Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Multi-metric Cache Replacement Policies in Vehicular Named Data Networks

Vehicular Named Data Network (VNDN) uses NDN as an underlying communication paradigm to realize intelligent transportation system applications. Content communication is the essence of NDN, which is primarily carried out through content naming, forwarding, intrinsic content security, and most importantly the in-network caching. In vehicular networks, vehicles on the road communicate with other vehicles and/or infrastructure network elements to provide passengers a reliable, efficient, and infotainment-rich commute experience. Recently, different aspects of NDN have been investigated in vehicular networks and in vehicular social networks (VSN); however, in this paper, we investigate the in-network caching, realized in NDN through the content store (CS) data structure. As the stale contents in CS do not just occupy cache space, but also decrease the overall performance of NDN-driven VANET and VSN applications, therefore the size of CS and the content lifetime in CS are primary issues in VNDN communications. To solve these issues, we propose a simple yet efficient multi-metric CS management mechanism through cache replacement (M2CRP). We consider the content popularity, relevance, freshness, and distance of a node to devise a set of algorithms for selection of the content to be replaced in CS in the case of replacement requirement. Simulation results show that our multi-metric strategy outperforms the existing cache replacement mechanisms in terms of Hit Ratio.
7.2-kV Single-Stage Solid-State Transformer Based on the Current-Fed Series Resonant Converter and 15-kV SiC mosfets

This paper proposes a novel two-level single-stage direct ac–ac converter for realizing a 7.2-kV medium-voltage (MV) solid-state transformer (SST) based on 15-kV SiC mosfets. A new current-fed series resonant converter (CFSRC) topology is proposed to address major challenges in MV ac–ac converters such as achieving zero-voltage switching (ZVS) for the MV mosfets across wide voltage and load ranges and minimizing system capacitance. The topology is analyzed with both time-domain analysis and first harmonic approximation to provide useful equations for circuit design. Constant deadtime strategy is adopted, allowing partial ZVS to occur at low-voltage (LV) levels. ZVS behavior over wide voltage range is investigated, and calculation of the associated loss from partial ZVS is presented. System parameters are optimized based on the tradeoff between conduction loss and switching loss. The 15-kV mosfet has been tested continuously at a park voltage of 10 kV and 37 kHz, indicating stable device operation and an extremely high voltage × frequency figure of merit. Moreover, inherent cycle-by-cycle current limiting in the proposed CFSRC under output short-circuit circumstance is realized by paralleling diodes to the LV resonant capacitors. Without employing any additional current sensors, the input and circulating currents are limited to a safe range automatically when the short-circuit occurs. This paper presents detailed short-circuit protection operating principles and peak resonant current equation to aid the design of the resonant tank. A full-scale and compact SST that converts 7.2 kV ac to 240 V ac is developed to verify the theoretical analysis. This is the highest reported voltage rating for two-level-based power converters without device series connection. ZVS is verified and achieved over wide voltage and load ranges with a peak efficiency of 97.8%. A short-circuit experiment is conducted at 3-kV peak voltage to verify the analysis. Experimental results closely match the theoretical analysis.
A 61-nW Level-Crossing ADC With Adaptive Sampling for Biomedical Applications

An ultra-low-power level-crossing analog-to-digital converter (LC-ADC) with on-chip adaptive sampling is presented. Different from conventional ADCs based on Nyquist sampling, LC-ADC utilizes sparsity of signals for low power data acquisition. To save power, the proposed adaptive sampling scheme is implemented with only one scaler and one high-precision comparator, which is in sharp contrast to conventional LC-ADCs that require an n-bit digital-to-analog converter and two comparators. Implemented in 0.18- $\mu {\mathrm{ m}}$ CMOS process, the proposed ADC consumes only 61 nW under 0.5V supply, and achieves 5.6 bits equivalent numbers of bits and 35 dB signal-to-noise and distortion ratio with an operating frequency up to 1 kHz.
Separable and Reversible Data Hiding in Encrypted Images Using Parametric Binary Tree Labeling

