bluuebunny/crossref_metadata_2025 huggingface dataset:
Vibration Control of Coupled Wind Tower–Nacelle–Blade System
Authors: Martins Yuri L. D. , Prado Zenon J. G. Del , Ávila Suzana M. , de Morais Marcus V. G.
Published: July 2022

Wind turbines are slender and flexible structures which can undergo large amplitude vibrations when subjected to external loads and, an important way to reduce these excessive vibrations is to apply structural control. In this work, the vibration control of the coupled wind tower–blade system subjected to external lateral loads and rotating blade is studied. To model the tower and blade, the nonlinear Euler–Bernoulli beam theory was applied, and the structural control device considered is a nonlinear inverted tuned mass damper pendulum (ITMDP), located at the top of the tower. The Rayleigh–Ritz method, together with Hamilton’s principle, is applied to obtain a set of coupled nonlinear ordinary differential equations of motion which are in turn solved by the Runge–Kutta method. First, the dynamic instability of the system is studied by considering the variation of the natural frequencies of the tower, as a function of the speed of rotation of the blade and the veering phenomenon is observed. The optimum parameters for the ITMDP are obtained and, a nonlinear dynamic analysis is performed to evaluate the influence of the tuned mass damper (TMD) in the nonlinear regime, by obtaining the time responses, resonance curves, Poincaré maps and basins of attraction. The obtained results show the importance of considering the coupled system and the good performance of the structural control in the dynamic behavior of the system.
Vibration Response Analysis of Tapered Porous FGM Plate Resting on Elastic Foundation
Authors: Kumar V. , Singh S. J. , Saran V. H. , Harsha S. P.
Published: July 2022

This paper attempts to demonstrate the vibration response of porous Functionally Graded Material (FGM) plate with variable thickness. For the first time, the porous tapered FGM plate being considered is mathematically modeled and assumed to be resting on a linear, parabolic, sinusoidal, and exponential varying Winkler’s elastic foundation. The even and uneven porosity distribution as a micro-defect is assumed in a tapered FGM plate that varies according to well-defined mathematical rules. The tapered FGM plate, across the edges, is supported with various boundary conditions. Simple Power (P-) and Sigmoid (S-) Law have been chosen for the homogenization of material properties that are tailored in the thickness direction. First-order shear deformation theory (FSDT) is applied to describe the displacement function for computing the strain field. The variational approach has been used to establish the formulation for free vibration response. The equation of motion has been derived using Hamilton’s principle and solved by implementing Galerkin Vlasov’s method. Parametric studies on elastic foundations have been done to explore the results and relevance to the real problems. It was observed that variable foundation has a significant effect on the tapered FGM plate rather than the tapered homogenous plate. In addition, it was witnessed that the effect of variable foundation effect diminishes as a constraint on the edges of the tapered FGM plate increases. Also, some benchmark results based on the porosity effect and the influence of variable elastic foundations are exhibited in this study for future reference.
Direct Prediction Method for Semi-Rigid Behavior of K-Joint in Transmission Towers Based on Surrogate Model
Authors: Tang Zhengqi , Li Zhengliang , Wang Tao
Published: July 2022

The assembled tube-gusset K-joint by bolts is a commonly used connection form in steel tubular transmission towers. At present, main existing research or design codes for steel tubular transmission towers regard this K-joint as either rigid or pinned connections, which do not consider the semi-rigid behavior of K-joint. In this paper, the semi-rigid behavior of K-joint in steel tubular transmission towers is investigated and a direct prediction (DP) method is proposed to evaluate the semi-rigid behavior of K-joints based on the support vector regression (SVR) model, especially to predict the moment–rotation curve of semi-rigid K-joints. First, the establishment and validation of the finite element (FE) model of semi-rigid K-joints are conducted. Second, a dataset of 144 samples generated by the FE model is used to train and test the SVR model. Finally, the accuracy assessment of the proposed DP method and comparison with other existing methods, including the Kishi–Chen model, EC3 model and ANN-based two-step prediction method, are presented. The accuracy assessment shows that predicted values of the proposed DP method based on the SVR model exhibit good agreement with the numerical analysis values, which indicates the quite high accuracy of this method. Additionally, the comparison reveals that the proposed DP method based on the SVR model for predicting moment–rotation curves is rather more accurate than other aforementioned methods. Therefore, the proposed DP method based on the SVR model is of high reliability in predicting the semi-rigid behavior of K-joints in steel tubular transmission towers, which affords an alternative way for further engineering analysis and initial design purposes.
Nonlinear Dynamic Behavior of a Generally Restrained Pre-Pressure Beam with a Partial Non-Uniform Foundation of Nonlinear Stiffness
Authors: Zhao Yuhao , Du Jingtao , Chen Yilin , Liu Yang
Published: July 2022

