Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Resource Allocation Algorithm in Fog Networks with Energy Cooperation

Fog networks with energy harvesting can extend the scope of services for users in time and space remarkably. However, the imbalance of the harvested renewable energy and the workloads of fog nodes (FNs) limits the performance of the whole fog computing system. This paper investigates on resource allocation in energy cooperation enabled fog computing networks, where FNs are connected with a smart grid and energy can be transferred between FNs. Firstly, an optimization problem is formulated to minimize the service latency of the fog computing system and is proved to be convex. After that, a cooperative graph-based distributed resource allocation (CGDRA) algorithm is proposed to solve the optimization problem by a distributed method. In our proposed CGDRA algorithm, an energy cooperative graph is constructed at first, then the FNs cooperate with their neighbors in energy by exchanging messages. Simulation results show that the CGDRA algorithm can balance the energy utilization ratios of different FNs and service latency of the fog network is reduced significantly. Moreover, the results obtained by our proposed CGDRA algorithm can approximate to the global optimal solutions with lower complexity compared with traditional centralized algorithm.
An Optical Joint Angle Measurement Sensor based on an Optoelectronic Sensor for Robot Manipulators

This paper presents the design of a joint angle measurement sensor using optoelectronic reflective sensors for use with robotic applications. It offers a minimised solution to shape sensing that can easily be integrated into robotic joints. A mathematical model used to characterize sensor behaviour is presented, and validated experimentally. A single unit of a robotic jointed finger is designed, and the sensing principle is tested with rotational motion. Results are presented and compared to simulated values. While the mathematical model can accurately estimate output signal with varying displacements, limitations of angle range means an updated sensor model is required, with addition of real electrical properties such as saturation of signal and resistance of electrical components. Regression fitting method is therefore done and a third order function was able to accurately estimate the output signal over a simulated sweep of joint angle values.
Edge Computing for Internet of Things: A Survey

The Internet of Things (IoT) is integrating the physical world with the information world. As more and more sensor devices are deployed in the IoT, IoT faces several challenges, such as transmission delay, data storage redundancy, and computing delay. The emergence of edge computing can address these challenges possibly. In this paper, we present an in-depth survey of the integration of edge computing and IoT. First, we briefly introduce the architecture of IoT and discuss a few challenges of IoT. Next, we give an overview of edge computing. We focus on the convergence of edge computing and IoT, and discuss the new architecture and advantages of EIoT. Finally, we summarize the applications of EIoT.
The optical, structural and morphological properties of ultrasonically sprayed ZnO:Mn films

ZnO and ZnO:Mn (at Mn incorporation rates between 1 and 5%) films were obtained at a substrate temperature of 350 ± 5 °C by the ultrasonic spray pyrolysis technique. Optical, structural and morphological properties of ZnO films as a function of Mn amount were discussed. Transmittance spectra, x-ray diffraction (XRD) patterns, scanning electron microscopy (SEM) micrographs and energy dispersive x-ray spectroscopy (EDS) analyses were used to investigate the optical, structural and morphological properties and elemental analyses, respectively. All films have high transmittance, and the band gap changed with Mn incorporation from 3.32 to 3.18 eV. From Urbach tail analysis, the widths of localized states were calculated between 163 and 389 meV. XRD patterns indicated that all films have polycrystalline structures and the best effect on the structural properties of the films was obtained with 4% Mn incorporation. It was seen from SEM micrographs that all films have almost homogeneous surfaces. EDS analyses showed that the amount of Mn element in the solid film increased depending on the increasing Mn incorporation in the solution. As a result, Mn incorporation has a strong effect on the optical, structural and morphological properties of ZnO films and all films, especially the 4% Mn-incorporated one, can be used in optoelectronic industry or photovoltaic solar cells due to their suitable optical and structural properties.
Improving Valence Prediction in Dimensional Speech Emotion Recognition Using Linguistic Information

