bluuebunny/crossref_metadata_2025 huggingface dataset:
Using Speech Recognition Algorithms to Improve Listening Training in College English Listening Instruction
Authors: Chen Xiaohua
Published: May 2024

English listening proficiency plays a crucial role in language learning and communication. Speech recognition algorithms can significantly enhance listening training in college English instruction by providing personalized and interactive learning experiences. These algorithms can transcribe spoken English passages, allowing students to receive immediate feedback on their comprehension and pronunciation. Additionally, they can generate exercises tailored to individual proficiency levels, offering targeted practice in areas needing improvement. Incorporating speech recognition technology into listening instruction not only promotes active engagement but also enables instructors to track students' progress more effectively. This paper proposed a novel approach leveraging Generative Adversarial Networks (GANs) within an Optimized Edge Computing (OEC) framework to enhance College English Listening Instruction through speech recognition. Traditional methods for English listening instruction often face challenges in providing authentic and personalized learning experiences. To address these limitations, we harness the power of GANs to generate synthetic speech data that closely resembles real-world English speech patterns. By integrating GANs with OEC, we achieve efficient processing of speech data at the edge, minimizing latency and bandwidth consumption while ensuring real-time feedback and interaction. Through extensive experimentation and analysis, demonstrate the superiority of our GAN-OEC framework over traditional baseline models and other speech recognition algorithms. Results demonstrated that the proposed model achieves an average accuracy of 90.6%, a fluency score of 8.5 out of 10, and a pronunciation accuracy of 84.6%. These results highlight the transformative potential of GAN-OEC in revolutionizing English instruction and language learning outcomes in educational settings.
Evaluation of Teaching Effectiveness Based on Bayesian Network Algorithm in Teaching and Learning Process in Higher Education Institutions
Authors: Xiaoyong Chen
Published: May 2024

The Bayesian network algorithm plays a pivotal role in enhancing the teaching and learning process in higher education institutions by facilitating personalized and adaptive learning experiences. This algorithm leverages probabilistic graphical models to represent relationships among various educational variables, such as student performance, learning resources, and teaching methods. Additionally, Bayesian networks aid instructors in optimizing course design and instructional strategies by identifying areas for improvement and evaluating the effectiveness of different teaching approaches. This paper explores the application of Hidden Markov Chain Bayesian Networks (HMCBN) in analyzing teaching effectiveness within higher education institutions. Teaching effectiveness is a multifaceted concept influenced by various factors, including teaching strategies, student characteristics, and learning outcomes. Traditional statistical methods often struggle to capture the dynamic and interdependent nature of these factors. Through the construction of HMCBN models, this study investigates the probabilistic relationships between teaching strategies, student characteristics, learning outcomes, and teaching effectiveness. For teaching strategies, the probabilities [0.3, 0.5, 0.2] indicate the likelihood of each strategy being employed, suggesting that Strategy 2 is the most frequently utilized, followed by Strategy 1 and Strategy 3. Similarly, the probabilities [0.4, 0.3, 0.3] for student characteristics suggest a relatively balanced distribution among the three characteristic categories. In terms of learning outcomes, the conditional probabilities reflect the influence of both teaching strategies and student characteristics on the outcomes achieved. For each combination of teaching strategy and student characteristic, the probabilities [0.1, 0.3, 0.6], [0.4, 0.5, 0.1], [0.3, 0.4, 0.3], [0.2, 0.5, 0.3], [0.3, 0.4, 0.3], [0.4, 0.3, 0.3], [0.1, 0.7, 0.2], [0.4, 0.5, 0.1], and [0.5, 0.4, 0.1] represent the probabilities of achieving different learning outcomes given specific combinations of teaching strategies and student characteristics.
Tactical Optimization of Soccer Game Based on Motion Trajectory Analysis Algorithm
Authors: Wang Juhai
Published: May 2024

Tactical optimization of soccer games using motion trajectory analysis algorithms involves the utilization of advanced computational techniques to analyze player movements and optimize team strategies. By applying motion trajectory analysis algorithms to tracking data obtained from sensors or video feeds, coaches and analysts can gain insights into player positioning, ball movement patterns, and team interactions during matches. This analysis helps identify tactical strengths and weaknesses, assess opponent strategies, and inform adjustments to game plans in real-time or during post-match analysis. By leveraging these algorithms, teams can refine their tactics, improve performance, and gain a competitive edge on the field. This paper introduces the Motion Trajectory Trigonometric Multi-Objective (MTTM-O) framework as a comprehensive approach to optimizing tactical decisions and predicting match outcomes in soccer. With trigonometric functions to model player trajectories and multi-objective optimization techniques, MTTM-O offers insights into the impact of tactical formations, expected goals, ball possession, and defensive solidity on match results.  Through scenario analysis and multi-objective optimization, we demonstrate the effectiveness of MTTM-O in enhancing strategic decision-making and performance analysis in soccer. Findings underscore the importance of tactical flexibility, adaptation to opponent strategies, and the balance between offensive and defensive aspects of gameplay for success on the field. Through multi-objective optimization, MTTM-O evaluates various tactical formations and their impact on match results. For instance, in scenario analysis, employing a 3-5-2 formation resulted in an expected goal (xG) of 2.2 and a ball possession percentage of 62%, leading to a decisive win. Conversely, a 4-4-2 formation yielded lower xG (0.8) and ball possession (47%), resulting in a draw. These findings highlight the importance of tactical flexibility and adaptation to opponent strategies for success on the field.
Evaluating the Learning Effectiveness of A Blended Teaching Model of College English Using A Decision Tree Algorithm
Authors: Sun Yanting
Published: May 2024

