bluuebunny/crossref_metadata_2025 huggingface dataset:
Mixed-Mode Electronically-Tunable First-Order Universal Filter Structure Employing Operational Transconductance Amplifiers
Authors: Raj Ajishek
Published: April 2022

In this paper, a new mixed-mode first-order universal filter configuration is presented that employs three operational transconductance amplifiers (OTAs) and one grounded capacitor (eminently suitable for IC chip fabrication). All three first-order generic filter functions, namely low pass filter (LPF), high pass filter (HPF) and all pass filter (APF) in all the four possible modes, namely voltage mode (VM), current mode (CM), transresistance mode (TRM) and transconductance mode (TCM) can be realized. The proposed configuration offers high input impedance and high output impedance. The pole frequency of the filter can be controlled electronically by varying a single transconductance. Nonideal analysis of the proposed filter structure has also been carried out and the results have been compared with those obtained from ideal analysis. The performance of the presented filter configuration has been corroborated through PSPICE simulations as well as experimental results. The various simulation and experimental results validate the practical viability of the proposed configurations.
Towards Fast and Accurate Federated Learning with Non-IID Data for Cloud-Based IoT Applications
Authors: Liu Tian , Ding Jiahao , Wang Ting , Pan Miao , Chen Mingsong
Published: April 2022

As a promising method of central model training on decentralized device data while securing user privacy, Federated Learning (FL) is becoming popular in the Internet of Things (IoT) design. However, when the data collected by IoT devices are highly skewed in a non-independent and identically distributed (non-IID) manner, the accuracy of the vanilla FL method cannot be guaranteed. Although there exist various solutions that try to address the bottleneck of FL with non-IID data, most of them suffer from extra intolerable communication overhead and low model accuracy. To enable fast and accurate FL, this paper proposes a novel data-based device grouping approach that can effectively reduce the disadvantages of weight divergence during the training of non-IID data. However, since our grouping method is based on the similarity of extracted feature maps from IoT devices, it may incur additional risks of privacy exposure. To solve this problem, we propose an improved version by exploiting similarity information using the Locality-Sensitive Hashing (LSH) algorithm without exposing extracted feature maps. Comprehensive experimental results on well-known benchmarks show that our approach can not only accelerate the convergence rate, but also improve the prediction accuracy for FL with non-IID data.
The two constants of spacetime structure and its dynamics
Authors: Dadhich Naresh
Published: April 2022

We would first show that how the two fundamental constants, the velocity of light, [Formula: see text], and the so called, cosmological constant, [Formula: see text], arise from geometric characterization of forcefree state of spacetime. They are the two most fundamental constants as they have been synthesized in the structure of spacetime, no other constant can claim this degree of fundamentalness. Next when spacetime turns inhomogeneous, Einstein gravity arises most naturally from the spacetime geometry without any prescription from outside; i.e. the inverse square law is mandated by the geometry, and not a prescription. It would then suggest that dynamics of a fundamental force should not be prescribed but should perhaps be determined by the geometry of appropriate spacetime manifold.
Null geodesics and shadow of 4D Einstein–Gauss–Bonnet black holes surrounded by quintessence
Authors: Heydari-Fard Malihe , Heydari-Fard Mohaddese
Published: April 2022

We study the properties of the null geodesics of four-dimensional Einstein–Gauss–Bonnet (4D EGB) black holes surrounded by quintessence matter, recently derived by Shah et al. [Phys. Lett. B 818 (2021) 136383]. Due to the quintessence correction, we discuss the radial and nonradial geodesics. For the case of nonradial geodesics we obtain the effective potential, photon sphere and impact parameter associated to the null geodesics in detail. We analyze the different possible orbits of massless particles (i.e. photons) such as unstable circular orbits and unbounded orbits and investigate the role of the Gauss–Bonnet coupling [Formula: see text] and the quintessence parameter q on the null geodesic trajectories. Moreover, we study the effects of the model parameters on the shadow cast by such black holes. The results are compared to that of Schwarzschild black hole with and without quintessence matter and 4D EGB black holes without quintessence. As a physical application of null geodesics, the deflection angle is calculated and the effect of the quintessence matter on it is investigated.
Seismic Retrofit of Existing Critical Structures Using Externally Connected Viscous Dampers
Authors: Lin Wang-Chuen , Wang Shiang-Jung , Hwang Jenn-Shin
Published: April 2022

To seismically retrofit existing critical structures like hospitals, it is not only necessary to guarantee that their performance is superior to that of general structures during and after earthquakes, but it is also very important to minimize the impact on daily operations and on patients during the reconstruction period. A seismic retrofit strategy involving external connections with linear viscous dampers whose damping coefficients are more efficiently distributed is proposed in this study. First, improper designs of added reaction structures and linked viscous dampers are effectively precluded by eliminating those that fall within undesired frequency ratio bands. Then, numerical examples are used to show that hospital structures retrofitted with viscous dampers at all stories and structures with dampers fitted only at lower stories perform satisfactorily. It is also shown that the higher the story linked by viscous dampers, the larger the damping coefficient and damper force required. In order to investigate the damping effect, a uniform distribution (UD) of the damping coefficient at all stories, a distribution based on the kinetic energy at all stories, and a more efficient distribution based on the kinetic energy at critical stories are analytically discussed and numerically examined. It is shown that adopting these three distributions can satisfactorily control performance, while adopting the first and third distributions requires the largest and smallest total damper forces, respectively. Consequently, adopting the distribution based on the kinetic energy at more important stories provides the most cost-effective retrofit strategy.
Zinbiel algebras are nilpotent
Authors: Towers David A.
Published: April 2022

