bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of Subway Investment Management Platform Under the Background of Informatization
Authors: Zhang Qinjian 
Published: August 2024

Abstract
This article aims to design a subway investment management platform based on DL (Deep Learning) to improve subway projects' investment efficiency and risk management levels. The article adopted the DL algorithm to comprehensively analyze historical subway investment data and constructed prediction and risk assessment models to achieve this goal. The application effect of the DL algorithm in subway investment management and the practicality of the platform were verified through simulation experiments. This article first collected a large amount of historical subway investment data and processed and learned these data using the DL algorithm. By constructing an NN (Neural Network) model, accurate prediction of investment return rate and market demand for subway projects has been successfully achieved. Furthermore, a risk assessment model was also constructed to quantify and evaluate potential risks in subway projects. The experimental results indicate that the DL algorithm has significant prediction and risk assessment advantages. Compared with traditional statistical learning methods and machine learning algorithms, the DL algorithm can more accurately predict investment return and market demand, providing users with more reliable decision support. In addition, the risk assessment model effectively helps users understand the risk status of the project and formulate corresponding risk management measures.
Construction of Image Education Knowledge Map Model Based on Data Mining Technology
Authors: Hongbo Liu , Omar Siti Zobidah , He Chen , Shanshan Wang 
Published: August 2024

Abstract
Data mining (DM) technology is increasingly used in higher education, especially imaging education. The IEKMM model connects knowledge, problems, and abilities, addressing asymmetrical relationships and supporting network reasoning tasks. The SSME model preserves IEKMM’s semantic information, enhancing instruction quality and efficiency, and advancing personalized learning initiatives. Findings reveal that the distributed representation of entities and relationships, trained using the SSME (Semantic Symbol Mapping Embedding) model, effectively preserves the original semantic information of the IEKMM. This provides a foundation for implementing knowledge maps in educational settings and is crucial for advancing personalized learning initiatives.
Teaching Management Data Analysis Method Based on Decision Tree Algorithm
Authors: Wang Peng 
Published: August 2024

Abstract
Driven by the current teaching management situation, teaching administrators at all levels generally hope to build a more complete teaching data operation center and data analysis system by using advanced information technology to provide teaching management personnel with a more comprehensive historical data analysis function. In the graph and improvement of the educating administration facts evaluation machine in this paper, the information warehouse and facts mining science used in the gadget are deeply studied. First of all, the troubles in the current instructing administration machine are analyzed in a centered manner, the technical framework of the entire teaching management data analysis system is designed and planned, and the various components of the framework are described and described in detail according to actual needs. Then, after the comparative evaluation of the facts warehouse and records mining strategies extensively used in more than a few fields in the present fields, the more than a few classical algorithms that can be utilized to the educating administration information evaluation device is improved, and the algorithms and algorithms are used to analyze the course grades and employment of the graduated alumni respectively, and the decision tree model is established, and finally the algorithm efficiency comparison chart is concluded that the improved C4.5 algorithm is better than the other three algorithms in terms of accuracy and time efficiency, and shows good classification performance.
Analysis and Innovation of Vocal Music Teaching Quality in Colleges and Universities Based on Artificial Intelligence
Authors: Hou HuiQing 
Published: August 2024

Abstract
The collision between the field of education and the field of artificial intelligence has helped the wisdom reform of college classrooms. At present, traditional vocal music teaching is inefficient and difficult to manage, but it is faced with the dilemma of resource shortage. Therefore, to improve the quality of classroom vocal music teaching in colleges and universities, using innovative thinking, this paper intends to design an artificial intelligence system for evaluating and analyzing classroom effects. Use the test vocal music characteristic parameters for comparison, through the analytic hierarchy process to calculate the quality of the classroom teaching evaluation index, and auxiliary management of the vocal music teaching process. The final simulation results are in line with expectations. It can not only evaluate the whole teaching process reasonably but also help teachers improve the quality of vocal music teaching, which has strong practical value.
Research on action analysis and guidance in aerobics blended learning based on data mining
Authors: Ge Zhibin , Xia Qionghua 
Published: August 2024

Abstract
Teaching has gradually become more important, no matter which aspect of teaching must be continuously improved and kept up with the pace of development. Aerobics teaching has not been paid much attention by the masses, and many remain in the traditional teaching mode, which will delay the development of aerobics. This paper conducts an in-depth study of aerobics mixed teaching and action analysis guidance under data mining: (1) The blended learning and data mining are fully explained, and only when the two are integrated can better research be carried out. (2) The research on aerobics movements is very complicated. The process and form of the movements are analyzed through the skeleton time graph convolution and spatial graph convolution, and the action probability PCA model is established to facilitate the public study. (3) Blended learning and traditional learning of aerobics After in-depth comparison, it is found that blended learning has more advantages than traditional learning in many aspects. The learning mode should keep pace with the times, and blended learning can better teach.
Application of Routing Algorithm Based on Logical Petri Nets in the Structural Design of Agricultural Products Logistics System
Authors: Wang ZhuYun , Wang LingLi , Xu Le 
Published: August 2024