The learning effectiveness of a blended teaching model of college English, utilizing a decision tree algorithm, demonstrates promising outcomes. This model combines traditional classroom instruction with online learning components, allowing for personalized and interactive learning experiences. By employing decision tree algorithms to analyze student data and performance metrics, instructors can tailor instructional strategies to individual learning styles and needs. This data-driven approach facilitates targeted interventions, adaptive feedback, and optimized course materials, ultimately enhancing students' English language proficiency and academic success. The blended teaching model harnesses the power of technology and data analytics to create dynamic and effective learning environments in college English education. \College English education. The HGBT-DT model combines genetic algorithms, blended teaching methods, and decision tree algorithms to tailor instructional strategies to individual student needs. Through a comprehensive study involving 100 students, we demonstrate the efficacy of the HGBT-DT model in enhancing language proficiency and critical thinking skills. Results indicate a significant improvement in student performance, with an average post-test score increase of 15 points compared to pre-test scores. Additionally, the HGBT-DT model achieves an optimization score of 0.90, indicating a high level of effectiveness in optimizing teaching strategies. Furthermore, decision tree analysis reveals personalized teaching recommendations, leading to improved student outcomes across diverse learner profiles. This study highlights the potential of the HGBT-DT model to revolutionize teaching practices and promote personalized learning experiences in College English education.
Application of Improved Association Rule Algorithm in Teaching Management Systems of Colleges and Universities
Authors: Qingming Wang
Published: May 2024

Teaching management systems (TMS) are comprehensive platforms designed to streamline various aspects of educational administration, instruction, and communication within academic institutions. These systems typically offer features such as course scheduling, grade management, attendance tracking, and communication tools for instructors, students, and administrators. TMS also facilitates content delivery, assessment creation, and student progress monitoring, providing a centralized hub for all aspects of teaching and learning. With the integration of modern technologies like cloud computing and mobile applications, TMS enhance accessibility, efficiency, and collaboration among stakeholders in education. This paper explores the integration of Frequent Pattern Decision Support Systems (FP-DSS) into Teaching Management Systems (TMS) and its impact on teaching and learning practices in higher education. Through a comprehensive experimental analysis, we investigate the effectiveness of FP-DSS in improving learning outcomes, personalization, and student engagement across various teaching methodologies. The findings reveal significant improvements in learning outcomes, with average exam scores increasing by up to 12% when FP-DSS is incorporated into innovative teaching methodologies. Additionally, we observed enhanced personalization of instruction, with a rating of 9 out of 10 for the effectiveness of FP-DSS in tailoring learning experiences to individual student needs. Furthermore, student engagement showed notable improvements across all experiments, with students actively participating in the learning process and demonstrating higher levels of motivation and interest.
Exploring the Cultural Significance and Economic Potential of a Wau Bulan Chatbot
Authors: Vinothini Kasinathan
Published: May 2024

This research paper aims to investigate the impact of cultural tourism on the economic development of a country. Cultural tourism, defined as tourism centred on cultural attractions and products, has emerged as one of the fastest-growing segments in the tourism industry. It plays a significant role in attracting visitors, generating revenue, and fostering cultural exchange. This study explores the cultural significance of Wau Bulan, a traditional Malaysian kite, as a case study to understand how cultural tourism can contribute to the country’s economic growth. Through an analysis of literature and case studies, the research highlights the various types of Wau Bulan, traditional manufacturing techniques, cultural symbolism, and regional craftsmanship. Additionally, it explores successful cultural tourism approaches implemented in other countries, such as China’s "One Belt, One Road" initiative and Japan’s cherry blossom season. The findings emphasize the importance of preserving cultural heritage, promoting cultural tourism, and harnessing its potential to boost the tourism industry and overall economy. The research concludes by suggesting strategies to further enhance cultural tourism experiences and maximize its benefits for local communities and tourists alike.
Impact of Under Voltage Load Shedding Approach for Voltage Security Control in Power Quality Environment
Authors: Syahrul Ashikin Azmi
Published: May 2024

Contingencies in power system are an ever-present problem for electrical engineers. They may cause the system to have low voltages due to active and reactive power deficiencies. Engineers shold consider the many solutions to approach this problem. The solution has to be appropriate to the contingency faced so as to be able to solve the issue without major damage to a power system. A drastic measure that can be used is by removing low voltage loads or ‘shedding’ the problematic loads. This method of Under Voltage Load Shedding is done by shedding or ‘islanding’ buses that have fallen to a predetermined minimum voltage for a predetermined time to prevent a cascade of blackouts in the widespread power system. The method to automate the process is by using two optimization techniques, Evolutionary Programming (EP) and Particle Swarm Optimization (PSO). This paper proposes a new hybrid algorithm, named Integrated Chaotic Swarm Based-Evolutionary Programming Optimization (ICSBEP) Technique for Voltage Security Control using Under Voltage Load Shedding (UVLS) approach. Voltage security is indicated by the reduction in voltage stability index, FVSI. In this study, EP, PSO and ICSBEP optimizations algorithms were developed and tested on a IEEE 30-bus reliability test system (RTS). Comparative studies were conducted to observe the advantages of the hybrid algorithm over traditional EP and PSO algorithms. The results obtained from the study can help manage the power quality of the system in ensuring that the customer receive secure electricity supply.
Reactive Power Management in Loss and Voltage Control via Integrated Clonal Accelerated Evolutionary Programming
Authors: Rahmatul Hidayah
Published: May 2024