This paper first introduces a parametric binary tree labeling scheme (PBTL) to label image pixels in two different categories. Using PBTL, a data embedding method (PBTL–DE) is proposed to embed secret data to an image by exploiting spatial redundancy within small image blocks. We then apply PBTL–DE into the encrypted domain and propose a PBTL-based reversible data hiding method in encrypted images (PBTL–RDHEI). PBTL–RDHEI is a separable and reversible method that both the original image and secret data can be recovered and extracted losslessly and independently. Experiment results and analysis show that PBTL–RDHEI is able to achieve an average embedding rate as large as 1.752 bpp and 2.003 bpp when block size is set to <inline-formula><tex-math notation="LaTeX">$2\times 2$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$3\times 3$</tex-math></inline-formula>, respectively.
Phase Reconfigurable Microwave Power Divider

A reconfigurable power divider (PD) that can operate either in an in-phase mode or out-of-phase mode is presented. To that end, the novel concept of using tunable phase shifter, which is a reflection-type loaded coupled lines, to emulate an effective variable length transmission line (TL) is utilized. The proposed PD uses a quarter-wavelength TL, a <inline-formula> <tex-math notation="LaTeX">$100~{\Omega }$ </tex-math></inline-formula> isolation resistor and two tunable phase shifters. The presented theoretical analysis shows that by properly selecting the parameters of the phase shifter, it can be used to approximate the performance of variable length TL. To validate the design, a prototype of dimensions 50 mm <inline-formula> <tex-math notation="LaTeX">${\times }$ </tex-math></inline-formula> 25 mm is built, using Rogers RO3010 substrate, and tested. The results indicate that the device can operate as an in-phase and out-of-phase by using suitable biasing voltages. Across the band 0.9–1.1 GHz, the device has more than 12 dB return loss at all the ports and more than 15 dB isolation between the two output ports with less than 5° phase deviation for both of the in-phase and out-of-phase states.
A Packaged Noise-Canceling High-Gain Wideband Low Noise Amplifier

This brief presents a bandwidth and gain enhancement technique for packaged single-ended wideband low noise amplifier (LNA) module for high-sensitivity receivers. Wide bandwidth, low noise figure (NF), and high power gain are achieved by using gate-source inductors assisted impedance matching, current reuse feed-forward noise cancellation technique, and integrated shunt peaking output buffer. Fabricated in UMC 65-nm CMOS technology, the proposed LNA packaged in quad-flat no-leads package module achieves a maximum power gain of 20.5 dB, NF of 2–2.5 dB, 3-dB bandwidth from 0.4 to 2.2 GHz, and third-order inter modulation intercept the point of −5 dBm while consuming 25 mA current (including buffer) from 1.2 V supply.
Energy-efficient Resource Allocation for NOMA-assisted Mobile Edge Computing

In this paper we evaluate the effect of increased wireless spectral efficiency on the performance of mobile edge computing. Specifically, we study the energy minimization of computation offloading for a multicarrier non-orthogonal multiple access (NOMA) assisted mobile edge computing (MEC) system. A joint radio-and-computational resource allocation problem is formulated, in which three different resources should be appropriately allocated, including subcarriers, transmission power and computational resources. The formulated resource allocation problem belongs to mixed integer nonlinear programming (MILNP) and is NP-hard. We propose therefore a heuristic solution consisting of two steps, NOMA clustering and subcarrier allocation, and joint computational resource and power allocation. Our numerical results show that NOMA based MEC significantly outperforms its OMA counterpart, especially in scenarios with strict delay limits, where both the transmission and the computational resources become scarce.
V2P Connectivity on Higher Frequency Band and CoMP Based Coverage Expansion

