Effective Supervision Research Articles

DPCTN: Dual path context-aware transformer network for medical image segmentation

Accurate segmentation of lesions in medical images is a key step to assist clinicians in diagnosis and analysis. Most studies combine the Transformer model with CNN at a single scale or use the highest-level feature tensor extracted by CNN as input to Transformer without fully exploiting Transformer’s potential. In addition, for the problems of structural boundary blurring, heterogeneous textures, etc., in medical images, most existing methods pay attention to using contour information to solve this problem but simply fuse the contour information and ignore the potential relationship between the regions and the contours. We propose the DPCTN network based on the traditional encoding–decoding structure, consisting of the CNN, Transformer dual backbone networks and parallel attention mechanisms, to achieve accurate segmentation in medical image lesions. Local and global multiscale feature information is extracted by CNN and Transformer. The Transformer block of channel cross fusion can implement multiscale information fusion of the high-level local features and reduce the impact of the redundant information. The dual backbone feature fusion module effectively couples the local and global high-level feature information. The decoder refines and enriches the boundary and regional features, layer by layer, to achieve effective supervision of the boundary and region. Considering the possible dimension collapse in the attention mechanism, a novel three branch transposed self-attention module is designed to reduce the information loss caused by feature pooling. To verify the effectiveness of our proposed method, subjective and objective comparative experiments and ablation experiments were performed on four medical segmentation tasks, polyps, skin lesions, glands and breast tumors. A large number of experimental results show that our method is superior to the current state-of-the-art method, reduces the standard deviation and is more robust. Source code is released at https://github.com/sd-spf/DPCTN.

Improving Teacher Competence in Supporting the Achievement of Basic Education Goals

Improving teacher competence plays a crucial role in achieving optimal goals in basic education. This article aims to discuss the importance of enhancing teacher competence in supporting the achievement of basic education goals. The study adopts a qualitative approach, utilizing interviews with six teachers and a literature review consisting of articles. The research procedure involves data collection through in-depth interviews with teachers and literature analysis to identify factors influencing teacher competence. The findings indicate that a deep understanding of the subject matter, the use of innovative teaching methods, effective classroom management skills, and professional development for teachers are essential factors in improving teacher competence. Furthermore, suggested strategies and initiatives include professional development programs, collaboration among teachers, effective supervision and mentoring, optimizing the use of supportive resources, and developing comprehensive assessment systems. It is emphasized that serious attention from the government and educational institutions is crucial in enhancing teacher competence to improve the quality of basic education and provide a better future for the next generation.

Exploration of performance appraisal Strategy based on Big data and enterprise Development investigate

In recent years, the reform of the power system structure has gone deeper and deeper, and the national reform goals of "legal basis, separation of government and enterprise, subject regulation, fair trade, reasonable price and effective supervision" are also being implemented step by step. In the process of the rapid development of the system architecture of electric power enterprises, many private enterprises have also joined in the complicated market competition. The challenge of power grid status also means that it is necessary to carry out internal exploration to effectively meet the market competition.
 As a kind of evaluation system used in enterprises, performance appraisal has many different levels of significance. Performance appraisal should be able to provide the basic strength for the vigorous development of the enterprise, create a fair, open and vibrant competitive environment, and provide guidance for the learning, work and development of employees. In the traditional practice of performance appraisal in the past, the appraisal system is often regarded as a relatively independent design unit, which is generally decoued from many background elements in the enterprise, such as the strategic objectives of the enterprise, the internal culture of the enterprise, the individual learning and development direction of the employee, and the attitude and guidance of the enterprise manager. However, under the background of current market reform, the important relationship between these factors and performance appraisal is being recognized more and more. In this context, this paper tries to explore the key points of performance appraisal strategies with big data technology as the main axis and enterprise development goals as the guidance.

