Miracle-dz/UniFAR-FTUs huggingface dataset:
"Focusing" of a Plane Electromagnetic Wave by a Uniform Dielectric Cylinder with a Graphene Coating

We investigated the focusing effects arising in the diffraction of H–polarized plane wave by a uniform dielectric cylinder with a graphene coating. The analytical solution of the wave-scattering problem is based on the Maxwell equations and the resistive boundary conditions on the zero-thickness graphene cover where the graphene electron conductivity was determined from the Kubo formalism. We use the spectra of normalized cross-sections: scattering and the absorption for finding the frequencies of plasmon resonance in graphene layer. Spatial distribution was computed of the field amplitude in the absorption maxima. Computations were performed out in the wide range of cylinder radius and the wavelength of incident radiation. We demonstrate that the field focusing at the rear surface of the cylinder takes place when the surface plasmon resonance occurs in the structure; the resonance frequencies of different plasmon modes fall into a wide band. An optimal value of the cylinder radius and the frequency of the incident wave were found corresponding to the highest focusing effect.
Gap Waveguide Structure with Three Functionalities: All-Stop, All-Pass, and Fully Reconfigurable Bandpass Filtering

This paper presents a new application of a gap waveguide structure to the design of multi-functional reconfigurable filters. For implementing multiple functionalities, a tunable texture pin structure is newly presented in this work. By virtue of the proposed tunable texture pin structure, a gap waveguide structure can be designed to have multiple responses. In this work, we design a gap waveguide structure capable of having all-pass, all-stop, and bandpass responses. More importantly, the center frequency, the bandwidth, and the order of the bandpass response can be adjusted. It is also demonstrated that transmission zeros can be produced in bandpass responses. The highly reconfigurable gap waveguide filter has been designed, fabricated and measured for demonstration.
Vehicle Identification using Eigenvehicles

In the current society, a lot of to the error rates caused by the reckless driving of some drivers that led to a high traffic accidents. As a result, there are widespread fears that some drivers did not respect the driving rules. As a result, there was an urgent need to implement an application to track off violated vehicles that pose a threat to lives. This work presents a compuerized scheme for vehicle identification using the eigenvehicles technique. The proposed strategy is consider as feature based system utilizing Principle Component Analysis (PCA). PCA will be used to reduce the feature vector dimensions for the vehicles. In addition, PCA will enable the proposed algorithm for recognize the vehicle in fast and effective way. Here, vehicles will be classified into (cars, buses, trucks) to assist radars that are located on the roads in detecting the type of a vehicle, and thus, determines whether the vehicle has violated the speed prescribed for them.
Comparison of Equivalent Circuit Models for a Multimode Dielectric Resonator Absorber

Two equivalent circuit models for a dielectric resonator absorber structure are developed and compared. The first model is based on the modal field distributions inside the resonator structure, while the other one is based on the modification of Foster’s reactance theorem. Circuit parameters of these models are extracted using a genetic algorithm. The input impedance magnitude and reflection coefficient from these circuits are compared with the results from full-wave simulation within the frequency range of 3 GHz - 18 GHz. It is shown that the equivalent circuit using modal field distribution has a higher mean deviation for both input-impedance magnitude and reflection coefficient than that based on the Foster equivalent circuit. But, from a physical point of view, the modal field distribution offers a better explanation for the generation of modes within the resonator. Both models can complement each other.
An approach to linear active disturbance rejection controller design with a linear quadratic regulator for a non-minimum phase system

This study proposes an approach to determining the controller gain based on the linear quadratic regulator (LQR) method for a non-minimum phase plant. The extended state observer is designed based on the conventional pole placement method to prevent the observer from being unstable. The control law is determined based on the LQR method in terms of fast responses of the plant outputs and the magnitude of its inputs. The stability of the whole closed-loop control system is evaluated using the Routh-Hurwitz stability criterion. The effectiveness of the proposed method is confirmed by performing numerical simulations and comparing their results with those of the conventional I–PD control. In addition, a superior robustness of the plant with a modeling error is achieved compared with that of the fundamental I–PD control system. Finally, the proposed LADRC with an LQR is confirmed to demonstrate a performance that is approximately the same as that of the conventional LADRC.
Design and Control of a Miniature Quadruped Rat-inspired Robot

