bluuebunny/crossref_metadata_2025_split huggingface dataset:
QR Sort: A New Non-Comparative Integer-Based Sorting Algorithm
Authors: Bushman Randolph 
Published: June 2023

Abstract
In this paper, we introduce a new stable, non-comparative integer-based sorting algorithm with an attainable linear time complexity, O(n). This approach utilizes the Quotient Remainder Theorem in conjunction with Counting Sort subroutines. This algorithm divides each input array element by a selected positive integer divisor, d, to generate representative remainder and quotient keys. We perform Counting Sort on the remain-der keys followed by the quotient keys. This method yields a time and space complexity of O(n + d + k/d), where k represents the difference between maximum and minimum array values. If we set the divisor, d, equal to the length of the input array, n, the complexity simplifies to O(n + k/n). As the length of the input array increases and the value of k remains constant, the time complexity converges to O(n). Our results indicate that our algorithm outperforms established integer-based sorting algorithms such as Counting Sort and Least Significant DigitRadix Sort with large input arrays. We present our methodology and comprehensive discussion of our results in the main body of the paper.
An improved modulation method for low common-mode current non-isolated series simultaneous power supply dual-input inverters for new energy generation applications
Authors: Sun Jiaqi , Sun Haoran , Jiang Jiahui 
Published: June 2023

Abstract
Multi-input power supply systems are mostly used in the field of combined power supply of multiple new energy sources, and multi-input inverters play an important role in multi-input power supply systems, but multi-input inverters have the problem of common mode currents. This paper proposes an improved modulation method for a non-isolated series simultaneous power supply type dual-input inverter with low common-mode current for new energy generation applications. The design of a simulation circuit based on the corresponding dual-input inverter shows that this type of inverter can suppress the common-mode current below 30mA and has the advantage of low switching stress, providing an effective single-stage inverter solution for the combined power supply of multiple new energy sources.
Mathematical modeling to predict the compressive strength of eco- friendly pervious concrete modified with waste glass powder
Authors: Ahmad Soran Abdrahman , Rafiq Serwan Khwrshid , Hilmi Hozan , Unis Hemn 
Published: June 2023

Abstract
Due to the climatic change and increase the flood rick in many countries, the usage of pervious concrete has been increased as a solution of the water collecting in the underground, since its usage will be in the low loaded area the usage of waste materials to obtain eco-friendly pervious concrete is one of the challenges to the researchers. This article deals with the proposing mathematical model (Linear regression, non-linear regression and artificial neural network) to predict the compressive strength of pervious concrete modified with waste glass powder as partial replacement of cement. Based on the obtained result artificial neural network (ANN) provide higher accuracy and efficiency compare to linear regression (LR) and nonlinear regression model (NLR) since its scatter index value (SI) value lower than 0.1 and its coefficient of determination value (R2) higher than LR by 22% and 17% compare to NLR.
Optimal Transport-Based Volumetric Shape Clustering
Authors: Effland Alexander , Rumpf Martin , Verhülsdonk Jan 
Published: June 2023

Abstract

Clustering of data points in $n$-dimensional Euclidean space, i.~e. assigning each data point to exactly one group (cluster) in order to detect previously unseen relations within the data set, has become a standard task for (unsupervised) machine learning. In this paper, this concept is generalized to shape data consisting of three-dimensional volumetric objects. As the underlying distance on the space of such objects, the optimal transport-based Wasserstein distance is considered and different variants of such a clustering approach are presented and compared. To counteract an over-smoothing of the cluster center volumes a variational autoencoder representing these cluster centers is incorporated. Numerical experiments for three distinct, volumetric data sets are presented to validate the performance of the proposed methods.
A Survey on Aspect-Based Sentiment Quadruple Extraction with Implicit Aspects and Opinions
Authors: Zhang Hao , Cheah Yu-N , Alyasiri Osamah Mohammed , An Jieyu 
Published: June 2023