For some transmission shafting, nonlinear supports are connected to beam structures through the pattern of the contact surface. Nonlinear foundations are typically installed to the beam structure for a limited range. The unsuitable installation mode of nonlinear foundations will make the parameters of nonlinear foundations no longer uniform. Most existing studies ignore the boundary rotational restraints of beam structures and concentrated mass introduced by the nonlinear supports or foundations. To improve the engineering acceptance of beam structures with nonlinearity, it is of great significance to study the dynamic behavior of the generally restrained pre-pressure beam structure with a partial non-uniform foundation of nonlinear stiffness. This study establishes the nonlinear vibration model of the beam structure with a local non-uniform nonlinear stiffness distribution. Nonlinear dynamic responses of the beam structure are predicted by the Galerkin truncation method (GTM). Mode functions of the generally restrained pre-pressure beam structure are set as the trail and weight function. The correctness of the GTM for dynamic prediction of the beam structure with a partial non-uniform nonlinear foundation is verified by using the harmonic balance method (HBM). The influence of sweeping ways of excitations and parameters of the partial non-uniform nonlinear foundation on nonlinear dynamic responses of the beam structure are investigated. Dynamic responses of the beam structure with a partial non-uniform nonlinear foundation are sensitive to their initial values. Vibration states of the beam structure are transformed effectively by changing parameters of the partial non-uniform nonlinear foundation. The vibration at both ends of the beam structure can be suppressed by applying suitable parameters of the partial non-uniform nonlinear foundation.
Representation of solutions to sticky stochastic differential equations
Authors: Garzón Johanna , León Jorge A. , Torres Soledad
Published: July 2022

In this paper, we study a representation for the solutions to sticky stochastic differential equations driven by a continuous process. The involved stochastic integral is interpreted in three different ways. Namely, we deal with Young integral defined by the fractional calculus, and the forward and symmetric integrals in the Russo and Vallois sense. The representation obtained in this paper depends on the amount of time spent by the solution at zero. Hence, we obtain the uniqueness for the solution among the processes that spend zero time at [Formula: see text].
Quadratic Particle Swarm Optimisation Algorithm for Task Scheduling Based on Cloud Computing Server
Authors: Wei Guanghui
Published: July 2022

The task scheduling is one of the core problems of cloud computing and aims to assign tasks reasonably, realise the optimal scheduling strategy and improve the operating efficiency of overall cloud computing system. For the shortcomings of traditional particle swarm optimisation (PSO) algorithm in total completion time and average completion time, a quadratic particle swarm optimisation (QPSO) algorithm is proposed. Using the proposed algorithm, people can find a scheduling result with the short total completion time of task and also ensuring the short average completion time of task. Finally, the research made a simulation experiment with Cloud Sim. Experiment results show that in the same condition setting, the algorithm proposed is superior to the traditional PSO algorithm. When the number of tasks increases, the comprehensive scheduling performance of QPSO is more than 20% higher than that of PSO.
The Effect of Corporate Social Responsibility on Stock Price Volatility — Evidence from Chinese Listed Companies
Authors: Song Xiaotong
Published: July 2022

This paper studies the relationship between corporate social responsibility (CSR) and stock price volatility based on data of Chinese A-share listed companies from 2010 to 2018, and further analyses the path and underlying mechanism of CSR that affects stock price volatility. With China’s gradual transition to a sustainable development model, both public and the government are paying increasing attention to CSR performance. At the same time, the Chinese government takes a more serious attitude towards systemic financial risks, emphasising the importance of controlling systemic risks such as an abnormal stock price on many public occasions. In this context, CSR and stock price volatility have received unprecedented attention, and it’s of great value for both industry and the government to explore the impact of CSR on stock price volatility.
An Axial Magnetic Field Effect on Frequency Analysis of Rotating Sandwich Cylindrical Shells with FG Graphene/AL Face Sheets and Honeycomb Core
Authors: Sobhy Mohammed , Radwan Ahmed F.
Published: July 2022

This article concerns with free vibration analysis of spinning sandwich cylindrical shells with functionally graded (FG) graphene/aluminum (Al) face sheets and honeycomb core exposed to an axial magnetic field. Lorentz magnetic force is derived by using Maxwell’s relations. The face layers are made of multi-nanocomposite sheets. Each sheet is composed of an Al matrix reinforced with graphene platelets (GPLs) that are uniformly distributed through the sheet thickness. The effective material properties of the face layers of the spinning sandwich cylindrical shells are derived employing the modified Halpin–Tsai model. The honeycomb core layer is made of hexagonal aluminum cells. According to the first-order shear deformation theory and Hamilton’s principle, five governing equations are obtained involving Lorentz force. Frequencies of the present model are analytically derived from the equations of motion. The present outcomes are examined by introducing some comparison examples. The effects of the geometric parameters, magnetic field parameter, GPLs weight fraction, core-to-face thickness ratio, circumferential wave number, axial wave number and spinning speed on the vibration of spinning sandwich honeycomb cylindrical shells are numerically discussed.
The Euler totient function on Lucas sequences
Authors: Saunders J. C.
Published: July 2022

