bluuebunny/crossref_metadata_2025 huggingface dataset:
DistilBERT with Adam Optimizer Tuning for Text-based Emotion Detection
Authors: Putri Farica Perdana
Published: November 2024

Emotion detection (ED) refers to identifying individual emotions or feelings, such as happiness, sadness, disappointment, fear, etc. The classic machine learning technique still relies on feature engineering, which makes it difficult to convey the meaning of words. Deep learning-based algorithms have recently been shown to be beneficial for emotion detection because they require only a simple feature creation process. Transfer learning is an approach that uses data similarities, data distribution, models, tasks, and other factors to apply knowledge learnt in one domain to a new domain. This study is to shed light on the fine-tuned models' efficacy in detecting emotions from the International Survey on Emotion Antecedents and Reactions (ISEAR) dataset. In order to optimize the model, we conducted the hyperparameters tuning on Adam optimizer in DistilBERT. The experiment examined the moment estimators and learning rate of Adam optimizer. The effect of the parameters to training and validation accuracy were presented and analyzed.
Examining the Impact of Platform Usage on Online Purchasing in E-commerce
Authors: Halim Fransiscus Ati , Djong Darren Irawan , Usman Sabrina Fajrul Ula
Published: November 2024

With the increasing number of consumers from diverse backgrounds engaging in online purchasing, e-commerce platforms such as Tokopedia, Shopee, TikTok Shop, and others play a significant role. This research aims to examine the influence of e-commerce platform usage on consumer preferences. A descriptive quantitative methodology was employed, utilizing a Google form questionnaire distributed among the researcher's immediate surroundings. The research findings indicate that several factors have a notable impact on users' preferences when making online purchases.
Implementation of Decision Support System Method to Evaluate Posyandu Program In Tangerang Selatan
Authors: Desanti Ririn Ikana , Maximus Jason , Sitorus Budi Berlinton
Published: November 2024

The goal of this study is to develop a decision support system (DSS) using the Technique for Order Preference by Similarity to Solution (TOPSIS) and Simple Multi-Attribute Rating Technique (SMART) approaches to evaluate the Posyandu Program. The case study focuses on Posyandu in Tangerang Selatan Regional. The local government runs Posyandu, an Indonesian public health service facility for women and children. This DSS system uses the TOPSIS approach to employ the ranking function and select the best alternative based on agreed-upon criteria with the local Posyandu. This approach calculates the distance between each option with a positive ideal solution and a negative ideal solution and then computes the relative preference value, which determines how to rank. In addition, the SMART approach assigns weights to each predefined criterion. Using the TOPSIS and SMART approaches to implement DSS at Posyandu helps people make decisions by providing them with the best ranking results based on predefined criteria. Thus, it is believed that the findings of this study would improve the quality of Posyandu services and contribute to the overall health of the community.
Sentiment; Clustering; K-Means Analysis Sentiment in Bukalapak Comments with K-Means Clustering Method
Authors: Nainggolan Rena , Tobing Fenina Adline Twince , Harianja Eva J.G
Published: November 2024

Technological development are very fast ini this era of globalization, to facilitate the work of many aspevt that can be utilized, as well as for the flow of information. By applying computer technology in varios fields, such as educations, entertainment, healt, tourism, culinary and so on. Clustering id one of the Data Mining techniques. Clustering works by combining a number of data or objects into one cluster, with the aim that each data ini one cluster will have data that is a similar as possible and different from data or objects in other groups. K-Means Clustering has the ability to perform computations that are relatively fast and efficient in combining large amounts of data. In this research, there are 1407 comments which will training data and testing data.
Measurement of Capability Level Using COBIT 5 Framework (Case Study: PT Andalan Bunda Bijak)
Authors: Sanjaya Dicky , Fianty Melissa Indah
Published: November 2024

PT Andalan Bunda Bijak is a company engaged in the distribution of baby equipment. In running its business, PT Andalan Bunda Bijak implements a system called MySoft to assist the company's business activities. The business development of the company has not fully run optimally. This is because there are still problems related to risk management (no SOP for handling problems, no division to handle problems, and no problem recording) and information security (no information security policy and no information security training). With this problem, it is necessary to measure the level of capability in corporate information technology governance. This study was conducted to analyze the level of corporate information technology governance capability using the COBIT 5 framework. This study uses 3 domains (EDM, APO, and DSS) and 4 processes (EDM03, APO12, APO13, and DSS05) obtained from the mapping results of PT Andalan Bunda Bijak's vision, mission, goals, and strategies for the problems faced by the company. Data was collected by interviewing the company's operational leaders and managers and observing the systems, documents, and company environment. The results of this study determined that each process was at level 1 (performed process). There is a gap of 1 level between the level of capability of the company's current state and the level of capability of the company's expectations. There are 28 recommendations for improvement given to the company.
Implementation of Scrum Method for Designing Website-Based E-commerce Application (Case Study: Putra Prabu Workshop)
Authors: Wijaya William , Tobing Fenina Adline Twince
Published: November 2024

