Quality Standards Research Articles

Penyediaan Pendidik dan Tenaga Kependidikan dalam Pendidikan Islam

Islamic education aims to develop individual potential as a whole, including spiritual, intellectual, emotional and physical aspects, in accordance with Islamic values ​​and principles. Therefore, qualified educators and educational staff are needed. This qualitative research uses a library research method, namely a research method carried out by observing various literature related to the problems in the research, in the form of papers, books or writings, both from print and online media. The results of this research are that the quality of educators and educational staff in Islamic educational institutions is currently still a complex and challenging issue. Even though there are efforts to improve quality standards, there are still various challenges that need to be overcome, such as lack of qualifications and competence of educators, low welfare, minimal training and professional development, and inadequate policy support. To overcome this challenge, collaboration is needed between the government, educational institutions and communities to implement structured training and development programs and improve the welfare of educators.

University-based academic programs in addiction studies in the regions of Australia and Aotearoa New Zealand: An overview.

Current trends in the addiction field reflect a significant emphasis on the workforce development and education. There are already some data about university-based addiction studies programs, but not much from Australasia. The aim is to provide an overview and describe the academic programs for addiction professionals in Australia and Aotearoa NZ. The research was conducted in 2017 and updated in 2023. Firstly, university websites were searched using pre-defined keywords, followed by a content analysis of the identified programs. The data were analysed and interpreted by using descriptive statistics. We found 21 universities in Australia (13) and Aotearoa NZ (8) where 46 single programs are provided. There are three bachelor programs, nine masters, and the majority of degrees include (post)graduate certificates and diplomas. No doctorate programs are identified. The taught courses provide comprehensive coverage of the addiction field topics. Twelve programs state clearly that there is clinical practice/internship included. Application to most programs requires completion of a relevant degree and in some cases possible clinical experience. In comparison to educational options in other regions, we observe a trend towards preparing university graduates for the workforce, thereby expanding the range of programs at lower levels. Most programs possibly represent clinically oriented education primarily specialising in addictions, and graduate programs in addictions for professionals with other disciplinary bases. Great emphasis is given to the quality standards of education, and also to relationship between education and labour market. Findings help opening opportunities to collaborate globally.

State Pharmacopoeia of the Russian Federation Edition XV: Development Priorities

INTRODUCTION. Regular reviews of the current portfolio of general chapters and monographs are essential to ensure the well-balanced development of the State Pharmacopoeia of the Russian Federation (Ph. Rus.) in line with the priorities of the national healthcare system.AIM. This study aimed to identify the most promising areas for further Ph. Rus. development through an analysis of recent legislative changes in Russia and the current compendial portfolio.DISCUSSION. This article compares Ph. Rus. editions XIV and XV, analyses the key features and structure of edition XV, and reviews amendments to the regulations governing the Ph. Rus. publication. The current compendial portfolio is dominated by monographs on chemical active substances; it also includes a substantial number of monographs on herbal drugs and herbal drug preparations. Noteworthy, edition XV is the first Ph. Rus. edition to include a separate section dedicated to monographs on excipients necessary for the development of pharmacy compounding. Moreover, this article analyses the coverage of active substances that are used for the production of listed vital and essential medicines.CONCLUSIONS. The authors outlined the priority areas for the development of quality standardisation. The Ph. Rus. should continue developing monographs on active substances that are used for the manufacturing and compounding of listed vital and essential medicines. In addition, the coverage of herbal drugs should be expanded. The Ph. Rus. should develop monographs on excipients that are used for the manufacturing and compounding of medicinal products. Finally, the Ph. Rus. should complete the development of requirements for biological medicinal products and relevant test methods.

