Miracle-dz/UniFAR-FTUs huggingface dataset:
Supporting the collaborative development of requirements and architecture documentation

In most software projects, particular requirements significantly drive the design of the software architecture by forcing architectural decisions to be made. As requirements and architecture are refined iteratively, their extensions and improvements need to be aligned continuously. Much research has been conducted to identify such requirements and their impact on architecture. However, it remains a problem how to collaboratively document such requirements and architectural knowledge under development. In particular, knowledge of architectural decisions such as assumptions or alternatives for the system erodes over time and can even vaporize completely. A major reason is the inability to easily manage informality and complexity of knowledge when performing both requirements engineering and architecture design. Therefore, we propose a documentation model for decisions supporting the intertwined documentation of related requirements and architecture knowledge. It provides documentation elements, which are common to both disciplines. In order to support refinement in documentation, knowledge can be iteratively accumulated at different levels of granularity. So the model fits to the twin peaks model of requirements and architecture. In consequence, the comprehension and collaboration between requirements engineers and system architects is improved by negotiating and refining the same documentation together in an ongoing process. We apply our approach to an example in order to demonstrate that it is applicable and useful for managing architectural decision knowledge in relation to the grounding requirements.
Energy Efficient Mobile Service Computing With Differential Spintronic-C-Elements: A Logic-in-Memory Asynchronous Computing Paradigm

During recent years, researchers throughout academia and industry have been advancing the theory, designing, and applications of mobile service computing through the Internet of Things (IoT). Research interest in mobile service computing stems from its performance, security, reliability, and power consumption. Hence, ultra-low power integrated circuits are essential for mobile service computing that can offer the advantages of low power for computational tasks in the IoT that is driven by the restricting constraints of power consumption and autonomy in both computation and idle phases. To attain the benefits of ultra-low power circuits, the energy-consuming and computational intense demands are imposed by the underlying processing and memory devices on which the conventional ultra-low power integrated circuit can benefit substantially from innovative hardware designs. Logic-in-Memory (LIM) architectures are considered as the potential approaches to attain goals within area and energy constraints starting with the lowest layers of the hardware stack. In this paper, we propose and implement the LIM asynchronous computing paradigm for energy-efficient mobile service computing. The results indicate that the proposed design achieves 38% leakage reduction and 30% accuracy improvement compared to the state-of-the-art non-volatile asynchronous circuits. At the system level, we compare our designs with various commercial microprocessors. The experimental results show that the asynchronous processors attain a four-fold throughput increase relative to their synchronous counterparts under these operating constraints. Therefore, the proposed design offers an approach toward tangible benefits of the battery-constrained embedded mobile service computing.
Sensor-less Control of a PMSM for Safety Critical Applications Using Hysteresis Current Control in Case of an Encoder Failure

Encoders are one of the critical parts in an electric drive system. In safety critical applications like an air plane a redundant and robust sensor-less controller with an approval in aviation is required. This paper presents a hysteresis current controller, which is implemented on a FPGA. We simulated the switching action and the controller dynamics and measured it on a test bench. We describe the transients excited by the switching action analytically. Although transients are excited at the switching moment, a stable operation of the machine is ensured. The results of simulation and measurement of the switching action show a maximal deviation of 6% in the stator current amplitude. The excited transients describe a sinusoidal shape for the rotor speed. The analytical solution of the oscillation amplitude deviates from the measured results by a maximum of 14%. The oscillation frequency is 24% up to 35% smaller, depending on the operating point. The differences are due to the assumption of phase currents with a constant amplitude. It is shown that the dq-current components follow the constant torque hyperbola, if the current reference amplitude changes. In case of a load torque change they will move on the constant stator current circle and turning clockwise for a load torque decrease and counter clockwise for an increase. Due to the working principle of the controller, the current distortion is significant and is measured to 29% in a defined operating point. The measurement results validate the simulation results. The implemented hysteresis current controller can be used to improve the redundancy of a control structure.
An Optimization Approach of Compressive Sensing Recovery Using Split Quadratic Bregman Iteration with Smoothed ℓ0 Norm

An optimization algorithm for image recovery is a core issue in the field of compressive sensing (CS). This paper deeply studied the CS reconstruction algorithm based on split Bregman iteration with ℓ1 norm, which enables the ℓ1 norm to approximate the original ℓ0 norm during the optimization process. Consequently, we proposed another novel algorithm improving the precision and the convergence speed based on split quadratic Bregman iteration (SQBI) with ℓ0 norm. Besides, we analyzed its convergence by proving two monotonically decreasing theorems. Inspired by previous researches, we applied smoothed ℓ0 norm for the optimization problem to replace the traditional ℓ0 norm in CS. The improvement is made by using a Gaussian function to approximate the ℓ0 norm, transforming it into a convex optimization problem, and eventually achieved a convergent solution by the steepest descent method. The experimental results show that under the same conditions, compared with other state-of-the-art algorithms, the reconstruction accuracy of the CS reconstruction algorithm based on the SQBI with smoothed ℓ0 norm is improved significantly, and its convergence rate is also accelerated as well.
Numerical solution of nonlinear parabolic systems by block monotone iterations