In dimensional emotion recognition, a model called valence, arousal, and dominance is widely used. The current research in dimensional speech emotion recognition has shown a problem that the performance of valence prediction is lower than arousal and dominance. This paper presents an approach to tackle this problem: improving the low score of valence prediction by utilizing linguistic information. Our approach fuses acoustic features with linguistic features, which is a conversion from words to vectors. The results doubled the performance of valence prediction on both single-task learning single-output (predicting valence only) and multitask learning multi-output (predicting valence, arousal, and dominance). Using a proper combination of acoustic and linguistic features not only improved valence prediction, but also improved arousal and dominance predictions in multitask learning.
Estimation and Tracking for Millimeter Wave MIMO Systems Under Phase Noise Problem

Millimeter wave (mmWave) system is a key technology for the fifth generation (5G). Precoding techniques can be applied in the radio frequency (RF) stage to achieve spatial multiplexing gain. Studying the problems of hardware imperfections in the RF stage for mmWave communication system is very important because it can affect the transmitted signals and overall system performance. In this article, mmWave MIMO system under phase noise problem is proposed. In addition, an optimization problem for the design of hybrid precoder under phase noise is formulated. An alternating minimization algorithm using manifold optimization is proposed to close the performance of the fully digital precoder. A realistic power consumption model is considered. To estimate the mmWave channel parameters and to track the phase noise parameters, a Bayesian Cramér-Rao lower bounds (BCRLBs), Kalman filter, least square (LS) and maximum a posterior (MAP) algorithms are proposed. Furthermore, the proposed system with ideal hardware mmWave system is compared with non-ideal system under amplified thermal noise and residual additive transceiver hardware impairments. Spectral efficiencies (SEs) of the proposed system are provided with different scenarios. The analytical and simulation tests show that the influence of phase noise problem may decrease SE performance, especially at higher phase noise.
A Generic Strategy for Node-Failure Resilience for Certain Iterative Linear Algebra Methods

Resilience is an important research topic in HPC. As computer clusters go to extreme scales, work in this area is necessary to keep these machines reliable. In this work, we introduce a generic method to endow iterative algorithms in linear algebra based on sparse matrix-vector products, such as linear system solvers, eigensolvers and similar, with resilience to node failures. This generic method traverses the dependency graph of the variables of the iterative algorithm. If the iterative method exhibits certain properties, it is possible to produce an exact state reconstruction (ESR) algorithm, enabling the recovery of the state of the iterative method in the event of a node failure. This reconstruction is exact, except for small perturbations caused by floating point arithmetic. The generic method exploits redundancy in the matrix-vector product to protect the vector that is the argument of the product. We illustrate the use of this generic approach on three iterative methods: the conjugate gradient method, the BiCGStab method and the Lanczos algorithm. The resulting ESR algorithms enable the reconstruction of their state after a node failure from a few redundantly stored vectors. Unlike previous work in preconditioned conjugate gradient, this generic method produces ESR algorithms that work with general matrices. Consequently, we can no longer assume that local diagonal submatrices used to reconstruct vectors are nonsingular. Thus, we also propose an approach for deriving nonsingular local linear systems for the reconstruction process with reduced condition numbers, based on a communication-avoiding rank-revealing QR factorization with column pivoting.
Image Fusion Using Pulsed Coupled Neural Network with Modified Spatial Frequency based on NSCT

There are vast Image Fusion (IF) procedures are being projected in many ways by different analysts. Each coordinate point, it means pixel-level spatial space IF strategies, for the most part, lead to differentiate decrease. Pyramidal IF plans with the end goal like Laplacian, inclination, discriminate, quantity of-low-pass, and the morphological pyramids, and so forth abandonment to existing any spatial direction selectivity in the disintegration technique, also later regularly source obstructive impacts. The generally applied Discrete Wavelet Transform (DWT) can keep ghostly statistics efficiently, however, it will not be able to communicate spatial attributes adequately. Thus, DWT based grouping tactics will not be able to save the striking highlights of input images effectively and present antiques and irregularities in the intertwined outcomes. As of late, a limited Multiscale Geometric Analysis (MGA) instruments were grown, for illustration, Curvelet, Contourlet, NSCT, and so on which don’t experience the ill effects of the issues of wavelet. There are many IF and MIF techniques that work dependent on MGA devices were likewise projected. It is hard for the doctor to analyze the malady from the MRI and CT image independently for the patient. So in our proposed work, the MRI and CT clinical image are converted into a 3-D image for a better finding of the illness influenced part progressively precise and clear.
150 GHz Differential Amplifiers with Lumped-Elements Matching Networks in 55 nm SiGe BiCMOS

