bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of Digital Inheritance of Meishan Folk Woodcarving Skills in the Information Age
Authors: Peng Bo
Published: March 2024

This study delves into the digital preservation of Meishan folk woodcarvings, emphasizing the use of virtual reality (VR) technology to enhance the transmission of this traditional art. Utilizing 3D modeling and VR platforms, the research scans and rebuilds wooden carvings for digital exhibition. The realism and interactivity of the virtual environment are improved through collision detection algorithms such as Orientation Bracketing Box (OBB) and Axial Bracketing Box (AABB), complemented by high-precision 3D models created with LIDAR scanning technology. Findings indicate that the VR system significantly enhances the efficiency and quality of digital preservation, offering a robust solution for safeguarding Meishan folk woodcarvings.
Virtual Reality Enables the Dissemination and Preservation of Early Works of Art
Authors: Cai Chunming
Published: March 2024

With the rapid development of digitalization and information technology, virtual reality (VR) technology has shown unique potential in disseminating and conserving early works of fine art, changing people’s traditional ways of appreciating and conserving fine art. The article examines the use of virtual reality technology in disseminating and preserving early works of art. The objective is to improve the accessibility and conservation efficiency of art works by using digitization methods. The study uses VR technology to digitize works that are more vivid and easy to disseminate in terms of visual communication, with a 35% increase in audience acceptance, and digital protection effectively reduces the rate of work attrition to about 20%. Through empirical analysis, it has been found that the digital platform that relies on VR technology improves art works’ dissemination effect and protection efficiency. Virtual reality technology is effective at protecting and disseminating early works of fine art, promoting the public’s appreciation and understanding of art, and providing a new method for the digital transformation of fine art works.
A study of key issues in parallel algorithms for face recognition based on genetic neural networks
Authors: Guo Kai , Li Biao , Li Hao , Bai Zhi
Published: March 2024

This study examines the effectiveness of Genetic Neural Networks (GNN) in face recognition, particularly in optimizing parallel algorithms to overcome the challenges posed by complex data. We have significantly improved recognition accuracy and computational efficiency by employing an adaptive genetic algorithm that fine-tunes neural network weights through Selection, crossover, and mutation. Our approach was tested across diverse datasets, covering variations in posture, age, ethnicity, and lighting conditions. The results demonstrate outstanding recognition rates: 99.82% on LFW, 97.94% on AgeDB-30, 95.11% on CFP-FP, 95.87% on CALFW, and 89.44% on CPLFW, showcasing exceptional robustness against complex lighting and occlusions. Additionally, our algorithm maintains balanced accuracy across different ethnicities with an overall recognition rate of 96.77% and boasts a substantial reduction in processing time to an average of 4.15 seconds. These advancements underscore the potential and practicality of our method in enhancing face recognition technology.
The Utilization of Virtual Reality Technology in the Scientific and Technological Protection and Cultural Inheritance of Clarke Porcelain--Taking Clarke Porcelain in the Collection of the City University of Macau as an Example
Authors: Huang Guang , Zhao Qiang
Published: March 2024

Virtual Reality (VR) technology heralds a transformative era for the safeguarding and disseminating cultural heritage. This paper examines its application through the lens of the Clark Porcelain collection at the City University of Macau, highlighting VR’s pivotal role in the scientific preservation and cultural transmission of these artifacts. By delving into the ornamental intricacies of Clark Porcelain, we evaluate VR’s effectiveness in protecting and showcasing these treasures. The study employs advanced techniques, including 3D virtual scene modeling, texture mapping, and collision detection, to replicate a museum setting, thus elevating the user’s interactive experience. An audience satisfaction survey indicates positive feedback, with relaxation and aesthetic satisfaction scores averaging 4.65 and 4.53, respectively. Moreover, ANOVA results reveal significant technological acceptance disparities across age groups. The Analysis further underscores VR’s substantial impact on cultural heritage promotion, noting the potential for better integration of Clark Porcelain with contemporary technologies. Virtual reality emerges as a formidable tool in the scientific conservation and cultural legacy of Clark Porcelain, offering fresh insights and technical backing for the modernization of traditional cultural heritage preservation.
Design and Innovation of English Teaching Methods in Colleges and Universities Based on Topological Number Theory
Authors: Li Nan , Wang Lei , Gao Mingli
Published: March 2024

This research delves into the innovative application of topological number theory to reform English language teaching methodologies in higher education. We introduce and assess a novel approach to English teaching in colleges and universities, inspired by the principles of topological number theory. Our methodology leverages a unique model for recognizing handwritten English based on visual topological cognition, applying the insights of topological cognition theory to enhance English language instruction. The empirical analysis reveals a low word error rate of just 9.42% for our model, outperforming traditional models like the CRNN, which exhibits a 15.12% error rate. In a 10-week instructional experiment, students taught using the topological approach demonstrated significant improvements across all dimensions of English learning compared to their peers in a control group. The findings underscore the substantial potential of topological number theory in elevating English language teaching in colleges, offering significant benefits in teaching effectiveness and student motivation.
Innovation and Evaluation Analysis of English Teaching Mode in Colleges and Universities Based on Wavelet Packet Decomposition
Authors: Wang Lei , Gao Mingli , Li Nan
Published: March 2024