Vehicle-installed access points (VAPs) based mobile network emerges as a flexible and efficient wireless access means for 5G and beyond. This paper reports analytical results on vehicle-to-pedestrian (V2P) connectivity on higher frequency band. Introducing 5G new radio (NR) numerology can expand applicability of orthogonal frequency division multiplexing (OFDM) on such intensive mobility environment where VAPs move past. Additional proposal is a coordinated multipoint (CoMP) based coverage expansion via multiple VAPs. Simulative evaluation also presents its effectiveness based on street canyon scenario.
Studies on the structure and electronic properties of Linear Chitosan-Silver nano-composite for biosensor applications

In the present study, we computed the geometrical and electrical influence of silver atoms (Ag) over chitosan (CS). The electrical influences were studied through analyzing the electrostatic potential map, the HOMO-LUMO orbitals, and the energy gap. Three systems were simulated for this study. They are, pure chitosan (CS), chitosan with one silver atom (CS-Ag) and chitosan with three silver atoms (CS-3Ag). The theoretical calculations were done using Density Functional Theory (DFT) at B3LYP level set theory with SBKJC basis set to obtain the structure and energetic properties of the systems. Our calculations confirmed that Ag atoms have minimal effect on the geometry of CS. Further, the simulation suggests that the interaction between Ag atoms and CS is due to purely a Van der Waals interactions on most of the electro-positive sites. On the other hand, the HOMO-LUMO orbitals of CS-Ag and Cs-3Ag show a higher density near to the Ag atoms, which result in a reduction of the energy gap. Finally, the antibacterial properties of CS and Ag combined with the low energy gap suggest that CSAg nano composite (CS-AgNc) could be a suitable nanomaterial for bio-sensing applications.
Data-Driven Multi-Hidden Markov Model-Based Power Quality Disturbance Prediction That Incorporates Weather Conditions

Power quality (PQ) disturbance in power systems has been a concern for operators and customers. The purpose is to locate and forecast the presence of PQ disturbances to suppress or avoid their negative effects on power grid and appliances. This study, using a multi-hidden Markov model (MHMM), motivates data-driven tools to achieve situation awareness of PQ disturbance. We first design a modified adaptive-sorted neighborhood method that consists of blocking and merging phases to locate PQ disturbance sources from a large volume of PQ records. We then group and discretize the data on disturbance sources and weather conditions according to regions. The capability of MHMM-based tools to predict future PQ disturbance level can be improved by clustering the training set of time series of PQ disturbance levels based on weather conditions. A Hadoop-based PQ analysis framework is proposed to reduce computational times, considering the volume of PQ data in a realistic power grid is large. We utilize numerical case studies that use real data collected from a power system of a Chinese city to investigate the correctness and feasibility of the proposed method.
New Signal Processing for Fast and Accurate QEPAS Measurements

Quartz Enhanced Photoacoustic Spectroscopy (QEPAS) gas sensors have been widely developed over the last decade. This technique takes advantage of a high quality factor micro tuning fork to enable high detectivity & high selectivity miniature gas sensors. Lock-in detection technique is classically used to measure the resonator amplitude proportional to gas concentration, but this technique is slow and does not follow the resonator frequency shift over temperature. This paper presents a new QEPAS signal processing technique that allows faster and more accurate measurements, that will enable accurate and fast multi gas sensors.
Flooded Area Segmentation from UAV Images Based on Generative Adversarial Networks

The detection, localization and evaluation of small flooded areas can contribute to decrease the economical damages of such disasters. The cheapest and most accurate method is to segment the aerial images taken from UAV. In this paper, we propose a new method for detection of regions of interest, like flooding in rural areas, using Generative Adversarial Networks (GAN) and Graphics Processing Units (GPU). The classical GPU is used to create, by parallel calculation of textural features, extracted from the co-occurrence matrix, the supervised mask of flood segmentation in the images from the learning set. Based on these images and their associated real masks, the weights of the generator and discriminator are established. A set of 40 images were used for the learning phase and another set of 60 images were used for method validation. The results demonstrate that the proposed method provide a high accuracy and robustness, comparing with other papers for flooding evaluation. Even if it is a relative long time to learn the GAN, in the operational phase the time for image segmentation process is very short.
A Character Prediction Approach in a Security Context using a Recurrent Neural Network