Pengaruh Pengalaman Kerja dan Pelatihan Kerja Terhadap Kinerja Karyawan Engineering Maintenance PT XYZ

Company's excellence center will be achieved with competent human resources towards the company's rapid competitiveness. This study aims to investigate how work experience and job training affect employee performance in the Engineering Maintenance Department Organisation at PT XYZ. Population and sample for this study included Engineering and Maintenance employees at PT XYZ. The research utilized multiple linear regression analysis as the primary method to examine the relationships between the variables. A quantitative approach was employed. Research sample was chosen using saturated sampling technique, the study involved a total of 35 respondents. Data analysis results indicate that work experience and job training significantly impact employee performance. According to the coefficient of determination test results, training and compensation contribute 43.2% to employee performance. From this research it is recommended to PT XYZ increase investment in training and develop strategies to enhance employee performance. This should help improve the quality standards of employee performance through training, enabling employees to gain more valuable experience, maintain a smooth production process, and produce high-quality goods.

Pengendalian Persediaan Sparepart dengan Menggunakan Metode Fifo di Warehouse di PT.Heinz ABC Indonesia Pasuruan

Spare parts inventory is a common problem faced by many companies that use lots of machines or robots in their production processes. Where the spare parts warehouse in the company is required to always be prepared and there is no delay in the availability of spare parts to continue to support production machine activities. If the availability of spare parts is late or empty, it will hamper the production process activities within the company. Seeing this problem, researchers are trying to maintain the availability of spare parts using the FIFO (first in first out) method so as to prevent delays or stock shortages. The FIFO method is a method of inventory management that uses product stock in the warehouse based on the time of entry. By using this method, it is hoped that there will be no delays or stock vacancies in the warehouse due to irregularities in picking up spare parts in the warehouse. The aim of this research is to ascertain how the use of the FIFO method affects the warehouse's ability to manage spare parts inventory efficiently. Field research is this type of research. This research uses a qualitative data analysis methodology and inductive reasoning, which starts with precise and real facts before drawing conclusions from them. The research results provide significant benefits in increasing operational efficiency and reducing the possibility of excess or shortage of stock, which can disrupt production and delivery processes. Efficient receiving also helps in maintaining spare parts quality, ensuring that only items that meet quality standards are received and stored. Application of the FIFO method in the spare parts warehouse at PT. Heinz ABC Indonesia also has a positive impact on inventory recording and reporting. With a more regular flow of goods in and out, the recording system becomes more accurate and easier to track. This makes it easier for the accounting and management team to carry out audits and identify potential problems.

AVALIAÇÃO DA EXECUÇÃO DE PRÉ-MOLDADOS EM RESIDÊNCIAS

The use of precast elements in residential construction has proven to be an effective and attractive option due to its speed, precision, and cost reduction. This research explores the particularities, benefits, and challenges associated with this construction method, covering various types of components, such as slabs and beams, as well as the stages of the process, including manufacturing, transportation, and assembly. Among the advantages are the uniformity of components, faster construction processes, waste reduction, and efficient material management, which promotes sustainability in the construction sector. However, challenges also arise, such as the need for rigorous planning, skilled labor, adherence to quality standards in production, and some limitations in project flexibility. Logistical issues and the resistance of structures to weather conditions are essential to ensure the durability of buildings. The study concludes that, despite certain constraints, the strategic use of precast elements can bring significant benefits to residential construction, especially with the advancement of new technologies and innovations.

