Miracle-dz/UniFAR-FTUs huggingface dataset:
Machining surface extraction method for shaft gear parts based on Mask R-CNN

Regarding the surface structure of shaft gear parts is complex, the difficulties of detection are that complex background and reflection of shaft gear parts might interfere the detection. Besides, the different types of defects in different areas cannot be detected independently. Therefore, it is necessary to extract each machining region. Traditional region extraction methods cannot effectively separate the object area from the background area due to the complex background and unclear boundaries. A region extraction method for shaft gear parts was offered in this study, which was based on Mask R-CNN. First of all, ResNet50 was used as the feature extraction network to extract the features of the image; then the feature pyramid network (FPN) was applied to fuse the information of different scale feature maps; in the next step, the region of interest (ROI) was generated by the region proposal network (RPN); finally, the machining region was segmented by the head network. Combined with the structural characteristics of the shaft gear, the model parameters were constantly adjusted to improve the accuracy of the model training process. The trained model was tested on the manually marked shaft gear data set. AP (Average Precision) value was 89.2%. With regard to segmenting complex background regions, experimental data suggested that the Mask R-CNN method is an effective approach which could achieve high-precision extraction of the machining area for shaft gear parts.
Coordination of Directional Overcurrent Relay Using PSO-DE Algorithm

A power system network has dynamic and complex characteristics. The continuity of electricity supply to customer side from the generation in stable, secure, and reliable is being a top priority to be considered. Preserving an operation of a power system on its operating point depends on its protection system scheme. Furthermore, carrying out the protection system requires a relay setting that can coordinate to carry out security. However, calculating the time dial setting (TDS) and the pickup current on each relay for practical work in industry is more difficult, complex, and takes a long time. In this paper, the directional overcurrent relay (DOCR) protection is coordinated by using hybrid particle swarm optimization - differential evolution (PSO-DE) algorithm. The proposed method is to minimize the TDS time and operating time of the relays by satisfying the protection coordination requirements. The simulation results showed that the total operating time and TMS using PSO-DE have faster operating times and TDS than other optimization algorithms.
Encapsulated gate-all-around InAs nanowire field-effect transistors

We report the fabrication of lateral gate-all-around InAs nanowire field-effect transistors whose gate overlaps the source and drain electrodes and thus fully encapsulates the nanowire channel. They feature large drive current and transconductance that surpass those of conventional non-gate-overlap devices. The improved device characteristics can be attributed to the elimination of access resistance associated with ungated segments between the gate and source/drain electrodes. Our data also reveal a correlation between the normalized transconductance and the threshold voltage, which points to a beneficial effect of our wet-etching procedure performed prior to the atomic-layer-deposition of the gate dielectric.
The Effect of Temperature and Humidity on Indoor LoRa Propagation Model

LoRa (Long Range) networks tend to be a prevailing technology for smart buildings applications. Its Chirp Spread Spectrum (CSS) modulation technique allows for higher receiver sensitivity. However, its unstable behaviour in terms of electromagnetic propagation motivated this paper to assess the influence of these parameters under temperature and humidity variations on the reliability of LoRa connectivity. The current work suggests a method that takes into consideration the indoor fluctuation of temperature and humidity. The current method is based on the Multi-Wall propagation Model (MWM) aiming at path loss calculation. Simulation results were verified with real- life measurements carried out in a Neapolis University Pafos (NUP) building. The simulation results are in good agreement with the measured data. Nevertheless, the study revealed that the environmental factors of temperature and humidity have a smooth effect on indoor path loss calculation.
Using Image Registration Method to Register UAV

For the UAV’s characteristics that is the date of camera shooting and photographing and digital map contain information, a UAV target location method is presented based on image matching. Firstly, using the artificial reconnaissance registration method that has improved, the UAV aerial images that consider digital map coordinates as the target are registered to obtain registration information. Then, the UAV video frame resolution containing the target is improved by improving the method of super-resolution reconstruction. Finally, making use of the Gaussian pyramid matching algorithm based on optical flow, the video frames are registered with the aerial to complete the target. By MATLAB and C++ simulation, achieving the above algorithm. The results proved that this method achieve the target location without the UAV position and attitude information, while improving the precision and speed of target location, that is an effective method for target location in the battlefield.
Degradation of Elastic Response of MMC Laminated Tubes due to Internal Fiber Cracks