Optimal Reactive Power Dispatch (ORPD) plays a crucial role in maintaining voltage stability, enhance power transfer capability, improve system efficiency, regulate voltages, manage congestion, facilitate renewable energy integration, and achieve cost savings in power systems. This paper presents a new optimization technique for optimal reactive power management in power transmission system, called Integrated Clonal Accelerated Evolutionary Programming (ICAEP) algorithm to optimize the reactive power to be dispatched by the generator buses under 3 scenarios with cases. The ICAEP was developed based on hybridization of the traditional Artificial Immune System (AIS) and Evolutionary Programming (EP). The two cases demonstrate the effect of reactive load increment at the chosen load buses; while the three scenarios represent the ORPD schemes which indicate the involvement of generator buses either 3 generators, 4 generators or 5 generators. Implementation of ICAEP outperformed AIS and EP in both objective functions either in minimum voltage maximization or power loss minimization, involving all the cases under the three scenarios. The performance of the ICAEP is evaluated on the IEEE 30-bus test system. The results would be beneficial to power system operators and planning expansion and knowing the status of their systems in their utilities. The developed optimization engine is also robust and feasible for further optimization problem solving initiatives.
Automated Text Recognition and Segmentation for Historic Map Vectorization: A Mask R-CNN and UNet Approach
Authors: Suresh Dodda
Published: May 2024

Historic maps are essential for comprehending how buildings and landscapes have changed over time. For this—vectorization can be a useful method of analysis for an extensive collection of these maps. However, text overlaps with structural elements—often makes this process more difficult. Therefore, an automated pipeline for text recognition, pixel-level text mask creation, dataset generation, and text bounding box detection has been proposed. Findings shows—text segmentation, detection, and recognition were demonstrated by the combination of Mask Region-based Convolutional Neural Network (Mask R-CNN) and UNet model achieved a 99.12% of all text occurrences in images—which also attained an accuracy of 87.72% while collecting text inside bounding boxes. This end-to-end pipeline shows potential for a wide range of future uses, especially when it comes to text removal for the purpose of making historic maps easier to vectorize and analyze—which will improve the understanding of historical buildings and landscapes.
Capacity Utilization Assessment Using Discrete-Event Simulation: Case Study of a High-Density Crowd Visiting the Holy Rawda in the City of Madinah
Authors: Kawther Saeedi
Published: May 2024

Managing a high-density crowd is challenging, especially when space is limited, due to increased risk of crowd disasters. There are many considerations to lower disaster risk and ensure crowd safety such as infrastructure, facility, staff, emergency response plan, education and awareness. This paper investigates capacity management, which is the most critical consideration when space is limited. Discrete-event simulation (DES) technique is highly adept at reproducing complex real-world operations and can incorporate numerous stochastic variables, thereby improving its effectiveness in decision-making. The objective of this study is to assess capacity utilization of small space through formulating space features and crowd dynamic with a DES model. The model is intended to provide support for informed decision-making process related to capacity management. A real case study about a high-density crowd visiting the Holy Rawda was employed. The data related to the visiting parameters and visit experience KPIs were captured through a range of interviews and actual visits. Comparing the results of the simulation scenarios against the proposed KPIs had a surprising result, there is only 79% utilization of the area, although, intensive high-density crowd were featured during all the visits. It means better management of the crowd may allow 21% more visitors to visit the Holy Rawda.
Electromagnetic Transverse Modes in Periodic Structures: Mathematical Analysis and Engineering Applications
Authors: Zeineb Klai
Published: May 2024

This study explores the electromagnetic transverse modes in periodic structures, combining mathematical analysis with practical engineering applications. We showcase how the deliberate arrangement of materials, using Maxwell's equations and Bloch's theorem, may control and guide electromagnetic waves for novel applications in devices. We emphasize the progress made in photonic crystals and metamaterials, which have resulted in significant developments in fields such as optical computing and stealth technologies. The debate encompasses the potential of computational methods to further improve the functions of materials and devices. This paper highlights the important interaction between theoretical physics and applied engineering, which lays the foundation for future technical advancements in wave manipulation.
Enhancing Power Quality in ON-Grid Systems with PV-STATCOM for Reactive Power Compensation
Authors: Amol A. Suryawanshi
Published: May 2024

This research investigates the integration of an Artificial Neural Network (ANN) controlled boost inverter into a solar photovoltaic (PV) system connected to the utility grid. The boost inverter, equipped with a Static Synchronous Compensator (STATCOM), ensures stable grid voltage and enhances power quality. The ANN controller fine-tunes the DC-AC conversion process of the boost inverter in real-time, ensuring efficient operation under varying PV output and grid conditions. The system's performance was evaluated through simulations, demonstrating its ability to efficiently manage PV power generation and correct reactive power in local loads, thereby enhancing system reliability and grid stability.
A Novel Optimized Colonic adenocarcinoma Detection using Deep Transfer Learning Approach with XceptionTS Model
Authors: Rakesh Patnaik
Published: May 2024