The internet is a technology that has now become a major necessity in the world. There are many applications designed using the internet to meet daily needs, such as educational, commercial and other applications. according to DataIndonesia.id the number of motorized vehicles in Indonesia, which according to vehicles in Indonesia reached 141.99 million units in 2021. Bengkel Putra Prabu is a workshop that operates in the city of Prabumulih, Putra Prabu has several problems, such as lack of intensive advertising. Scrum is a software engineering method using agile principles that relies on team collaboration, incremental products and an iteration process to realize the final result. The results show user acceptance of the system system was 76.06% for the Perceived Ease Of Use category, 73.51% for the Perceived Usefulness category, 71.53% for the Atitude Toward Using category, and 71.89% for the Behavioral Intentional category. The conclusion of this research the system that has been created is well received by users.
Comparison of Fine-tuned CNN Architectures for COVID-19 Infection Diagnosis
Authors: Jonathan Jonathan , Widjaja Moeljono , Suryadibrata Alethea
Published: November 2024

SARS-CoV-2 (COVID-19) virus spread quickly worldwide affects a variety of industries. The government took preventive steps to control the infection, such as diagnosing the human's lung by taking an X-Ray to see if the lungs were infected with COVID-19 or not. Using several pre-trained Convolutional Neural Network models as the basic model, this research deconstructs the comparison of fine-tuned architecture to identify which pre-trained model delivers the best outcomes in diagnosis by applying machine learning. Comparison is conducted using two scenarios that use batch sizes 64 and 32. Accuracy and f1 score are two evaluation metrics used to justify the model's good performance because the images in the real world, especially for positive classes, are scarce. According to the study, EfficientNetB0 outperforms other pre-trained models, namely ResNet50V2 and Xception, which achieved an accuracy of 0.895 and f1 score of 0.8871.
Analysis of the 5th-Grade Student and Teacher’s Needs Based on Learning Style in Emancipated Curriculum to Develop Differentiated Assessment
Authors: Ni Putu Deliana Mentari  , Ni Wayan Surya Mahayanti  , Luh Gd Rahayu Budiarta
Published: November 2024

This research aims to analyze the needs of grade 5 elementary school students and teachers based on learning styles in the emancipated curriculum to develop differentiated assessments. This research took place in Buleleng with 27 students and one teacher as respondents. Using the descriptive qualitative method, the data was collected through direct observation, interviews, open-ended questionnaires using the VARK Fleming (2001) model, and English textbook analysis. The results of the analysis of interviews with teachers showed the conclusion that the implementation of the curriculum had not yet been optimal and is still in the adjustment stage; therefore, the learning and assessment process is not yet differentiated. The analysis of student questionnaires shows that there are different student learning styles, with the visual learning style being the most dominant, received 143 answers. With these results, teachers can modify learning media and activities to meet each student's needs and learning styles.
Critical Thinking in 21st Century Learning: The Impact of Artificial Intelligence (AI) on Teaching English as a Foreign Language (TEFL)-A Philosophical Perspective
Authors: Fikri Muslim
Published: November 2024

Abstract: About the use of Artificial Intelligence (AI) in the context of Teaching English as a Foreign Language (TEFL), numerous articles have discussed its impact, ranging from positive to negative effects. Although the majority of literature asserts that AI has a significantly positive impact, this research aims to evaluate and critically analyze these effects. The focus of this study is on the variables of critical thinking, the impact of AI on TEFL, and philosophical perspectives. This research employs a qualitative approach with document analysis methods, beginning with the selection of documents based on authenticity, credibility, representativeness, and meaning factors. The research findings support the positive effects of using AI in TEFL, emphasizing the improvement of students' English language skills in speaking and writing, particularly in terms of grammar. However, the research highlights the importance of specific conditions that must be met for these positive impacts to be achieved. A critical analysis of AI's impact on TEFL reflects the necessity of incorporating critical thinking in this research to avoid uncertainties. The study also explores philosophical views related to ontology, epistemology, and axiology. In the ontological perspective, AI aids students in understanding existence and reality in language learning, especially concerning vocabulary, phrases, and grammar. From an epistemological perspective, AI serves as a foundation for students' knowledge acquisition by presenting tailored learning materials and supporting a deep understanding of linguistics. Meanwhile, from the axiological perspective, the use of AI creates positive values such as accessibility, diversity, and equality in education.
Relationship Between Self-Confidence and Speaking Ability among the Private Islamic Junior High School Students
Authors: Dewi Erniyanti Nur Fatahhela , Pratami Mentari
Published: November 2024

