Miracle-dz/UniFAR-FTUs huggingface dataset:
User Centric and Collaborative Movie Recommendation System Under Customized Platforms

Topping the entertainment industry, movies have become a really life-changing factor for this industry. The only difficulty individuals are facing right now is to find the right content which fits their choice of demands. To solve this problem, recommendation systems have been brought into use. Various filters can be applied to find the content of your desire. The aim of this paper is to predict user’s movie rating along with genre in order to recommend movies. The movies are recommended based on user activity and content to which they potentially give high ratings. User choices and history makes it easier to predict movies and filter out content. Many methods have been used to implement a recommendation system, but in this paper, we have majorly used collaborative filtering for recommending and content-based filtering for sentiment analysis. It will be used to output a list of recommended movies based on an individual’s choice, ratings, likes and past behavioral pattern. In this paper, to improve accuracy and effectiveness, similarity score is used. It is a numerical value that ranges between 0 to 1 and helps to determine how much a group of items are similar to each other. Cosine similarity makes the process effective by quantifying the similarity in the form of angular distance. As compared to Euclidean distance, cosine similarity is used because the precision of the cosine angle and the equi-distance of movies are almost identical.
Preparation and Analysis of Micro-rectangular Coaxial Structure-Based Power Divider

The micro-rectangular coaxial line was fabricated by the printed circuit board technology, and the micro-rectangular coaxial structure-based power divider was achieved. The size of the power divider is small, and the width of the isolation wall between the neighboring lines of power divider is only 240 um. The traditional micro-system integration technology (bonding, soldering, thermoacoustic welding and so on) was used to install the power divider to the test fixture. In the frequency range of 14.0 GHz $\sim$ 17.0 GHz, the measured transmission loss $\vert S21 \vert$ obtained from the power divider with test fixture is less than 3.9 dB, the isolation $\vert S23 \vert$ is greater than 22.0 dB, and the port voltage standing wave ratio (VSWR) is less than 1.7, all of which meet the requirements of the design standard.
A Method to Suppress Vibration Due to Dynamic Eccentricity by Using Triple Three-phase Winding Motor

Permanent magnet synchronous machines (PMSMs) are widely used in a variety of applications. Dynamic eccentricity of the rotor is one of the obstacles in the manufacturing process. This obstacle causes an imbalanced electromagnetic force and causes unexpected vibrations. In this research, the effect of dynamic eccentricity on the temporal and spatial harmonic distribution of electromagnetic force and vibration are investigated. Moreover, compensation methods have been proposed to suppress the vibrations due to dynamic eccentricity by using multi-sector and multi-phase motor. The compensation current is obtained by optimization. The effectiveness of the proposed method is verified by finite element analysis (FEA).
Slope Sensing for Optimum Dynamic Gate Driving of SiC Power MOSFETs

To suppress excessive gate voltage swings during switching, a resistance is normally used to limit the charging rate of the gate capacitance (CG). Modern solutions, such as segmented gate drivers, can be used to dynamically control the gate resistance RG to minimize ringing while maintaining the fast-switching speed of the transistor. The timing or dynamic pattern of the gate resistance is critical in the optimization of the device and circuit performance. Traditionally, this gate drive pattern is obtained via a trial-and-error or iterative procedure. This paper proposes a method to automatically determine the timing intervals by monitoring the gate signal (VGATE) through slope sensing with analog filter and subsequent mixed-signal processing. The output timing indicator (TSEG) is then fed back to the segmented gate driver IC to achieve automatic adjustments of the dynamic driving pattern. The proposed system is able to determine the optimum TSEG for dynamic gate driving. For the SiC power MOSFET used in our testing, segmented RG driving between 2.5 and 10 Ω does not hinder the switching speed, while keeping the undershoot of the SiC module to be within 1 V or 5% of the total applied gate voltage.
Joint Resource Allocation and Power Control for V2V Communication of High-density Vehicle Network

