Miracle-dz/UniFAR-FTUs huggingface dataset:
Background subtraction using a convolutional neural network

Background subtraction is a first step in many video content analysis applications including object tracking and event recognition. Algorithms that take into account the neighborhood of each analyzed pixel tend to outperform pixel-based approaches. Most of these spatial-based algorithms use hand-crafted local features combining color and texture information to compare the patches. We propose to use a convolutional neural network (CNN) to predict similarity between patches in the current image and in the background model. Pairs of patches extracted from existing background subtraction dataset with pixel-accurate labeling are used to train the neural network. The use of a siamese network architecture with a dot product layer allows to compute the convolutions for each patch only once resulting in a local feature descriptor optimized for background subtraction. Therefore, the proposed similarity metric can be incorporated in existing adaptive background models without significant computational overhead. We demonstrate the robustness of the proposed approach in terms of precision and recall on a subset of ChangeDetection.net dataset and show that our method outperforms existing color-and texture-based descriptors used for background subtraction.
Optimisation of planar rectangular coil achieving uniform magnetic field distribution for EV wireless charging based on genetic algorithm

Inductive power transfer is a method that can be used to transfer power to electric vehicles. The output power and the transmission efficiency drop significantly when there is a misalignment between receiver on the vehicle and transmitter on the parking spot. This can be resolved by designing the transmitter coil that produces uniform magnetic fields for wireless charging. Here, a planar rectangular coil with unevenly spaced turns is proposed for improving the uniform magnetic field distribution over the charging zone, together with the genetic algorithm for determining the geometric parameters of the coil structure. An analysis that is divided into four design variables is presented. The magnetic characteristic of the optimal unevenly spaced transmitter coil using genetic algorithm and optimal evenly spaced transmitter coil using conventional method are compared and analysed. The uniform magnetic field distribution of the designed prototype is measured by an electric and magnetic field probe and by a receiver coil. The measured results agree well with the theoretical values and validate the improved uniform magnetic field distribution.
Mapping coffee crops in southeastern Brazil using spectral mixture analysis and data mining classification

ABSTRACT The task of mapping coffee crops using multispectral data sets is not yet a trivial routine. This is because coffee fields are extremely heterogeneous in terms of spectral reflectance. This study therefore aims to contribute to the mapping of coffee crops using multispectral imagery with 23.5 m spatial resolution taken by the Linear Imaging Self Scanner (LISS III) instrument on board the Indian Remote Sensing (IRS) satellite system. The section of land covered by this study is a traditional coffee-producing province located in the south of the State of Minas Gerais, southeastern Brazil. Whereas the pixel mixture effect was managed using spectral mixture analysis (SMA), the classification was carried out using data mining (DM) techniques. The decision tree (DT) outcomes were evaluated using a simple and qualitative method based on the elements of photointerpretation. In total, eight land-use and land-cover (LULC) types were mapped, including three classes of coffee-growing land expressing different phenological conditions and management. These were named ‘Production Coffee’, ‘Mixed Coffee’, and ‘Old/Pruned Coffee’. The results showed that the methodology was effective for mapping LULC types, as the workflow adopted simplified image interpretation and offered improvements in the classification performance. Despite the coffee-cultivation classes having a large spectral variability, which increases the chances of classification errors, not many confusions were observed involving the three coffee classes mapped with other categories of use. This therefore shows that the method was efficient in isolating the coffee classes (with an accuracy greater than 70%) from other categories of use. Comparing the results obtained in this work with a conventional maximum-likelihood (ML) classification, the results revealed that when using the methodology described, the confusions between classes were less dispersed and an improvement of approximately 10% was observed in the mapping of the Production Coffee class.
Pairgrams: Understanding Collaborative Analysis Behavior with Visualization

We report on our work towards understanding analytic rea soning processes in face-to-face collaborative analysis using visualization techniques. How analysts reason is an active topic of research and in our community we know even less about how a group forms an understanding, insight, and reasons about data. We report on our effort in capturing the richness of reasoning activities through mixed-method approaches and show how Pairgrams-a visualization of interactions with an analytics workspace by pairs of participants-helped us to understand collaborative analysis and reasoning
Une approche pour les architectures logicielles à composants multimédia

Dans cet article nous proposons un meta-modele pour les architectures a base de composants multimedia heterogenes. Il n'existe actuellement pas de solution generique pour deployer automatiquement de telles architectures. La mise en evidence des incompatibilites d'assemblage entre composants est une necessite dans de telles approches. En effet, les architectures logicielles valident les aspects fonctionnels, ce qui n'est pas suffisant pour garantir un assemblage realiste et remedier aux problemes d'heterogeneite des flux de donnees echanges. Nous proposons, pour mettre en evidence ces incompatibilites et permettre de trouver des solutions, une approche basee modele appelee MMSA (Meta-model for Multimedia Software Architecture). Elle permet la description d'architectures logicielles exprimant un systeme logiciel comme une collection de composants qui manipulent differents types et formats de donnees et qui interagissent par l'intermediaire de connecteurs d'adaptation.
Sensing strategies in wearable bio-mechanical systems for medicine and sport: a review