In 2009, Luca and Nicolae [[Formula: see text], Integers 9 (2009) A30] proved that the only Fibonacci numbers whose Euler totient function is another Fibonacci number are [Formula: see text], and [Formula: see text]. In 2015, Faye and Luca [Pell numbers whose Euler function is a Pell number, Publ. Inst. Math. 101(115) (2017) 231–245] proved that the only Pell numbers whose Euler totient function is another Pell number are [Formula: see text] and [Formula: see text]. Here, we add to these two results and prove that for any fixed natural number [Formula: see text], if we define the sequence [Formula: see text] as [Formula: see text], [Formula: see text], and [Formula: see text] for all [Formula: see text], then the only solution to the Diophantine equation [Formula: see text] is [Formula: see text].
Proof of Kaneko–Tsumura conjecture on triple T-values
Authors: Berger Sasha , Chandra Aarav , Jain Jasper , Xu Daniel , Xu Ce , Zhao Jianqiang
Published: July 2022

Many [Formula: see text]-linear relations exist between multiple zeta values, the most interesting of which are the weighted sum formulas. In this paper, we generalize these to Euler sums and Kaneko and Tsumura’s multiple [Formula: see text]-values, a variant of the multiple zeta values, by considering generating functions of the Euler sums. Through this approach, we are able to re-prove a few known formulas, confirm a conjecture of Kaneko and Tsumura on triple [Formula: see text]-values, and discover many new identities.
An asymptotic expansion for a Lambert series associated to the symmetric square L-function
Authors: Juyal Abhishek , Maji Bibekananda , Sathyanarayana Sumukha
Published: July 2022

Hafner and Stopple proved a conjecture of Zagier that the inverse Mellin transform of the symmetric square [Formula: see text]-function associated to the Ramanujan tau function has an asymptotic expansion in terms of the nontrivial zeros of the Riemann zeta function [Formula: see text]. Later, Chakraborty et al. extended this phenomenon for any Hecke eigenform over the full modular group. In this paper, we study an asymptotic expansion of the Lambert series [Formula: see text] where [Formula: see text] is the [Formula: see text]th Fourier coefficient of a Hecke eigenform [Formula: see text] of weight [Formula: see text] over the full modular group.
Divisibility and distribution of mex-related integer partitions of Andrews and Newman
Authors: Ray Chiranjit
Published: July 2022

Andrews and Newman introduced the minimal excludant or “[Formula: see text]” function for an integer partition [Formula: see text] of a positive integer [Formula: see text], [Formula: see text], as the smallest positive integer that is not a part of [Formula: see text]. They defined [Formula: see text] to be the sum of [Formula: see text] taken over all partitions [Formula: see text] of [Formula: see text]. We prove infinite families of congruence and multiplicative formulas for [Formula: see text]. By restricting to the part of [Formula: see text], Andrews and Newman also introduced [Formula: see text] to be the smallest odd integer that is not a part of [Formula: see text] and [Formula: see text] to be the sum of [Formula: see text] taken over all partitions [Formula: see text] of [Formula: see text]. In this paper, we show that for any sufficiently large [Formula: see text], the number of all positive integer [Formula: see text] such that [Formula: see text] is an even (or odd) number is at least [Formula: see text].
Infinite families of class groups of quadratic fields with 3-rank at least one: quantitative bounds
Authors: Lee Siyun , Lee Yoonjin , Yoo Jinjoo
Published: July 2022

We improve an effective lower bound on the number of imaginary quadratic fields whose absolute discriminants are less than or equal to [Formula: see text] and whose ideal class groups have 3-rank at least one, which is [Formula: see text]. We also obtain a better bound on the number of imaginary quadratic fields with 3-rank at least two, which is [Formula: see text]; the best-known lower bound so far is [Formula: see text]. For finding these effective lower bounds, we use the Scholz criteria and the parametric families of quadratic fields [Formula: see text] and [Formula: see text] (defined as follows) with escalatory case. We find new infinite families of quadratic fields [Formula: see text] and [Formula: see text], where [Formula: see text] and [Formula: see text] are integers subject to certain conditions for [Formula: see text]. More specifically, we find a complete criterion for the 3-rank difference between [Formula: see text] and its associated quadratic field [Formula: see text] to be one; this is the escalatory case. We also obtain a sufficient condition for the family [Formula: see text] and its associated family [Formula: see text] to have escalatory case. We illustrate some selective implementation results on the 3-class group ranks of [Formula: see text] and [Formula: see text] for [Formula: see text].
On a result of Koecher concerning Markov–Apéry-type formulas for the Riemann zeta function
Authors: Dilcher Karl , Vignat Christophe
Published: July 2022