Study of the Framework and Attributes of Ethical Standards in Journalism

It has always been difficult to create fair evaluation criteria for journalists, especially when it comes to judging morality and ethical conduct in news reporting. These guidelines function as yardsticks for gauging the ethics of news topics and the objectivity of journalistic techniques. These criteria are becoming more and more difficult as journalism changes, especially in the digital age. Fostering ethical journalism requires an understanding of its categorization and internal structure. This analysis employs a conceptual framework to explore the evaluation standards of news ethics. The method involves: Literature Review: Examining existing academic literature, ethical codes, and industry guidelines to outline the prevailing evaluation standards in journalism. Thematic Analysis: Identifying and categorizing the components of evaluation standards into normative and quality standards, assessing their relevance to different aspects of journalistic practice. Case Studies: Analyzing specific instances where journalistic ethics were put to the test, allowing for a practical understanding of how these standards function in real-world scenarios. The primary objective of this study is to clarify the internal structure of journalistic ethics evaluation standards and highlight the distinctions between normative and quality standards. By doing so, the analysis aims to provide insights into how these standards can be effectively applied to evaluate news behaviors and moral character in journalism. What is deemed ethical in one context may not hold the same weight in another. This relativity underscores the importance of understanding the specific circumstances surrounding journalistic practices. Historical Context: The evolution of journalistic ethics is tied to historical events and societal changes. Standards that once sufficed may need reevaluation to address contemporary challenges, particularly with the rise of digital media and misinformation. Complex Internal Structure: The internal structure of evaluation standards can be multi-layered, with different levels of criteria applied depending on the context and specific ethical dilemmas faced by journalists. This complexity requires continuous dialogue and adjustment as new ethical challenges arise. Practical Implications: Journalists and media organizations must engage with these standards actively, incorporating them into training and policy development. By fostering an understanding of both normative and quality standards, the industry can promote a more ethical and accountable journalism practice.

The Relation Between Passively Collected GPS Mobility Metrics and Depressive Symptoms: Systematic Review and Meta-Analysis.

The objective, unobtrusively collected GPS features (eg, homestay and distance) from everyday devices like smartphones may offer a promising augmentation to current assessment tools for depression. However, to date, there is no systematic and meta-analytical evidence on the associations between GPS features and depression. This study aimed to investigate the between-person and within-person correlations between GPS mobility and activity features and depressive symptoms, and to critically review the quality and potential publication bias in the field. We searched MEDLINE, PsycINFO, Embase, CENTRAL, ACM, IEEE Xplore, PubMed, and Web of Science to identify eligible articles focusing on the correlations between GPS features and depression from December 6, 2022, to March 24, 2023. Inclusion and exclusion criteria were applied in a 2-stage inclusion process conducted by 2 independent reviewers (YT and JK). To be eligible, studies needed to report correlations between wearable-based GPS variables (eg, total distance) and depression symptoms measured with a validated questionnaire. Studies with underage persons and other mental health disorders were excluded. Between- and within-person correlations were analyzed using random effects models. Study quality was determined by comparing studies against the STROBE (Strengthening the Reporting of Observational studies in Epidemiology) guidelines. Publication bias was investigated using Egger test and funnel plots. A total of k=19 studies involving N=2930 participants were included in the analysis. The mean age was 38.42 (SD 18.96) years with 59.64% (SD 22.99%) of participants being female. Significant between-person correlations between GPS features and depression were identified: distance (r=-0.25, 95% CI -0.29 to -0.21), normalized entropy (r-0.17, 95% CI -0.29 to -0.04), location variance (r-0.17, 95% CI -0.26 to -0.04), entropy (r=-0.13, 95% CI -0.23 to -0.04), number of clusters (r=-0.11, 95% CI -0.18 to -0.03), and homestay (r=0.10, 95% CI 0.00 to 0.19). Studies reporting within-correlations (k=3) were too heterogeneous to conduct meta-analysis. A deficiency in study quality and research standards was identified: all studies followed exploratory observational designs, but no study referenced or fully adhered to the international guidelines for reporting observational studies (STROBE). A total of 79% (k=15) of the studies were underpowered to detect a small correlation (r=.20). Results showed evidence for potential publication bias. Our results provide meta-analytical evidence for between-person correlations of GPS mobility and activity features and depression. Hence, depression diagnostics may benefit from adding GPS mobility and activity features as an integral part of future assessment and expert tools. However, confirmatory studies for between-person correlations and further research on within-person correlations are needed. In addition, the methodological quality of the evidence needs to improve. OSF Registeries cwder; https://osf.io/cwder.