The surge in information technology has catalyzed a pivotal shift towards innovative English teaching methodologies in higher education, garnering significant attention in educational research. This study introduces wavelet packet decomposition as a novel approach to both the innovation and evaluation of English teaching methods in colleges and universities, aiming to enhance teaching efficacy and scientific rigor. By employing wavelet packet decomposition for data analysis and utilizing a cloud-based evaluation model for teaching assessments, we investigate the impact of a new teaching mode at College M. Results reveal that students exposed to this innovative teaching strategy outperformed their counterparts in the control group on English cognitive tests, particularly in foundational areas such as grammar, where the experimental group achieved an impressive average success rate of 86.73%, compared to the 25%-50% range of the control group. These findings highlight the substantial benefits of the innovative teaching mode in elevating students’ English learning outcomes, particularly in grasping basic concepts. Furthermore, integrating a cloud evaluation model offers a comprehensive and scientific framework for assessing teaching effectiveness. This research validates the efficacy of the novel teaching model and introduces an innovative evaluation methodology for English education in tertiary institutions.
The Construction of Wisdom Teaching Mode of Physical Education and Training in Colleges and Universities in the Internet Era
Authors: Qian Yahui
Published: March 2024

The rise of the intelligent teaching model, relying on artificial intelligence and digital information technology, provides students with personalized and autonomous learning pathways. The model encourages students to learn independently and develop personally by integrating online and offline learning resources, enhancing their innovation and practical skills. Educational innovation has focused on exploring how to effectively incorporate competent teaching resources to improve teaching efficiency and students’ physical education skills. This study designed a new smart teaching mode for physical training science using blended learning theory and artificial intelligence technology. The differences in students’ physical education performance, participation, and satisfaction between the traditional and intelligent teaching modes were analyzed by comparison. The students who used innovative teaching methods in the study were better than those who used conventional teaching methods in 100-meter sprint and basketball shooting accuracy, with an average improvement rate of 15%. According to the study, the intelligent teaching mode can effectively enhance students’ physical education learning efficiency and mastery of movement skills, paving the way for a new development direction in college physical education.
Exploring the Methods and Paths of Integrating Entrepreneurship and Innovation Education into Applied Undergraduate Education
Authors: Wu Yuefeng
Published: March 2024

In the context of a global enthusiasm for innovation and entrepreneurship, this study explores practical strategies for incorporating entrepreneurship and innovation education into applied undergraduate curricula, marking a pivotal shift in educational reform. Utilizing a PEST analysis, cloud computing for resource allocation, and decision tree algorithms, we comprehensively examine the innovation and entrepreneurship education landscape in applied educational institutions. Our study demonstrates that strategic resource allocation can substantially improve both the utilization efficiency of resources and the overall impact of education. Establishing a resource allocation system enhances the alignment between educational resources and specific tasks, leading to marked improvements in resource efficiency. Comparative assessments indicate that applied institutions are particularly adept at fostering students’ entrepreneurial and innovative capacities, with student-led ventures in these institutions generating an average net profit of 210,000 to 500,000 yuan and capturing a market share of 58.88%. The research underscores the necessity of constructing a supportive framework for innovation and entrepreneurship education, advocating for an interdisciplinary stance and stronger school-business partnerships as essential components for optimizing educational effectiveness in applied undergraduate programs.
Identification of English Teaching Effectiveness and Students’ English Proficiency Development in Colleges and Universities Combining Refined Bilinear Attention Networks
Authors: Xi Lihong
Published: March 2024

With the current application of artificial intelligence in education, English teaching methods in colleges and universities are developing rapidly. In this paper, we explore the application of the streamlined bilinear attention network to enhance students’ English proficiency and evaluate teaching effectiveness to improve teaching efficiency and improve students’ English proficiency. The study applies the bilinear attention mechanism to effectively process visual information during college English teaching using computerized visual learning methods to improve the accuracy of classroom teaching quality assessment. The methodology includes implementing a bilinear attention mechanism and applying a deformable convolution module to extract more accurate image features and optimize model performance. The model achieves 98.89% accuracy in facial expression recognition on the CK+ dataset, and 88.5% and 78.9% on the RAF-DB and Fer2013 datasets, respectively. Through online emotion evaluation experiments, the model performed well in recognizing emotional activity in teaching videos, which is highly consistent with the manual evaluation results. In analyzing students’ English proficiency development, the model-assisted teaching method can significantly improve students’ listening, grammar, phonetics, and many other abilities, with a mean value of self-evaluation reaching 4.09576 points. It shows the effectiveness of the streamlined bilinear attention network in assessing the teaching effectiveness of English teaching in colleges and universities and improving students’ abilities. Not only does the model accurately identify emotional activity in the classroom, but it also enhances students’ English learning.
Speech Recognition Enhancement and Compression Perception in Russian Translation Teaching Cooperative System Application
Authors: Xu Di
Published: March 2024