Robot-rat interaction test is a promising way to characterize the animal sociality for biomedical application. However, currently developed robotic rats are mostly driven by wheels, resulting in limited movement agility. It is an arduous task to realize both the morphology and functionality of rat limbs within restricted dimension. In this specified scale, it is not only difficult to design efficient mechanism to achieve high-speed movement but also difficult to integrate many actuated joints to accomplish multiple motion modes. To address these problems, we modularly designed a miniature quadruped robot making full use of connecting rod mechanism to mimic rat limbs. To generate bio-inspired quadruped gait by using a compact control board, we developed a locomotion controller based on central pattern generators (CPG). Together with particle swarm optimization (PSO) algorithm, the stride frequency and length can be adjusted by parameters. Both simulation and experimental tests show that our quadruped rat-inspired robot is able to implement three motion modes. 1) Crouch-standing action: the robotic rat is able to stand up from initial state (kneeling action) without manual support. 2) Forward walking: the robot reaches a maximum speed of 10cm/s. 3) Turning action: the robotic rat has a small turning radius of 12 cm that is only half of its body length. The outperformance of this robotic rat show high promises in performing natural robot-rat interaction in future.
A U-Band Power Efficient MMIC Frequency Tripler with Integrated Output Amplifier

Design and development of a U-band MMIC active frequency tripler with integrated output amplifier has been presented in this paper. The circuit has been designed in a cascaded two-stage configuration using GaAs based pHEMT technology. Measured results show more than 10 dBm of output power and 5 dB of conversion gain at 47 GHz. Rejection of unwanted harmonics is in excess of 35 dBc. Total dc power consumption of the circuit is only 100 mW. This power efficient, highly stable MMIC tripler can produce high quality reference signal with sufficient power for millimeter wave (MMW) wireless transceivers.
Predictive Analysis of Rapid Spread of Heart Disease with Data Mining

cardiovascular disease is the leading cause of mortality for both sexes in worldwide. Heart disease is increasing at a rapid rate in both older and younger generation of males and females now days. So in need demand of right strategies, development and implementation of effective health monitoring policies should be emphasized to combat the epidemic of heart related diseases. So early detection and treatment with the use of both conventional and innovative technique must be preferred In this paper we have used the UCI machine learning repository Cleveland heart disease database having 303 instance and 76 attributes. For the proposed method we have used the Information gain concept for selection of best attribute and processes the selected features using weka and python. This paper identifies the gap of research on prediction of heart disease based on python Anaconda navigator, spyder and weka platform on which we have much emphasized. The various techniques, processes which have used to train the model of heart datasets such as feature selection, numpy, pandas library, decision tree classifier, KNN classifier, entropy, gini-index, confusion matrix.The result shows that decision tree classifier is most effective and appropriate for prediction of UCI repository Cleveland heart dataset.
Multi-Objective Optimal Power Flow With Improving Voltage Stability and Loss Minimization Using Moth Flame Optimization Algorithm

The present work introduced optimization of multi-objectives optimal power flow problem using non-dominated sorting moth flame optimization (NSMFO) technique. The best compromise solutions among the pareto front is decided with the fuzzy decision making technique. The efficacy and competence are validated through the IEEE 30-bus network. The outcomes are collated with certain modern optimization algorithms.
Semi-Global Output Consensus of Multi-Agent Systems Subject to Actuator Saturation: A Low and High Gain Approach