In this paper, we show that every finite-dimensional Zinbiel algebra over an arbitrary field is nilpotent, extending a previous result that they are solvable by other authors.
On triple homomorphisms of Lie algebras
Authors: Jafari Mohammad Hossein , Madadi Ali Reza , Traustason Gunnar
Published: April 2022

Let [Formula: see text] and [Formula: see text] be two Lie algebras over a commutative ring with identity. In this paper, under some conditions on [Formula: see text] and [Formula: see text], it is proved that every triple homomorphism from [Formula: see text] onto [Formula: see text] is the sum of a homomorphism and an antihomomorphism from [Formula: see text] into [Formula: see text]. We also show that a finite-dimensional Lie algebra [Formula: see text] over an algebraically closed field of characteristic zero is nilpotent of class at most [Formula: see text] if and only if the sum of every homomorphism and every antihomomorphism on [Formula: see text] is a triple homomorphism.
On partial augmentations of elements in integral group rings
Authors: Bovdi Victor , Maróti Attila
Published: April 2022

Inner relations are derived between partial augmentations of certain elements (units or idempotents) in group rings.
Subordinate quadratic forms and isometric maps over semirings
Authors: Izhakian Zur , Knebusch Manfred
Published: April 2022

This paper expands the theory of quadratic forms on modules over a semiring [Formula: see text], introduced in [11–13], especially in the setup of tropical and supertropical algebra. Isometric linear maps induce subordination on quadratic forms, and provide a main tool in our current study. These maps allow lifts and pushdowns of quadratic forms on different modules, preserving basic characteristic properties.
Raman and RBS Analysis of Silicon Ion Implanted Gallium Arsenide
Authors: Yadav A. R. , Dubey S. K. , Sulania I.
Published: April 2022

This paper analyzes the effect of 100[Formula: see text]keV silicon negative ion implantation in semi-insulating gallium arsenide sample for the fluences varying between [Formula: see text] and [Formula: see text][Formula: see text]ion[Formula: see text]cm[Formula: see text] using Raman spectroscopy, Rutherford backscattering spectroscopy and Electron spin resonance spectroscopy. The gallium arsenide sample implanted with silicon negative ion for different fluences showed shift in the TO peak position with respect to unimplanted gallium arsenide sample. Increase in the broadening of TO peak was observed in the as-implanted samples, indicating development of stress and phonon confinement due to the incorporation of silicon in gallium arsenide crystal lattice. Annealing of as-implanted samples showed stress relaxation. Increase in RBS backscattering yield was observed in the as-implanted samples. Annealing of as-implanted (with high fluence) sample showed flat RBS yield response. ESR measurement study revealed restructuring of defects in the gallium arsenide sample implanted with fluence of [Formula: see text][Formula: see text]ion[Formula: see text]cm[Formula: see text] after annealing to the temperature of [Formula: see text]C.
Study of the Transition State of SnO2 Cluster with NO2 Gas Molecule via Density Functional Theory
Authors: Jafer Nabaa F. , Hussein Mohammed T.
Published: April 2022

Density functional theory (DFT) with B3LYP level and 6-311G[Formula: see text] basis sets for light atoms like N and O and SDD basis sets for heavy atoms like Sn is used to examine the interaction of tin dioxide nanocrystals with nitrogen dioxide as a function of temperature from 273[Formula: see text]K to 373[Formula: see text]K through a Gaussian 09W software program. Gibbs free energy, enthalpy, and entropy of activation and reaction are calculated. The situation of transition of SnO2 clusters toward nitrogen dioxide is investigated. According to the findings, the activation energy of SnO2 clusters with nitrogen dioxide increases as the temperature rises (in negative value). Gauss view 05 was used to investigate the geometrical structure of SnO2 cluster nanostructures and the nitrogen molecule. Spectroscopic analysis of the force constant, IR, Raman scattering and reduced masses as a function of frequencies had been investigated and compared to the experimental value of longitudinal optical (LO) modes of 690[Formula: see text]cm[Formula: see text] for SnO2 and 1600[Formula: see text]cm[Formula: see text] for NO2.
Al Modified Orthorhombic Molybdenum Trioxide as NO2 Gas Sensor
Authors: Halwar Dharma K. , Deshmane Vikas V. , Patil Arun V.
Published: April 2022