Colonic adenocarcinoma is a major contributor to global mortality, highlighting the crucial need for efficient detection and classification techniques. This research presents a new method called XceptionTS for classifying and detecting colon cancer using colonoscopy pictures. The XceptionTS method utilizes deep transfer learning techniques by leveraging the Xception model architecture. Nonlinear Mean Filtering (NMF) is used as a noise reduction method in image processing to improve the quality of colonoscopy pictures. We combine the MobileNetV2 and ResNet-50 models for healthcare image segmentation and feature extraction, respectively. The XceptionTS classifier efficiently gives accurate class labels to medical photos by combining Tabu Search Optimization with the strong Xception architecture. The assessment of the effectiveness of XceptionTS model is done using a dataset of 1560 colonoscopy images. An extensive comparison study is undertaken by analyzing the efficacy of our suggested approach with existing research. The XceptionTS system outperforms previous methodologies in colon cancer classification and detection tasks, showing higher accuracy and robustness according to experimental results. Our findings indicate that the XceptionTS technique shows potential as an advanced tool to increase the effectiveness of Colonic adenocarcinoma diagnosis, which could lead to better patient outcomes and healthcare management.
Improving Power Quality in a Grid-Connected Hybrid Power System through the Implementation of a Fuzzy Logic Controller
Authors: Rambabu.yerra
Published: May 2024

The examination of modeling and designing grid-connected hybrid power systems with efficient control strategies is the focus of this study. Integration of wind and photovoltaic systems into the ac-bus bar system is a common practice in enhancing operational performance. Utilization of Matlab Simulink software is employed for the design of this hybrid system, incorporating efficient MPPT control algorithms to optimize power generation from solar and wind sources under varying climatic conditions. Analysis of the maximum power point tracking mechanism and control methods of the hybrid power system is conducted, particularly in response to changes in weather conditions such as wind speed and solar radiation. Maintaining grid voltages and Unity Power Factor (UPF) while feeding currents into the grid is essential for the hybrid system. The employment of Proportional Integral (PI) control instead of Fuzzy Logic Controller (FLC) in the voltage-oriented control approach is explored to enhance power quality.
Developing a Model for Understanding the Factors that Affect Individuals' Intentions to Share Personal Information
Authors: Abdulaziz Aborujilah
Published: May 2024

With the outbreak of COVID-19, digital contact tracing (DCT) applications have been implemented to track the transmission of the highly contagious disease. However, there has been significant resistance to using these apps due to individuals' concerns about disclosing personal information. This study aimed to examine individuals' intentions to reveal their details on DCT applications. A conceptual framework was developed incorporating theories of dual calculus, Hofstede's cultural theory, information boundary theory, and individual factors. A quantitative approach was employed, using a random sampling methodology to gather data from 533 respondents. The proposed framework was validated through partial least squares path modeling. The findings revealed that COVID-19-related stress, lack of transparency, and uncertainty avoidance negatively predicted intentions to disclose personal information. Conversely, collectivism, expected community-related outcomes of sharing information, expected personal outcomes of sharing information, and information privacy concerns positively predicted intentions to disclose personal information. This research provides insights into the factors that influence the widespread acceptance of DCT applications and can assist related authorities in ensuring their successful implementation.
UX Design for an E-commerce Application: A Design Thinking Perspective
Authors: Joselle D. Concepcion
Published: May 2024

The development of e-commerce applications has revolutionized the way people conduct business, but challenges still exist in designing applications that align with user needs and expectations. This study aims to document the design-thinking (DT) approach used in the development of a customized e-commerce application based on the user's perspective, with the goal of extracting the user experience of traditional commerce processes to identify its features. In this study, we focused on the first four phases of DT, which include empathize, define, ideate, and prototype, to gather insights and understand the experiences, needs, pain points, and solutions of the local producers. The data gathered from interviews and observations was subjected to content analysis to identify patterns and themes related to desired features. After analysis, the researchers identified key app features, including integrating data analytics for product performance and demand forecasting, introducing a peer-vendor marketplace, a vendor-managed inventory management system, and a product verification system for authenticity. A mockup prototype design was created and presented to users for feedback. The study highlights the importance of user perspectives in e-commerce app design and the value of design thinking in creating a customized user experience that aligns with user needs.
Classification of Intracranial Hemorrhage (CT) Images Using CNN- LSTM Method and Image-Based GLCM Features
Authors: Sangepu Nagaraju
Published: May 2024

In this study, a hybrid approach is utilized, which combines image-based grey-level co-occurrence matrix attributes and transformed-based attributes. The combination of attribute-based techniques is more accurate in categorizing cerebral hemorrhages in CT images when compared with the transformed attribute-based and image-attribute-based approaches. Deep learning methods, particularly long short-term memory (LSTM), have gained popularity in natural language processing applications like text and sentiment analysis. This paper presents an in-depth deep-learning system that is fully automated. The purpose of the system is to organize radiological data and identify cases of intracranial hemorrhage (ICH) for diagnosis. The structure of the proposed DL model includes 1D convolution neural networks (CNN), long short-term memory (LSTM) units, and a logistic function. A significant dataset consisting of 12,852 radiological reports of head computed tomography (CT) was used to train and assess these components.
Deduplication Methods Using Levenshtein Distance Algorithm
Authors: Valeriano Eugene S.
Published: May 2024