Analisis Pendidikan Bermutu Melalui Tugas dan Kompetensi Supervisor

This abstract aims to discuss the importance of supervision in achieving quality education and fostering competent teachers. Education plays a vital role in developing a superior generation with character, aligned with the national philosophy of Pancasila, and contributing to society, the nation, and the state. In the current era of globalization, where competitiveness is crucial, quality education becomes essential. Supervision activities conducted by supervisors significantly contribute to the progress of education. Through effective supervision and guidance, teachers can enhance their skills and ultimately improve students' learning outcomes. Both principals and supervisors should possess the necessary understanding of their roles and responsibilities in order to produce qualified teachers. Several competencies are required to fulfill these tasks successfully. This study emphasizes the significance of supervision in shaping the educational landscape and the role of competent supervisors in fostering quality education.

Circumstances, policing, and attrition of multiple compared to single perpetrator rape cases within the South African criminal justice system

BackgroundResearch into the circumstances of rape, and criminal justice system responses, is pivotal to informing prevention and improving the likelihood of justice for victims. In this paper, we explore the differences in the circumstances of multiple-perpetrator rapes (MPRs) and single-perpetrator rapes (SPRs), their case management, and attrition, and describe areas for improvemensuplt around rape response within the South African criminal justice system.MethodsThe sample comprised 3952 rape cases reported to the South African Police Services (SAPS) in 2012, selected through a multi-stage random sampling of 172 police stations from a total of 1164 police stations in the nine provinces, followed by the random selection of cases from each station’s case list. Data were abstracted from police dockets, medico-legal examination forms, charge sheets, and trial transcripts. MPRs were defined as cases in which more than one perpetrator had sexual contact with the victim during a single incident, i.e., sexually assaulted or raped. Descriptive statistics and Chi-square tests for associations were used to compare MPRs and SPRs in circumstances of the rape, case management, and attrition.ResultsSeventeen percent of cases were MPRs. MPRs were comparably more violent crimes with a higher frequency of aggressive tactics employed by perpetrators, for example, abductions, firearms use, and threats to kill. Overall, cases were often poorly handled by police, and there were deviations from standard policing and investigation procedures; we found more evidence of this with MPRs compared to SPRs. MPR cases were most likely to have been closed by police due to undetected perpetrators in combination with other victim reasons. The weaker investigations of MPRs were associated with higher attrition rates compared to SPRs, firstly at the police investigation and subsequent stages.ConclusionsThe findings confirm differences in case management, patterns of attrition and trajectories of MPRs compared to SPRs. In an overall context of high rape case attrition and impunity for perpetrators, MPR victims are even less likely to see justice served than SPR victims. There needs to be much more effective supervision of rape case investigations by SAPS, particularly in MPR cases. Continual investigator training strengthened supervision and better resourcing are necessary to improve MPRs detection and convictions in adherence to the Directives for rape policing.

Unified building change detection pre-training method with masked semantic annotations

Building change detection (CD) using remote sensing images plays a vital role in urban development, and deep learning models attracted attention for their potential to accomplish CD tasks automatically. However, most methods are still facing challenges, such as the costly and time-consuming process of constructing CD datasets and the severely imbalanced distribution of positive and negative samples preventing loss functions from functioning as desired in the training process. Inspired by weak supervision have demonstrated excellent performance in solving the above-mentioned problems, a unified change detection pre-training paradigm is proposed to accomplish the CD task using a small number of samples and improve the inference accuracy of building change detection. The keys of this proposed method are as follows. First, the pre-training paradigm detects building changes using pseudo-labels and them generated by highly available semantic segmentation datasets. Second, a balanced sample distribution is ensured by using the proposed method for semantic masked building areas and controlling the proportion of the areas. Third, multi-task networks for simultaneous building extraction and change detection are used in the proposed unified paradigm, owing to the semantic information can be employed as an effective supervision signal to assist with the CD training to solve the problem that pseudo-labels adversely affect the ability of the algorithm to converge. In particular, experiments were performed on three challenging datasets. For aerial WHU-CD and satellite Gaofen Challenge-CD datasets, our pre-trained weights generated with pseudo-bitemporal samples were applied to subsets containing different proportions of ground truth for fine-tuning, respectively. Notably, 10% of ground truth for fine-tuning with our pre-trained weights obtained intersection over union (IoU) comparable to that obtained using 100% of the CD ground truth without our pre-trained weights, whereas an even greater IoU was achieved using 30% of ground truth with our pre-trained weights. Experiments demonstrated that the performance of our method based on a small number of samples was superior to that of conventional supervised learning methods. When conducting experiments with 100% ground truth, the results showed that the use of our pre-trained weights yields IoU that substantially exceeds that of conventional supervised learning methods. The results of experiments conducted on the LEVIR-CD dataset proved the excellent transferable performance of our method. The proposed method can greatly reduce the need for high-quality CD labels and alleviate bottlenecks caused by an imbalanced distribution. Moreover, our method can improve CD accuracy and has excellent generalization capabilities.