The aim of this study is to prepare thick films of MoO3 with various weight percentages of aluminum dopant and study its gas sensing characteristics. The thick films were prepared on alumina substrate using easily reproducible, cost-effective screen printing method. The films were characterized using XRD, FESEM, EDS and static gas sensing apparatus. The XRD analysis confirmed the presence of Molybdenum trioxide (JCPDS 05-0508) and aluminum (JCPDS 31-0026). The XRD conveyed that aluminum has occupied an interstitial position and got oxidized to alumina. FESEM showcased the characteristic lamellar structure of MoO3 with voids. The EDS data showed that films were having oxygen excess and the oxygen vacancies increased with aluminum doping percentage. Resistivity and activation energies decreased first and then increased with dopant (aluminum) percentage. The Al5 films showed a minimum resistivity ([Formula: see text]m) and activation energy (0.19 eV). The TCR had a negative value for all five films supporting n-type semiconductor behavior of the films. The Al5 films showed 84.3% sensitivity to 1000 ppm of NO2 gas at 200°C. Authors discussed adsorption-desorption based gas sensing mechanism in detail. Research work tested efficient NO2 gas sensor using aluminum-doped MoO3 thick films.
Disparity estimation based on fusion of vision and LiDAR
Authors: Ma Chao , Pei Shanshan , Sun Guoliang , Meng Ran , Luo Kun
Published: April 2022

Advanced driver assistance systems improve driving safety and comfort by applying onboard sensors to collect environmental data, analyze environmental data and decision making. Therefore, advanced driver assistance systems have high requirements for distance perception of the environment. Perceptual sensors commonly used in traditional solutions include stereo vision sensors and the Light Detection and Ranging (LiDAR) sensors. This paper proposes a multi-sensing sensor fusion method for disparity estimation, which combines the perceptual data density characteristics of stereo vision sensors and the measurement accuracy characteristics of LiDAR sensors. The method enhances the sensing accuracy by ensuring high-density sense, which is suitable for distance sensing tasks in complex environments. This paper demonstrates with experimental results on real data that our proposed disparity estimation method performs well and is robust in different scenarios.
Responsive Policy Decisions for Improving the Accuracy of Medical Data Analysis in Healthcare-Based Human–Machine Interaction Systems
Authors: Altameem Ahmed , Shaheer Akhtar M. , Altameem Torki , Fouad H. , Anil Sukumaran , Kim Young Soon , Youssef Ahmed E.
Published: April 2022

Human–computer interaction (HCI) is deployed in various real-time applications, including healthcare, for automated patient response. In such applications, robot-assisted interactive scenarios are modeled to handle patient queries and provide precise information. Timely query sensing and accurate data analysis are required to achieve accurate patient responses. In this study, responsive policy decision (RPD) using manifold mediator learning (MML) is introduced to improve data detection accuracy and accuracy in robot-assisted HCI applications. The initial decision-making process in data analytics is based on interaction stages and medical data detection. After identifying the most appropriate policy, respondents are provided with time-based responses based on the patient’s queries. When it comes to improving the accuracy of data analysis decisions, machine learning uses policies based on interaction stages and previous state efficiency of HCI responses. The experimental analysis proves the reliability of the proposed method by improving the accuracy of data analysis and reducing its complexity and response time for the varying queries and time intervals.
Relativistic deformed kinematics: From flat to curved spacetimes
Authors: Relancio José Javier
Published: April 2022

Doubly special relativity has been studied for the last 20 years as a way to go beyond the special relativistic kinematics, trying to capture residual effects of a quantum gravity theory. In particular, in doubly special relativity, the Einstenian relativity principle is generalized, adding to the speed of light another relativistic invariant, the Planck energy. There are several papers in the literature showing a connection between this deformed kinematics and a curved momentum space. Here we review how such kinematics can be derived from geometrical ingredients in a rigorous way, and how they can be generalized when regarding a curved spacetime. For the last aim, it is mandatory to consider a particular geometry for all phase-space variables, the so-called generalized Hamilton spaces. This construction allows us to define a spacetime in these theories, which in fact depends on the momenta. Then, starting from such a momentum dependent metric, we also revise several concepts of general relativity, with the final aim of establishing a self-consistent geometrical structure from which quantum gravity phenomenology can be explored.
Product manifolds as realizations of general linear symmetries
Authors: Lawrence Tom
Published: April 2022

This paper considers the relationship between geometry, symmetry and fundamental interactions — gravity and those mediated by gauge fields. We explore product spacetimes which (a) have the necessary symmetries for gauge interactions and four-dimensional gravity and (b) reduce to an [Formula: see text]-dimensional isotropic universe in their flat space limit. The key technique is looking at orbits of the operator form of symmetric rank-two tensors under changes of coordinate system. Orbits containing diagonal matrices are seen to correspond to product manifolds. The [Formula: see text] symmetry of the decompactified universe acts nonlinearly on such a product spacetime. We explore the resulting Kaluza–Klein theories, in which the internal symmetries act indirectly on space of the extra dimensions, and give two examples: a six-dimensional model in which the gauge symmetry is [Formula: see text] and a seven-dimensional model in which it is [Formula: see text]. We identify constraints that can be placed on any rank-two symmetric tensor to obtain such spacetimes: relationships between polynomial invariants. The multiplicities of its eigenvalues determine the dimensionalities of the factor spaces and hence the gauge symmetries. If the tensor in question is the Ricci tensor, other than two-dimensional factor spaces all the factor spaces are Einstein manifolds. This situation represents the classical vacuum of the Kaluza–Klein theory.
Confined chiral dynamo action in torsional dilatonic DWs from CME discontinuities
Authors: Garcia de Andrade L. C.
Published: April 2022

