bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of microwave β-(Al
x
Ga

1−

x
)2O3/Ga2O3 lateral Schottky barrier diodes
Authors: Shaikshavali Dudekula , Kannadassan D
Published: April 2022

High power microwave Schottky barrier diodes (SBDs) are required to develop detectors and mixers in advance the millimeter-wave (mm-wave) wireless technologies such as fifth generation long-term evolution. To achieve high efficiency and sensitivity in SBDs, materials/structures with high mobility and low series resistance are needed. In this regard, we have proposed the two dimensional electron gas of β-(Al
x
Ga

1
−
x

)2O3/Ga2O3 heterostructure channel lateral SBDs (LSBDs) for the first time. To design high performance LSBDs, detailed physical models of both β-(Al
x
Ga

1
−
x

)2O3 and Ga2O3 were studied and characterized with experimental results. These physical models were used to perform realistic numerical simulations of DC, small signal and large signal conditions. It was observed that the structural and compositional aspects of heterostructure are largely influencing the small signal sensitivity and cut-off frequencies. Also the large signal analysis reveals that the LSBD can operate in linear detection of microwave signals, up to 38 dBm. By scaling down the device to a sub-micron channel length, a cut-off frequency of

>

1.5 THz was achieved in the proposed LSBD. Comparison with state-of-the-art SBDs, the observations from DC, small signal and large signal analysis recommend the proposed β-(Al
x
Ga

1
−
x

)2O3/Ga2O3 LSBDs for high power and mm-wave/sub-THz detector/mixer application.
Structural and ultrasound studies of Pr2O3 settlement in AlNaBi–phosphate spectacles
Authors: El-Denglawey A , Saddeek Yasser B , Aly K A , Showahy A A , Alharbi T
Published: April 2022

Pr2O3 doped bismuth-phosphate glasses have been produced via an ordinary melt quenching tool. Glasses have a chemical content (5–x) Al2O3–15Na2O–20Bi2O3–60 P2O5 –xPr2O3 with x values between 0 and 2 mol%. The structural and mechanical features of the prepared phosphate-based glasses were investigated. The XRD spectra confined the amorphous type of these glasses. Furthermore, the influence of Pr2O3 on the mechanical features has been explored and related to the structure. The relationship between structural variations and the contents of Pr2O3 has been investigated in terms of FTIR and by the determination of the density and the ultrasonic velocity. The density and the ultrasonic velocities were utilized to calculate the elastic moduli of the glasses. The acquired results indicate that the ultrasonic velocity and the elastic moduli increase as a function of Pr2O3 in the whole explored studied glasses. The analysis of FTIR spectra refers that Pr2O3 is interstitial settled in the phosphate network with [PrO7] associated with covalent Pr–O–P bonds, whereas Bi2O3 and Al2O3 settle on the network with [BiO6], and [AlO6] units. These experimental features coincide with a compact structure and act in a manner that Pr2O3 incorporates the glassy network with plenty of bridging oxygen atoms. These arguments encourage the use of these glasses in radiation shielding materials.
The effect of dark matter discreteness on light propagation
Authors: Koksbang Sofie Marie , Räsänen Syksy
Published: April 2022

Light propagation in cosmology is usually studied in the
geometrical optics approximation which requires the spacetime
curvature to be much smaller than the light wavenumber. However, for
non-fuzzy particle dark matter the curvature is concentrated in
widely separated spikes at particle location. If the particle mass
is localised within a Compton wavelength, then for masses
≳104 GeV the curvature is larger than the energy of CMB
photons.

We consider a post-geometrical optics approximation that includes
curvature. Photons gain a gravity-induced mass when travelling through
dark matter, and light paths are not null nor geodesic. We find that
the correction to the redshift is negligible. For the angular diameter
distance, we show how the small average density emerges from the large
local spikes when integrating along the light ray. We find that there
can be a large correction to the angular diameter distance even for
photon energies much larger than the curvature. This may allow to set
a strong upper limit on the mass of dark matter particles. We discuss
open issues related to the validity of our approximations.
The influence of approximation in generalized uncertainty principle on black hole evaporation
Authors: Du Xin-Dong , Long Chao-Yun
Published: April 2022

The generalized uncertainty principle is often used to modify various thermodynamics systems by regarding the greater-than-equal relation as an approximate relation. We give a method to improve this approximation and compare the differences between the original and improved methods during the evaporation of black hole from two aspects of positive and negative parameters. Finally, we prove the rationality of the improved method and give some guiding opinions.
Temperature-based Collision Detection in Extreme Low Light Condition with Bio-inspired LGMD Neural Network
Authors: Zhang Yicheng , Hu Cheng , Liu Mei , Luan Hao , Lei Fang , Cuayahuitl Heriberto , Yue Shigang
Published: April 2022

