Framework For Supervision Research Articles

Self-adaptive label discovery and multi-view fusion for complementary label learning

Unlike traditional supervised classification, complementary label learning (CLL) operates under a weak supervision framework, where each sample is annotated by excluding several incorrect labels, known as complementary labels (CLs). Despite reducing the labeling burden, CLL always suffers a decline in performance due to the weakened supervised information. To overcome such limitations, in this study, a multi-view fusion and self-adaptive label discovery based CLL method (MVSLDCLL) is proposed. The self-adaptive label discovery strategy leverages graph-based semi-supervised learning to capture the label distribution of each training sample as a convex combination of all its potential labels. The multi-view fusion module is designed to adapt to various views of feature representations. In specific, it minimizes the discrepancies of label projections between pairwise views, aligning with the consensus principle. Additionally, a straightforward mechanism inspired by a teamwork analogy is proposed to incorporate view-discrepancy for each sample. Experimental results demonstrate that MVSLDCLL learns more discriminative label distribution and achieves significantly higher accuracies compared to state-of-the-art CLL methods. Ablation study has also been performed to validate the effectiveness of both the self-adaptive label discovery strategy and the multi-view fusion module.

An evaluation of a quality improvement initiative examining benefits and enablers and challenges and barriers of implementing and embedding core clinical supervision in primary care

Background Core Clinical Supervision has become a valued activity that impacts on the culture and organisational delivery of healthcare. It embeds good practice to ensure that staff have a high skill set, desirable professional attitudes, and provide high quality evidence-based care. It also helps to support good clinical governance and enhances staff retention (CQC 2013). A supervision framework has been adopted and adapted from the ‘General Practice – Developing confidence, capability, and capacity. A Ten Point Action Plan for General Practice Nursing’ ( NHS England 2018 ) and applied at scale across Yorkshire and the Humber, with minimal impact on clinical capacity, quality, and safety. This initiative coincides with general practice (and the wider health service) being under enormous pressure managing the effects of the COVID-19 pandemic, with impact on staff wellbeing and retention. The main aims are to evaluate the impact of embedding the Core Supervision training across primary care practice and strengthen course content for future delivery. Methodology and Methods A quantitative approach using an online survey, was completed by multi-professional primary care staff who had completed the Core Supervision Training. Findings Practitioners indicated that they required protected time due to competing demands and visible senior buy in to undertake core supervision. Additionally, practitioners who had participated or supervised sessions felt the benefits on staff wellbeing and indicated that it improved patient care delivery. Conclusion and Implications Survey findings suggest further research on embedding core supervision within primary care and a focus on national and local strategies are required. Standardised learning outcomes across the regions to ensure transferability of supervision practice and review training in supervision processes, particularly around conducting a supervision session.

Introduction to Trauma-Informed Counselor Education and Supervision (TICES) Framework

Many counselors in training may be susceptible to traumatization and/or retraumatization during their training process due to the elevated prevalence of their past trauma experience and the nature of their professional work involving exposure to trauma narratives in coursework and during fieldwork. Recognizing the growing need for a trauma-informed approach in training future helping professionals, including counselors-in-training, we present an overview of a framework called the Trauma-Informed Counselor Education and Supervision (TI-CES). This framework draws on assumptions and principles from trauma-informed care (TIC). Also, we address the applications of four key assumptions (i.e., Realize, Recognize, Respond, and Resist retraumatization) and six principles (i.e., Safety; Trustworthiness and transparency; Peer support; Collaboration and mutuality; Empowerment, voice, and choice; and Cultural, historical, and gender issues) of the TIC. These assumptions and principles are specifically tailored to address the unique challenges and needs of counselor education and supervision. In addition, we offer stepwise key recommendations to prevent (re) traumatization and mitigate the impacts of trauma exposure at three critical levels: throughout the program admission, during the program, and after exposure to traumatic components of training. By following the recommendations, counselor educators and supervisors can create a supportive and safe environment that fosters the well-being of counselors-in-training while equipping them to respond effectively to potentially traumatizing components in their training.

Developing a robust architecture framework for effective supervision and management of cloud environments

Developing a robust architecture framework for effective supervision and management of cloud environments

Global explanation supervision for Graph Neural Networks.