In this paper, spin polarized domain walls in Einstein–Cartan (EC) gravity have been recently investigated [L. C. Garcia de Andrade, Einstein–Cartan non-supersymmetric dynamo walls, Ann. Phys. 432 (2021).], where the spin polarizes along the direction orthogonal to planar domain wall. In this case, dynamo effects may appear on the wall. Moreover, dilatonic domain walls (DDWs) have shown to be responsible for inflating DWs in EC gravity, where DWs were non-magnetized [L. Garcia de Andrade, Axial and chiral anomalies in Riemann–Cartan spacetime black holes and electrodynamics, Class. Quantum Grav. 16 (1999) 2097–2103.]. In this paper, our goal is to show that when we consider a magnetized DW in the EC–Maxwell cosmology, the dilaton potential in the form of a DDW potential expressed in terms of torsion and the magnetic energy density may drive dynamo effects. Analytical solution of the dynamo equation shows that depending on the handness of DDW metric, the magnetic fields are amplified by dynamo action. From the coupled system of ECM and dilaton field equations, we find a relation between the magnetic energy density of [Formula: see text] and the DDW torsion of [Formula: see text] which leads to a thin DDW thickness of [Formula: see text]. For a galactic magnetic field, energy density of [Formula: see text] leads to a thickness of [Formula: see text], a much thinner DDW. For galactic dynamo amplification, the ratio r between the magnetic energy density and photon energy density is around [Formula: see text]. From this ratio, a relation between photon mass density and torsion is obtained. Chiral Magnetic effect (CME), torsion and magnetic discontinuities along the wall are investigated. Magnetic field discontinuity across the wall allows us to understand why the magnetic fields at DDW must be located along the wall since the orthogonal magnetic field may vanish.
A note on Einstein and Tolman energy-momentum complexes in general relativity
Authors: Ali Ahmad T. , Khan Suhail , Gouda Ashraf A.
Published: April 2022

In this paper, it is shown that energy-momentum tensors defined by Einstein and Tolman in the general theory of relativity are same for any spacetime. It is also shown that in general theory of relativity, the Einstein super-potential [Formula: see text] and Tolman super-potential [Formula: see text] are different in general. Four different examples are also given to ensure the validity of our established statements. In all these examples, we observed that the values of the Einstein [Formula: see text] and Tolman [Formula: see text] super-potentials are different but the Einstein and Tolman energy-momentum distributions come out as same. All the results obtained in these four examples are consistent with the already obtained results in the literature.
Purchasing Warning Mechanism Based on Text Sentiment Analysis
Authors: Zhu Yuxuan , Hu Junjie , Li Bingjie
Published: April 2022

Under the background of economic globalization and professional division of labor, each link of enterprise supply chain management is facing more and more risks. Over the past two years, due to the turbulent situation at home and abroad and the repeated outbreaks of COVID-19 around the world, the normal procurement work has been greatly affected which means the purchase cost increases and even out of stock occur. The rapid development of big data, artificial intelligence and other technologies has brought new tools and means for enterprise risk management. This paper focuses on the procurement work in enterprise operation management, and analyzes how to obtain procurement related news or current review texts, and analyzes their emotional tendency to evaluate and quantify the public opinion risk of procurement by natural language processing (NLP), denoted as NLP. By combing the crawled text data, we add some purchase related words to a corpus which can analyze good and bad emotions and train a model. We use the model to score the manually labeled text data to determine the optimal threshold of positive news and negative news. Under this threshold, the accuracy of text emotion analysis is 85.4%. Finally, through a case analysis, we show the specific implementation of procurement public opinion risk score evaluation.
A deep recursively learning LSTM model to improve cyber security botnet attack intrusion detection
Authors: Padmavathi B. , Muthukumar B.
Published: April 2022

The occurrence of botnets over the network is crucial as it shows advent effect on various applications like finance, cyber-security, and healthcare application. Botnets are refined and more dangerous in their functionality over the network model. Most of the prevailing models and flow- and rule-based models feel challenging to predict the bot functionalities in a preventive manner. Therefore, the modeling of efficient and automated botnet detection approaches is highly essential. This research concentrates on modeling a novel botnet detection approach based on the recursively analyzing the flow of features of the network nodes spatially and temporally where the attack samples are intra-dependent time-series data. The hierarchical structural design of the network helps to integrate various levels of feature information and learns the spatial and temporal information automatically among the adjacent network connection. This process is carried out by the proposed architectural model known as Recursively Learning Long Short-Term Memory over spatial and temporal ([Formula: see text]. Thus, the bot activities are detected by recursively analyzing the limited number of nodes. The [Formula: see text] model is modeled to improve the efficiency of the network by eliminating unnecessary activities. The proposed model is validated using the online accessible CTU-13 dataset and benchmarked against the prevailing classification approaches for botnet detection. The simulation is done in a MATLAB environment, and the outcomes work efficiently and evaluated with prevailing models to project the significance of the [Formula: see text] model.
Public and Private Information: Firm Disclosure, SEC Letters, and the JOBS Act
Authors: Agarwal Sumit , Gupta Sudip , Israelsen Ryan
Published: April 2022