This paper presents compact D-band amplifiers in 55 nm SiGe BiCMOS technology. Device models and design tools are first validated with measurements on elementary components above 100 GHz. Then, amplifiers are designed leveraging lumped components in matching networks for minimum area occupation. A differential topology is developed for robustness against parasitic effects of the non-ideal ground, a key issue with lumped components at high frequency. Experimental results are in very good agreement with simulations. The 1-stage amplifier reaches 8 dB gain at 156 GHz and 17.8 GHz bandwidth in 0.026 mm2 silicon area. The 2-stage amplifier displays 17.4 dB gain at 157 GHz with 42.7 GHz bandwidth in 0.048 mm2. Compared to previously reported SiGe amplifiers in similar frequency range, more than 2x core area reduction is demonstrated at comparable gain-bandwidth product.
Calcium phosphate nanoparticles with adjustable dispersability and crystallinity

Approximately spherical calcium phosphate nanoparticles with a diameter of about 50 nm can be prepared by rapid precipitation from water and subsequent colloidal stabilization by coating with polymers (polyvinylpyrrolidone, PVP, and polyethyleneimine, PEI). If they are either washed with isopropanol followed by air-drying, or freeze-dried, they can be easily redispersed in polar organic solvents in colloidal form. High-resolution transmission electron microscopy (HRTEM) and electron diffraction showed that their internal crystallinity depends on the drying method: After freeze-drying, the particles remain amorphous whereas all other drying methods lead to nanocrystalline particles. TEM observations also suggest a disordered surface layer (with a thickness of about 5 nm) of the crystalline particles, consisting of hydroxyapatite and calcium oxide. The presence of calcium oxide was ascribed to a surface layer of calcium carbonate that was formed by precipitation in a hydrated surface layer from atmospheric carbon dioxide and then decarboxylated in the TEM. In conclusion, we show how calcium phosphate nanoparticles can be prepared with defined crystallinity and dispersability while their external size and shape are retained.
Steering Control for Autonomous Vehicle using Model Predictive Controller

In this paper, an effective solution for the steering control system which is indeed an important part to build the autonomous vehicle is presented. A Model Predictive Controller (MPC) is designed to control the steering angle. Vehicle is controlled by varied counting of the steering angles according to the obstacle's position in the lane. The system has obstacle swerving abilities which is supplemented by a LIDAR detector. The proposed setup analyses the space surrounding the vehicle's lane and tracks moving obstacles. The foremost maneuver is to initiate the motive force to quickly move the vehicle to an adjacent lane, drive past the obstacle and move to the initial lane. Other feature incorporated is the Lane Keeping Assist (LKA) system used to detect when the vehicle deviates from the lane and accordingly adjusts the steering angle mechanically. This performance of the controller is evaluated using MATLAB simulations and is implemented on vehicle prototype.
A Transmission-Line-based Phase Shifter for High-Speed, Ultra-Low-Power N-PSK Transmitters

