Miracle-dz/UniFAR-FTUs huggingface dataset:
Backstepping Terminal Sliding Mode MPPT Controller for Photovoltaic Systems

In this paper, a new Maximum Power Point Tracking (MPPT) control for a Photovoltaic (PV) system is developed based on both backstepping and terminal sliding mode approaches. This system is composed of a solar array, a DC/DC boost converter, an MPPT controller, and an output load. The Backstepping Terminal Sliding Mode Controller (BTSMC) is used via a DC-DC boost converter to achieve maximum power output. The stability of the closed-loop system is guaranteed using the Lyapunov method. This novel approach provides good transient response, low tracking error, and very fast reaction against solar radiation and PV cell temperature variations. Furthermore, chattering, which constitutes the main disadvantage of the classic sliding mode technique is eliminated. To show the effectiveness and robustness of the proposed control, different simulations under different atmospheric conditions are conducted in Matlab/Simulink. Keywords-backstepping; terminal sliding mode control; Lyapunov stability; maximum power point tracking; photovoltaic system
Similarities Between Human Structured Subject Indexing and Probabilistic Topic Models

: This paper adds statistical findings from natural language processing to an ongoing interdisciplinary research project between lawyers and information scientists. The project proposes an indexing scheme that follows a content grid of six predefined categories, also called facets in a broad sense. These facets try to capture the essential structure of legal information and are based on Ranganathan’s fundamental facets as well as on the famous Roman lawyer’s Gaius tripartite division of persons, things and actions. The prototype database, built as part of the project, consists of nearly 2,500 cases which have been manually indexed. The present study uses the prototype database to investigate whether similarities exist between human subject indexing and automatically clustered terms. We first examine the similarities between the indexing terms and terms generated by a term frequency–inverse document frequency approach. Then we investigate the similarities between the indexing terms and word clusters generated by unsupervised probabilistic topic models, namely latent Dirichlet allocation (LDA) and the correlated topic model (CTM). On average, the similarities of the manually indexed terms with the topic terms are not high but statistically significant, and for some cases we find strong similarities in which the clustered terms of the topic models match well the humanly indexed terms. Correlations are slightly higher when using the CTM instead of LDA. Our results indicate that topic modelling could be beneficial at least for semi-automatic indexing. Disentangling further which facets contain those terms that predominantly cause similarities with automatically clustered terms could further enhance the support for human structured subject indexing.
The Impact of Training and Development on Employee Performance of Apparel Industry in Sri Lanka

The main objective of the study is to identify how training and development affects operational level employee performance in the context of the apparel industry in Sri Lanka. The researchers carefully chosen three leading apparel sector companies in Sri Lanka for this study. The reason for selecting this research topic is that it was identified that apparel companies were facing issues where employees make errors and delays and their performance has significantly reduced. It was identified that there are mistakes and delays from machine operators’ side which affects target achievement, thereby shipment delays to the end customer. Over the last year, there was an error rate of 5 percent which causes a massive waste of materials and fabric. Key performance indicator achievement fell by 10 percent which hit revenue adversely and this has led to customers delaying payments and moving on to competitors who are more punctual. This demonstrates the importance of training and development which will reduce errors, mistakes and delays. The independent variables considered were orientation training, coaching, job rotation, mentoring and continuous job training while the dependent variable was employee performance in the apparel industry. A structured questionnaire was used to gather data which was distributed to 210 respondents who were selected on convenience sampling. The findings denoted that there is a strong positive impact of all independent variables on the dependent variable.
Online Job Search and Recruitment Platform for College Students Based on SSH

With Nowadays, human society has entered the rapid development stage of information globalization. The Internet has come into our life in an all-round way and has an impact on all aspects. More and more social activities are gradually transferring to the Internet. In order to solve the problem of difficult employment for Chinese college students after graduation, and to conform to the general trend of the development of the times, The idea of building an employment platform for college students has emerged. This system uses MyEclipse as the development tool, SSH as the basic framework, mainly uses JSP technology to develop the website, and MySQL as the database. Analyze the functional requirements of the website. The front desk is divided into student users and enterprise users. Student users mainly realize the function of viewing recruitment information and sending resumes. Enterprise users mainly realize the function of publishing recruitment information and reading resumes. The administrator can log in the background to manage user information, publish recruitment news, publish recruitment information, upload documents and other operations. The development of this website aims to achieve the employment of college students and improve the efficiency of College Students' job-hunting and enterprise recruitment.
A Modified Method of Filtering for FBMC Based 5G Communications on Minimizing Doppler Shift