This paper examines the impact of the recently passed Jumpstart Our Business Startups (JOBS) Act on the behavior of market participants. Using the JOBS Act — which relaxed mandatory information disclosure requirements — as a natural experiment on firms’ choices of the mix of hard, accounting information and textual disclosures, we find that relative to a peer group of firms, initial public offering (IPO) firms reduce accounting disclosures and change textual disclosures. Because it allows a partial revelation of IPO quality, only textual disclosures affect underpricing. We also find that the Securities and Exchange Commission (SEC) changes its behavior post-JOBS Act in responding to draft registration statements. Specifically, the SEC’s comment letters to firms are more negative in tone, and more forceful in their recommendations, focusing on quantitative information. Finally, under the JOBS Act, investors place more emphasis on the information produced by the SEC when pricing the stock. Returns following public release of the letters vary by about 4% based on letter tone.
Edge fluctuations for random normal matrix ensembles
Authors: García-Zelada David
Published: April 2022

A famous result going back to Eric Kostlan states that the moduli of the eigenvalues of random normal matrices with radial potential are independent yet non-identically distributed. This phenomenon is at the heart of the asymptotic analysis of the edge, and leads in particular to the Gumbel fluctuation of the spectral radius when the potential is quadratic. In the present work, we show that a wide variety of laws of fluctuation are possible, beyond the already known cases, including for instance Gumbel and exponential laws at unusual speeds. We study the convergence in law of the spectral radius as well as the limiting point process at the edge. Our work can also be seen as the asymptotic analysis of the edge of two-dimensional determinantal Coulomb gases and the identification of the limiting kernels.
Information: 'I' vs. 'we' vs. 'they'
Authors: von Hanxleden Reinhard
Published: April 2022

Seeking a balance between protecting and using personal data.
Meaning and context in computer programs
Authors: Videla Alvaro
Published: April 2022

Sharing domain knowledge among programmers using the source code as the medium.
Parametric Timed Pattern Matching
Authors: Waga Masaki , André Étienne , Hasuo Ichiro
Published: April 2022

Given a log and a specification, timed pattern matching aims at exhibiting for which start and end dates a specification holds on that log. For example, “a given action is always followed by another action before a given deadline”. This problem has strong connections with
monitoring
real-time systems. We address here timed pattern matching in the presence of an
uncertain
specification, i.e., that may contain timing parameters (e.g., the deadline can be uncertain or unknown). We want to know for which start and end dates, and for what values of the timing parameters, a property holds. For instance, we look for the minimum or maximum deadline (together with the corresponding start and end dates) for which the property holds. We propose two frameworks for
parametric
timed pattern matching. The first one is based on parametric timed model checking. In contrast to most parametric timed problems, the solution is effectively computable. The second one is a
dedicated
method; not only we largely improve the efficiency compared to the first method, but we further propose optimizations with skipping. Our experiment results suggest that our algorithms, especially the second one, are efficient and practically relevant.
Modern tech can't shield your secret identity
Authors: Hong Jason
Published: April 2022

The
Communications
website, http://cacm.acm.org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of
Communications
, we'll publish selected posts or excerpts.

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Follow us on Twitter at http://twitter.com/blogCACM

http://cacm.acm.org/blogs/blog-cacm

Jason Hong considers how modern computing technologies would undermine superheroes' anonymity.
Raising robovoices
Authors: Mone Gregory
Published: April 2022

New systems can model and synthesize voices, and even translate them into other languages.
Two paths for digital disability law
Authors: Reid Blake
Published: April 2022

Understanding the legal drivers of efforts to make technology accessible.
Meat Consumption and Sustainability
Authors: Parlasca Martin C. , Qaim Matin
Published: April 2022

Meat has become a controversial topic in public debates, as it involves multiple sustainability dimensions. Here, we review global meat consumption trends and the various sustainability dimensions involved, including economic, social, environmental, health, and animal welfare issues. Meat has much larger environmental and climate footprints than plant-based foods and can also be associated with negative health effects. Technological options can help to increase the sustainability of meat production, but changes in consumption are required as well. At least in high-income countries, where people consume a lot of meat on average, notable reductions will be important. However, vegetarian lifestyles for all would not necessarily be the best option. Especially in low-income countries, nutritious plant-based foods are not available or affordable year-round. Also, livestock production is an important source of income for many poor households. More research is needed on how to promote technological and behavioral changes while managing sustainability trade-offs.
Composition Formula for Saigo Fractional Integral Operator Associated with V‐Function
Authors: Chandak Sunil , Alaria Anita , Shimelis Biniyam
Published: April 2022

In this study, we form integral formulas for Saigo’s hypergeometric integral operator involving V‐function. Corresponding assertions for the classical Riemann–Liouville (R‐L) and Erdélyi–Kober (E‐K) fractional integral operator are extrapolated. Also, by putting in the transformations of Beta and Laplace, we can establish their composition formulas. By selecting the appropriate parameter values, the V‐function may be reduced to a variety of functions, including the exponential function, Mittag–Leffler, Lommel, Struve, Wright’s generalized Bessel function, and Bessel and generalized hypergeometric function.
Construction of Legal Reporting Information Platform Based on Natural Optimization Algorithm
Authors: Feng Xiaojie , Zhou Yi
Published: April 2022

