Reviewerly/exHarmony huggingface dataset:
Analysis of the Effect of Corner Points and Image Resolution in a Mechanical Test Combining Digital Image Processing and Mesh-free Method

In this paper, we presen t a DIP-MLS testing method that combines digital image processing with a rigid body-based MLS differencing approach to measure mechanical variables and analyze the impact of target location and image resolution. This method assesses the displacement of the target attached to the sample through digital image processing and allocates this displacement to the node displacement of the MLS differencing method, which solely employs nodes to calculate mechanical variables such as stress and strain of the studied object. We propose an effective method to measure the displacement of the target's center of gravity using digital image processing. The calculation of mechanical variables through the MLS differencing method, incorporating image-based target displacement, facilitates easy computation of mechanical variables at arbitrary positions without constraints from meshes or grids. This is achieved by acquiring the accurate displacement history of the test specimen and utilizing the displacement of tracking points with low rigidity. The developed testing method was validated by comparing the measurement results of the sensor with those of the DIP-MLS testing method in a three-point bending test of a rubber beam. Additionally, numerical analysis results simulated only by the MLS differencing method were compared, confirming that the developed method accurately reproduces the actual test and shows good agreement with numerical analysis results before significant deformation. Furthermore, we analyzed the effects of boundary points by applying 46 tracking points, including corner points, to the DIP-MLS testing method. This was compared with using only the internal points of the target, determining the optimal image resolution for this testing method. Through this, we demonstrated that the developed method efficiently addresses the limitations of direct experiments or existing mesh-based simulations. It also suggests that digitalization of the experimental-simulation process is achievable to a considerable extent.
Methodology, application and platform for urban security planning and management

With the acceleration of economic development and urban construction, urban security accidents have occurred around the world with alarming frequency, causing serious casualties and economic losses. Urban security planning and management as emerging areas of research have drawn widespread attention. For city development plans, urban security planning and management have become one of major topics. This paper first outlines the principles of urban security planning and management, combined with the construction of a digital and intelligent platform for urban emergency management. This research then analyzes the core technology and equipment support system of urban security management and its practical application. It also presents a new model based on urban security planning and management, followed by examples of its application in some mega infrastructure development for security planning and design (for example, Singapore Changi Airport and Shanghai Hongqiao Airport Transportation Hub). Additionally, a blast protection concept of urban security planning and management is provided.
Exploring the Effects of Green Transformational Leadership on Job Satisfaction in Pakistan's Pharmaceutical Industry: The Mediating Role of Intention

This study investigates the relationship between green transformational leadership (GTL), job satisfaction (JS), and the mediating role of 'intention' in Pakistan's pharmaceutical industry within the framework of the resource-based view (RBV) theory. The research uncovers that GTL, encompassing environmental consciousness, ethical conduct, and innovation, is a unique organizational resource that shapes employees' intentions toward embracing sustainable practices. A quantitative methodology was adopted to achieve the aims of the study. Data were collected through an online survey to manage the data (418 valid responses), and Smart-PLS structural equation modeling (PLS-SEM) was employed to hypothesize a model. The results demonstrate that GTL had little significant direct effect on JS. This study also found that intention has a full mediation effect between GTL and JS. Additionally, the study found that the correlation among GTL is affected by JS and intention. This study contributes to the literature and body of knowledge on green human resource management and organizational behavior through the lens of RBV theory.
Educator’s Spirit is the Primary Orientation of the Construction of a High-Quality Teacher-Team in the New Era

The educator’s spirit is the professional ethos that must be cultivated in the process of shaping the new generation of teachers. It serves as the foundational pillar for the growth and development of educators, aligning with the essential prerequisites of a robust educational landscape in the modern era. The spirit of the educator is the primary guiding force behind the cultivation of high-quality teachers in the new era. By elucidating the connotations and essence of the educator’s spirit, it becomes evident that integrating it into teacher development holds unique value. This integration contributes to the advancement of teachers’ morality and ethical frameworks, ensuring effective education delivery that meets public satisfaction and strengthens the nation’s educational strategy. The integration of the educator’s spirit into teacher development is a practical imperative for educators in the new era. It clarifies their value orientation, equips them to navigate risks and challenges, and reconnects them with the true essence of education. Furthermore, incorporating the educator’s spirit into the standardization, cultivation, and institutional frameworks presents a tangible pathway to enhancing the high-quality evolution of teacher development in the new era.
Deep Learning Based Multi-Camera Person Tracking and Re-identification System

