bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Generalized Sandwich Beam for Global Stability Analysis of Tall Buildings with Shear Walls Using a Modified Transfer Matrix Method
Authors: Pinto Cruz Mao Cristian
Published: May 2023

This research presents the study of the global buckling analysis of tall buildings with shear walls of significant length, where it is not possible to neglect the stiffness due to local shear. In order to correctly idealize the tall building, this research proposes a novel generalized sandwich beam replacement resulting from the generalization of the classical sandwich beam by including an additional mechanism due to the consideration of the local shear stiffness. The association of mechanisms of model shows that the proposed beam results from the series coupling of the classic sandwich beam and the local shear beam. Four characteristic stiffnesses and three kinematic fields associated with the model are considered. The differential equations and boundary conditions governing equilibrium are obtained by applying a variational approach using Hamilton’s principle to the relevant Lagrangian function. A modified transfer matrix method is proposed that diagonalizes the inverse of the zero transfer matrix and reduces the computational cost to solve the equilibrium equations numerically. The modified transfer matrix method allows the analysis to be generalized to buildings with uniform and non-uniform properties along their height considering a constant or variable compressive load along the height of the building. A parametric analysis is presented to evaluate the importance of the inclusion of the local shear mechanism of the shear walls. The results of the numerical examples are encouraging and show that at a reduced computational cost, the presented numerical procedure can greatly help engineers in the preliminary and final structural analysis of tall buildings.
Sensitivity Analysis of Dry Friction Damper in Stay Cables
Authors: Martins Thiago César , de Sousa Gonçalves Lauren Karoline , Vieira Gregório Sandro
Published: May 2023

The aim of this study is to provide an overview of damper sensitivity with dry friction mechanism in relation to its positioning and force to control cable vibrations in cable-stayed bridges. Finite element method is used to implement the cable model. Decay tangent evaluation takes into account the damper position varying in the first 5% of cable total length. To numerically solve the second-order nonlinear ordinary differential equation, the Newmark method with average acceleration is used. The results indicate the appearance of higher vibration modes with the application of dry friction damping, which can influence the interaction between two dampers. With the application of two dry friction dampers to the same cable using the equivalent viscous damping theory and the Newmark method, it is possible to perceive different results, where dry friction presents a considerable gain when not adapted to the linear viscous damping theory.
Integral domains with a few semistar operations
Authors: Mimouni A.
Published: May 2023

In this paper, we deal with integral domains with only a few semistar operations. Mainly, we give complete characterizations of integral domains with exactly three (respectively, four) semistar operations (respectively, semistar operation of finite character). Examples to illustrate our main theorems are given.
p-Numerical semigroups with p-symmetric properties
Authors: Komatsu Takao , Ying Haotian
Published: May 2023

The so-called Frobenius number in the famous linear Diophantine problem of Frobenius is the largest integer such that the linear equation [Formula: see text] ([Formula: see text] are given positive integers with [Formula: see text]) does not have a non-negative integer solution [Formula: see text]. The generalized Frobenius number (called the [Formula: see text]-Frobenius number) is the largest integer such that this linear equation has at most [Formula: see text] solutions. That is, when [Formula: see text], the [Formula: see text]-Frobenius number is the original Frobenius number.

In this paper, we introduce and discuss [Formula: see text]-numerical semigroups by developing a generalization of the theory of numerical semigroups based on this flow of the number of representations. That is, for a certain non-negative integer [Formula: see text], [Formula: see text]-gaps, [Formula: see text]-symmetric semigroups, [Formula: see text]-pseudo-symmetric semigroups, and the like are defined, and their properties are obtained. When [Formula: see text], they correspond to the original gaps, symmetric semigroups and pseudo-symmetric semigroups, respectively.
Distributive FCP extensions
Authors: Picavet Gabriel , Picavet-L’Hermitte Martine
Published: May 2023

We are dealing with extensions of commutative rings [Formula: see text] whose chains of the poset [Formula: see text] of their subextensions are finite (i.e. [Formula: see text] has the FCP property) and such that [Formula: see text] is a distributive lattice, that we call distributive FCP extensions. Note that the lattice [Formula: see text] of a distributive FCP extension is finite. This paper is the continuation of our earlier papers where we studied catenarian and Boolean extensions. Actually, for an FCP extension, the following implications hold: Boolean [Formula: see text] distributive [Formula: see text] catenarian. A comprehensive characterization of distributive FCP extensions actually remains a challenge, essentially because the same problem for field extensions is not completely solved. Nevertheless, we are able to exhibit a lot of positive results for some classes of extensions. A main result is that an FCP extension [Formula: see text] is distributive if and only if [Formula: see text] is distributive, where [Formula: see text] is the integral closure of [Formula: see text] in [Formula: see text]. A special attention is paid to distributive field extensions.
On the hemispherical transform in the half-space and related Radon transforms
Authors: Rubin B.
Published: May 2023