Self-confidence has an essensial part to start any actions, especially for speaking foreign language. This research was aimed to see the relationship among students’ self-confidence and speaking ability. The research’s instruments were questionnaire of self-confidence and speaking ability test. This research used regression and correlation analysis to find out the relationship between the variables. The results indicated that there was a significant relationship between students' self-confidence and speaking ability. It can be concluded that there was a strong relationship between the variables. Therefore, this research suggested the importance of increasing students’ self-confidence. All of these implications contribute to increasing students’ speaking ability in oral descriptive essays.
PENGARUH RASIO KEUANGAN TERHADAP PERTUMBUHAN LABA PADA PERUSAHAAN FOOD AND BEVERAGE YANG TERDAFTAR DI BURSA EFEK INDONESIA
Authors: Anggreini Dea Rinda , As’ari Hasim
Published: November 2024

Tujuan penelitian ini adalah untuk menganalisis pengaruh rasio keuangan pada pertumbuhan laba Perusahaan makanan dan minuman yang terdaftar di Bursa Efek Indonesia tahu 2021-2023. Rasio likuiditas, aktivitas, solvabilitas, dan profitabilitas adalah komponen dari rasio keuangan yang diuji. Sampel yang digunakan adalah 59 perusahaan yang dipilih menggunakan metode purposive sampling dengan total data sebanyak 177. Teknik analisis yang digunakan adalah regresi linier berganda untuk menguji hubungan antara variable-variabel independent dengan variabel dependen. Hasil penelitian menunjukkan bahwa rasio aktivitas dan profitabilitas tidak memberikan pengaruh yang signifikan terhadap pertumbuhan laba, sebaliknya rasio likuiditas dan solvabilitas memberikan pengaruh yang signifikan terhdap pertumbuhan laba. Studi ini menunjukkan bagaimana pengambilan Keputusan keuangan memengaruhi investor dan manajemen perusahaan.
The impact of digital technologies on the effectiveness of management in the agricultural sector of the Kyrgyz Republic
Authors: Kadyraliev Almaz , Oruntayeva Asmat , Kamchybekov Tolobek , Abyshov Ilgiz , Bigali Aizat
Published: November 2024

This study aimed to identify current trends in the use of digital technologies in the agricultural sector of the Kyrgyz Republic. It used theoretical approaches to study the global development of digital technologies and empirical methodologies to assess their implementation in Kyrgyz agricultural enterprises. The findings indicated the growing importance of digital agricultural technologies for improving the efficiency of agricultural operations worldwide, including in Kyrgyzstan. This progress increases the ability to more effectively meet consumer demand for the products produced by these enterprises. The integration of technologies such as artificial intelligence, database systems, robotics, smart sensors and automation into the management of Kyrgyzstan's agricultural enterprises is leading to cost optimisation, lower production costs, higher yields and the production of higher quality agricultural goods. Improving management efficiency is a key element of these reforms and is crucial for the successful operation of companies in the sector, especially in light of the current economic conditions. Modern digital technologies significantly increase the efficiency of management in the Kyrgyz agricultural sector by facilitating the rapid collection and processing of data.They also expand the possibilities for making the right management decisions, and thus increase the overall efficiency of enterprises in the country's agricultural sector
Safe Execution of Parallel Component Applications on an Unstable Heterogeneous Cluster Platform
Authors: Peng Yunfeng , Shi Congming , Gao Guowei , Wang Jianan , Liu Hai
Published: November 2024

Parallel component technology improves the development efficiency and performance of parallel software. Parallel component applications often need to be deployed on unstable heterogeneous cluster platforms. By analyzing the running mechanism of parallel component applications, this paper realizes the method of optimizing the deployment and running management of parallel components on the basis of modelling and managing the computing resources of heterogeneous platforms. This method can select nodes with light load to deploy parallel component code, and monitor the status of computing resources during the component operation. Our method can find the unavailable computing resources in time, and redeploy the parallel components running on them to other nodes with light load, which reduces the adverse impact of computing resource failure on the operation of component applications, and ensures the safe execution of parallel component applications on unstable heterogeneous platforms and achieves the expected results.
Large-Scale Simulated Storage Tank Settlement and Strain Simulation
Authors: Zhao Yongtao , Yong Ruisheng , Cao Jiaqi , Wang Jingzhi , Sun Jipei
Published: November 2024

Under the action of hydraulic pressure, the storage tanks built on soft soil foundation are prone to produce various settlement and deformation. The stability of the tank is very sensitive to settlement deformation, and the uneven settlement around the tank is the most disadvantageous to the stability of the tank. In this paper, a 1:16 simulated tank (5m in diameter, 1.44m in height) was tested by fiber grating strain measurement with uneven settlement, and the results were compared with those of finite element analysis. The results show that the main stress on the tank wall is along the axis of the tank, and the maximum strain on the tank wall occurs during the settlement process, which highlights the importance of on-line dynamic monitoring.
Study on Potential Exploitation and Benefit of Flood Control in Waterfall Reservoir
Authors: Ma Xirong , Fan Wenzhan , Lv Xiangsi , Wang Jinguo , Wang Lidan
Published: November 2024