It is an enormous challenge for intelligent vehicles to avoid collision accidents at night because of the extremely poor light conditions. Thermal cameras can capture temperature map at night, even with no light sources and are ideal for collision detection in darkness. However, how to extract collision cues efficiently and effectively from the captured temperature map with limited computing resources is still a key issue to be solved. Recently, a bio-inspired neural network LGMD has been proposed for collision detection successfully, but for daytime and visible light. Whether it can be used for temperature-based collision detection or not remains unknown. In this study, we proposed an improved LGMD-based visual neural network for temperature-based collision detection at extreme light conditions. We show in this study that the insect inspired visual neural network can pick up the expanding temperature differences of approaching objects as long as the temperature difference against its background can be captured by a thermal sensor. Our results demonstrated that the proposed LGMD neural network can detect collisions swiftly based on the thermal modality in darkness; therefore, it can be a critical collision detection algorithm for autonomous vehicles driving at night to avoid fatal collisions with humans, animals, or other vehicles.
Using deep learning to detect the presence/absence of defects on leather: on the way to build an industry-driven approach
Authors: Adão Telmo , Gonzalez Dibet , Castilla Yusbel Chavez , Pérez José , Shahrabadi Somayeh , Sousa Nuno , Guevara Miguel , Magalhães Luis G.
Published: April 2022

In textile/leather manufacturing environments, as in many other industrial contexts, quality inspection is an essential activity that is commonly performed by human operators. Error, fatigue, ergonomic issues, and related costs associated to this fashion of carrying out fabric validation are aspects concerning companies’ strategists, whose mission includes to watch over the physical integrity of their employees, while aiming at enhanced quality control methods implementation towards profit maximization. Considering these challenges from a technical/scientific perspective, machine/deep learning approaches have been showing great skills in adapting a wide range of contexts and, in particular, industrial environments, complementing traditional computer vision methods with characteristics such as increased accuracy while dealing with image classification and segmentation problems, capacity for continuous learning from experts input and feedback, flexibility to easily scale training for new contextualization classes – unknown types of occurrences relevant to characterize a given problem –, among other advantages. The goal of crossing deep learning strategies with fabric inspection processes is pursued in this paper. After providing a brief but representative characterization of the targeted industrial context, in which, typically, fabric rolls of raw-material mats must be processed at a relatively low latency, an Automatic Optical Inspection (AOI) system architecture designed for such environments is revisited [1], for contextualization purposes. Afterwards, a set of deep learning-oriented training methods/processes is proposed in combination with neural networks built based on Xception architecture, towards the implementation of one of the components that integrate the aforementioned system, from which is expected the identification of presence/absence of defective textile/leather raw material at a low-latency. Several models powered by Xception were trained with different tunning parameters, resorting to datasets variations that were set up from raw images of leather, following different annotation strategies (meticulous and rough). The model that performed better reached 96% of accuracy.
Application of Machine Learning Approaches in Health Care Sector to The Diagnosis of Breast Cancer
Authors: Wassim Ahrou , Elarbi Elalaouy , Khadija Rhoulami
Published: April 2022

Breast cancer (BC) is a kind of malignant disease that represents the primary reason of women’s death around the world, cancer cells form tumors which lead to weakening the functioning of the immune system. If the main risk factors are known and detected correctly, the cure rate becomes higher, and the inappropriate treatments which are the main cause of death will be avoided. Today, several avenues for advancing breast cancer classification research are being studied, in particular to strengthen screening and develop an early diagnosis plan. The purpose of this paper is to approach the unfolding of machine learning techniques in the clinical field to categorize and discriminate patients between malignant and benign groups. Modeling of cytological characteristics based on machine learning is proposed to improve predictive performance. In this work, three proposed algorithms of machine learning techniques have been used for the analyze and classification of Wisconsin breast cancer database, k Nearest Neighbors (k-NN), Naive Bayes (NB) and Support Vector Machine (SVM). We will compare learning metrics of both, using train/test split and cross validation. The obtained results shows that KNN offers the best accuracy (97.07%), NB classifier (94.15 %) and SVM classifier (94.73%).
Penetration Multilayer Overload Signal Generation Based on TransGAN
Authors: Fang Anqi , Li Rong
Published: April 2022

With the booming development of modern electronic technology, artificial intelligence in the military field is showing a fast-rising trend, but at the same time, it is also facing the dilemma of a serious shortage of data. To address the current problems of low number and unbalanced categories of penetration multi-layer overload signals, a TransGAN-based penetration multi-layer overload signal generation method is proposed in combination with the fruitful neural network model of deep learning. Firstly, the dataset is built using overload signals that have been tested in practice at the range. Secondly, generator and discriminator are constructed. Generator borrowing the model structure of TransGAN, which consists of Transformer Encoder for learning the feature mapping of the overload dataset, and discriminator using a simple attention mechanism to reduce the complexity of the model. Finally, the generator and discriminator are trained and optimized using a generative adversarial network to achieve the penetration multilayer overload signal. Finally, the generative adversarial network is utilized to train and optimize the generator and discriminator to achieve penetration multilayer overload data generation. Experimental results show that the method can generate effective overload data with a different number of layers, which can address the issue of the lack of penetration multilayer overload signals to a certain extent.
Lightweight and Effective Human Pose Estimation Model Based on Multi-Angle Knowledge Distillation
Authors: Li Hua
Published: April 2022