We consider an integral transform which maps functions on the Euclidean half-space to integrals of these functions over hemispheres centered on the boundary hyperplane. The main results include sharp [Formula: see text]-[Formula: see text] estimates for this transform and new explicit inversion formulas under minimal assumptions for functions. The main idea is an intriguing connection between the hemispherical transform, the Radon transform over paraboloids, and the transversal Radon transform over hyperplanes meeting the last coordinate axis.
A Modified Manta Ray Foraging Algorithm for Edge Server Placement in Mobile Edge Computing
Authors: El-Ashmawi Walaa H. , Ali Ahmed F. , Ali Ahmed
Published: May 2023

Owing to the rapid growth of the Internet of Things (IoT) and mobile devices, big data has been generated, and a cloud computing system is required to manipulate it. The main issue in this system is the access delay (AD) when the IoT and mobile devices offload their workload on the servers and the workload balance among them. Mobile edge computing (MEC), which has a sufficient distribution of edge servers (ESs) and resources, has been developed to overcome this problem. The placement of ESs in MEC is an NP-hard problem and a multi-objective optimization (MOO) problem that aims to reduce the AD between mobile users and ES and balance the workload among these servers. In this paper, we propose a new hybrid natural-inspired algorithm by combining the manta ray foraging algorithm and the uniform crossover operator to find the optimal edge server placement (ESP) in MEC and minimize the AD between mobile users and the ES. Although the standard manta ray foraging optimization (MRFO) algorithm can balance diversification and intensification, it suffers from premature convergence. We invoke a uniform crossover operator in the standard MRFO algorithm to overcome this problem. In addition, the standard MRFO algorithm is designed to solve continuous optimization problems and is unsuitable for solving discrete problems. However, ESP is a discrete optimization problem. We modified the operators in the standard MRFO algorithm to solve the ESP problem, achieving an optimal solution in terms of minimizing the AD between BSs and ESs and balancing the workload among ESs. The proposed algorithm is then tested on the Shanghai Telecom dataset and compared with five other algorithms. The results show that the proposed algorithm achieves the least AD, and the workload balance reaches about 52% compared with the other algorithms.
Optimization on large interconnected graphs and networks using adiabatic quantum computation
Authors: Padmasola Venkat , Chatterjee Rupak
Published: May 2023

In this paper, we demonstrate that it is possible to create an adiabatic quantum computing algorithm that solves the shortest path between any two vertices on an undirected graph with at most [Formula: see text] qubits, where [Formula: see text] is the number of vertices of the graph. We do so without relying on any classical algorithms, aside from creating an ([Formula: see text]) adjacency matrix. The objective of this paper is to demonstrate the fact that it is possible to model large graphs on an adiabatic quantum computer using the maximum number of qubits available and random graph generators such as the Barabási–Albert and the Erdős–Rényi methods which can scale based on a power law.
Quantum simulation of quantum mechanical system with spatial noncommutativity
Authors: Hasibul Hassan Chowdhury S. , Chowdhury Talal Ahmed , Nasri Salah , Nazim Omar Ibna , Saad Shaikh
Published: May 2023

Quantum simulation has become a promising avenue of research that allows one to simulate and gain insight into the models of high energy physics whose experimental realizations are either complicated or inaccessible with current technology. We demonstrate the quantum simulation of such a model, a quantum mechanical system with spatial noncommutativity, which is inspired by the works in noncommutative geometry and noncommutative field theory for a universal quantum computer. We use the novel group theoretical formalism to map the Hamiltonian of such a noncommutative quantum system into the ordinary quantum mechanical Hamiltonian and then carry out the quantum simulation using the Trotter–Suzuki product formula. Furthermore, we distinguish the impact of the noncommutativity parameter on the quantum simulation, especially on the Trotter error, and point out how its sizable value affects the simulation.
The Improved Irwin’s Model for Crack Problems in Power-Law Hardening Materials
Authors: Huang Yufeng , Wang Hua , Guo Fenglin
Published: May 2023

In this paper, an improved Irwin’s model for power-law hardening materials is established through the static equivalence between the linear elastic stress solution and the stress redistribution in the plasticity-affected zone (PAZ) under small-scale yielding (SSY) conditions. HRR solution is adopted to describe the stress field within the crack-tip plastic zone (CTPZ). Analytical expressions of the effective stress intensity factor (SIF) and the size of PAZ are derived to illustrate the effect of CTPZ on the fracture behavior for power-law hardening materials. Influences of external load and hardening exponent on fracture behavior are explored. The proposed model can assess the toughening effect of CTPZ accurately using the SIF ratio, which is always smaller than 1. This model can be applied to various materials obeying power-law hardening constitutive equations. It will reduce to the extended Irwin’s model for elastic-perfectly plastic materials in the limiting case.
Synthesis of TpTt/CdS Nanocomposite Structures for Methylene Blue Catalytic Degradation
Authors: Xu Chao , Zhang Zhicheng , Xiong Xudong , Fan Zhao , Wang Yongqian
Published: May 2023