Abstract
Quadruple sentiment analysis is an essential task in aspect-based sentiment analysis that aims to understand people's viewpoints by analyzing four elements in text: category, aspect, opinion, and sentiment polarity. In recent years, quadruple sentiment analysis tasks have received extensive research attention for capturing comprehensive sentiment information in sentences. This paper focuses on the latest progress in quadruple sentiment analysis tasks. Additionally, the paper provides a summary of the application of methods based on pre-trained language models and datasets in quadruple sentiment analysis with implicit aspects and opinions. It discusses techniques for constructing more practical quadruple sentiment analysis systems in generative large model scenarios. The paper's final section outlines quadruple sentiment analysis research's current challenges and future directions. Moreover, the paper suggests that using advanced language models, such as ChatGPT, holds promise for improving the accuracy and efficiency of quadruple sentiment analysis. Overall, this paper sheds light on the importance of quadruple sentiment analysis and highlights opportunities for further research in this field.
The First Principle Calculation of the Properties of Aluminium and Gallium Using Density Functional Theory.
Authors: Enaroseha Omamoke O. E. , Oyibo Obed , Esi Oghenevovwero E. , Tuggen Edward O. , Nomuoja Jennifer A. 
Published: June 2023

Abstract
The theoretical calculations for the structural, thermodynamic, electrical and mechanical characteristics of aluminum and gallium were studied using ab initio principles. The Density Functional Theory (DFT) was used as the methodology, and it provides solutions to the Kohn – Sham equation. The elemental structures were obtained using Xcryden software, and the exchange correlation functions within the Perdew – Burke – Ernzerhof (PBE) functional were treated using the PAW pseudo – potentials and Generalized Gradient Approximation (GGA). The results obtained from the ab initio calculations engulf that the structural properties of a(A), B(GPa), B’(GPa) and E(eV) for both elements studied. The parameters obtained for the mechanical properties C11, C12 and C44 were calculated for both metals. The elastic properties; G, B/G, E, µ, A and H were also calculated for both elements. The results obtained for aluminum shows the values of B, C’, C11, C12 and C44 are 45, 3.9, 50.20, 47.6 and 31 respectively. For gallium we obtained 47, 4.03, 52.373, 44.313 and 29.0 corresponding to B, C’, C11, C12 and C44 respectively.
Contact endoscopic surface vascular and epithelial morphology in leukoplakia and carcinoma of the vocal cords Contact endoscopy in leukoplakia and carcinoma of vocal cords
Authors: Pavlidis Pavlos , Tseriotis Vasileios Spyridon , Matthias Christopher , Katsikari Ioulia , Chatzinikolaou Aimilios , Gouveris Haralampos 
Published: June 2023

Abstract
Background: Leukoplakia is a macroscopic morphological term for thick white or grey mucosal patches that can represent various histologic diagnostic entities ranging from hyperplasia to malignancy. Aim was the study morphology of the superficial mucosa and microvascular network of the vocal cords in patients with suspected glottic squamous cell carcinoma (SCC) using contact endoscopy (CE).
Material and Methods Seventy-nine patients (21 female, 58 male), with a mean age of 57.5 years ± 7.12 (range, 32–73 years), were prospectively enrolled and evaluated.
Of these patients, 58 had leukoplakia (Group A/41 males and 17 females, with a mean age of 53.7 years ± 6.65), and 21 (Group B/ 17males and 4 females/ with a mean age of 60.5 years ± 6.04) had malignant lesions (pT1, n=6; p T2, n=8; pT3, n=8; Group B), as proven by the results of the histological examination. Further, 79 non-smokers (control group - group C) were studied. CE imaging findings were classified into five types (I to V) based on the features of the mucosal intra-epithelial capillary loops. CE findings were correlated to the histologic findings. A separate analysis involving smoking status was done.
Results: The CE-based intraepithelial papillary capillary loop classification score was strongly correlated with the histological findings. Age was strongly associated with both malignancy and bilateral involvement. Smoking habits didn’t significantly differ between patients with unilateral and bilateral SCC.
Conclusions: CE imaging of the vocal cord mucosal capillaries may be useful for the early detection of glottic SCC and pre-cancerous lesions.
The role of big data analytics in improving teacher training in developing countries: A literature Review
Authors: ABTEW ADMAS , Endebu Alemisa 
Published: June 2023