In the field of human pose estimation, most of the existing methods focus on improving the generalization performance of the model, while ignoring the significant efficiency issues. This leads to an increasing amount of model parameters and needs to take up more and more computing resources, which greatly reduces the practical value of the model. In order to solve this problem, we propose a novel lightweight network structure called Effective and Lightweight Pose Network (ELPN). At the same time, for the sake of alleviating the difficulty of lightweight model training, we propose a Multi-Angle Pose Distillation (MAPD) model training method that can more effectively train particularly small pose network models. In quantitative experiments, our models have excellent performance on two mainstream benchmark datasets: the MPII and the COCO. In qualitative testing, our models can accurately locate the keypoints of complex human movements. These fully demonstrates the efficiency and effectiveness of our methods. Our models have the characteristics of high precision, small size and fast inference speed. It is a cost-effective model with greater practical value.
Holographic Study of Non-Stationary Surface Deformations by the Method of Combined Exposure of Interferograms
Authors: Selivanov Yu M , Dzyuba A P , Klymenko S V , Shevchenko V V
Published: April 2022

The article presents a method of holographic research of non-stationary deformations of a surface by method of two exposures, one of which is carried out in its static state, the other in motion. The derivation of formulas for quantitative analysis of the obtained interferograms for a number of typical cases of surface motion is given, as well as a general algorithm for determining the displacements from the interferogram. The features and results of approbation of the method are given. It is shown that the method is very broad in the application of holographic interferometry. Its application makes it possible to obtain highly informative qualitative and quantitative data on the field of unstable displacements of the test element at any moment of its deformation, using for this purpose low-power continuous-wave lasers (instead of expensive high-power sources) and, accordingly, relatively inexpensive and compact holographic measuring devices.
Electromagnetic Waves’ Dynamic Simulation in a Confined Space Under Limiting Conditions
Authors: Shovhelia D , Sokolova N
Published: April 2022

This study aims at finding the most advantageous algorithm for dynamic simulation of the propagation of electromagnetic waves inside buildings. The method is based on fast estimation of Wi-Fi signal strength when passing obstacle within the building and the modified Smart3D algorithm. A software application for dynamic simulation of the best wireless network coverage under restrictive conditions was developed in Autodesk® Revit® environment. The application calculates Wi-Fi signal attenuation of buildings, estimates position of signal sources to get the best network coverage.
PharmaLab: A Tool to Study the Drug Action on the Mouse Ventricular Myocyte
Authors: Camargo M L A , Goroso D G , Bissaco M A S , Silva R R
Published: April 2022

Mathematical and computational modeling has been a great ally in the development of new drugs. It helps by providing preliminary results that ultimately guide the path that the tests should take. Thus, the objective of this work was to develop the PharmaLab computational tool, which simulates the pharmacological action in the mouse ventricular myocyte using the mathematical model of Mullins & Bondarenko (2013). Having as one of the main differentials the integration with a model for the force of contraction, at PharmaLab it is possible to perform pharmacological tests by changing parameters of the mathematical model and registering drugs to be used in the simulations. The computational tool has its own interface for plotting results and support material for educational use. As a demonstration of the tool, a validation was performed, comparing simulations with experimental data for the drug Niferidil and two “in silico” tests: SS-68 correcting the “Catecholaminergic Polymorphic Ventricular Tachycardia” (CPVT) and Niferidil correcting the Short QT Syndrome (SQTS). The drugs showed good results in the correction of arrhythmias. Finally, it can be concluded that the PharmaLab computational tool has resources for use in both research and teaching.
Physics Concept Space: An Application of Fischer’s Thought Space
Authors: Chekuri N R
Published: April 2022

A Physics Concept Space is constructed using Fischer’s Thought Space, a general thought space that explains how individuals continually construct thoughts and modify them through conscious actions on events (Aes) in Physical Sociocultural Environments (PSCEs) from birth throughout the life span. Thought Developmental Equations (TDE) that operate on the physics concept space take two physics concepts and construct new concepts using the operations augmented-intercoordination (⊗), compounding (⊕), and shift of focus (<>). Diffisimliar metric dp
, a measure for the number of similar, different, and non-diffesimilable properties and an individual’s comprehension of thoughts at a given time, reveals the development and connectedness of the concept space through the life span. At any given time, only the part of the space associated with actions (Aes) is active while they are being performed. No two concept spaces activated simultaneously or at two different times are the same, but the construction mechanism is the same. Granott’s transition process and the dp
explain the underlying cognitive process. Furthermore, several properties of physics concept space such as near and far connectedness, continuum space, bases, subspaces, multiplicity, product spaces, and dynamic nature, along with the skills required to construct physics space, are discussed. The properties of the space show that it is a highly connected space, supporting a tenet of the epistemology of physics.
Motion of Mass Source in Stratified Fluid
Authors: Baydulov Vasiliy G , Knyazkov Dmitri , Shamaev Alexey S
Published: April 2022

