Miracle-dz/UniFAR-FTUs huggingface dataset:
A Camera-Based Approach to Prevent Fingerprint Hacking

Fingerprints is nowadays the most largely used biometric technology for personal identification. With emerging ubiquity of high-definition digital cameras, the risk of fingerprint hacking from photo and video pictures increase. This article discusses the fingerprint hacking problem and presents a new camera-based anti-hacking approach. The technique automatically scans a captured picture for fingerprint images and if found modifies the images to protect the fingerprint information. An experimental evaluation of software prototype shows that it provides robust detection of fingerprints with less than 1sec. delay for 1600x1200 pixel images and almost invisible impact on image quality (less than 1% increase in PSNR).
Design of a Ku-Band High-Purity Transducer for the TM01 Circular Waveguide Mode by Means of T-Type Junctions

A new mode transducer for converting the TE10 rectangular waveguide mode to the TM01 circular waveguide mode is presented. The novel topology is based on two T-type junctions with in-phase excitation at their input rectangular ports. The first one is an H-plane T-junction in rectangular waveguide. The second one differs from the standard E-plane T-junction in the excitation, which is carried out by modes excited with fields having the same in-phase polarization at the input rectangular ports, and has the output port in circular waveguide. This configuration exploits the symmetry of the modes under consideration to achieve a high-purity conversion, controlling the propagating circular waveguide TE11 mode to a maximum level of -42 dB in the whole operation band. The design bandwidth is 2 GHz centered at 12 GHz with a return loss level higher than 28 dB. In addition, the transducer can be divided in a main body plus a cover for easing the manufacturing. In order to verify the proposed geometry, a back-to-back arrangement has been measured connecting two similar aluminum transducers with four different angles between their rectangular ports (0°, 45°, 90°, and 180°). The excellent experimental results validate the novel transducer with a measured converting efficiency higher than 98.2% in a 16.7% relative frequency bandwidth.
A New Compatible Fast Acquisition Algorithm for Parameter-varying Spread Spectrum Signals

Burst spread spectrum signal is one of the main characteristics of Beidou RDSS inbound signals. A new compatible fast acquisition algorithm for parameter-varying spread spectrum signal based on FFT is introduced to process the defects that the traditional fast acquisition algorithm can't process the signals with different synchronization-head length adaptively and compatibly. The new algorithm uses parallel processing to realize adaptive acquisition compatibly for parameter-varying spread spectrum signal according to the actual application feature of different duration signals. Meanwhile, to make the most of optimizing the acquisitive performance of weak signals, use the coherent accumulation to improve the signal-to-noise ratio and use time-frequency parallel processing to improve processing efficiency. At last, it is proved that the method can fast acquire different spread spectrum signals by the simulation experiment.
Batch Look Ahead Orthogonal Matching Pursuit

Compressed sensing (CS) is a sampling paradigm that enables sampling signals at sub Nyquist rates by exploiting the sparse nature of signals. One of the main concerns in CS is the reconstruction of the signal after sampling. Many reconstruction algorithms have been proposed in the literature for the recovery of the sparse signals - Basis Pursuit, Orthogonal Matching Pursuit (OMP), Look Ahead Orthogonal Matching Pursuit (LAOMP) are some of the popular reconstruction algorithms. LAOMP, a modification of OMP, improves the reconstruction accuracy of OMP by employing a look ahead procedure. But LAOMP suffers from the drawback of being very expensive in terms of the computational time. In this paper we propose a modified version of the LAOMP algorithm called Batch-LAOMP which has a lesser computational complexity and also gives better performance in terms of reconstruction accuracy as seen from the results of the numerical experiments.
Development of a Personal Life Guard for Swimmers

By using the latest technology in the IoT field we have managed to build a Personal Life Guard for Swimmers which can track by GPS the coordinates of the user and alert the lifeguards if that person is in danger. By using LiPo batteries cells in combination with software component, we can save the battery life and send distress signals up to 7 days due to the low-power consumption of the LoRa and GPS modules (under 35mA). In order to fit all the electronics modules in one water tight enclosure, we had do develop custom electronics board (PCB) and custom mechanical parts using 3D printing. This project is intended to improve the safety of the swimmers across the Black Sea shores, bringing us one step closer to the concept of Smart Cities and, by the research and development done in this project, to highlight the key steps for developing a IoT network with all its components and features, testing the limits and capabilities of both terminal components of the network and the gateways which translate the LoRa messages into packets for sending them across Ethernet to a base server for data analysis.
Emotional State Sensing by Using Hybrid Multivariate Empirical Mode Decomposition and Synchrosqueezing Transform