Long Duration Forecasting and its Performance Capability for Seasonal Variation Modelling of Residual Chlorine Concentrations: A Comparative Evaluation of two Small-scale Water Distribution Systems in Japan

Chlorine dosing control is a critical task for health security, complying with drinking water quality standards while achieving customer satisfaction. In Japan, this became more difficult due to decreasing number of technical personnel as a result of declining population and huge retirement of veterans. As experienced-based dosing control still exists and is considered inefficient due to risks of inaccurate dosing and need of experienced manpower, streamlining of operations is needed. This study aims to address these concerns through the development and evaluation of a deep learning model for residual chlorine concentrations capable of forecasting long durations. In this paper, the model is investigated in seasonal timeframe analyzing trends and variations. Two water distributions systems of varying network—simple and complex, are also compared to further analyze model performance and versatility. The model utilizes the past 24 hours of flow rate, chlorine level at treatment plant, water temperature, and residual chlorine at private homes as input to predict the 12 hours ahead of residual chlorine at private homes evaluated at hourly training lengths of 0.5, 1, 1.5, 2 years. Results revealed that the model achieved high accuracy in predicting hourly residual chlorine with general increasing model error from winter, spring, autumn, and summer due to the progressing instabilities in chlorine concentrations from low to high temperatures. Moreover, smaller system tends to be more unstable incurring lower model performance relative to larger system. In terms of optimal training length, ≥1Y training models are found to have lesser chance of data drift occurrence prospectively reducing model retraining frequency in the future.

Finding wholegrain pasta quality: what are the challenges and opportunities?

This review approaches the challenges and opportunities regarding wholegrain pasta’s quality. Bibliometric maps were created to help visualize wholegrain pasta studies’ main themes and chronology. Most research findings have focused on digestibility and nutritional enhancement, although concerns such as raw materials and processing conditions require further investigation. The main challenges are regulatory harmonization and developing quality standards to evaluate and produce wholegrain pasta. Thus, further research is necessary to overcome these challenges and improve technological and sensory quality of wholegrain pasta.

Maximizing Steel Slice Defect Detection: Integrating ResNet101 Deep Features with SVM via Bayesian Optimization

Accurate detection of defects on steel surfaces is crucial for maintaining quality standards in steel production. This paper addresses the challenge of classifying steel sheets into distinct defect categories by presenting a robust method that leverages deep learning and advanced optimization techniques. We propose a novel approach that utilizes the ResNet101 model to extract deep features, which are then classified using a support vector machine (SVM). To enhance the SVM's performance, Bayesian optimization is employed for hyperparameter tuning. Our method is validated using the "Severstal: Steel Defect Detection" dataset from Kaggle, achieving a validation accuracy of 89.1% and a test accuracy of 90.6%, with a classification error of 0.10934. Additionally, the area under the curve (AUC) for each class exceeds 0.95 in both the validation and test sets, demonstrating excellent discriminatory power. Further evaluation on the DAGM dataset achieved flawless results, with an accuracy of 100%, AUC of 1, sensitivity of 100%, specificity of 100%, precision of 100%, MCC of 100%, F1 score of 1, and kappa of 100%. On the NEU dataset, our method achieved an accuracy of 97.92%, sensitivity of 97.92%, specificity of 99.58%, precision of 98.06%, F1 score of 0.9791, MCC of 97.55%, and kappa of 92.50%. These results demonstrate the robustness and adaptability of the proposed method, offering an efficient and reliable solution for automating steel defect detection and surface defect classification in industrial applications.

Analysis of Supply Chain Risk Control in Aceh Nut Work Using the House Of Risk Method Approach (Case Study: Nutmeg Oil Industry in South Aceh Regency)

South Aceh nutmeg oil plays an important role in the trade of essential oils from Indonesia. 70-80% of Indonesia's nutmeg oil trade comes from South Aceh. However, on the other hand, there is a disruption in price stability in the production of South Aceh nutmeg oil which is influenced by the quality standards of nutmeg oil. The purpose of this study is to identify potential risks that arise in the supply chain, find risk agents as the cause of the risk and control the risk by designing risk mitigation and its formulation in the structure of the nutmeg oil supply chain in South Aceh. The technique used in this study is the House Of Risk (HOR) method. The study has obtained 23 risk events and 17 priority risk agents covering Source, Make, Distribution and Costumer (Return) activities. Then from the risk agents obtained, 11 priority mitigation actions were also obtained as a control of the performance of the nutmeg oil supply chain that can be applied in an effort to reduce the occurrence of supply chain risks so that the industry is able to produce optimally and is able to improve the quality of nutmeg oil which of course has a positive impact on the selling value.

