bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Vehicle Detection Algorithm Based on Embedded ARM
Authors: Deng Yueming , Deng Dan 
Published: October 2024

Abstract
Based on the theory of machine learning in the field of artificial intelligence, this paper proposes to use the computer vision platform OpenCV to construct an embedded ARM vehicle detection model. Determine the ARM embedded software and hardware and adopt Haar features for the Adaboost algorithm to design the OpenCV vehicle classifier. Cross-compile the ARM chip using Linux to generate new firmware for OpenMV. Use the DFU tool for embedded ARM chips to upgrade and re-burn them into the embedded development board for machine vision OpenMV. By using the classifier file and OpenCV’s image processing algorithm, the work of vehicle detection and recognition is completed, and the vehicle target is labeled with a candidate box in the picture and video. The results demonstrate that the algorithm in this paper maintains the leakage detection rate and false detection rate below 5% in four different working conditions: strong light, normal light, weak light, and nighttime, thereby fully demonstrating the effectiveness of the research conducted in this paper.
Research on College Students’ Career Planning and Employment Guidance Strategies Assisted by Artificial Intelligence
Authors: Feng Ke 
Published: October 2024

Abstract
The number of college graduates is increasing year by year, and college students’ career planning and employment have always been a high concern of the community. The article describes the specific role of artificial intelligence technology in assisting college students’ career planning and employment guidance and combines WEB technology to construct a college student’s career planning and employment guidance service platform. The information entropy is used to construct the feature importance set of student employment data, and the simple Bayesian algorithm is used to realize the construction of the classification model of student employment service data in combination with the feature importance. On the basis of considering the selection of students’ employment information, the time decay factor is introduced to improve the personalized recommendation algorithm, and the cosine similarity between students’ employment positions is calculated so as to realize the generation of students’ employment service information recommendation. The area of the classification ROC curve of the plain Bayesian model is more than 95%, the classification time for student employment service data is only 5.62ms, and the F1 value of the employment service information recommendation result is 6.03% higher than that of the traditional method. The college students’ career planning and employment guidance service platform was only satisfactory for 31.77% of the students, with the highest satisfaction score of 3.69 for getting information. Relying on artificial intelligence technology can help students make personalized recommendations for employment service information, which can improve the level of career planning and guidance for college students.
Daily Load Forecasting and Data-Driven Strategies for Steel Industry Based on Random Forest Modeling
Authors: Wang Siteng , Zhang Luxi , Cao Zhiyuan , Zhang Rui , Zhang Liwei 
Published: October 2024

Abstract
As a large power consumer, the iron and steel industry urgently needs to improve productivity, reduce energy consumption, and save costs by revolutionizing energy management. In this study, we design a power demand management system for the iron and steel industry, and around the load management module, we propose a data-driven strategy based on daily load situational awareness and introduce the random forest model into daily load forecasting in the iron and steel industry. At the same time, the projection principle is applied to improve the traditional gray correlation similar day selection algorithm, and a combination method of daily load forecasting based on the gray projection improved random forest algorithm is proposed. The electric load data of the iron and steel industry in a specific region is utilized as an experimental sample to investigate the model’s forecasting performance and the impact of the data-driven strategy. The model for daily load forecasting in this paper has an average relative error of 1.18%, which is better than other models. The application of the data-driven strategy brought about 6.99% and 6.69% reductions in load demand and basic electricity cost. The data-driven strategy for the steel industry based on the Random Forest model can predict electric loads more accurately and reduce energy costs, as shown by the results.
Research on Enterprise Financial Management Strategy and Framework for Digital Transformation
Authors: Zhang Yingying 
Published: October 2024

Abstract
In the wave of the information age, enterprises must undergo digital transformation in order to respond to and implement the national development strategy and improve their core competitiveness. This paper constructs a strategic framework for enterprise financial management in digital transformation and evaluates the effects of digital transformation on profitability levels and operating costs. A theoretical model is created for the impact of digital transformation on enterprise financial management; research hypotheses are proposed, research variables are established, and research hypotheses are tested for authenticity. After the implementation of digital transformation, the subject enterprise M Group has not maintained its net profit growth for a long time. However, it has been on an upward trend from 2014 to 2016. The growth rate of net profit is expected to be within 20% from 2017 to 2023, with room for further development. In the benchmark regression of the model, it was found that there is a significant positive correlation between the index of financial digital transformation and the financial performance of businesses, with a coefficient of 0.0154 at the 5% level. This means that the more businesses digitize their finances, the better their financial performance.
The guiding significance of consumer visual perception on the packaging design of cultural and creative products
Authors: Huang Yuchun 
Published: October 2024