Previous experimental work has shown a reduction in the effective elastic response of [±45°]s SiC/Ti composite tubes under axial and torsional loading. There is considerable evidence of fiber/matrix debonding in off-axis plies and the presence of preexisting fiber cracks, extending radially from the carbon core of the SiC fiber, is also well documented. In this work, the Generalized Method of Cells (GMC) micromechanical model is used to calculate a constitutive equation for the composite material in each ply, in the presence of fiber cracks or fiber/matrix debonds. These constitutive equations are used in the exact analytical solution for the problem of an arbitrarily laminated tube under axisymmetric or torsional loading. By employing GMC in the solution to the tube problem, predictions are made as to the degree of degradation of the elastic response of these tubes due to partial or full debonding of the fiber/matrix interface or preexisting fiber cracks or a combination of both. These theoretical predic.
Bioengineering Strategies for Developing Vaccines against Respiratory Viral Diseases

Respiratory viral pathogens like influenza and coronaviruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have caused outbreaks leading to millions of deaths. Vaccinations are, to date, the best and most economical way to control such outbreaks and have been highly successful for several pathogens. Currently used vaccines for respiratory viral pathogens are primarily live attenuated or inactivated and can risk reversion to virulence or confer inadequate immunity. SUMMARY Respiratory viral pathogens like influenza and coronaviruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have caused outbreaks leading to millions of deaths. Vaccinations are, to date, the best and most economical way to control such outbreaks and have been highly successful for several pathogens. Currently used vaccines for respiratory viral pathogens are primarily live attenuated or inactivated and can risk reversion to virulence or confer inadequate immunity. The recent trend of using potent biomolecules like DNA, RNA, and protein antigenic components to synthesize vaccines for diseases has shown promising results. Still, it remains challenging to translate due to their high susceptibility to degradation during storage and after delivery. Advances in bioengineering technology for vaccine design have made it possible to control the physicochemical properties of the vaccines for rapid synthesis, heightened antigen presentation, safer formulations, and more robust immunogenicity. Bioengineering techniques and materials have been used to synthesize several potent vaccines, approved or in trials, against coronavirus disease 2019 (COVID-19) and are being explored for influenza, SARS, and Middle East respiratory syndrome (MERS) vaccines as well. Here, we review bioengineering strategies such as the use of polymeric particles, liposomes, and virus-like particles in vaccine development against influenza and coronaviruses and the feasibility of adopting these technologies for clinical use.
Short Term Wind Speed Forecasting Based on Feature Extraction by CNN and MLP

At present, most of the short-term wind speed forecasting researches directly use the original data as the input or break them down, and take the decomposed series as the input for forecasting model. There is a lack of feature analysis of the original data and the decomposed series. In this paper, from the perspective of feature analysis of wind speed, Ensemble Empirical Mode Decomposition (EEMD) and Convolutional Neural Networks (CNN) are used to decompose the sequence and extract features, and Multilayer Perceptron (MLP) is used to predict the wind speed. Firstly, EEMD is used to decompose the wind speed into a series of subsequences; Secondly, CNN is used to extract the features of each decomposition layer, and the input variables of each decomposition layer are constructed; Finally, MLP is used to predict each decomposition layer; At the same time, Adam is used to optimize the parameters of CNN and MLP. The results of case study and comparison show that EEMD-CNN-MLP-Adam has high prediction and good generalization, which can provide reference for wind speed prediction in different regions and periods.
Design and Optimization of a BLDC Motor for Small Power Vehicles

This paper aims to present the steps in designing of a BLDC motor for small power vehicles, in which the dimensions are imposed by adopting the direct-drive concept applied to a 12-inches wheel. The motorized small power vehicles legislation imposes a maximum power and a limited speed for certain skills in driving on the public streets. These are the initial condition in developing such kind of motors for electrical motorcycle.Using special software, the designed stage allows a parametric analysis to obtain an optimized mechanical solution and a good electromagnetic configuration of the in-wheel direct-drive motor. Skewed slot construction is adopted in the optimization process, which seems to be a good solution in the improvement of the cogging torque and also a possibility to increase the speed of the motor at low resistant torque, for this motor topology with 24 stator slots and 22 rotor permanent magnets.
Research on Dynamic Reactive Power Coordinated Control Strategy of Doubly-fed Wind Turbine Based on Improved Genetic Algorithm

Exploiting the reactive voltage regulation capability of a doubly-fed induction wind generator (DFIG) and improving the reactive power response speed of wind turbines are important tasks in enhancing a power system’s voltage stability. This approach determines the reactive power distribution scheme of the two based on the regulation capacity of the stator and grid-side converter of a 1.5MW DFIG in the West Mongolia Power Grid. When the system reactive power demand surpasses the DFIG reactive power output limit, an additional active power control based on the reactive power difference is suggested. The improved genetic algorithm (IGA) is adopted to determine the additional controller parameter values. This control reduces the minimum output active power of the unit while ensuring that the reactive power output limit is increased to meet the reactive power demand of the system. Ultimately, the accuracy of the control strategy is validated through experiments.
Stock Prediction by Analyzing the Past Market Trend

