Miracle-dz/UniFAR-FTUs huggingface dataset:
Iterative Processing Structure for the Single-Channel Mixture of Digital-Modulated Adjacent-Frequency Source Signals

Considering the high cost and complexity of multiple-channel blind source separation, single-channel solutions have elicited a significant amount of interest in source separation. Joint maximum likelihood sequence estimation implemented by the Viterbi algorithm (VA) is a seemingly ultimate solution to the problem of data transmission over dispersive channels. However, both joint reduced-state sequence estimation (JRSSE) and joint delayed-decision feedback sequence estimation (JDDFSE) have numerous shortcomings when applied to single-channel blind signal separation. Hence, joint double-direction DDFSE (JDD-DDFSE) is proposed in this article. JDD-DDFSE employs joint VA (JVA) of the low-order channel twice. The estimated symbols from the initial JVA are utilized to equalize the causal and non-causal taps of the channel beyond the trellis state in the second JVA. A method that can derive the log likelihood ratio of the estimated symbols is provided; the complexity of this method is considerably lower than that of soft-output VA or the BCJR algorithm. Hence, the entire computation complexity of the iterative separation structure basically remains unchanged compared with that of the no-iteration structure. For the non-causal channel, the proposed algorithm has the lowest computation complexity and demonstrates a separation performance similar to that of conventional JVA, JRSSE, and JDDFSE algorithms.
An FPGA Accelerator for Embedded Microcontrollers Implementing a Ternarized Backpropagation Algorithm

To better utilize artificial intelligence (AI) in the edge domain, such that it is more attractive and fruitful, the development of low-power and -resource AI devices dedicated to online learning is very important issue to be solved. We proposed new ternarized backpropagation (TBP) algorithms [1] and verified to be favorably compatible with fixed-point 16 bit backpropagation (FixedBP). In this paper, we present our implementation method of TBP on an FPGA as an accelerator for embedded microcontrollers, and evaluate the TBP on the FPGA to achieve a 15.7 % reduction of the logic elements of the FPGA, 12.3 % reduction of the registers, 90.9 % reduction of the multipliers, and 49.8 % reduction of the SRAM usage, comparing with those for the FixedBP. We verify its capabilities for training MNIST classification task with a mini-batch size of one. In addition, we demonstrate image recognition system as application example.
An Improved Differential Evolution Algorithm for Operating Optimization of a Distillation Unit

This paper studies a challenging optimization problem of operating variables for a distillation unit (DU) widely used in oil refineries. The problem aims to optimize the operating variables when a new environment (e.g., the feedstock properties change) arises. We first establish the operation optimization model of the DU. Subsequently, we propose an improved differential evolution (IDE) algorithm that meets the problem characteristics to solve this optimization problem. In the IDE algorithm, a mutation operator is used to obtain a mutant individual (also called mutant vector), and an adaptive scheme is proposed to update the scaling factor used in the mutation strategy to balance the exploitation and exploration capabilities of the algorithm. We introduce an effective strategy to correct infeasible operating variables in the mutant vector to improve the optimization efficiency of the algorithm. Experiments show the superiority of the IDE algorithm compared to other algorithms.
Optimum Switching Angles for Multilevel Inverter for Minimization of THD

Power Electronic Converters are essential units for the utilization of non-conventional and green energy sources such as PV Cells. The quality of output from the power converters is the major concern for the designers and users. This paper focuses on the reduction of total harmonic distortion (THD) which indicates the enhancement of power quality. Total Harmonic Distortion (THD) can be minimized by generating the switching signal to the active devices for level transition in multilevel inverters using digital controllers at pre-calculated optimum switching instants (angles). This paper gives the strategy of computing the optimum switching time instants for reducing THD. The Simulation of a Hybrid multilevel inverter of nineteen level output using only twelve active switches in MATLAB/Simulink using pre-calculated switching instants is presented in this paper.
Molecular Dynamics Study on Mechanical Properties of Nanocrystalline tantalum

The study of nanocrystalline(NC) polycrystals is a hot topic, and the study of nanomaterial properties by molecular dynamics has become the first choice for many researchers. The purpose of this paper is to simulate the tensile tests of single and polycrystalline tantalum by molecular dynamics(MD) to obtain its mechanical properties. Firstly, the Ravelo-EAM potential was used to conduct tensile tests on tantalum in the <100> direction. Secondly, it can be seen that the elastic modulus E100 decreases with the temperature gradually increases from 1 K to 1500 K according to the simulation results. Finally, the Hall-Petch(H-P) effect based on grain size is verified from the tensile test of polycrystalline tantalum.
Pedestrian Presence Detection System Based on Image Processing