The study aimed to propose methods to improve the data integrity of the Relational databases such as MS SQL, MySQL and PostgreSQL via record duplication detection. The FODORS and ZAGAT Restaurant database benchmark datasets have been utilized to facilitate the processes involved in preparing and delivering high-quality data. Furthermore, the Levenshtein distance algorithm was used to propose three (3) methods namely: default, eliminating equal string, and knowledge-based libraries to cut duplicate records in the database. In the 70% selected threshold, the average detected duplicate records of 88 out of 112 records in the restaurant dataset. Finally, to efficiently detect duplicate records in the database, depend on the data being analyzed and threshold selected.
Cost-Effective Automatic Portable Air Purifier
Authors: Deekshitha Arasa
Published: May 2024

Indoor air pollution has become a severe concern on human health due to improper ventilation, pets and fine dust particles. The demand for efficient air purifiers has surged, yet many existing solutions are generally pricey and lack portability. The suggested air purifier uses modern filtration technologies, including activated carbon filters, to remove a wide range of airborne contaminants, such as dust, allergies, pet hair, and volatile organic compounds (VOCs). By adopting a tiny and lightweight design, the purifier offers outstanding portability, enabling customers to experience clean and fresh air wherever they go. The proposed air purifier possesses a distinctive design that integrates a high electric field generator and UV light source. The high electric field technique effectively accumulates and neutralizes airborne particles, including dust, pollen, mold spores, and germs. Simultaneously, the UV light component kills dangerous microbes, such as viruses and bacteria, by breaking their DNA structure, offering cleaner and healthier air. To achieve best performance and energy economy the air purifier adopts an automated operation mode. The device operates only upon the detection of motion a human being.
Financial Access and Financial Risk Attitudes towards Improving Microenterprise Performance
Authors: Dedy Sukmana
Published: May 2024

Microenterprise sector plays a pivotal role in driving economic growth in developing nations. This research aims to devise a financial literacy strategy that augments the performance of microenterprise customers of Indonesia's Shariah Microbank in DKI Jakarta. Improving the performance of micro businesses is not only the responsibility of Bank Syariah Indonesia but also the responsibility of many parties, namely the role of the government through the establishment of KNEKS and KDEKS which aim to increase sharia financial literacy and need to be supported by associations both the Sharia Economic Society (MES) and universities who are concerned with increasing sharia financial literacy which leads to improving the performance of micro businesses. This is achieved by investigating the determinants of microenterprise performance, focusing on the financial literacy of the customers availing microfinance services from the said bank. This study adopts a quantitative approach and employs Structural Equation Modeling (SEM) to analyze data, with financial access as mediating variables. The results are further evaluated through Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis—a robust research technique for identifying obstacles and refining effective strategies. The study comprises a sample of 500 microenterprise operators who are clients of the Shariah Microbank in DKI Jakarta. The analysis reveals the following insights: (1) Financial literacy exhibits a positive and moderate influence on the microenterprise performance of Shariah Microbank customers in DKI Jakarta. (2) Financial access demonstrates a positive and moderate impact on microenterprise performance. (3) Financial literacy exhibits a positive and moderate effect on financial access. (4) financial literacy has a positive and moderate effect on financial risk attitudes, (5) financial risk attitudes have positive an insignificant effect on micro business performance, (6) financial literacy through financial access as a mediating variable has a positive and moderate effect on micro business performance, (7) financial literacy through financial risk attitudes variables have positive an insignificant affect the performance of micro business enterprises. This encompasses strategic programs including: (1) Financial proficiency through collaborative Shariah microfinance training within the Islamic Ecosystem and expansion and optimization of the BSI Microentrepreneur Center; (2) Financial attitude and behavior enhancement via workshops on Shariah microfinancial planning and mentorship by BSI personnel for microenterprise operators; (3) Financial access enhancement through intensified digitalization of Shariah microfinancial services and integration of bundled products and services (e.g., incorporating licensing and halal standardization).
Strategic E-Procurement and AI Integration: Pioneering Solutions for Global Service Sector Challenges
Authors: Tara Prasad Tripathy
Published: May 2024

This research article investigates challenges and innovative procurement approaches within the Service Sector. Specifically, through the lens of ten diverse global companies within the service sector, where traditional processes are being transformed through procurement software, yet complexity in implementing procurement software is ever on the rise with the need for customization, integration, user adoption and compliance with regulation and security. Add to this, the cost implications and constant improvements in technology and a picture of the challenges faced is painted. This study examines the multifaceted challenges faced by companies operating in the service sector and how they implement innovative strategies to overcome challenges. The study looks at the challenges, solutions that have been designed and implemented and how successful they have been. A detailed analysis of ten individual cases, utilities transformers to entertainment, and impact of collaborative strategies and organizational culture on how successful these have been presented. The results provide for a richer understanding of procurement challenges and innovative approaches that can be applied and provide insight into success and failure and reasons why, with technology integration, strategy collaboration and organizational cultures providing keys to success. Additionally, gaps in the literature that lead to areas of further study are presented.
Az újraélesztési lánc fejlesztésének lehetőségei - egy országos adatokra épülő kutatás tanulságai
Authors: Mikesy Gergely , Belicza Éva , Sinka Lászlóné Adamik Erika
Published: May 2024