Koecher in 1980 derived a method for obtaining identities for the Riemann zeta function at odd positive integers, including a classical result for [Formula: see text] due to Markov and rediscovered by Apéry. In this paper, we extend Koecher’s method to a very general setting and prove two more specific but still rather general results. As applications, we obtain infinite classes of identities for alternating Euler sums, further Markov–Apéry-type identities, and identities for even powers of [Formula: see text].
Electrophoresed Graphene Coatings for Corrosion Prevention: A Review
Authors: Das Amlan , Sahu Deepak Kumar , Das Sanjeev , Mallik Archana
Published: July 2022

Corrosion has been the foremost factor affecting the longevity of metals and alloys since ages. It can be thought of as the force of nature which strives to bring the refined form of elements back to their original state. However, human applications are essentially based on refined forms of elements, thereby creating the need for corrosion protection. Corrosion prevention methodologies span between coatings, inhibitors, sacrificial anodes. Coatings have seen maximum utility due to their simplicity and low cost. Researchers are on the lookout of a durable, environment-friendly, cheap coating. Graphene, a carbonaceous material is a new found interest delivering optimistic results. It carries the advantage of being a 2D material, whereby thin coatings with superior quality can be achieved. Additionally, its chemical inertness has proven to be a useful characteristic. On similar lines, electrophoretic deposition (EPD) is low cost and simple technique which has attracted the attention of researchers. It has been used to deposit colloidal solutions onto suitable substrates, mostly ceramics. The significance is growing steadily owing to its capability in producing thin films, nanomaterials and composite coatings. This paper highlights the use of graphene through EPD for synthesis of anti-corrosive coatings.
Equitable partition for some Ramanujan graphs
Authors: Alinejad M. , Erfanian A. , Fulad S.
Published: July 2022

For a [Formula: see text]-regular graph [Formula: see text], an edge-signing [Formula: see text] is called a good signing if the absolute eigenvalues of its adjacency matrix are at most [Formula: see text]. Bilu and Linial conjectured that for each regular graph there exists a good signing. In this paper, by using the concept of “Equitable Partition”, we prove the conjecture for some cases. We show how to find out a good signing for special complete graphs and lexicographic product of two graphs. In particular, if there exist two good signings for graph [Formula: see text], then we can find a good signing for a 2-lift of [Formula: see text].
Modified block-matching algorithm for moving object tracking in video surveillance
Authors: Vasekar Shridevi Sukhadeo , Shah Sanjeevani K.
Published: July 2022

Video surveillance has risen as one of the most promising methods for people who live alone in their dwellings. Few video surveillance innovations have recently been introduced. However, due to various changes in illumination, abrupt shifts in target appearance, identical non-target artifacts in the background, and occlusions, developing a reliable video surveillance algorithm remains a difficult challenge. This work attempts to introduce a new framework for moving object detection and tracking by following four major phases: “Video-to-Frame Conversion, Pre-Processing, Background Subtraction, Feature-Based Multi-object Detection, Multi-object Tracking by Filtering”. Initially, in the Video-to-Frame Conversion process, the recorded input video clips are transformed into distinct frames. During pre-processing, the noise is removed from the video frame using a filtering approach, and thereby the nature of the images will be enhanced. In the proposed work, a Weiner filter is used to remove noise and other undesirable features during the pre-processing. Then, to distinguish the frontal areas of objects, background subtraction is performed using the neutrosophic set in noiseless video frames (pre-processed frames). The objects in the background-subtracted frames are separated using Improved Region Growing (IRG) segmentation model in the Feature-Based Multi-object Detection phase. The objects in the frames are determined from this segmented image. The Modified Full Search Algorithm is being used to track the object (motion estimation) on the video frame after it has been identified in the segmented phase. The Modified full search block matching algorithm (MFSA) is introduced in this research work to find the appropriate mobility. Promising results have been obtained by the proposed work, and also the mathematical excellence of the new method is also proven over other state-of-the-art models.
A two-group epidemiological model: Stability analysis and numerical simulation using neural networks
Authors: El Yamani Mohamed Anass , El Karkri Jaafar , Lazaar Saiida , Aboulaich Rajae
Published: July 2022

This work has two principal goals. First, we investigate the asymptotic behavior of a two-group epidemiological model and determine the expression of its basic reproduction number using the dynamical systems approach based on the spectral radius of the relative matrix. Second, we simulate the obtained analytical results using a new deep learning method that associates the ordinary differential equations governing the model to neural networks. A general disease-free equilibrium is considered and sufficient conditions of stability and convergence are formulated. A detailed description of the neural network model used in the simulation is provided. Moreover, the proposed deep learning simulation algorithm is compared to the simulation provided by “odeint”, a function from “SciPy” which is a Python library of mathematical routines.
Automatic Recognition and Digital Documentation of Cultural Heritage Hemispherical Domes using Images
Authors: Maalek Reza , Maalek Shahrokh
Published: July 2022