In the digital age, characterized by the ubiquity of big data and artificial intelligence, Russian translation education is poised for transformative change. This study explores the integration of advanced speech recognition and compressed perception technologies into Russian translation instruction, highlighting their potential to elevate educational quality and translator training. Utilizing the Spring Boot framework, we developed a comprehensive Russian translation teaching system, incorporating a Russian-Chinese speech translation model that leverages the RNN Transducer model and an N-gram language model, alongside compressed perception theory for efficient speech signal processing. Our findings reveal a notable enhancement in Russian speech recognition accuracy and processing speed, with a 4.73% improvement in endto-end speech detection accuracy and a significant reduction in word error rate, outperforming CTC and CTC-LM models by 14.79% to 24.85%. Furthermore, speech quality and intelligibility scores experienced marked improvements. The application of speech recognition enhancement and compressed perception technologies emerges as a vital strategy for enriching Russian translation pedagogy and fostering the development of proficient translators.
Strategic Analysis of Informatization of International Trade Enterprises’ Economic Management Models Based on Game Theory Models
Authors: Yang Xinran
Published: March 2024

Exploring the economic management models of international trade enterprises, this research highlights the significant role of informatization strategies informed by game theory. Through the prism of game theory, we analyze the interplay among various stakeholders, including risk takers, managers, and executors. Our study reveals that appropriate risk-taking can drastically lower operational risks. A case in point is Company A, which witnessed a notable improvement in financial stability, with its Z-score rising from 2.6785 in 2005 to 4.6314 in 2022. As theAnalysis shows, effective risk management plays a pivotal role in boosting economic efficiency, evident through enhanced total asset turnover and gross operating margins. This study underscores the utility of a game theory-based economic management model in improving risk management and financial efficiency, thereby advancing the implementation and refinement of informatization strategies within enterprises.
Construction of Local Fiscal Revenue Forecasting Model Based on SVR Model
Authors: Yu Xianghui
Published: March 2024

With the development of the economy at hand, local fiscal revenue forecasting is becoming increasingly important for policy making and budgetary management. In this paper, based on SVR (Support Vector Regression) model, the method of building a more accurate local fiscal revenue forecasting model is discussed. The study is constructing a local fiscal revenue forecasting model based on the SVR model to improve forecasting accuracy. The PCA method is applied to preprocess the data to reduce multicollinearity and extract the key influence factors. The SVR model is used to forecast, and the appropriate kernel function and model parameters are chosen. The model’s ability to predict accurately is demonstrated by the average prediction error of 2.47% in the short-term and 3.29% in the medium- and long-term forecasts. The PCA-SVR model is more effective in dealing with seasonal and short-term shocks than traditional time series models. The study proved that the SVR model is an effective and powerful tool for predicting local fiscal revenues.
Research on the Practice of Collaborative Parenting between Mental Health Education and Student Management in Colleges and Universities in the Information Age
Authors: Zhang Tingting
Published: March 2024

In today’s digital era, mental health challenges among college students are escalating. This study investigates how integrating mental health education with student management can foster college students’ comprehensive growth. Employing fuzzy clustering for mental health analysis and leveraging both sample-weighted and feature-weighted algorithms, we assess the mental well-being of students from varied familial backgrounds. Our findings reveal that students from particular family backgrounds exhibit significantly lower mental health scores across personality, emotional stability, behavioral habits, self-awareness, and social interactions, with marked disparities in depression and anxiety levels. The adoption of a collaborative parenting approach markedly improved the mental health outcomes for these students, reducing depression and anxiety scores by 1.815 and 1.436 points, respectively. The study advocates for a concerted effort in mental health education and student management within higher education institutions, emphasizing support for students from challenging family environments to nurture their holistic well-being.
A Spatio-Temporal Network Model of Chinese Ethnic Culture Transmission Paths Cultural
Authors: Zhou Xuefang
Published: March 2024

The current social network analysis method is essential in dealing with massive data on network relationships. By treating individuals, organizations, or countries as nodes and their relationships as connecting lines, the network diagrams provided a new perspective for studying social structure and communication paths. When exploring the path of Chinese national culture, the spatio-temporal network model can better analyze cultural diffusion’s dynamic characteristics and efficiency, and then optimize the diffusion strategy to promote the global diffusion of Chinese culture. In this study, the efficiency and characteristics of cultural diffusion are analyzed in depth using social network analysis, with indicators such as point degree centrality, mediated centrality, proximity centrality, and network flatness. The effectiveness of cultural diffusion is influenced by the identification of critical nodes and the trust propagation mechanism in the normalized model. Estimated by the generalized least squares method, the model demonstrates the increased efficiency of cultural dissemination under specific dissemination attributes and narrative attributes, in which the average number of plays of Chinese cultural content on the TikTok platform reaches 13,585,700, the number of likes reaches 355,123, and the number of comments is 31,398. Enhancing the global communication efficiency of Chinese national culture can be achieved by optimizing the social network structure and content strategy. This study provides a scientific basis and practical guidance for spreading Chinese culture globally, and emphasizes the importance of social platforms in cultural dissemination.
University English Translation Teaching in the Context of Artificial Intelligence: Problems and Countermeasures
Authors: Sun Yanan
Published: March 2024