Compliance with the Basel Core Principles and supervisory structure: A cross-country analysis

This paper is motivated by the implementation of the new banking supervision structure in the European Union (EU) and the possible conflict of interest between monetary policy and the supervision authority within the European Central Bank (ECB). The empirical analysis considers the relationship between the structure of banking supervision and the compliance with the Basel Core Principles (BCP) for effective supervision. A sample of 21 countries and the Euro Area (EA) is used. In addition to the structure of bank supervision, a list of independent variables is considered to explain the dependent variable. The results suggest that the supervisory structure has no statistical significance at any notable significance level on compliance with the BCP. On the contrary, financial freedom is a statistically significant variable.

Registered Behavior Technicians' Training Experiences for Severe Problem Behavior: A Survey.

Registered Behavior Technicians (RBTs) are the primary paraprofessionals who deliver applied behavior analysis (ABA) services to individuals with autism spectrum disorder (ASD) under supervision of a Board Certified Behavior Analyst (BCBA). Effective training and supervision for RBTs providing ABA services is critical, especially for technicians working with children who exhibit severe behaviors. Recent research has assessed the needs of BCBAs working with individuals who exhibit severe problem behavior (Colombo et al., 2021). However, no research exists to identify the needs and ongoing training offered to the RBTs who provide ABA services to clients who exhibit severe problem behavior. Thus, the purpose of the current study was to survey RBTs for their initial training experiences and ongoing supports offered when working with clients who exhibit severe problem behavior. Results indicated that some RBTs reported appropriate initial and ongoing training, however, 13% reported receiving no initial training and 29% reported receiving no ongoing training when working with clients who engaged in severe problem behavior. In addition, 75% of RBTs reported sustaining an injury themselves and 36% reported their client sustained some type of injury. Suggestions for improvement for training RBTs working with this population and directions for future research are discussed.

Hybrid Domain Consistency Constraints-Based Deep Neural Network for Facial Expression Recognition.

Facial expression recognition (FER) has received increasing attention. However, multiple factors (e.g., uneven illumination, facial deflection, occlusion, and subjectivity of annotations in image datasets) probably reduce the performance of traditional FER methods. Thus, we propose a novel Hybrid Domain Consistency Network (HDCNet) based on a feature constraint method that combines both spatial domain consistency and channel domain consistency. Specifically, first, the proposed HDCNet mines the potential attention consistency feature expression (different from manual features, e.g., HOG and SIFT) as effective supervision information by comparing the original sample image with the augmented facial expression image. Second, HDCNet extracts facial expression-related features in the spatial and channel domains, and then it constrains the consistent expression of features through the mixed domain consistency loss function. In addition, the loss function based on the attention-consistency constraints does not require additional labels. Third, the network weights are learned to optimize the classification network through the loss function of the mixed domain consistency constraints. Finally, experiments conducted on the public RAF-DB and AffectNet benchmark datasets verify that the proposed HDCNet improved classification accuracy by 0.3-3.84% compared to the existing methods.

Tax enforcement and corporate financial irregularities: Evidence from China

This paper examines whether and how tax enforcement affects corporate financial irregularities in China, utilizing the merger of the State Tax Bureau (STB) and Local Tax Bureaus (LTB) in 2018 as a quasi-natural experiment. Our findings show that stricter tax enforcement significantly reduces corporate financial irregularities, especially for firms with lower tax compliance, poorer internal governance, laxer external supervision, and lower economic status. Furthermore, the mechanism tests demonstrate that stricter tax enforcement forces firms to reduce tax avoidance and tax reporting irregularities. These findings are consistent with the effective supervision channel. Our findings suggest that stricter tax enforcement can improve the quality of corporate information disclosure, and providing useful insights for alleviating information asymmetry and improving information environment in the Chinese capital market.