Bevezetés: A kórházi körülmények között bekövetkező szívhalál alapvetően gyakori eseménynek minősül. Az okok feltérképezése segíthet a megelőzésben, mert bár vannak olyan kórképek, amelyek esetében a kórházi körülmények között fellépő hirtelen szívmegálláskor esetén tökéletesen végrehajtott reanimáció sem hozhat pozitív eredményt, törekedni kell arra, hogy az újraélesztési folyamat megfelelő módon történjen, ne függhessen annak szervezettségétől a beteg túlélési esélye.
Célkitűzés: Célunk, hogy felhívjuk a figyelmet az egészségügyi intézményekben végzett újraélesztések eredményességének növelési lehetőségeire.
Módszer: A témában készült kutatás, valamint az azóta a NEVES rendszerbe érkezett adatok feldolgozása alapján mutatunk be összefüggéseket, illetve szakirodalmi- és intézményi jógyakorlatok bemutatásán keresztül igyekszünk fejlesztési javaslatokat bemutatni.
Eredmények: Felmérésünk szerint hazánkban a kórházi körülmények között bekövetkezett szívhalálok reanimációinak során jelentős intézményi, osztályos, és eszköz rendelkezésre állási különbségek fedezhetők fel. Érdemes minden intézménynek saját felmérést készíteni tehát, viszont az az adatokból, és a bevont szakértők véleménye alapján is látszik, hogy az oktatásban, és a kommunikációs fejlesztések terén is több hazai intézményben lehetne újításokat bevezetni.
Megbeszélés: Az intézményi szintű eredményesség javulásának egyik fontos kritériuma az ellátási feltételek megfelelőségének biztosítása, ugyanakkor az eszközös, és humán erőforrás fejlesztések, az újraélesztés, valamint az újraélesztési lánc működésének oktatása, valamint az intézményi kommunikáció javítása is a kórházak eredményességét javíthatják. 
Következtetés: Az újraélesztési lánc intézményi működése egy nagyon komplex folyamat, ahol a jól működő gyakorlat nem mindig párosul a sikeres újraélesztésekkel. Jelen közlemény célja az, hogy bemutassa az újraélesztési lánc esetleges hibás működése mögött meghúzódó okokat, és ezekre adekvát megoldási javaslatokat, működő jógyakorlatokat mutasson meg.
Telemedicina a hazai gyermekgyógyászati járóbeteg-szakellátásban
Authors: Kovács Erika Krisztina
Published: May 2024

A telemedicina a járóbeteg-szakellátás egyik lehetséges formája. Az elmúlt években az infokommunikációs technológia fejlődésével egyre inkább elérhető. A COVID-19 járvány és a távolságtartási szabályok felgyorsították elterjedését Magyarországon is. Nemzetközi szakirodalomban hatalmas mennyiségű információ áll rendelkezésre a telemedicina alkalmazhatóságával kapcsolatban gyermekgyógyászati kórképekben. A magyarországi közfinanszírozott ellátás finanszírozási adatbázisának elemzésével a hazai gyakorlat összevethető a külföldi tapasztalatokkal, különösen a gondozás, az életkor, a betegségcsoportok és a területi egyenlőtlenség szempontjából. Bár a telemedicinától a területi egyenlőtlenségek csökkentését várják, az adatok alapján azt lehet megállapítani, hogy magában a telemedicina ellátásban is vannak területi különbségek, sőt ezek betegségcsoportokban különbözőek. A várttal ellentétben nem jelenik meg a kistelepülésen élők túlsúlya a használók között. Az eredmények rámutatnak arra, hogy az egységes országos telemedicina-fejlesztés mellett a regionális szempontokat is figyelembe kell venni ahhoz, hogy az egyenlőtlenségek csökkenjenek.
Mesterséges intelligencia alapú GPT-modellek felhasználásának lehetőségei és korlátai egészségügyi alkalmazások fejlesztésében
Authors: Angyal Viola , Dinya Elek
Published: May 2024

Bevezetés: Az internet megjelenése jelentős hatással volt az egészségi állapotokkal kapcsolatos információkeresésre. Az OpenAI által fejlesztett ChatGPT, egy szövegalapú párbeszédre képes generatív mesterséges intelligencia, tovább erősítette ezt a tendenciát. A ChatGPT integrációs lehetőségeinek köszönhetően számos személyre szabott GPT alkalmazás jelent meg az egészségügyi területeken.
Célkitűzés: Munkánk legfőbb célkitűzése az volt, hogy megvizsgáljuk jelenleg milyen személyre szabott GPT modellen alapuló, bármely egészségügyi területet érintő, mesterséges intelligencia-alkalmazások állnak a cikk írásának pillanatában rendelkezésre.
Módszer: Munkánk során egy több, mint 10 000 különböző, személyre szabott GPT alkalmazást tartalmazó adatbázist vizsgáltunk. Összesen 406 db személyre szabott, egészségügyi témával foglalkozó GPT alkalmazást azonosítottunk, melyeket további vizsgálatoknak vettünk alá, míg végül 232 db-ra szűkítettük le a vizsgált alkalmazások listáját. Általunk meghatározott kategóriákba soroltuk őket, végül pedig értékeltük és összehasonlítottuk a nemzetközi irodalomban talált kutatásokkal.
Eredmények: Összesen tíz kategóriába soroltuk az alkalmazásokat, melyek közül a legnépszerűbbek a személyre szabott diéta és fitnesz, valamint a mentális egészség támogatására irányuló fejlesztések voltak. Megállapítható, hogy az egyre fejlődő technológia révén a személyre szabott GPT alkalmazások sokféle szociális segítő szerepét tölthetik be a jövőben, segítve az embereket az élet különböző területein.
Következtetés: Összeségében elmondható, hogy ezek az alkalmazások új távlatokat nyithatnak a személyre szabott egészségügyi segítségnyújtásban, jelentős társadalmi hatással. Nem szabad azonban megfeledkeznünk arról, hogy a technológia kockázatot is rejt magában. A felhasználókat mindig tájékoztatni kell, hogy kritikusan értékeljék a kapott válaszokat és konzultáljanak egészségügyi szakemberrel mielőtt döntést hoznak.
Kulcsszavak: mesterséges intelligencia, személyre szabott GPT, digitális egészségügy,
adatvezérelt egészségügy
Pelvic fractures in blunt trauma patients: A comparative study
Authors: Fokin Alexander A , Wycech Knight Joanna , Tharp Madison E , Brinton Kyler C , Gallagher Phoebe K , Xie Justin Fengyuan , Weisz Russell D , Puente Ivan
Published: May 2024

