Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Aquatic Exercise Therapy on the Quadriceps Muscle Electromyography and Pain in Women with Knee Osteoarthritis

Purpose: Osteoarthritis is one of the biggest problems of the elderly population which may lead to disability and health problems and has socioeconomical consequences. Therefore, a therapeutic method that can help these people and reduce the complications of this disease has great importance. The aim of this study was to investigate the effect of aquatic exercise therapy on the quadriceps muscle electromyography and pain management in women with knee osteoarthritis. Methods: Thirty elderly women with knee osteoarthritis were selected and then divided into two groups by simple random sampling, experimental (age: 58.73±4.78) and control (age: 56.93±5.43). It should be noted that the average age of the experimental and control groups was not significant (P=0.344, t=0.963). The experimental group did aquatic exercise therapy for a period of 20 sessions with a frequency of five sessions per week, and each session lasted for 60-45 minutes. Before and after the intervention, the electrical activity of the quadriceps muscles using surface electromyography biovision made in Switzerland and pain using a visual pain scale (Visual analog scale) were measured. Data were analyzed by paired and independent sample t-test at a significance level of p≤0.05. Results: Although aquatic exercise therapy did not have a statistical significance on electrical activity of the vastus medialis oblique (p=0.711), vastuslateralis (p=0.494) and rectus femoris muscles (p=0.831), however, it increases the mean of the electrical activity of the muscles. Results also showed this training reduce pain in patients (p=0.001). Conclusion: Aquatic exercise therapy had no desired effect on quadriceps muscle electromyography. However, this trial has a desirable effect on reducing pain in women with knee osteoarthritis.
Global B-Spline Approximations of Singular Real Algebraic Plane Curves

This paper proposes an algorithm for globally approximating real algebraic plane curves of degree k with B-spline curves of the same degree. Each connected component is approximated with a B-spline curve. It is suitable for all irreducible real plane algebraic curves with arbitrary genus (including singular curves). This method is based on our blowup sampling method of algebraic curves, which solves the difficult problem of sampling around singular points in essence. The experimental results show that the algorithm achieves better accuracy than the
Adaptive Affinity Learning for Accurate Community Detection

The task of community detection has become a fundamental research problem in complex network analysis. Intuitively, similar nodes are more likely to be contained in the same community. However, most existing community detection methods cannot extract the intrinsic similarity between nodes. Thus, they may fail to identify the real community structures. In this paper, we propose to learn an affinity matrix adaptively, which can capture the intrinsic similarity between nodes accurately, and therefore benefit the community detection results. Specifically, the proposed model first embeds each node into a low-dimensional space through a transformation matrix with the community structures being preserved. Then, our model learns the affinity matrix in this low-dimensional space. The affinity matrix is further utilized to guide the learning of the community membership matrix via manifold regularization. The above three matrices are learned simultaneously and updated iteratively under the framework of Alternating Direction Method of Multipliers (ADMM). Extensive experiments show that our model can outperform the state-of-the-art approaches.
A Data Collection Collar for Vital Signs of Cows on the Grassland Based on LoRa

In recent years, animal husbandry in China has developed rapidly. However, due to poor network environment in pastoral areas, IoT technology is difficult to apply. Due to the lack of effective supervision, livestock suffer from varying degrees of health problems. This has seriously affected the development of animal husbandry. The emergence of lowpower, long-distance Internet of Things technologies, represented by Lora, has made it possible to establish a realtime monitoring system for the behavior of livestock. This system includes nodes, gateways, and servers, and is based on LoRaWAN. These nodes take the SX1278 as the core and integrate the STM32L151 low-power controller, GPS, and accelerometer. The system is tested and analyzed. The experimental results show that the scheme has the characteristics of long communication distance, low power consumption, convenient networking, and good real-time performance. It has a wide range of application prospects.
Investigation of Non-Contact Biometric System Using Capacitive Coupling Electrodes

Recently road accidents caused by drivers falling sleep has been increasing among other car accidents. Many studies report that drowsiness occurs during driving, and it is required to develop the driver drowsiness detection system. In this study, the authors use capacitive coupling electrode sensors that enable sensing the condition of a person while driving a car without physical constraints and even being unaware of the device. This paper explains about the measurement principles of capacitive coupling electrodes, the configuration of analog circuit, and a digital filter for $R$ wave detection algorithm using a microcomputer are described. Thereafter, experiments to prove the created system can measure the RR interval are described. Further, it is shown that the RR interval measured by the system is as accurate as a cardiograph equipment electrocardiograph.
Layout Geometry Impact on DDSCR Devices for High Voltage ESD Protection