In contrast to the sudden change in global scenario with respect to shifting of things to online on a vast scale and unprecedented fluctuation of the global market, stocks have gained a lot of attention. Market prediction has always been an enigma for investors. Whether it be decoding the way market repeats itself or analyzing the trends that could help get better value for the investment, investors have always been keen on finding an efficient solution that could predict the price with utmost accuracy. This paper presents a study of different technologies that are currently being used for analyzing and predicting the stock market trend. The analysis of past trends has been done using the values for previous close, open, high, low, and close of the stock for a period of six years from the data that has been gathered from the stocks registered on the National Stock Exchange (NSE). For handling such a huge dataset and analyzing the trend in it, Python and R programming languages have been extensively used.
Single-Point Mutations in the N Gene of SARS-CoV-2 Adversely Impact Detection by a Commercial Dual Target Diagnostic Assay

This paper reports the identification of single-point mutations in the N gene of SARS-CoV-2 associated with a gene target failure by the Cepheid Xpert commercial system. In order to determine the mutation(s) responsible for the N gene detection failures, the genomic products from the Cepheid Xpert system were sequenced and compared to whole genomes of SARS-CoV-2 from clinical cases. ABSTRACT Accurate and rapid diagnostic tests are a critical component for the early diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and of the overall control strategy for the current pandemic. Nucleic acid amplification tests are the gold standard for diagnosis of acute SARS-CoV-2 infection, and many real-time PCR diagnostic assays have been developed. Mutations that occur within the primer/probe binding regions of the SARS-CoV-2 genome can negatively impact the performance of diagnostic assays. Here, we report two single-point mutations in the N gene of SARS-CoV-2 associated with N gene target detection failures in the Cepheid Xpert Xpress SARS-CoV-2 assay, the first a C to T mutation at position 29197, found in five patients, and the second a C to T mutation at position 29200, found in eight patients. By sequencing the Xpert amplicons, we showed both mutations to be located within the amplified region of the Xpert N gene target. This report highlights the necessity for multiple genetic targets and the continual monitoring and evaluation of diagnostic assay performance. IMPORTANCE This paper reports the identification of single-point mutations in the N gene of SARS-CoV-2 associated with a gene target failure by the Cepheid Xpert commercial system. In order to determine the mutation(s) responsible for the N gene detection failures, the genomic products from the Cepheid Xpert system were sequenced and compared to whole genomes of SARS-CoV-2 from clinical cases. This report is the first to our knowledge which characterizes the amplified PCR products of the Xpert system, confirming the mutations associated with the gene target failure. The mutations identified have previously been reported.
Comparison of the Efficacies of Topical Anaesthetics in the Reduction of the Pain during Peripheral Intravenous Cannulation: A Randomised Trial

Objective This study aimed to compare the efficacies of two different topical anesthetic agents and placebo in the reduction of the pain observed during intravenous (IV) cannulation. Methods Study enrolled a total of 129 healthy male donors and IV cannulation was performed to antecubital region. The donors were assigned into three groups. Prilocaine-lidocaine mixture cream (E), lidocaine spray (X) and Placebo cream (P) were given to patients. After the administration the donors were waited for approximately 45 minutes. The pain experienced by the donors after the insertion of 16 gauge cannula in arms was recorded as “pain experienced at minute 0, 5 and 15” on 100 mm visual analog scale (VAS). Results In the first group, there was no significant difference between mean VAS scores recorded after the administration of prilocainelidocaine mixture cream and lidocaine spray before IV cannulation. Mean VAS value was 9.1 mm with prilocaine-lidocaine mixture cream and 9.3 mm with lidocaine spray. In the second group, we detected significant difference between mean VAS scores recorded after the administration of lidocaine spray and placebo cream. Mean VAS value was 9.8 mm with lidocaine spray and 24.3 mm with placebo (p<0.05). In the third group, we found statistically significant difference between VAS scores recorded after the administration of prilocaine-lidocaine mixture cream and placebo cream. Mean VAS value was 8.8 mm with prilocaine-lidocaine mixture cream and 33.0 mm with placebo cream (p<0.05). Conclusion Although both agents administrated before IV cannulation were superior to placebo in adult patients in this study, we can state that these drugs were not superior to each other and showed similar efficacy.
Collaboration between courses in the interdisciplinary course Food Microbiology