The advancement of technology has resulted in severe issues in the natural environment, notably organic water contamination that poses a significant threat to living organisms. To mitigate such problems, various technological solutions have been developed to treat water pollution. The emergence of photocatalytic semiconductor technology has enabled the utilization of numerous novel semiconductor composites for pollution control due to their high efficacy and eco-friendliness. In this paper, TpTt/CdS composites were produced via a simple two-step process, and the resulting samples were characterized using X-ray diffraction, field emission scanning electron microscopy, Fourier transform infrared, X-ray photoelectron spectroscopy, ultraviolet (UV)–visible and photodegradation experiments using methylene blue to simulate organic pollutants. The experimental findings reveal that the composite structure system enhances the radiation absorption capacity of CdS in the UV range, as well as the adsorption capability of organic pollutants. This introduces a fresh concept for modifying semiconductor composite structures and highlights the considerable potential of CdS in degrading organic contaminants.
Heteroatom (N, P)-driven carbon nanomaterials for high-energy storage in supercapacitors
Authors: Liu Yong , Zhang Xian , Zhang Ke , Wang Zifeng , Li Guang
Published: May 2023

Nanoflower-like hollow carbon sphere (CS) materials with two different heteroatoms doping (N, P) were prepared by a simple synthetic method (NPCS). The specific surface area of NPCS can reach a high value of 396 m2/g. The NPCS has a high degree of hollowness and the self-assembled nanosheet of NPCS forms a fast electron transport channel, and also increases active area in contact with electrolyte. The doping of heteroatoms increases the defect level of the carbon-based nanomaterials and changes the local electron state of the material, thus forming storage sites on the surface of the material, which can be used as a station for ions collecting and distributing. The material was studied as an active material for supercapacitors, and the specific capacitance reached 274.9 F/g. After the 4000th cycle stability test, it still maintained 95.2% of the specific capacitance, indicating that the material has excellent properties of supercapacitor materials.
Optimal strategies for the static black-peg AB game with two and three pegs
Authors: Jäger Gerold , Drewes Frank
Published: May 2023

The AB Game is a game similar to the popular game Mastermind. We study a version of this game called Static Black-Peg AB Game. It is played by two players, the codemaker and the codebreaker. The codemaker creates a so-called secret by placing a color from a set of [Formula: see text] colors on each of [Formula: see text] pegs, subject to the condition that every color is used at most once. The codebreaker tries to determine the secret by asking questions, where all questions are given at once and each question is a possible secret. As an answer the codemaker reveals the number of correctly placed colors for each of the questions. After that, the codebreaker only has one more try to determine the secret and thus to win the game.

For given [Formula: see text] and [Formula: see text], our goal is to find the smallest number [Formula: see text] of questions the codebreaker needs to win, regardless of the secret, and the corresponding list of questions, called a [Formula: see text]-strategy. We present a [Formula: see text]-strategy for [Formula: see text] for all [Formula: see text], and a [Formula: see text]-strategy for [Formula: see text] for all [Formula: see text] and show the optimality of both strategies, i.e., we prove that no [Formula: see text]-strategy for a smaller [Formula: see text] exists.
Injective-edge-coloring of planar graphs with girth restriction
Authors: Bu Yuehua , Wang Peng , Zhu Hongguo
Published: May 2023

A [Formula: see text]-[Formula: see text]-[Formula: see text]-[Formula: see text] [Formula: see text] [Formula: see text] [Formula: see text] [Formula: see text] is a mapping [Formula: see text] such that [Formula: see text] for any three consecutive edges [Formula: see text],[Formula: see text],[Formula: see text] of a path or a [Formula: see text]-cycle. [Formula: see text][Formula: see text] has a [Formula: see text]-injective-edge-coloring[Formula: see text] is called the injective chromatic index of G. In this paper, we prove that for planar graphs [Formula: see text] with [Formula: see text], (1)[Formula: see text] if [Formula: see text]; (2)[Formula: see text] if [Formula: see text].
The weighted Tower of Hanoi
Authors: Mehiri El-Mehdi , Belbachir Hacene
Published: May 2023

The weighted Tower of Hanoi problem is a new generalization of the classical Tower of Hanoi problem, where a move of a disc between two pegs [Formula: see text] and [Formula: see text] is weighted by a positive real [Formula: see text]. This new problem generalizes the concept of finding the minimum number of moves to solve the Tower of Hanoi, to find a sequence of moves with the minimum total weight. We present an optimal dynamic algorithm to solve the weighted Tower of Hanoi problem, as well as some of its properties. We also show the link of this generalization to the Tower of Hanoi variants with restricted disc moves, and how this new problem can generalize the concept of restricting a disc move.
Recommender systems based on matrix factorization and the properties of inferred social networks
Authors: Uribe Santiago , Ramirez Carlos , Finke Jorge
Published: May 2023

Recommender Systems (RS) are a vital part of companies with an active participation on the web. These companies require strategies that allow them to take advantage of product ratings from users in order to provide future recommendations to other users. In the last decade, several algorithms have been developed for movie recommendation, with Matrix Factorization algorithm being one of the most popular algorithms. Our approach is to evaluate the performance of this recommendation algorithm in scenarios where underlying social networks, which characterize certain types of interactions between users, can be inferred. In particular, the MovieLens dataset is used, which consists of approximately 100,000 ratings by 671 users on 9066 movies, during the period from 29 March 1996 to 24 September 2018.
Intelligent Hybrid Trading Strategies Based on Quantum-Inspired Algorithm
Authors: Kuo Shu-Yu , Jiang Yu-Chi , Chou Yao-Hsin
Published: May 2023