Recent advancements in optical metrology have enabled continuous documentation of dense 3-dimensional (3D) point clouds of construction projects, including cultural heritage preservation projects. These point clouds must then be further processed to generate semantic digital models, which is integral to the lifecycle management of heritage sites. For large-scale and continuous digital documentation, processing of dense 3D point clouds is computationally cumbersome, and consequentially requires additional hardware for data management and analysis, increasing the time, cost, and complexity of the project. Fast and reliable solutions for generating the geometric digital models is, hence, eminently desirable. This article presents an original approach to generate reliable semantic digital models of heritage hemispherical domes using only two images. New closed formulations were derived to establish the relationships between a sphere and its projected ellipse onto an image. These formulations were then utilised to create new methods for: (i) selecting the best pair of images from an image network; (ii) detecting ellipses corresponding to projection of spheres in images; (iii) matching of the detected ellipses between images; and (iv) generating the sphere's geometric digital models. The effectiveness of the proposed method was evaluated under both laboratory and real-world datasets. Laboratory experiments revealed that the proposed process using the best pair of images provided results as accurate as that achieved using eight randomly selected images, while improving computation time by a factor of 50. The results of the two real-world datasets showed that the digital model of a hemispherical dome was generated with 6.2 mm accuracy, while improving the total computation time of current best practice by a factor of 7. Real-world experimentation also showed that the proposed method can provide metric-scale definition for photogrammetric point clouds with 3 mm accuracy using spherical targets. The results suggest that the proposed method was successful in automatically generating fast and accurate geometric digital models of hemispherical domes.
New Method for Museum Archiving: “Quantitative Analysis Meets Art History”
Authors: Kim Minseo
Published: July 2022

As museums are encouraged to explore new ways to generate digital content, and quantitative methods are being used to suggest new angles and important analysis tools for art-historical research and museum archives. Recent advances in digital image processing provide valuable data to describe the content of an artwork and support all the parties concerned with the authentication, appreciation, preservation, and archiving of artworks. Particularly, identification of artist-specific indicia or classification of the artistic style of paintings must be performed for indexing large artwork databases. Thus, we determined primary criteria based on feature-based analysis and suggested a new archiving framework for applications that enable collection, management, and visualization of artworks.
A Polynomial Degree Bound on Equations for Non-rigid Matrices and Small Linear Circuits
Authors: Volk Ben Lee , Kumar Mrinal
Published: July 2022

We show that there is an equation of degree at most poly(
n
) for the (Zariski closure of the) set of the non-rigid matrices: That is, we show that for every large enough field 𝔽, there is a non-zero
n
2
-variate polynomial
P
ε 𝔽[
x
1, 1
, ...,
x

n, n

] of degree at most poly(
n
) such that every matrix
M
that can be written as a sum of a matrix of rank at most
n
/100 and a matrix of sparsity at most
n
2
/100 satisfies
P(M)
= 0. This confirms a conjecture of Gesmundo, Hauenstein, Ikenmeyer, and Landsberg [
9
] and improves the best upper bound known for this problem down from exp (
n
2
) [
9
,
12
] to poly(
n
).

We also show a similar polynomial degree bound for the (Zariski closure of the) set of all matrices
M
such that the linear transformation represented by
M
can be computed by an algebraic circuit with at most
n
2
/200 edges (without any restriction on the depth). As far as we are aware, no such bound was known prior to this work when the depth of the circuits is unbounded.

Our methods are elementary and short and rely on a polynomial map of Shpilka and Volkovich [
21
] to construct low-degree “universal” maps for non-rigid matrices and small linear circuits. Combining this construction with a simple dimension counting argument to show that any such polynomial map has a low-degree annihilating polynomial completes the proof.

As a corollary, we show that any derandomization of the polynomial identity testing problem will imply new circuit lower bounds. A similar (but incomparable) theorem was proved by Kabanets and Impagliazzo [
11
].
Planar Graph Isomorphism Is in Log-Space
Authors: Datta Samir , Limaye Nutan , Nimbhorkar Prajakta , Thierauf Thomas , Wagner Fabian
Published: July 2022

Graph Isomorphism is the prime example of a computational problem with a wide difference between the best-known lower and upper bounds on its complexity. The gap between the known upper and lower bounds continues to be very significant for many subclasses of graphs as well.

We bridge the gap for a natural and important class of graphs, namely, planar graphs, by presenting a log-space upper bound that matches the known log-space hardness. In fact, we show a stronger result that planar graphcanonizationis in log-space.
On Proving the Correctness of Refactoring Class Diagrams of MDE Metamodels
Authors: Altoyan Najd , Batory Don
Published: July 2022

Model Driven Engineering
(

MDE

)
is a general-purpose engineering methodology to elevate system design, maintenance, and analysis to corresponding activities on models. Models (graphical and/or textual) of a target application are automatically transformed into source code, performance models, Promela files (for model checking), and so on for system analysis and construction.

Models are instances of
metamodels
. One form an
MDE
metamodel can take is a [class diagram, constraints] pair: the class diagram defines all object diagrams that could be metamodel instances; object constraint language (
OCL
) constraints eliminate semantically undesirable instances.