As one of the important disaster prevention and mitigation facilities, reservoir can regulate flood and reduce the flow of downstream river by storing flood. In order to fully tap the flood control potential of the reservoir and improve the flood control capacity of the reservoir, this study takes the Waterfall Reservoir as an example, through tapping its potential in the aspects of gate transformation, flood holding capacity, operation conditions, etc., and puts forward the optimization scheme of flood sluice and operation mode. On this basis, combined with the principle of compensation regulation, the flood process and its change trend, the reduction of peak flow and the delay of peak time are analysed systematically. The results show that after reservoir regulation, the maximum overflow capacity of the river is the designed peak flow of the interval under the condition of 20 to 50 years of flood, and the downstream river is flowed according to the safe flow under the condition of 20 years of flood, the flood containment capacity of the reservoir is greatly strengthened, and the flood storage capacity of the downstream river is significantly improved. The research can provide reference for the rational operation of reservoir flood, reservoir planning and design and watershed planning.
Study on the Internal Flow Choking of Dual-Thrust Solid Rocket Motors
Authors: Shang Rongkang , Xu Jinsheng
Published: November 2024

Based on Reynolds-averaged Navier-Stokes equations and k-ω turbulence model, the numerical simulation of the ignition transient of a single chamber double thrust solid rocket motor with large aspect ratio is carried out. The simulation results show that gas flow congestion occurs in the early stage of ignition, and a fluid throat is induced in the narrow port upstream of the transition region, which causes intense pressure oscillation in the transition region and produces a high pressure boost rate. At the same time, the flow separation between the downstream gas and the wall occurs, resulting in a secondary ignition point, which speeds up the flame propagation process.
Design of Simulation System Based on Real Time Fiber Reflective Memory
Authors: Zhang Duo , Chang Yutong , Lu Yi , Zhang Xin , Zhang Xiao
Published: November 2024

In the hardware-in-the-loop simulation environment of a certain type of tactical missile, the real-time simulation software which is developed based on the Windows XP platform is needed for simulation calculation and simulated launch control. By analyzing the overall architecture of the simulation system and the real-time principle of RTX, as well as studying the characteristics of real-time VMIC in RTX environment, the real-time communication process of software is designed, and the simulation software of the transmission control unit, based on Windows XP+RTX environment, is developed. This design enables software control of simulated launch of missiles and real-time communication of data. According to the results of hardware-in-the-loop simulation experiments, the simulation software meets the requirements.
Hybrid Equilibrium Optimizer and Differential Evolution Algorithm for Optimization Combined Heat and Power Economic Dispatch Problem
Authors: Song Panpan , Luo Qifang , Zhou Yongquan
Published: November 2024

The Combined Heat and Power Economic Dispatch (CHPED) problem is one of the most complex energy dispatch problems in terms of find the solution that minimizes the fuel cost while satisfying various constraints. Therefore, this paper tries to combine the Differential Evolution (DE) algorithm and the Improved Equilibrium Optimizer (IEO) for the characteristics of equilibrium optimizer (EO) which is easily trapped in local optimum this paper adopts two methods for improvement, which are improved equilibrium pool mechanism and quasi-opposite based learning (QOBL) mechanism. Secondly, DE and IEO are mixed using the selection phase of DE to obtain DE-IEO. The superior performance of DE-IEO is verified by comparative analysis with various other algorithms mentioned in the literature on the large-scale CHPED system. The statistical results show that DE-IEO achieves satisfactory results on the CHPED problem, providing another solution to complex optimization problems.
Genetic Algorithm Based Spot Location Method for Surface Plasmon Resonance Imaging Data of Microarray
Authors: Liu Feiyu , Fang Zhewen , Zhou Jiayi , Zou Yucheng , Zhou Yue , Wang Zhiyou
Published: November 2024

In this research paper, we present a novel ellipse location method for surface plasmon resonance imaging (SPRi) sensing based on genetic algorithm and spatial mapping technique. By mapping the microarray information from the top view image of sensor slide to SPRi image data, we divided the microarray areas in the image data into grids. To expedite the ellipse detection process in the local grids, we employed image sharpening and a bonus-penalty mechanism to accelerate the fitness value assessment of ellipse fitting in the genetic algorithm. Different from the ellipse locating method based on OpenCV, our method can detect all the spots in both protein and small microarrays accurately. The above results indicate that our method can be applied in high-throughput SPRi detections.
Algorithm for Intelligent Modeling of Digital Body Twins
Authors: Chen Shuming , Dai Yongbo , Zou Xiaohui
Published: November 2024