Investing in stocks is a common choice for financial management. Technical indicators (TIs) assist investors in determining the best trading time to make a fortune. Moving average (MA) and relative strength index (RSI) are the most common TIs. The proposed hybrid technique maximizes the capabilities of these two indicators. This study utilizes the quantum-inspired algorithm to assist effectively in searching for the optimal solution in the vast solution space. The proposed trading system contains four innovative features. First, the traditional usage restriction of MA and RSI is removed to increase their potential effectiveness and identify the most profitable trading strategy. Second, this research proposes an innovative hybrid indicator (HI) that combines MA and RSI to simultaneously achieve both benefits. HI eliminates the restriction of employing a single indicator at once. Third, an efficient quantum-inspired algorithm, the Global-best-guided Quantum-inspired Tabu Search Algorithm with Quantum NOT Gate (GNQTS), effectively and efficiently explores optimized parameters. Fourth, this study proposes 60 sliding windows to determine the optimal period for training and testing. The investment targets include well-known indices: DJIA, S&P 500, NASDAQ Composite Index, and NYA, as well as high-reputation companies on the US stock market: DJIA components. By removing the restrictions imposed by these two indicators and the use of HI, the experiment results demonstrate that GNQTS can discover optimal parameters to generate higher returns than state-of-the-art methods and buy-and-hold (B&H) strategies. The proposed hybrid strategy provides for the promising prospect of quantum-inspired applications and the utilization of multiple indicators.
Molecular docking, QTAIM analysis, UV-Vis spectra, vibrational analysis, and electronic properties of Lantadenes C and D — A complete comparative study
Authors: Pandey Anoop Kumar , Sharma Ankit Kumar , Shukla Shashwat , Mishra Abhinav , Singh Vijay , Dwivedi Apoorva
Published: May 2023

We have done geometry optimization of two conformers of Lantadene series C and D. The fundamental vibrational frequencies with intensity have been done by using B3LYP/6-311G (d, p) method. The complete vibrational assignments of wavenumbers are made on the basis of potential energy distribution (PED). The nonbonding interactions in Lantadenes C and D are calculated by using the same level theory at the bond critical point (BCP). The calculated topological parameters at BCP are utilized to determine the nature and strength of interactions. We have also computed HOMO–LUMO gap and plotted frontier orbital HOMO–LUMO surfaces, molecular electrostatic potential surfaces to explain the reactive nature of Lantadenes C and D. The electronic transition spectra UV–Vis spectra of Lantadenes C and D are calculated by using TDDFT theory. The values of hyperpolarizability show a probable use of these compounds in electro-optical applications. The natural bonding orbital theory is utilized to calculate transition of electron from donor to acceptor which is very useful to describe nonbonding as well as bonding interactions. The calculated value of Log [Formula: see text] and Log [Formula: see text] for Lantadene C Lantadene D established its pharmaceutical behaviors. The biological activity of Lantadenes C and D is also calculated by using PASS online server for [Formula: see text]. The docking of Lantadene C Lantadene D is also performed by using Auto dock with predicted drug by Swiss dock online server.
Synthetic Data Generation for Morphological Analyses of Histopathology Images with Deep Learning Models
Authors: Tabakov Martin , Galus Krzysztof , Zawisza Artur , Chlopowiec Adam R. , Chlopowiec Adrian B. , Karanowski Konrad
Published: May 2023

In this study, we introduce a new synthetic data generation procedure for augmentation of histopathology image data. This is an extension to our previous research in which we proved the possibility to apply deep learning models for morphological analysis of tumor cells, trained on synthetic data only. The medical problem considered is related to the Ki-67 protein proliferation index calculation. We focused on the problem of cell counting in cell conglomerates, which are considered as structures composed of overlapping tumor cells. The lack of large and standardized data sets is a critical problem in medical image classification. Classical augmentation procedures are not sufficient. Therefore, in this research, we expanded our previous augmentation approach for histopathology images and we proved the possibility to apply it for a cell-counting problem.
Accounting for Residential Nonpayment Risk for Water Utility Financial Sustainability
Authors: Smull Erika , Doyle Martin
Published: May 2023

