purchases, autonomous vehicle routing, smart home sensor data, and more. The massive scale and complexity of this data, however, not only vastly surpasses human processing power, but also goes beyond limitations with regard to computation and storage. That is, there is an urgent need for methods and tools that summarize large interconnected data to enable faster computations, storage reduction, interactive large-scale visualization and understanding, and pattern discovery. Network summarization-which aims to find a small representation of an original, larger graph-features a variety of methods with different goals and for different input data representations (e.g., attributed graphs, time-evolving or streaming graphs, heterogeneous graphs). The objective of this tutorial is to give a systematic overview of methods for summarizing and explaining graphs at different scales: the node-group level, the network level, and the multi-network level. We emphasize the current challenges, present real-world applications, and highlight the open research problems in this vibrant research area.
The Design of 220kV Substation Grounding Grid with Difference Soil Resistivity Using Wenner and Schlumberger Methods

This paper presents the design of 220kV substation grounding grid with difference resistivity soil according to horizontal and vertical two layer soil model is structure using the MALT program of CDEGS Software. The target of this paper is to minimize the touch and step voltages when the resistivity soil is high, in 220kV urban substation pending a direct lightning stroke. Also, it is shown that for a sensor located on the ground, close to 220kV substation, the magnetic field component vertical to the structure can also experience a considerable attenuation, perhaps due to the effect of the induced currents in the substation. The results are confirming by numerical simulations, obtained using NEC-4 and IEEE Guide for Safety in AC Substation Grounding. The step by step procedure for designing 220kV substation grounding grid has been presented for which design parameters were obtained by CDEGS Software.
An Exploratory Study on Motivational Predictors in Internet Gaming Disorder Among Peruvian Gamers

According to many reports, one of the fastest growing industries in the US is video games. In Peru, it is estimated that Peruvians spent more than one hundred million dollars annually in videogames. However this number may be underestimated since piracy is a common practice. With the rapid proliferation of this form of entertainment, the inclusion of Internet Gaming Disorder (IGD) in section III of the Diagnostic and Statistical Manual of Mental Disorders and the recent inclusion of Gaming Disorder in the beta draft of the 11th International Classification of Diseases, many academic researchers and health professionals have become concerned with the addictive properties of videogames. Previous research has found that motivational factors have an important role in addictive behaviors. For this reason, the present study aimed to identify the main motivational factors underlying IGD. To reach this goal, a large empirical survey was carried out among 821 Peruvian gamers. Results showed that escape and fantasy were the factors that most predict IGD among Peruvian gamers. Implications for mental health professionals, game developers, and academics are discussed.
Record2Vec: Unsupervised Representation Learning for Structured Records

Structured records - data with a fixed number of descriptive fields (or attributes) - are often represented by one-hot encoded or term frequency-inverse document frequency (TF-IDF) weighted vectors. These vectors are typically sparse and long, and are inefficient in representing structured records. Here, we introduce Record2Vec, a framework for generating dense embeddings of structured records by training associations between attributes within record instances. We build our embedding from a simple premise that structured records have attributes that are associated, and therefore we can train the embedding of an attribute based on other attributes (or context), much like how we train embeddings for words based on their surrounding context. Because this embedding technique is general and does not assume the availability of any labeled data, it is extendable across different domains and fields. We demonstrate its utility in the context of clustering, record matching, movie rating and movie genre prediction.
Constraint Based Testing and Verification of Java Bytecode Programs

In this paper, we propose to apply constraint based testing and verification of Java bytecode programs augmented with their user specifications. The main objective of this approach is to detect inconsistencies between a Java Program and its user specification at the Bytecode level, and also to explore the execution paths of the program searching for which of them may contain such inconsistencies. Thus, we propose firstly to exploit the constraints of the precondition to put the method under test in its invocation context and consequently to guide the generation of the input test data. And secondly, we perform a verification of the program relatively to its post-state to detect the execution paths of the method under test that do not respect their specifications, in the unit testing context. However, the Java method under test and the user specifications are not in the same level of abstraction. To deal with this problem, we suggested to specify the bytecode program with Pre/Post conditions at the bytecode level using the static bytecode instrumentation.
Optimal Design of SRMs for Comparable Output with PMSMs

This paper deals with the design and optimization of a 12/8 switched reluctance machine (SRM) to be used in a 48V automotive cooling fan module (CFM). The main design objective is for it to fit into the same installation space as the reference 15/10 ferrite-based synchronous machine, when performing the same mechanical characteristic. Through optimization of the winding's filling factor, a similar RMS current consumption, at the rated operating point, as that of the reference machine is targeted. Finally, the two motors are to be compared regarding the cost of active materials and efficieney.