This paper presents a transmission-line-based phase shifter for use in a PSK/APSK ultra-low-power transmitter. In upcoming extreme high-data-rate communications standards, the power consumption of complex digital-to-analog converters will dominate the total power consumption. Therefore, other means have to be found to enable complex modulation schemes while providing high power efficiency. The proposed phase shifter implements a switched delay with only switching transistors and a transmission line, making this a very energy-saving design. It can be applied to any N-PSK modulation with bit depth N by configuring the transmission line length via selecting the appropriate switches. Furthermore, several different modulation depths can be implemented on one chip by using only a set of switches. The design in a 22 nm FDSOI node shows feasibility of the proposed approach with successful QPSK and 8-PSK modulation at 56 GHz and 28 GHz, respectively.
Combining Photoplethysmography and Ballistocardiography to Address Voluntary Head Movements in Heart Rate Monitoring

Daily vital signs monitoring is very important for detecting diseases in early stages and for preventive treatments. Such a task can be achieved by taking advantage of the omnipresence of cameras in people’s personal space. As heart-related diseases are part of the leading causes of deaths worldwide, monitoring heart-related vital signs appear to be very crucial. In this article we aim to provide a touchless approach and propose a robust method for estimating heart rate through analysis of face videos. In particular, we consider a challenging scenario, i.e., the user is on a video call and may often move his/her head. Existing touchless, vision-based methods use either photoplethysmography (PPG) or ballistocardiography (BCG). PPG methods exploit color changes in human skin during heartbeats caused by blood volume variations, but this is very sensitive to unstable lighting conditions. On the other hand, BCG methods exploit subtle head motions caused by Newtonian reaction to blood influx into the head at each heartbeat, thus being sensitive to a subject’s voluntary head movements. Unlike conventional studies where either a PPG method or a BCG method is used, we propose to combine both to overcome the weakness faced by each method. We use BCG methods as the main approach due to their better accuracy on heart rate estimation, and PPG methods are used as the secondary backup to improve the accuracy in cases of large and frequent voluntary head movements. To this end, we introduce a dynamic voting system that effectively combines results of several variants of PPG and BCG methods. Experiments conducted on 20 healthy subjects with different skin tones in different lighting conditions show that our method has better accuracy compared to state-of-the-art methods, well addressing large voluntary head movements. Our method had a mean absolute error of 1.23 beats per minute (BPM) in the cases without voluntary head movements and 2.78 BPM in the cases with voluntary head movements.
A multi-input hybrid converter for small off-grid solar photo-voltaic system

The solar photovoltaic system for standalone applications is growing rapidly due to its compatibility and simplicity of implementation. However, an important barrier to the fast development of solar power systems is the decreased efficiency due to shaded PV arrays. Thus, it is of paramount importance to address the module mismatch loss and partial shading impacts. The new intelligently built buildings contain combined AC and DC loads, also the concept of hybrid nano-grid and micro-grid are in trend. The solar PV systems generates DC power and can supply DC load with the use of DC-DC converter. For supplying the AC loads, DC power must be converted into AC power with the help of DC-AC converter. Conventional solar PV system consist of two stage power conversion, first stage to harvest maximum power by using DC-DC converter and second stage to achieve suitable DC-DC or DC-AC conversion. This article suggests a multi-input single stage hybrid converter which can generate maximum power from solar PV system during normal operating conditions as well as during following conditions like partial shading, module mismatch, and module open circuit conditions and delivers power to AC loads, DC loads simultaneously. The proposed approach has been simulated in Matlab Simulink software for 300 Watt power rating.
A DLL-based Body Bias Generator for Minimum Energy Operation with Independent P-well and N-well Bias

This paper proposes an area- and energy-efficient DLL-based body bias generator (BBG) for minimum energy operation that controls p-well and n-well bias independently so that the BBG can minimize total energy consumption under a skewed process condition between nMOSFETs and pMOSFETs. The proposed BBG is composed of digital cells compatible with cell-based design, which results in low energy consumption and small area. A test circuit is implemented in a 65-nm FDSOI process. Measurement results using a 32-bit RISC processor implemented on the same chip show that the proposed BBG can reduce energy consumption close to a minimum where the amount of excess energy is 3%. In this condition, energy and area overheads of the BBG are 0.2% and 0.12%, respectively.
Diffuse Reflectance Infrared Fourier Transform Spectra of Biofilm-Containing Sediments: Influence of Sample Lyophilization and Drying Temperature