Nowadays, cybersecurity focuses on detecting intrusions and anomalies with the aid of automated methods, exploratory visual analysis systems or real-time monitoring with dynamic visual representations. Current research in cybersecurity is not yet at the point where analysts can rely on systems for assuring security. Being in a Data Era, the amount of gathered data can play opposite roles: on one side, to serve the security of an organization, but on the other, to pose security threats. Our paper aims to present a technical implementation of a recurrent neural network that predicts characters in a security context. The end goal of the proposition is to create an application for adding security to a web server by predicting log entries before an actual attack. If such a server would get a certain entry pattern, it will predict a new log before an actual attack. Results demonstrate that character prediction can be achieved with 40% accuracy.
DFIG Topologies for DC Networks: A Review on Control and Design Features

The doubly fed induction machine has been traditionally adopted in adjustable-speed ac power generation drives in order to take advantage of the reduced rating for the power electronic interface. Aside this well-established application where the doubly fed induction generator (DFIG) is controlled by a back-to-back converter, recent literature records a growing interest toward un-conventional DFIG drives for dc power generation, combining DFIG high control freedom with simplified power electronic interfaces to achieve an overall cheap and fully controllable system. Despite several concepts have been demonstrated on small-scale rigs, there is a lack of systematic comparison among different topologies and control solutions. This paper bridges this gap by providing a review of recent topologies, their control, design and performance, and operation issues. As major novelties, this paper includes off-spec performance comparison of different torque-ripple mitigation strategies, discussion of sizing requirements for generator and power electronics, fundamental aspects of the behavior under voltage dips, and priorities and challenges for future research on the subject.
Bi-level Optimal Scheduling of Demand Response Integrated Energy Hub Through Cost and Exergy Assessments

Energy hub has gained its popularity recently in describing the multi-energy complements in integrated energy systems. In this paper, a novel bi-level optimal scheduling model for a demand response integrated energy hub is established aiming at a balance between cost analysis and exergy assessment. A modified steam injected gas turbine structure is introduced to flexibly transit working status according to demand changes. The Karush-Kuhn-Tucker condition and big M method are applied to transform the nonlinear model to a mixed integer linear programming problem, which can be easily solved by commercial solvers. Case study of a smart multi-energy building demonstrates the effectiveness of the proposed model. Results show that the scheduling method in this paper enables significant reduction in the total operating costs and improvement of the overall exergy efficiency. Besides, the modification of energy converting device and application of interruptible load effectively alleviate energy supply pressure of distributed power grid and increase the service life of energy storage devices.
Broadband Circularly Polarized Filtering Antennas

This paper consists of two parts. The first part presents a review of the recent development in broadband circularly polarized filtering antennas. The second part presents a novel design of broadband integrated filtering antenna based on eighth-mode SIW (EMSIW) resonators for rectenna applications. This work has three main novel contributions. First, by adjusting the external quality factors and coupling coefficients of the resonators in this filtering antenna, optimum input impedance with a complex value can be realized within the filtering antenna. Thus there is no need for an external impedance matching network, which is usually required between the antenna and the rectifying circuits; Second, compared with traditional microstrip resonators, high-Q EMSIW cavities are used to increase antenna gain; third, the coupling gap between the EMSIW resonators also acts as the feeding structure of the radiator. So the feeding structures are all on the middle layer. The ground plane on the back side is a complete structure without any defects. This novel structure design improves front-to-back ratio to enhance the antenna receiving efficiency. To validate this method, two C-band circularly polarized integrated filtering antennas with an input impedance of 50 $\Omega $ and complex impedance are designed, simulated, and fabricated. The measured results show that the operating frequency bandwidth of the proposed antennas is more than 14.5% at C-band with the gain above 8 dBi. The 3-dB axial ratio bandwidth is larger than 8.5% and the front-to-back ratio is higher than 18 dB. Moreover, the proposed antenna with complex impedance is conjugate matched with the input impedance of a specific rectifying circuit at 5.8 GHz and harmonics suppression at the second-harmonic frequency is achieved.
Nash Equilibrium Seeking for Games in Hybrid Systems

