Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of an Efficient Routing Technique based on Clustering

When it comes to extending the lifespan of Wireless Sensor Networks, the concept of clustering is quite useful because it lowers the energy consumption required for their operation as well as the message overhead, extending the network lifetime. Wireless sensor networks have unique routing protocol requirements because of the dispersed network and architecture. In this paper, a decentralised hierarchical cluster-based WSN routing algorithm is discussed. This method reduces the amount of control packets by running the clustering and multi hop routing algorithms simultaneously. The findings of this study, when compared to the LEACH protocol, which is a well-known and popular protocol in this category, confirm the notion that energy conservation will increase network longevity.
Design of Dielectric Structures with Nonuniform Holes Optimized for Backscattering Reduction

We present design and optimization of three-dimensional dielectric structures that provide efficient backscattering reduction (BSR). Although BSR is a subject involved in a plethora of applications and is studied intensively in the literature, the complexity of the designed structures often leads to challenges in fabrication and production phases. In this study, very effective BSR is achieved with relatively simple dielectric geometries using only a single material and air-filled holes. Moreover, with the designed structures, BSR can be achieved not only in a single frequency range but also in two frequency bands. All structures are solved and analyzed by the multilevel fast multipole algorithm (MLFMA) and optimizations are successfully performed by combining this method with genetic algorithms (GAs). By optimizing the size, arrangement, and depth of holes on dielectric structures, backscattering from a metal plate can be reduced by as much as 37 dB.
A Gallium Nitride Intelligent Power Module Based on Bonding Wire Interconnection

Short switching time of gallium nitride high electrons mobility transistors (GaN HEMTs) cause much more challenge for their package and integration. This article1proposes a hybrid packaging method based on bonding wire technology. This interconnection method inevitably increases the parasitic inductance of drive loop, leading to crosstalk and gate oscillation. A driving strategy to suppress these phenomena is applied in the gate loop. Finally, a hybrid packaging intelligent power module combined with print circuit board and direct bonding ceramic is fabricated. The power loop stray inductance of GaN HEMT half bridge is reduced to 1.94nH according to the experiment result. Based on the GaN half bridge of designed module, a 2.14kW boost converter has been built in this paper and its peak efficiency reaches 98.28%.
A Systematic Parasitic Capacitance Extraction Procedure for Three Level Neutral Point Clamped Inverter Modules

This paper develops a cost-effective and accurate procedure for parasitic capacitance extraction for three-level neutral-point-clamped (3L-NPC) inverter modules. Compared to traditional methods, which require full system measurements or open-module configuration to obtain the module parasitic capacitances, this paper simply estimate the parasitic capacitances from the ringing frequency of the common mode (CM) current in the proposed extended double pulse test (eDPT) setup. The proposed analytical method has been verified and compared with the traditional open-module measurement results. The extracted parasitic capacitances have also been used in the CM electromagnetic interference (EMI) model and show good accuracy in predicting the CM noise spectrum compared to the experimental results from a three-phase inverter-filter test bed.
Study of Characteristics and Applications of Microwave Photonic Radar

Photonic generation of microwave signals has no-table advantages in terms of high frequency (up to millimetre-wave band), broad frequency tunability, minimal transmission loss in optical fibres, and high resistance to electromagnetic interference. Here, we present a photonic-based radar that is powered by electronic-based optical modulation, allowing for increased resolution and doing away with the need for radar signal processing and generation using ultrafast electronics. With a significant reduction in system complexity, this radar lays a crucial technological foundation for the development of next-generation broadband radars, which are crucial for universal sensing applications including autonomous driving, surface mapping, and, meteorological monitoring.
Dual-polarized Patch Antenna of Large Frequency Tuning Range at mm-Wave Frequency Bands