The study presents a methodology for detection of pedestrian presence at road crossings. It is based on image processing and a recognition background pattern. For each camera image is applied a filter in order to exclude pedestrians outside the waiting enclosure from affecting the system’s decisions. Next, the object is converted to black and white format and is divided into sections. Each section is compared with the corresponding section from the recognition pattern pixel-by-pixel. The relative error between the two images is then compared to a critical value, and a decision is made. The analysis of the images by sections reduces the influence of potential vibrations, thus significantly increasing the probability for correct recognitions.
Phase Tracking Algorithm of IEEE 802.15.4g MR-OFDM with Frequency Offset

IEEE 802.15. 4g Standard specifies multi-rate and multi-regional orthogonal frequency division multiplexing (MR-OFDM) physical layer, which supports principally outdoor, low-data-rate, wireless, smart metering utility network (SUN). The inter-channel interference (ICI) results in subcarrier frequency sampling offset and phase shift for signal on MR-OFDM. In this paper, phase tracking algorithms which estimate and compensate the offset on symbols are studied. A basic phase tracking method is presented that the phase rotation of reception signal can be recognized by using the data on the pilot tones. Furthermore, in order to mitigation the influence of noise, an average-based algorithm is proposed as a modified solution. In contrast with the basic method, the average-based algorithm enhances the reliability of phase tracking. Simulations of algorithms are assessed, which are in accordance with theoretical analysis.
Precise Point Set Registration Algorithm for Indoor Scene Reconstruction

In this paper, we propose a precise point set registration algorithm for indoor scene reconstruction. Firstly, as for the problem that sensor samples unevenly, point-to-plane metric is introduced into our model, which effectively makes use of the surface structure information of point set and improves registration result. Secondly, to handle with noises and outliers in indoor scene, correntropy is introduced. To solve our model, we propose a variant of Iterative Closest Point (ICP) algorithm, which iteratively establishes point-to-point correspondence and calculates rigid transformation parameters. After that, the simulated experiments demonstrate the accuracy and robustness of the proposed algorithm compared with other methods. Besides, it is also used to indoor scene reconstruction and the result is satisfying.
Dependence of Unsupervised and Supervised Segment of Three Dimensional Medical Images on Clustering and Deep Learning Formation

The purpose of this paper is to gift a completely unique unattended phase technique for3 Dimensionalmedical pictures. Complex blue brain technology (CNNs) has lead to a great improvement in image dimensions. But, the most recent technology works on administered instructions, requiring huge\1amount of manually interpreted data. Thus, it has become really difficult to decrypt the difficult medical reports. The main proposes paper a unique approach to deep learning and knots for segmentation. Our decision structure consists of 2 coordinates. In the first, we tend to deep study merits represent of coaching spots from a target pictures victim joint knot learning (JULE) that corresponding\1spots representations created by a CNN and updates and measures the CNN framework using knot labels as super ordinate signals. It tend to further extended JULE to three dimensional medical report by using three dimensional convolutions surround the CNN unique style. In\1second section, it tend to use k-means to the deep represents from the fully trained CNN\1project cluster labels to the destination picture so as to get the fully segmental image. We evaluated our ways in which on three footage of malignant neo plastic disease patterns scanned with microcomputed diagrammatical representation (microtechnology). The self-starting carving of medicinal regions in micro-technology would possibly a lot of subsidize to the carving evaluation technique. our tend to aim to mechanically allot every and every pictures into the zone of invasive malignant neo plastic disease, non-invasive malignant neo plastic disease, and traditional trim. Our experiments show improvement of required skills for deep learning of medical images lineup.
The Hard Side of Business and IT Alignment

Despite the critical importance of achieving business and IT alignment in organizations, its practical operationalization at the level of specific actors, decisions, and documents still remains rather shadowy. This paper explains the operationalization of alignment as a pipeline with five distinct decision-making phases: positioning, focusing, prioritizing, assessing, and implementing.
Blockchain Enabled Trust-Based Location Privacy Protection Scheme in VANET

While enjoying the convenience brought by Location Based Service (LBS), the location privacy of vehicles in VANET may be disclosed. Distributed k-anonymity, as one of the most popular privacy protection methods, fails to take the trustworthiness of participants into account, resulting in malicious tracing of vehicles, which further leads to the sensitive information leakage, and even the safety threat of personal property. To address this issue, we propose a blockchain enabled trust-based location privacy protection scheme in VANET. Specifically, by analyzing the different requirements of the request vehicle and the cooperative vehicle during the process of constructing the anonymous cloaking region, as well as combining the characteristics of these two roles, we devise the trust management method based on Dirichlet distribution, such that both the requester and the cooperator will only cooperate with the vehicles they trust. Moreover, by employing blockchain, we also proposed the data structure to record the trustworthiness of vehicles on publicly available blocks timely, so that any vehicle can access the historical trust information of counterparties whenever necessary. Finally, the construction process of anonymous cloaking region is presented. Security analysis and extensive experiments indicate that the proposal is resilient to various trust model attacks, it can effectively detect the malicious vehicles, and preserve the location privacy of vehicles in the anonymous cloaking region construction, while the required time delay is limited.
Design and Experimental Demonstration of Compact Polarization Reconfigurable Antennas