A metamodel
refactoring
is an invertible semantics-preserving co-transformation, i.e., it transforms both a metamodel
and
its models without losing data. This article addresses a subproblem of metamodel refactoring: how to prove the correctness of refactorings of class diagrams without
OCL
constraints using the
Coq
Proof Assistant.
Explainable Integration of Social Media Background in a Dynamic Neural Recommender
Authors: Zhang Yihong , Hara Takahiro
Published: July 2022

Recommender systems nowadays are commonly deployed in e-commerce platforms to help customers making purchase decisions. Dynamic recommender considers not only static user-item interaction data, but the temporal information at the time of recommendation. Previous researches have suggested to incorporate social media as the temporal information in dynamic neural recommenders after transforming them into embeddings. While such an approach can potentially improve recommendation performance, the effectiveness is difficult to explain. In this article, we propose an explainable method to integrate social media in a dynamic neural recommender. Our method applies association rule mining, which can generate human-understandable behavior patterns from social media and e-commerce platforms. With real-world social media and e-commerce data, we show that the integration can improve accuracy by up to 14% while using the same data. Moreover, we can explain the positive cases by examining relevant association rules.
L2MM: Learning to Map Matching with Deep Models for Low-Quality GPS Trajectory Data
Authors: Jiang Linli , Chen Chao-Xiong , Chen Chao
Published: July 2022

Map matching is a fundamental research topic with the objective of aligning GPS trajectories to paths on the road network. However, existing models fail to achieve satisfactory performance for low-quality (i.e., noisy, low-frequency, and non-uniform) trajectory data. To this end, we propose a general and robust deep learning-based model,
L2MM
, to tackle these issues at all. First, high-quality representations of low-quality trajectories are learned by two representation enhancement methods, i.e.,
enhancement with high-frequency trajectories
and
enhancement with the data distribution
. The former employs high-frequency trajectories to enhance the expressive capability of representations, while the latter regularizes the representation distribution over the latent space to improve the generalization ability of representations. Secondly, to embrace more heuristic clues, typical mobility patterns are recognized in the latent space and further incorporated into the map matching task. Finally, based on the available representations and patterns, a mapping from trajectories to corresponding paths is constructed through a joint optimization method. Extensive experiments are conducted based on a range of datasets, which demonstrate the superiority of
L2MM
and validate the significance of high-quality representations as well as mobility patterns.
Deep Ensemble Learning for Human Activity Recognition Using Wearable Sensors via Filter Activation
Authors: Huang Wenbo , Zhang Lei , Wang Shuoyuan , Wu Hao , Song Aiguo
Published: July 2022

During the past decade, human activity recognition (
HAR
) using wearable sensors has become a new research hot spot due to its extensive use in various application domains such as healthcare, fitness, smart homes, and eldercare. Deep neural networks, especially convolutional neural networks (
CNNs
), have gained a lot of attention in
HAR
scenario. Despite exceptional performance,
CNNs
with heavy overhead is not the best option for
HAR
task due to the limitation of computing resource on embedded devices. As far as we know, there are many invalid filters in
CNN
that contribute very little to output. Simply pruning these invalid filters could effectively accelerate
CNNs
, but it inevitably hurts performance. In this article, we first propose a novel
CNN
for
HAR
that uses filter activation. In comparison with filter pruning that is motivated for efficient consideration, filter activation aims to activate these invalid filters from an accuracy boosting perspective. We perform extensive experiments on several public
HAR
datasets, namely, UCI-HAR (
UCI
), OPPORTUNITY (
OPPO
), UniMiB-SHAR (
Uni
), PAMAP2 (
PAM2
), WISDM (
WIS
), and USC-HAD (
USC
), which show the superiority of the proposed method against existing state-of-the-art (
SOTA
) approaches. Ablation studies are conducted to analyze its internal mechanism. Finally, the inference speed and power consumption are evaluated on an embedded
Raspberry Pi Model 3 B plus
platform.
Multiple Imputation Ensembles for Time Series (MIE-TS)
Authors: Aleryani Aliya , Bostrom Aaron , Wang Wenjia , Iglesia Beatriz
Published: July 2022

Time series classification has become an interesting field of research, thanks to the extensive studies conducted in the past two decades. Time series may have missing data, which may affect both the representation and also modeling of time series. Thus, recovering missing data using appropriate time series-based imputation methods is an essential step. Multiple imputation is a data recovery method where it produced multiple imputed data. The method proves its usefulness in terms of reflecting the uncertainty inherit in missing data; however, it is under-researched in time series problems. In this article, we propose two multiple imputation approaches for time series. The first is a multiple imputation method based on interpolation. The second is a multiple imputation and ensemble method. First, we simulate missing consecutive sub-sequences under a Missing Completely at Random mechanism; then, we use single/multiple imputation methods. The imputed data are used to build bagging and stacking ensembles. We build ensembles using standard classification algorithms as well as time series classifiers. The standard classifiers involve Random Forest, Support Vector Machines, K-Nearest Neighbour, C4.5, and PART while TSCHIEF, Proximity Forest, Time Series Forest, RISE, and BOSS are chosen as time series classifiers. Our findings show that the combination of multiple imputation and ensemble improves the performance of the majority of classifiers tested in this study, often above the performance obtained from the complete data, even under increasing missing data scenarios. This may be because the diversity injected by multiple imputation has a very favourable and stabilising effect on the classifier performance, which is a very important finding.
Making Low-Power and Long-Range Wireless Backscatter Transmitters
Authors: Varshney Ambuj
Published: July 2022