With the increasing popularity of Graph Neural Networks (GNNs) for predictive tasks on graph structured data, research on their explainability is becoming more critical and achieving significant progress. Although many methods are proposed to explain the predictions of GNNs, their focus is mainly on "how to generate explanations." However, other important research questions like "whether the GNN explanations are inaccurate," "what if the explanations are inaccurate," and "how to adjust the model to generate more accurate explanations" have gained little attention. Our previous GNN Explanation Supervision (GNES) framework demonstrated effectiveness on improving the reasonability of the local explanation while still keep or even improve the backbone GNNs model performance. In many applications instead of per sample explanations, we need to find global explanations which are reasonable and faithful to the domain data. Simply learning to explain GNNs locally is not an optimal solution to a global understanding of the model. To improve the explainability power of the GNES framework, we propose the Global GNN Explanation Supervision (GGNES) technique which uses a basic trained GNN and a global extension of the loss function used in the GNES framework. This GNN creates local explanations which are fed to a Global Logic-based GNN Explainer, an existing technique that can learn the global Explanation in terms of a logic formula. These two frameworks are then trained iteratively to generate reasonable global explanations. Extensive experiments demonstrate the effectiveness of the proposed model on improving the global explanations while keeping the performance similar or even increase the model prediction power.

Academic visualization study of aesthetic medicine management and related legal research since 2000.

Aesthetics medicine, a controversial branch of clinical medicine known for its high degree of commercialization, faces numerous conflicts, particularly in some developing countries. The global aesthetics medicine industry requires enhancements of its legal and supervision framework and risk management systems. This paper aimed to provide a comprehensive visual analysis of academic achievements related to regulatory and legal issues in the field of aesthetic medicine and to identify its development trends and research hotspots. The Web of Science Core Collection was employed to retrieve relevant studies, resulting in a total of 602 research articles after selection. Utilizing bibliometric methods and CiteSpace, this study analyzed the primary countries, institutions, authors, journals, hotspots, frontiers, and trends in this domain. The findings indicated rapid increases in the number of published papers. The United States emerged as the leading contributor with 131 research papers and the highest intermediate centrality. Eleven keyword clusters were identified, with "adolescence" and "office-based surgery" being the most recent topics. We also analyzed the trends and frontiers of legal research in medical aesthetics. The importance of informed consent has been increasingly emphasized, and research in the field of medical aesthetics has been gradually expanding beyond individual cosmetic procedures. The management system has become more comprehensive, moreover, guidelines and medical laws have been continually published, with research shifting toward a holistic perspective that encompasses patients, medical aesthetic providers, and regulatory authorities in the study of medical aesthetics regulation and legislation. This paper also proposes some innovative directions for future research and applications.

Weakly Supervised Detection of Baby Cry

Detection of baby cry is an important part of baby monitoring. Almost all existing methods use supervised SVM, CNN, or their varieties. In this work, we propose to use weakly supervised anomaly detection to detect baby cry. In this weak supervision framework, we only need weak annotation if there is a cry in an audiofile. We design a data mining technique using the pre-trained VGGish feature extractor and an anomaly detection network on long untrimmed audiofiles. The obtained datasets are used to train a delicately designed super lightweight CNN for cry/non-cry classification. This CNN is then used as a feature extractor in an anomaly detection framework to achieve better cry detection performance.

Basel core principles for effective banking supervision: an update after a decade of experience

The Basel Committee on Banking Supervision’s Core Principles for Effective Banking Supervision (BCPs) are a universally applicable minimum standard for sound prudential regulation and supervision of banks and banking systems. Supervisors use these principles to assess the quality of their regulatory and supervisory frameworks, while the International Monetary Fund (IMF) and the World Bank use them, as part of their Financial Sector Assessment Programme, to assess the efficacy of the banking supervision framework and supervisory approach in each jurisdiction. Since they were first introduced in 1997, the BCPs have undergone two revisions (in 2006 and 2012). In April 2024 the Basel Committee on Banking Supervision published a modification of the standard to account for developments over the last decade, the impact of structural trends in the sector and the lessons learned from previous implementations of the core principles. This article takes a look at the key aspects of this update, the main changes of which refer to new risks, such as climate-related financial risks and the digitalisation of finance, operational resilience, non-banking financial intermediation, financial risk, risk management practices, and systemic risk and macroprudential oversight.