Burnout among behavior analysts in times of crisis: The roles of work demands, professional social support, and psychological flexibility

BackgroundThe purpose of this study was to apply the Job-Demands Resources model as a framework to examine the relationship between work demands and burnout among behavior analysts working in human service settings during the Covid-19 pandemic. We specifically investigated the work demands-burnout relationship and how psychological flexibility, supervisor support, and coworker support related to burnout, whether as moderators or as mediators of work demands. MethodA sample of 298 ABA practitioners participated in a cross-sectional investigation in April-May 2021 and reported sociodemographic and job-related characteristics, information about the impact of Covid-19 on work, work demands, psychological flexibility, supervisor support, and coworker support. We conducted regression-based analyses of moderation and multiple mediation. ResultsGreater work demands predicted higher levels of exhaustion and disengagement. Psychological flexibility and supervisor support partially mediated the influence of work demands on exhaustion and burnout; neither moderated the influence of work demands on exhaustion or burnout. Coworker support did not function as a moderator or mediator in the work demands-burnout relationship. ConclusionsFindings highlight the need for effective caseload management and supervision practices, along with initiatives that create opportunities for increased, positive interaction with supervisors and among colleagues. Providing psychological flexibility skills training may benefit behavior analysts as a burnout management strategy. As a personal resource, however, it may be insufficient to mitigate burnout in times of crisis when work demands are higher than usual. Organizations should consider multi-faceted burnout interventions that address personal and workplace factors to both increase personal/job resources and reduce job demands.

APPLYING THE PYRAMID OF SUPERVISION TO CONCEPTS OF RELATIONALLY-FOCUSED INTEGRATIVE PSYCHOTHERAPY

The Supervision Pyramid provides an effective supervision tool that attends to the supervisee, the client, and the supervisor. It is divided into four levels: identifying the problem; exploring and elaborating on what is learned; experimentation and consolidation; and solving the problem with the goal of the supervisee’s increased capacity to identify solutions and to embrace professional challenges. This article proposes that the core factors of psychotherapy supervision are accomplished through the incorporation of Erskine’s “Keyhole Model”, which spotlights the significance of eight relational needs; the importance of the psychotherapist’s inquiry, attunement, and involvement; the effective use of acknowledgement, validation, normalization and presence; as well as a necessary sensitivity to the client’s nascent affects, rhythm, style of cognition, and level of development.

CROSS-CULTURAL SUPERVISION: CLINICAL SUPERVISORS’ PERCEPTION OF WORKING WITH INTERNATIONAL STUDENTS

Supervision theories or models have traditionally not been centered on cross-cultural supervision (e.g., American clinical supervisors working with international trainees). To this end, this qualitative study sought to explore cross-cultural supervision from the perspective of clinical supervisors. A total number of 10 supervisors participated in the current study. Three themes emerged from the supervisors’ data: (1) systemic issues, acculturation, and power differential; (2) reciprocal learning and supervisory relationship; and (3) effective supervision strategies. Findings may help advance clinical supervision with international students, enable mental health professionals and training programs better understand the cross-cultural supervision process with international trainees

Promoting Effective Doctoral Supervision through Relational Pedagogy: The Supervisor as Shepherd and Counsellor in Doctoral Education

This paper examines relational pedagogy as an effective approach to promoting success in doctoral supervision. The author reflects on his relationship with his thesis supervisor and advocates for teachers and supervisors to consider ways in which relational pedagogy may become a key element and approach in doctoral supervision and education. It reveals how his doctoral supervisor cultivated a trusted shepherd-counsellor relationship that led to the expected outcomes. The study proposes that promoting shepherding and counselling roles in doctoral supervision is a supportive way to foster such rapport for successful candidature. The paper positions dialogue as a vital element of relational pedagogy. It sees the need for supervisors and higher educational institutions to adopt shepherding-counselling roles to provide students with the right assistance to become successful in their doctoral journey. Keywords: Doctoral Supervisor, Doctoral Education, Relational Pedagogy, Doctoral Candidate, Shepherding and Counselling

Implementation of Newborn Hearing Screening in Albania.

