Miracle-dz/UniFAR-FTUs huggingface dataset:
Channelized-Based Denoising Generalized Orthogonal Matching Pursuit for Reconstructing Structural Sparse Signal Under Noise Background

This paper proposed a channelized-based denoising generalized orthogonal matching pursuit algorithm (gOMP) for reconstructing structural sparse signal in engineering application. The algorithm combines the compressive sensing channelization method, the pre-estimation-based adaptive method with the gOMP. By channelizing the observation matrix, the algorithm first eliminates most of the channels that only contain noise with a residual-based detection method. Then, according to a pre-estimated sparsity level, the signal can be accurately and adaptively reconstructed by re-screening the redundant support obtained by the gOMP. The two steps of the algorithm effectively reduce the deterioration of the reconstruction caused by noise, thereby significantly improving the output signal-to-noise ratio (SNR). A mathematical derivation of the reconstruction conditions is given. Also, the computational complexity and the theoretical SNR improvement are discussed. Besides, the upper bound of the reconstruction error in the noise environment is mathematically analyzed. Finally, the experiments verified the performance analysis and detailedly demonstrated the advantages of the proposed algorithm for recovering structural sparsity signals under noise interference. The results show that the proposed scheme considerably outperforms any existing adaptive and denoising greedy algorithm in the sense of the reconstruction accuracy and the output SNR.
Single-image Dehazing Algorithm Based on Convolutional Neural Networks

The paper proposes a new single image dehazing method based on a convolutional neural network. Our method directly learns an end to end mapping between the haze images and their corresponding haze layers (i.e. residual images between haze images and non-haze images). A convolutional neural network takes the haze image as an input and the residual image as an output. Then, a recovered dehazed image can be obtained by removing the residual from the haze image. Residual learning allows the network to directly estimate the initial haze layer with relatively high learning rates, which reduce computational complexity and speed-up the convergence process. Since the initial haze layer is only approximate, we use a guided filter to refine this layer to avoid halos and block artefacts, which makes the recovered image more similar to a real scene. The algorithms are tested on fog images with different fog densities. Comparisons are provided with other dehazing algorithms. Experiments demonstrate that the proposed algorithm outperforms state-of-the-art methods on both synthetic and real-world images, qualitatively and quantitatively.
Hybrid Path Planner for Efficient Navigation in Urban Road Networks through Analysis of Trajectory Traces

Computing optimal routes in a road network is both space and time-consuming. This paper proposes an innovative way of finding a route, given the traffic conditions of every edge present in the map. This article aims to bring about a convergence between methods used in routing data over a network and path planning used in AI technique. It makes use of certain concepts of network routing tables in order to develop path planners suitable for urban conditions. It also has a linear space complexity.
IoT Based System for Passenger Service in Railways with Secure ICN Architecture

The project is about to implement Internet of Things (IoT) technology in Railways. Goal is to constitute a secure IoT system by using Information Centric Networking (ICN) architecture to comprehend the key requirements of IoT system. The proposed system is based on ICN architecture. ICN is the architecture which supports multicast, mobility and security. Mobility is the necessity here in the proposed IoT system in railways. System contains passenger information which should remain secure. Hence, ICN architecture is used as a base for IoT system in railways. The Internet of Things (IoT) based system is for catering passengers' services and requests in long journey railways. The system is to collect requests from passengers from each coach, track the location of crew members within train and allocate them requests from passengers. This allocation of the requests to the crew members takes place depending on the service arrival time, location information and workload factor of crew member. As proposed project is based on ICN architecture, it will use secure device discovery concept to make system more secure.
Design and Analysis of a Linear Array Antenna with Beam Steering Facility

The proposed paper presents the design of a linear array antenna of lx6 with beam steering. The antenna resonates at a frequency of 2.45GHz. The proposed antenna can be used for wireless communication. The antenna is designed on the substrate FR4_epoxy having a thickness of 165mm. The design proposed in this paper is lx6 Linear antenna array at 2.45 GHz frequency with beam steering for wireless communication.
Opto-electrical Properties of GaN/Si Nanoheterostructure Array Device