The paper considers the problem of determining properties of an underwater moving source by analyzing the perturbation that it creates in electromagnetic or hydrodynamic fields. The computer program has been developed to simulate the spatial propagation of gravitational waves from the mass source moving along an arbitrary trajectory in a stratified fluid. The calculation results are in good agreement with analytical results obtained in the far-field approximation and with the results of experiments on the flow around underwater obstacles, moreover, the proposed technique allows to simulate any arbitrary motion of the source. Two new approaches to solving the inverse problem of determining the characteristics of the source of disturbances are proposed. The first one is based on the analysis of the signal received by radio-sensors, that scan the surface of the ocean. The second one uses data obtained from sensors installed directly in the water column.
Organizing Large Data Sets for Efficient Analyses on HPC Systems
Authors: Gu Junmin , Davis Philip , Eisenhauer Greg , Godoy William , Huebl Axel , Klasky Scott , Parashar Manish , Podhorszki Norbert , Poeschel Franz , Vay JeanLuc , Wan Lipeng , Wang Ruonan , Wu Kesheng
Published: April 2022

Upcoming exascale applications could introduce significant data management challenges due to their large sizes, dynamic work distribution, and involvement of accelerators such as graphical processing units, GPUs. In this work, we explore the performance of reading and writing operations involving one such scientific application on two different supercomputers. Our tests showed that the Adaptable Input and Output System, ADIOS, was able to achieve speeds over 1TB/s, a significant fraction of the peak I/O performance on Summit. We also demonstrated the querying functionality in ADIOS could effectively support common selective data analysis operations, such as conditional histograms. In tests, this query mechanism was able to reduce the execution time by a factor of five. More importantly, ADIOS data management framework allows us to achieve these performance improvements with only a minimal amount of coding effort.
Research on Electromagnetic Interference of Lightning Current on Secondary Cable in Substation
Authors: Liu Shengjun , Yin Yanzeng , Qi Hongbin , Wang Xuejia
Published: April 2022

Secondary cable is an important equipment for ubiquitous power Internet of things to transmit information. When the substation grounding grid is struck by lightning, part of the lightning current flows through the shielding layer of secondary cable and produces core-to-sheath potential difference, which seriously threatens the safety of the secondary system. Fourier transform was used to decompose the lightning current in frequency domain, and the core-to-sheath potential difference at the end of the secondary cable was obtained by calculating the shielding layer current and transfer impedance at each frequency component. The effects of soil resistivity, lightning current waveform, distance between lightning stroke point and cable and grounding grid on the core-to-skin potential difference of secondary cable were studied. It is shown that the core-to-sheath potential difference of secondary cable increases with the increase of soil resistivity, the peak value, and the tail time of lightning current. The core-to-sheath potential difference decreases with the increase of the distance, while the core-to-sheath potential difference increases with the increase of conductor spacing of the grounding grid. The core-to-sheath potential difference with copper grounding grid is smaller than that with steel grounding grid.
Influence of Normalization Techniques on Multi-criteria Decision-making Methods
Authors: Mhlanga Sandile Thamie , Lall Manoj
Published: April 2022

One of the most significant steps in solving multi criteria decision-making (MCDM) problems is the normalization of the decision matrix. The consideration for the normalization of the data in a judgment matrix is an essential step as it can influence the ranking list. This study investigates the effects of normalization on an AHP-VIKOR hybrid method in the selection of Web services. The Web services considered in this research offer similar functionalities but with different Quality of Services (QoS). For the purpose of this study, ten web services were selected. Each of these services were evaluated against five difference QoS requirements namely, response time, throughput rate, latency, availability, and reliability to determine the most appropriate Web services. The five normalization techniques employed are linear sum, linear max, linear max-min, enhanced accuracy and vector normalization. It was observed that different ranking lists are produced when applying different normalization techniques to the VIKOR method and normalization has an influence on the final ranking list.
Forensic Analysis of the IoT Operating System Ubuntu Core
Authors: Castelo Gómez Juan Manuel , Roldán Gómez José , Martínez José Luis Martínez , Amo Mínguez Álvaro del
Published: April 2022

The number of cyber incidents in which an Internet of Things (IoT) device or system is present is increasing every day, requiring the opening of forensic investigations that can shed light on what has occurred. In order to be able to provide investigators with proper solutions for performing complete and efficient examinations in this new environment, IoT systems and devices are being studied from a forensic perspective so that tools and procedures can be designed accordingly. In this article, the IoT version of one of the most used Linux distributions, namely Ubuntu, is studied to determine in what way a forensic investigation of this system should be performed, detailing how to approach the acquisition and analysis phases. In addition, both the volatile and non-volatile artifacts that might held useful information are listed and described.
Scale-Adaptive Selection Network with Dynamic Focal IoU Loss
Authors: Xu Wenxiong , Yin Jun , Sun Zepei , Wang Keyang , Shao Ming
Published: April 2022