Abstract
The packaging of cultural and creative products plays a crucial role in enhancing their competitiveness, with exquisite packaging significantly contributing to meeting the personalized needs of consumers and stimulating their desire to purchase. This paper examines the visual perception factors involved in the packaging design of cultural and creative products using the visual attention mechanism and categorizes the design factors according to demand using the Kano model. The hierarchical analysis method is used to determine the consumer demand weight of each design factor. The packaging solutions for cultural and creative products are finalized, and the TOPSIS method is employed to assess each solution. The hierarchical analysis model achieves consistency ratios of 0.076, 0.016, 0.003, and 0.004 for the target layer Z and the criterion layers M, O, and A, respectively, all of which are less than 0.1, thereby passing the consistency test. Among the three designed packaging schemes for cultural and creative products, scheme 1 has the largest S value, which is 0.899. Therefore, scheme 1 is the best design scheme. The existing sample scheme has a S value of 0.013, which is smaller than that of the other three design schemes. The integrated Kano-AHP-TOPSIS packaging design path’s design schemes for cultural and creative products are more likely to meet consumers’ needs, demonstrating the path’s practical feasibility and the importance of consumer visual perception in shaping packaging design for these products.
Analysis of garment watermark design based on multilayer coding genetic algorithm
Authors: Zhou Ying 
Published: October 2024

Abstract
It has become a trend to publish clothing design works in the form of digitized images and other media on the network. This topic focuses on the watermark logo of clothing design. After sorting out the ideas of copyright protection of clothing design, constructing a clothing watermark design model based on the discrete cosine variation method and using a multilayer coding genetic algorithm to find the optimization band to improve the invisibility and robustness of the watermark. Experiments are designed to explore the aesthetic effect of clothing watermark design, and it has been found that the model in this paper achieves the maximum capacity in the steganography task with good concealment. Different attack training results in the model’s PSNR and SSIM values exceeding 40 and 0.92, respectively. The NC value stays above 0.91 under different intensity attacks, which validates the invisibility and robustness of the garment watermark design model based on a multilayer coding genetic algorithm. The model in this paper has improved garment watermark embedding and watermark extraction capabilities.
Managing Inclusion and Financial Education for Sustainable Development
Authors: Robles Luis Fernando Zamudio , Romero Roberto Burgueño , Mendias Bryan Alonso Ramos 
Published: October 2024

Objective: The objective of this study is to analyze the importance of effective management of financial inclusion and education in the context of sustainable development, highlighting its impact on the achievement of the SDGs. It also aims to identify the main challenges faced by vulnerable populations in accessing financial services and propose comprehensive strategies to improve financial literacy and accessibility, contributing to a more inclusive and equitable society.

Theoretical Framework: For this research we have several relevant approaches and theories such as: financial inclusion theory; its relationship with the SDGs; financial education theory, as well as inclusion and sustainable development.

Method: The methodology adopted for this research comprises a qualitative approach, based on the review of documents, public policies and government programs on financial inclusion and education to assess their effectiveness with respect to the SDGs. Data from the World Bank's Data Dashboard (The Global Findex Database, 2024) was analyzed using content analysis, which allowed identifying key themes and gaining a deeper understanding of the perceptions and experiences related to the evaluated programs..

Results and Discussion:The results obtained revealed that, although there is progress in financial inclusion in Mexico, there are still areas of opportunity to improve access to and use of financial services, especially among the most vulnerable segments of the population. It is necessary to highlight the need to continue working on the promotion of financial inclusion in Mexico and in other regions, through public policies that promote financial education, technological innovation, and collaboration between the public and private sectors.

Research Implications: The practical implications of this research include the improvement of public policies and programs focused on financial inclusion and education, promoting more equitable access to financial services in vulnerable populations. At a theoretical level, the study provides a deeper understanding of the relationship between financial management and sustainable development, offering a conceptual framework that links financial inclusion with the SDGs. This strengthens the academic analysis on how financial education can drive inclusive economic growth.