This study aims to demonstrate the superiority of a pan-attribute-based intelligent algorithm in comparison to traditional interpolation and fitting methods. The focus is on revolutionizing 3D geological modeling for more efficient resource exploration and environmental management. The algorithm leverages attribute fields to reconstruct continuous boundaries without discretization, incorporates various trend parameters, and achieves rapid and intelligent calculations. The validation system incorporates industry logic through typical cases, highlighting the algorithm’s unique advantages.The results show that the algorithm significantly outperforms traditional methods, enabling precise 3D geological representations. The integration with digital twins further enhances simulation capabilities for natural, artificial, and virtual objects.The combination of the algorithm and digital twins paves the way for a new generation of intelligent agents that significantly exceed human intelligence in specialized tasks. This study serves as a foundation for future research and applications in AI-supported productivity.
The Psychological Analysis for College Students’ Entrepreneurship Based on Deep Learning and BP Neural Network
Authors: Deng Yan , Qi Jingyu , Zhao Shuduo
Published: November 2024

The ideological and political instruction of college students is an important teaching content in colleges and universities. Entrepreneurial mental quality refers to the psychological personality characteristics that play a motivating role in entrepreneurial practice activities. It is the foundation of individual entrepreneurial quality and the core content of entrepreneurial instruction. Therefore, this paper explores the entrepreneurial psychology of college students from entrepreneurial motivation, entrepreneurial ability, entrepreneurial personality, and entrepreneurial skills based on deep learning and back propagation neural networks under the ideological and political instruction threshold. The questionnaire analysis method is used to collect data on the entrepreneurial psychology of college students in XX City. The results indicate that: (1) College students pay much attention to personal economic independence and early return to their parents in entrepreneurship, with scores of 3.65990 and 0.95135, respectively. (2) The low scores of entrepreneurial ability are “unless the task is very complex, I rarely accept the advice of others” and “more extensive market development marketing knowledge.” The coefficients are 2.6633 and 2.9377, respectively, indicating that college students lack actual exercise and are not integrated into the entrepreneurial process. (3) College students and entrepreneurs have strong responsibility and openness in their entrepreneurial personality traits. The average value of thinking that they can determine the success or failure of the enterprise is relatively low. (4) The power of the role models of successful entrepreneurs in society and the influence of local entrepreneurial culture both give entrepreneurial college students substantial achievement and life-oriented motivation. The research results can help colleges and universities carry out entrepreneurship instruction and provide a reference for shaping an entrepreneurial instruction model suitable for China’s colleges and universities. In addition, it provides suggestions for domestic universities to formulate corresponding career guidance and career planning counseling measures for college students and develops possible training models. In this way, it will cultivate and improve college students’ awareness of entrepreneurial motivation, innovation ability, entrepreneurial personality, knowledge, and skills related to entrepreneurship. Also, it will promote employment with college students’ independent entrepreneurship.
Enhanced Russian Literature Inspired Optimization Algorithm for True Power Loss Reduction in Electrical System
Authors: Kanagasabai Lenin
Published: November 2024

Enhanced Russian Literature inspired optimization (ELR) algorithm is applied for solving the true power loss reduction problem. Communal sleaze, Innocence, Loneliness, Human nature of noble and wicked, Lifecycle and demise, Trust and misery of the Russian Literature “The Idiot” has been considered to formulate the algorithm. In the section of exploration of the algorithm, communal sleaze, innocence, loneliness is considered. JN 1 Covid Variant algorithm is integrated in the procedure, to enhance the exploration ability of the procedure. The methodological recommended cluster on JN 1 Covid Variant Virus progression is an autonomous cluster of specialists that sporadically observers and assesses the progression of JN 1 Covid Variant and measures if explicit transmutations and amalgamations of alterations amend the attitude of the virus. The procedure factors and the delinquent variables are fixed grounded on the succeeding aim function. Projected Enhanced Russian Literature inspired optimization (ELR) algorithm is validated in IEEE 118 bus system.
Simulation Approach for Optical Diagnostics of Structure-Inhomogeneous Objects
Authors: Angelsky Oleg , Zenkova Claudia , Ivanskyi Dmytro , Tkachuk Vladyslav , Ursuliak Yulia
Published: November 2024

This paper demonstrates the use of luminescent carbon nanoparticles (CNPs) for studying structurally inhomogeneous optical fields that carry diagnostic information about heterogeneous material objects. The study analyzes methods for synthesizing nanoparticles with various specifically tailored optical and electrical properties to address different diagnostic tasks. The unique optical properties of carbon nanoparticles, along with their particle size of around a few dozen nanometers, are key factors in using these particles as probes for optical speckle fields. Optically-driven nanoparticles can function as a contactless alternative to atomic-force profilometry. The research shows that the light-induced motion of nanoparticles suspended in an optical field allows for the detection and localization of intensity minima and phase singularities. Luminescence enables real-time registration of the coordinate positions of carbon nanoparticles. The paper also presents a simulation approach for reconstructing the scalar optical field intensity distribution by analyzing the positions of nanoparticles. The optical speckle field’s skeleton is examined using the Hilbert transform to restore the phase, with special attention given to the restoration of phase singularities within the speckle field.
Creating Prediction Model for Car Prices by Using Machine Learning Algorithms
Authors: Limani Bind , Bytyçi Eliot
Published: November 2024