Device-to-device (D2D) communication has been considered as a possible enabler for vehicle-to-vehicle (V2V) applications, which induces the intra-cell interference inevitably. To ensure road safety and traffic efficiency, V2V has stricter requirements of latency, reliability, and access availability. In this paper, we propose a resource allocation method in a high-density vehicle network to maximize the number of reliable vehicular links. Firstly, we analyze and mathematically model the actual requirements for vehicular communications and traditional cellular links, and propose a problem formulation to fulfill these requirements. Secondly, we propose the serial and the clustering resource allocation algorithm to solve the resource allocation problem. The simulation results are presented to illustrate that the proposed schemes can provide reliable communication and improve the number of vehicles successfully established communication.
Exploiting Mobile Carrying to Improve the Capacity of Satellite Networks

In satellite networks, information can be transmitted either directly by inter-satellite links or the movement of satellites carrying. Consequently, how to quantify network capacity, considering both the carrying and transmission capability of satellites is crucial to the deployment of satellite networks. In this paper, we define the capacity of satellite networks consisting of both, and propose a strategy to exploit the mobile carrying of satellites under the constraint of service requirements. Then, we reveal the theoretical relationship between satellite carrying and the network capacity. The theoretical analysis and simulated results show that 1) satellite carrying can improve the network capacity when the service delay constraints could be released; 2) The capacity gain from satellite carrying is influenced by network parameters, such as orbital altitude, number of satellites, and storage capacity.
Q-learning Based Intelligent Ant Colony Scheduling Algorithm in Heterogeneous System

In view of the variable task structure and complex scheduling environment of heterogeneous computing system, and the low efficiency of existing scheduling algorithms, this paper abstracts the system by establishing a directed acyclic graph and a target system model, and proposes a Q-learning based intelligent ant colony scheduling algorithm. The algorithm adapts the scene to the scheduling environment, dynamically calculates the Q matrix according to the reward function, and the Q matrix is used as the initial pheromone of the ant colony algorithm. According to the pseudo-random proportional rule to select the processor, and the scheduling list is formed by the constraint relationship between the components to complete the task allocation. Analysis by randomly generating task graphs shows that this algorithm is more suitable for heterogeneous computing systems and computationally intensive tasks. Compared with ACO、 QMTS and GA algorithms, this algorithm reduces the scheduling lengths by average of 35.22%、 27.41% and 20.41% respectively, can obtain better scheduling results.
Embedded Tightly Coupled INS/DGPS-DGAL Navigation Filter on a Mass-Market Single-Board Computer

This work contributes to the highly relevant research topic of integrating sophisticated navigation algorithms on mass-market embedded platforms for use, for example, on ship pilotage information systems that assist pilots in harbor maneuvers and lock entries. Therefore, the integration of a tightly coupled navigation filter on a Raspberry Pi 4B mass-market single-board computer is presented. An existing unscented Kalman filter (UKF) is integrated into a specially adapted multi-threading framework which uses classic real-time scheduling techniques. The UKF fuses measurements from an industrial-grade inertial measurement unit (IMU) and observations from global satellite navigation systems (GNSS). Hence, a full 6-DOF state estimation is achieved. The results represent a breakthrough for mobile and compact navigation for mass-market applications. To achieve high positioning performance and to enhance the number of usable satellites, recent available differential corrections of a virtual reference station (VRS) for the observations of the new Galileo (GAL) system are used in addition to GPS observations. Real word tests prove the online capability of the approach. Even with the additional GAL satellites, the computational load remains remarkable low. With an average total execution time of 0.45 ms it is proved that a tighly coupled UKF can be integrated on a Raspberry Pi 4B. The UKF achieves 1 m positioning accuracy which meets the International Maritime Organization (IMO) requirements in port areas; under GNSS signal degrading conditions, the average 2D error is about 1.5 m.
Research on Control System of DC Pulse Power Supply for Fast EDM