The relevance of wearable sensing systems has increased in recent years, particularly in medicine and sport. In these fields, the main benefit of non-invasive and comfortable wearable devices is the real time evaluation of a patient’s physiological conditions. Body monitoring is generally based on the measurement of heart rate, heart rate variability, body motion, breath, skin temperature and metabolic parameters (electrolytes, lactic acid, pH, etc). The basic requirements of wearable systems are lightness, flexibility, reliability and low power consumption. In addition, wearable sensors must provide acceptable levels of accuracy, repeatability and noise. Different solutions have been proposed to develop sensors specifically for wearable systems. The evolution of materials, the reduction of power consumption and the development of fiber treatments have supported the prototyping of integrated wearable sensing systems. The goal of this review is to provide a general description of the technologies relating to wearable sensors that have been adopted in medicine and sport, and to review device typologies, sensing strategies and future perspectives.
Systematic Phase Correction for Direction-of-Arrival Estimation in Spectrally Interleaved OFDM MIMO Radar

This paper presents a phase correction method to improve direction-of-arrival (DOA) estimation in spectrally interleaved orthogonal frequency-division multiplexing (OFDM) multiple-input-multiple-output (MIMO) radar systems. It is new in the way that a phase correction step is introduced between the range-Doppler processing and the DOA estimation. The phase correction results in an improved dynamic range. Both processing steps, range–velocity and DOA, are performed using discrete Fourier transforms (DFTs). This paper starts by introducing the waveform and reviewing range–velocity processing in OFDM radars. After that, the new phase correction method is introduced. Then, the concept is implemented in a quantitative simulation. The last part includes the system description and measurement in an outdoor scenario. Finally, the simulation and measurement results are discussed.
The First 3D-Printed and Wet-Metallized Three-Axis Accelerometer With Differential Capacitive Sensing

In this paper, the innovative fabrication process for electro-mechanical sensors, born from the smart combination of 3D-printing and wet-metallization and previously demonstrated in a <inline-formula> <tex-math notation="LaTeX">$z$ </tex-math></inline-formula>-axis accelerometer, is employed to fabricate a fully 3D three-axis accelerometer. Thanks to the three-dimensionality of the printing process, a central symmetry along the three axes can be obtained by design, unlike in common 2D-like microfabrication processes. Electrostatic differential sensing is obtained through the metallization procedure and the subsequent mounting of fixed electrodes on an external frame of the mechanical structure. Experimental tests under accelerations show good agreement with theoretical predictions. With relatively small dimensions (features as low as <inline-formula> <tex-math notation="LaTeX">$450~\mu \text{m}$ </tex-math></inline-formula>), very high capacitive sensitivity (> 200 fF/g) and low theoretical thermo-mechanical noise, the proposed three-axis accelerometer represents a further step towards the development of an innovative fabrication process for high-performance, customizable, and low-cost electro-mechanical devices.
A New Algorithm for Detecting Failure to Clear Mode of Circuit Breakers Using Fundamental Frequency Component of Voltage Signals

This paper introduces a new algorithm for the early detection of abnormal arcing conditions of circuit breakers (CBs). Any interruption with a higher arcing time compared to maximum permissible arcing time of CB is defined as a CB failure to clear mode. Measuring CB arcing time is not easy because there is no control on the mechanical opening and closing instants of CB contacts. Nevertheless, there is a correlation between the spectral energy densities of CB arcing voltages and arcing times of CB. This correlation is used by calculating the spectral energy densities of the instantaneous system voltage and the instantaneous CB voltage across its terminals utilizing discrete Fourier transform for two periods of the system frequency. The difference between the spectral energy densities at the fundamental frequency is defined as a criterion for identifying a failure to clear mode. Whenever this criterion exceeds a predefined trip level, it indicates the occurrence of a failure to clear mode. In this situation, a trip signal is initiated for adjacent CBs to isolate the faulted CB and the fault. The results obtained from computer simulations and measurements show that the algorithm discriminates between normal and abnormal arcing conditions of CB.
Influence et correction des interférences dues aux décalages en fréquence sur les transmissions OFDM dans un système multi-utilisateurs