Natural optimization algorithms have attracted much attention from researchers because they can simulate or explain certain prediction processes. The traditional method of predicting the factor value of legal reporting information based on causal window has shortcomings caused by individual weak classifiers, so the prediction adaptability is poor. Aiming at the construction of the early warning model of legal reporting information, this paper proposes a semi-integrated natural optimization algorithm. The natural optimization algorithm uses the variance of the supporting area factor to characterize the smoothness of the factor neighborhood and uses the optimal threshold parameter for factor classification. It solves the capacity-distortion problem of the hidden algorithm of traditional legal reporting information. The experimental results show that the natural optimization algorithm has better performance. The classification error rate in the question is reduced to 0.137, which effectively promotes the practicability of classification prediction of legal reporting information.
Design and Optimization of a Triangular Shear Piezoelectric Acceleration Sensor for Microseismic Monitoring
Authors: Shi Yannan , Jiang Shuaishuai , Liu Yang , Wang Yiying , Qi Penglei
Published: April 2022

Aiming at the characteristics of low sensitivity and narrow frequency range of existing microseismic monitoring sensors for mine water hazard prevention and control, a piezoelectric acceleration sensor for microseismic monitoring based on a kind of triangular shear structure is proposed. Firstly, the structure of the triangular shear piezoelectric acceleration sensor is designed, and its dynamic model is built. The structural and material parameters related to natural frequency and sensitivity are analyzed. Then, the selection of piezoelectric ceramic materials is discussed. The parametric design of the designed sensor is carried out, and its finite element structural model is built by ANSYS. The modal analysis, resonance response analysis, and piezoelectric analysis of the designed sensor are carried out. The simulation results indicate that the working frequency and sensitivity of the designed sensor meet the requirements of microseismic monitoring. Response surface optimization is adopted to analyze the influence of sensor element design variables on the sensitivity and resonant frequency of the designed sensor. The reoptimized design of the reference sensor improves the resonant frequency of the designed sensor by 9.46% and the charge sensitivity by 18.96%. Finally, the designed sensor is calibrated, and the microseismic signal detection experiment is carried out. The results indicate that the resonant frequency of the designed sensor is 6150 Hz, the working frequency is 0.1-2050 Hz, and the charge sensitivity is 1600 pC/g. The sensor can detect microseismic signals with a wide frequency range and high sensitivity.
High-Resolution Computer Tomography Image Features of Lungs for Patients with Type 2 Diabetes under the Faster-Region Recurrent Convolutional Neural Network Algorithm
Authors: He Yumei , Tan Juan , Han Xiuping
Published: April 2022

The objective of this study was to adopt the high-resolution computed tomography (HRCT) technology based on the faster-region recurrent convolutional neural network (Faster-RCNN) algorithm to evaluate the lung infection in patients with type 2 diabetes, so as to analyze the application value of imaging features in the assessment of pulmonary disease in type 2 diabetes. In this study, 176 patients with type 2 diabetes were selected as the research objects, and they were divided into different groups based on gender, course of disease, age, glycosylated hemoglobin level (HbA1c), 2 h C peptide (2 h C-P) after meal, fasting C peptide (FC-P), and complications. The research objects were performed with HRCT scan, and the Faster-RCNN algorithm model was built to obtain the imaging features. The relationships between HRCT imaging features and 2 h C-P, FC-P, HbA1c, gender, course of disease, age, and complications were analyzed comprehensively. The results showed that there were no significant differences in HRCT scores between male and female patients, patients of various ages, and patients with different HbA1c contents (

P
>
0.05

). As the course of disease and complications increased, HRCT scores of patients increased obviously (

P
<
0.05

). The HRCT score decreased dramatically with the increase in the contents of 2 h C-P and FC-P after the meal (

P
<
0.05

). In addition, the results of the Spearman rank correlation analysis showed that the course of disease and complications were positively correlated with the HRCT scores, while the 2 h C-P and FC-P levels after meal were negatively correlated with the HRCT scores. The receiver operating curve (ROC) showed that the accuracy, specificity, and sensitivity of HRCT imaging based on Faster-RCNN algorithm were 90.12%, 90.43%, and 83.64%, respectively, in diagnosing lung infection of patients with type 2 diabetes. In summary, the HRCT imaging features based on the Faster-RCNN algorithm can provide effective reference information for the diagnosis and condition assessment of lung infection in patients with type 2 diabetes.
Image Processing and Multi-Instance Learning-Based Recognition of Abnormal Behavior in Integrated Pipe Corridors
Authors: Xiao Peng , Zhang Zhenji , Kang Laisong
Published: April 2022

The use of big data technology to efficiently access valid corridor monitoring information embedded in unstructured data and to achieve fast and effective processing of video surveillance data is an effective means of monitoring abnormal behavior in integrated corridors. The study first divides the longer surveillance video into multiple parts and then extracts functions for each part based on CenterNet. Inspired by the area under the curve concept, MIAUC was further applied to a loss function model, which encouraged higher scores for anomalous segments compared to normal segments. Also, by formulating anomaly detection as a regression problem, methods based on weakly labeled training data will consider both normal and anomalous behavior for anomaly detection. To alleviate the difficulty of obtaining accurate segment-level labels, Multiple Instance Learning (MIL) is utilized to learn the anomaly model and detect video segment-level anomalies during testing. The results of the research enable effective 24/7 monitoring, storage functions, intrusion detection functions, and emergency linkage functions.
A Method of Key Posture Detection and Motion Recognition in Sports Based on Deep Learning
Authors: Pan Shaohong
Published: April 2022