Yoga in Schools: Self-Care for Administrators and Teachers

Since early 20th century, yoga is applied as a therapeutic intervention to provide various psychophysiological benefits. It has been positioned as an effective tool to combat compassion fatigue of professionals. School based yoga is usually integrated in Physical Education curriculum or department. Yoga’s development in China has become the prevalent fitness choice founded by imported knowledge and traditional interpretation of body technique. School administrators can equally have emotional concerns, similar internal struggles and external conflicts with others but minimal literature on self-care is studied about them. The purpose of this study was to assess the yoga in schools and examine the self-care of administrators and supervisors. This study was anchored on Mindful-Based Supervision Framework by Haberlin (2020) which involves Mindful walking, Deep listening, Mindful notetaking, and Meditation. The latter was the focus of the study that uses yoga to achieve self-care among school administrators in China. The study involved mostly male respondents between 31-36 years old with permanent employment as teachers who served as administrators or supervisors for one year. Using quantitative descriptive correlational design, respondents agreed in all attributes in yoga in school such as objectives, content, and impact and occasionally practiced all attributes of self-care in terms of physical, psychological, emotional, spiritual, and balanced self-care practices. To strengthen and intensify the yoga program for teachers and school administrators, self-care strategies were recommended to be integrated as the output of the study.

A Localized Instructional Supervision Framework for the Junior High Schools of Cervantes National High School

A Localized Instructional Supervision Framework for the Junior High Schools of Cervantes National High School

General Practitioners' Experience of Remote Consultations by Telephone in the General Practice Setting during the COVID-19 Pandemic.

The coronavirus disease 2019 (COVID 19) pandemic brought substantial changes in the way doctors used to interact with patients. In the general practice, consultation over the phone has become a norm now. However, it is not well known how this new mode of consultation affected clinicians' practices. Objective of this study was to find out if doctors working in the general practices were trained enough for telephonic consultation and how this new mode of consultation affected their clinical practice in general. It was an online survey. Information was gathered by using an online questionnaire which was sent electronically to general practitioners (GPs) and general practitioner speciality trainees (GPSTs) working in the general practices based in Leicestershire. Data were analyzed by using software SPSS. Descriptive characteristics of participants were reported in terms of numbers and percentages, whereas Chi square test was run to assess if there is a difference between GPs and GPSTs in terms of their experience of remote consultations by telephone. The questionnaire response rate was 69.3% (n = 133/192). Of the total, 54.1% (n = 72/133) of participants were women. About 36% (n = 48/133) of the participants were GPSTs, whereas 64% (n = 85/133) were qualified GPs. Not having enough training for phone consultation, technical issues during consultation, inadequate supervision framework, difficulties in building therapeutic alliance with patients, making diagnosis and risk assessment, and increased duration of consultation were identified as issues. Similarly, concerns around patients' confidentiality and medico legal issues were highlighted. GPs and GPSTs reported similar difficulties. In conclusion, lack of training for the telephonic consultation has been identified as a unanimous issue along with other challenges to phone consultations. There is an urgent need to take measures to make telephone consultation more successful, enjoyable, and safe for patient care by addressing identified issues. Larger studies with representative samples are needed to increase generalizability of our findings.

Evaluating and enhancing natural resource asset management efficiency in China: A data envelopment analysis study