Broadband systems for WLAN and WMAN (wireless metropolitain or local area networks) rely on OFDM (Orthogonal Frequency Division Multiplexing) modems (802.11a, HiperLAN/2, HiperMAN,.). The data rates offered by such systems are sufficient for numerous applications but the system bottleneck could be in the number of subscribers the systems could support at high data rates. To overcome this problem we propose to use multi-user detection (MUD) techniques to increase the number of simultaneous transmitters in the same frequency band in the same time slot. New impairments arise when performing such transmissions such as frequency impairments between the different subscribers due to low cost local oscillators. This results in a loss of orthogonality at the receiver side between the sub-carriers. We thus propose in this papier an ad hoc receiver taking into account these new impairments. This work is partially supported by the IST project STRIKE (FP5 IST-2001-38354).
Digital Transformation at BP is Starting to Add Up to Billions

About 3 years ago, upstream executives at BP came together and recognized that this down cycle was not like the ones before. The moment marked the beginning of the company’s “digital journey,” one that it says is paying off in spades. “Our industry—our sector—it fundamentally changed,” said Ian Cavanagh, the head of modernisation and transformation at BP. As a nearly 29-year veteran of the company, encompassing his entire oil and gas career, he spoke with authority on how shifting conditions have redefined what it means to be a supermajor in the 21st century. It means taking on the controversial issue of global climate change by promising to find ways to increase energy production while lowering the overall car-bon footprint. BP’s answer to this “dual challenge” includes big investments in the electrical vehicle sector, solar power, and wind power. But more to its core, the tidal forces of volatile commodity prices meant that BP needed to go on a digital technology shopping spree to either find more oil and gas, or get it out of the ground at a lower cost. Today’s portfolio features a growing list of in-house innovations, such as a new fiber-optic interpretation company that BP is spinning off to the outside world and a team of robots that will soon assume a lead role in offshore inspections. BP reported in January that its new seismic device called Wolfspar led to the discovery of more than 1 billion bbl of oil in place at its Thunder Horse field in the Gulf of Mexico. Dozens of other technology developments have come together with outside help, including a major digital twin project in the Gulf of Mexico and an artificial intelligence program that aims to prevent sand production problems in the Caspian region. But no matter how high the technology stack grows, a digital transformation ends up being a people problem. BP is keenly aware that the modern workforce—now dominated by a tech-savvy millennial generation—has expectations for management that go beyond the size of the paycheck. They want to work at companies that move fast and are willing to kill off the status quo best summarized with the phrase “We’ve always done it that way. ” Cavanagh argues that BP has answered this call. “To retain and attract the best talent in the world, in our industry and outside our industry, we had to change several things about how we do work,” he said, noting that without getting this human element right, “we’re in trouble. ” Transforming BP meant that executives would have to put their weight behind an effort to root out the traditional oil and gas decision-making processes that Cavanaugh recognized as “slow, and quite cumbersome. ” In their place today are approaches described as “agile,” a word that has risen to become a cornerstone principle of today’s management methodology.
Linear partition heuristics for a generalized delivery workload balancing problem with an allocation of cargoes to interim storage lanes

Given m periodic deliveries performed by a single tractor and a finite set N of cargoes with their arrival times and processing times, we are asked to find a feasible partition of the cargo set N into m disjoint subsets. The workload of a delivery is defined to be the sum of processing times of cargoes assigned to the delivery. The m periodic deliveries are required to be balanced on their workloads. We treat the maximum distance of a workload from a prescribed guiding mark as a balancing criterion. The maximum distance is equivalent to the ordinary maximum workload over the m periodic deliveries when the guiding mark is given to be zero. In the actual assembly plant motivating this study, allocating each cargo to one of interim storage lanes determines a partition of the cargo set N, and the feasibility of a partition of the N depends on the practical fact. In this paper, we propose a dynamic programming based heuristic algorithm which runs in polynomial time and returns a linear partition of a cargo list. Since the maximum distance criterion contains the ordinary maximum workload as a special case, the proposed heuristic can be regarded as a generalization of an existing linear partition procedure of minimizing the maximum sum of processing times for a subsequence of cargoes. We also conduct numerical experiments to demonstrate the performance of the proposed heuristic with a meaningful guiding mark.
A multi-objective model for risk mitigating in supply chain design

The goal of this study is to recognise various factors for responsive SCs that affect supply risk and model their impact on SC design and operation. We propose a conceptual model for SC responsiveness that encompasses practices such as flexibility, agility, internal integration, and visibility. This conceptual model is utilised to build up a multi-objective, multi-period SC design and operation model. A heuristic algorithm is developed to find the supplier, product, period, and production rate for the numerical problem. The improved genetic algorithm (GA) produces solutions with more accuracy in considerably less time than a traditional GA. Finally, an approach to prioritise the objective functions is developed that allows managers to focus on specific objective functions more than optimum values. This approach provides risk-averse, responsiveness-oriented, cost-effective managers the capability to set priorities based on their policies.
Um Modelo de Análise de Crédito para o Cartão BNDES utilizando um Sistema Neuro-Fuzzy NFHB