This research paper presents a novel Deep Learning Based Multi-Camera Person Tracking and Re-identification System designed to enhance security and surveillance in public spaces. Leveraging advanced technologies including Object Detection through YOLO and Deep SORT, the system offers an efficient solution for monitoring and tracing individuals across multiple camera views. Through object detection, individuals are identified within each camera frame, while Deep SORT ensures seamless tracking as they move across different camera perspectives. Additionally, a person re-identification module enhances tracking accuracy by extracting distinctive features and linking individuals across various camera views using unique identifiers. This system represents a significant advancement in surveillance capabilities, contributing to the development of effective and user-friendly surveillance solutions.
A study of the thermal evolution of permeability and porosity of porous rocks based on fractal geometry theory

FractalsAccepted Papers No AccessA study of the thermal evolution of permeability and porosity of porous rocks based on fractal geometry theoryTongjun Miao, Aimin Chen, Richeng Liu, Peng Xu, and Boming YuTongjun Miao, Aimin Chen Search for more papers by this author , Richeng Liu Search for more papers by this author , Peng Xu Search for more papers by this author , and Boming Yu Search for more papers by this author https://doi.org/10.1142/S0218348X24500518Cited by:0 (Source: Crossref) PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Remember to check out the Most Cited Articles! Check out New & Notable Titles in Nonlinear ScienceIncludes authors Leon O Chua, Bruce J West and more " FiguresReferencesRelatedDetails Recommended Accepted Papers Metrics History Received 13 December 2023 Accepted 20 February 2024 PDF download
Digitalization of Education of the Future—A Trend or a Requirement of the Time?

The article substantiates the need to introduce innovative digital technologies in the future education system as a natural response to changes in the socio-economic sphere of social being. Particular attention is paid to the source of the active use of digital technology - digitalization, the concept of electronic functionality is formulated. The authors highlighted the main trends in the development of digital education and assumed that these dynamics will only grow in the future. The article reflects the main trends in the development of digital education, analyzes their strengths, and considers reservations about their implementation. The authors managed to present the digital transformation of the educational process as a global trend aimed at creating a new information society functioning in an innovative digital environment.
Optimized deep learning multi-model investigation of images for ground water level detection

&lt;p&gt;When referring to groundwater in the context of the normal water cycle, the word “reservoir” is acceptable. Compared to the atmosphere or fresh surface water, groundwater has a much greater capacity to hold water. Despite the high degree of variety and complexity of the subsurface ecosystem, there is currently only a small amount of data available. People who depended on reality-based models ran into both of these challenges at some point. Statistical modeling was used in order to get a more accurate calibration of the model throughout the course of time. Because of the expansion in global population, governments in both wealthy and developing nations are increasingly looking to groundwater as an essential resource for satisfying the water requirements of their populations. Because water was preserved in such a large amount, it may be used again, even when there is a drought or other dry time. In this manuscript, a Particle Swarm Optimization (PSO) enabled Visual Geometry Group (VGG) 16 deep learning model is used in order to determine the level of ground water. Accuracy, specificity and sensitivity of PSO enabled VGG is highest among the algorithms used in the experimental study. Accuracy of PSO VGG 16 is 92.5 percent, specificity and sensitivity of PSO VGG 16 is 99 percent.&lt;/p&gt;
Review of Intelligent Ship Path Planning Algorithms

Intelligent ship route planning has become an important research direction in the field of shipping in recent years. This paper first provides an overview of the basic theory of intelligent ship route planning. Secondly, various intelligent ship route planning algorithms are introduced, including methods based on A* algorithm, artificial potential field algorithm, RRT algorithm, and reinforcement learning. These algorithms analyze information such as ocean environment, predict sea conditions and traffic conditions, and consider ship dynamics and navigation safety constraints to provide efficient and safe navigation routes for ships. Finally, this paper points out the key issues and future development directions in intelligent ship route planning. The continuous innovation and application of intelligent ship route planning algorithms will provide more intelligent and efficient ship transportation services for the shipping industry, promoting the sustainable development of the shipping industry.
Exploring the Performance of PySpark and Scikit-Learn Libraries in Developing Fall Detection Systems