BACKGROUND

Pelvic fractures (PF) with concomitant injuries are on the rise due to an increase of high-energy trauma. Increase of the elderly population with age related comorbidities further complicates the management. Abdominal organ injuries are kindred with PF due to the proximity to pelvic bones. Presence of contrast blush (CB) on computed tomography in patients with PF is considered a sign of active bleeding, however, its clinical significance and association with outcomes is debatable.

AIM

To analyze polytrauma patients with PF with a focus on the geriatric population, co-injuries and the value of contrast blush.

METHODS

This retrospective cohort study included 558 patients with PF admitted to level 1 trauma center (01/2017-01/2023). Analyzed variables included: Age, sex, mechanism of injury (MOI), injury severity score (ISS), Glasgow coma scale (GCS), abbreviated injury scale (AIS), co-injuries, transfusion requirements, pelvic angiography, embolization, laparotomy, orthopedic pelvic surgery, intensive care unit and hospital lengths of stay, discharge disposition and mortality. The study compared geriatric and non-geriatric patients, patients with and without CB and abdominal co-injuries. Propensity score matching was implemented in comparison groups.

RESULTS

PF comprised 4% of all trauma admissions. 89 patients had CB. 286 (52%) patients had concomitant injuries including 93 (17%) patients with abdominal co-injuries. Geriatric patients compared to non-geriatric had more falls as MOI, lower ISS and AIS pelvis, higher GCS, less abdominal co-injuries, similar CB and angio-embolization rates, less orthopedic pelvic surgeries, shorter lengths of stay and higher mortality. After propensity matching, orthopedic pelvic surgery rates remained lower (8% vs 19%, P < 0.001), hospital length of stay shorter, and mortality higher (13% vs 4%, P < 0.001) in geriatric patients. Out of 89 patients with CB, 45 (51%) were embolized. After propensity matching, patients with CB compared to without CB had more pelvic angiography (71% vs 12%, P < 0.001), higher embolization rates (64% vs 22%, P = 0.02) and comparable mortality.

CONCLUSION

Half of the patients with PF had concomitant co-injuries, including abdominal co-injuries in 17%. Similarly injured geriatric patients had higher mortality. Half of the patients with CB required an embolization.
Meta-analysis of new intervention measures for preventing side effects of artificial joint replacement
Authors: Jiang Wei , Zhu Ting-Biao
Published: May 2024

BACKGROUND

Intertrochanteric fracture of the femur occurs mostly among older people, and seriously affects daily life and quality of life. At present, physical intervention, drug treatment, routine intervention and rehabilitation training are widely used for prevention of side effects, but it is still inconclusive which intervention has the best effect.

AIM

To compare the effects of new intervention measures for preventing side effects of artificial joint replacement.

METHODS

We searched the Chinese and English literatures for comparative studies on the prevention of side effects of new interventions for artificial joint replacement from July 2013 to June 2023 in China HowNet, PubMed, Wanfang, Weipu and other databases. Study quality was evaluated by improved Jadad scoring standard, and the effects of different interventions on preventing different complications were analyzed by meta-analysis of evidence-based medicine with Review Manager 5.0 software.

RESULTS

Ten articles, including 869 cases, were finally included. The preventive effects of different interventions on the side effects of artificial joint replacement were studied, and valid data were extracted. There were two articles on the preventive effects of drug intervention, four on comparison of the preventive effects of combined and single interventions, and three on the preventive effects of physical intervention, rehabilitation training and routine intervention. Meta-analysis showed that the preventive effect of rivaroxaban was significantly better than low molecular weight heparin calcium [mean difference (MD) = -0.16, 95%CI: -0.28 to -0.04, P < 0.05]. The effect of combined intervention was significantly better than that of single intervention (MD = -0.08, 95%CI: -0.16 to -0.01, P < 0.001). Physical intervention was significantly better than routine intervention and rehabilitation training (MD = 0.26, 95%CI: 0.16–0.36, P < 0.001).