Este trabalho apresenta um modelo para análise de crédito para o Cartão BNDES utilizando um sistema Neuro-Fuzzy Hierárquico BSP que constitui um passo importante para uma aproximação do BNDES com as micro, pequenas e médias empresas. Foram selecionadas trezentas e dezoito solicitações de crédito retiradas aleatoriamente dos pedidos feitos ao BNDES. Estas solicitações foram analisadas por especialistas em crédito, dos bancos emissores, que decidiram por conceder ou não o crédito solicitado. Após aplicado o modelo, os resultados alcançados, pelo classificador, foram considerados plenamente satisfatórios pelos especialistas, pois na totalidade dos casos que foram apresentados para serem avaliados pelo indutor, o modelo apresentou a mesma opinião do banco emissor.
Thermal Decomposition of a Single AdBlue® Droplet Including Wall–Film Formation in Turbulent Cross-Flow in an SCR System

The selective catalytic reduction (SCR) methodology is notably recognized as the widely applied strategy for NOX control in exhaust after-treatment technologies. In real SCR systems, complex unsteady turbulent multi-phase flow phenomena including poly-dispersed AdBlue® spray evolve with a wide ranging relative velocity between the droplet phase and carrier gas phase. This results from an AdBlue® spray that is injected into a mixing pipe which is cross-flowing by a hot exhaust gas. To reduce the complexity while gaining early information on the injected droplet size and velocity needed for a minimum deposition and optimal conversion, a single droplet with a specified diameter is addressed to mimic a spray featuring the same Sauter Mean Diameter. For that purpose, effects of turbulent hot cross-flow on thermal decomposition processes of a single AdBlue® droplet are numerically investigated. Thereby, a single AdBlue® droplet is injected into a hot cross-flowing stream within a mixing pipe in which it may experience phase change processes including interaction with the pipe wall along with liquid wall–film and possible solid deposit formation. First of all, the prediction capability of the multi-component evaporation model and thermal decomposition is evaluated against the detailed simulation results for standing droplet case for which experimental data is not available. Next, exploiting Large Eddy Simulation features the effect of hot turbulent co- and cross-flowing streams on the dynamic droplet characteristics and on the droplet/wall interaction is analyzed for various droplet diameters and operating conditions. This impact is highlighted in terms of droplet evaporation time, decomposition efficiency, droplet trajectories and wall–film formation. It turns out that smaller AdBlue® droplet diameter, higher gas temperature and relative velocity lead to shorter droplet life time as the droplet evaporates faster. Under such conditions, possible droplet/wall interaction processes on the pipe wall or at the entrance front of the monolith may be avoided. Since the ammonia (NH3) gas generated by urea decomposition is intended to reduce NOX emission in the SCR system, it is apparent for the prediction of high NOX removal performance that UWS injector system which allows to realize such operating conditions is favorable to support high conversion efficiency of urea into NH3.
A Survey Paper on Software Architecture Visualization

Understanding the software architecture is a vital step towards building and maintaining software systems. But software architecture is an intangible conceptual entity. Therefore, it is hard to comprehend a software architecture without a visual mapping that reduces the burden on the human brain. Visualizing software architecture has been one of the most important topics in software visualization. Not only are architects interested in this visualization but also developers, testers, project managers and even customers. This paper is a survey on recent and key literature on software architecture visualization. It touches on efforts that defined what characteristics an effective visualization should have. It compares various efforts in this discipline according to taxonomies such as dimensionality, multiplicity of views and use of metaphors. The paper also discusses trends and patterns in recent research and addresses research questions that are still open for further investigation.
Skew Angle Detection of the Vehicle License Plate Image and Correct Based on Radon Transformation

Correction of the skew vehicle license plate is very substantial to the license plate images segmentation and recognition.In this paper, we present a method based on Radon transformation, which can estimate the skew angle by seeking the frame of the license plate, and then we also propose a method to rectify the traffic plate with two steps.Eventually, the mathematical morphologic procedures are used to smooth the image.
Impact of Cascading and Common-Cause Outages on Resilience-Constrained Optimal Economic Operation of Power Systems

Common-cause and cascading outages in extreme power system conditions may challenge traditional N-k transmission security strategies. This paper proposes a resilience index (RI) to evaluate the power system adaptability to extreme conditions and establishes the resilience-constrained economic dispatch (RCED) model and solution methodology in power system operations. A three-stage outage sampling method is presented to assess the proposed RI in severe weather conditions culminating in common-cause and cascading outages. In the proposed RCED model, customized contingency constraints are introduced to represent common-cause and cascading outages in extreme events and two penalty terms are considered that can adjust power transmission flows for lowering outage risks in a power grid. An optimization method is presented to solve the RCED model efficiently with an absolute value function introduced in both objective function and constraints. A sufficient and necessary condition is proposed to ensure the optimality of the linearized solution is the same as that of the original problem. Case studies show the effectiveness of the proposed model and methodology.