For fifth-generation (5G) wireless technologies, one major problem is Doppler shift. In order to overcome this problem, a filter called Fractional Powered Binomial (FPBF) Windowed PHYDYAS filter is proposed in this paper for FBMC system. 5G communication and how Doppler shift worked in 5G communication have been explored in short here. For this the role of different parameters like Signal Interference Ratio (SIR), sub-carrier spacing, guard band has also been explored. The performances of this filter was compared with PHYDYAS filter through parameters like Signal to Interference Ratio (SIR), Bit Error Rate (BER), and impulse responses within the time and frequency domain. The performance of 5G communications and other parameters have been investigated through MATLAB simulations.
High-speed Friction Predicted Model of Tread Rubber Based on Experimental

The friction behavior of tread rubber directly affect service life of aircraft tires. In this paper, the High-speed friction tester has been developed, and friction tests with different loads and speeds have been carried out. Here, a numerical High-speed friction model is developed based on the tests. Results indicate that the coefficient decreases when the speed and load increase, and there is a power function between the load and the contact pressure. Besides, a High-speed friction predicted model is developed, which considered the influence of contact presure and speed based on the Power function friction model.
Secrecy Performance of Uplink-Downlink NOMA Network at Physical Layer

Physical layer security of a composite network, which includes both the uplink and downlink non-orthogonal multiple access (NOMA) system, has been analyzed. In this network, the relay is working as interface between the uplink and downlink NOMA system. Due to deep fading and shadowing, two legitimate destinations and the eavesdropper (EAV) are able to receive the information signals from the relay only. We have considered a scenario at the relay in which the relay decodes the strongest signal first when it does not know the transmit power of the information signals. To secure the confidential information, the jammer has been considered to secure the information from the EAV. For the considered model, the secrecy outage probability is analyzed as a performance metric using MATLAB based simulation. The optimal value of the relay transmit signal to noise ratio and the worst value of the transmit signal to noise ratio of the source one is indicated.
Quantification of Urea Adulteration with Impedance Spectroscopy in Cow Milk

Cow milk plays an important role in nutrition of human being, especially in infant stage. An attempt is carried out to quantify urea adulteration in cow milk with help of impedance spectroscopy. Designed sensor and signal conditioning circuit converts impedance of milk to voltage. This changes in impedance in turn changes in phase angle of the output signal of sensor, enables identifying milk adulterated with different percentage of urea. After confirming frequency used for detection, the effect of level of adulteration on resistance, impedance and phase angle are investigated with developed method. Experimentation endows detection and quantification of urea in Cow milk with measurement of impedance as well as phase angle of output signal. Though simple design of sensors and signal conditioning circuit, the system allows urea detection up to 70mg in 100ml of milk. The estimation of adulteration in milk with developed system is possible within 45 seconds. This time required to settle down the temperature of the milk due to addition of urea. The effect of temperature after addition of urea can further be studied.
Improving Control of a Teleoperated Robot Using an Adaptive Oscillator to Perform a Rhythmic Task for Foundry Applications

The aim of this paper is to show the interests of using dynamic oscillators in a control loop of a teleoperated collaborative robot to achieve rhythmic tasks like cleaning, brushing, strumming, etc. Indeed, dynamic oscillators have the interesting property to synchronize to an external rhythmic signal applied to its input. Experiments consist of teleoperation of compliant robot with a haptic device interfaced with a dynamic oscillator aiming to execute rhythmic movements like brushing a surface. The dynamic oscillator, which is inserted in the close-loop at the robot working space level, is able to synchronize both with the movements the human applies on the haptic device and to the external forces measured on the robot effector. Preliminary results of experiments show that the oscillator helps the operator to produce a robot movement close to a human one, while reducing by around 40% the robot power consumption compared to a control without an oscillator.
Methods of Exploiting Multispectral Imagery for the Monitoring of Illicit Coca Fields

State-of-the-art deep learning (DL) algorithms for automatic target recognition (ATR) typically rely on transfer learning from networks pre-trained on RGB imagery. In this work, we investigate the benefits of using additional spectral information contained in multispectral satellite imagery, with the targeted development of a suite of ATR algorithms to detect and segment illicit coca fields in Colombia. In support of this effort, the team curated a custom multispectral dataset of coca fields in WorldView-3 imagery, starting with Sentinel-2 annotations provided by expert image analysts. We present baseline land cover classification results using traditional methods, and compare these results to detection metrics obtained with Faster R-CNN and Mask R-CNN. The DL algorithms are run on classic RGB imagery and false color imagery, which exploits the near-infrared image content. Mean average precision metrics indicate that the standard RGB imagery outperforms false-color imagery. Deep learning-based semantic segmentation algorithms are also investigated, with a comparison between training on RGB and false color imagery. Finally, we include a discussion of ongoing research to modify state-of-the-art convolutional neural networks to accept multispectral inputs of more than three channels, while still benefitting from pretrained RGB weights.
Work Surface Arrangement Optimization Driven by Human Activity