This paper deals with investigating numerical methods for solving coupled system of nonlinear parabolic problems. We utilize block monotone iterative methods based on Jacobi and Gauss--Seidel methods to solve difference schemes which approximate the coupled system of nonlinear parabolic problems, where reaction functions are quasi-monotone nondecreasing or nonincreasing. In the view of upper and lower solutions method, two monotone upper and lower sequences of solutions are constructed, where the monotone property ensures the theorem on existence of solutions to problems with quasi-monotone nondecreasing and nonincreasing reaction functions. Construction of initial upper and lower solutions is presented. The sequences of solutions generated by the block Gauss--Seidel method converge not slower than by the block Jacobi method.
Researching on the linear X-ray detector application of in the field of steel-core belt conveyor inspection system

For the sake of avoiding no real time image during steel roe core conveyor inspection with Magnetic particle Testing technology and no way to eliminate variety of noise, this article introduces a new steel rope core inspection system with linear X-ray detection which can continuously inspect conveyor with real time image, in order to offer clearer and more direct radiative images of defect and joint to user, then further reasonable method can be adopted to avoid accident.
Applying Web Service to Distributed Multimedia Content Analysis

The Web is catalyzing a transition from PC-based software and file systems to Internet-based applications and Web services. We aim at the combination of multimedia computing and Web technologies (Web Services) together that supports uniform naming, protection, and access for Multimedia Content objects stored by Web services to accomplish distributed computing. At a high level, it creates an integrated file and object system from heterogeneous, multimedia content objects dispersed across the Internet. Based on this fact, we proposed a novel framework of distributed multimedia computing in this paper. In this framework, the concept of workflow which can describe business processes logically is introduced. Some experiments show the effectiveness of the proposed framework.
A Two-Stage Ensemble of Differential Evolution Variants for Numerical Optimization

Differential evolution (DE) is a popular paradigm of evolutionary algorithms, which has been widely applied to solve diverse optimization problems and has gained much success in a series of academic benchmark competitions. Recently, ensemble methods received an increasing attention in designing high-quality DE algorithm. Motivated by this consideration, a novel two-stage ensemble of DE variants, called TSEDE, has been proposed in this paper. In TSEDE, based on the number of fitness evaluations, the whole evolutionary process is divided into two stages. In the former stage, TSEDE using a multi-population-based framework focuses on improving the searchability, which employs three popular and efficient DE variants, namely SHADE, JADE, and “DE/current-to-rand/1. ” In the latter stage, LSHADE is used to emphasize the convergence. Moreover, an elite strategy is used to ensure that the current best solution is assigned to each constituent variant at each generation. TSEDE is tested on the CEC2005 benchmark suit and compared with nine typical algorithms. The results confirm that the proposed method is very competitive.
Transfer Learning with deep Convolutional Neural Network for Underwater Live Fish Recognition

Recently, underwater video analysis are more used by marine ecologists to study fish populations as this technique is non-destructively, generates huge amount of visual data and does not perturb underwater environment. Automated methods for processing the recorded data are required because visual processing can be time consuming, subjective and costly. However, the underwater environment poses great challenges due to changes in luminosity, complex backgrounds and free movement of fish. In this paper, we present a convolutional neural network that was trained with transfer learning framework for fish species recognition. First, we use the original AlexNet model to extract fish features from images on the available underwater dataset. Then, to improve the performance, we fine-tune the model on the dataset. Finally, we re-extract features after that AlexNet has been fine-tuned. We use a linear SVM classifier for species classification. The proposed approach reach an accuracy of more than 99% that demonstrates its effectiveness.
Arbitrary Category Classification of Websites Based on Image Content

This paper presents a comprehensive methodology for general large-scale image-based classification tasks. It addresses the Big Data challenge in arbitrary image classification and more specifically, filtering of millions of websites with abstract target classes and high levels of label noise. Our approach uses local image features and their color descriptors to build image representations with the help of a modified k-NN algorithm. Image representations are refined into image and website class predictions by a two-stage classifier method suitable for a very large-scale real dataset. A modification of an Extreme Learning Machine is found to be a suitable classifier technique. The methodology is robust to noise and can learn abstract target categories; website classification accuracy surpasses 97% for the most important categories considered in this study.
Novel Approach (Intersection Point Determination Method) to Maximize The Output of Solar PV System Under Fast Changing Environmental Condition