Feature pyramid network is wildly applied to predict the targets at different scales in many one-stage detectors. However, most of them treat all feature levels without level-wise attention. As a result, different levels may capture the same object and predict totally different labels, which lead to lower AP on evaluation. Besides, many classic detectors aim at relieving the imbalance between hard and easy samples on classification task, while we find the fact that hard-easy imbalance also exists in localization. To general detection task, bboxes regressed at high IoU are much less than those at low IoU so that detector can easily be biased towards suboptimal bboxes and localization accuracy will be harmed. Based on these two points, in this paper, we propose a Scale-Adaptive Selection Network (SASNet) with a novel Dynamic Focal IoU (DF-IOU) loss. The Scale-Adaptive Selection Network introduces multi-scale attention mechanism into feature pyramid so as to assign attention weight for feature maps on each level, which enables the network to select the dominant levels for prediction and alleviate the prediction conflicts between different levels. Furthermore, we design Dynamic Focal IoU loss to increase loss contribution of easy targets so that the coordinates of these easy targets can regress better and the bounding box will fit tighter. Our experimental results show that our SASNet with DF-IoU loss can increase average precision of objects at small, medium and large scale on the MS COCO and CCPD dataset.
A Trusted IoT Communication Architecture Based on Blockchain and Named Data Network
Authors: Sun Yizhe , Chen Shiyou , Fang Yadong , Xu Wei , Luo Qun , Rui Lanlan
Published: April 2022

The trusted cross-domain sharing capability of the Internet of Things (IoT) terminals needs to be improved urgently. Aiming at the technical issues of routing overhead and authentication security of data sharing of IoT devices, this paper proposes a trusted transmission architecture for network-chain collaboration. Introduce the mobile edge computing (MEC) platform in named data network (NDN) to deploy blockchain light nodes and improve the PBFT consensus algorithm. Besides, a cross-domain authentication algorithm based on elliptic curve encryption is proposed. Simulation results show that the improved PBFT and cross-domain authentication algorithm can effectively improve IoT cross-domain sharing capabilities.
Control of a Semi-autonomous Powered Wheelchair
Authors: Sanders D , Tewkesbury G , Haddad M , Kyberd P , Zhou S , Langner M
Published: April 2022

A model reference controller for a powered wheelchair is described. The chair is fitted with sensor systems to assist a disabled user with steering their chair. The controller can cope with varying circumstances and situations. Non-linear terms are compensated for using an adaptive and automatic scheme. Consistent and dependable veer-controll is considered and the system was able to deal with uncertainties, for example changing surfaces, different shifting weights of users, hills, bumps, slopes and differences in tires and wheels. The controller has a quasi-linear closed-loop behaviour and that means that extra outer control loops can be appended later, for example path-following algorithms. An assistive agent was also created so that sperate wheelchairs will be able to communicate with each other in the future.
Adaptive Cruise Control of Virtual Coupled Trains Based on Sliding Mode
Authors: Wang Di , Cao Yuan
Published: April 2022

In this paper, the adaptive cruise control method for the virtually coupled train set (VCTS) in rail transit is proposed. First of all, a leader-following VCTS dynamics model is constructed by analyzing the dynamic evolution of VCTS in a real-world environment, taking into account uncertain parameters, unknown disturbances and controller input saturation. Next, to cope with the position and speed constraints, the position artificial potential field function and the speed barrier function are embedded into the designed sliding manifold. And a novel adaptive cruise control protocol is designed, which can simultaneously deal with uncertain resistance parameters and unknown disturbances while tracking the desired cruise speed and maintaining the desired distance. Based on Lyapunov stability theory, the proposed control protocol guarantees the ultimate boundedness of all subsystems. Finally, the simulation results verify the effectiveness of the theoretical analysis.
A Comparative Study: The Benefits of a Novel Illuminance Calculation Method over Luminance Calculation Method for Optimal Roadway Lighting Design Applications
Authors: Thurairajah U
Published: April 2022

This paper discusses the challenges and impacts of the luminance calculation method for roadway lighting applications and recommends a novel illuminance calculation method as the most suitable for Roadway Lighting Applications. This change would reduce the costs of roadway lighting design without increasing risks, which will benefit society and the profession. Luminance calculations are complicated and take approximately five times longer than the new illuminance calculation method, provide no additional insight, and result in the same design outcome. This paper makes a comparative study and analyzes both methods using regular comparative assessment and quantitative and qualitative assessments and provides a solution to the over 50-year-old challenge. The quantitative evaluation uses a sample case study and examines its corresponding benefit-cost ratio. The qualitative approach is to complete a survey among the peers and the lighting designers. This is the first paper to address all these parameters of roadway lighting holistically. This paper will be helpful for academics, researchers, scientists, engineers, consultants, architects, lighting designers, contractors, developers, financial institutions, and government agencies funding outdoor lighting.
Implementation of Multiple Feature Selection Algorithms for Speech Spoofing Detection
Authors: Faham Ali Zaidi Syed , Xu Longting
Published: April 2022