With the rapid development of artificial intelligence, university English translation teaching faces many challenges and opportunities. This article studies the problems in teaching in this context and proposes effective countermeasures. Diagnostic analysis and factor analysis are used in the article to conduct an in-depth study of the three levels of the teaching process: knowledge skills, autonomy, and emotional development. The students achieved a 70% mastery rate in knowledge and skills, while their independence and emotional development performance was 60% and 50%, respectively. This paper proposes an English speech translation system based on artificial intelligence to enhance teaching effectiveness. After a 14-week teaching experiment, the average grade of the students in the experimental class improved by about 6.82 points compared to the traditional teaching class, proving the system’s effectiveness. The study diagnosed the current problems in university English translation teaching, verified the potential of AI technology in improving teaching quality through empirical research, and combined with AI technology can effectively improve the quality and efficiency of university English translation teaching.
Construction and Research of Aerobics Teaching Evaluation Platform in Colleges and Universities in the Age of Digital Technology
Authors: Wang Haiying , Liu Song
Published: March 2024

As digital technology advances, college aerobics instruction must evolve to enhance teaching efficiency and quality through tech-based solutions. Traditional aerobics evaluation faces challenges like subjectivity, delayed feedback, and inefficiency, hindering quality improvement and modern teaching management. This study introduces a novel, efficient, scientific evaluation platform for aerobics teaching, focusing on quantitative assessment and refined management. The platform demonstrates significant benefits by developing an evaluation index system, utilizing a genetic algorithm for index weight optimization, and employing a fuzzy comprehensive evaluation method for teacher performance. Results show enhanced student satisfaction, a notable 14.81% increase in assessment scores among the experimental group, and improved skill quality and application. This platform offers a fresh perspective and pathway for elevating aerobics teaching in higher education.
Study on the Construction of Educational Management System to Integrate the Elements of Civic and Political Programs with the Employment and Precision Support for Poor College Students in Colleges and Universities under the Learning Migration Theory
Authors: Xu Gaochao
Published: March 2024

Facing the complex and changing job market, poor students in colleges and universities face severe challenges. This study explores how to construct an educational management system for precise employment support for poor college students in colleges and universities by integrating elements of the Civics and Political Science program under the guidance of the learning transfer theory to enhance employment ability and increase employment opportunities. The entropy weight-TOPSIS method is used in the study to assess the quality of employment help for poor college students in a comprehensive manner. Among the 10 colleges and universities, the evaluation scores of the quality of employment assistance work range from 0.25 to 0.7567, and the average score is 0.4432, which concludes that there is a significant difference between different colleges and universities in the quality of employment assistance work. Through the analysis of the multiple linear regression model, it is found that individual career level, school guidance level, and ability development level are the key factors affecting the satisfaction of employsment precision help for poor college students, and the influence of ability development level is the most significant. To improve the employment quality of poor college students, colleges and universities should prioritize individualized guidance and ability development when providing employment assistance.
Fault Detection and Failure Rate Analysis of New Energy Vehicles Based on Decision Tree Algorithm
Authors: Tan Ping , Gong Lanlan
Published: March 2024

New energy vehicles are vital in promoting environmental protection and technological innovation. Fault detection still faces challenges during its operation, and efficient and accurate methods for fault diagnosis are urgently needed. This paper proposes a fault detection and analysis model based on a decision tree algorithm for the fault detection problem of new energy vehicles. The dataset applicable to the model is prepared by preprocessing in-vehicle network data, including data cleaning, integration, and other steps. Fault prediction can be realized after using C4.5 algorithms to construct a decision tree. With a precision of 82.26% on the test set, this model is highly accurate in fault detection, which is 1.23 percentage points higher than the traditional decision tree algorithm. The model’s effectiveness and efficiency in handling large-scale data were demonstrated by its training and testing on training sets of different sizes. Using the traditional algorithm, a training set of 80,000 data was used to reduce the model’s running time from 274,432 seconds to 249,269 seconds. This study provides a practical methodology for fault diagnosis of new energy vehicles, improving fault detection accuracy while optimizing computational efficiency. Real-time monitoring and timely maintenance of new energy vehicles require this.
Parasites in Wildlife in the Federation of Bosnia and Herzegovina
Authors: Omeragić Jasmin , Kapo Naida , Škapur Vedad , Softić Adis , Goletić Šejla , Šaljić Ermin , Goletić Teufik
Published: March 2024