Abstract
The use of big data analytics is becoming increasingly prevalent in various fields, including education. This systematic literature review examines the role of big data analytics in improving teacher training in developing countries. The review synthesizes and analyzes the findings from 11 selected studies published between 2015 and 2023. The studies were identified through a comprehensive search of electronic databases, and they were analyzed using a thematic analysis approach. The findings of this review suggest that big data analytics has the potential to improve teacher training in developing countries. The studies reviewed provide evidence of the potential of big data analytics to improve teacher training, and highlight the various ways in which big data analytics can be applied in the field of education. The key findings of the studies suggest that big data analytics can be used to identify areas where teachers need additional support and training, evaluate the effectiveness of different training and teaching strategies, provide insights into student learning and performance, and inform evidence-based policies and decisions related to education. However, there are limitations to be considered, and further research is needed to fully understand the impact of big data analytics on education outcomes. The studies included in this review were conducted in different countries with different education systems, so the findings may not be generalizable to other contexts. Furthermore, most of the studies used a quasi-experimental design, which may be susceptible to bias and confounding factors. Additionally, the studies focused on specific interventions and strategies related to teacher training, so the broader impact of big data analytics on education outcomes is unclear.
Spatial characteristics of urban evapotranspiration effects on the thermal environment
Authors: Gan Xiangyue , Zhang Yu , Wu Zixuan , Wang Yuchen , Han Haifeng , Yang Xiaoyan 
Published: June 2023

Abstract
Evapotranspiration (ET) is an important process of the regional hydrothermal cycle. However, it is unclear how the mitigation of urban ET in urban thermal environments occurs in a spatial context. Landsat 8 satellite images from 2014 to 2018 of Xuzhou and corresponding meteorological observations were selected, and the improved mono-window algorithm (IMW) and urban RS-PM model were applied to invert land surface temperature (LST) and ET, respectively. In addition, spatial analysis methods (a profile analysis, standard deviation ellipse (SDE) analysis, and bivariate Moran's I) were employed to quantify and simulate the spatial characteristics of the ET effect on LST. The results indicated the following: (1) There was a significant linear negative correlation between ET and LST, which confirms that ET has a negative effect on LST; (2) the SDE overlap ratios between patches with higher ET and lower LST imply that higher ET patches have a significant impact on the spatial distribution of LST; and (3) bivariate Moran's I between ET and LST and their linear mixture spectral analysis (LISA) maps reveal a significant negative spatial correlation between ET and LST. In addition, the landscape pattern of higher ET parches is also an important factor affecting the environmental temperature.
A Review on the Deep Learning-based Surface Reconstruction from the
Point Clouds
Authors: He Chengfa , Shou Huahao , Zhou Jiali 
Published: June 2023

Background:
Point cloud has become one of the most important data formats for 3D
presentation because of the increased availability of acquisition devices and its wide applications.
Deep learning has the most powerful ability to capture features from data and has successfully
solved various problems in the field of image, such as classification, segmentation, and generation.
Deep learning is commonly used to process data with a structured grid, while point cloud is irregular
and unstructured. The irregularity of point clouds makes it difficult to use deep learning to solve the
problems represented by point clouds. Recently, numerous approaches have been proposed to process
point clouds with deep learning to solve various problems.

Objective:
The objective of this study is to serve as a guide to new scholars in the field of deep
learning on 3D surface reconstruction from point clouds as it presents the recent progress in deep
learning-based surface reconstruction for point clouds. It helps scholars to grasp the current research
situation better and further explore the search direction.

Method:
This study reviews the recent progress in deep learning-based methods used for surface reconstruction
from point clouds and large-scale 3D point cloud benchmark datasets commonly used.