The ASVspoof challenge sequences were proposed to lead the research in anti-spoofing to a new level for automatic speaker verification (ASV). It’s verified that constant Q cepstral coefficients (CQCC) processes speech in variable frequencies with adjustable resolution and outperforms the other generally used features and Linear Frequency Cepstral Coefficient (LFCC) is used in high-frequency areas. The feature selection algorithm is offered to decrease computational complexity and overfitting for spoofed utterance detection. Precisely, there’s a demand for feature selection algorithms that are computationally effective and sensitive to feature interactions so that useful features aren’t falsely excluded during the ranking process. We experiment on the ASVspoof 2019 challenge for the assessment of spoofing countermeasures. After the evaluation of our given algorithms and data gives us an equal error rate (EER) and tandem discovery cost function (t-DCF) values. Experimental results on ASVspoof 2019 physical access referring to multiple feature selection approaches show a breakthrough compared to the baseline.
Effect of Resonance Interference on MEMS Gyroscopes and Filtering Algorithm Elimination
Authors: Wu Junjie , Sun Yufei , Guo Peng , Feng Lihui , Zhang Yongbin , Zhang Youqi
Published: April 2022

The mechanical structure of MEMS gyroscope is a spring-mass-damper system, which is susceptible to interference near the resonant frequency. This work compared the interference effects of mechanical vibrations and high frequency sound waves on MEMS gyroscopes. Three MEMS gyroscopes ADXRS620 were interfered by vibrations and sound waves near the resonant frequency. The error outputs increased linearly with the increase of interference intensity. The maximum error output could reach 88.95 °/s, which seriously affect the normal operation of the gyroscope. The waveforms of gyroscope outputs under acoustic and vibration interference were almost coincident, which showed the similarity of acoustic and vibration interference. However, to produce the same effect on gyroscopes, the power required of vibration interference was much less than that of acoustic interference. Taking one of the gyroscopes for example, when the SPL of acoustic interference was up to 90 dB, the maximum error was only 3.37 °/s. But when the acceleration amplitude of vibration interference reached 0.050 g, the maximum error was 3.42 °/s. In addition, the effectiveness against vibration interference of the filtering algorithm based on orthogonal demodulation was verified by testing the self-developed gyroscope. Vibration interference could be reduced by 98.88% at most.
Distributed Incentive Mechanism Based on Hyperledger Fabric
Authors: Li Baohui , Fang Yadong , Xu Wei , Wang Jiaxing , Rui Lanlan , Lei Min
Published: April 2022

Crowd sensing is a new type of data acquisition method that can efficiently and diversify the realization of sensing tasks. However, this method currently has some problems, such as data storage being overly dependent on third-party platforms, and there is a lack of reliable data credible evaluation methods. To solve this problem, our paper proposes a distributed incentive mechanism based on Hyperledger Fabric (HF-DIM) in the Crowd sensing scenario. In particular, the following questions are studied: How to achieve distributed incentive to solve the traditional incentive that relies on a centralized platform? How to evaluate the credibility of the sensing data provided by the users? To the former question, we implement a multi-attribute auction algorithm based on smart contracts, and distributed incentives are implemented using blockchain deployed contracts. To the latter question, We propose a K-nearest neighbor outlier detection algorithm based on geographic location and similarity to evaluate the credibility of the data and establish a reputation index based on the credibility of the data. Through simulation experiments using real data set, the feasibility and effectiveness of the proposed framework and algorithm are verified.
An Improved Genetic Algorithm for the Uncapacitated Facility Location Problem and Applications in Oil and Gas Fields
Authors: Zhou Jun , Wang Xuanqing , Zhang Lulu , Zhou Xuan , Jing Siqi , Liang Guangchuan
Published: April 2022

Uncapacitated Facility Location Problem (UFLP) is a NP-hard Problem that to determine the optimal Location of facilities. In this paper, the general Genetic Algorithm (gGA) is first introduced and adopted to solve a small case of UFLP (case1). Then an improved genetic algorithm (iGA) based on real coding is proposed to solve the UFLP problem. This paper mainly makes appropriate adjustments in the selection of fitness function, crossover operator and mutation operator to be more suitable for UFLP. Facilities thus can be roughly allocated according to the cost of facilities and the demands of customers. Case2 was calculated by several CAP data (CAP101, CAP103, CAP104, CAP131, CAP133, CAPB and CAPC) in OR-LIBRORY. The results proved that the iGA is feasible and effective, and it is found that 80% of the results obtained by the iGA are within 0.05% of the optimal solutions. Compared with several other common algorithms, the advantages of iGA increase as the scale of calculation increases. Finally, applying iGA to an on-site oilfield pipeline network, it was found that it can find the optimal solution in a short time.
A Two-stage Successive Approximation Method of Dynamic Programming for Operations of Cascaded Hydropower Plants with Navigation Demand
Authors: Shao Qizhuan , Wang Mingbo , Liu Shuangquan
Published: April 2022