Two compact polarization reconfigurable antennas are presented. The first is an electrically small, low-profile, planar, Huygens source antenna with four reconfigurable polarization states. It has very useful realized gain values in its broadside direction, symmetric radiation patterns, and low back radiation in all four polarization states. The second is a compact, wideband, planar tri-polarization reconfigurable filtenna. It exhibits a wide impedance bandwidth, stable realized gain, and good out-of-band rejection performance for all three of its reconfigurable states. Both of these compact polarization reconfigurable antennas were fabricated and tested. The measured results, in good agreement with their simulated values, demonstrate their efficacy to reconfigure their polarization states.
A High Level Synthesis Approach for Application Specific DMA Controllers

In this paper, we propose a method to generate an application specific DMAC between a DFM and DRAM by utilizing HLS on an FPGA. Using this approach, DFM application developers can design DMAC corresponds to various memory access patterns according to each application with reducing a design burden. To address the feasibility of this approach, we discuss performance evaluation with empirical experiments.
A Geometric Positioning Method of Mine TOA based on Improved Kalman Filter and Parameter Fitting

As a large number of equipment existed in the mine roadway, non-line of sight (NLOS) delay of electromagnetic wave propagation will have an adverse impact on the positioning accuracy of time of arrival (TOA) of the mine, which cannot meet the problems of underground emergency rescue, personnel operation management and the construction of mine Internet of things. According to the formation of NLOS, the propagation delay of electromagnetic wave NLOS in roadway is divided into random NLOS delay and fixed NLOS delay. Combined with the characteristics of ranging error caused by the two types of NLOS delay, a geometric positioning method of mine TOA based on improved kalman filter and parameter fitting is proposed. Firstly, the symmetrical double-sided two way ranging (SDS-TWR) is adopted to eliminate the influence of synchronization delay and timing error on TOA positioning accuracy. Then the improved kalman filter algorithm is used to filter the random NLOS delay error of roadway. Finally, parameter fitting and projection geometry algorithm are used to improve the positioning accuracy of the system. The simulation results show that the proposed method has a significant inhibiting effect on TOA positioning error and can realize the effective application of TOA method in NLOS environment of mine.
Fair Use of Collected Energy for Relay Selection Strategy

For the energy bottleneck introduced by the randomness of relay node energy collection in wireless energy harvesting cooperative communication system, a relay selection method considering the energy consumption fairness (RS-ECF) of relay nodes was proposed. In the method, the energy consumption ratio of each relay node is maintained equal, thereby determining the transmission power of the relay node. The simulation results show that the proposed method can not only improve the average channel capacity of the system, but also improve the energy utilization efficiency. Meanwhile, the relay power is also determined by the relay selection, which can save the computing resources of the system.
Fabrication-as-a-Service: A Web-Based Solution for STEM Education Using Internet of Things

Recently, fabrication laboratories (Fab Labs) have been shown to have a great impact on learners’ academic and personal progress. As a result, an increasing effort is being put to integrate Fab Labs into schools’ curricula. Yet, owing to the high cost of setting up and maintaining Fab Labs as well as the lack of sufficient funding for most schools and universities, only a limited number of institutions can afford them. In this article, we propose a new concept called Fabrication-as-a-Service (FaaS) that uses Internet of Things to democratize access to Fab Labs via enabling a wide learning community to remotely access these computer-controlled tools and equipment over the Internet. It employs a two-tier architecture consisting of a hub, deployed in the cloud, and a network of distributed Fab Labs. Each Fab Lab interacts with the hub and other digital labs via a Fab Lab Gateway. This is to support scalability and high availability of fabrication services as well as ensure the system’s security. FaaS also adopts an innovative master–slave approach that uses inexpensive external hardware to monitor and control the activity of expensive fabrication equipment. This article also describes the FaaS deployment in the context of the European Union Horizon 2020 NEWTON project. Multiple scenarios have been deployed to fully illustrate the benefits of the FaaS architecture and to assess the performance of its communication protocol stack.
Attacks, Countermeasures and Security Paradigms in IoT

IoT is reaching new heights at a rapid pace but it has many vulnerabilities so it is important to discuss them. Various technological advancements have taken place because of IoT in the fields such as transport, commerce and healthcare. Various characteristics of IoT have been discussed in this paper such as Intelligence, large scale, sensing, unique identification, dynamic environment, heterogeneity, connectivity, self-configuring and authenticity. Security requirements in IoT have also been discussed in the paper. In order to secure the ML model, various security paradigms are discussed in this paper such as Bluetooth Low Energy Security, Firewalls, Datagram Transport Layer (DTLS) Security, etc.
Recent Progress in the Development of CORC Cable-In-Conduit Conductors