In this paper, we aim at guiding people to accomplish a personalized task, work surface organizing, in mixed reality environment, which can also be applied to intelligent robots. Through the cameras mounted in a MR device, e.g., Hololens, we firstly capture a person's daily activities in real scene when he uses the work surface. From such activities, we model the individual behavior habits and apply them to optimize the arrangement of the work surface. A cost function is defined for the optimization, considering general arrangement rules and human habitual behavior. The optimized arrangement is suggested to the user by augmenting the virtual arrangement on the real scene. To evaluate the effectiveness of our approach, we conducted experiments on a variety of scenes.
An Efficient Machine Learning-based Approach for Android v.11 Ransomware Detection

Android ransomware is a threatening malware that is targeting individuals and enterprises. Many existing approaches suggested different ransomware detection solutions to protect users’ devices and data. These solutions used mainly static-based or dynamic-based analysis systems. However, the current solutions have considered only the old versions of Android platforms. In this paper, an efficient machine learning-based ransomware detection approach is proposed. This approach has studied deeply the latest version of Android (Version 11, API Level 30) to include the updated list of features including permissions and API packages calls that might be utilized by ransomware attacks. A new dataset was created after parsing 1000 apps to extract these features. Afterwards, different machine learning techniques were executed to generate different predictive models for Andoird ransomware. Some predictive models reached 98.3% of detection accuracy even after reducing around 26% of the overall features set.
Self-Started Piezoelectric Energy Conditioning System based on Electrostatic Driving MEMS Switch

This paper proposed a simple-structured, low cost, high-efficiency piezoelectric energy conditioning system, replacing the active electronic controllers with electrostatic MEMS switch, to decrease the intrinsic energy consumption and the complexity of the energy management circuit. With the extremely small leakage current, the average power consumption of the MEMS switch was approximately equal to as low as $1.85\times 10^{-12}\mathrm{W}$ within one charging cycle, and the highest energy conversion efficiency of 76% was obtained during testing.
ResD-Unet Research and Application for Pulmonary Artery Segmentation

In the three-dimensional reconstruction of the pulmonary artery and the identification of pulmonary embolism, experts find it difficult to accurately estimate the severity of the embolism in the pulmonary artery, due to its irregular shape and complex adjacent tissues. In effect, segmenting the pulmonary artery accurately is the basis for assessing the severity of pulmonary embolism, and it is also a challengeable task. To solve this problem, this study proposes a ResD-Unet architecture for pulmonary artery segmentation. To begin with, the U-Net network is used as the basic structure, which allows efficient information flow and good performance in the absence of a sufficiently large dataset. In what follows, novel Residual-Dense blocks are introduced in the ResD-Unet architecture to refine image segmentation and build a deeper network while improving the gradient circulation of the network. Finally, a novel hybrid loss function is utilized to make full use of the advantages of the binary cross entropy loss, Dice loss and SSIM loss. Equipped with the hybrid loss, the proposed architecture is able to effectively segment the object areas and accurately predict the structures with clear boundaries. The experimental results show that the proposed framework can achieve high segmentation accuracy and efficiency, and the segmentation results are comparable to that of manual segmentation.
Experimental and Numerical Studies of the Free Surface Flow over the Patterned Weir

The paper is concerned with experimental and numerical investigations of the flow around an immersed broad-crested weir with different cavities, in the presence of free surface. The numerics are performed with the Fluent code using the RNG $k-\varepsilon$ turbulence model coupled with VOF for the computation of the free surface. The numerical results and visualizations are corroborated with the aim to investigate the interaction between the free surface profile and the wake developed in the cavities of the broad-crested weir.
Efficient Algorithms for Point and Area Sweep–Coverage in Wireless Sensor Networks

In wireless sensor networks, coverage is a significant challenge, reflecting how well the sensor nodes (SNs) cover a target area. If we use static SNs for continuous coverage but it is energy-consuming. Instead of constant monitoring, periodic monitoring is also sufficient for content in some cases, and it is also less energy-consuming. The $t$-sweep coverage is the coverage after a given time $t$ of the points or sub-area in a target by the SNs. Determining the best set of mobile SNs to ensure sweep-coverage with a consistent speed is NP-hard. In this article, we propose a new 1.5-approximation approach for resolving the sweep-coverage issue for a chosen point of interest. The best approximation for point sweep-coverage challenge in the literature has 2-approximation. We also propose a new $1.5\sqrt{2}$-approximation area sweep-coverage algorithm for sweep-coverage problem for a chosen area of interest. The best-known approximation approach for area sweep-coverage issue has $2\sqrt{2}$-approximation. Finally, we simulate the proposed and existing and the proposed approaches are resulting better performance over the existing ones.
Field Oriented Control of Permanent Magnet Synchronous Motor with Graphical User Interface