The past decade has seen significant increases in the deployment of wireless embedded systems. However, several challenges exist that may hinder, or even stop, this rapid growth. Among them, a significant power asymmetry among platform components is a major concern. In particular, the radio transmitters consume orders of magnitude more power than the remaining components. One promising approach to address this challenge is to design wireless transmitters based on the backscatter mechanism. This mechanism allows wireless transmissions to occur at a similar power budget to sensing and computation operations in wireless embedded systems. In this article, we discuss designing transmitters based on backscatter mechanism that achieve a large range with a low power consumption, and thus bridge the power asymmetry among the components of wireless embedded systems.
2022 ACM SIGMOBILE Outstanding Contributions Award
Authors: Poor H. Vincent
Published: July 2022

For significant and lasting contributions to research on mobile computing and communications and wireless networking, Dr. Andrea Goldsmith is the recipient of the 2022 SIGMOBILE Outstanding Contributions Award. Dr. Goldsmith is a world-class scholar and entrepreneur in the field of wireless communications. Her work, beginning in the 1990s, on the capacity of fading communication channels, and on the use of adaptive modulation schemes to achieve this capacity, has had considerable influence on the thinking of the wireless networking community as the need for highercapacity wireless systems has exploded over the intervening years.
VeriMask
Authors: Long Yan , Curtiss Alexander , Rampazzi Sara , Hester Josiah , Fu Kevin
Published: July 2022

In response to the mask shortage during the first wave of the COVID-19 pandemic, we developed an open-source wireless sensor platform, VeriMask, to facilitate per-mask verification of the moist-heat decontamination process for N95 masks. The aim of VeriMask was to enable safe, easy, and accessible moist-heat decontamination in underresourced facilities to protect frontline healthcare workers by lowering their risk of infection from reused N95 masks. In this article we will introduce the VeriMask platform, challenges we encountered in this emergency-response design, design criteria, and lessons learned from our interactions with clinical and near-clinical partners. We hope to raise attention as to how society can be better prepared against future pandemics and other forms of crises by leveraging the expertise of the mobile computing, trustworthy computing, and medical communities.
Accounting for Digital Variability in Crowd Work
Authors: Joshi K. D. , Taylor Joseph , Deng Xuefei (Nancy)
Published: July 2022

Our AMICS TREO paper started the conversation regarding the digital variability that exists in different types of crowd work enabled by online platforms, such as Uber, Instacart, Upwork, and Amazon Mechanical Turk (MTurk) (Taylor et al., 2020). We argued that the degree to which online platforms digitize their work elements (e.g., tasks, assets, governance, and support services) is germane to understanding how crowd work differs among these platforms. Here we seek to extend this dialogue by highlighting three areas of consideration. These considerations will sharpen the focus of future crowd work research by making the digital variability a central character in information systems (IS) research.
Conceptualizing Information Systems Development as an Organizational Routine
Authors: Vial Gregory , Rivard Suzanne
Published: July 2022

Research acknowledges that information systems development (ISD) teams experiment with, overlook, or adapt the methods that they purportedly use. Given this, one stream of research adopts a perspective focused on prescriptions based on the idea of a method. Another stream of research adopts a perspective anchored in the view that human agency plays a critical role in the unfolding of ISD projects. We suggest that our understanding of ISD can be enriched by mobilizing both perspectives. Specifically, we propose a conceptualization of ISD as an organizational routine based on the ontology developed by Feldman and Pentland. We build on the elements of this ontology- (1) the idea of a routine (the ostensive aspect) and (2) its enactment (the performative aspect) as the two mutually constitutive aspects of organizational routines; and (3) the role of artifacts as mediators of the relationship between actors and the ostensive and performative aspects of organizational routines - to develop theoretical arguments explaining the benefits of applying this ontology to the ISD phenomenon. Extending the contextual boundaries of Feldman and Pentland's ontology, we propose research avenues that have the potential to contribute to our understanding of this core phenomenon of the IS discipline.
RISC Ph.D. studies program
Authors: Hemmecke Ralf
Published: July 2022

The RISC1 curriculum is open to Ph.D. students with a background in either mathematics or computer science and a strong interest (and preferably prior knowledge) in the respective other area.
South Asian Language Practices: Mother Tongue, Medium, and Media
Authors: LaDousa Chaise , Davis Christina P.
Published: July 2022