A GaN/Si nanoheterostructure array was synthesized using the functional substrate of silicon nanoporous pillar array (Si-NPA) by CVD method. An n-GaN nanocolumnar/p-Si nanocrystalline nanoheterojuction array solar cell was fabricated and the GaN nanocolumnar grew along the [0001] direction. The device has an average integrated reflection of ∼4.79% at the range of 300-1200 nm. The solar cell showed aVoc of 0.82 V, aJsc of 23.21 mA, aFF of 38.3% and a maximum power conversion efficiency of 7.29%. The results provide a new conception of mass-nanoheterojuctions for photovoltaic filed.
Efficient Distributed-Memory Parallel Matrix-Vector Multiplication with Wide or Tall Unstructured Sparse Matrices

This paper presents an efficient technique for matrix-vector and vector-transpose-matrix multiplication in distributed-memory parallel computing environments, where the matrices are unstructured, sparse, and have a substantially larger number of columns than rows or vice versa. Our method allows for parallel I/O, does not require extensive preprocessing, and has the same communication complexity as matrix-vector multiplies with column or row partitioning. Our implementation of the method uses MPI. We partition the matrix by individual nonzero elements, rather than by row or column, and use an "overlapped" vector representation that is matched to the matrix. The transpose multiplies use matrix-specific MPI communicators and reductions that we show can be set up in an efficient manner. The proposed technique achieves a good work per processor balance even if some of the columns are dense, while keeping communication costs relatively low.
The Spectral Conversion Layer Incorporated with Species of LDS and UC Phosphors on Single-Junction GaAs Solar Cells to Enhance Photovoltaic Performance

In this study, photovoltaic performance enhancement of single-junction GaAs solar cells using a spectral conversion layer incorporated with luminescent down-shifting (LDS) and up conversion (UC) phosphor-species is experimental demonstrated. The photo-luminescent wavelengths of proposed LDS- and UC-phosphor species are 512 nm and 650-660 nm, respectively. Optical reflectance and external quantum efficiency response are used to examine LDS and UC effects. The performance enhancements are confirmed by photovoltaic current density-voltage curves under AM 1.5G solar simulation. An impressive increasing in absolute efficiency of 0.91% (from 22.92% to 23.83%) was obtained when the cell coated with a spectral conversion layer incorporated with LDS and up UC phosphor-species, compared to the reference cell efficiency of 22.92%t.
Semi-Analytical Model for Skewed Magnet Axial Flux Machine

The compact design, and high power density distinguishes axial flux permanent magnet (AFPM) machine from other variants of permanent magnet machine. Recent research focused on the development direct drive axial flux machine in several practical area such as wind power generators, electrical vehicle drives, and servo applications. However, the interaction between PMs and slots, produces undesirable cogging torque. This torque produces mechanical vibration, noise, torque ripples, voltage ripples and speed ripple in machine. Enormous design techniques including skewed slot, skewed magnet, axillary slots, magnet pitch ratio and many more have been reported in literature for its reduction. However, these design techniques adversely affects the pattern of no load magnetic field, and consequently, machine performance. In this paper, an analytical model is developed to evaluate the effects of magnet skewing on the performance of AFPM machine. The no load magnetic field, and cogging torque are evaluated for three different types of open slots stators topologies viz. type 1: trapezoidal slot, type 2: Parallel slot, and type 3: trapezoidal slot are investigated. The analytically obtained results are compared with finite element analysis (FEA) for the validation. Finally, the cogging torque of skewed and unskewed AFPM machines are compared.
The Band-Sampled-Data collection for the search of continuous gravitational wave signals