Due to Kosova’s significant automobile trade industry, a number of online marketplaces have been developed where these vehicles can be listed. Therefore, we may gather data from automobile listings and place it in a dataset utilizing web scraping methods. We must then first handle this dataset in order to make it appropriate for model training. After processing, we can go on to the depiction of some simple graphs to help us better understand the trends and phenomena present in the dataset and the relationships between the characteristics. We can build predictive models that we may use to make predictions using machine learning algorithms like linear regression, ridge regression, and random forests. The highest value of the R2 variable, which ranges from 0 to 1 and is used to gauge the model’s quality, is 0.8174 and was attained using Random Forest algorithm.
Research on the Technical Scheme of Assembly Design of Teaching Buildings in Colleges and Universities
Authors: Wang Qihui , Xie Dan , Yang Jianlin , Dong Shuzhao
Published: November 2024

In recent years, with the vigorous promotion of prefabricated buildings nationwide, the application of prefabricated buildings in the construction of university campuses has also attracted widespread attention in the industry. Although there are some successful cases of prefabricated university buildings, which provide valuable experience for the application of prefabricated buildings in university campus buildings, at present, the research on prefabricated university campus buildings in China is still relatively scarce. In view of this situation, this paper takes the assembly design of teaching buildings in colleges and universities as the research object, and combines BIM modeling, collision detection, carbon emission calculation and other technical means to explore the technical solutions under the demand of flexibility. The goal of this study is to promote the rapid, economic and high-quality construction of university buildings, promote the development of research theories and methods of prefabricated building systems, and provide new ideas and methods for the future development of university buildings.
An Improved 2-Approximation Algorithm for the Rectilinear Steiner Tree Problem with Minimal Number of Steiner Points
Authors: Li Jianglin , Wang Wencheng , Chen Yinhua , Zhang Tongquan
Published: November 2024

In this paper, we present an improved algorithm for the rectilinear Steiner trees problem with minimal number of Steiner points. Given a set X of n terminal points in the L1 plane and a positive constant L, it is asked to construct a Steiner tree T interconnecting of these n terminal points, with the length of each edge in that tree T is no more than L. It has been proven that this problem is NP-hard and there exists a 2-approximation algorithm in time O(n3). By using the strategies of the sweep-line algorithm and a leaf-deletion technique in a special forest composed of selected edges from a rectilinear minimum spanning tree on X, we propose an effective 2-approximation algorithm in time O(n log n).
Utilizing Paired Data for Training Real-ESRGAN for Enhanced Super-Resolution Image Restoration in Coal Mine Environments
Authors: Zheng Libo , Hu Tao , Zheng Dong , Liu Cong , Qin Zhu
Published: November 2024

Intelligent mining is the core technical support for high-quality development in the coal industry. High-resolution underground images provide critical data for intelligent analysis but often suffer from low quality due to environmental factors and imaging technology limitations. This paper proposes a lightweight super-resolution reconstruction method for mine images, integrating hierarchical features and attention mechanisms, to address these challenges. By leveraging the Real-ESRGAN model and fine-tuning it with paired high-resolution and low-resolution images from the CMUID dataset, we achieve significant improvements in image quality. The effectiveness of the proposed method is validated through extensive experiments, with performance metrics demonstrating enhanced image restoration capabilities compared to traditional methods.
Optimization of Photovoltaic System Modelling: A Comparative Study and Experimental Validation Using Bond Graph Methodology and a Genetic Algorithm
Authors: Adar Mustapha , Babay Mohammed-Amine , Boussif Mourad , Khaouch Zakaria , Abbassi Zakarya , Najih Youssef , Mabrouki Mustapha
Published: November 2024

In this study, we present a methodology designed to model a solar photovoltaic plant. Our approach emphasizes simplicity in modeling procedures. Specifically, we employ the Bond Graph Approach to construct a solar cell model, which is represented by a circuit consisting of one diode and two resistors. To deduce the five unknown parameters of the solar cell, we employ the genetic algorithm. The primary objective of this modeling endeavor is twofold: first, to scrutinize and gain insights into the operational behavior of the PV plant, and second, to develop a more precise and dependable PV model capable of replicating PV panel performance under outdoor environmental conditions. To ascertain the accuracy of our proposed model, we conduct a comparative analysis with both the MATLAB PV model and empirical data. This comparative assessment encompasses monocrystalline PV technology. We conduct simulations using real-world temperature and solar irradiation data for four different days, representing various seasons throughout the year. These simulations are executed using the 20-Sim software platform. Our findings reveal that the proposed model exhibits greater accuracy than does the MATLAB PV model. Furthermore, the results demonstrated a high level of fidelity in reproducing experimental data under the specific operational conditions and for the considered PV technologies.
Analysis of Factors Affecting the Appearance of Reinforced Concrete Segments
Authors: Qiu Yuetao
Published: November 2024