Residential “Nonpayment risk” for water utilities — the risk of revenue loss from residential customers not paying water bills — is a financial risk for water service providers that remains poorly understood. Current rate setting strategies do not explicitly consider nonpayment risk and are generally informed by past payment histories. We develop a new heuristic model to categorize and evaluate water utility pricing (rate setting) strategies that are responsive to the effects of nonpayment (i.e., delinquency) on water utility revenues. The model is the first attempt, to our knowledge, to theorize the impact of residential nonpayment on utility revenues. The method draws on the theory behind the Kelly Criterion, a strategy developed in the mid-20th century now used by investors in portfolio management. The results of our thought exercise show that even excessive nonpayment levels (50% each year) do not negate the effectiveness of rate increases for revenue generation, but that nonpayment management can provide revenue benefits. Without political motives, utilities with high nonpayment may be inclined to continue raising water rates, unless higher water rates result in higher nonpayment levels. As such, we highlight the need to understand “nonpayment elasticity”: the change in nonpayment due to changes in water rates. We illustrate how increased nonpayment elasticity can decrease the percent of potential revenue collected, particularly when water rates are increased substantially. The simple model provides a method to evaluate the financial sustainability of elevated nonpayment rates in water utility management and financial risk analysis.
IMPLEMENTATION OF THE NEW PERFORMANCE APPRAISAL SYSTEM IN THE BRUNEI PUBLIC SECTOR: INITIAL RESPONSES
Authors: PANG LI LI , MOHIDDIN MOHAMAD SHAH RIZAL AMIR HJ , ISMAIL MUHAMMAD AMIRUDDIN
Published: May 2023

This paper is a case study on Brunei Darussalam’s public sector employees’ observations regarding the new performance appraisal system introduced in 2018. While the new system was aimed at instilling a more “performance-driven” public sector, however, based on the survey findings of this paper, a majority of respondents raised their concerns on the key performance indicators (KPIs) and other aspects of the appraisal system. The findings highlight the need for more research to be done on appraisal systems and their processes, specifically in the public sector, where an effective appraisal system can create a performance-driven public sector which can improve overall governance.
Multi-View Enhanced Graph Attention Network for Session-Based Music Recommendation
Authors: Wang Dongjing , Zhang Xin , Yin Yuyu , Yu Dongjin , Xu Guandong , Deng Shuiguang
Published: May 2023

Traditional music recommender systems are mainly based on users’ interactions, which limit their performance. Particularly, various kinds of content information, such as metadata and description can be used to improve music recommendation. However, it remains to be addressed how to fully incorporate the rich auxiliary/side information and effectively deal with heterogeneity in it. In this paper, we propose a
M
ulti-view
E
nhanced
G
raph
A
ttention
N
etwork (named
MEGAN
) for session-based music recommendation. MEGAN can learn informative representations (embeddings) of music pieces and users from heterogeneous information based on graph neural network and attention mechanism. Specifically, the proposed approach MEGAN firstly models users’ listening behaviors and the textual content of music pieces with a Heterogeneous Music Graph (HMG). Then, a devised Graph Attention Network is used to learn the low-dimensional embedding of music pieces and users and by integrating various kinds of information, which is enhanced by multi-view from HMG in an adaptive and unified way. Finally, users’ hybrid preferences are learned from users’ listening behaviors and music pieces that satisfy users real-time requirements are recommended. Comprehensive experiments are conducted on two real-world datasets, and the results show that MEGAN achieves better performance than baselines, including several state-of-the-art recommendation methods.
Disease Simulation in Airport Scenario Based on Individual Mobility Model
Authors: Han Zhenyu , Ma Siran , Gao Changzheng , Shao Erzhuo , Xie Yulai , Zhang Yang , Geng Lu , Li Yong
Published: May 2023

As the rapid-spreading disease COVID-19 occupies the world, most governments adopt strict control policies to alleviate the impact of the virus. These policies successfully reduced the prevalence and delayed the epidemic peak, while they are also associated with high economic and social costs. To bridge the microscopic epidemic transmission patterns and control policies, simulation systems play an important role. In this work, we propose an agent-based disease simulator for indoor public spaces, which contribute to most of the transmission in cities. As an example, we study Guangzhou Baiyun International Airport, which is one of the most bustling aviation hubs in China. Specifically, we design a high-efficiency mobility generation module to reconstruct the individual trajectories considering both lingering behavior and crowd mobility, which greatly enhances the credibility of the simulated mobility and ensures real-time performance. Based on the individual trajectories, we propose a multi-path disease transmission module optimized for indoor public spaces, which includes three main transmission paths as close contact transmission, aerosol transmission, and object surface transmission. We design a novel convolution-based algorithm to mimic the diffusion process, which can leverage the high concurrent capability of the graphics processing unit to accelerate the simulation process. Leveraging our simulation paradigm, the effectiveness of common policy interventions can be quantitatively evaluated. For mobility interventions, we find that lingering control is the most effective mobility intervention with 32.35% fewer infections, while increasing social distance and increasing walking speed have a similar effect with 15.15% and 18.02% fewer infections. It demonstrates the importance of introducing crowd mobility into disease transmission simulation. For transmission processes, we find the aerosol transmission involves in 99.99% of transmission, which highlights the importance of ventilation in indoor public spaces. Our simulation also demonstrates that without strict entrance detection to identify the input infections, only performing frequent disinfection cannot achieve desirable epidemic outcomes. Based on our simulation paradigm, we can shed light on better policy designs that achieve a good balance between disease spreading control and social costs.
Pipeline Design for Data Preparation for Social Media Analysis
Authors: Bono Carlo A. , Cappiello Cinzia , Pernici Barbara , Ramalli Edoardo , Vitali Monica
Published: May 2023