Results:
Several relevant articles on deep learning used for surface reconstruction from point clouds
and some recent patents on deep learning applications are collected and reviewed in this paper. The
difficulty of irregularity of point clouds can be overcome by deep learning methods, thus achieving
remarkable progress in surface reconstruction.

Conclusion:
Deep learning for 3D surface reconstruction from point clouds is becoming a research
hotspot due to its performance in terms of anti-interference and generalization. Although the advance
is remarkable, there are still some challenges that need to be further studied.
Development of an Anti-rollover Warning and Active Intervention
Controller for Wheeled Tractor
Authors: Gao Jie , Yin Chengqiang , Yuan Guanhao 
Published: June 2023

Background:
Tractor rollover accidents are the most severe problem in agricultural production.
According to the statistical analysis of the rollover incidents, some rollover accidents can
be avoided by timely anti-rollover warning and active control. There are a few researches on the
anti-rollover control for agricultural tractors, although great progress in the research on tractor security
has been achieved, such as rollover protective structure design.

Objective:
The purpose of this patent study was to develop a controller with the function of warning
as well as active anti-rollover control employing the power motor installed on the steering column
to adjust the front wheel angle and control the rollover index within the safety range.

Methodology:
The structure block for the hardware of the controller was devised that included data
obtaining, rollover risk estimation, rollover warning, and front-wheel steering control sections. The
main circuits have been designed in detail by adopting module methods, such as motor control circuit,
positioning and transmission circuit, etc. The control scheme has been demonstrated by designing
an overview of the overall architecture, including rollover indicator calculation, load transfer
ratio (LTR) controller design, and front-wheel steering angle tracking controller design. C language
has been used to accomplish the software design.

Results:
The active anti-rollover controller can calculate and keep the LTR within the stable range
by adjusting the front wheel angle in real-time. The fast response and smoothness of the results
demonstrate that the controller can fulfill the designed function.

Conclusion:
The developed controller can meet the control requirement due to several advantageous
aspects, such as reliability, effectiveness, and practicability. It is prospective for the developed
controller to provide a valuable reference to reduce tractor rollover accidents.
Pengaruh Kualitas Pelayanan Terhadap Kepuasan Peserta Didik pada LKP Bahasa Inggris di Kota Malang
Authors: Rahmania Nur Cholidia , Redjeki Endang Sri , Widianto Edi 
Published: June 2023

Abstrak: Kualitas pelayanan menjadi salah satu tolak ukur dalam menilai kualitas LKP, sedangkan kepuasan merupakan aspek luaran dalam menilai kualitas pelayanan LKP. Meningkatnya jumlah LKP di Kota Malang menjadi hal yang menarik, apakah dengan banyaknya LKP di Kota Malang selaras dengan kualitas pelayanan yang diberikan?. Penelitian ini bertujuan untuk: 1) mengetahui kualitas pelayanan LKP Bahasa Inggris di Kota Malang, 2) mengetahui kepuasan peserta didik pada LKP Bahasa Inggris di Kota Malang, 3) menganalisis pengaruh kualitas pelayanan terhadap kepuasan peserta didik pada LKP Bahasa Inggris di Kota Malang. Penelitian ini menggunakan pendekatan kuantitatif dengan jenis penelitian survey. Analisis data penelitian menggunakan statistik deskriptif dan explanatory research. Hasil penelitian menunjukkan bahwa: 1) kualitas pelayanan pada LKP Bahasa Inggris di Kota Malang dikategorikan baik, 2) kepuasan peserta didik atas layanan yang diberikan LKP Bahasa Inggris di Kota Malang dikategorikan puas, 3) terdapat pengaruh kualitas pelayanan terhadap kepuasan peserta didik pada LKP Bahasa Inggris di Kota Malang. The Effect of Service Quality on Student Satisfaction at the English Course and Training Institute (LKP) in Malang.Abstract: Service quality is one of the benchmarks in assessing the quality of LKP, while satisfaction is an output aspect in evaluating the quality of LKP services. The increasing of LKP in Malang is an interesting matter. Is the number of LKP in Malang consistent with the quality of services provided? This study aims to: 1) knowing the service quality of English LKP in Malang, 2) knowing student satisfaction in English LKP in Malang, 3) analyze the effect of service quality on student satisfaction in English LKP in Malang. This research uses a quantitative approach to the type of survey research. Data analysis used descriptive statistics and explanatory research. The results showed that: 1) the quality of service at the English LKP in Malang was categorized as good, 2) the students' satisfaction with the services provided by the English LKP in Malang was categorized as satisfied, 3) there was an effect of the effect of service quality on student satisfaction at the LKP English in Malang.
Geometrical Motifs Batik Sarongs Kelantan and Terengganu
Authors: Legino Rafeah , Zuhir Nikfarhana , Samin Mohd Azhar 
Published: June 2023