The efficiency of China's natural resource asset management system significantly influences the sustainable utilization of resources and the promotion of an environmentally sustainable economy. In this research, we employ a Data Envelopment Analysis (DEA) model to assess and analyze the efficiency and dynamic changes within China's natural resource asset management system. Our analysis is based on panel data collected from 30 provinces spanning the years 2007–2019. Our findings reveal that only three provinces demonstrated DEA effectiveness in managing natural resource assets, highlighting substantial regional disparities in efficiency. The presence of multiple institutions operating independently has led to a situation of overlapping responsibilities, resulting in critical issues related to redundant management. Inadequate resource tax collection intensity and a low tax utilization rate have contributed to the insufficiency in resource tax utilization. Local industrial structures and government priorities have hindered the active involvement of industrial enterprises in natural resource asset management in certain regions. We categorize changes in the efficiency of system operations in non-DEA-effective regions into three types: a temporary increase followed by a continuous decline, a gradual increase with overall low efficiency, and a rapid increase with relatively high overall efficiency. Consequently, this study offers policy recommendations aimed at enhancing the efficiency of natural resource asset management: (1) Clarify the ownership of natural resource assets and establish a well-defined hierarchical proxy system along with an integrated supervision framework. (2) Allocate resource tax revenue reasonably and promote collaborative coordination between resource taxes and other policy measures. (3) Strengthen the government's commitment to natural resource asset management, draw insights from advanced regions' experiences, and tailor policy approaches to the specific conditions of different regions to effectively balance economic development and environmental protection.

Language Models in the Loop: Incorporating Prompting into Weak Supervision

We propose a new strategy for applying large pre-trained language models to novel tasks when labeled training data is limited. Rather than apply the model in a typical zero-shot or few-shot fashion, we treat the model as the basis for labeling functions in a weak supervision framework. To create a classifier, we first prompt the model to answer multiple distinct queries about an example and define how the possible responses should be mapped to votes for labels and abstentions. We then denoise these noisy label sources using the Snorkel system and train an end classifier with the resulting training data. Our experimental evaluation shows that prompting large language models within a weak supervision framework can provide significant gains in accuracy. On the WRENCH weak supervision benchmark, this approach can significantly improve over zero-shot performance, an average 19.5% reduction in errors. We also find that this approach produces classifiers with comparable or superior accuracy to those trained from hand-engineered rules.

Optimising postgraduate supervision using multilevel modeling techniques in a constrained higher education environment

The paper developed a multilevel model (MLM) of postgraduate (PG) supervision to improve the academic publication and PG completion rate. Crowdsourcing essentials were used in the development of the model. The crowds consisted of the MLM made of students from Honours to doctoral levels. Teamwork was also implored, where the teams were level mates and supervisory teams. The simplest form of the model has the potential to generate over 65 academic manuscripts for journals. Monitoring of the supervision process can provide maximized completion of the PG research studies. Research capacity building would be effected for the doctoral and master’s students making them able to supervise and co-supervise from Honours to doctoral levels upon completion of their studies. The study condemned the use of a single supervisor for several doctoral students. It recommended the implementation of the model (the MLM PG Supervision Framework). It further recommended that doctoral students should be assigned co-supervisors, preferably varied for different students, to enable diversity in the supervision experience.

Khuôn khổ giám sát rủi ro tài chính liên quan đến biến đổi khí hậu của Ngân hàng Nhà nước Việt Nam

Climate change is happening rapidly and poses a significant risk to the global economy. International organizations have issued many regulations to manage and supervise climate-related financial risk (CRFR) to ensure the financial system’s safety. This paper uses the content analysis method to evaluate the CRFR monitoring framework of the State Bank of Vietnam compared with the Basel Committee on Banking Supervision. The results show that the CRFR supervision framework in Vietnam is still under development; the regulations and guidelines are not specific and not yet in line with the international framework, such as not clearly defining the responsibilities of senior management in CRFR monitoring, not providing guidance on the implementation, evaluation, and monitoring of the results of scenario analysis and stress testing on the resilience of banks to climate change, not clearly announcing the monitoring objectives and improving the quality of supervisors, and not requiring financial institutions to disclose information related to CRFR.

Analisis Kinerja Keuangan pada PT. Bank Sinarmas Tbk yang Terdaftar pada Bursa Efek Indonesia Tahun 2019 – 2023