In a data-driven culture, in which analytics applications are the main resources for supporting decision-making, the use of high-quality datasets is mandatory to minimize errors and risks. For this reason, data analysis tasks need to be preceded by a data preparation pipeline. The design of such a pipeline is not trivial: the data analyst must carefully choose the appropriate operations considering several aspects. This is often performed by adopting a trial-and-error approach that does not always lead to the most effective solution. In addition, extracting information from social media poses specific problems due to the need to consider only posts relevant for the analysis, for its dependence from the context being considered, for its multimedia contents, and for the risk of filtering out informative posts with automatic filters. In this article, we propose a systematic approach to support the design of pipelines that are able to effectively extract a relevant dataset for the goal of the analysis of data from social media. We provide a conceptual model for designing and annotating the data preparation pipeline with quality and performance information, thus providing the data analyst preliminary information on the expected quality of the resulting dataset in a context-aware manner. The generation of metadata related to the processing tasks has been recognized as essential for enabling data sharing and reusability. To this aim, the dataset resulting from the pipeline application is automatically annotated with provenance metadata to get a detailed description of all the activities performed by the pipeline on them. As a case study, we consider the design of a pipeline for creating datasets of images extracted from social media in order to analyze behavioural aspects during COVID-19.
A Survey on Deep Learning for Symbolic Music Generation: Representations, Algorithms, Evaluations, and Challenges
Authors: Ji Shulei , Yang Xinyu , Luo Jing
Published: May 2023

Significant progress has been made in symbolic music generation with the help of deep learning techniques. However, the tasks covered by symbolic music generation have not been well summarized, and the evolution of generative models for the specific music generation task has not been illustrated systematically. This paper attempts to provide a task-oriented survey of symbolic music generation based on deep learning techniques, covering most of the currently popular music generation tasks. The distinct models under the same task are set forth briefly and strung according to their motivations, basically in chronological order. Moreover, we summarize the common datasets suitable for various tasks, discuss the music representations and the evaluation methods, highlight current challenges in symbolic music generation, and finally point out potential future research directions.
Swahili Speech Dataset Development and Improved Pre-training Method for Spoken Digit Recognition
Authors: Kivaisi Alexander R. , Zhao Qingjie , Mbelwa Jimmy T.
Published: May 2023

Speech dataset is an essential component in building commercial speech applications. However, low-resource languages such as Swahili lack such a resource that is vital for spoken digit recognition. For languages where such resources exist, they are usually insufficient. Thus, pre-training methods have been used with external resources to improve continuous speech recognition. However, to the best of our knowledge, no study has investigated the effect of pre-training methods specifically for spoken digit recognition. This study aimed at addressing these problems. First, we developed a Swahili spoken digit dataset for Swahili spoken digit recognition. Then, we investigated the effect of cross-lingual and multi-lingual pre-training methods on spoken digit recognition. Finally, we proposed an effective language-independent pre-training method for spoken digit recognition. The proposed method has the advantage of incorporating target language data during the pre-training stage that leads to an optimal solution when using less training data. Experiments on Swahili (being developed), English, and Gujarati datasets show that our method achieves better performance compared with all the baselines listed in this study.
Generative Design of Housing Spatial Layout Based on Rectangular Spaces
Authors: Ahmadi Javid , Maddahi Seyyed Mehdi , Mirzaei Reza
Published: May 2023

The generative spatial layout design process can generate and optimize a wide range of design responses by complying with all desired requirements and criteria and evaluating them based on one or more specific functions. Considering the complexities and diversity of spatial layout responses, it is important to know the various mechanisms of the product design process related to them. Based on this, the aim of this research is to provide a mechanism for designing a generative spatial layout (GSL) based on a housing design problem. The method of this research with a quantitative approach is the simulation and placement of spaces through coding in Grasshopper and Python software under the Grasshopper platform. The main variables of the research are the dimensions of the spaces of the residential unit, the proximity matrix, and the spatial relationships of the residential unit. With the restrictions made, 440 spatial layout responses were produced in four general shapes, including an incomplete square, a rectangle with a one-to-two ratio, an incomplete rectangle with an incomplete one-to-two ratio, and L-shape. The geometrical data of production plans have been subjected to correlation and linear regression tests in the SPSS software. Two models have been developed based on the perimeter of the plan and the area of its peripheral rectangle. Based on the obtained results, GSL design will be able to provide more favorable solutions. The results indicate that, by providing the design constraints in all the results, the area-oriented approach to the productive design of housing configurations can serve as an assistant mechanism for the designer in providing a variety of floor plans in terms of area for the designer.
P2Y12 Inhibitors in Acute Coronary Syndromes: A Real-World, Community-Based Comparison of Ischemic and Bleeding Outcomes
Authors: Sachdeva Amit , Mutyala Ratnabhushan , Mantri Neha , Zhu Shiyun , McNulty Edward , Solomon Matthew
Published: May 2023