Recently, the industries of the electricity production in the world, mainly concentrate on the commercial use and development of the Renewable Energy Resources (RER) because the availability of the Conventional Energy Resources (CER) are limited. At present, the cost of production of electricity through Solar Photovoltaic (SPV) system is significantly higher than that of CER because the production technology of SPV cells is costly. The efficient use of electricity produced can be done when SPV system work on their maximum power point (MPP). For this, a tracker (MPPT) with SPV system is required. In the industries of SPV cells, two challenges have to be faced, first is to reduce the cost of power generation and second is to maximize the output efficiency. In this paper, novel search methodology with an objective function is proposed to determine MPP of SPV system under the fast-changing environmental condition. The proposed algorithm is based on "Intersection Point Determination Method (IPDM)". Various testing benchmark systems have been used to validate the performance of the proposed method. Also, the Simulink model of the benchmark system has been prepared in the MATLAB Simulink environment, and the result of simulation has been compared with the current results.
Colonization of multidrug resistant pathogens in a hybrid pediatric cardiac surgery center

Introduction The incidence of multidrug resistant microorganisms worldwide is increasing. The aim of the study was to present institutional experience with the multidrug resistant microorganism colonization patterns observed in children with congenital heart diseases hospitalized in a hybrid pediatric cardiac surgery center. Material and methods Microbiological samples were routinely collected in all children admitted to our department. All microbiological samples were analyzed with regard to multidrug resistant microorganisms: methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), Gram-negative rods producing extended-spectrum beta-lactamases (ESBL), multidrug resistant Gram-negative rods (MDR-GNRs), carbapenemase-producing Klebsiella pneumoniae (KPC), carbapenem-resistant Acinetobacter baumannii (CRAB) and Pseudomonas aeruginosa (CRPA). Results In 30 (9%) swabs ‘alert’ pathogens from the above group of listed microorganisms were found. All positive swabs were isolated in 19 (16.1%) children. Multidrug resistant pathogen colonization was statistically significantly more often observed in children admitted from other medical facilities than in children admitted from home (38% vs. 10%, p = 0.0089). In the group of children younger than 6 months ‘alert’ pathogen were more often observed than in older children (34.1% vs. 5.4%, p < 0.001). Conclusions Preoperative multidrug resistant pathogen screening in children admitted and referred for congenital heart disease procedures may be of great importance since many of these patients are colonized with resistant bacteria. Knowledge of the patient's microbiome is important in local epidemiological control along with tailoring the most effective preoperative prophylactic antibiotic for each patient. The impact of preoperative screening on postoperative infections and other complications requires further analysis.
Efficient Divisible E-Cash in the Standard Model

We construct an efficient divisible e-cash scheme without random oracle by using the recent Groth-Sahai(GS) proof system. Our scheme is off-line and truly anonymous without a trusted third party. The efficiency of the construction of the binary tree and the withdrawal protocol are improved by exploring a new generation algorithm. Moreover, we use a technique to prove the correct monetary value spent by the user. Some security properties of our scheme, such as anonymous, divisible, unforgeability and exculpability, are proved in the standard model.
A Modular Step-Up High-Voltage Bipolar Pulse Generator

In this paper, a modular topology is presented for generating high-voltage pulsed power. The proposed structure consists of Marx-type modules, which are based on the switched-capacitor (SC) concept. This module receives an input voltage and, depending on the requirement of the user, produces an output voltage either equal to the input or twice as much as the input voltage, which shows the flexibility of our model. The capability of the module to produce a doubled output makes it appropriate for applications with low input voltage sources. Also, the topology has the capability of generating combined wide and narrow pulses. The topology was simulated in MATLAB Simulink and a laboratory setup was built to test its operation. The results validate the theoretical basis of the structure.
Overview of Smart Grids Architecture and Design

Nowadays the use of electricity has become indispensable for both individuals and factories. Due to technological development, this use is growing. This energy source is produced on demand, when this demand exceeds the capacity of the production plants, the whole system is blocked. Smart Grids have emerged to solve many of the problems of traditional networks such as the integration of renewable generation energies, or the automation of tasks to reduce the interaction of humans with the network.In this article, this work consists of a study on Smart Grids architecture and design and the impact of the assimilation of renewable energies into the electricity grid.
PWM Modulation and Control Strategy for LLC-DCX Converter to Achieve Bidirectional Power Flow in Facing With Resonant Parameters Variation