DDSCR devices with finger-type, snake-type and track-type layout are studied and fabricated in $0.5\mu \mathrm{m}$ 18V CMOS process. The finger-type DDSCR achieves the highest failure current about 13.06A, which is also the device that occupies the smallest chip area in three layout styles. In view of the efficient discharge capability (It/area), the finger-type structure provides more than 50% and 66% current handling capability per area higher than the snake-type and track-type, respectively. Due to its better area efficiency, the finger-type structure should be a promising layout of the DDSCR in the input and output ports ESD protection applications.
Comparison of Magnetic Field Distribution in Induction Machines with Different Types of Combined Star-Delta Stator Windings

Two basic types of induction machines with combined star-delta stator windings have been analyzed by means of numerical simulations based on lump parameter and finite element method models. The use of suitably designed combined star-delta winding may lead to the suppression of selected high spatial harmonics of the magnetic flux density in the air gap and, thus, to an improvement of the energy efficiency. The results of numerical simulations are verified by measurements on an experimental machine.
Design and Application of Intelligent Data Mining Algorithm for Utility Indexes System of Distribution Automation

A Data-Mining algorithm based on the Support-Confidence-Lift Framework is designed to mine strong association and correlation rules, conforms to the logic of distribution automation system, from the mass and poor-quality historical database of distribution automation system. And two of the four core utility indexes of distribution automation system combined with the historical database of a certain practical distribution grid are taken as the case to illustrate the application of this algorithm. Furthermore, the indexes calculated with or without the data-mining algorithm and their corresponding statistical data are compared and studied carefully. The comparison fully demonstrates that the powerful ability of the algorithm to excavate hidden information and relationships among mass data is valuable to the practical electrical distribution engineering.
Analysis of IoT-Enabled Solutions in Smart Waste Management

Internet of Things (IoT) has attracted widespread applicability not only limited to smart cities and communities but also in water, waste management and so on. It strength lies in the high impacts it created in the daily life and the potential user's behavior. However, for it to be more effective and increase its adoption, it is require to be energy efficient, able to communicate and share information across extended coverage. Existing technology such as Low Power Wide Area Network (LPWAN) with Long Range (LoRa) has been promising. In the perspective of waste management, several different IoT-enable solutions have been proffered with each having its own strengths and weaknesses that requires improvements. Therefore, this paper performs a review of existing IoT-enabled solutions in smart cites' waste management to bring together the state-of-the-art. The objective is to gain insights into the strengths and weaknesses in order to bring improvements and innovations to manage waste effectively and efficiently as well as maintain a healthy environment in our cities. We performed reviews on 15 research articles in the literature and the results obtained shows that existing solutions were similar in the technologies used but have some drawbacks such as sensing accuracy hindered by various weather conditions, users prone to unauthorized access and short range capabilities. This thus, calls for further improvement and innovation.
A Tunable Fraud Detection System for Advanced Metering Infrastructure Using Short-Lived Patterns

We propose a fraud detection systems (FDS) for advanced metering infrastructure based on anomaly detection on the energy consumption reports from smart meters. Fraud inspection is triggered when a discrepancy between the energy supplied by the grid and that reported by smart meters is detected. We use an innovative approach, where consumption reports registered shortly before and after the discrepancy detection are compared to detect a fraud. Our FDS introduces an important innovation by showing that it is possible to use only a small set of recent measures to define a consumption pattern. We call these patterns short-lived because they are expected to represent the behavior of a consumer for a short period, only enough to detect an ongoing fraud. This approach allows the FDS to account for natural changes in the consumption behavior of users and also helps to preserve their privacy. The FDS can be tuned, using an optimization procedure, by imposing constraints on the true or false alarm rates, or maximizing an objective function that represents the revenue of the utility.
Assessment Method of Wind Farm Harmonic Emission Level Based on Improved Covariance Characteristic of Random Vectors

The wind farm side harmonic impedance could not be neglected when assessing the wind farm harmonic emission level. Because of the low impedance characteristic of the wind turbine filter. This paper presents a new method to estimate the wind farm harmonic emission level at the point of common coupling (pee) based on improved covariance characteristic of random vectors. According to the topological structure of the wind farm, the equivalent harmonic impedance of the wind farm is calculated, with the measured data at pee the wind farm harmonic source is obtained. Since the system side harmonic source and wind farm side harmonic source are approximately independent, the background harmonic related term can be eliminated by using the covariance characteristic, then the system side harmonic impedance can be calculated. We can calculate the wind farm harmonic emission level. The harmonic impedances of wind turbines are aggregated to simplify the calculation of the wind farm side harmonic impedance. Based on the results of simulation and measured data, it verifies that the proposed method is effective to eliminate the background interference when evaluate wind farm harmonic emission level, and the proposed method is also effective when the background harmonic is large.
Mupsych App für Android Smartphones: Eine neue Möglichkeit für music experience sampling