Falls pose a significant risk for the elderly population, often resulting in serious injuries and decreased quality of life. Accurate and effective fall detection systems can play an important role in reducing these risks. This study conducts a comparative analysis of the performance of PySpark and Scikit-Learn libraries in the development of fall detection models. PySpark offers a distributed computing environment specifically designed for big data processing, while Scikit-Learn is a Python-based library widely used for data analysis and machine learning. Five popular machine learning algorithms, including logistic regression, gradient boosting classifier, random forest, support vector machine, and Decision Tree, were used to build fall detection models using both PySpark and Scikit-Learn. Models were evaluated using a comprehensive set of measurements including accuracy, sensitivity, specificity, and confusion matrix. In addition to the five popular machine learning algorithms included in the study, 26 different features were extracted from the Sisfall dataset, one of the most comprehensive fall and daily life activity datasets, in five main categories: basic statistical features, frequency domain features, time series features, motion features, and relational features. These features were incorporated into fall detection models to improve their ability to accurately identify falls. The findings reveal that both PySpark and Scikit-Learn provide strong and effective results in fall detection. Logistic regression emerged as the best performing algorithm in both libraries, achieving the highest accuracy rates. However, PySpark exhibited slightly longer training times compared to Scikit-Learn, which performed better in testing. Ultimately, this study will benefit researchers and practitioners involved in the development of robust and effective fall detection systems, thereby enabling improved safety and well-being for the elderly population. Additionally, it contributes to the literature by presenting a comprehensive feature extraction methodology for fall detection, which has not been explored extensively in previous research works.
PENGARUH METODE PRIVAT TERHADAP KELANCARAN MEMBACA IQRA’ DI MADRASAH DINIYAH TPA/TPQ “HIDAYATUSH SHIBYAN” NGRECO KABUPATEN KEDIRI

This research aims to evaluate the effectiveness of using private methods in improving students' reading skills at Madrasah Diniyah TPA/TPQ "HIDAYATUSH SHIBYAN". This research uses a systematic and scientific quantitative approach to explore the relationship between the use of private methods and the ability to read iqra'. This research method is included in the exploratory category, with a survey approach carried out in the field. Data was collected through interviews, observation and documentation. The results of the research show that reading mastery is the main focus in the learning process at Madrasah Diniyah TPA/TPQ "HIDAYATUSH SHIBYAN". Even though there is only one teacher teaching in each class, all students receive equal attention and the material is taught with variety to keep students interested. The application of private methods allows more intense interaction between teachers and students, facilitating better understanding of learning material. However, the success of this method depends on the balance between the number of teachers and students and the availability of sufficient time. This research concludes that learning methods that focus on individual interactions between teachers and students, such as private methods, are effective in improving students' reading abilities and comprehension at Madrasah Diniyah TPA/TPQ "HIDAYATUSH SHIBYAN". The research results provide valuable insights for educational practitioners in improving the quality of learning in non-formal educational institutions and confirm the importance of focusing on reading mastery in the educational process.
Designing an instructive program according to the problem-solving method for some athletics activities)) researcher

&#x0D; The research aims to:1- Preparing an instructive program according to a problem-solving method for students of the College of Physical Education and Sports Sciences for some athletics activities.2- Knowing the effect of the counseling program according to the problem-solving method on the practical achievement anxiety of students of the College of Physical Education and Sports Sciences for some athletics activities.The researcher used the experimental approach with two equal groups due to its suitability to the nature of the research. The research community was identified by students of Faculties of Physical Education and Sports Sciences (fourth stage) in the universities (Diyala - Tikrit - Mosul - Kirkuk) for the academic year (2018/2019) for the morning study, which amounted to (551) Students (*) As for the research, it was chosen randomly from the University of Kirkuk / College of Physical Education and Sports Sciences, whose number is (42) students who have high scores in the scale and a percentage of (37.83%) of the fourth stage students, who are (101) students Divided into two groups, an experimental group and a control group for the purpose of implementing the counseling program to solve problems on them. As for the building, it was (410) students and the exploratory experimental (40) students, and the researchers used the statistical means SPSSThe researcher concluded the following:1- The use of problem-solving method reduces practical achievement.2- The mentoring program has an effective effect on students ’awareness of themselves, organizing their ideas and experiences, and enhancing their self-confidence in order to face the exam situations.As for the recommendations, they were:1- Emphasis on the use of scientific methods in psychological preparation and the use of counseling and psychological programs for students that enhance their personality and move away from the manifestations of anxiety that affect their scientific and practical achievement.2- Entering students in courses and seminars specialized in psychological counseling to direct them to reinforce positive cases to control the manifestations of anxiety and control these manifestations in a positive way&#x0D; &#x0D;
Fuzzy Clustering-Based Grouping for Mapping the Distribution of Student Success Data