CONCLUSION

Rivaroxaban combined with rehabilitation training is preferred for preventing deep vein thrombosis after artificial joint replacement. In the prevention of pulmonary embolism, rivaroxaban drug intervention is given priority. The effect of combined intervention is better than that of single intervention.
Surgical treatment of myasthenia gravis using a robotic system – a literature review and a description of the first surgery in Poland
Authors: Wiłkojć Michał , Czyżykowski Łukasz , Kiszka-Wiłkojć Aleksandra , Sośnicki Witold , Doniec Jacek , Zieliński Marcin , Kwiatkowski Andrzej , Walędziak Maciej
Published: May 2024

Wprowadzenie i cel

Na świecie leczenie miastenii z użyciem systemów robotycznych jest stosowane w chirurgii klatki piersiowej od 20 lat. W Polsce po raz pierwszy operację torakochirurgiczną z zastosowaniem takiego systemu przeprowadzono 22 lutego 2022 r. w Wojskowym Instytucie Medycznym – Państwowym Instytucie Badawczym w Warszawie. Wykonano wtedy tymektomię rozszerzoną metodą torakoskopii z użyciem systemu robotycznego da Vinci Xi.

Materiał i metody

Zastosowano dostęp lewostronny z użyciem trzech trokarów roboczych i insuflacją CO2. Po uwidocznieniu lewego nerwu przeponowego uwolniono lewy dolny róg grasicy wraz z tłuszczem lewego kąta przeponowo- żebrowego. Następnie odpreparowano grasicę wzdłuż lewego nerwu przeponowego od worka osierdziowego, uwidoczniono lewą żyłę ramienno-głowową, zaopatrzono gałęzie żylne do grasicy i wypreparowano rogi górne grasicy do poziomu dolnych biegunów tarczycy. Szeroko otwarto prawą jamę opłucnej i wypreparowano grasicę wzdłuż prawego nerwu przeponowego wraz z otaczającą tkanką tłuszczową oraz tłuszczem prawego kąta przeponowo-żebrowego. Preparat usunięto z pola operacyjnego i do obu jam opłucnej założono pojedynczy dren 24 Fr, wprowadzony przez jeden z portów torakoskopowych.

Wyniki

Operacja trwała 162 minuty. W okresie pooperacyjnym nie stwierdzono powikłań, drenaż całkowity wyniósł 50 ml, dren usunięto w 1. dobie po zabiegu. Nasilenie bólu pooperacyjnego było na średnim poziomie, co pozwoliło na wypisanie pacjentki w 2. dobie po operacji. W badaniu histopatologicznym preparatu pooperacyjnego wykazano obecność zanikowej grasicy wraz z otaczającym tłuszczem i węzłami chłonnymi.

Wnioski

Zastosowanie systemu robotycznego w rozszerzonej resekcji grasicy u pacjentki z miastenią pozwoliło na przeprowadzenie bezpiecznego i radykalnego zabiegu, a przez to zmniejszenie nasilenia bólu pooperacyjnego i skrócenie hospitalizacji.
Selected predictive factors of new-onset atrial fibrillation in patients with heart failure
Authors: Dąbrowska Martyna , Uziębło-Życzkowska Beata , Jurek Agnieszka , Maciorowska Małgorzata , Krzesiński Paweł
Published: May 2024

Atrial fibrillation, which is one of the most commonly diagnosed arrhythmias in adults, is associated with high morbidity and mortality. Atrial fibrillation is also the most common arrhythmia in patients with heart failure, and it has been shown to increase the risk of death, heart failure-related hospitalization, and stroke or transient ischemic attack. Considering these clinical and therapeutic implications, it seems advisable to assess patients for risk factors of atrial fibrillation. The purpose of this study was to present the predictors of new-onset atrial fibrillation particularly in patients with heart failure.
Pharmacological treatment of scars after gynaecological and obstetric surgeries
Authors: Chochowska Małgorzata , Martowski Łukasz
Published: May 2024

Jednym z najczęstszych powodów zgłaszania się pacjentek do fizjoterapeuty uroginekologicznego jest blizna po operacji ginekologicznej (np. usunięcia macicy), uroginekologicznej (np. leczenia zaburzenia statyki narządów miednicy mniejszej lub nietrzymania moczu) lub położniczej (np. cięcia cesarskiego). Konsekwencją przebytej operacji mogą być: blizna przerostowa lub bliznowiec, przewlekły ból miednicy, dyspareunia, niepłodność, nieswoiste dolegliwości układów pokarmowego, moczowego lub rozrodczego, zespoły bólowe narządu ruchu lub zaburzenie wzorca postawy ciała i chodu. Aby przeciwdziałać konsekwencjom zrostów pooperacyjnych lub je ograniczyć, należy w sposób planowany wdrożyć terapię blizny, najlepiej z wykorzystaniem odpowiednich środków farmakologicznych jako podłoża. W przypadku wielu z przeznaczonych do tego celu preparatów nie udowodniono ich skuteczności lub jej nie badano. W artykule omówiono substancje aktywne
wchodzące w skład preparatów do leczenia blizn, wyszczególniając ich charakterystykę, mechanizm działania, aspekty farmakologiczne i dostępne badania naukowe na ich temat. Przedstawiono również autorski plan terapii blizny, uwzględniający etapy gojenia się rany, i wskazano metody, w których zasadne jest zastosowanie środków farmakologicznych.