Quality control of eddy covariance fluxes of two ecosystem types with local flux-variance similarity functions in West Africa

Ecosystem capacity studies for carbon sequestration and water extraction are largely conditioned by Eddy Covariance (EC) measurement availability and quality. Our study aims at evaluating several procedures of EC data qualification. Indeed, quality control of EC data is generally ensured by stationarity and well-developed turbulence tests. The latter is based on integral turbulence characteristic (ITC) models. In this study, we revisited the quality control procedure using locally established ITC models for wind speed components and atmospheric scalars (temperature, humidity and carbon dioxide molar densities) in unstable and stable conditions. We also considered the interdependence of flux qualities because of the corrections applied to fluxes during their preprocessing. The analyses were carried out using one year of data collected above a woodland forest and mixed crop sites, both situated in Northern Benin, West Africa. From these analyzes we note that the quality flags vary depending on the use of local or existing ITC models. Also, the test of turbulence development on atmospheric scalars, previously neglected, is of great importance in the quality control of data. Thus, taking into account the ITC models associated with the atmospheric scalars established locally in the well-developed turbulence test as well as taking into account the interdependence of the flux quality have considerably improved the standard quality control procedure used in effectively filtering unrealistic flux data while keeping a considerable percentage of good and medium quality data.

Development of conceptual provisions for implementing innovative technologies to quality standards of public passenger transport

This paper reports a study of the main principles for the formation of public passenger transport service quality standards. The object of the research is public passenger transport services. The task of the study is the development of conceptual foundations for the formation of quality standards using modern innovative technologies. It has been established that the main factor in achieving the quality of public passenger transport services is taking into account innovative technologies and compliance with the criteria and norms of EU standards. Features in the functioning of public passenger transport in the world have been studied, including the use of information platforms for tracking the movement of transport routes, Internet applications, ensuring safety and compliance with environmental requirements. The criteria that serve as indicators of improving the efficiency of the quality of services have been defined, among the main ones are the availability of transportation, comfort, frequency of traffic, and waiting time, quality of service, as well as safety. A system of forming the quality of public passenger transport services has been proposed, which involves determining the needs and requirements of consumers of public passenger transport services, ensures the development of measures to improve the quality of services and their certification. A comprehensive approach to the formation of the quality of public passenger transport services based on the introduction of innovative technologies has been formed, which could make it possible to determine the level of their innovative development, as well as ways to improve it. This approach takes into account the relationship between implemented measures, measuring the level of service quality and the distribution of obligations to ensure the level of services determined by quality criteria. This makes it possible to determine the required level of quality of public passenger transport services and to form a relationship between the level of innovative technologies and the stages of the approach. The practical significance of the results is the design of tools that would ensure the improvement of the quality of public passenger transport services.

WEB BASED INTERNAL QUALITY MANAGEMENT INFORMATION SYSTEM A DESIGN AND PROTOTYPING

Improving the quality of education in higher education institutions is crucial to support the development of human resources and the progress of the nation. Utpadaka Swastika University, as one of the higher education institutions in Indonesia, is committed to producing high-quality and competitive graduates. To ensure this quality, an effective and efficient internal quality assurance system (SPMI) is necessary. This research aims to design and build an internal quality assurance system based on the web using PHP and MySQL at Utpadaka Swastika University with the prototyping method. Software testing is conducted through Black Box Testing. This internal quality assurance system aims to ensure the quality of higher education provided by universities through the implementation of the Tridharma of Higher Education, in order to realize the vision and meet the needs of stakeholders. The achievement of quality assurance goals through the internal quality assurance system will be accredited through external quality assurance systems. This system can assist in presenting document information accessible to program heads, leaders, auditors, administrators, and quality assurance body (LPM) leaders. It facilitates program heads in the process of collecting and submitting documents for evaluation and audit instruments, allowing the LPM to directly identify issues and quality standards in the internal quality assurance process. This system is expected to be used as a reference for further development of an Internal Quality Assurance System so that the system can have better features.