In recent years, utilizing Hilbert-based time- frequency methods in emotional state sensing research attracted attention in the brain computer interfaces. Primarily, Hilbert Transform-based empirical mode decomposition (EMD) was found to be suitable for emotional state modeling studies. In more recent studies, models of emotional state recognition were proposed in which the classification was implemented by using the features obtained after applying the time, frequency, and time-frequency domain methods to intrinsic mode functions achieved by operating EMD. In this study, an analysis of emotional state recognition is proposed by using the features of the synchrosqueezing coefficients obtained in the classification process after applying the Synchrosqueezing Transform to intrinsic mode functions achieved by using Multivariate EMD. As a result, EEG data available in the DEAP database were categorized as low and high for valence, activation, and dominance dimensions, and 4 different classifiers were utilized in the classification process. The most satisfying ratios of valence, activation and dominance were attained 76%, 68%, and 68% respectively.
A Kinetic Monte Carlo Simulator to Characterize Resistive Switching and Charge Conduction in Ni/HfO2/Si RRAMs

A 3D kinetic Monte Carlo (kMC) simulation tool has been developed to study the resistive switching (RS) processes that allow Ni/HfO2/Si devices to work as non-volatile memories. The simulator is tuned with numerous experimental data and it can reproduce the device current in forming, set and reset processes, the cycle-to-cycle variability and other characteristics linked to the stochasticity of RS operation. The evolution of conductive filaments (CFs) for different RS cycles is analyzed in depth, as well as the filaments density and resistance.
Energy and Execution Time Comparison of Optical Flow Algorithms on SIMD and GPU Architectures

This article presents and compares optimized implementations of two optical flow algorithms on several target boards comprising multi-core SIMD processors and GPUs. The two algorithms are Horn-Schunck (HS) and TV-L1, and have been chosen because they are both well-known, and because of their different computational complexity and accuracy. For both algorithms, we have made parallel optimized SIMD implementations, while HS has also been implemented on GPUs. For each algorithm, the comparison between the different versions and target boards is carried out in a two-dimensional fashion: in terms of computing speed-in order to achieve real-time computation-and in terms of energy consumption since we target embedded systems. The results show that for HS, the GPUs are the most efficient in both dimensions, able to process in realtime performances (25 frames per second) up to 8Mpix images for 0.35J per image, against 1.8Mpix images for 0.24J per image on CPU. The results also highlight the impact of optimizations on TV-L1: far slower than HS without optimization, it can almost match its performance after optimization on CPU, and can achieve real-time performances with 0.25J for 1.4Mpix images. We hope these results will help developers design optical flow embedded systems.
WT-Based Data-Length-Variation Technique for Fast Heart Rate Detection

The traditional Fourier transform has a short-term window effect when using the bio-radar to extract vital signs parameters such as respiratory and heartbeat. The wavelet transform (WT) can separate the respiratory signal and heartbeat signal accurately. Though meanwhile, it's difficult for fast heart rate detection when using non-contact continuous-wave radar. More importantly, respiratory harmonic peak might be incorrectly picked as the heartbeat signal if its magnitude is larger than the heartbeat peak in frequency spectrum. An effective data-length-variation technique is proposed in this paper to detect heartbeat signal quickly and accurately. At the same time, respiratory harmonic is depressed with this technique. This technique is verified through actual measurement by the pulse radar system using the Meyer wavelet. Compared with the existing technique, the accuracy is higher and the average error of heatbeat is reduced obviously using 4-6-s length of data compared with the traditional Fourier transform.
Predicting Anchor Links Based on a Supervised Iterative Framework with Strict Stable Matching

Nowadays, more and more people have their own accounts in different social networks, and they might use the different email addresses or phone numbers in different networks, so how to identify the same person among different social networks become a vital problem, called network alignment. Users with different accounts are called anchor users, researches showed that using some known anchor users to predict the potential anchor links for the full network is an effective way. To predict more accurate anchor links, the paper proposes a new prediction framework ISS, based on a reality of partially aligned social networks, it applies supervised learning based on social feature extraction and strict stable matching, which improve the accuracy of the prediction result, what is more, we apply an iterative framework to refine known information and maximize the prediction results. Experiments have conducted in two realworld heterogeneous social networks, Foursquare and Twitter, and it demonstrates that ISS can predict anchor links among heterogeneous social networks very well and outperform other similar prediction methods.
Robust Beamforming Design for Secure DM-Based Relay Networks With Self-Sustained Jammers