Originality/Value: The originality and value of this research lies in its focus on the direct relationship between financial inclusion and financial education with the SDGs, an area underdeveloped in the literature. The research offers a new perspective by assessing how financial education can be a key tool for achieving equitable and sustainable development. Its contribution to the literature is in providing a detailed analysis of public policies and government programs, highlighting their effectiveness and identifying areas for improvement, which brings a comprehensive and updated approach to the study of financial inclusion.
Human β-Defensin 2 as a Link between EBV Infection and Multiple Sclerosis
Authors: Refaat Aya , Younis Hala 
Published: October 2024

Multiple sclerosis (MS) is the result of a complex interaction between environmental factors and genetic predisposition.
Epstein-Barr virus (EBV) is a significant environmental risk factor associated with MS. Human- beta defensin 2 (HβD-2) is a crucial innate immune response proteint that as an inflammatory marker protects humans from pathogens invading the body like viruses. Therefore, a case-control study was conducted on 90 subjected (48 patients with MS and 42 healthy controls) to examine the role of HβD-2 in EBV viral load infection and MS patients. An enzyme-linked immunosorbentassay kit was used to measure HβD-2 levels in serum. The viral load of EBV was determined using a real-time PCR. The findings revealed that median HβD-2 levels in patients were significantly lower than in controls. (96.62 vs.124.8 ng/mL; p < 0.01). According to the receiver operating characteristic curve analysis, HβD-2 is good predictor for MS disease (area under the curve=0.739; p < 0.001). EBV frequency was lower in MS patients compared to the controls, although difference was not statistically significant (25 vs. 38.1%; p = 0.181).On other hand, the median (EBV) load was substantially greater in patients than in healthy controls ( 8.55 vs. 1.4 DNA copy/100 cells). This study concluded that HβD-2 levels showed no significant differences in each age group, sex, Expanded Disability Status Scale (EDSS) of multiple sclerosis patients, rather showed an inverse significant correlation (correlation coefficient = - 0.432) with EBV load, which protect against human viral infections.
Inhibition of the Hyaluronidase Enzyme Produced by Staphylococcus Bacteria Using Vasicine Alkaloids of the Vasica Plant
Authors: Fayyad Sara Ali , Majeed Majid Rasheed 
Published: October 2024

Hyaluronidase is an enzyme that breaks down primarily hyaluronic acid, thereby disrupting the structural integrity of the extracellular matrix (ECM) found in connective tissues, which is considered a virulence factor. The aim of this research was to study the effect of a plant-active compound (vasicine) that was separated from a plant sample as an inhibitor agent for the hyaluronidase enzyme that was isolated from Staphylococcus aureus, which is considered a virulence factor. 120 samples were randomly isolated from infected burns. The isolates showing highly hydrolyzed zones were identified. Cell growth as well as hyaluronidase activity are measured spectrophotometrically by the turbidity reduction assay. The results showed that 100 out of 120 clinical samples grew bacteria when cultured on blood agar medium. Also, it was found that of the 100 isolates, 56 (56%) belonged to S. aureus and had an inhibitory zone of hyaluronidase of 5–26 mm, and the inhibitory zone was increasing over time.
Influence of Forced Field on Blood Flow in an Overlapping Stenosed Arterial Section
Authors: Dhange M. , Sankad G. , Bhajakkanar U. , Jaafar Nurul Aini 
Published: October 2024

This article presents the theoretical analysis of the nonlinear behavior of the blood flow through an angled arterial segment with overlapping stenosis. A mathematically created time-variant stenosis emerges from the formation of arterial narrowing brought on by atheroma. An elastic cylindrical tube with a moving wall is used to represent the artery, and the Casson liquid is used to simulate blood that flows through it. The nonlinear elements that arise in the equations, govern blood flow are taken into account. The impact of the pulsatile pressure gradient that caused by the regular heartbeat on the flow process in the stenosed artery is demonstrated mathematically. By employing the boundary conditions, the present analytical technique can easily compute the velocity profiles, wall shear stress, and flow resistivity. To carry out a systematic quantitative study, the desired quantities are numerically computed. The results are graphically presented in the discussion section. They provide an overview of how the degree of stenosis and the malleability of the artery wall influence blood flow abnormalities. The application of the current model is adequately justified by many significant conclusions.
s-WH Modules
Authors: Mohammed Osama Basim , Ghawi Thaar Younis 
Published: October 2024