Parasitic diseases of wild animals represent an important area of research. In addition to the significant impact on wildlife health and fitness, many parasitic diseases have zoonotic implications. Due to limited scientific information, this research aimed to investigate parasitic diseases in wildlife in Bosnia and Herzegovina (B&H), focusing on the Federation of Bosnia and Herzegovina (FB&H), emphasizing zoonotic species. In the period from April 2020 to November 2022, we conducted research on 9 wildlife species. We analyzed fecal samples to detect and identify diagnostic stages (eggs, larvae, cysts, and oocysts) of various animal endoparasites using coprological methods, such as sedimentation, flotation, and the Baermann technique. The MERIFLUOR® Cryptosporidium/Giardia test was also used for the detection of Cryptosporidium oocysts and Giardia cysts. In the case of red foxes, intestinal samples were examined using the intestinal scraping technique to detect adult helminths. All collected muscle samples were subjected to the artificial digestion method for Trichinella detection. From 1,278 samples, 70.9% were positive. Parasitic infections were confirmed in 15.9% (11/69) of bears; 83.7% (262/313) of red foxes; 67.6% (44/65) of wolves; 25% (1/4) of wildcats; 20% (1/5) of badger; 43.7% (7/16) of martens; 39.7% (76/191) of wild boars; 84.5% (350/414) of deer, and 77.1% (155/201) of hares. The finding of zoonotic parasites (Toxocara canis, Uncinaria spp., Trichinella spp., Echinococcus spp. etc.) is particularly important due to their potential detrimental effects on human health, which highlights the need for further investigations.
Minimisation of AC Grid Side Input Power Factor Angle for Three-phase AC to Three-phase AC Matrix Converter under Varying Load
Authors: Basak Abhinandan , Syam Prasid , Mukherjee Kaushik
Published: March 2024

Minimisation of AC grid side input power factor angle for a ‘matrix converter (MC)’ improves the efficiency of the grid. Input volt-ampere requirement is minimum if the current drawn by the ‘MC’ is sinusoidal and input displacement power factor (IDPF) is unity. A MC is inherently capable of maintaining a unity displacement power factor (UDPF) angle at its input terminals. However, the input currents drawn from the grid are not sinusoidal. The high-frequency ripples are suppressed by input current filters (ICFs).These filters additionally introduce a leading phase angle for the current which varies with the loading. This phase lead can be compensated by adjusting the angle between the input current space vector and the input voltage space vector of the MC. The computation of this adjustment angle depends on the estimation of power losses in the switching devices. A simple method is proposed in this paper to estimate the switching losses without measuring device voltages and currents using the perturbation technique. The perturbation logic depends on input current, instantaneous active and reactive power computed at regular intervals of time. The proposed method effectively minimises the IDPF angle very close to zero. The experimental results are included for validation,
Modified ResNet152v2: Binary Classification and Hybrid Segmentation of Brain Stroke Using Transfer Learning-Based Approach
Authors: Parimala Nallamotu , Muneeswari G
Published: March 2024

Introduction: The brain is harmed by a medical condition known as a stroke when the blood vessels in the brain burst. Symptoms may appear when the brain’s flow of blood and other nutrients is disrupted. The World Health Organization (WHO) claims that stroke is the leading cause of disability and death worldwide. A stroke can be made less severe by detecting its different warning symptoms early. A brain stroke can be quickly diagnosed using computed tomography (CT) images. Time is passing quickly, although experts are studying every brain CT scan. This situation can cause therapy to be delayed and mistakes to be made. As a result, we focused on using an effective transfer learning approach for stroke detection.

Material and methods: To improve the detection accuracy, the stroke-affected region of the brain is segmented using the Red Fox optimization algorithm (RFOA). The processed area is then further processed using the Advanced Dragonfly Algorithm. The segmented image extracts include morphological, wavelet features, and grey-level co-occurrence matrix (GLCM). Modified ResNet152V2 is then used to classify the images of Normal and Stroke. We use the Brain Stroke CT Image Dataset to conduct tests using Python for implementation.

Results: Per the performance analysis, the proposed approach outperformed the other deep learning algorithms, achieving the best accuracy of 99.25%, sensitivity of 99.65%, F1-score of 99.06%, precision of 99.63%, and specificity of 99.56%.

Conclusions: The proposed deep learning-based classification system returns the best possible solution among all input predictive models considering performance criteria and improves the system’s efficacy; hence, it can assist doctors and radiologists in a better way to diagnose Brain Stroke patients.
First implementation of quality control procedures on selected X-ray machines in South of Benin
Authors: Soglo Tino Romeo , Inkoom Stephen , Hasford Francis , Sosu Edem K. , Biaou Olivier
Published: March 2024

Introduction: The use of X-ray equipment for medical diagnostic radiography procedures has increased due to advances and complexity of radiological procedures. Achieving good image quality while keeping exposure of workers, public and patient exposure to an acceptable level has become a prerequisite for the radiology department in order to comply with best international practices. The aim of this study was to undertake quality control measurement of seven (7) diagnostic radiography equipment in the south of Benin, the first of its kind.

Material and methods: Multifunction detector (Piranha) and beam alignment test tool were used to perform quality control tests on seven (7) X-ray units. The method used as well as the interpretation of the results was based on the American Association of Physicists in Medicine (AAPM), United States Food and Drug Administration (FDA), Healing Arts Radiation Protection (HARP), Institute of Physics and Engineering in Medicine (IPEM), International Atomic Energy Agency (IAEA) and Canadian Safety code 35 (S.C 35) recommendations.

Results: The quality control results showed that all X-ray equipment investigated were within standard limits for accuracy of exposure time below 10 ms; reproducibility of kVp, exposure time and dose output; specific dose-kVp2 linearity; and specific dose-mAs linearity. Five (5) out of seven (7) diagnostic X-ray machines passed quality control tests such as X-ray beam alignment, exposure time above 10 ms and kVp accuracy. One (1) X-ray machine failed the quality control test of beam filtration at 70 kVp and above.