Newborn hearing screening (NHS) was implemented in Albania in four maternity hospitals in 2018 and 2019. Implementation outcome, screening outcome, and screening quality measures were evaluated. Infants were first screened by midwives and nurses before discharge from the maternity hospital and returned for follow-up screening. Acceptability, appropriateness, feasibility, adoption, fidelity, coverage, attendance, and stepwise and final-referral rates were assessed by onsite observations, interviews, questionnaires, and a screening database. A post hoc analysis was performed to identify reasons for loss to follow up (LTFU) in a multivariate logistic regression. In total, 22,818 infants were born, of which 96.6% were screened. For the second screening step, 33.6% of infants were LTFU, 40.4% for the third, and 35.8% for diagnostic assessment. Twenty-two (0.1%) were diagnosed with hearing loss of ≥40 dB, six unilateral. NHS was appropriate and feasible: most infants are born in maternity hospitals, hence nurses and midwives could perform screening, and screening rooms and logistic support were supplied. Adoption among screeners was good. Referral rates decreased steadily, reflecting increasing skill. Occasionally, screening was repeated during a screening step, contrary to the protocol. NHS in Albania was implemented successfully, though LTFU was high. It is important to have effective data tracking and supervision throughout the screening.

CAPITAL STRUCTURE AND FIRM FINANCIAL PERFORMANCE OF LISTED DEPOSIT MONEY BANKS IN NIGERIA: MODERATING EFFECT OF BOARD FINANCIAL LITERACY

The purpose of this work is to examine the interaction of members of the board with financial knowledge on the association among capital structure with firm financial performance in the Nigeria DMBs. Empirical studies were reviewed to scrutinize the upshot of capital structure in connection to the performance of firms. As the result of the foregoing, this study introduces board financial literacy as a moderator variable to interact between capital structure with performance of firms. A correlational design was adopted. Population and sample size of the study consists of 13 listed DMBs on the floor of Nigeria Stock Exchange for the period 2012 to 2021. Fixed effects regression model was employed to analyse the data of the study. Diagnostic test was conducted to confirm the validity of the statistical inferences of the study. The result shows that BFL moderated the correlation involving DEFR with financial performance. Also, the result found that EFR and DEFR were not significant to the firm financial performance of DMBs in Nigeria. This work recommends that board members with financial literacy should come up with effective policy towards encouraging debt financing in their entities by effective supervision so as to enhance the overall firms’ financial performance as well as safeguarding shareholders interest. Research in future should replicate this topic in a domain other than DMBs.

Machine Learning for Early Mental Health Support and Offenders Correction

The effective rehabilitation and supervision of law offenders are vital to promoting community safety and enabling individuals to reintegrate into society. Community supervision presents several challenges for agencies like the Adult Parole Authority (APA), which must oversee individuals released from prisons under various forms of supervision, including courtesy supervision for different counties and interstate compact cases. With such a large number of individuals under supervision, the APA struggles to provide adequate oversight and support to guide individuals towards positive behavioral changes and reduce the risk of recidivism. To address these challenges, this paper proposes a machine learning-based system designed to monitor and support individuals under community supervision. The model would track various indicators to identify individuals at risk of self-harm or harming others and enable the APA to provide timely and appropriate support to these individuals. Improving the monitoring and support offered during the rehabilitation and supervision period would enhance the effectiveness of community supervision and contribute to safer and more stable communities.

Challenges in capstone project supervision by academic faculty: A case study

Supervision of capstone projects in engineering programs is an interdisciplinary challenge, for both students and Faculty. The project considered the highlight of the undergraduate program, summarizes all the knowledge students have accumulated throughout their studies and aims to train them for the challenges of graduate engineers. Although the project is usually perceived as leading to successful products and learning outcomes, pedagogical disparities are emerging, emphasizing a deep need for change. This study examines the essence of capstone supervision in Mechanical Engineering, the faculty’s role within it, and stakeholders’ perception, using questionnaires, semi-structured interviews, participant observation, and analysis of primary sources. The study reveals that in contrast to the significance of supervision found to stakeholders, Faculty are under considerable pressure and perceive the significance of supervision as low, and as a time-consuming task, without proper compensation. The current processes show significant pedagogical disparities and limitations, resulting in low interest from academic supervisors. In addition, the academic institution was found to have dissatisfaction with the faculty’s supervision, even though there are no clear definitions or guiding methods for the supervisors. Accordingly, academic institutions must create greater motivation, interest, and compensation among Faculty. It is necessary to reduce the load on supervisors and to foster independent functioning by students. Effective supervision is essential for success and student development, which requires a deep need for proper preparation and training Faculty to be supervisors. Desired learning outcomes should be updated in order to optimally prepare the students for their future role, and maintain the relevance of academic institutions. Keywords: Capstone project supervision, final project in engineering, supervisor-lecturer, engineering education, engineering faculty, instructional methods (syn: pedagogy), faculty training.

