Miracle-dz/UniFAR-FTUs huggingface dataset:
Secure Beamforming in Full-Duplex Two-Way Relay Networks With SWIPT for Multimedia Transmission

With the advent of 5G, multimedia services in wireless communication networks will grow dramatically. So far, many researches have focused on improving security, throughput and channel capacity to support multimedia services. In this paper, a new system model of full-duplex (FD) two-way amplify-and-forward (AF) relay network with simultaneous wireless information and power transfer is presented, where two FD legitimate nodes with two single-antenna communicate with each other via energy-constrained AF relay with multiple antennas, and there is a half-duplex node with single antenna who intends to eavesdrop. This paper targets to maximize the secrecy sum rate of the system by designing the transmit beamforming vector of relay under power constraint and zero-forcing constraint, where two energy harvesting protocols, namely, power splitting and time switching are considered. However the maximization problem is a non-convex optimization, and it is very complex to solve. Therefore a linear method is used to find the lower bound of the secrecy sum rate and the non-convex problem is transformed into a convex optimization problem. After that, an iterative algorithm based on difference-of-convex programming is proposed to solve this convex optimization problem. The simulation results show the good convergence of the proposed iterative algorithm and also the superiority of secrecy sum rate of our proposed scheme compared with two traditional schemes.
3D Semicircular Flash Memory Cell: Novel Split-Gate Technology to Boost Bit Density

Three-dimensional (3D) semicircular split-gate flash memory cells have been successfully developed for the first time. Reduction of fringing field effects is essential to extract maximum performance from the split-gate cells, and careful design of Floating Gate (FG) cells achieves superior program slope and program/erase window at much smaller cell size relative to circular Charge Trap (CT) cells. It is projected that the semicircular split-gate FG cell is a promising candidate to realize more than four bits/cell (QLC) for significantly higher memory density at a lower number of stacking layers.
Modelling, Simulation and Balancing of a Car Direction with Fiber Optic Gyroscope and Fuzzy Logic Algorithms

Fiber optic gyroscopes (FOGs) are optoelectronic devices sensitive to angular rotation. Fuzzy control is an effective structure for converting mathematical models of real life systems into numerical values. In this study, an open-loop FOG has been designed for a car that a length of 4.5 meters and constant speed. The signal received from the gyroscope’s detector output has been analyzed and it has been observed that the dynamic measurement range of the Sagnac phase shift is between [-10 10] degrees. Software has been developed for the simultaneous operation of FOG design with the fuzzy logic algorithm to simulate sudden direction change of the car. The car’s direction has been balanced with the fuzzy logic algorithms. Balancing times and distances have been obtained for 60, 90, 120 and 150 km/h constant speeds. Theoretical calculations and simulation results show that it is possible to balance the car direction with fuzzy logic algorithms.
Scaling and Interoperability of All-Path with Bridged and SDN Domains using VXLANs

All-Path protocols, namely ARP-Path and TCP-Path, provide shortest path bridging by using path discovery and backwards learning in meshed topologies. However, their domain size may be limited to prevent excessive Layer 2 (L2) broadcast traffic overload in hosts. This paper proposes the use of Virtual Extensible Local Area Network (VXLAN) to solve this issue. Moreover, this paper also verifies the extensibility of All-Path domains and its interoperability with other different L2 protocols via VXLAN, which enables flexible network hy-bridization. Although encapsulation via VXLAN is heavier than other standard protocols designed for L2 scalability, the overall advantages and suitability for virtualized networks are excellent. Results show full compatibility and interoperability combined with good throughput and delay performance.
A Compact Dual-Band Filtering Antenna with High Selectivity

A compact dual-band filtering antenna with high selectivity is presented in this paper. The proposed antenna with U-shaped slot etched consists of a square patch, SIW cavity, and T-shaped coupled microstrip line. The SIW cavity functions as a common resonator using its two orthogonal mode (TM120, TM210), leading to compact size. The patch with U-shaped slot etched which acts as radiating patch, combines with two orthogonal modes of SIW cavity to realize dual-band filtering antenna. The simulated result shows broadside peak gain of antenna is 5.83 dBi at low-band operating frequency (3.167GHz-3.250GHz) while 4.44 dBi at high-band operating frequency (3.653GHz-3.709GHz). Due to generation of the two far-field zero radiation point between low and high working band, high selectivity is obtained.
A Novel Crow Search Algorithm Auto-Drive PSO for Optimal Allocation and Sizing of Renewable Distributed Generation