In this paper, we propose to use self-sustained jammers to generate artificial noise with the aim of enhancing the physical layer security of a directional modulation (DM) relay system. To this end, we specifically tackle an optimization problem of designing beamforming vectors at the source, relay, and jammers to maximize a lower bound on the average secrecy rate of the considered system. Due to that the optimization problem is non-convex and the optimization variables are coupled, and so we cannot directly solve this problem. As such, we first develop a centralized scheme to achieve the near-optimal beamforming vectors with the aid of semidefinite relaxation, successive convex approximation, and an alternating iterative algorithm. The tightness of the incurred relaxation and the convergence of the involved algorithm are proved. To reduce the overhead and complexity of the centralized scheme, we also develop two decentralized schemes with partial cooperation and without cooperation among devices to obtain suboptimal beamforming vectors. Our examination shows that the developed centralized scheme can achieve similar performance as the optimal beamforming vectors, which can only be obtained through exhaustive numerical search. Our examination also specifies the conditions under which the decentralized schemes can achieve similar or significantly worse performance relative to the centralized scheme. Furthermore, our examination demonstrates that the developed three schemes are robust to the angle estimation errors in practical DM systems.
A Novel Feature for Nasalised Vowels and Characteristic Analysis of Nasal Filter

Nasal tract is an important part of our vocal tract system. It provides major impact for production of nasalised and hypernasal speech. Despite it's huge importance, the effect of nasal tract is not yet largely studied. This work is done with a motivation that, understanding characteristics of nasalised vowels and nasal filter will help in detecting nasalised speech. We have designed a device to separate nasal murmur from oral speech, when nasalised speech is spoken. In this work we have analysed speech data collected from different speakers. Firstly we have analysed nasalised vowels and found a novel feature for nasalised vowels. Then, various signal processing techniques are used to analyse the variability of nasal filter for different nasalised vowels. It is found that the nasal filter, which is the reason for nasalisation of vowels, is invariant across different nasalised vowels. Nasalised speech are produced when the nasal tract gets coupled with vocal tract. When the effect of coupling is experimented from a signal processing point of view, we found that it has an effect of addition.
Repeat-pass SAR Interferometry Experiments with Gaofen-3: A Case Study of Ningbo and Nanjing Area

This paper illustrates the repeat-pass interferometric SAR (InSAR) results of Gaofen-3 (GF-3), a Chinese civil SAR satellite. The SAR images are acquired in November 2016 and March 2017 from Ningbo and Nanjing area, particularly, the images in Nanjing area are the first meter degree interferometric pair. With the spatial baseline about 600 m and time baseline 116 days, the coherence of the most urban areas still achieves good enough to generate the digital elevation model (DEM), whereas for the mountain areas, the decoherence phenomenon is serious. During the InSAR processing, we compared several baseline estimating methods and obtained a good flat-earth phase removed interferogram map. By using the latest SAR interferogram filter and phase unwrapping method we proposed, we improved the coherence up to 0.8 in urban area. To reduce the spread unwrapped phase errors coursed by low coherence area, we partitioned the unwrapped phase map and calibrated the baseline and phase offset parameters based on the partitioned image. Then the DEM of high coherence areas were retrieved in each block, and for low coherence areas, the existing DEM auxiliary method was used. In addition, after the orthorectification, we evaluated the elevation model by comparing with the elevation values extracted from SRTM and field measured GPS elevation. And the result shows that accuracy of the elevation map is about 10 m (RMSE) in most of the studied region.
An Implementation of Cable Resistance in Modified Droop Control Method for Parallel-connected DC-DC Boost Converters

For load current sharing between parallel-connected DC-DC boost converters, a modified droop method with varying cable resistance is presented in this paper. The droop method provides a suitable current sharing in the system because there is no intercommunication link between the parallel-connected modules. However, when the cable resistance is considered, a small mismatch in output voltage of parallel-connected converters leads to circulating current and unequal load current sharing between two modules. To resolve this issue without using a communication link between modules, the modified droop method based on cable resistance implementation is proposed to improve the load current sharing. This can be established by adjusting the output voltage for each converter of the parallel-connected converters individually and according to modified load regulation characteristic of the droop method. The effectiveness of the proposed method is demonstrated using Matlab/Simulink simulations.
A Genetic Algorithm for Designing Uncoded Space-Time Labelling Diversity Mappers

The extent to which Uncoded Space-Time Labelling Diversity is able to improve the error performance of space-time block coded (STBC) systems is dependent on the binary mappers used to encode information. Existing design techniques are limited; as they either rely on symmetry-based heuristics, or constrain the size of the constellation due to high computational costs. This paper proposes a new genetic algorithm for labelling diversity (LD) mapper design which is applicable to constellations of any shape or size. The proposed algorithm is tested using 16QAM, 64QAM, 32PSK and three 16APSK constellations that do not display diagonal symmetry. The proposed LD mappers match the best heuristic designs for 16QAM and 64QAM. The 32PSK LD mapper produced achieves a diversity gain of ≈8dB when compared to the available heuristic-based LD mapper. In addition, the 16APSK mappers achieve a diversity gain of approximately 3 to 8dB compared to Alamouti-coded STBC systems for the three non-symmetric constellations considered.
Evaluation of Received Signal Power in On-Body Dynamic Channel Considering Human Walking Motion