Food Microbiology is an interdisciplinary 12.5 ETCS second-year) course in a CDIO-based Bachelor of Engineering program in Food Science at The Technical University of Denmark (DTU). The course was first offered in 2011. Each session in the Food Microbiology course combines theory and practice in order to strengthen the students’ application-oriented competences and engagement. In this paper the results from the evaluation of the course will be presented and a discussion will be carried out about how the students responded to the multidisciplinary, real-life projects and how it affects student learning. The aims of this study were to test 1) the students’ perception combining theory with small laboratory exercises and 2) the students’ perception of how the course collaborates with and combines theories and practices from other current semester courses. The students evaluated the course in general using the Course Experience Questionnaire (Ramsden, 1991) and by answering a questionnaire concerning the collaboration between the other courses. It can be concluded that the combination of: theory/laboratory exercises/report writing stimulated the students’ motivation and that collaboration between other mandatory semester courses mainly was rated positively by the students.
A Text Matching-based Knowledge Fusion Method For Power Metering Domain

In the process of constructing the knowledge graph in the domain of electric power metering, the knowledge often comes from several different data sources, and because of the differences in structure and content among the data sources, there are also problems of multiple meanings of words and unclear referents in the integration of the acquired knowledge. Therefore, knowledge fusion processing is needed to eliminate the ambiguity of entities and attributes in terms of denotation. This paper proposes a knowledge fusion method based on text matching technology. The method includes three core steps. Firstly it use a crawler system to obtain corpus data. Secondly it use the BERT-based knowledge extraction model to extract knowledge and build the entity information knowledge base. Finally the entities are matched at the semantic level to complete the knowledge fusion process. The experimental results prove that the knowledge fusion effect of the method in this paper is good and the entity matching rate is high.
An Overview of Electric Vehicle Charging Data Acquisition and Grid Connection Standards for Power System Studies and EV-Grid Integration

Electrification of the transportation sector has been one of the major focuses for worldwide emission reduction. The growing number of electric vehicles (EVs) result in a higher number of charging stations, which brings some concerns related to the secure and efficient operation of power networks. A fundamental challenge impeding progress on forecasting, planning, and regulatory reform in the EV grid integration arena has faced a lack of access to relevant EV data sets. Alongside, the standardization of the EV charging stations and grid interfaces are also of extreme significance to enable EV adoption. Indeed, there are several components of EVs that need to be standardized for convenient and safe vehicle use. Thereby, in this research paper, a comprehensive review of EV data acquisition and grid connection standards have been presented, comprising of twenty-one different EV charging data repositories from various countries and a summary of the existing standards associated with EVs and their interconnecting components. This document will provide guidance to the EV researchers and practicing engineers.
A Wide Load Range ZVS Inverter for Radio Frequency Capacitively Coupled Plasma

Capacitively Coupled Plasma (CCP) is widely used in thin film deposition, dielectric etching and dusty plasma experiments. Plasma generation is important equipment for CCP. It needs to output an adjustable radio frequency voltage within a wide load range. However, the current plasma generation is commonly composed of radio frequency power amplifier and matching network, which leads to either low power density or low frequency stability. In this paper, an inverter topology is proposed. It can realize zero voltage switching (ZVS) operation within a wide load range, thus generating CCP directly. The voltage gain and the ZVS operation condition are analyzed in detail. A step-by-step parameter design method is given. A 13.56-MHz 25-W prototype inverter which can realize ZVS within 0-1.2k$\Omega$0-130pF is tested in CCP discharges with argon, and the experimental results demonstrate the feasibility of the inverter and the effectiveness of the parameter design.
GREEN SUPPLY CHAIN MANAGEMENT: A LITERATURE REVIEW

Sustainable development has made remarkable progress in establishing environmental and social sustainability towards operations management and the supply chain. Manufacturers in the late 1980’s went beyond what was required in the legislation and went for a greener approach in their operations systems. The purpose of this paper is to briefly review the literature of the green supply chain management (GrSCM) over the last twenty years. The key themes that came out of the literature are: green operations, green design, green manufacturing, reverse logistics and waste management. This paper will briefly discuss these issues. This paper will also mention the reasons why organisations would opt for a green supply chain. This essay will then conclude that there is a gap in the literature in terms of the stakeholder views towards green supply chain management. Knowing the different stakeholders’ views to greening initiatives requires qualitative study such as interviews – to portray the different views about the concept and how this would implicate management decisions.