In this paper, we present a dual-polarized frequency-reconfigurable patch antenna working at millimeter wave frequency bands for 5G applications. A square patch is surrounded by four metallic L-shaped walls. Four ideal varactor diodes are placed between the corners of the square patch and L-shaped walls. Frequency tunability is achieved by adjusting the capacitances of the varactor diodes. Two 50-Ω probes are used to feed the square patch which can excite two orthogonal polarizations. Operating frequency can vary from 23 GHz to 45 GHz with a 10-dB return loss when the capacitance decreases from 0.05 pF to 0.005 pF. The isolation between two polarizations is better than 13 dB over the operating frequency bands. Cross-polarization level is lower than −15 dB. In addition, the quality factor of varactor diodes is studied to demonstrate its influence on antenna efficiency.
Motion planning of space robot obstacle avoidance based on DDPG algorithm

In order to solve the problem of unstructured environment and complex operation task of space robot, this paper use DDPG algorithm which is data-driven and model free in the obstacle avoidance motion planning of 7-DOF space robot of free-floating base. Aiming at the difficulty and the low speed of the convergence of DDPG algorithm, artificial guidance term is added on the basis of traditional sparse reward function. This paper proposes an improved method of reward function based on task decomposition architecture, in which the weight coefficients of obstacle avoidance guidance term and target guidance term are dynamically adjusted. Simulation results show that the proposed method effectively improves the convergence performance of the algorithm, and enables the space robot to better complete the task of avoiding collision and approaching the target point.
Continuous Rectangular Phoenix Cells Mapping for Direct Copolar and Crosspolar Optimization of Quasi-Periodic Reflective Surfaces

This paper proposes a general methodology to enhance the efficiency of the direct optimization of the copolar and crosspolar radiation of large aperture quasi-periodic reflective surfaces (QPRS) antennas by ensuring the layout continuity without abrupt geometrical variation. This is done through the exploitation of the Phoenix cells (PC) properties, by efficiently parametrizing and interpolating PC lookup tables. In particular, the proposed parametrization allows the description of the QPRS layout through continuous functions without losing precision. Indeed, the description of the QPRS through continuous functions, namely B-spline functions, allows for to reduction of the large- scale optimization problem dimensions and naturally ensures the layout smoothness. A use case of a large faceted contour beam reflectarray (RA) is presented, showing a remarkable improvement in both the copolar and the crosspolar discrimination levels compared to classical synthesis techniques and the RA layout smoothness is practically demonstrated.
Numerical simulation and parameters inversion for non-symmetric two-sided fractional advection-dispersion equations

Abstract This paper deals with numerical solution and parameters inversion for a one-dimensional non-symmetric two-sided fractional advection-dispersion equation (FADE) with zero Neumann boundary condition in a finite domain. A fully discretized finite difference scheme is set forth based on Grünwald–Letnikov's definition of the fractional derivative, and its stability and convergence are proved by estimating the spectral radius of the coefficient matrix of the scheme. Furthermore, an inverse problem of simultaneously determining the fractional order and the dispersion coefficients is investigated, and numerical inversions are carried out by using the optimal perturbation regularization algorithm. The inversion results show that the fractional order and the dispersion coefficients in the FADE can be determined successfully by the final observations.
Rapid Curve Scanning Global MPPT for PV Applications Under Partial Shading

When the Photovoltaic (PV) cells that form a PV module are exposed to different levels of solar irradiance (partial shading), several maximum power points might be created. Traditional Maximum Power Point Tracking (MPPT) methods operate at the first Maximum Power Point (MPP) found, and disregard the possibility of finding a higher-power MPP (global maximum). As a result, PV modules operating under partial shading conditions can incur on significant energy losses. This work introduces a Rapid Curve Scanning Global MPPT (RCS-GMPPT) method by combining the intuitive concept of I-V curve scanning with large-signal state-plane modelling to achieve an extreme scanning speed. As a result, the method is capable of finding the GMPP in under lms. The RCS-GMPPT is fully compatible with digitally controlled power converters, and it can be implemented as an add-on with minimum processing requirements. The analysis is supported by detailed mathematical procedures and validated by simulation and experimental results.
Deep learning based cross-view image matching for UAV geo-localization