Moving target recognition and analysis is an important research direction in the field of computer vision, which is widely used in our life, such as intelligent robot, video surveillance, medical education, sports competition, and national defense security. By analyzing the video of weightlifting, this paper extracts the key postures of athletes’ training, so as to assist coaches to train athletes more professionally. Based on DL (Deep Learning), a key pose extraction method of sports video (RoI_KP for short) based on classified learning of regions of interest is proposed. By fine-tuning CNN (Convolutional Neural Network), a network model suitable for video classification of weightlifting in the region of interest is obtained. Finally, according to the classification results, the selection strategy of classification results is designed to extract key poses. According to the characteristics of different modal information, different DNN (deep neural network) is adopted, and various depth networks are combined to mine the multi-modal spatio-temporal depth features of human movements in video. Experimental results show that the method proposed in this paper is very competitive.
Innovation and Development of University Education Management Informationization in the Big Data Environment
Authors: Li Xiaojun
Published: April 2022

With the arrival of the big data era, the role of big data can be fully utilized, and the comprehensive data evaluation is carried out to perform education information evaluation. In the general circumstance of computerized learning, college teaching regulation has new features and novel orientations. Along with the speedy progression of sci-tech, the pace of dissemination of data is continuously quickening, and it is being increasingly easy for the public to interact and carry on with their lives. Because people use the network to access a variety of data information, the system cannot handle huge amounts of data; this is the cause of the era. In the process of the comprehensive approach of the information age, with the impact of the Age of Big Data, the administration of intelligence in universities has transformed. Big Data InfoTech has infiltrated into all realms of community lifestyle. How to cope with the transformation of informationization of university education management in the era is a serious challenge for relevant personnel. This study begins by discoursing the essential implication of big data, followed by a diagnosis of the questions involved in the establishment of computerization in high schools under the environment of big data, comprising the imminent solutions to the dilemmas in collegiate education maintenance, the issues raised by privatization in high schools, and the strategies for education management. This is followed by the proposal of the innovative educational administration informationization development trend in the big data context. In this research, there are 11 professors in the expert group, accounting for 44%, 8 associate professors, accounting for 32%, and 6 lecturers or below, accounting for 24%. This study makes full use of a large number of procedural data generated in educational management activities to achieve an efficient, comprehensive, accurate, and objective evaluation, which provides strong technical support for educational management informatization evaluation.
Gender Disparities in Students’ Entrepreneurial Self-Efficacy (ESE) with Various Areas
Authors: Pandang Abdullah , Umar Nur Fadhilah , AkhmadHarum  , Hajati Kartika , Hamidi Bahramuddin
Published: April 2022

Previous research showed that entrepreneurial self-efficacy (ESE) plays an essential role in the behavior and success of a person’s career in entrepreneurship. On the other hand, various reports also showed that women’s participation in entrepreneurial work is still meager compared to that of men. The research examined differences in ESE and distribution among male and female students in various majors in vocational high schools from a region with a dominant ethnicity, namely, Bugis-Makassar, namely, Makassar City. This research is aimed at determining the differences between male and female students’ entrepreneurial self-efficacy (ESE) from various areas of expertise at vocational high schools in Makassar. This study consisted of 812 students (331 males and 481 females), representing seven areas of expertise. They were selected using a multistage cluster sampling technique from 11 vocational high schools in Makassar, Indonesia. The applied ESE instrument was adapted from the Entrepreneur Self-Efficacy Scale. Data were analyzed using descriptive and inferential analyses, i.e., MANOVA and independent samples

T

-test. The results indicated that gender segregation is still high in the distribution of students. Furthermore, the disparity of ESE is found between male and female students in various areas of expertise at vocational high schools.
Dermoscopic Findings of Discoid Lupus Erythematosus Involving the Eyelids
Authors: Cortez de Almeida Rita Fernanda , Ferreira Bianca de Franco Marques , Melo Daniel Fernandes , Benez Marcela , Vincenzi Colombina , Starace Michela , Tosti Antonella
Published: April 2022

Introduction: Although facial involvement in discoid lupus erythematosus (DLE) is common, eyelid involvement is atypical. Identifying this condition is challenging due to misdiagnosis, and it is essential to avoid potential deformities of the eyelid margin. Case Presentation: We, herein, report the dermoscopic findings in 2 female patients with a confirmed diagnosis of DLE who presented eyelids involvement. Discussion/Conclusion: This study highlights the importance of performing a dermoscopy examination to help physicians obtain an early diagnosis of DLE.
Effect of Local Corticosteroid Administration on CD8+CD25+Foxp3+ Tregs in Neutrophilic CRSwNP
Authors: Lin Lin , Lan Jing , Dai Fei , Wei Jinjin , Chen Zheng
Published: April 2022