The penetration of renewable distributed generations (RDGs) into traditional distribution systems (TDSs) remedies many of its deficiencies and shortcomings. Also, it provides mutual technical, economic and environmental benefits for both electricity companies and their customers as well. With a 25% load increase for the standard IEEE 30-bus system, buses 19, 26 and 30 have the lowest voltage magnitudes among all buses. Therefore, these weak buses are selected initially to allocate RDGs. Three cases, namely, one RDG allocated, two RDGs allocated and three RDGs allocated, of RDGs insertion are covered. A novel crow search algorithm auto-drive particle swarm optimization (CSA-PSO) technique is proposed for the first time in this study to specify the optimal allocation, sizing, and number of RDGs based on the total cost and power losses minimization objectives. A new reduction percent formula is used to estimate the reduction in total cost and the total power losses. These will help us to discern between the best cases based on total cost minimization and those based on total power losses minimization to pick up the best among all best cases. In brief, RDGs allocated on buses 19 and 30 is the best among all cases based on total cost reduction and total power losses reduction. Therefore, buses 19 and 30 are recommended to allocate a wind farm and a solar photovoltaic, respectively based on technical and economic issues. Finally, the simulation findings revealed the superiority of the CSA-PSO algorithm in solving the optimal power flow problem with RDGs compared to the state-of-the-art metaheuristic techniques.
A Compact Ka-band 35W Power-Combining Amplifier

This paper presents the development of a 35W Ka-band Power-combining Solid-states Power Amplifier (SSPA) with 80% power combining efficiency (PAE). The amplifier consists of an eight-way rectangular spatial waveguide power splitter/combiner and eight power amplifier MMIC chips, these chips were fed by a novel Horizon-Vertical bias supply scheme, which effectively decrease the size of the module. The eight-way power splitter/combiner was combined with three-stage waveguide E-plane T-junction and eight ceramic microstrip probes designed for matching rectangular waveguide with MMICs. Moreover, the SSPA module was fabricated and continuous-wave output saturated power and power-added efficiency (PAE) measurements are performed, which indicated a good performance of the amplifier.
Energy Management Strategy Considering Battery Efficiency for Grid-Tied Microgrids During Summer in the Kingdom of Saudi Arabia

The rise in interest for renewable energy sources (REs) is opening up many research areas in microgrids, renewable energy generation (REG) and energy storage systems (ESS) to improve the reliability of the microgrid. This paper presents a study on a grid-tied microgrid with a battery energy storage system (BESS) for a residential load considering the summer operational cost of the microgrid in the Kingdom of Saudi Arabia (KSA). The operational cost of the microgrid is minimized using linear programming (LP) available in GAMS optimization software. The constraint on the microgrid is also analyzed. The microgrid is modeled based on the knowledge of the available data for PV generation, power demand and the price of electricity in Summer within the kingdom. The objective is to optimize the operational electricity cost of the microgrid within 24 hours. Furthermore, the effect of reduced forecasting error and an increase in the PV generation to balance the power flow of microgrid is investigated. The lithium-ion battery has been selected for this study because of its high efficiency and low charge/discharge temperature.
An Improved Vision-Based Indoor Positioning Method

Vision-based indoor positioning technology is a practical and effective method to solve the problem of indoor positioning and navigation. Compared to Bluetooth-based and WiFi-based positioning methods, vision-based positioning method can provide reliable and low-cost services using a camera without extra pre-deployed hardware. To improve the robustness and accuracy of traditional visual positioning algorithm, this paper proposes a pixel threshold based eight-point method and an improved epipolar constraint algorithm. The traditional eight-point method only uses Euclidean distance as a selection indicator for feature points. The pixel coordinates of some feature points are distorted when the positioning scene changes, which may cause mismatch. The proposed method introduces the pixel threshold constraint to improve the quality of output feature points. Further, the epipolar constraint algorithm is modified by adding a new cost function to improve the accuracy of fundamental matrix calculation, thereby improving the positioning precision. Performance simulation analysis shows that the proposed algorithm can effectively improve indoor positioning precision.
Power Quality Improvement of Grid Connected Inverter

This paper presents the important issue relevant to inverter which is operated in grid connected mode. Now a day, power quality improvement is research topic for carious applications field. Similar to other enhancement, power quality plays fundamentals role in inverter based applications. Inverter provides specific parameters for grid synchronization when it should be minimize the Total Harmonics Distortions (THD). Power Quality (PQ) issues are based on experimental simulation verifies the errors between grid parameters and inverter parameters, THD Calculations, Active-Reactive power measurements. Grid interfaced inverter provides the requirement for interfacing of inverter with electrical grid can be analyzed using presented model.
Monolithic 3D SRAM-CIM Macro Fabricated with BEOL Gate-All-Around MOSFETs