This article focuses on the issue of honeycomb and pockmarks in Reinforced Concrete Segments. The slump of concrete should be controlled at 140 mm, the air content of concrete can be controlled at around 1.7%, the pouring and vibration time should be controlled at 9 min, and water-based release agents and polycarboxylate mother liquor should be selected as release agents. It is recommended to use viscosity reducing polycarboxylate to achieve the minimum honeycomb and pockmarks.
Performance Characteristics Analysis and Modeling of Near Space Parachute UAV
Authors: Chen Shaoqian , Xiao Ben , Hao Shiyu , Liu Mengyan , Zou Dan
Published: November 2024

In recent years, the strategic value of near space has become more and more prominent. The high-aspect-ratio UAV with excellent lift-drag performance is an important aircraft to explore the airspace. In the traditional application mode, this type of UAV relies on its own power to take off from the ground and climb to the near space. However, when the UAV crosses the troposphere, it is very likely that it will encounter unstable airflow area and cause damage to the body structure. Therefore, the near space parachute UAV came into being. In this paper, we will model and analyze its subduction and leveling in near space, so as to lay the foundation for subsequent research.
Mosaic Method for Bridge Surface Imaging Based on Image Correction and Path Optimization
Authors: Xiong Shaohui , Chen Zhengfei , Miao Chaojie , Kuang Lu , Hu Li
Published: November 2024

To address the fundamental issue of large-scale bridge surface defect detection by inspection robots, an innovative stitching method based on image correction and shooting path optimization is proposed. By presetting shooting angles, distances, cropping ratios, and camera parameters, reasonable shooting step lengths and paths are determined. Correction coefficients are calculated for each photo, and the photos undergo refined processing of correction followed by cropping according to the cropping ratio, eliminating distortions and redundant information during the shooting process. The cropped and corrected photos are then seamlessly stitched together in numerical order to generate complete and high-quality images. The stitching method in this study is not only suitable for complex scenes without prominent feature points but also significantly reduces computational resource consumption by simplifying calculation processes and optimizing algorithm design. A verification experiment was conducted on the Mozhai Wujiang Grand Bridge of the Chongqing-Hunan Expressway Duplication Project, successfully stitching together a complete image of the bridge’s main girder. Compared with traditional image stitching methods, this method significantly improves stitching efficiency and accuracy while ensuring the accuracy and reliability of the stitching results. This study provides an efficient and accurate image stitching technology for bridge surface defect detection, with broad application prospects and important practical value.
The degree of nutritional knowledge, attitude and performance of patients with acute coronary syndrome on arrival, discharge day and 3 month after discharge: A longitudinal study
Authors: Moaddab Fatemeh , Salari Arsalan , Kazemnezhad Leili Ehsan , Zaersabet Fatemeh , Rouhi balasi Leila , Mahdavi-Roshan Marjan , Soodmand Mostafa
Published: November 2024

BACKGROUND:

Acute coronary syndrome is one of the most common chronic, progressive, and life-threatening diseases in most countries in the world. One of the effective factors in re-hospitalization of these patients is the lack of knowledge about the correct diet therapy.

OBJECTIVE:

This study aimed to compare the degree of nutritional knowledge, attitude, and performance of patients with acute coronary syndrome on arrival, discharge day, and 3 months after discharge in 2017-2018.

METHODS:

This longitudinal study was conducted on 125 patients with acute coronary syndrome who were referred to Dr. Heshmat hospital in Rasht as the exclusive heart center in Guilan province (Northern Iran). Convenience sampling was done using a valid two-part questionnaire including demographic information and nutritional KAP. Data were analyzed by descriptive statistics and analytical statistics in SPSS.

RESULTS:

The nutritional knowledge and attitude score of the majority of the samples decreased over the time interval (from time of arrival until the referral to the clinic), but the nutritional performance of patients increased in the period; the mean score on arrival was less than the score at the discharge time.

CONCLUSION:

The results of this study emphasize the importance of nutrition education in people with the acute coronary syndrome.
Decreasing patient dose in digital mammography with Bayesian image	estimation
Authors: Baydush Alan H. , Floyd Jr. Carey E.
Published: November 2024

{\it Purpose:} The effect of Bayesian image estimation (BIE), which reduces image scatter and improves contrast-to-noise ratios (CNR), on reduced dose digital mammography is studied.

{\it Methods/Materials:} Standard dose digital mammographic images of the ACR breast phantom were acquired with and without a grid. Additional images were acquired without the grid at reduced exposures and were processed by BIE. CNR values were computed for visible masses before and after processing for each exposure and compared to using a grid.

{\it Results:} With no change in exposure, BIE applied to the image acquired without the grid improves CNR from 209 to 520% over that provided by the grid. While these results were not as good at reduced exposures, BIE processing still improved CNR from 236 to 465% over a grid.