The strategic role of banking as an intermediary institution manifests through its ability to gather and channel funds from the public to support economic activities, ultimately enhancing the stability of the country's economic structure. The importance of banking health in the fund collection process requires a sound condition and banking services that attract public interest. Bank health evaluation can be conducted through various methods, including the CAMEL method covering capital, asset quality, management, earnings, and liquidity, as well as the RGEC method encompassing Risk Profile, Good Corporate Governance, Earnings, and Capital. Bank Sinarmas, as one of the public banks in Indonesia, has played a significant role in economic recovery through the distribution of People's Business Credit (KUR) and its success in maintaining the health of the banking sector. This research is descriptive with a quantitative approach, utilizing literature review and documentation as data collection techniques. The results of this study indicate that the financial condition of PT Bank Sinarmas Tbk from 2019 to 2023 can be classified as generally “healthy”. However, in terms of Asset Quality and Management aspects, it falls into the "Fairly Healthy" category, while in terms of Profitability, specifically the Return on Asset (ROA) ratio, it is categorized as "Less Healthy." The findings are expected to serve as a guide for the company, assisting in maintaining a healthy financial state and improving areas that are less healthy to uphold public trust. The research contributes to academic literature, serving as a significant reference for the development of financial management knowledge, particularly in the analysis of financial statements. It is also envisioned as a foundation for further research with similar focuses. As guidance for future researchers, it is recommended to broaden the scope of research by involving other financial ratio indicators, following the latest methods in accordance with the regulatory framework of financial institution supervision in Indonesia.

A template augmented distant supervision framework for Chinese named entity recognition

Distant supervision has been proven to be an efficient way of generating labeled instances for Named Entity Recognition (NER). However, it suffers from dictionary biases and ambiguous entities, resulting in noisy and incomplete labels. To overcome this drawback, this paper proposes a template augmented distant supervision framework, which generates high-quality labeled training data with minimal human effort. Specifically, we use distant supervision to extract sentences that contain entities and apply a pre-trained language model to encode these sentences. The encoded sentences are clustered and then for each cluster, three sentences are sampled out to form a seed template pool. The seed templates are calibrated and decomposed to decouple the connection between different parts. Finally, the seed templates and entity dictionary are combined with pre-trained language model to generate semantically coherent and precisely labeled training data. Experimental results on the EC and NEWS datasets and a practical electronic after-sale Q&A dataset with multiple pre-trained language models demonstrate that the proposed framework is able to improve the F1 score of the distantly supervised NER models by 7.9%–12.9%.

One-Bit Supervision for Image Classification: Problem, Solution, and Beyond

This article presents one-bit supervision, a novel setting of learning with fewer labels, for image classification. Instead of the training model using the accurate label of each sample, our setting requires the model to interact with the system by predicting the class label of each sample and learn from the answer whether the guess is correct, which provides one bit (yes or no) of information. An intriguing property of the setting is that the burden of annotation largely is alleviated in comparison to offering the accurate label. There are two keys to one-bit supervision: (i) improving the guess accuracy and (ii) making good use of the incorrect guesses. To achieve these goals, we propose a multi-stage training paradigm and incorporate negative label suppression into an off-the-shelf semi-supervised learning algorithm. Theoretical analysis shows that one-bit annotation is more efficient than full-bit annotation in most cases and gives the conditions of combining our approach with active learning. Inspired by this, we further integrate the one-bit supervision framework into the self-supervised learning algorithm, which yields an even more efficient training schedule. Different from training from scratch, when self-supervised learning is used for initialization, both hard example mining and class balance are verified to be effective in boosting the learning performance. However, these two frameworks still need full-bit labels in the initial stage. To cast off this burden, we utilize unsupervised domain adaptation to train the initial model and conduct pure one-bit annotations on the target dataset. In multiple benchmarks, the learning efficiency of the proposed approach surpasses that using full-bit, semi-supervised supervision.

Need for a New Framework for Supervision of Counsellors in the Indian Context: A Review

Need for a New Framework for Supervision of Counsellors in the Indian Context: A Review

PROCEDURAL ASPECTS OF ACCEPTING FUNDS AS A NOTARY’S DEPOSIT IN THE PERFORMANCE OF THE DEBTOR’S OBLIGATIONS BY THIRD PARTIES IN A BANKRUPTCY CASE

This article attempts to identify procedural features when accepting funds as a notary’s deposit in the performance of the debtor’s obligations by third parties in a bankruptcy case. The author concludes that the procedure under consideration is applicable not only in the course of external management, but also in the framework of supervision and bankruptcy proceedings. The paper discusses the stages in the performance of a notarial action to accept a notary as a deposit when third parties fulfill the debtor’s obligations in a bankruptcy case, and also highlights the characteristic features of special legal regulation.