Introduction: CD8+CD25+Foxp3+ regulatory T cells (Tregs) play an important role in human’s immune tolerance. The study was aimed to assess the influence of budesonide nasal spray on CD8+CD25+Foxp3+ Tregs and to evaluate their cellular functions in neutrophilic chronic rhinosinusitis with nasal polyps (CRSwNPs). Methods: Fifteen patients with neutrophilic CRSwNPs were enrolled and received physiological saline or budesonide nasal spray treatment (Saline or Budesonide group) for 3 months. Nasal tissue samples were obtained from normal subjects or those patients and cultured in vitro. CD8+CD25+Foxp3+ Tregs were separated from normal or NP tissues and also cultured in vitro. Then interleukin (IL)-10 and its mRNA were evaluated in the above cell cultures. The cells were applied into NP cultures. Finally, myeloperoxidase (MPO), interferon (IFN)-γ, IL-1β, and tumor necrosis factor (TNF)-α were assessed in the tissue cultures. Results: CD8+CD25+Foxp3+ Tregs decreased in NP tissues. Budesonide administration did not enhance the percentage of these cells in polypoid tissues. IL-10 and its mRNA were increased in the above cell cultures from NPs. However, there were no statistical differences between the two treatments in the IL-10 expression. Additionally, levels of MPO, IFN-γ, IL-1β, and TNF-α were totally elevated in NP tissue cultures and reduced after the administration of CD8+CD25+Foxp3+ Tregs. However, there were no significant differences in concentrations of these mediators between these two groups of the CD8+CD25+Foxp3+ Tregs treatment in vitro. Conclusion: The findings indicate that CD8+CD25+Foxp3+ Tregs might regulate the neutrophilic inflammation, and budesonide nasal spray therapy could not ameliorate the inflammation in neutrophilic CRSwNPs.
Comparison between Amplatzer and Watchman Left Atrial Appendage Closure Devices for Stroke Prevention in Atrial Fibrillation: A Systematic Review and Meta-Analysis
Authors: Qiao Jianzhong , Zhang Bin , Wang Jie , Pan Lingxin , Cheng Tieniu , Wang Yuan , Xiong Enlai
Published: April 2022

Introduction: The Amplatzer and Watchman left atrial appendage closure (LAAC) devices are the two most frequently used devices for LAAC devices worldwide. This meta-analysis aimed to compare the safety and efficacy of the two devices. Methods: We searched the PubMed, EMBASE, and the Cochrane Library for studies up to February 6, 2022 that compared the safety and efficacy of the Amplatzer and Watchman devices. Results: Fifteen studies including 2,150 patients in randomized controlled trials and 2,526 patients in observational studies were included in the meta-analysis. Amplatzer device was associated with higher rates of major procedure-related complications (odds ratio [OR]: 1.99, 95% confidence interval [CI]: 1.45–2.74, p < 0.0001) and device embolization (OR: 1.99, 95% CI: 1.09–3.64, p = 0.03). However, Amplatzer device had lower rates of total peridevice leak (PDL) (OR: 0.48, 95% CI: 0.27–0.83, p = 0.009), significant PDL (OR: 0.27, 95% CI: 0.12–0.57, p = 0.0007) and device-related thrombus (DRT) (OR: 0.67, 95% CI: 0.48–0.95, p = 0.02). No statistical differences were observed between the two devices in other safety and efficacy endpoints, such as pericardial effusion, cardiac tamponade, air embolism, vascular complications, ischemic stroke/transient ischemic attack (TIA), hemorrhagic stroke, all-cause death, cardiovascular death, and bleeding. Conclusions: Amplatzer LAAC device was associated with higher rates of major procedure-related complications, especially in device embolization. Watchman LAAC device was associated with higher rates of PDL and DRT. There were no significant differences between two devices in ischemic stroke/TIA, hemorrhagic stroke, all-cause death, cardiovascular death, and bleeding.
High Values of Drain Fluid Epidermal Growth Factor and Transforming Growth Factor-Beta Are Associated with the Development of Pancreatic Fistula after Pancreatoduodenectomy
Authors: Marchegiani Giovanni , Perri Giampaolo , Giovinazzo Francesco , Zanini Sara , Turri Giulia , Innamorati Giulio , Salvia Roberto , Bassi Claudio
Published: April 2022

Introduction: Postoperative inflammatory response may act as a major determinant of anastomotic failure after pancreaticoduodenectomy. In this pilot study, we investigated the potential role of drain fluid cytokines in predicting postoperative pancreatic fistula (POPF). Methods: Drain fluid TGF-β, IGF-1, EGF, and IL-6, together with serum amylase and drain fluid amylase, were measured on POD1 and correlated with the development of POPF. Results: The study population consisted of 66 patients. POPF and Clavien-Dindo ≥3 morbidity rates were 12.1% and 9.1%, respectively. Patients developing POPF presented significantly higher values of POD1 serum amylase level (477 vs. 54 UI/L, p < 0.001), drain fluid amylase (7,500 vs. 127 UI/L, p < 0.001), TGFβ (94 vs. 40 pg/g, p = 0.045), and EGF (17 vs. 13, p = 0.015). There were no differences in terms of IGF-1 and IL-6 values. Conclusion: Assessing the local inflammatory response after pancreatoduodenectomy could represent a promising field of research since both TGFβ and EGF seem to be associated with the occurrence of POPF.