Financial feasibility: developing and commercializing Turmeric Kombucha with the business model canvas

Turmeric Kombucha, a fermented drink combining the anti-inflammatory properties of turmeric, represents a promising product of functional beverage market. In order to successfully bring Turmeric Kombucha to market, it is essential to evaluate its commercialization potential. This involves assessing the Business Model Canvas (BMC) and financial feasibility metrics. This study aims to determine the feasibility and strategies for successfully commercializing Turmeric Kombucha for development a business plan with scale up the production of Turmeric Kombucha. The result indicate that Turmeric Kombucha has a viable business model with 9 elements. Based on financial shows that Net Present Value (NPV) of $ 13,405,417.62, an Internal Rate of Return (IRR) of 71.42 %, a Payback Period (PP) of 0.59 years, and Break-Even Point (BEP) metrics of 3,173 units and $ 4,914.46. The analysis shows strong financial viability and significant growth potential for Turmeric Kombucha, supported by sustainable and efficient supply chain partnerships. The features and characteristics of the obtained results in this study, namely: a) high consumer interest from health-conscious individuals over 18 years old; b) health benefits of Turmeric Kombucha include hepatoprotective, immunomodulatory, antidiabetic, and antioxidant properties; c) key resources include efficient production processes, user-friendly equipment, and adequate human and financial resources. The practical application of these results involves strategies for scale up of market expansion, quality standardization, and supply chain enhancement. Customer relationships are fostered through direct and indirect distribution channels such as marketplaces, word-of-mouth, and retail stores.

Inisiasi Pengolahan Air Embung dengan Teknologi Multimedia Filter (MMF) sebagai Solusi Air Bersih di Kabupaten Bojonegoro

Clean water and proper sanitation are fundamental human needs. Nganti Village, located in Ngraho Subdistrict, Bojonegoro Regency, faces significant drought and clean water shortages, particularly during the dry season. The water quality remains subpar despite the presence of springs and water reservoirs. Consequently, processing raw water from the village's reservoir can offer a viable solution. This service activity aims to harness water reservoirs as a clean water source through multimedia filter (MMF) technology. The activities, conducted from 2022 to the end of 2023, encompass four stages: socializing the program plans, constructing multimedia filters (MMF), installing the water treatment unit on-site, and evaluating water quality, followed by necessary follow-ups. The primary activities involve installing water treatment units with MMF technology in collaboration with village officials and the community. The treated water is then tested for quality at the IPB University laboratory. Test results indicate that MMF technology significantly improves water quality, reducing parameters such as Magnesium, Manganese, Calcium, Iron, and Phosphate by 25.8‒97.8%, thus meeting quality standards. However, some parameters, such as TSS, COD, and Zinc, still exceed quality standards, necessitating further processing. This advanced water treatment requires involvement from the local government, particularly in funding through community empowerment programs, to install advanced treatment units and provide operational support for these units.

Voxel-wise segmentation for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural networks

AbstractAdditive Manufacturing (AM) has emerged as a manufacturing process that allows the direct production of samples from digital models. To ensure that quality standards are met in all samples of a batch, X-ray computed tomography (X-CT) is often used in combination with automated anomaly detection. For the latter, deep learning (DL) anomaly detection techniques are increasingly used, as they can be trained to be robust to the material being analysed and resilient to poor image quality. Unfortunately, most recent and popular DL models have been developed for 2D image processing, thereby disregarding valuable volumetric information. Additionally, there is a notable absence of comparisons between supervised and unsupervised models for voxel-wise pore segmentation tasks. This study revisits recent supervised (UNet, UNet++, UNet 3+, MSS-UNet, ACC-UNet) and unsupervised (VAE, ceVAE, gmVAE, vqVAE, RV-VAE) DL models for porosity analysis of AM samples from X-CT images and extends them to accept 3D input data with a 3D-patch approach for lower computational requirements, improved efficiency and generalisability. The supervised models were trained using the Focal Tversky loss to address class imbalance that arises from the low porosity in the training datasets. The output of the unsupervised models was post-processed to reduce misclassifications caused by their inability to adequately represent the object surface. The findings were cross-validated in a 5-fold fashion and include: a performance benchmark of the DL models, an evaluation of the post-processing algorithm, an evaluation of the effect of training supervised models with the output of unsupervised models. In a final performance benchmark on a test set with poor image quality, the best performing supervised model was UNet++ with an average precision of 0.751 ± 0.030, while the best unsupervised model was the post-processed ceVAE with 0.830 ± 0.003. Notably, the ceVAE model, with its post-processing technique, exhibited superior capabilities, endorsing unsupervised learning as the preferred approach for the voxel-wise pore segmentation task.