Rapid electrical discharge machining (EDM) is a new machining method which uses high-energy pulse current to realize arc discharge, and cuts off the arc by the impact of flushing fluid, so as to realize the rapid removal of workpiece materials. It is very effective for complex cavity and large allowance removal of difficult cutting materials. In this paper, a digital control system of pulse power supply used to explore the rapid electrical machining process is designed. The main circuit of the power supply is designed. ZVZCS full bridge converter with IGBT soft switching technology is used for circuit inversion. After rectification, high power and large current output can be obtained. The parameters are optimized through the simulation of the main circuit, and its performance is verified by the prototype experiment.
MapReduce Model Using FPGA Acceleration for Chromosome Y Sequence Mapping

Genome assemblies sequenced by a Whole Genome Shotgun (WGS) project predict an organism’s function and history. Sequence alignment is the foundation of bioinformatics by a computational search through large genome sequence databases, which generally requires enormous amounts of memory and takes a long execution time. In this paper, an Optimized Smith-Waterman algorithm based on the Gotoh algorithm with an affine gap for accuracy alignment, the divide and conquer technique, and the MapReduce framework implemented to establish a parallel process. This model was implemented on Virtex 7 field-programmable gate arrays (FPGAs). These techniques provide a better performance, reduce the hardware requirements, improve the accuracy, increase the computational throughput, and accelerate the alignment process for big data available in a complete Y chromosome. The hardware proposed system can achieve high performance, low time consumption 1.699 ns, and decrease FPGA utilization for big data alignments Y chromosome is used as an example.
Effects of Ionization and Displacement Damage in AlGaN/GaN HEMT Devices Caused by Various Heavy Ions

The electrical degradation in AlGaN/GaN high-electron-mobility transistors (HEMTs) is examined under irradiation with 7.6-MeV carbon (C), 20-MeV oxygen (O), and 30-MeV fluorine (F) ions <italic>in situ</italic>. To characterize the radiation damage in the HEMTs, the ionizing dose <inline-formula> <tex-math notation="LaTeX">$D_{i}$ </tex-math></inline-formula>, displacement dose <inline-formula> <tex-math notation="LaTeX">$D_{d}$ </tex-math></inline-formula>, and number of vacancies versus the chip depth in the devices have been calculated for heavy ions. As expected, in all three types of HEMTs, the output current decreases more than 30% and threshold voltage positive shifts after the irradiation fluence of <inline-formula> <tex-math notation="LaTeX">$4\times 10^{12}$ </tex-math></inline-formula> ions/cm<sup>2</sup>. The performance degradation of AlGaN/GaN HEMTs is caused by radiation-induced charged defects. Based on calculation and experimental results, it is shown that the nonionizing energy loss (NIEL) method is not suitable for estimating the degradation of AlGaN/GaN HEMTs either considering gallium vacancy or considering both gallium vacancy and nitrogen vacancy. In the same displacement damage dose, the threshold voltage degradation rate depends on the type of incident particles and independent of the channel length. The damage caused by carbon ions is the smallest and the damage caused by fluoride ions is the largest.
Ensembling Multiple Radio Maps with Dynamic Noise in Fingerprint-based Indoor Positioning

Fingerprint-based indoor positioning is widely used in many contexts, including pedestrian and autonomous vehicles navigation. Many approaches have used traditional Machine Learning models to deal with fingerprinting, being k-NN the most common used one. However, the reference data (or radio map) is generally limited, as data collection is a very demanding task, which degrades overall accuracy. In this work, we propose a novel approach to add random noise to the radio map which will be used in combination with an ensemble model. Instead of augmenting the radio map, we create n noisy versions of the same size, i.e. our proposed Indoor Positioning model will combine n estimations obtained by independent estimators built with the n noisy radio maps. The empirical results have shown that our proposed approach improves the baseline method results in around 10% on average.
Agricultural Pest Detection System Based on Machine Learning