{\it Conclusions:} BIE processing of reduced exposure level images offers increased CNR and subjective visualization compared to images acquired with a grid at standard exposure.
A preliminary study on adaptive field-of-view tracking in	peripheral digital subtraction angiography
Authors: Bennett James R. , Bai Er-Wei , Halloran John I. , Wang Ge
Published: November 2024

About two million peripheral angiographies are performed annually in the United States, hence a reduction in exposure would yield significant healthcare benefits. The synchronization of bolus traveling, the table motion, and the fluoroscopic imaging chain can be highly effective for dose reduction in Digital Subtraction Angiography (DSA) by minimizing the field-of-view according to the vascular anatomy of the region traveled by the bolus. The goal of this paper is to demonstrate the feasibility of adjusting the field-of-view while tracking the contrast bolus, thus reducing the dosage of both the bolus and the radiation. The speed of the bolus is respectively estimated in the systole and diastole stages. An EKG-gated Hammerstein model is used to predict the bolus chasing speed. A real-time algorithm is designed to extract the bolus dynamics, and define the field of view transversely and longitudinally. A limb stabilization technique is also presented to suppress any significant image misalignment. Our simulation results show that the proposed techniques are promising for clinical applications.
A reconstruction formula for soft tissue X-ray phase	tomography
Authors: Wu Xizeng , Liu Hong
Published: November 2024

In clinical x-ray phase imaging, the significant tissue attenuation cannot be ignored. In x-ray phase tomography, the presence of tissue attenuation requires acquisition of at least two images for the retrieval of tissue phase for a given tomographic view. This paper presents an important observation that the same map of the projected electron densities can determine both the phase and attenuation maps of soft tissues, provided that the dominance of incoherent scattering holds. Based on this observation a new strategy to perform the phase retrieval was developed. A 3-D phase tomography reconstruction formula was derived, which combines the three-dimensional inverse Radon transform with the phase retrievals for soft tissues. This new formula alleviates all the technical difficulties associated with the requirement of acquiring two images per tomographic view for phase-retrievals in x-ray phase tomography.
Comparing X-ray optics: Performance standards
Authors: Lee Susanne M. , Formica Sarah P.
Published: November 2024

Many different performance measures are used to characterize x-ray optics, sometimes resulting in radically different rankings. This makes it difficult, even for practitioners intimately involved in the field, to compare results from different optics and for different applications. To truly understand and appreciate advances in a specific type of optic – polycapillary optics – different methods of optic comparison are evaluated and their relevance explained. These methods include transmission efficiency, flux, flux density, equivalent distance, normalized gain, insertion gain, and effective capture angle. Polycapillary focusing optics with varying input and output parameters are compared using these different performance standards.
FastGrasp: Efficient Grasp Synthesis with Diffusion
Authors: Wu Xiaofei , Liu Tao , Li Caoji , Ma Yuexin , Shi Yujiao , He Xuming
Published: November 2024

Effectively modeling the interaction between human hands and objects is challenging due to the complex physical constraints and the requirement for high generation efficiency in applications. Prior approaches often employ computationally intensive two-stage approaches, which first generate an intermediate representation, such as contact maps, followed by an iterative optimization procedure that updates hand meshes to capture the hand-object relation. However, due to the high computation complexity during the optimization stage, such strategies often suffer from low efficiency in inference. To address this limitation, this work introduces a novel diffusion-model-based approach that generates the grasping pose in a one-stage manner. This allows us to significantly improve generation speed and the diversity of generated hand poses. In particular, we develop a Latent Diffusion Model with an Adaptation Module for object-conditioned hand pose generation and a contact-aware loss to enforce the physical constraints between hands and objects. Extensive experiments demonstrate that our method achieves faster inference, higher diversity, and superior pose quality than state-of-the-art approaches. Code is available at https://github.com/wuxiaofei01/FastGrasp. [https://github.com/wuxiaofei01/FastGrasp]
Untangling Magellanic Streams
Authors: Zaritsky Dennis , Chandra Vedant , Conroy Charlie , Bonaca Ana , Cargile Phillip A. , Naidu Rohan P.
Published: November 2024

The Magellanic Stream has long been known to contain multiple HI strands and corresponding stellar populations are beginning to be discovered. Combining an H3-selected sample with stars drawn from the Gaia catalog, we trace stars along a sub-dominant strand of the Magellanic Stream, as defined by gas content, across 30∘ on the sky. We find that the dominant strand is devoid of stars with Galactocentric distance \(\lesssim 55\) kpc while the subdominant strand shows a close correspondence to such stars. We conclude that (1) the two Stream strands have different origins, (2) they are likely only close in projection, (3) the subdominant strand is tidal in origin, and (4) the subdominant strand is composed of disk material, likely drawn from the disk of the Small Magellanic Cloud. _Subject headings:_ Magellanic Clouds (990), Magellanic Stream (991), Milky Way stellar halo (1060)