For the first time, below 400°C-fabricated gate-all-around (GAA) transistor fabrication process was demonstrated with monolithic computing-in-memory (CIM) circuit. Key enablers are plasma-assisted atomic layer etching (PA-ALE), plasma immersion ion implantation (PIII) and far-infrared laser activation (FIR-LA). The 3D stackable single-grained Si GAA MOSFETs thus fabricated exhibit record-high Ion/Ioff ratio (~108) with low Ioff (pFETs<10–2 nA/μm). Moreover, the stackability of the GAA MOSFETs and the differential output of dual-mode 10T SRAM readout enable 2x throughput in the CIM circuitry.
Bubbloid Algorithm: A Simple Method for Generating Bubble-like Line Drawings

In this paper, I propose a simple method for generating bubble-like line drawings, which is named as bubbloid algorithm. In this algorithm, two-dimensional regions are modeled as polygons, and their vertex positions are adjusted iteratively to minimize an objective function. This algorithm not only makes each region's surface smooth but also makes each region's area close to a target value, which is specified in advance. Four possible applications of the algorithm are shown: drawing bubbles as two-dimensional computer graphics, graph drawing, geographical data visualization, and image warping.
Research on BLDC Control System Based on Model Prediction and Integral Separation PID Algorithms

Brushless DC Motor (BLDC) adopts current and speed PID closed-loop control. In order to ensure the control t performance, it is necessary to collect the precise parameters of the motor in real time, which results in poor dynamic control performance of the motor. To solve this problem, this paper proposes a BLDC current loop control scheme based on two-step model predictive control, which inherits the advantages of traditional model predictive control On the other hand, it solves the problem that the digital control system has a period delay. In order to increase the anti-disturbance ability of the control system, a new integral-separated PID control method based on the traditional PID control method is proposed in this paper. The new integral-separated PID control method is applied to BLDC speed and current closed-loop control. This control method not only has strong anti-disturbance ability, but also can effectively solve the system oscillation caused by overshoot of the traditional PID control system The problem Finally, the effectiveness and practicability of the two methods are verified by matlab/simulink simulation and experiment.
Sparse dynamic inner principal component analysis for process monitoring

In this paper, a novel sparse dynamic inner principal component analysis (SDiPCA) method is proposed for process monitoring. First, a simple regression-type approach of dynamic inner principal component analysis (DiPCA) is discussed. To derive sparse principal components, an elastic net regularization is imposed on this regression-type problem. Then a new optimization criterion is established and solved through an alternating algorithm. On the basis of the SDiPCA model, four monitoring statistics are constructed to reflect the process status. Also, the reconstruction-based contribution (RBC) method is employed to isolate faulty variables. Finally, a case study on the Tennessee Eastman process is conducted to illustrate the superior performance of the proposed SDiPCA method compared with DiPCA method.
Output Tracking Control for the One-Dimensional Heat Equation with Unknown Disturbance by the Dirichlet Boundary Actuation

In this paper, output tracking problem for heat equation with general disturbance at left extremum and the Dirichlet control input at the right extremum is considered, which is solved by the Active Disturbance Rejection Control(ADRC) method. First, an infinite dimensional disturbance observer is constructed to estimate the disturbance. Secondly, we design an auxiliary system which used the estimate of the disturbance at left boundary and the reference signal at right boundary. Then, by using the hidden regularity of the right extremum of the auxiliary system to design the servo system, which contains the disturbance information transmitted from the left extremum and appear at the right extremum. As a result, the one-dimensional heat equation achieves the purpose of completing disturbance suppression and reference tracking. Finally, some simulation results are presented to illustrate the effectiveness of the proposed scheme.
Research on Alternating Adaptive Control Strategy of Moment of Inertia and Damping Coefficient of VSG

With the depletion of traditional energy sources, microgrid control technology represented by VSG has received extensive attention. In order to overcome the shortcomings of traditional VSG control methods, such as long transient time and over-damped operation mode, An alternating adaptive control strategy by changing the moment of inertia and damping coefficient of VSG was established by further analyzing the influence of moment of inertia and damping coefficient on the dynamic output characteristics of VSG and verified by simulation on MATLAB/Simlink platform. The theoretical analysis and simulation results show that the control method can compensate for the above defects.
A Novel Proposed Pooling for Convolutional Neural Network

In this paper, we aim to improve the performance, time complexity and energy efficiency of deep convolutional neural networks (CNNs) by combining hardware and specialization techniques. Since the pooling step represents a process that contributes significantly to CNNs performance improvement, we propose the Mode-Fisher (MF) pooling method. This form of pooling can potentially offer a very promising results in terms of improving feature extraction performance. The proposed method reduces significantly the data movement in the CNN and save up to 10% of total energy, without any performance penalty.
Non-contact Heart Rate Monitoring Using Machine Learning