Linen Quality and Guest Satisfaction in Star-rated Hotels in Upper East Region of Ghana

Purpose: Linen as launderable textiles is indispensable in the hotel business. Guests pay for hotel services rendered and deserve quality linen. Linen (bed linen, bath linen, guest room curtains) is expected to be clean, crisp, spotless, attractive and comfortable. Linen quality can be attributable to the fibre of fabric, care and maintenance. Thus, the study investigated linen quality and guest satisfaction in star-rated hotels in Upper East Region of Ghana. The reference was on the relationship that exists between linen quality and guest satisfaction and to test if any association existed between them.
 Methodology: The study employed a descriptive survey research design. A sample of 327 guests was sampled using a random sampling technique. Data were collected using a questionnaire. Analysis of data was done by the use of SPSS version 26. Data were presented using both descriptive and inferential statistics. The descriptive statistics were frequencies, percentages, means and standard deviations. For the inferential statistics, Spearman’s Rank-Order correlation was used to determine the relationships, directions, and magnitude among the study variables. The regression model was used for testing the hypotheses. The hypothesis was tested at a 5% level of significance.
 Findings: The findings revealed an association existed between linen quality and guest satisfaction with a moderate positive correlation (r =.04 to .52) and statistically significant (R2 =.197, F(2, 324) = 39.80, β = .522, p = .000). The hypothesis there is no association between linen quality and guest satisfaction was rejected at 95% confidence level. The study concluded linen quality significantly influences guest satisfaction. However, the predictor variable (linen quality) explained approximately 19.2% of the variations in guests’ satisfaction.
 Unique Contribution to Theory, Practice and Policy: The study employed Expectancy-Disconfirmation Paradigm (EDP) model. The expected clean, comfortable and adequate linen met the expectation of the guests for satisfaction to occur. The study recommended stakeholders in the hotel industry should continuously ensure standards on linen quality to improve guest satisfaction. It is suggested the hotel management should purpose to provide quality linen and ensure proper care and maintenance of linen through effective supervision. The study as well calls for the Ghana Tourism Authority, the regulatory body for hotel activities to set standards and intensify monitoring activities regarding the quality of linen presented to guests. As an avenue for the hotels to acquire more knowledge, skills and a better attitude towards the handling of linen, the government of Ghana can institute policies on training on linen management.

Blockchain-oriented approach for detecting cyber-attack transactions

With the high-speed development of decentralized applications, account-based blockchain platforms have become a hotbed of various financial scams and hacks due to their anonymity and high financial value. Financial security has become a top priority with the sustainable development of blockchain-based platforms because of an increasing number of cyber attacks, which have resulted in a huge loss of crypto assets in recent years. Therefore, it is imperative to study the real-time detection of cyber attacks to facilitate effective supervision and regulation. To this end, this paper proposes the weighted and extended isolation forest algorithms and designs a novel framework for the real-time detection of cyber-attack transactions by thoroughly studying and summarizing real-world examples. Furthermore, this study develops a new detection approach for locating the compromised address of a cyber attack to resolve the data scarcity of hack addresses and reduce time consumption. Moreover, three experiments are carried out not only to apply on different types of cyber attacks but also to compare the proposed approach with the widely used existing methods. The results demonstrate the high efficiency and generality of the proposed approach. Finally, the lower time consumption and robustness of our method were validated through additional experiments. In conclusion, the proposed blockchain-oriented approach in this study can handle real-time detection of cyber attacks and has significant scope for applications.