The operations of cascaded hydropower plants have always been recognized as a complex system optimization problem. The difficulty of modelling and optimization solution is further aggravated when comprehensive water demands for power generation, navigation and ecology are considered. This study develops an optimization model for operations of cascaded hydropower plants with navigation demands, and proposes a two-stage successive approximation method of dynamic programming. In the model, the navigation demand is considered as a constraint. The first stage is to optimize the operation of cascaded hydropower plants with no consideration of navigation demand. The optimized result is taken as an initial solution of the last stage. Moreover, the navigation constraint is introduced in the solution procedure to obtain a reasonable operation scheme. The method is implemented on operations of a cascaded hydropower plants with navigation task in Southwest China. The results show that the navigation demand can be satisfied by coordination of cascaded hydropower plants. Moreover, this constraint has an effect on the monthly distribution of total energy production during one year. In addition, the computing efficiency and solution accuracy are analysed by using different discrete steps.
Structural and thermal properties of InSb:Mn with MnSb clusters
Authors: Durante Rincón C A , González-Laprea J , Mendoza Oliveros M E , Castro J A , Quintana E , Fermín J R
Published: April 2022

III-V family compounds doped with transition metals are promising materials for spintronic applications. Synthesis of an In0.9Mn0.1Sb ingot was thus carried out by direct fusion of the stoichiometric mixture of the constituent elements, followed by controlled cooling. The ingot obtained showed p-type conductivity. Scanning Electron Microscopy (SEM) images show MnSb clusters in an InSb matrix doped with Mn, a result like that found when the compound is obtained using other techniques. Energy-dispersive X-ray spectroscopy (EDS) shows that the atomic ratio of the clusters is Mn/Sb = 0.896 ± 0.025, while the atomic ratio of the matrix is In/Sb = 1.013 ± 0.005. The indexation of the powder X-ray diffraction pattern at room temperature yielded a majority cubic phase of InSb doped with Mn, with a lattice parameter a = 6.474173 Å and cell unit volume V = 271.36Å3
, while non-indexed reflections are associated with the presence of MnSb rich in Sb. The phase transition temperatures were obtained from differential thermal analysis (DTA) measurements on powder samples in evacuated quartz capsules. It can be observed that fusion of the InSb matrix doped with Mn occurs between 485 °C and 528 °C, unlike the congruent fusion of the InSb at 527.7 °C; while the fusion of the Sb-rich MnSb clusters occurs between 494 °C and 509 °C. These temperatures are lower than those reported for the Sb-rich side of the phase diagram of the Mn-Sb binary system, which shows a decrease in the thermal stability of the compounds. The estimated fusion enthalpies for InSb:Mn and antimony-rich MnSb are, respectively, 4.8 Kcal/mol and 117.4 Kcal/mol.
Polarization and biomineralization of hydroxyapatite-barium titanate composites
Authors: Uribe R , Rojas I , Riofrio M C , Lascano L , González G
Published: April 2022

In the search of new materials for bone regeneration, the materials with piezoelectric properties look very promising. It has been reported that piezoelectric materials induce bone growth and enhance implant integration. Additionally, it has been found that bioactivity increases in negatively charge surfaces such as polarized BaTiO3 (BT) and polarized hydroxyapatite (HAp). Additionally, it is known that BaSO4 (BS) increases biocompatibility. Therefore, in this work, composites materials of 80BT/20BS (BTS) in different proportions with HAp (HAp/BTS: 10/90, 30/70, 50/50, 70/30 y 90/10) were prepared by a mixture of nanometric powders and then they were sintered at 1000 °C for a period of 5 h. The materials were polarized at 130, 300 and 400 °C applying a DC electric field of 1 kV/mm, during 1 h. The electric field was maintained until the material was cooled down to room temperature. The electric and piezoelectric response were measured immediately after cooling, after 1 h and after 24 h. The dielectric measurements of materials were performed at different frequencies (0.1 to 100 kHz). The polarized and unpolarized materials were immersed in simulated body fluid (1.5 SBF) for 7 and 19 days. The deposition and growth of hydroxyapatite using the biomimetic method was followed by FTIR and SEM. The polarization effect on the crystalline growth of hydroxyapatite formed from the SBF solution has been demonstrated. The process of biomineralization of HAp on HAp/BTS composites increased considerably with the addition of barium titanate, this effect greatly improved in polarized materials. The typical coral-like morphology characteristic of HAp formation from SBF deposition was observed after 7 days of SBF immersion for polarized composites. Excellent dielectric properties were determined by adding 30% Of BaTiO3, obtaining for these composites dielectric constant values of the order of 20 to 10 kHz, values similar to that of human bones. Therefore, these materials look very promising for bone regeneration.
Dust adhesion physics on photovoltaic surfaces and its application on assisted natural cleaning of solar trackers
Authors: Cruz G A , Vorobiev P
Published: April 2022