This study shows how geometric patterns are used on some Kelantan and Terengganu batik sarongs. A visual research visit was made to batik makers in Kelantan and Terengganu. This study was unique because it was based on observation and had the right digital documentation for further analysis. Geometric features were mapped using recent and previous related literature and visual images. This method will help figure out how long motifs last and how they change in both states. The results showed the motifs, how the basic geometric shapes were made, and how other characters showed up in the geometric settings.
Improving Surveillance of Human Tick-Borne Disease Risks: Spatial Analysis Using Multimodal Databases
Authors: Maxwell Sarah P , Brooks Chris , Kim Dohyeong , McNeely Connie L , Cho Seonga , Thomas Kevin C 
Published: June 2023

Background
The extent of tick-borne disease (TBD) risk in the United States is generally unknown. Active surveillance using entomological measures, such as presence and density of infected nymphal Ixodes scapularis ticks, have served as indicators for assessing human risk, but results have been inconsistent and passive surveillance via public health systems suggests TBDs are underreported.

Objective
Research using various data sources and collection methods (eg, Google Trends, apps, and tick bite encounters [TBEs] reports) has shown promise for assessing human TBD risk. In that vein, and engaging a One Health perspective, this study used multimodal databases, geographically overlaying patient survey data on TBEs and concomitant reports of TBDs with data drawn from other sources, such as canine serological reports, to glean insights and to determine and assess the use of various indicators as proxies for human TBD risk.

Methods
This study used a mixed methods research strategy, relying on triangulation techniques and drawing on multiple data sources to provide insights into various aspects of human disease risk from TBEs and TBDs in the United States. A web-based survey was conducted over a 15-month period beginning in December 2020 to collect data on TBEs. To maximize the value of the covariate data, related analyses included TBE reports that occurred in the United States between January 1, 2000, and March 31, 2021. TBEs among patients diagnosed with Lyme disease were analyzed at the county level and compared to I scapularis and I pacificus tick presence, human cases identified by the Centers for Disease Control and Prevention (CDC), and canine serological data. Spatial analyses employed multilayer thematic mapping and other techniques.

Results
After cleaning, survey results showed a total of 249 (75.7%) TBEs spread across 148 respondents (61.9% of all respondents, 81.7% of TBE-positive respondents); 144 (4.7%) counties in 30 states (60%) remained eligible for analysis, with an average of 1.68 (SD 1.00) and median of 1 (IQR 1) TBEs per respondent. Analysis revealed significant spatial matching at the county level among patient survey reports of TBEs and disease risk indicators from the CDC and other official sources. Thematic mapping results included one-for-one county-level matching of reported TBEs with at least 1 designated source of human disease risk (ie, positive canine serological tests, CDC-reported Lyme disease, or known tick presence).

Conclusions
Use of triangulation methods to integrate patient data on TBE recall with established canine serological reports, tick presence, and official human TBD information offers more granular, county-level information regarding TBD risk to inform clinicians and public health officials. Such data may supplement public health sources to offer improved surveillance and provide bases for developing robust proxies for TBD risk among humans.