Health monitoring is an important parameter to determine the health status of a person. Measuring the heart rate is an easy way to gauge our health. Normal heart rate may vary from person to person and a usually high or low resting heart rate can be a sign of trouble. There are several methods for the measurement of heart rate monitoring such as ecg, ppg etc. Such methods having a disadvantage that these are invasive and have a continuous contact with the human body. In order to overcome this problem a new system is proposed using camera. In this method a blind source separation algorithm is used for extracting the heart rate signal from the face image. Viola jones based face detection algorithm is used to track the face. FastICA algorithm is exploited to separate heart rate signal from noise and artefacts. Machine learning algorithm is implemented to standardize the signal. The data is successfully tested with real time video.
Distributed Secondary Control for Islanded Microgrids with Event-triggered Strategy

This paper investigates the consensus problem of the frequency and voltage in islanded microgrid. A distributed secondary control strategy is proposed which is based on the multi-agent cooperative control method combined with event-triggered mechanism and achieves the frequency and voltage restoration. During the control process, the controller is designed to work as necessary to mitigate the communication burden and the number of executions. In addition, the influence of communication delay on control algorithm is taken into account in this paper. Finally, several simulation results verify the effectiveness of the proposed methods.
The measurement matrix optimized by information operator improvement

The signal sample tool which is called measurement matrix or observation matrix is very important for the theory of compressive sensing. Decreasing the correlation between any two different columns of the information operator is the basis of the design and optimization of the measurement matrix. Based on it, the non-diagonal elements of the upper triangular matrix of the QR decomposition of information operator was set to zero to increase its minimum singular value and decrease the column correlation of information operator, and thus this method can enhance the performance of the measurement matrix. Experiments illustrate that when the algorithm of this paper is utilized, the recovery error of signals and images are both diminished.
Fault detection of gas sensor arrays based on KNN rules

Fault detection techniques are critical to improving the efficiency of airborne overall equipment. It has been recognized that fault detection based on the k nearest neighbor rules (kNN) can effectively handle some of the characteristics of the gas sensor process, such as multimode bulk trajectories and nonlinearities. However, the computational complexity and storage space involved in kNN's neighbor search prevents it from being monitored online, especially for high-dimensional situations. In order to solve this problem, Before the implementation of kNN rules to fault detection, we reduce dimensions by principal component analysis (PCA) and propose a K-fold cross-verification method in the training stage of the model to learn from multiple directions, which plays a good role in improving the accuracy of fault diagnosis. This method enables the verification set to traverse all the data sets during the division of the training set and the test set, thus avoiding the problem of local minima to a certain extent. In the specified range of K values, the smaller the K value is, the fewer the nearest neighbors are, and the more useful training samples can not be included, resulting in the increase of false recognition rate; the K value is too large and the noise significantly affects the error rate; the optimal K value is obtained by cross-verification K nearest neighbor algorithm, so that the error rate of pattern recognition is the lowest. The practical application shows that this method can realize the on-line diagnosis and location of array gas sensor faults, and can be applied to other similar systems.
The use of intraperitoneal chemotherapy.

The i.p. route of drug administration has a clearly defined theoretical basis. Detailed information is now available on the i.p. pharmacology and toxicity of most drugs active in ovarian cancer. In addition, there are clearly defined clinical situations in which use of this form of therapy would be rational. The major remaining task is to conduct well-designed clinical trials to determine the actual value of this approach.
A Comparative Verification of Ordering Methods of Design to Document Production Outsourcing Services

We showed that there are 3 levels of "production purpose", "reader's psychology" and "design" specifically as an ordering method when requesting design work. It was statistically confirmed that the "appropriateness" and the "easiness to understand" improve when the order content includes "reader psychology". In particular, it was recognized that "comprehensibility" would be improved if the "reader's psychology" instruction was given without the "production purpose" instruction. As a result, it is considered that the inclusion of "reader psychology" in the content of the order has improved the evaluation of designer for the ordering method.
Sea Surface Boundary Line Detection Based on Edge Energy Feature Matrix of Sequential Images

Accurate detection of sea surface boundary line(SSBL) can decrease the search range of maritime target detection with an important meaning. However, it is a challenge task to detect the sea surface boundary line under the interference of various sea waves, rolling mountains, clouds, vessels, sea fogs, uneven illumination etc. This paper proposed a new sea surface boundary line detection algorithm based on edge energy feature matrix of sequential images. We enhance the stable edges by edge superimposition of sequential edge images, which creates edge energy feature matrix for better detection of SSBL. Then, the improved algorithm of Hough transform is utilized to compute the edge energy of straight lines. Finally, the maximal energy straight line was detected as SSBL. Experimental results show the proposed algorithm has strong anti-interference ability and has obvious advantages over other similar algorithms.