Soiling is a problem that affects energy production of solar panels. Dust particles are deposited on the surface of the panel by the wind currents. Adhesion occurs due to Van der Waals forces, depending on the contact area of the tempered glass surface with the dust particle, due to gravitational force acting on the mass of the particles, and due to capillary forces, which are increased with the amount of humidity, depending on the climate. In this project, the positioning capabilities of a solar tracker were used to achieve better assisted natural washing under conditions of weak and heavy rain, using a “passive cleaning” when the rain is intense and an “active cleaning” when the rain is weak. For passive cleaning, the effect of varying the inclination angle while washing and drying was studied and quantified, analysing the formation of stains generated by raindrops drying. It was evident that the higher the angle of inclination the greater the effect of gravity on the drops, facilitating their sliding and falling off the panel, however, it was found that it is possible to carry out passive cleaning at an angle of inclination that does not require prominent deviation from the angle that fits the position of the sun, in fact, it is enough with an inclination angle of 30° to achieve an effective passive cleaning process. In active cleaning, a rocking movement is performed by varying the angle of inclination of the solar tracker with values of + θ and -θ, which increases the contact time of the raindrops with the surface of the solar panel, allowing a better sweep of dust particles and therefore a more complete washing even in light rain conditions. Active cleaning improves the results in surface cleaning in almost 57% when compared to passive cleaning, in light rain conditions.
Developments for enhancing the luminous intensity of LEDs by optimizing their structures
Authors: Liu Zhaojin
Published: April 2022

The brightness enhancement of the light emitting diode (LED) can satisfy the increasing demands of illumination of human beings. However, the low-rate recombination of electron-hole pairs, isotropic nature of the spontaneous emission as well as the large refractive index of the materials used for LEDs usually limits the performance of the light output. Therefore, it is necessary to address these challenges, trying to enlarge the light output power with high optoelectronic efficiency. This review will analysis the factors that can influence the behaviour of the LEDs and the method to overcome these issues by optimizing the structures of epilayers and LED chips.
Research on in the interaction between laser and electron-positron plasma in cone target
Authors: shan Fei , Wang Pengpo , Zhang Pei , Shi Jiahao , Li Dapeng , Hang Xianfeng , Wang Yilei
Published: April 2022

Laser is used to accelerate the electron-positron plasma by ponderomotive force. Due to the electric field, electron and positron will have transverse diffusion in the acceleration. In this paper, a scheme is proposed to get high-energy particle beam by binding electron-positron plasma with hollow gold target. The transverse diffusion is restrained in the gold target. Particles can be continuously accelerated by ponderomotive force and the neutral particle beam is obtained in space. The tight focusing of laser makes the ponderomotive force stronger and stronger in the cone target. The energy gain obtained by the scheme is far beyond the limit of the ponderomotive force, which provides theoretical support for the practical application of electron-positron beam.
Vectorial wavefront holography based on a polarisation-insensitive hologram
Authors: Ren Haoran
Published: April 2022

Polarisation holography generally demands polarisation-sensitive holograms for reconstructing either polarisation-multiplexed holographic images or polarisation-sensitive image channels. To date, polarisation holography is underpinned by the Jones matrix method that uses birefringent holograms, including ultrathin metasurface holograms, limiting the polarisation control to orthogonal polarisation states. Here I introduce a novel concept of vectorial wavefront holography by exploiting the wavefront shaping of a structured vector beam. I will show that a phase hologram can be used to tailor the polarisation interference of a vector beam in momentum space, creating arbitrary polarisation states that include but not limited to the linear, circular, azimuthal, and radial polarisations. This opens an unprecedented opportunity for the multiplexing generation of arbitrary polarisation distributions in a holographic image. The demonstrated vectorial wavefront holography offers flexible polarisation control without using birefringent optical materials, which may find applications in polarisation imaging, holographic encryption, holographic data storage, multi-view displays, holographic Stokesmeter, and polarimetry.
Effect of regression and re-aging treatment on tensile yield strength anisotropy of 7050 aluminum alloy
Authors: Xie Linjun , Yuan Wuhua
Published: April 2022

In this study, the evolution rule of yeild strength and microstructure along the axial, hoop and radial directions of 7050 aluminum alloy ring forging during Regression and re-aging (RRA) heat treatment was studied by using the experimental technology of tensile property test and transmission electron microscope (TEM) and Electron backscatter diffraction (EBSD) observation. During the RRA process, the evolution rule of intragranular and intergranular precipitates along axial, hoop and radial directions of 7050 aluminum alloy ring forging was described by establishing a model. After the pre-aging stage, the yield strength of samples along the axial, hoop and radial directions of forgings shows obvious anisotropy, and the anisotropy decreases gradually after regression and re-aging treatment. The results show that the cause of the larger yield strength anisotropy is the inhomogeneous size and distribution of precipitates after the pre-aging stage; After the regression stage, the cause of the reduction of the yield strength anisotropy is due to the homogeneous distribution of intragranular precipitates; After re-aging treatment, the reasons of further reduction of the yield strength anisotropy are because of more homogeneous distribution of intragranular precipitates and the discontinuous of intergranular precipitates.