This paper designs an agricultural pest detection system based on machine learning. The system consists of pest detection algorithm and PC terminal system. The algorithm uses resnet50 as the backbone network, uses Feature Pyramid Network (FPN) to extract features, and optimizes them by Stochastic Gradient Descent (SGD) and Non-Maximum Suppression (NMS). Finally, the method is implemented by HALCON machine vision software. The PC side uses C # as the development language and C / S three-tier architecture for development, which is realized by visual studio 2015 combined with MySQL database. The system can detect and count the uploaded pest images, and save the detection results to MySQL database. The system constructed 27 agricultural common pest detection data sets, with an average precision of 92.5%. The experimental results show that the system can be effectively applied to the actual detection.
An Approach to Acquire Path-Following Skills by Industrial Robots From Human Demonstration

Industrial robots have mainly been programmed by operators using teach pendants in a point-to-point scheme with limited sensing capabilities. New developments in robotics have attracted a lot of attention to robot motor skill learning via human interaction using Learning from Demonstration (LfD) techniques. Robot skill acquisition using LfD techniques is characterised by a high-level stage in charge of learning connected actions and a low-level stage concerned with motor coordination and reproduction of an observed path. In this paper, we present an approach to acquire a path-following skill by a robot in the low-level stage which deals with the correspondence of mapping links and joints from a human operator to a robot so that the robot can actually follow a path. We present the design of an Inertial Measurement Unit (IMU) device that is primarily used as an input to acquire the robot skill. The approach is validated using a motion capture system as ground truth to assess the spatial deviation from the human-taught path to the robot’s final trajectory.
Efficient System Capacity User Selection Algorithm in MU-MIMO

Radio resource allocation is a major research field in wireless networks. The main challenge is to find the most suitable user for each time and frequency resource to ensure the Quality of Service (QoS) requirements. The use of Massive Multiple-Input-Multiple-Output (MIMO) makes it possible to simultaneously schedule several users on the same time and frequency resources. This is a new paradigm for resource scheduling. In this context, resource allocation algorithms have to account for the choice of users served on the same time and frequency resource in their decision mechanism. In this paper we analyze the impact of different group sizes on system capacity using several user selection algorithms and we propose a new user selection algorithm which performs closer to the optimal algorithm proposed in the literature.
A Sub-Synchronous Oscillation Suppression Strategy for Doubly Fed Wind Power Generation System

During the power transmission of doubly-fed induction generator (DFIG), due to the influence of series compensating capacitance and long-distance transmission, DFIG is prone to sub-synchronous oscillation, which damages the stability of the system. By establishing the mathematical model of DFIG system, the cause of sub-synchronous oscillation and its influence on the control strategy of DFIG system are discussed. In order to solve the problem of performance degradation of traditional phase-locked loop (PLL) under sub-synchronous oscillation, an improved PLL is proposed to replace the traditional PLL. Aiming at the problem that the control of rotor side converter(RSC) and grid side converter(GSC) in doubly-fed wind power generation system under sub-synchronous oscillation is disturbed by harmonic signals, a control method of adding a quasi resonant controller in the control link of RSC and GSC to suppress sub-synchronous oscillation is proposed, and the feasibility of the method is verified by simulation and experiment. Finally, based on the research process of RSC direct resonance control, the sub-synchronous oscillation suppression strategy based on harmonic current extraction is proposed for the frequency adaptability of the quasi resonant controller. The actual performance of the sub-synchronous oscillation suppression strategy is verified through simulation and experiment. The experimental results show that the strategy is effective.
Secure AF Relaying in Power-Constrained UAV Networks

This paper proposes a secure amplify-and-forward (AF) relaying scheme in unmanned aerial vehicle (UAV) networks while accounting for the power consumption limitations of UAVs. Since a UAV's battery life is limited, we propose selecting the UAV relays based on their probability of availability, which we model to be a function of the UAV's power consumption model. Then, physical layer security is achieved by partitioning the limited available relays into information relaying UAVs and cooperative jammers while aiming to maximize the secrecy rate of the network when an eavesdropper is located in the vicinity of the destination node. Meanwhile, the information bearing relays use beamforming to enhance the information delivery to the destination, and the cooperative jamming relays use precoded artificial-noise scheme to degrade the eavesdropping links' received signal-to-noise ratios. Simulation results show significant secrecy rate enhancements when the proposed schemes are adopted compared to conventional relaying scenarios, especially when cooperative jamming is deployed.
Improved Beam Training with Finite Slots in Millimeter Wave Wireless Communications