This paper studies semi-global output consensus problem for multi-agent systems. The dynamics of each follower agent is described by a linear system subject to both actuator saturation and external disturbances. The dynamics of leader agent is also described by a linear system which generate both the tracking signal and disturbance as the exosystem does in output regulation problem for individual system. Solvability conditions are established based on the agent dynamics and the communication topology. For the follower agents, low-and-high gain based linear state feedback control laws are constructed such that all the outputs of agents achieve output consensus when the communication topology among the follower agents is a connected undirected graph, and the leader is a neighbor of at least one follower. Simulation results are given to illustrate the theoretical results.
CSRR loaded SIW Structure based Novel Dielectric Sensing Methodology for mm-wave 5G Communication Band

In this work, the novel dielectric sensing methodology using complementary split ring resonator (CSRR) loaded substrate integrated waveguide (SIW) based planar resonant sensor in the mm wave 5G (24.25-27.5GHz) frequency band is presented. The proposed methodology involves tuning of resonant frequency of CSRR in the pass band of SIW structure contrary to the CSRR loaded SIW filters where resonant frequency has to be kept in the stop band of SIW. Designed sensor helps to obtain relatively higher sensitivity due to presence of strong electric field at the position of CSRR (center of SIW). The presented sensing methodology is quite attractive as it does not require rigorous sample preparation which is the main requirement in conventional cavity approach. Design of the proposed sensor is validated by comparing the unloaded transmission coefficient generated using the CST and the HFSS. Thereafter, numerical model of the designed sensor is used for dielectric sensing of number of the radome, planar substrate, and building materials in order to understand their effect on the 5G band of communication system. Proposed sensor can find its potential application in communication industry involving deployment of 5G band through accurate dielectric testing of the employed materials.
Decentralized flocking of multi-agent system based on MPC with obstacle/collision avoidance

Most of the literature on flocking of multi-agent system with obstacle/collision avoidance make essential distinction between agents and obstacles. This paper proposes a decentralized model predictive flocking algorithm, and addresses the problems by defining obstacles as special agents, which enables agents to effectively evade external obstacles and to avoid colliding with neighbors while forming a stable $\alpha$-lattice structure. We not only numerically verify the effectiveness of the algorithm with 50 agents in the MATLAB, but also achieve obstacle avoidance of ten UAVs on a software-in-the-loop simulation platform.
High Gain Three Dimensional SIW Horn Antenna Array for Automotive Radar Applications

This paper represents the three dimensional array of SIW horn antenna for 24GHz applications, with improved gain when compared to the single antenna element and SIW horn antenna linear array structure. The two dimensional SIW horn antenna array does not satisfy the condition of half wavelength distance between the consecutive antenna element, hence the structure has poor gain. To improve the gain of a horn antenna a three dimensional structure is proposed. The combined beam of four antenna element provides the low HPBW radiation pattern. The maximum gain achieved from the structure is 8.8 dB at the desired frequency, whereas the single element SIW horn antenna has a maximum gain of 5.6dB. At 24 GHz, the SIW horn antenna is a good candidate for radar applications. Multiple horn antennas are combined to satisfy the high gain condition of automotive radar applications.
Exponential stabilization of delayed state-dependent switching neural networks by intermittent control

Here, we investigate the exponential stabilization of state-dependent switching neural networks with time-varying delays by intermittent control. Several new criteria ensuring exponential stabilization of state-dependent switching neural networks are obtained. In addition, the new criteria do not impose any restriction on the size of time-varying delays. Numerical simulations on the chaotic systems are presented to illustrate the obtained results.
Why Symbolic AI is a Key Technology for Self-Adaption in the Context of CPPS

The vision of smart factories are self-diagnosing, self-optimizing and self-adapting Cyber-Physical Production Systems (CPPS). Self-adaption, on which this paper focuses on, means that the CPPS can adapt itself to a changing environment, so that the downtime costs can be reduced by using the system modules most efficient. An architecture is introduced and demonstrated on a concrete use case to show how this capability can be achieved by using different Artificial Intelligence (AI) techniques. For each technique, we define challenges that have to be solved to use it in a real world environment. Additionally, we illustrate the symbolic and subsymbolic AI and argue why symbolic AI is an important aspect in the context of CPPS.
AC Surface Flashover and Gas Generation Difference of the Cellulose Insulation Pressboard Immersed in Novel 3-Element Mixed Oil and Mineral Oil