This article introduces the concept of strongly-WH module which is a proper generalized of Hopfian modules. A module is called strongly-WH, briefly -WH if, any -small surjective -endomorphism of is an automorphism. We specify and provide some properties of this concept. Furthermore, we have established connections between strongly-WH modules and various other concepts. We demonstrate that every strongly-WH module is -weakly Hopfian. As well as, we provide cases in which the concepts of WH, -weakly Hopfian, and strongly-WH modules are equivalent.
Internal Electrostatic Discharge Modeling: Validation and Fitting Using Tests on Insulated Wires
Authors: Chinn James , Kim Wousik , Andersen Allen , Thorbourn Dennis , Martin Eduardo 
Published: October 2024

Electron beam tests were conducted to observe the internal electrostatic discharge behavior of four wire samples arcing into three termination resistors. The charging environment during the test was also simulated using 3-D NUMIT to calculate the expected voltage development within each wire. The impedances of the wires and the test setup were measured and included in a circuit model of the discharging wire connected to the measurement circuit. The circuit model was fit to the largest discharge observed on a 50 Ω load. The circuit model was then used to simulate discharges into 5 kΩ and 10 MΩ terminations, and the simulated pulses were compared to observed pulses on those terminations. Simulated peak voltages agree with observed voltages to within a factor of 1.6 and simulated decay times agree with observed decay times to within a factor of 2.3. For large pulses, derived source voltages range from 3.7 to 15.5 kV, derived source capacitances range from 4 to 11 pF, and derived source resistances range from 1100 to 3500 Ω.
Mixing Enhancement Mechanism of Liquid Jet in Supersonic Crossflow with Gas Throttling
Authors: Zhou Yaozhi , Cai Zun , Li Qinglian , Li Fei , Yang Xiaolong , Wang Taiyu , Li Chenyang , Wei Feng , Chen Zihang , Sun Mingbo 
Published: October 2024

Numerical and experimental studies were conducted to uncover the physical aspects of a liquid jet injected into a supersonic crossflow with gas throttling systematically. The results were obtained with the inflow conditions of a Mach number of 2.0, a total temperature of 300 K, and a total pressure of 0.55 MPa. The results show that fuel–air mixing is considerably enhanced due to shock-induced flow distortion by adding gas throttling. The strength of downstream backpressure determines the distance of forward movement of the throttling shock wave train and the flowfield structure in the channel. When the mass flux of gas throttling is high, the influence of throttling gas spreads across the expansion section, resulting in significant flow separation in front of the liquid jet. It is found that the spray flashback phenomenon is similar to the flame flashback phenomenon that occurs in the supersonic combustion process under the action of a precombustion shock train. The wall counterrotating vortex pair and induced cavity streamwise vortices are enhanced with the increase of the flux of gas throttling. The relatively high-pressure environment generated by gas throttling promotes the atomization of droplets. As a result, the mixing enhancement mechanism of a liquid jet in a supersonic crossflow with gas throttling is mainly due to the combined effects of 1) the shock waves separating the side wall boundary layer and modifying the local flow state of air in the combustor, which lead to a dramatic increase in fuel–air mixing, and 2) the streamwise vorticity values as well as the residence time resulting from channel blockage elevating.
Eficácia de infiltrações intra-articulares guiadas por ultrassom no tratamento da dor em pacientes com Osteoartrite do Joelho
Authors: Santana Bruno Sousa , Oliveira Larissa Alencar de , Xavier Rodson Melo , Tannus Lorena de Oliveira , Feitosa Marcela de Oliveira 
Published: October 2024

Objetivo: Realizar revisão integrativa sobre a eficácia de infiltrações intra-articulares guiadas por ultrassom no tratamento da dor em pacientes com osteoartrite do joelho. Métodos: Trata-se de um estudo do tipo revisão integrativa. A amostra foi composta por trabalhos científicos que responderam à questão de pesquisa e a coleta de dados realizada em fevereiro de 2024. Resultados: Constatou-se que o tratamento oral para OAJ não é suficiente para controlar a doença e, por essa razão, a prescrição de infiltração por via intra-articular tem sido satisfatória, principalmente quando guiadas por ultrassom. As infiltrações melhoram a rigidez, a capacidade funcional e a mobilidade. Além disso, proporcionam maior conforto, bem-estar e qualidade de vida para o indivíduo com OAJ. Conclusão: as infiltrações intra-articulares guiadas por ultrassom são mais eficientes que outras modalidades farmacológicas, por reduzirem significativamente as queixas álgicas em período mais prolongado, melhorar a rigidez, capacidade funcional, mobilidade e por assegurar aos portadores de OAJ maior conforto, bem-estar e qualidade de vida. Além disso, as infiltrações intra-articulares guiadas por ultrassom são realizadas de forma mais segura e eficaz.