Deep learning models for hepatitis E incidence prediction leveraging Baidu index.

Infectious diseases are major medical and social challenges of the 21st century. Accurately predicting incidence is of great significance for public health organizations to prevent the spread of diseases. Internet search engine data, like Baidu search index, may be useful for analyzing epidemics and improving prediction. We collected data on hepatitis E incidence and cases in Shandong province from January 2009 to December 2022 are extracted. Baidu index is available from January 2009 to December 2022. Employing Pearson correlation analysis, we validated the relationship between the Baidu index and hepatitis E incidence. We utilized various LSTM architectures, including LSTM, stacked LSTM, attention-based LSTM, and attention-based stacked LSTM, to forecast hepatitis E incidence both with and without incorporating the Baidu index. Meanwhile, we introduce KAN to LSTM models for improving nonlinear learning capability. The performance of models are evaluated by three standard quality metrics, including root mean square error(RMSE), mean absolute percentage error(MAPE) and mean absolute error(MAE). Adjusting for the Baidu index altered the correlation between hepatitis E incidence and the Baidu index from -0.1654 to 0.1733. Without Baidu index, we obtained 17.04±0.13%, 17.19±0.57%, in terms of MAPE, by LSTM and attention based stacked LSTM, respectively. With the Baidu index, we obtained 15.36±0.16%, 15.15±0.07%, in term of MAPE, by the same methods. The prediction accuracy increased by 2%. The methods with KAN can improve the performance by 0.3%. More detailed results are shown in results section of this paper. Our experiments reveal a weak correlation and similar trends between the Baidu index and hepatitis E incidence. Baidu index proves to be valuable for predicting hepatitis E incidence. Furthermore, stack layers and KAN can also improve the representational ability of LSTM models.

A Comparison of Medical Education Policies in Japan and Singapore with a Focus on Governance: Implications for Korea

Among Asian nations, Japan, Singapore, and South Korea exemplify countries with high standards of medical quality. This review explores the differences in medical education policies between Japan and Singapore, particularly concerning governance, and discusses the implications for South Korea’s medical education policies. Relevant documents were analyzed by referencing scholarly articles and data from governmental and expert organizations in each country. In Japan, advances in medical education policies include initiatives such as the regional quota system and the core curriculum model, which emphasize stakeholder engagement and transparency. However, challenges persist due to limited stakeholder participation, necessitating a transition toward a more equitable governance paradigm. Singapore’s model features robust public-private partnerships with minimal direct governmental intervention, emphasizing innovation and community integration, as seen in the Healthier SG project. These case studies demonstrate effective governance involving significant stakeholder collaboration and strategic financial investments. Conversely, South Korea’s medical education policies face challenges from a predominantly government-centric approach, with an absence of cohesive governance structures and inadequate involvement from essential professional stakeholders. This situation has led to policy inconsistencies and a deficit of strategic direction, exacerbated by insufficient financial support for educational infrastructure and program development. The experiences of Japan and Singapore indicate that it would be beneficial for South Korea to adopt integrated governance frameworks that prioritize transparency and collaboration. Furthermore, increasing financial investment in medical education could mitigate existing deficiencies and improve the quality and effectiveness of its healthcare education system.