Surface flashover fault is one of the most challenge issues in oil-cellulose insulation pressboard system used in power transformer. In this study, a comparative study of the AC surface flashover properties of the novel 3-element mixed oil-cellulose insulation pressboard (3EMO-IP) and mineral oil-cellulose insulation pressboard (MO-IP) was performed under needle-plate and finger-finger electrode, respectively, measurement including dielectric property, surface flashover voltage, damage of cellulose pressboard surface and the gas generation behaviors after multiple surface flashover. Results show that the cellulose insulation pressboard immersed in the novel 3-element mixed insulation oil (3EMO) has higher relative permittivity and dielectric loss factor at 50 Hz, and also has slightly lower surface resistivity. The AC surface flashover voltage of the 3EMO-IP is higher than that of MO-IP under needle-plate and finger-finger electrode (electrode distance 5 mm, 10 mm, 15 mm and 20 mm). Compared to MO-IP, the lower electric field intensity at the oil-pressboard interface, as well as more difficult for surface charge accumulation of 3EMO-IP and the higher breakdown voltage of 3EMO lead to the higher AC surface flashover voltage of 3EMO-IP. Moreover, the carbonization of fibers in 3EMO-IP is slightly less. After multiple surface flashover, C2H2 and total hydrocarbon gases are the main differences between 3EMO-IP and MO-IP, which is more marked with the increase of flashover times. This study offers a reference for improving the surface flashover property of oil-pressboard insulation system by using 3EMO.
Completion of the 8 MW Multi-Frequency ECRH System at ASDEX Upgrade

Over the last 15 years, the Electron Cyclotron Resonance Heating (ECRH) system at the ASDEX Upgrade tokamak has been upgraded from a 2 MW, 2 s, 140 GHz system to an 8 MW, 10 s, dual frequency system (105/140 GHz). Eight gyrotrons were in routine operation during the current experimental campaign. All gyrotrons are step-tunable operating at 105 and 140 GHz with a maximum output power of about 1 MW and 10 s pulse length. The system includes 8 transmission lines, mainly consisting of oversized corrugated waveguides (I.D. = 87 mm) with overall lengths between 50 and 70 meters including quasi-optical sections at both ends. Further improvements of the transmission lines with respect to power handling and reliability are underway.
Scaled leader-following consensus of networked agents under packet losses

This paper is concerned with the scaled leader-following consensus in discrete-time multi-agent systems with packet losses. The scaled leader-following consensus means that agents eventually reach convergence at their own scale following the state of the leader. In comparison to existing scaled consensus literature, the environment of packet losses is introduced into scaled consensus issue for the first time in this article, in which the success or failure of information transmission in each link is independently represented by a Bernoulli random variable. Based on a stochastic distributed control protocol, it is shown that the scaled leader-following consensus with packet losses can be achieved if and only if the interaction topology contains a spanning tree rooted at the leader. Finally, a simulation example is shown to illustrate the effectiveness and feasibility of the theoretical result.
High Resolution Passive THz Imaging Array With Polarization Reusage in 22nm CMOS

A 12-pixel THz Focal Plane Array (FPA), integrated in Global Foundries 22nm CMOS technology, enabling high resolution passive THz imaging, is presented. The array efficiently couples blackbody radiation from 200 GHz to 600 GHz to Schottky Barrier Diodes (SBDs) in a differential topology. An antenna-detector co-design results in an average Noise Equivalent Power (NEP) of 0.9 pW/$\sqrt{\text{Hz}}$. An extremely small array periodicity is achieved by using two orthogonal polarizations. Such configuration enables passive imaging with a near-diffraction limited resolution while simultaneously maintaining a high optical efficiency of 42%. The array is currently in tape-out and measurements will be presented at the conference.
Energy Efficiency of Gait Rehabilitation Robot: A Review