Abstract
In agricultural services, logistics around agricultural products has been the focus of academic attention. To implement efficient and safe logistics of agricultural products and optimize logistics' overall efficiency and investment cost. This paper describes in detail the routing algorithm based on logical Petri nets, proposes a research system for agricultural product logistics based on the routing algorithm, and analyses system operation results through simulation experiments. The specific conclusions are as follows: (1) The logistics information modeling software based on logical Petri net is established, and the LPN model of the logistics information set is built based on it. (2) It is proposed that the server computer acts as a cloud service platform. The independent computer represents the traditional logistics information retrieval model, and the computational efficiency has been significantly improved. (3) The use of server computers to obtain logistics information in 300-400ms and the use of stand-alone computers to obtain logistics information in 50-120ms, the use of server computers to obtain logistics information is more efficient than using stand-alone computers. (4) Logistics data is a fast-growing trend; stand-alone computers cannot store massive data.
Application and Optimization of WIFI Positioning algorithm in College Classroom Roll Call: A Positioning Strategy based on Mathematical Optimization
Authors: Zhou Shuqiang 
Published: August 2024

Abstract
In this paper, the WIFI localization algorithm based on the signal intensity feature matching is studied and combined with the mathematical optimization strategy. By constructing accurate mathematical models, the algorithm can process signal intensity data more accurately and reduce the influence of environmental factors on the localization results. This positioning strategy based on mathematical optimization not only improves the positioning accuracy, but also improves the stability and practicability of the system, and provides an innovative technical means for the classroom roll call system in universities, which has important practical value and promotion prospects.
Can VO2max be accurately estimated using exercise-duration based prediction equations and a nomogram?
Authors: Adam Natalie A. , Duquette Adriana M. 
Published: August 2024

Abstract

Study aim: The purpose of this study was to examine a large cohort of young Canadian adults to determine if exercise time from a maximal Bruce Treadmill Protocol could accurately predict measured VO2max values by inputting the total exercise time into prediction equations and a nomogram.

Materials and methods: 550 kinesiology undergraduate student (280 male and 270 female) participants, with a mean body mass (BM) of 72.08 ± 15.05 kg, mean age of 21.16 ± 1.26 years old and mean height of 171.95 ± 10.25 cm completed a maximal graded exercise test to obtain their VO2max (measured). Predicted VO2max was calculated with various equations using the variable of total exercise test time. Linear regression models were created to determine how well the predicted VO2max values compared to the measured values.

Results: Across all VO2max calculation methods, males obtained higher VO2max values on both the measured (49.89 ± 9.21 mL/ kg/min) and predicted values (46.04–55.40 mL/kg/min) and exercised for a longer duration of time (14.33 minutes) compared to females (40.89 ± 7.50 mL/kg/min, 38.87–48.36 mL/kg/min, 11.92 minutes). Classifications and percentile rankings were created using each measured and predicted method.

Conclusions: The Healthy Persons Equation [6], Healthy Men and Women Equation [2], Active and Sedentary Women/Men Equations [10, 22] and nomogram [13] cannot accurately predict VO2max in healthy young adults, with R2 values between 0.38–0.50. The Healthy Persons Equation [6] was found to very closely mimic the seven-category classifications determined from the measured CPET VO2max values.
Changes in adipokine indicators depending on A1166C polymorphism of the angiotensin II type 1 receptor gene as a predictor of the arterial hypertension
Authors: Pidruchna Svitlana , Shmanko Volodymyr , Zakharchuk Uliana , Tokarskyy Oleksandr , Hnizdyukh Roman , Lynkhatskyi Petro , Kuzmak Iryna , Yaroshenko Tetyana , Bandas Iryna , Vasylyshyn Nadija , Ostrivka Oksana , Mudra Alla , Palytsya Liliya , Letniak Nataliya , Pohorielova Oksana 
Published: August 2024

Abstract

Objective. Genetic factors substantially contribute to the development and duration of arterial hypertension. The study of the A1166C polymorphism of the angiotensin II type 1 receptor gene (AGTR1) in arterial hypertension is an auspicious area for assessing the relationship between heredity, hypertension development, and adipokines, but it still remains debatable. The purpose of the current study was to investigate serum adipokines levels depending on the AGTR1 A1166C polymorphism.

Methods. A total of 86 patients with arterial hypertension were examined, who underwent the evaluation of the allelic A1166C polymorphism of AGTR1 by polymerase chain reaction with electrophoretic detection and determination of serum adipokines levels using enzyme-linked immunosorbent assay.