The detection of gravitational wave signals in the LIGO and Virgo interferometric detector data, is possible thanks to the application and development of several data analysis techniques and to the improvement in the detector sensitivity. A particular type of signal, still undetected by the LIGO-Virgo collaboration, is the so-called continuous wave signal (CW). A CW signal is a quasi-monochromatic signal, deeply buried in the data and modulated by several physical effects. In order to extract the signal from the detector noisy data, several data handling and manipulations should be performed. In particular this type of gravitational wave is recovered using techniques from Fourier analysis and phase demodulations. In this work we will present a new data framework called Band-Sampled-Data (BSD) collection developed for all the searches of CW signals, and the main features of the data used in this context will be described.
Content-Agnostic Web Browsing Quality Assessment

Web browsing is one of many people’s everyday activities, not only for doing business, but also for leisure purposes. From the provider’s point of view it is necessary to know how the service is perceived by the end users and what factors really influence quality. The problem is how to find a relation between objectively measured network performance parameters and the quality perceived by customers. The second problem is how to choose the content and design the web page which will be tested. The authors propose a method of web browsing quality assessment, which is not sensitive to the content and web page design. This makes the method more universal.
Context aware stopwords for Sinhala Text classification

When working with Text Classification (TC), often the term �stopword� can be heard. Words in a document that are frequently occurring, but meaningless in terms of Information Retrieval (IR) are called Stopwords. There are various stopword lists available for many languages. According to the best of knowledge, no any generic stopword list has been built for the Sinhala language. This paper demonstrates how to generate a domain-specific stopword list from a given data set of Sinhala Newspapers. Hence, the seven stopword identification methods previously applied to other languages are presented to remove stopwords. Then, a new algorithm for building a domain-specific stopword list is proposed. For this method, it is assumed that average F-measure and average accuracy for the set of different stopword lists are measured by the performance of two classifiers. Based on the given comparative study, the most effective method to classify stopwords in Sinhala corpus can be identified.
Analysis on Gradient Propagation in Batch Normalized Residual Networks

We conduct a mathematical analysis on the Batch normalization (BN) effect on gradient backpropagation in residual network training in this work, which is believed to play a critical role in addressing the gradient vanishing/explosion problem. Specifically, by analyzing the mean and variance behavior of the input and the gradient in the forward and backward passes through the BN and residual branches, respectively, we show that they work together to confine the gradient variance to a certain range across residual blocks in backpropagation. As a result, the gradient vanishing/explosion problem is avoided. Furthermore, we use the same analysis to discuss the tradeoff between depth and width of a residual network and demonstrate that shallower yet wider resnets have stronger learning performance than deeper yet thinner resnets.
Performance Analysis of Memory Cloning Solutions in Mobile Edge Computing

This paper deals with the problem of service migration in the emerging scenarios of Mobile Edge Computing. Mobile edge computing is achieved by moving the traditional cloud infrastructures, exploited by many today applications, close to the network edge in order to reduce the response times in the so called tactile-internet. However, because of user mobility, such an application architecture may pose the problem of service migration in case of handover from one server site to another. After introducing the current solutions for dealing with service migration and, in particular, the approaches based on service decomposition into multiple layers, we quantify the migration time and the service downtime achieved under different policies (pre-copy, post-copy and hybrid-copy) for stopping and synchronizing the application between source and destination server. Numerical results are provided for RAM-intensive applications, for which a pre-copy approach can be particularly interesting.
Graph Edit Distance Testing through Synthetic Graphs Generation

Error-tolerant graph matching has been demonstrated to be an NP-problem, for this reason, several suboptimal algorithms have been presented with the aim of making the runtime acceptable in some applications. These algorithms have been tested with relative small graphs due to the computation of the true distance for comparison purposes is too costly. We present a method to generate graphs together with an upper and lower bound distance with linear computational cost. Through this method, we can test the behaviour of the known or new sub-optimal error-tolerant graph matching algorithms against a lower and an upper bound graph edit distance on large graphs, even though we do not have the true distance. The computational cost to generate a pair of graphs together with their upper and lower bounds is linear with regard to the number of nodes. The practical experimentation shows that the runtime to generate a pair of graphs is negligible with regard to the runtime to match them.
Assessment of Pharmaceuticals, Personal Care Products, and Hormones in Wastewater Treatment Plants Receiving Inflows from Health Facilities in North West Province, South Africa