Background. Randomized trials have shown superiority of the novel P2Y12 inhibitors over clopidogrel in patients with acute coronary syndrome (ACS), but clinical benefit in the community remains controversial. Our objective was to compare the safety and efficacy of clopidogrel to ticagrelor and prasugrel in patients with ACS undergoing percutaneous coronary intervention (PCI) in a real-world population. Methods. We conducted a retrospective cohort study of patients with ACS who underwent PCI and were discharged with clopidogrel, ticagrelor, or prasugrel from 2012 to 2018 within Kaiser Permanente Northern California. We used Cox proportional hazard models with propensity-score matching to evaluate the association of the P2Y12 agent with the primary outcomes of all-cause mortality, myocardial infarction (MI), stroke, and bleeding events. Results. The study included 15,476 patients (93.1% on clopidogrel, 3.6% on ticagrelor and 3.2% on prasugrel). Compared to the clopidogrel group, ticagrelorand prasugrel patients were younger with less comorbidities. In multivariable models with propensity-score matching, we found a lower risk of all-cause mortality in the ticagrelor vs the clopidogrel group (HR (95% CI) 0.43 (0.20–0.92)), but no differences in the other endpoints, and no difference between prasugrel and clopidogrel among any endpoints. A larger proportion of patients on ticagrelor or prasugrel switched to an alternative P2Y12 agent vs. clopidogrel (

p

 < 0.01), and a higher level of persistence was seen among patients on clopidogrel vs. ticagrelor (

p

 = 0.03) or prasugrel (

p

 < 0.01). Conclusion. Among patients with ACS who underwent PCI, we observed a lower risk of all-cause mortality in patients treated with ticagrelor vs clopidogrel, but no difference in other clinical endpoints nor any differences in endpoints between prasugrel vs. clopidogrel users. These results suggest that further study is needed to identify an optimal P2Y12 inhibitor in a real-world population.
Particle Ratios in a Multicomponent Nonideal Hadron Resonance Gas
Authors: Parra Rameez Ahmad , Uddin Saeed , Bashir Waseem , Bashir Inam-ul
Published: May 2023

We have considered formation of a multicomponent nonideal hot and dense gas of hadronic resonances in the ultrarelativistic heavy ion collisions. In the statistical thermal model approach, the equation of state (EoS) of the noninteracting ideal hadron resonance gas (IHRG) does not incorporate either the attractive part or the short-range repulsive part of the baryonic interaction. On the other hand, in the nonideal hadron resonance gas (NIHRG) model, we can incorporate these interactions using the van der Waals (VDW) type approach. Studies have been made to see its effect on the critical parameters of the quark-hadron phase transition. However, it can also lead to modifications in the calculated relative particle yields. In this paper, we have attempted to understand the effect of such van der Waals-type interactions on the relative particle yields and also studied their dependences on the system’s thermal parameters, such as the temperature and baryon chemical potential

μ

B

. We have also taken into account the decay contributions of the heavier resonances. These results on particle ratios are compared with the corresponding results obtained from the point-like, i.e., noninteracting IHRG model. It is found that the particle ratios get modified by incorporating the van der Waals-type interactions, especially in a baryon-rich system which is expected to be formed at lower RHIC energies, SPS energies, and in the forthcoming CBM experiments due to high degree of nuclear stopping in these experiments.
IOT and Blockchain-Based Cloud Model for Secure Data Transmission for Smart City
Authors: Al-Farhani Liwa H. , Alqahtani Yahya , Alshehri Hamdan Ali , Martin R. John , Lalar Sachin , Jain Rituraj
Published: May 2023

The widespread use of the Internet of Things (IoT) technology has both good and bad things about it. There must be a full and reliable security system in place for the Internet of Things so that things can work together in a safe way and intrusions cannot happen. There are now many more ways to keep the Internet of Things safe, thanks to a detecting system. As machine learning and deep learning technologies have become better, a lot of good intrusion detection systems have been made. This kind of study is covered. These two types of security are compared in this study. The current machine-based intrusion detection system is broken down into more detailed categories based on detection technology, data source, architecture, and operating method. These categories are as follows: It is talked about how IoT security will grow in the future and how to understand its intrusion detection system too. In this paper, a cloud-based blockchain security model has been presented for secure data transmission over IoT.
Multihop Uplink Communication Approach Based on Layer Clustering in LoRa Networks for Emerging IoT Applications
Authors: Bomgni Alain Bertrand , Ali Hafiz Munsub , Shuaib Mohammed , Mtopi Chebu Yann
Published: May 2023

LoRa technology is widely used in the Internet of things network applications. It enables low-volume data transmission via small wireless devices. The principle of LoRa networks (an LPWAN technology: Low Power Wide Area Network) is to transmit data by air from sensors with a short transmission range, about over ten kilometers. These sensors should not be powered by electricity, and batteries power them. Hospital visits are inevitable, but current advances in communication could reduce the burden on hospitals with remote (from home) treatments using these wireless sensors. Thus, using the LoRaWAN protocol could greatly facilitate patient diagnosis by transmitting data between doctors and patients in real time and with minimal energy consumption. The objective of this work is to set up a multihop IoT network containing a large number of sensors based on LoRa for uplink communication. This work evaluates the energy consumption and the packet delivery rate in the multihop IoT network. The simulation result shows that the proposed approach reduces power consumption by 50% and improves the packet delivery rate by 2% compared to the existing state of the art.
Effective Teaching Design Based on the Combination of BOPPPS Model and Tina Virtual Simulation Software
Authors: Wu Changdong , Deng Zhenli , Wei Jincheng
Published: May 2023