Conclusions: The findings of this study have provided baseline data for other radiology departments to embark on similar QA/QC activities, and also explore options for optimization of patient dose. However, there is a need to extend the study to cover more diagnostic X-ray machines throughout the country. It is anticipated that this would ultimately assist in improving radiation protection and safety during medical diagnostic radiological procedures.
Aplikasi Plasma Dingin pada Produk Segar
Authors: Arda Gede
Published: March 2024

Plasma non-termal adalah gas terionisasi yang terdiri dari molekul netral, atom tereksitasi, dan molekul bermuatan. Beberapa molekul sangat reaktif sehingga bereaksi dengan cepat terhadap bahan organik atau non-organik. Karena sifatnya, plasma baru-baru ini diterapkan untuk mendekontaminasi produk pertanian dari berbagai kontaminan. Dalam produk segar seperti buah dan sayuran, plasma non-termal digunakan untuk membunuh bakteri dan mikroorganisme lain yang menempel pada permukaan produk, atau untuk mendegradasi residu pestisida yang melapisi produk. Kontaminan ini mempengaruhi kualitas produk dengan cara tertentu sehingga dapat mengurangi keuntungan yang diperoleh produsen, penangan, dan penjual. Beberapa mekanisme yang menjelaskan bagaimana plasma non-termal mengurangi tingkat kontaminan telah diusulkan oleh para peneliti. Intinya adalah spesies reaktif merusak dinding sel mikroorganisme sehingga tidak dapat hidup atau rusak, dan mereka juga dapat bereaksi terhadap senyawa pestisida dan mendegradasinya menjadi senyawa yang tidak terlalu berbahaya. Namun, spesies reaktif yang sama tidak hanya bereaksi terhadap materi target tetapi juga bereaksi terhadap jaringan produk di sekitar plasma yang diaplikasikan dan mempengaruhi kualitas produk yang diolah. Makalah ini mengulas pengaruh plasma non-termal terhadap kualitas produk segar dari sudut pandang fisik, fisiologis, kimia, dan mikrobiologis.

 

Non-thermal plasma is ionized gas which comprised of neutral molecules, excited atom, and charged molecules. Some of the molecules are so very reactive that react rapidly to almost organic or non-organic matter. Due to its properties, plasma is recently applied to decontaminate agricultural products from various contaminants. In the case of fresh produce such fruit and vegetable, non-thermal plasma is used to kill bacteria and other microorganisms attached to a product’s surface, or to degrade the pesticide residues coating the product. These contaminants affect product quality in a certain way thus, they could reduce the profit gain by producers, handlers, and sellers. Some mechanisms explained how non-thermal plasma reduce the level of contaminant have been proposed by researchers. The point are the reactive species damage the cell wall of microorganisms making them non-viable or damaged, and they could react to pesticide compounds as well and degrade them to less harmful compounds. However, the same reactive species not only react to target-matter but also react to product tissues around the plasma applied and affect the quality of the treated product. This paper reviews the effect of non-thermal plasma on fresh product quality from physical, physiological, chemical, and microbiological viewpoints.
Validando productos de precipitación diaria estimados por sensoramiento remoto con estaciones pluviométricas en la cuenca Vilcanota, Perú
Authors:   Universidad Nacional Agraria la Molina, Lima, Perú / Centro de Investigación y Tecnología del Agua (CITA), Universidad de Ingeniería y Tecnología (UTEC), Lima, Perú, Risco Eber , Lavado Waldo ,   Universidad Nacional Agraria la Molina, Lima, Perú / Servicio Nacional de Meteorología e Hidrología del Perú, Lima, Perú, Rau Pedro ,   Centro de Investigación y Tecnología del Agua (CITA), Universidad de Ingeniería y Tecnología (UTEC), Lima, Perú, Condom Thomas ,   Université Grenoble Alpes, CNRS, IRD, INRAE, Grenoble-INP, Institut des Géosciences de l’Environnement, Grenoble, Franceof Environmental Geosciences de l’Université Grenoble Alpes, Grenoble, Francia
Published: March 2024