The presence of 17 pharmaceutical and personal care products (PPCPs) belonging to various therapeutic categories was investigated in two hospital wastewater treatment plants (WWTPs) in North West Province, South Africa. The compounds were extracted from wastewater samples by solid-phase extraction and analysed by liquid chromatography-tandem mass spectrometry. The results showed that ofloxacin, chloramphenicol, and bezafibrate were generally below the limit of quantification (LOQ) in the analysed samples. Acetaminophen and ibuprofen were the dominant pharmaceuticals in the influent streams with corresponding concentrations ranging from 21 to 119 μg/L and 0.3 to 63 μg/L, respectively. Both WWTPs were shown to have the capability to remove some of the target PPCPs, including acetaminophen (76-98%), tetracycline (15-93%), ibuprofen (44-99%), and triclocarban (13-98%). The monitoring of the target PPCPs in both influent and effluent samples of the investigated WWTPs revealed that the discharge of inadequately treated effluents could be contributing to the possible increase in the concentrations of these contaminants in the receiving environmental compartments. Further studies must be focused on the broader characterisation of these matrices in order to assess the potential ecological impacts of this waste disposal practice.
A Design and Development of P I Controlled Based MPPT for Photovoltaic Systems

This study presents a design and development of PI controller based maximum power point tracking (MPPT) techniques for solar charge controller using DC to DC BUCK converter. Solar charge controller helps in increasing the efficiency of the solar power transferred to the battery. The main problem in solar charger system is to maintain the DC output power from the solar panel as constant. The MPPT solar charge controller in this research consists of solar panel, DC to DC BUCK converter, MPPT solar charge controller, battery and resistance load. In this control system, it is necessary to measure the PV array output power and to change the duty cycle of the DC to DC BUCK converter control signal. The testing conditions of the system prototype is varying the irradiation of lighting simulation. The numerical method results that simulation with MATLAB/SIMULINK and experimental results had proved the effectiveness of the proposed system.
Densely Connected Single-Shot Detector

One-stage object detection approach which utilizes multi-scale feature maps to predict objects is currently the best real-time detector. However, in this approach, the high-resolution feature maps which are responsible for detecting small objects are harder to learn a proper abstraction of objects than the low-resolution feature maps. The problem is that these feature maps have to transform sufficient low-level information to the next layer while learning high-level abstraction. In this paper, we develop a transformation module which adopts the dense structure to simplify the learning problem of high-resolution feature maps. In addition, we utilize the inception module to enrich the representation power of high-resolution feature maps. Extensive experiments on most object detection datasets clearly demonstrate the effectiveness of our method. In particular, on PASCAL VOC 2007/2012, our method outperforms all the existing one-stage methods. Our model based on the VGG-16 network also achieves competitive result on MS COCO.
A Novel Modular 18-Slot 10-Pole PMSM with 9-Phase Unequal-Coil-Pitch Fractional-Slot Winding

This paper proposes a novel modular 18-slot 10-pole permanent magnet synchronous machine (PMSM) with 9-phase unequal-coil-pitch fractional-slot winding (UCP-FSW). The proposed machine allows stator to be modularized while significantly reducing rotor loss, which usually plagues the PMSMs with the conventional fractional-slot concentrated windings (FSCWs). Moreover, it also exhibits the merits of low cogging torque, low torque ripple and easy manufacturing. The structure of the proposal and the winding factor of the working harmonic are described and computed in detail. In addition, the main electromagnetic characteristics of the proposed machine are analyzed by finite element method (FEM) and compared with those of its 15-slot 10-pole counterpart equipped with the conventional FSCW.
Development of a wafer level packaging technology for high voltage applications