Results. In the group of patients with arterial hypertension, a significant increase in serum adipokines (resistin, adiponectin, and leptin) levels was found against the background of a decrease in the antianorexic hormone ghrelin with a predominance of CC genotype carriers compared with AA genotype carriers of the AGTR1. A statistically significant decrease in ghrelin and an increase in serum adipokines (resistin, adiponectin, and leptin) in CC genotype carriers compared with AA genotype carriers of the AGTR1 were found suggesting that CC genotype carriers may be predictors of the development of arterial hypertension in our patients.

Conclusions. Statistically significant decrease in ghrelin and increase in serum adipokines (resistin, adiponectin, and leptin) were found in CC genotype carriers compared with AA genotype carriers of the AGTR1, which suggests that carriers of the CC genotype are predictors of the arterial hypertension development in our patients.
Remarks on the Increasing of Liability of for Certain Traffic Offences
Authors: Łucarz Katarzyna 
Published: August 2024

Abstract
The author discusses the nature and scope of changes introduced to the Code of Petty Offences and the Code of Procedure in Petty Offences Cases by the Act of 2 December 2021. The amendment represents a drastic intervention by the legislator in the current legal framework regarding offences against safety and order in transportation. It foresees significant modifications in the legal and criminal response to these offences, transformations in the characteristics of selected types of prohibited acts, and proposes entirely new types of prohibited acts. The analysis suggests that the guiding principle behind these changes is to increase the degree of punitiveness of petty offences law towards perpetrators of traffic violations. This legislative approach raises concerns about the instrumental use of petty offences law with respect to the perpetrators of these offences. The adopted direction of changes raises suspicions that the legislator has not thoroughly familiarised themselves with the matter covered by their intervention. In any case, it is not grounded in the current state of traffic criminality, or in the analysis of judicial practice. An increase in repressiveness has never directly translated into a reduction in traffic criminality. The latter is a much more complex problem, involving the necessity of multi-faceted references.
Termination of Employment Relationship in Uniformed Services in Connection with their Reorganisation or Dissolution–Constitutional Issues
Authors: Szustakiewicz Przemysław , Wieczorek Mariusz 
Published: August 2024

Abstract
This article addresses the legal issues arising from the transformation of internal security bodies within the structure of public administration, specifically focusing on how such events impact the service relationship of officers employed in those structures (the so-called ‘uniformed services’). The analysis covers regulations governing the service relationships of officers in the State Protection Office, Government Protection Bureau, and Customs Services in connection with the dissolution of these institutions and the establishment of the Internal Security Agency, the Intelligence Agency, the State Protection Service, and the Customs and Fiscal Service. Theoretical and legal models are identified, and substantive legal provisions are presented to assess their compliance with the relevant provisions of the Constitution of the Republic of Poland.
An optimized integral performance criterion based commercial PID controller design for boost converter
Authors: Irshad Mohammad , Vemula Naresh Kumar , Devarapalli Ramesh , Kumar Gundavarapu Venkata Nagesh , Knypiński Łukasz 
Published: August 2024

Abstract
Boost converters often face challenges such as sluggish dynamic behavior, inadequate voltage regulation, and variations in input voltage and load current. These issues necessitate the need for closed-loop operation. Nature-inspired optimization algorithms (NIOA) have demonstrated their effectiveness in delivering enhanced solutions for various engineering problems. Several studies have been conducted on the use of proportional-integral-derivative (PID) controllers for controlling boost converters, as documented in the literature. Some studies have shown that using fractional order PID (FO-PID) controllers can lead to better performance than traditional PID controllers. Nevertheless, implementing FO-PID can be quite complex. Considering the widespread use of commercial PID controllers in industrial settings, this study focuses on finding the best tuning for these controllers in DC-DC boost converters. The approach used is particle swarm optimization (PSO) based on integral performance criteria. Simulation results indicate that the proposed controller achieves superior performance, evidenced by the lowest settling time, overshoot, integral absolute error (IAE), and integral squared error (ISE) values under varying input voltage and load current conditions, compared to both PID and FO-PID controllers. These findings have been confirmed through hardware implementation, which demonstrates the effectiveness of the proposed controller.
Comparative performance analysis of robust and adaptive controller for three-link robotic manipulator system
Authors: Sweta  , Deolia Vinay Kumar , Kumar Jitendra 
Published: August 2024