Monitoring of biofilms in sediments formed inside drinking water distribution systems is important due to their destructive activity and their degradation of water quality. The goal of this study was to examine the influence of drying mode and temperature upon sediments containing biofilms using diffuse reflectance infrared Fourier transform spectroscopy. Sediments were collected from sections of potable water pipes and dried at 22, 40, 105 degrees Celsius, or lyophilized. The presence of biofilm residues was demonstrated. Lyophilization of biofilms and drying at temperatures higher than 22 degrees Celsius affected the infrared spectra. The least invasive method involved air-drying of the biofilms at 22 degrees Celsius.
Disparity compensation of light fields for improved efficiency in 4D transform-based encoders

Efficient light field en coders take advantage of the inherent 4D data structures to achieve high compression performance. This is accomplished by exploiting the redundancy of co-located pixels in different sub-aperture images (SAIs) through prediction and/or transform schemes to find a m ore compact representation of the signal. However, in image regions with higher disparity between SAIs, such scheme’s performance tends to decrease, thus reducing the compression efficiency. This paper introduces a reversible pre-processing algorithm for disparity compensation that operates on the SAI domain of light field data. The proposed method contributes to improve the transform efficiency of the encoder, since the disparity-compensated data presents higher correlation between co-located image blocks. The experimental results show significant improvements in the compression performance of 4D light fields, achieving Bjontegaard delta rate gains of about 44% on average for MuLE codec using the 4D discrete cosine transform, when encoding High Density Camera Arrays (HDCA) light field images.
Leaky Wave Fed Substrate Integrated Horn Antenna

Linearly flaring horn antennas typically suffer from low aperture efficiency, especially for large apertures. While spline horns can improve the aperture efficiency, this is at the cost of increased and more complex profile. This paper introduces a novel compact horn antenna fed by leaky waves from the horn arms, which presents a good aperture efficiency and geometrical simplicity. The proposed H-plane high gain horn consists of two leaky-wave waveguides. To demonstrate the idea, two leaky-wave waveguides are implemented in the technology of substrate integrated waveguide (SIW). The horn flaring angle is as large as 110° in this example. By combining the two leaky-wave radiation, a linearly phased wave front is formed. As a result, a high antenna gain of 14.3 dBi at 27 GHz is achieved, with the beamwidth of 6° and side-lobe level of −18 dB. There is no constrains on the horn flaring angles and radiation aperture sizes. This compact leaky-wave SIW horn antenna is very promising for the application as high gain antennas and feed.
Trajectory control of vehicles with a discrete linearized model

Developing of qualitative planning and control systems for self-driving vehicles is one of the most crucial scientific and technical issues. Solution of this issue will allow promoting self-driving technologies to urban areas with critical demands to driving safety, smoothness and efficiency. Here we propose the hybrid approach consisting of planning and control algorithms working together to drive a vehicle through complex environments with uncertainties. For efficient and fast work of this system we provide a vehicle model in a form of discrete transfer functions that are easily integrated into the control process.
Phosphor Based White LED Driver by Taking Advantage on the Remanence Effect

This paper presents the development of a control circuit to enhance the performances of LED lamps. In this direction, a comparison between the luminous intensity of normal LED based lamps and mid-power ones, for both continuous and switching conditions has been made. The already well know control technologies were analyzed and a study was conducted to increase the lighting performances by rising the operating frequency and magnifying the contribution of remanence effect and thus increasing the efficiency of the light source. To achieve this, in the first stage of the project the power and control circuits have been modeled, related to desired parameters and tested in simulation software. In the second stage, the proposed circuit was implemented by functional blocks and in the last stage, tests were made on the circuit and on light sources in order to process the results. The power consumption has been decreased nearly to a half of it and the luminous flux raised with 15% due to overcurrent and remanence effect that we used.