Beamforming (BF) is usually adopted in millimeter wave wireless systems to compensate high path loss. To increase the received power at user equipment (UE), beam training (BT) is performed to align the beam direction between base station (BS) and UE, where good trade-off between BT overhead and BF gain is preferred. In this letter, two memory-less statistical BT algorithms with finite slots are proposed to reduce the overhead and failure probability of BT, including minimum BT overhead (MO-BT) algorithm and minimum failure probability of BT (MFP-BT) algorithm. Both algorithms make the assumption that memory-less BS randomly select a beam in each slot, based on the prior probability of UE preference, and UE feeds back the beam index to BS to inform which beam should be adopted. By carefully adjusting the probability mass function of beam scanning at BS, MFP-BT can reduce the failure probability of BT, and MO-BT can reduce BT time consumption when compared to their traditional BT counterpart. Numerical results demonstrate the superior performance of our proposed algorithms.
Gamma-Ray- and Neutron-Induced Photocurrent and Readout Noise in LYSO+SiPM Packages

Lu<sub>2(1–<italic>x</italic>)</sub>Y<sub>2<italic>x</italic></sub>SiO<sub>5</sub> (LYSO) crystals readout by a silicon photomultiplier (SiPM) will be used in the barrel timing layer of a precision timing detector for the Compact Muon Solenoid (CMS) experiment at the High-Luminosity Large Hadron Collider (HL-LHC). This detector is expected to be exposed up to 5-Mrad <inline-formula> <tex-math notation="LaTeX">$\gamma $ </tex-math></inline-formula>-ray dose, <inline-formula> <tex-math notation="LaTeX">$2.5\times 10^{13}$ </tex-math></inline-formula> charged hadrons/cm<sup>2</sup>, and <inline-formula> <tex-math notation="LaTeX">$3\times 10^{14}\,\,\text{n}_{\mathrm {eq}}$ </tex-math></inline-formula>/cm<sup>2</sup> at the HL-LHC for 10 years of operation. We present results of the photocurrent in LYSO+SiPM packages induced by Co-<inline-formula> <tex-math notation="LaTeX">$60~\gamma $ </tex-math></inline-formula>-rays and Cf-252 neutrons of the expected dose rate and neutron flux, respectively. The <inline-formula> <tex-math notation="LaTeX">$\gamma $ </tex-math></inline-formula>-ray-induced readout noise is about 30 keV, which is negligible when compared to the 4.2-MeV signal from the minimum ionization particle signals. The neutron-induced readout noise is about 7 keV, which is more than a factor of 4 smaller than that from the <inline-formula> <tex-math notation="LaTeX">$\gamma $ </tex-math></inline-formula>-rays.
An Internet of Things(IoT) Based Intelligent Framework for Healthcare – A Survey

An Internet of Things Technology has been broadly utilized in different fields, and smart healthcare is one of its significant application regions. The remote Medical care monitoring framework in the hospital and numerous healthcare centres has encountered critical development, and convenient medical care monitoring frameworks with emerging innovations are becoming of great concern to many countries worldwide nowadays. A hybrid model of Cloud and IoT architecture design is used to support real-time applications and apply Artificial Intelligence to the data generated by the wearable sensor network. Accessibility of cloud-based frameworks along with security protection address critical issues that describe the Internet of Medical Things (IoMT) devices and models from being a reliable and proper solution for an objective. In this paper, we propose a brief survey of overall use of IoT-based frameworks in medical services, starting with an early medical care monitoring design based on wearable sensors and progressing to a discussion of the most recent fog/edge computing technologies for smart healthcare framework.