Nash equilibrium seeking for games in a class of hybrid systems is investigated in this paper. Different from the existing works, the players in the present game framework are composite of a set of continuous-time players and a set of discrete-time players. Nash equilibrium seeking for such a hybrid game is challenging as some players update their actions in continuous time while the remainders update their actions in discrete time. To accommodate the hybrid games, we firstly consider a case in which the players update their actions according to the hybrid gradient play (i.e., the continuous-time players update their actions according to the continuous-time gradient play with sampled information flow while the discrete-time players update their actions according to the discrete-time gradient play). Then, we consider the case in which the players have restricted access to their opponents' actions. A hybrid consensus-based strategy is proposed for this case. The stability of the Nash equilibrium under the proposed hybrid seeking strategies is theoretically proven by utilizing Lyapunov stability analysis. Lastly, the hybrid seeking strategies are validated through a numerical example.
Galvanometer scanner modeling for Selective Laser Melting deflection system simulation

Modeling of the actuating element of the three axis galvanometer based actuator for Selective Laser Melting (SLM) additive manufacturing (AM) process is addressed in this paper. Dynamic behavior of the single axis galvanometer motor actuator is studied with physical considerations that improve basic linear and simplified existing models and extend the frequency domain validity of the proposed model. Optimal feedback and feedforward-type control structure synthesis is derived through a black-box identification of the actual industrial system for the models validation purpose. Responses of the developed models are compared to experimental data. Modeling errors coming from both the actuator behavior (angular position values) and the marking process qualities (marking and focusing planes geometrical parameters) are found to be sufficiently small to allow the developed simulator to be used as an entry point for future investigations on the the single axis motor and the complete three axis actuator system.
UMBmark : a method for measuring, comparing, and correcting dead-reckoning errors in mobile robots

This paper presents a new approach to accurate and reliable dead-reckoning with mobile robots. The approach makes use of special properties of our recently developed MultiDegree-of-Freedom (MDOF) mobile platform, in which two differential-drive mobile robots (called "trucks") are physically connected through a compliant linkage. Using one linear and two rotary encoders, the system can measure the relative distance and bearing between the two trucks. During operation, both trucks perform conventional dead-reckoning with their wheel encoders, but, in addition, use information about their relative position to correct dead-reckoning errors. Our system, called Compliant Linkage Autonomous Platform with Position Error Recovery (CLAPPER), requires neither external references (such as navigation beacons, artificial landmarks, known floorplans, or satellite signals), nor inertial navigation aids (such as accelerometers or gyros). Nonetheless, the experimental results included in this paper show one to two orders of magnitude better positioning accuracy than systems based on conventional dead-reckoning.
International Journal of Advanced Robotic Systems towards a Stable Robotic Object Manipulation through 2d-3d Features Tracking Regular Paper

In this paper, a new object tracking system is proposed to improve the object manipulation capabilities of service robots. The goal is to continuously track the state of the visualized environment in order to send visual information in real time to the path planning and decision modules of the robot; that is, to adapt the movement of the robotic system according to the state variations appearing in the imaged scene. The tracking approach is based on a probabilistic collaborative tracking framework developed around a 2D patch‐based tracking system and a 2D‐3D point features tracker. The real‐time visual information is composed of RGB‐D data streams acquired from state‐ of‐the‐art structured light sensors. For performance evaluation, the accuracy of the developed tracker is compared to a traditional marker‐based tracking system which delivers 3D information with respect to the position of the marker.