TSV first or TSV last are technologies used in 3D packaging, that are now well described in the literature. However there is still room for some improvement especially in the field of TSV isolation. Certain applications such as power applications or light emitting diodes serially powered on the 230 Volts-50 Hz network require some trench isolation for wafer level packaging. In this case the breakdown voltage (up to 600 V) of the trench/TSV becomes a critical issue. In this study different organic and mineral passivation layers were tested to classify their resistance to high voltage. The impact of the Temperature process and the deposition method is shown. Some thermal oxides are also tested and the breakdown voltage is found to be around $800\mathrm{V}/ \mu \mathrm{m}$. Some FEM simulations were achieved showing the influence of the trench geometry. The oxide is then implemented on pixelated samples fabricated on 200mm highly doped Si wafers. Experimental measurements show a breakdown voltage location at the trench crossing zone and a value of $400 \mu \mathrm{m} /\mathrm{V}$ in accordance with the FEM simulations.
Developemet of C-Band High Integration & High Efficiency Space-Borne T/R Module

As the hardcore of phased array antennas, the development of highly reliable TIR module for satellite SAR application becomes the research sticking point. Due to satellite In SAR application, the TIR module is required for high - efficiency, low-loss, low-mass, high amplitude and phase stability and high reliability. In this paper, a C-band Dual-channels T/R Module based on GaN high power MMIC and GaAs high-integrated multifunctional MMIC with multichip module (MCM) packing technics is introduced, which realizes the integration of microwave signal amplification, TIR control, digital amplitude and phase control, high voltage modulation. Compared with GaAs technics, the power amplifier based on GaN MMIC has higher output power and higher power added efficiency, accordingly decreases the total heat loss consumedly of SAR system. The T/R module channel provides over 41.5dBm output power, 29dB receive gain and 2.8dB noise figure, over 37% power added efficiency, weight only 35g, the size is 64mm×39.6mm×7mm, with high-efficiency and low-loss, miniaturization and low-mass, high reliability.
Analytical drain current model to study the impact of interface trap charges on device performance of Double Gate Ge Ferroelectric FET (DGGeFeFET)

In the present study, an analytical model has been proposed to study drain current characteristics for long channel Double Gate Germanium Ferroelectric FET (DGGeFeFET) by solving Poisson's equation and Landau-Khalatnikov equation. It has been shown that by incorporating ferroelectric layer with a device with Germanium channel a significant increase in current drivability can be achieved and also the major drawbacks of high leakage current and large inherent interface trap density in Ge based devices can be eliminated. To gain insight as to how negative capacitance results in improvement in device characteristics of DGGeFeFET in the presence of interface trap charges, we have done a comparative analysis with Double Gate Germanium FET (DGGeFET) for various values of interface trap density. It was found that the negative capacitancecan help to overcome the deterioration in device characteristics which is a result of presenceof interface trap charges.
Understanding the Temporal Fading in Wireless Industrial Networks: Measurements and Analyses

The wide deployment of wireless industrial networks still faces the challenge of unreliable service due to severe multipath fading in industrial environments. Such fading effects are not only caused by the massive metal surfaces existing within the industrial environment but also, more significantly, the moving objects including operators and logistical vehicles. As a result, the mature analytical framework of mobile fading channel may not be appropriate for the wireless industrial networks, especially the majority fixed wireless links. In this paper, we propose a qualitative analysis framework to characterize the temporal fading effects of the fixed wireless links in industrial environments, which reveals the essential reason of correlated temporal variation of both the specular and scattered power. Extensive measurements with both the envelop distribution and impulse response from field experiments validate the proposed qualitative framework, which will be applicable to simulate the industrial multipath fading characteristics and to derive accurate link quality metrics to support reliable wireless network service in various industrial applications.