Um die alltägliche Musiknutzung zu erfassen, wurden bislang verschiedene Ansätze des Experience Sampling eingesetzt. Diese Methode wurde bereits in den 1980er Jahren entwickelt und vielfach in der Musik- und Mediennutzungsforschung eingesetzt. Dieser methodische Ansatz versucht es zu ermöglichen, dass Hörer im Alltag zu ihrem Konsum befragt werden können. Allerdings sind viele der Studien die auf Experience Sampling beruhen mit einigen Limitationen behaftet. Eine moderne und rezeptionsnahe Möglichkeit für die Messung alltäglicher Musiknutzung über internetfähige mobile Endgeräte mit einem Android Betriebssystem bietet die App MuPsych. Mithilfe dieses Programms können Nutzer direkt während der Musikrezeption oder zu weiteren bestimmten Zeitpunkten über ihr eigenes persönliches Endgerät befragt und ihr Musikkonsum fortlaufend erfasst werden. Der vorliegende Artikel stellt zunächst die Forschungstradition des Experience Sampling kurz dar, um dann auf die Funktionen, die die App MuPsych für diese Erhebungsmethode bietet einzugehen. Schließlich wird beschrieben wie die App nutzbar für eigene Forschungsvorhaben gemacht werden kann.
Development of Nano UAV Platform for Navigation in GPS-Denied Environment Using Snapdragon

In order to develop a nano UAV in a GPS-denied environment, a visual-inertial system (VINS) consisting of a monocular camera and a low-cost inertial measurement unit (IMU) should be integrated, as they make a minimum, ultra lightweight sensor suite that enables both autonomous flight and sufficient environment awareness. Although there are numerous potential applications, getting to understand the structure of the flight platform can be cumbersome and confusing. Packages and resources provided on the Qualcomm developer network (QCN) and their official GitHub group ATLFlight contain un-unified and disorderly chunks of information. In this paper, we present an organized documentation that presents in detail, the platform structure as a whole, from hardware to software architecture, including installation and API related applications.
Design of Multiphase Single-Switch Impedance-Source Converters

Focus is on the design of a multiphase galvanically isolated quasi-z-source dc-dc converter based on the single-switch topology. A novel control approach uses phase shedding for input-parallel-output-series architecture to achieve a wide input voltage regulation range. Current ripples are analyzed to implement the quasi-Z-source network with discrete and coupled inductors. Proposed approach provides for modeling of the latter taking into account leakage inductances of the coupled inductors and interactions between cells and the wiring inductance. An experimental prototype rated for 300 W, capable of delivering the rated power within the input voltage range of 10 V to 60 V was used. Experimental results demonstrate the performance of the developed concept implemented with resonant currents in the isolating transformer. Influence of the voltage-dependent resonant capacitance on the converter operation was analyzed.
Coordinated Control Strategy and Simulation Analysis of Hybrid Energy Storage System for Wind Farm

With the rapid development of new energy power generation technologies such as wind power and photovoltaic, the fluctuation of new energy output power caused the obvious change of voltage value, which affected the power supply quality and the stable operation of the power system. The paper analyzed the short-term rapid and high-power charging and discharging characteristics of super capacitor in hybrid energy storage system. Proposed the method of using power decoupling and voltage stabilization control strategy of four-quadrant voltage source converter and bidirectional DC/DC converter to suppress the wind farm output power fluctuation. The wind farm accessed with the hybrid energy storage system is simulated and analyzed in DigSILENT/PowerFactory. Simulation results indicated the effectiveness of the coordinated control strategy in suppressing the fluctuation of the wind farm output power and improving the stability of the voltage stability.
Economic Operation of PV-DG-Battery Based Microgrid with Seamless Dual Mode Control

This paper presents an economic operational control for solar photovoltaic (PV)-diesel generator (DG)-battery based microgrid, in standalone (SA) as well as grid connected (GC) modes. This system achieves multiple objectives of maintaining power quality at the grid and the DG currents free of harmonics inspite of the nonlinear loads, seamless synchronization of the grid and DG, maximizing the renewable power harnesssed, minimizing the fossil-fuel based DG power and maximizing its fuel efficiency by operating it on 80% to 100% of its rating. The total harmonics distortions (THDs) in grid current and load voltage are maintained as per the IEEE 519 standard. Moreover, the synchronization and load voltage interruption periods have been maintained within limits as per the IEEE 1547 standard. Furthermore, the battery energy management system (BEMS) is used to regulate battery current and maintain its state of charge (SOC). This system with proposed control is simulated in MATLAB/Simulink to demonstrate satisfactory performance in different scenerios.
A Strong and Practical Authentication Mechanism Using PassText and OTP