Abstract
Three-link robotic manipulator systems (TLRMS) often used in automation industries offer many capabilities, but become very complex in terms of their control and operations. In order to enhance trajectory tracking in the X and Y axes, this study investigates the application of a fractional-order nonlinear proportional, integral, and derivative (FONPID) controller for a three-link robotic manipulator system (TLRMS). Using a cost function that combines the integral of square error (ISE) and the integral of absolute change in controller output (IACCO), the cuckoo search algorithm (CSA) maximises the performance of the controller. The fractional-order term enhances the robustness and the nonlinear term supports the adaptiveness of the FONPID controller. The fractional-order proportional, integral, and derivative (FOPID) and classic PID controllers are contrasted with the FONPID controller's efficacy. The findings show that the CSA-tuned FONPID performs better than the other controllers, providing more robust and accurate tracking. By demonstrating fractional-order control's promise for intricate robotic systems, this study advances the discipline.
Series partial power converter with half bridge LLC series resonant converter for PV application
Authors: Kurichiparambil Sebin Davis , Jegathesan Varghese 
Published: August 2024

Abstract
This study proposes a series partial power converter with a half-bridge LLC series resonant converter for photovoltaic (PV) applications. The main advantage of the implementation of a partial power converter with LLC series resonant converter is zero voltage switching (ZVS) operation of primary side enables the converter to work at a higher switching frequency. The partial power topology used in the proposed converter enables low power rating switches in the primary, which in other terms reduces the primary current. The proposed converter achieves excellent efficiency due to its ZVS and partial power operating capabilities. The valuation of the proposed converter is done in MATLAB Simulink with a 300 W PV module, which is made to operate in varying irradiance and module temperature of 25 °C. The operational waveforms and the power outputs obtained when the proposed converter is implemented by using perturbation and observation (P&O) maximum power point tracking (MPPT) control algorithm are discussed in this paper.
Morphological and molecular characterisation of the nematode parasite Graphidioides affinis (Secernentea: Trichostrongylidae) in Patagonian maras, Dolichotis patagonum, kept in a zoo in Sofia, Bulgaria
Authors: Panayotova-Pencheva Mariana , Laskowski Zdzisław , Pyziel Anna Maria 
Published: August 2024

Abstract

Introduction
Patagonian maras, rodents endemic to South America, are classified as a near-threatened species. Various factors affect their health including parasitic diseases. The aim of this study was to perform morphometric, molecular and phylogenetic characterisation of one such parasitic disease agent, the nematode Graphidioides affinis, specimens of which were found in captive Patagonian maras.

Material and Methods
In March 2023, 18 Patagonian maras kept at the Sofia Zoo in Bulgaria were investigated with the use of coprological methods. Following the investigation, the animals were dewormed with the use of albendazole. Dead adult nematodes found in the faeces of dewormed maras were collected and preserved in 70% ethanol, and morphometrically, molecularly and phylogenetically analysed.

Results
The morphometric analyses confirmed the nematodes to be Graphidioides affinis. The partial nucleotide sequences of the small subunit ribosomal rDNA (SSU), the internal transcribe spacer 2 (ITS2) and the large subunit ribosomal DNA (LSU) of G. affinis were obtained. These are the first available nucleotide sequences of this parasite. The phylogenetic analyses of the species showed its distinctiveness in comparison to other gastrointestinal nematodes, as it was grouped separately.

Conclusion
The Patagonian maras kept in a European zoo retained their original parasitofauna which are related to South America.
Contribution to a New Algorithm to Perform an Automatic Self-Calibration of Current Sensors
Authors: Beladjine Djamel Eddine , Boudana Djamel , Moualdia Abdelhafidh , Wira Patrice 
Published: August 2024

Abstract
Sensors calibration plays a crucial role in controlling systems and achieving fault-tolerant control by ensuring accuracy, performance, safety, energy efficiency, and compliance with standards. It is an essential to maintain the reliability and effectiveness of modern control systems across various applications. In this paper, we represent a new algorithm that processes a set of raw data collected by a sensor to find the mapping function that relates the raw data to the real value of the measured signal by the sensor. Working on sensors with an unknown mapping function, unknown parameters, or with external disturbances, that affects their behaviour, represents a problem; moreover, it takes a lot of time and effort to calibrate the sensor before each use. Several techniques were used to overcome these aspects mostly by recording the output of the sensor for different input values that change manually, to calibrate the sensor. However, the represented technique in this paper can easily provide us with the input/output model of a specific sensor by doing only one experiment; it also improves the accuracy of the measurements as it is a self-calibrating technique that reduces the nonlinearity and noise problems to deliver a better estimation of the measured signal, which is validated in this paper experimentally using a low-cost current sensor by comparing the obtained results from this algorithm with the results using the extracted input/output model illustrated in the datasheet. Furthermore, if the sensor is pretty poor, and if the application requires more precision, the provided estimation by the mapping function can be mixed with other sensor/s readings using sensor fusion algorithms to find a more precise value of the input. The represented algorithm can also perform self-calibration while evaluating the functionality of the application and the variations of the temperature and other external disturbances that affect the sensor.