Learning activities are the main activity in the overall teaching and learning process in schools. This is because whether or not the achievement of educational goals depends on how the learning process is carried out by students. The uneven level of student success in learning is one of the problems in the school's efforts to realize the vision and mission of SMKN 5 Pekanbaru in preparing skilled graduates to be able to work in certain sectors by the public interest and the industrial world. In this study, mapping and grouping student grade data was carried out using the Fuzzy C-Means algorithm to provide information to the school in making the right decisions and optimizing the learning process. Furthermore, clustering was carried out in several experiments K=3 to K=7, and obtained the best validity value tested with the Silhouette Index of 0.4277 located at K=5. Then the distribution of cluster 5 on student score data was obtained with details, namely cluster 1 with a capacity of 1 student, cluster 2 with a capacity of 27 students, cluster 3 with a capacity of 1 student, cluster 4 with a capacity of 10 students, cluster 5 with a capacity of 23 students.
Sentiment Classification of Robot Hotel Content using NBC and SVM Algorithm

Sentiment analysis plays a pivotal role in comprehending public sentiment, notably within digital communication, where copious amounts of textual data are generated daily. This study delves into the efficacy of sentiment classification models, namely the Naive Bayes Classifier (NBC) and Support Vector Machine (SVM), within the imbalanced datasets commonly encountered in sentiment analysis tasks. Employing a comparative analysis methodology, a dataset comprising robot hotel reviews from online platforms is the basis for evaluation. Both NBC and SVM models undergo training and assessment, with and without the Synthetic Minority Over-sampling Technique (SMOTE), to rectify the class imbalance. Performance evaluation relies on critical metrics, including accuracy, recall, precision, f-measure, and Area Under Curve (AUC) to gauge model effectiveness. Findings demonstrate SVM's superiority over NBC in terms of accuracy (SVM: 76.88%, NBC: 67.43%), precision (SVM: 92.03%, NBC: 86.87%), recall (SVM: 58.88%, NBC: 41.00%), f-measure (SVM: 71.78%, NBC: 55.63%), and AUC (SVM: 0.907, NBC: 0.961). Incorporating SMOTE significantly enhances both models' performance, particularly in addressing class imbalance concerns. Although NBC exhibits a more balanced performance across precision and recall metrics, SVM demonstrates heightened accuracy and predictive capability in sentiment classification tasks. These findings underscore the pivotal role of algorithm selection and preprocessing techniques in optimizing sentiment analysis performance, thereby providing invaluable insights for practitioners and researchers alike.
Educational Media Of Ancient History Through Interactive, Evocative, And Interactive Display Design For Sangiran Museum Krikilan Cluster

The Sangiran site is one of the most important prehistoric sites in the world, more than 50% of hominid fossils are found in this area and has extraordinary importance because it is considered a complete ecosystem laboratory consisting of geology, palaeontology, palaeobotany, and archaeology (ICOMOS, 1996). By UNESCO, the Sangiran Ancient Human Site was designated as a World Culture Heritage on 5 December 1996 in Merida (Mexico) by the World Heritage Committee with number C593, since then Sangiran has belonged to the world and has become one of three centres of ancient human evolution in addition to similar sites in Africa and China. Preservation of cultural knowledge through cultural knowledge by designing the Museum as a centre of information and cultural preservation. A museum through the exhibition system (museum display system) to convey information. The use of museum display facilities, tailored to the needs of the museum and the type of collection to be exhibited. The museum display system enables information communication. In the display system, objects are placed in displays with interpretations that can explain their meaning. The use of supporting facilities, also known as museum displays, is tailored to the needs and type of museum collection to be exhibited. To display a collection of artefacts about ancient human history, Sangran Museum Krikilan Cluster uses three presentation approaches: intellectual approach, romantic (evocative) approach, and interactive approach. The aim of this design is to determine an alternative display system in the exhibition space of the Sangiran Museum Krikilan Cluster to attract more visitors, both local and foreign.