The modern home appliances are designed with energy efficiency considerations. This paper presents the use of a permanent magnet synchronous motor (PMSM) in a washing machine and field-oriented control (FOC) for it. The main focus of this work is creating a graphical user interface (GUI) that provides an interactive set of input parameters and data output so that the user can find the optimal parameters for the system. The proposed model is verified by numerical simulation and can be generalized to a wide range of motor types and control strategies.
A Novel Method for Automatic Camouflage Pattern Synthesize

Camouflage plays an indispensable role in modern military. Generally, a camouflage pattern includes a plurality of shapes units, which are split by elemental colors. The fixed camouflage pattern is low adaptability and concealability for changeable battlefields. Moreover, the conventionally camouflage design is time and resource consuming for manual drawing. In this paper, we propose a dynamic camouflage synthesizing method. Firstly, the texture patterns of one class of battlefield images is extracted using convolutional transfer network. We use 3*3 convolution kernels to extract texture features. And the covariance matrix is used as loss function to calculate the loss of different image texture features. Colors construction and their distribution of the specified battlefield images is extracted according to a clustering-based algorithm. Finally, the statistical color units are embedded into the texture patterns. We assess the adaptability and the concealability of synthesized camouflage using Eye Tracking based criteria. Comparing to the People’s Liberation Army Type 87 woodland pattern and the digital camouflage pattern synthesized using our previous method, testing results of our synthesized camouflage patterns were better in different saccade indicators. This demonstrates camouflage pattern synthesize proposed got better concealment and the validity of proposed method. Besides, we also compared our method with local binary pattern for extracting texture features. The experiments results indicated the method proposed had better consistency to the scene images.
A Compact and Symmetric UWB Bandpass Filter using Stepped Impedance Resonator (SIR) and Defected Ground Structure (DGS)

In this paper, a compact and symmetric Ultra-Wide Band Bandpass filter (UWB-BPF) is designed on a low loss RT Duroid 5880 substrate. The proposed filter is constructed by stepped impedance resonator (SIR) on the top side and defected ground structure (DGS) in the bottom. The ground plane is etched by circular patch, square and vertical slots to enhance the performance of the filter. Simulations are carried out in HFSS software. The outcome of the filter in terms of 3 dB bandwidth is about 8 GHz covering the frequency range from 2 to 10.1 GHz with a Fractional bandwidth of 106.7%. From the filter response, it is observed that the filter is highly selective with two transmission zeros and three attenuation poles at 3.6 GHz, 6.7 GHz and 8.7 GHz. The parametric analysis of the filter with variation in structural parameters is also presented.
How Can Video Game Atmosphere Affect Audience Emotion with Sound

Sound plays a vital role in the medium that delivers the message and enhances the viewer experience as well. From research and testing methods, it can be seen that the sound has an impact on the listener, however the degree of impact depends on the experience of the audience that can be resonated with that or the mental strength of the listeners. In addition, the degree of impact depends on the type and other elements of the medium that create a great environment for the audience to feel more easily. All of these findings prove that sound can create ambience and change the mood of an audience. But other elements are needed to create a perfect atmosphere and influence the audience's mood.
High Data Transfer Rate Spatial Division Multiplexing for Short Range non-Line-of-Sight Ultraviolet Optical Transmission

To overcome the inherent bandwidth limitation of non-line-of-sight (NLOS) ultraviolet communication (UVC) channel, a novel space division multiplexing (SDM) framework based on non-coplanar rotation angle is established. The influence of SDM structure parameters on inter-channel interference (ICI) is studied to obtain the optimal antenna configuration. And a Gaussian approximate distribution (GAD) signal detection model is presented, which simplifies the calculation of the Bit error rate (BER) of the Photon multiplier tube (PMT) reception and is suitable for complex ICI analysis. Furthermore, a low ICI scheme based on the relationship between BER and the interference factor is proposed to increase the data transmission rate or reduce the alignment configuration. As a result, the maximum data rate increases to 34 Mbps, or the alignment demand decreases by 33.33% at most. Moreover, these analysis results and techniques can be applied to other NLOS scattering optical wireless communication systems.