This paper presents the evaluation of the received signal power in an on-body dynamic channel considering human walking motion. On the basis of statistical data, a human walking model is derived, while the simulation of the received signal power of the ankle-wrist channel is carried out. It is confirmed that the received power of the on-body channel degrades significantly because of the geometrical locations and polarization characteristics of transmitting and receiving antennas.
MLB+-tree: A Multi-level B+-tree Index for Multidimensional Range Query on Seismic Data

Seismic processing is an important technology in petroleum industry. Processing results are usually observed and analyzed by petroleum scientists via interactive applications. In these applications, multidimensional range queries are frequently executed to fetch the data that users are interested in. The traditional B+-tree index does not work well for these queries because considerable index data has to be scanned from storage devices during the query execution. In this paper, we present MLB +-tree, a multi-level B+-tree index to accelerate multidimensional range queries on seismic data. Thinner index slices will be accessed by using MLB +-tree and query latency is reduced accordingly. An adaptive index selection method is also introduced to find the best index for various queries. Our experiments show that MLB +-tree outperforms B+-tree in most multidimensional range queries on different datasets. Since most queries are ad-hoc, fast index construction is desirable in seismic processing. To cope with this problem, we present a distributed index construction algorithm based on the map-reduce programming model. Our implementation of this index construction algorithm gains approximately linear speedup on a 64-nodes high-performance cluster in our experiment.
Flexible Artificial Magnetic Conductor Reflector for Wearable Antenna Application

Wearable communication systems required high performance, compact and flexible antenna devices. In this paper, a flexible artificial magnetic conductor (AMC) reflector is designed using square patch array for wearable antenna application at the Industrial, Scientific and Medical (ISM) frequency of 2.45 GHz. The proposed AMC reflector is composed of 3 × 3 squares patches with concentric slots to gain the wide bandwidth response. A flexible dielectric material of RO3003@ from Rogers Corporation with the relative permittivity of 3.0 and the thickness of 0.5 mm is used as a dielectric substrate for the reflector deployment as well as for the wearable antenna. The characterization results show that the integration of flexible AMC reflector with a wearable antenna has improved radiation characteristic and gain of the antenna. The results indicate that the proposed flexible AMC reflector has the feasibility for performance enhancement of wearable antenna especially in wireless body area network (WBAN) communications.
An Architecture for Dynamic Context Recognition in an Autonomous Driving Testing Environment

The Internet of Things (IoT) envisions billions of connected objects being able to sense, act and communicate with each other. This situation provides rich opportunities to dynamic context recognition mechanisms, which aim to make use of the connected sensors to recognize desired context information. However, there are still several challenges to solve for dynamic context recognition mechanisms to be implemented. One of those challenges is dynamic resource selection, the ability to dynamically select between different data sources to detect a specific type of information and to adapt this selection, when necessary. In this paper, we present an agent-based architecture to combine event-driven Service-Oriented Architecture (SOA) with a data streaming platform to enable dynamic context recognition. The architecture has been defined in the scope of a testing environment for autonomous driving. There, it is used to dynamically select data sources to provide information to autonomous vehicles and applications based on them.
A Probabilistic Perspective for Power Flow and Its Implication to Power Network Analysis

The interpretation of power flows from a probabilistic perspective is an important topic in the development algorithms of complex network theory for power system analysis, as it is conceived as the theoretical foundation for many new techniques such as machine learning and artificial intelligence. In this paper, we first show that power flow can be mathematically represented as the equilibrium of probabilistic energy movements on a graph. We demonstrate that such an equilibrium can be reached if the energy movements follow the commonly known random process of Markov chains. This work advances the current state of the art by showing a way that connects the power flow models and the random walk models of complex networks. Moreover, several new insights on the electrical betweenness centrality measures used in power grid vulnerability analysis are presented from this new probabilistic perspective.
Energy and Spectral Efficient Tradeoff for Massive MIMO Enabled Heterogenous Networks with Wireless Backhaul

In this paper, we provide a general framework to investigate the tradeoff between spectral efficiency (SE) and energy efficiency (EE) in massive multiple input multiple output (MIMO) enabled heterogeneous networks (HetNets) with wireless backhaul. Our target is to optimize joint beamforming and power allocation to maximize SE and EE simultaneously, so we formulate it as a multi-objective optimization problem. Based on the weighted Tchebycheff method, we transform the multi-objective optimization problem into a single-objective optimization problem with involving quality of service (QoS) in terms of the minimum rate constraints of each user, the interferences between intra-cell and inter-cell, and capacity-limited wireless backhaul. Since the problem is not convex, we provide a novel iterative algorithm that is a combination of successive convex approximation (SCA) and alternating optimization (AO) to solve it effectively. Both theoretical analysis and numerical results demonstrate that the proposed algorithm can fast converge and the EE-SE tradeoff performance is superior over existing power allocation algorithm.