Unmanned Aerial Vehicles (UAVs) geo-localization refers to finding the position of a given aerial image in a large reference satellite image. Due to the large scale and illumination difference between aerial and satellite images, it is challenging that most existing cross-view image matching algorithms fail to localize the UAV images robustly and accurately. To solve the above problem, a novel UAV localization framework containing three-stage coarse-to-fine image matching is proposed. In the first stage, the satellite image is cropped into several local reference images to be matched with the aerial image. Then, ten candidate local images are selected from all of the local reference images with a simple and effective deep learning network, LPN. At last, a deep feature-based matching is employed between candidate local reference images and aerial images to determine the optimal position of the UAV in the reference map via homography transformation. In addition, a satellite-UAV image dataset is proposed, which contains 3 large-scale satellite images and 1909 aerial images. To demonstrate the performance of the proposed method, experiments on the large-scale proposed dataset are conducted. The experimental results illustrate that for more than 80% of the testing pair images, the proposed method is capable of refining the positioning error within 5 pixels, which meets the needs of UAV localization and is superior to other popular methods.
Wideband Planar Printed Aperture on a Triangular Lattice for Millimeter Wave Applications

This paper presents experimental results for a Planar Ultra-wideband Modular Antenna (PUMA) array integrated with a coaxial feed network using Ball Grid Array (BGA) technology. A PUMA aperture is designed and manufactured with a BGA interface in place of typical feed structures. The BGA-backed PUMA aperture is then connected to a matching BGA interface on a coaxial through test circuit, allowing typical embedded element RF characterization performance and functionality evaluation of the PUMA aperture as a BGA package.
Wideband mmWave Wireless Power Transfer: Theory, Design and Experiments

A new type of wireless power transfer system is presented with wideband mmWave transmitters and rectennas. The proposed system transmits a beam formable and beam steerable signal by exploiting the inherent frequency-dispersive nature of a passive leaky wave antenna, thereby eliminating the need for active phased array and other costly control methods. Multiple nodes can be wirelessly powered simultaneously by using a wideband mmWave rectenna to harvest the frequency scanning signals. A 24-34 GHz rectenna was designed in a highly integrated fashion and has been tested to show its high conversion efficiency of >50% at the frequency and power levels of interest. We have presented a system demonstration for remotely charging diverse nodes at > 1 m distance by using the proposed system with feedback control for the multi-tone frequency modulation and sweeping of the transmitting signals. Our work has showcased the passive beamforming and multi-node tracking of mmWave WPT system using significantly reduced cost and complexity.
High-Frequency Fully-ZVS Isolated Current-Fed Bidirectional DC-DC Converter

In this paper, an isolated high-frequency current-fed DC-DC bidirectional converter with zero voltage switching (ZVS) operating is proposed. The proposed converter can be operated as both step-up and step-down converter. In the proposed converter, there is a main transformer which is used for isolation of low voltage side from the high voltage side. Moreover, the proposed converter has achieved the capabilities of having an isolated structure with lower volume, bidirectional operation, high voltage conversion ratio, zero voltage switching operation of all four switches, simple switching pattern, achieving a simple controlling scheme for the whole range of duty cycle (O<D<l), high-frequency operation, and high-power density. The proposed converter is implemented for an operating frequency of 1MHz and the experimental results verify the theoretical results.
The Indonesia Stock Exchange Composite Prediction based on Macroeconomic Indicators using ARIMA, LSTM, and ANN