Good teaching effect comes from effective teaching design. In this article, we combined the advanced teaching concept BOPPPS model with Tina virtual simulation software to develop the teaching design. BOPPPS model is an effective and efficient teaching model. It includes six parts such as bridge-in, objective, preassessment, participatory learning, postassessment, and summary. In this article, bridge-in is introduced by practical examples of triode amplifier circuits. Objective includes knowledge objective, ability objective, and value objective. Preassessment is realized by simulating the triode output characteristic. Participatory learning is presented by simulating three kinds of basic amplifier circuits and analyzing simulation results. Besides that, flipping classroom is designed to stimulate students’ learning enthusiasm and innovation ability. Postassessment is completed by asking some questions. Summary is completed by students and supplemented by teachers. In this process, different simulation waveforms are obtained by using the Tina virtual software to simulate the various circuits layer by layer. Practice has shown that the proposed method not only improves students’ ability of analyzing and designing practical circuits, but also stimulates students’ learning enthusiasm. Teaching design ideas become clearer, and the teaching quality is improved.
A Novel Digital Predistortion Identification Algorithm Based on Variable Forgetting Factor Recursive Least Square Method
Authors: Song Wenxian , Wang Guofu , Ye Jincai
Published: May 2023

The transmitting signal of wireless communication system is impaired by the nonlinearity of RF power amplifier (PA) which leads to signal distortion and spectrum spillover, by which the signal transmission quality is affected. Digital predistortion (DPD) is an efficient and economical way to correct the nonlinear effects of power amplifiers. The recursive least square (RLS) recognition algorithm is commonly used to extract the correction coefficients of the DPD model, and the accuracy of the extraction directly affects the system performance. In this paper, a new variable forgetting factor identification algorithm (new variable forgetting factor recursive least square, NVFFRLS) is proposed for recursive least square (RLS) identification algorithm. The 64-QAM signal is combined with a memory polynomial (MP) predistortion model for predistortion system simulation. The experimental results show that, compared with the RLS identification algorithm and two kinds of variable forgetting factor RLS identification algorithms, the algorithm has smaller estimation error, faster convergence, and better tracking capability, stability, and adaptability; the predistortion system based on NVFFRLS identification algorithm can compensate the nonlinear memory effects of power amplifier more effectively.
Supporting Mechanism of Pile-Anchor Systems for Deep Foundation Pits in Alpine Regions during the Spring Thaw
Authors: Shi Qiang , Zhao Dehui , Wang Ye , Li Yufeng , Zhu Lei , Cheng Zhihe
Published: May 2023

This study investigated the supporting mechanism of the retaining piles and prestressed anchor cables of a deep foundation pit in alpine regions during the spring thaw. A numerical model was developed based on a subway project in Changchun City. Field monitoring data and the numerical model were used to analyze the variations in the ground settlement, horizontal displacement of the pile tops, and axial force of the anchor cables during the spring thaw under different working conditions. The results demonstrated that changes in the ground settlement primarily occurred in the late stages of the spring thaw with no obvious settlement phenomena because of the thaw. The pile top displacement of most piles remained stable. The axial force of the anchor cables gradually decreased and then sharply increased early in the spring thaw and then slowly decreased in the middle and late stages. Increasing the pile length decreased the pile top displacement to a certain point. Moreover, increasing the pile length increased the axial force of the first anchor cable but decreased the axial force of the lower four anchor cables. Furthermore, increasing the pile spacing increased the pile top displacement and axial force of the five anchor cables. Increasing the incident angle of the anchor cables decreased the pile top displacement and increased the axial force of the first, third, and fourth cables. The axial force of the second cable was minimized at an incident angle of 14°, and the axial force of the fifth cable was minimized at incident angles of 16° and 18°.
A Study on Regular Domination in Vague Graphs with Application
Authors: Shi Xiaolong , Akhoundi Maryam , Talebi A. A. , Mojahedfar Masome
Published: May 2023

Vague graphs (VGs), which are a family of fuzzy graphs (FGs), are a well-organized and useful tool for capturing and resolving a range of real-world scenarios involving ambiguous data. In graph theory, a dominating set (DS) for a graph

G

∗

=

X
,
E

is a subset

S

of the vertices

X

such that every vertex not in

S

is adjacent to at least one member of

S

. The concept of DS in FGs has received the attention of many researchers due to its many applications in various fields such as computer science and electronic networks. In this paper, we introduce the notion of

ϵ

1

,

ϵ

2

,

2

-Regular vague dominating set and provide some examples to explain various concepts introduced. Also, some results were discussed. Additionally, the

ϵ

1

,

ϵ

2

,
2

-Regular strong (weak) and independent strong (weak) domination sets for vague domination set (VDS) were presented with some theorems to support the context.