In recent years, three unique ReBCO-CORC CICC samples with six-around-one cable layout were developed as technology demonstrators at CERN in collaboration with Advanced Conductor Technologies. The tests of these conductors at low temperature in external magnetic field yielded very promising results, but also showed several issues requiring improvement. A new 2.8 m long CORC CICC has been prepared to replace a degraded sample. The voids between CORC strands in the new sample are filled with solder alloy to provide increased mechanical support to the strands, however, this yielded an additional set of new challenges. The conductor has a design critical current of 100 kA at 10 T and 4.5 K and is designed specifically for high-current bus-bars and large detector-type magnets. It therefore features a copper jacket and practical conduction cooling via a cooling line embedded in the jacket.
Distributed Model Predictive Control Based Formation Tracking For Differential Drive Robots

This paper presents a two-layer distributed Non-Linear Model predictive control (NLMPC) scheme for the formation tracking of the differential drive robots which also provides obstacle avoidance. The first layer of the control architecture is concerned about the generation of reference trajectories for the leader and the followers satisfying the formation constraints. In the second layer, a distributed NLMPC is implemented for tracking the reference trajectory from the first layer. In order to make it robust, a disturbance observer is integrated with the NLMPC.
Semi-Direct Visual Odometry Based on Monocular Depth Estimation

Among various visual sensors used in various visual odometry methods, monocular cameras are more suitable for small mobile platforms due to their low costs, light weights and low power consumptions. However, the depth of the scene cannot be measured by monocular camera so all kinds of monocular visual odometry or SLAM algorithms inevitably have the defect of scale ambiguity, which greatly limits their application in real world. To solve the above problems, a semi-direct visual odometry algorithm based on monocular depth estimation is proposed in this paper, we add a monocular depth estimation module into the semi-direct visual odometry, which provides good initial values to the depth filter. In this way, the inherent defect of scale ambiguity is overcome, and the accuracy and robustness of monocular visual odometry are improved.
Research on Learning Method Based on Hierarchical Decomposition

The most impressive aspect of human intelligence is skill acquisition—identifying important behavioral components, retaining them as skills, refining them through practice, and applying them in new tasks. In the field of artificial intelligence, the representation and learning of such hierarchical skills are significant open problems. In this paper, we introduce the important applications of hierarchical learning, and the related models and methods of hierarchical learning, as well as problems and solutions encountered in the process of hierarchical learning.
Space Vector PWM Scheme for Three Phase Three Level T-type NPC Inverter

Multi-level inverters (MLI) have been widely used for dc to ac power conversion for different applications. Different PWM methods are used to control the multilevel inverters. Among various PWM methods, space vector pulse width modulation (SVPWM) is the superior method. As the number of level increases, the execution of space vector modulation (SVPWM) for multilevel inverters is difficult. In this paper a basic space vector modulation scheme is applied to three phase three level T-type NPC in which dwell time calculation is done for one sector only, and same can be mapped for other sectors. Simulation and experimental results are presented for performance validation.
Triple Beam Design of a Novel Radial Gap Waveguide Slot Antenna Array

In this paper, a triple beam slot antenna array operating at X-band is proposed. The corporate-feed slot antenna is based on a radial ridge gap waveguide (RGW) power divider, and is excited by a central coaxial connector. Compared with the traditional slot antenna array, the proposed antenna array is capable of generating any number of beams, especially odd beams. Furthermore, each beam can be individually modulated.
Free Space Optical Communication and Laser Beam Propagation through Turbulent Atmosphere: A Brief Survey

In this survey paper, a brief survey has been performed about the free space optical communication (FSO), which has emerged as an innovative hot topic in the field of research. This paper inspected about the features and challenges faced by FSO communication. Here, it is focused about atmospheric turbulence, one of the main challenge FSO has to encounter during the propagation of laser beams through free space. The survey has also been undergone regarding the various modulation schemes, and various laser optical beam profile that can be used in FSO as optical source of propagation. The analysed techniques employed for the process of modulation are Amplitude shift keying(ASK), Binary phase shift keying(BPSK), Quadrature phase shift keying(QPSK), Pulse position modulation(PPM), Pulse amplitude modulation(PAM), Pulse width modulation(PWM). Also, investigated about the effect of different types of aberrations such a tilt, astigmatism, coma, and spherical aberrations present in a turbulent atmosphere on different laser beam profiles such as Bessel Gaussian (BG) beam, Laguerre-Gaussian (LG) beam, Hermite-Gaussian (HG) beam, Helical beam.