The capital market will make it uncertain to collect investments in the future because it is constantly shifting. This ambiguity shows that there are risks that investors must accept. Investors typically aim to maximize their expected return considering the risk taken. In order to minimize investment risk, it is critical to measure the movement of the stock market. Indonesia Stock Exchange (IDX) indicator values are a reflection of the state of the stock market. The focus of this research is to forecast the IDX using macroeconomic factors that reflect the current state of the economy. Interest rates, inflation rates, money supply, and exchange rates are the macroeconomic variables. Bank Indonesia provided secondary data for this study. ARIMA, LSTM, and ANN are the approaches used in this study. This approach is thought to be useful for handling issues, representing complex patterns of each macroeconomic variable, and predicting values with lowest error. Based on the research results, the Root Mean Square Error (RMSE) for the ARIMA (0.087), LSTM (0.0298), and ANN (0.0466). The best time to predict is 2 months before. The RMSE value proves that macroeconomic variables are good indicators to predict the IDX movement.
Symplectic structures from topological Fukaya categories

The topological Fukaya category is the global sections of a certain sheaf of categories on a Lagrangian skeleton. Nadler has given a combinatorial description of this sheaf in the case of generic singularities. We show here that restriction to the boundary of this sheaf of categories determines a shifted Lagrangian morphism on the corresponding moduli spaces. Examples of such moduli spaces include wild character varieties, certain cluster varieties, multiplicative Nakajima varieties, and the augmentation variety of knot contact homology. More generally, the moduli space of objects in the Fukaya category of any Weinstein manifold is expected to be of this form. The general machinery of shifted symplectic geometry then returns symplectic and Poisson structures, and quantizations when these can be expected.
Multi-Objective Parametric Analysis of EV Traction Inverter between Reliability and Efficiency

Transportation electrification is rapidly gaining momentum to reduce greenhouse gas emissions and carbon foot-prints. To help accelerate a swift transition to decarbonization, alternative modes of transportation, such as electric vehicles (EV) must provide superior performance and competitive advantages in regards to reliability (longevity), efficiency (fuel economy), and volumetric energy or power density (compact integration) in contrast to fossil fuel-powered transports. However, achieving optimum designs is challenging due to the multiple physical domain interactions between thermal, electrical, and mechanical systems within an EV drivetrain. Hence, this paper focuses on the multi-parametric design analysis of the EV traction inverter system to perform trade-off studies between two competing objectives: reliability and efficiency. A seamless performance evaluation process was developed between PLECS, a simulation platform for power electronic systems and the optimization computation of genetic algorithm based on NSGA-II in Python to achieve a reliable repetition of varied operating modes of the inverter to seek optimized parameters and non-dominant solutions. A realistic, high-fidelity, and multi-domain EV model based on the known physical parameters of Nissan Leaf was developed in PLECS along with a dynamic driving profile. The paper further discusses parametric design analysis and comparison based on different power module materials and operating conditions, such as EV battery voltage and power module switching frequency. The simulation results show that an optimized SiC solution can provide a higher efficiency design whereas higher reliability can be expected with the optimized IGBT-based designs.
Towards Effective Multipath Scheduling with Multipath QUIC in Heterogeneous Paths

Quick UDP Internet Connection (QUIC) is a network transmission protocol proposed by Google which has lower latency, higher flexibility and stronger security compared with TCP. Multipath QUIC (MPQUIC) further enhance the user experience and adapt the large-scale network traffic by using multiple paths. Different from Multipath TCP (MPTCP), MPQUIC scheduler can perform finer granularity stream scheduling. In heterogeneous paths, MPQUIC not only has to consider inter-stream HoL blocking, but also encounters severe intra-stream HoL blocking within individual stream; in addition, MPQUIC scheduler needs to control scheduling rate to ensure that stream data is not backed up in sub-path queue, but also the bandwidth of sub-path is fully utilized. However, existing scheduling algorithms cannot solve the problems above. Therefore, we propose multi-stream hierarchical scheduling algorithm(MS-HS), which speeds up the transmission of high-priority streams by controlling data allocation rate and giving each stream two priority levels. We evaluate the benefits of MS-HS under heterogeneous paths by comparing it with the classical scheduler of MPQUIC. Our evaluation shows that our scheduler can reduce up to 31.4% of the high-priority stream completion time, while MS-HS achieves higher throughput than the original best scheduler.
Liquid Based Phantom Preparation and Dielectric Characterization for Breast Cancer Imaging