The LLC resonant converter can be used as a dc–dc transformer (DCX) to provide isolation and fixed voltage transfer ratio. For applications requiring bidirectional power transmission, this paper proposes a PWM modulation and control strategy to achieve naturally bidirectional power flow for LLC-DCX, even in the case when the resonant parameters vary. Without the loss of generality, the proposed modulation can achieve ZVS of one side switches and ZCS of other side switches. Meanwhile, the additional benefits are that the PWM logic exchanging of the primary full bridge and the secondary full bridge is avoided and the auxiliary SR circuit is not needed. This simplifies the control and makes the converter to achieve naturally bidirectional power flow. Meanwhile, according to the analysis, it can also provide a fixed voltage conversion ratio independent of switching frequency if properly designed. Furthermore, to accurately locate the zero-crossing instant of the current when resonant parameters vary, the optimal duty cycle tracking based on the perturbation and observation method (P&O) is adopted. The characteristics and design considerations of the proposed modulation and control are also presented in detail in this paper. Finally, the experimental results are given to verify the effectiveness and advantages of the proposed solution.
Image Denoising using K-SVD Algorithm based on Gabor Wavelet Dictionary

denoising problem can be addressed as an inverse problem. One of the most recent approaches to solve an inverse problem is a sparse decomposition over overcomplete dictionaries. In sparse representation, images are represented as a linear combination of dictionary atoms. In this paper, we propose an algorithm for image denoising based on Orthogonal Matching Pursuit (OMP) for determining sparse representation over Gabor Wavelet adaptive dictionary by K- SVD algorithm. The results of this algorithm have more efficiency of image recovery than using DCT dictionary.
Arterial pressure and cerebral blood flow variability: friend or foe? A review

Variability in arterial pressure and cerebral blood flow has traditionally been interpreted as a marker of cardiovascular decompensation, and has been associated with negative clinical outcomes across varying time scales, from impending orthostatic syncope to an increased risk of stroke. Emerging evidence, however, suggests that increased hemodynamic variability may, in fact, be protective in the face of acute challenges to perfusion, including significant central hypovolemia and hypotension (including hemorrhage), and during cardiac bypass surgery. This review presents the dichotomous views on the role of hemodynamic variability on clinical outcome, including the physiological mechanisms underlying these patterns, and the potential impact of increased and decreased variability on cerebral perfusion and oxygenation. We suggest that reconciliation of these two apparently discrepant views may lie in the time scale of hemodynamic variability; short time scale variability appears to be cerebroprotective, while mid to longer term fluctuations are associated with primary and secondary end-organ dysfunction.
A Four-Quadrant Three-Phase AC-DC Converter for Virtual Electric Traction Machine

Virtual electric traction machine (VETM) is a power electronic converter based system capable of emulating behavior of an electric motor. The widely used VETM systems in industrial drives testing environment, makes use of traditional two-stage AC-DC-AC converter. However, this multistage conversion requires DC link energy storage device as well as individual control algorithm. Hence, to simplify control and reduce number of converter stages, this paper proposes a three-phase AC-DC converter topology suitable for four-quadrant operation of VETM system. Unlike twelve switches in traditional AC-DC-AC converter, the proposed topology uses ten power semiconductor switches reducing switching losses. In this paper, a detailed operation of proposed converter is presented in along with simulation and experimental results for a 2 kW PMSM motor emulator.
Are the Incomes of the Managers in the Listed Companies Consistent with their Performances in the Fully Competitive Industry in China?

The listed companies in the fully competitive industry have their own characteristic, which is that a manager’s performance can often reflect the contribution of the manager due to the hard competition in the market so that the manager performance is closely linked with the manager’s income. So in the fully competitive industry, are the two consistent with each other in China? This article chooses the firms in the electronic industry in China as a sample, using paired-samples T test, cross tabs and correlation analysis from both longitude and latitude, and we finds the managers’ income is not consistent with their performance. The reason of this problem is the lag of the entrepreneurs’ labor market development and vacancy of shareholders in China.
Solar Power Based Water Pump Employing Z-Source Inverter for PMSM Drive

Single stage ZSI (Z Source Inverter) based solar PV (Photovoltaic) power conversion system is presented in this paper for PMSM (Permanent Magnet Synchronous Motor) used for water pump load. Most generic design objectives of water pumping systems are high efficiency, reliability, low maintenance and cost optimization. The proposed system eliminates the need of conventional DC–DC conversion stage for extracting the maximum power of PV array and driving a PMSM simultaneously. It results in reduced complexity with an increase efficiency and minimum voltage stress across the switches. In the proposed scheme, simple boost control approach with field-oriented control mode is used for the ZSI. The MATLAB simulation results are shown for validating the proposed concept under variations in operating conditions.