La precipitación representa uno de los elementos más importantes dentro del ciclo del agua para la representación de la oferta hídrica en cuencas hidrográficas. Debido a una inadecuada distribución de estaciones, seguridad, relieve, accesibilidad, etc., existe escasez de estos datos en cuencas andinas del Perú. Esto representa uno de los principales inconvenientes que afrontan los investigadores en ciencias de la tierra y ciencia del clima para la representación de manera espacial y temporal de la precipitación. En los últimos años, el avance de las tecnologías permite la estimación de las variables hidrológicas a partir de técnicas de sensoramiento remoto. Estos datos deben ser evaluados con observaciones meteorológicas. En esta investigación se evaluaron once productos de precipitación estimada por sensoramiento remoto (PPEDsr) que estiman la precipitación. La evaluación de los PPEDsr se realizó para el periodo 1981-2018 a paso de tiempo: diario, de diez días y mensual. Se utilizó los estadísticos descriptivos: error medio (ME), correlación de Pearson (R), raíz del error medio cuadrático (RMSE), error absoluto medio (MAE) y BIAS relativo (BIAS). Además, de los estadísticos categóricos: Probabilidad de Detección (POD), Tasa de Falsas Alarmas (FAR), Índice de éxito Crítico (CSI). Los productos MSWEP, CHIRPS, TRMM-3B42, PERSIANN-CDR, resultaron ser más eficientes para representar la variabilidad espacial de las precipitaciones diarias y acumuladas en la cuenca del Vilcanota. Los datos de sensoramiento remoto mostraron ser útiles para representar la variabilidad espacio-temporal de la precipitación la cuenca Vilcanota, los resultados sugieren que los datos de sensoramiento remoto podrían ser utilizados para simular el balance hidrológico en cuencas hidrográficas de montaña andinas con escasa información in-situ.
The Mediating Effect of Job Satisfaction in the Influence of Non-Physical Environment on Employee Performance
Authors: Sundjoto  , Roy Sumaryono  , Sari Anita Kartika
Published: March 2024

Purpose: This study explores the impact of non-physical environment on job satisfaction and employee performance, with an emphasis on the mediating role of job satisfaction. Involving 125 staff-level respondents from paper companies in East Java,
 
Methods: This study used Structural Equation Modeling Partial Least Squares (SEM PLS) method to analyze quantitative data collected through Likert-scale questionnaires.
 
Resullt and Conclusion: The findings showed that the non-physical environment has a significant positive influence on job satisfaction and employee performance. In addition, the mediating role of job satisfaction was found to be significant, indicating that job satisfaction is able to mediate the relationship between non-physical environment and employee performance.
 
Research Implication: Managerial implications include improving non-physical facilities and strategies to increase job satisfaction.
 
Originality/Value: This research contributes to the understanding of the complex dynamics in the work environment and offers insights for human resource managers to improve working conditions and employee performance. Recommendations involve improving management policies and practices to create an environment that supports and stimulates optimal performance.
Potencjalne zmiany w obecnym podziale kraju na województwa a opinia młodzieży szkolnej z wybranych ośrodków regionalnych
Authors: Parol Adam R. , Gręda Łukasz
Published: March 2024

W artykule przeanalizowano potencjał wprowadzenia zmian w obecnie obowiązującym podziale administracyjnym Polski na poziomie wojewódzkim. Zagadnienie rozpatrzono z dwóch perspektyw. Z jednej strony dokonano przeglądu koncepcji pojawiających się w ostatnim ćwierćwieczu, zakładających zmniejsze- nie lub zwiększenie liczby jednostek najwyższego szczebla, a z drugiej – przeanalizowano opinie młodzieży szkolnej uczącej się w wybranych ośrodkach regionalnych w Polsce (w potencjalnych stolicach województw lub w miastach mogących obawiać się utraty tego statusu). W badaniu wzięto pod uwagę następujące miasta: Częstochowę, Kalisz, Koszalin, Płock, Radom i Słupsk (jako potencjalne stolice województw), a także Gorzów Wielkopolski, Kielce, Toruń i Zieloną Górę (jako miasta, które mogłyby stracić status miasta wojewódzkiego). Badanie wykazało niewielkie zainteresowanie kwestą zmian na administracyjnej mapie Polski w analizowanej grupie społecznej, czyli wśród osób urodzonych po 1998 r., nieznających innego podziału. Warto zaznaczyć, że opinia uczniów jest częściowo zbieżna z poglądami przedstawianymi w debacie publicznej i naukowej dotyczącej tego tematu.
Pendampingan Sertifikasi Halal Pada UMKM Makanan Ringan Di Desa Bansari Kecamatan Bansari Kabupaten Temanggung
Authors: Pradewi Gunarti Ika , Chailani Muchammad Iqbal , Arifah Siti
Published: March 2024

Nowadays, halal products have become a lifestyle as well as a necessity for people in Indonesia. The government has tried to fulfil these needs by providing halal certification. This effort certainly requires the participation of various parties including academics. To support these efforts, the author conducted community service in Bansari village related to obtaining halal certification for existing MSMEs. Assistance is carried out using the PAR (Participatory Action Research) method which starts from the stages of (1) Community Research Social Problem Diagnostic, (2) Community Strategic Planning, (3) Community Resource Mobilisation, and (4) Reflection.  The results of the assistance carried out are first, the Bansari Village community has insight into the processing and presentation of halal products that have been determined by the government; second, the community has an NIB; third, the Bansari village community becomes skilled in processing and marketing their processed products so that they can be accepted by the market both offline and online markets.Keywords: Halal certification, Halal products, UMKMAbstrakSaat ini produk halal menjadi gaya hidup sekaligus kebutuhan bagi masyarakat di Indonesia. Pemerintah telah berupaya memenuhi kebutuhan tersebut dengan menyediakan sertifikasi halal. Upaya tersebut tentu membutuhkan partisipasi berbagai pihak termasuk akademisi. Untuk mendukung upaya tersebut penulis melakukan pengabdian kepada masyarakat di desa Bansari terkait dengan perolehan sertifikasi halal bagi UMKM yang ada. Pendampingan dilakukan dengan menggunakan metode PAR (Participatory Action Research) yang dimulai dari tahap (1) Community Research Social Problem Diagnostic, (2) Community Strategic Planning , (3) Community Resource Mobilication, dan (4) Reflection.  Hasil dari pendampingan yang dilakukan adalah pertama, masyarakat Desa Bansari memiliki bekal wawasan dalam pengolahan dan penyajian produk halal yang telah ditetapkan oleh pemerintah; kedua, masyarakat memiliki NIB; ketiga, masyarakat desa Bansari menjadi terampil dalam mengolah dan memasarkan produk olahan mereka agar bisa diterima oleh pasar baik pasar offline maupun online.Kata Kunci: Sertifikasi halal, Produk halal, UMKM
Upaya Pemberdayaan Masyarakat Melalui Pusat Kegiatan Belajar Masyarakat (PKBM) Banti Indonesia di Kecamatan Grobogan
Authors: Qilbi Churaina Ainal , Anjelitha Retha
Published: March 2024