Developing of the phantom for specific reason like skin, fat, glandular and tumor for breast tissue is very important part of the actual measurement of the Devices or antenna which is useful for the breast cancer imaging system. Till now such phantom is not reported very clearly therefore in this paper we have attempted to develop the phantom material for different dielectric properties similar to breast phantom. In this proposed work Polyethylene Glycol (PEG) and NaCl and water based liquid phantom has been prepared for breast cancer imaging. Various range of the Dielectric properties of the mixture has been achieved with the variation of PEG, Water and NaCl. This liquid based phantom deals with the development of realistic breast phantom dedicated to microwave imaging for breast cancer detection. The Dielectric properties of the solution hass been measured from 1GHz to 10GHz .
A Reconfigurable Modular Switched Capacitor Structure for High Efficiency Over a Wide Input Voltage Range

Accommodating a wide input voltage range often causes significant variation in efficiency and power dissipation, limiting the maximum power which can be delivered. A reconfigurable modular switched capacitor structure capable of maintaining a very high efficiency over a wide input voltage range is proposed in this paper. The proposed solution is freely scalable to suit arbitrary range of input while enabling reduced voltage stresses on the power switches and maintaining optimal operation. It is also widely adoptable in different designs. Two experimental prototypes had been built and tested to validate the effectiveness of the proposed solution.
Improved Q-MRAS Based Online Rotor Time Constant Compensation for IFOC Induction Motor Drives

In the conventional Q-based MRAS scheme for rotor time constant estimation, the inductance information is crucial. If incorrect inductance value is used, the output of the Q-based MRAS model generates steady-state error, resulting in the degraded vector control performance. Such inductance parameter is generally obtained by self-commissioning tests, which are not only cumbersome but also imperfect. First, this paper presents a theoretical background of the effects of the inductance estimation error on the conventional Q-based MRAS model in terms of reactive power, angle error, and torque error. In sequence, a stator flux λ-based MRAS is proposed for the inductance compensation. The proposed scheme can update the inductance information in real time and improves the performance of IFOC. It does not require a self-commissioning test for inductance mapping with respect to motor current or flux. Additionally, the implementation of the proposed method is simple. Simulation and experimental results verify the effectiveness of the proposed method.
Cooperative differential game-based approximate optimal tracking control for reconfigurable robot

In this paper, a cooperative differential game-based approximate optimal tracking control method is proposed for the reconfigurable robot system. The reconfigurable robot system's dynamic model is expressed by the subsystem's formulation. According to the adaptive dynamic programming (ADP) approach, the approximate optimal tracking control policy is developed by a fuzzy logic-based cooperative differential game manner for addressing the coupled HJB equation. Then, the closed-loop robotic system is proved to be asymptotically stable according to the Lyapunov theorem. At last, two types of simulation results have proved the effectiveness as well as the advantage of the proposed cooperative differential game-based approximate optimal tracking control method.
Fault Location Method of Bistribution Network Based on Heuristic Splitting Algorithm

A heuristic separation algorithm-based traveling wave detection method is proposed in view of the severe mixing of waveforms of fault traveling waves in distribution network and the difficulty in identifying the position of wave front in case of high-resistance grounding fault with low slope and low amplitude of wave front. Firstly, use wavelet analysis to decouple the initial fault traveling wave signal, then use heuristic division algorithm (abbreviated as BG algorithm) to detect the sudden change point of the fault traveling wave, and use threshold method to accurately locate the traveling wave front. In addition, a new double-end traveling wave distance measurement method that is not affected by wave velocity and line length is derived based on the transmission characteristics of the line and traveling wave, which improves the accuracy and reliability of traveling wave fault location results.