Scholars such as Murray Emeneau and John Gumperz made India prominent in the development of sociolinguistics as a field of study through their simultaneous attention to difference and cohesiveness. Later, scholars stressed the ideological mediation of practice, especially the importance of colonial constructions that continue to be relevant in the postcolonial period. Work on specific notions such as mother tongue and medium of instruction, and the salience of English, led scholars to provide insights into multilingual practices in Bangladesh, Nepal, Pakistan, and Sri Lanka. Finally, a vast scholarship on an array of older and newer media forms ranging from early print publications to social media has posed questions about the possibilities of representation and participation. Ethnographic approaches to digital media that focus on the complex dynamics between ideologies and practices have put South Asia at the forefront of studies of communication.
The Validity of Marketing Strategy of Tourist Attractions Based on Experiential Marketing
Authors: Song Mei , Niu Tianjiao , Wang Linna , Wang Xiaoyi
Published: July 2022

With the development of economy, people’s demand for travel is also increasing. They are no longer satisfied with the single standardized travel products of travel agencies and begin to pursue personalized. When many customers travel, the most important thing is their subjective feelings. This is also the focus of tourism enterprise research. Therefore, introducing experiential marketing into tourism and realizing experiential marketing can enhance the sense of experience of tourism, improve the economic benefits of tourism, and promote the development of tourism. This paper mainly studies the application of experiential marketing in tourism industry. In this paper, based on the tourism situation of Qingyan Ancient Town and the tourism marketing activities of other tourist attractions, combined with my own design, we developed an optimized design scheme of experiential marketing. In the process of implementation, there are still areas to be improved, and the author will continue to study and learn from the sharing of other scholars. The purpose of this paper is to study the validity of marketing strategies of tourist attractions based on experiential marketing. On the one hand, the research of this paper can enrich the theory of experience marketing; on the other hand, it can also provide reference for the reality of tourism marketing, which has theoretical and practical significance.
Mechanical Property Test and Finite Element Simulation Analysis of KH-560 Coupling Agent-Modified PVA Rubber Concrete
Authors: Li Lijuan , Wang Weijian , Xu Zhijun , Niu Zijuan , Li Xiaoyang , Wang Qian
Published: July 2022

KH-560 coupling agent can significantly improve the cement mortar and the rubber connection interface compatibility problem of poor weak associativity. This is also the problem that rubber concrete cannot be widely used in practical engineering. Therefore, in this study, the improvement of the performance of PVA rubber concrete by the interface modified by KH-560 coupling agent was studied from the aspects of macromechanics, mesostructure, and numerical simulation. The macromechanical test shows that KH-560 coupling agent improves the compressive, flexural, and shear strength of PVA rubber concrete, and the failure mode of the modified PVA rubber concrete also changes from plastic failure to brittle failure. Through FTIR test and SEM observation, it was found that when the rubber concreted is stressed, the PVA fiber and the cement base jointly bear the external force, absorb energy, and play the role of reinforcement. The finite element (ABAQUS) simulation analysis found that the simulated data were similar to the actual test results, and the reliability of the test results was verified by data fitting. The final experimental results of this research have practical guiding significance for the researchers of concrete composite materials to research compression and bending and shearing of test blocks with different dosages. It is used to provide a reliable theoretical basis in the actual engineering.
[Retracted] The Relationship between Sleep Quality and Hemodialysis and Nursing Intervention in Uremia Patients Based on Intelligent Data
Authors: Lin Aixia , Zhang Fujuan , Zhang Huifang
Published: July 2022

Uremia is a manifestation of end‐stage renal failure and is a clinical syndrome shared by various advanced renal diseases. In recent years, the prevalence of uremia has been increasing. Maintenance hemodialysis therapy is used as the treatment of choice for uremia and is widely used. For uremia, the day‐to‐day treatment has a serious impact on the patient’s symptoms, causing a lot of unnecessary burdens to life. While imposing a severe symptom burden on patients, excessive sleep deprivation repair time can cause various risk injuries and further increase the probability of patient mortality. The resulting sleep deprivation can lead to the functional damage of multiple organs and systems such as the cardiovascular system and the immune system. Therefore, improving sleep quality can increase the survival rate of patients to a certain extent. There is less domestic attention to its related research, and there are not many discussions on the pathogenesis. Based on this, this paper proposes to explore the effect of hemodialysis on the sleep quality of patients with uremia under the support of intelligent data. In this study, it was found that MHD patients had various sleep quality problems, and the incidence of sleep disturbance was 61.78%. The experimental results in this paper show that the incidence of sleep disturbance in diabetic nephropathy is 89.7%. This may be combined with a series of complications in patients with diabetes, which in turn affects the quality of sleep in patients. It may increase patient mortality and affect patient quality of life and survival. Therefore, we should pay close attention to the prevention of various complications in diabetic dialysis patients, which will help to improve sleep quality.