Community empowerment is an effort to optimize the ability of a society or community to improve skills, understanding, attitudes, abilities and be able to utilize existing resources to create welfare and independence so that the community becomes more empowered in the economic, social and cultural fields. One form of effort in empowerment is through non-formal education. One example of non-formal education that organizes learning activities is PKBM (Community Learning Activity Center). The Community Learning Activity Center (PKBM) Bakti Indonesia is one of the PKBMs in Grobogan District. PKBM Bakti Indonesia has an activity program that includes equivalency education, PAUD, TPA, community reading parks, skills such as computer training, multimedia training, and PKW training (Entrepreneurial Skills Education). This study aims to determine community empowerment efforts through PKBM in Grobogan District. This research uses a qualitative approach with descriptive methods. Data collection was done by interview, observation, and documentation. The results of the study show the role of PKBM Bakti Indonesia in community empowerment efforts in Grobogan District. In the field of education, the community is empowered through non-formal education institutions. While in the economic field, the community is empowered through the utilization and development of natural and human resources through PKW (Entrepreneurial Skills Education). Keywords: Empowermen,; Community, Community Learning Center
استخدام استراتيجيات ترتيب الكلمات في تعليم الصرف خاصة في موضوع الصيغة لطالبات الصف الثاني في معهد دار الأخوة للبنات الثاني
Authors: Hanifa Faricha Nidaul , Muassomah Muassomah , Salsabila Jehan
Published: March 2024

Pembelajaran shorof atau morfologi terkadang dianggap mudah dipelajari bagi pembelajar bahasa Arab tingkat pemula, sehingga mata pelajaran ini pun mulai diajarkan di kelas  2 SMP di berbagai sekolah, salah satunya di Pondok Pesantren Daarul Ukhuwwah Putri 2 Malang. Penelitian ini mebahas tentang strategi pembelajaran shorof dengan permainan susun kata yang disesuaikan dengan kurikulum dan buku ajar pondok tersebut, yaitu kurikulum KMI. Peneliti ingin mendeskripsikan bagaimana proses pembelajaran dengan strategi susun kata pada materi shorf sighatul kalimat santriwati kelas 2 di Pondok Pesantren Daarul Ukhuwwah Putri 2 serta mendeskripsikan kelebihan dan kekurangan strategi tersebut. Metode penelitian ini menggunakan metode penelitian deskriptif kualitatif. Data yang diperoleh berupa catatan lapangan, foto, dokumentasi dan lain-lain. Penellitian kualitatif adalah penelitian yang dilakukan berdasarkan paradigma, strategi dan implementasi model secara kualitatif. Hasil pembahasan dapat disimpulkan bahwa penggunaan Strategi Susun Kata Pada Pembelajaran Shorf Sighatul Kalimat Santriwati kelas 2 di Pondok Pesantren Daarul Ukhuwwah Putri 2 membawa pengaruh positif pada pembelajaran shorof. Dilihat dari hasil observasi yang menunjukkan peningkatan kesemangatan santriwati dalam belajar serta memberi inovasi baru bagi guru dalam menyampaikan materi dan mengambil evaluasi.
تأثير لعبة جينغا (JENGA PERMAINAN)على تعليم المفردات في المدرسة الابتدائية الإسلامية المتكاملة المرمحة كامبونغ دالام باريامان
Authors: Saidah Nimatus - , Aisyah Devy -
Published: March 2024

The purpose of this discussion is to determine the effect of playing jenga on mufradat learning in Al-Marhamah Kampung Dalam Pariaman Integrated Islamic Elementary School students. And researchers used experimental research methods with three data collection instruments, namely through observation, interviews, and exams/tests. The research design is Quasi Experiment Design with Nonequivalent Control Group Design. And after the researcher used the jenga game for abstract learning, the researcher found that the results of to were greater than tt, namely 2.55 1.71 therefore Ho was rejected and Ha was accepted, meaning that there was a difference between the value of mufradat learning by using the jenga game with the value of mufradat learning without using jenga games. The conclusion from this study is that playing jenga has an effect on the value of mufradat learning in students.