Nowadays, especially with technology’s fast development and the constant increase of the computational power, password authentication mechanism is not enough anymore to provide complete protection which makes securing data a harder task every day. This paper aims to implement a strong authentication mechanism with a practical reauthentication technique that answers the research question “how to increase the security of the authentication mechanism without sacrificing convenience? ”. The proposed solution is a combination of a text file that the user has to modify, “PassText”, and a one-time password “OTP”. This paper is based on achieving four main solution requirements: convenience, security, cost, and speed. Our proposed solution breaks the rules of security-convenience tradeoff by providing an intelligent authentication combination that provides security and convenience at the same time.
Prescriber Computer Order Entry: System Design

This continuing feature will inform readers about the process of implementing, maintaining, and supporting prescriber computer order entry (PCOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.
Comparison of Joint Friction Estimation Models for Laboratory 2 DOF Double Dual Twin Rotor Aero-dynamical System

Twin Rotor Aero-dynamical System (TRAS) include non-negligible nonlinearities due to frictions in the joints. In this study, joint frictions of the 2 DOF Double Dual Twin Rotor Aero-dynamical System (TDDTRAS) were estimated based on experimental data and simulation dynamic responses. Three different friction estimation models such as Non-Conservative, Linear, and a Non-linear friction models were compared to estimate the joint frictions of the (TDDTRAS) developed in our laboratory. Based on comparative experimental friction analysis, the joint frictions of the (TDDTRAS) are estimated better using Non-Linear friction model (NLFM). The mathematical model with NLFM is developed for simulation and controller. A robust dynamics model was obtained by the NLFM which will be used in the inverse dynamic model for the PID controller. PID controllers designed based on the mathematical model with nonlinear friction model. Accurate inverse model and the joint friction compensation improved PID controller performance for the TDDTRAS.
Optimization of Switched Reluctance Motor Drive Firing Angles Using Grey Wolf Optimizer for Torque Ripples Minimization

Switched reluctance motor (SRM) has various advantages which makes it an excellent candidate for many applications; nevertheless, its main drawback is torque ripples. This paper aims to enhance the SRM operation by reducing its torque ripples without the need for expensive and sophisticated physical changes in the motor materials or design. The SRM converter firing angles are optimized to produce the lowest possible torque ripples. The response surface method (RSM) is used to obtain the SRM optimization function that relates torque ripples with firing angles, and grey wolf optimizer (GWO) is used to minimize this function. The objective function convergence speed using the proposed GWO is compared with genetic algorithm (GA), and it is found to be faster than GA. Simulation and experimental results show the effectiveness of the proposed approach in enhancing SRM operation by providing the SRM converter firing angles that result the minimum feasible torque ripples.
Research on Application of High-capacity Power Electronic Technology in Urban Power Grid

Large-scale urban power grid is facing increasingly serious trend of heavy load problem. The cost of traditional solutions is usually high due to large investment and difficult implementation of urban construction. In this literature, the application of three types of power electronic technology in solving unbalanced power flow of urban power grid is considered. The technical theory of UPFC is analyzed for entry point. By comparing with flexible DC technology and SSSC which are of the same type with UPFC, the application scenarios of three types of power electronic devices are demonstrated and the feasibility of UPFC above flexible DC technology and SSSC in urban power grid are proposed. Then an actual problem of a real urban power grid and several solutions including UFPC are studied and compared, which shows the application potential of UPFC in project perspective.
A Droop Based-Control Strategy of Stand-Alone Single-Phase Converters for Microgrid Applications

A control technique based on dynamic model of stand-alone single-phase voltage-source converter (SPVSC) in dq reference frame and droop curve equation is proposed in this paper to stable the voltage of point of common coupling (PCC) when renewable energy resources (RERs) are linked in a microgrid structure. The proposed control strategy is designed with respect to the aimed state variables of PCC frequency and voltage magnitude as well as the droop curve specifications. Moreover, an evaluation on PCC voltage frequency and voltage magnitude-based curve is presented for further analyzing the proposed controller performance. Simulation results in MATLAB/SIMULINK software prove the abilities of proposed controller in reaching stable operation of PCC voltage in microgrid application under load alteration.
Customer Segmentation and Strategy Development Based on User Behavior Analysis, RFM Model and Data Mining Techniques: A Case Study

The RFM (Recency, Frequency and Monetary) model provides an effective analysis for decision makers in order to target their customers and develop appropriate marketing strategies according to their previous behaviors. Although the RFM model has been widely applied in various areas of marketing, its simplicity threatens its effectiveness since it does not consider the customers' relationship and changes in customers' behavior. In this paper, we propose an R+FM model which configures the segmentation according to the business changes and clusters customers using K-Means. We applied our model on Digikala company, the biggest E-Commerce in Middle East, and compared our model with the Digikala's previous RFM model which used Customer Quantile Method. Moreover, we built strategies for each segment and ran an SMS campaign according to those strategies. The results of the campaign showed that our Segmentation Model improved the number of purchase and average monetary of the baskets.