Gait rehabilitation robots have been reported to reduce impairment and regain functional abilities of gait disorder significantly. While energy efficiency is essential in the process of gait rehabilitation, few gait rehabilitation robots can achieve it. This paper aims to emphasize the importance of energy efficiency on the development of gait rehabilitation robots and conduct a view of rehabilitation training approaches as well as robots. Gaps and conflicts in traditional rehabilitation robots are analyzed based on the rehabilitation requirements and energy efficiency. While related research in reduction on energy consumption of human and optimization of human with device together during walking, is summarized. Finally, we discuss and highlight the future directions regarding the energy-efficient feature in gait rehabilitation robots.
Circumventing Uniqueness of XOR Arbiter PUFs

A fundamental property of Physical Unclonable Functions (PUFs) is uniqueness, which results from the intrinsic characteristics of each PUF instance. However, PUF architectures employ elements whose physical characteristics and behavior may be very similar among different instances, thus leaking unwanted information. We explore the consequences of this effect by mounting Template Attacks over XOR Arbiter PUFs. In the attack, Challenge-Respose Pairs (CRPs) are profiled in one FPGA instance of the PUF to predict responses of a different FPGA instance, obtaining up to 80% of accuracy. We show that replicating the same attack strategy with a well-known Machine Learning (ML) algorithm would not be as effective, since different PUFs instances will not share similar CRP sets. Our template attack only needs few CRPs for profiling (at most 170), but it can be applied to different instances without additional training, which Machile Learning cannot do with unbiased PUF instances.
On the Relationship Between Energy Consumption and Driving Behavior of Electric Vehicles Based on Statistical Features

With the development of the new energy vehicle industry, the problem of energy consumption has gradually attracted attention. The existing researches on energy consumption of new energy vehicles are mainly based on clustering methods. However, clustering does not construct a direct relationship between energy consumption and other factors. This paper will explore the relationship between driving behavior and energy consumption. We use the driving data of electric vehicles to construct a set of statistical indicators describing driving behavior, and then divide the kinematic segments and calculate the statistical features in each segment. The features in one segment form a sample and thus we obtain a large number of samples. These samples are used to train a BP neural network. By using the BP neural network, the results on fitting the relationship between driving behavior and electricity consumption per kilometer are derived, that is, the mean square error is 0.014, and R2 score is 0.91. The analysis of the network parameters further indicates that there exist some features that are more important than others. This implies that the driving behavior related to these features may improve the vehicle’s energy consumption level.
A Differential Reflection-Type Phase Shifter Based on CPW Coupled-Line Coupler in 45nm CMOS SOI

This paper presents a mm-wave fully differential coplanar waveguide (CPW) vertically-coupled lines coupler and a reflection type phase shifter (RTPS) based on the proposed coupler. The use of grounded strip line structure for vertical coupling in CPW based coupler provides not only the improved coupling properties than the edge coupling but also provides the opportunity of using surrounding area efficiently to reduce area. The proposed coupler and phase shifter are designed and fabricated in 45nm CMOS SOI technology. Measured insertion loss of the coupler is ~ 6 dB from 18 to 43 GHz. A digitally controlled parallel LC load is used for controlling the phase of the phase shifter. Measured phase tuning range is 115 degrees, with insertion loss variation of 4.5 to 9 dB, for a frequency range of 39 GHz to 45 GHz. Total drawn area of the phase shifter is 0.214 mm2. The area of the proposed RTPS is smaller than the recently published state-of-the-art structures.
Assessing and Measuring Caring in Nursing and Health Science

Key features of this new second edition: * A chapter providing a comprehensive literature review of the research and measurement of caring * A chapter entitled "Caring Factor Survey," which presents a new scale based on Watson's original theory of human caring * Chapters outlining instruments for care measurement, including Holistic Caring Inventory, Peer Group Caring Interaction Scale, and many more * New instruments focused on assessing caring at the administrative-relational caring level * An updated section dedicated to challenges and future directions of the measurement of caring