This research underscores the importance of enhancing the early detection of diabetic retinopathy and glaucoma, two prominent culprits behind vision loss. Typically, retinal diseases lurk without symptoms until they inflict severe vision impairment, underscoring the critical need for early identification. The research is centered on the potential of leveraging fundus images, which offer invaluable insights by analyzing various attributes of retinal blood vessels, such as their length, width, tortuosity, and branching patterns. The conventional practice of manually segmenting retinal vessels by medical professionals is both intricate and time-consuming, demanding specialized expertise. This approach, reliant on pathologists, grapples with limitations related to scalability and accessibility. To surmount these challenges, the research introduces an automated solution employing computer vision. It conducts an evaluation of diverse retinal vessel segmentation and classification methods, including machine learning, filtering-based, and model-based techniques. Robust performance assessments, involving metrics like the true positive rate, true negative rate, and accuracy, facilitate a comprehensive comparison of these methodologies. The ultimate goal of this research is to create more efficient and accessible diagnostic tools, consequently enhancing the early detection of eye diseases through automated retinal vessel segmentation and classification. This endeavor combines the capabilities of computer vision and deep learning to pioneer new benchmarks in the realm of biomedical imaging, thereby addressing the pressing issues surrounding eye disease diagnosis.
Six Sigma is an organized and systematic method for strategic process improvement that relies on statistical and scientific methods to reduce the defect rates and achieve significant quality up-gradation. Six Sigma is also a business philosophy to improve customer satisfaction, a tool for eliminating process variation and errors and a metric of world class companies allowing for process comparisons. Six Sigma is one of the most effective advanced improvement strategies which has direct impact on operational excellence of an organization. Six Sigma may also be defined as the powerful business strategies, which have helped to improve quality initiatives in many industries around the world. With the use of Six Sigma in casting industries, rejection rate is reduced, customer satisfaction is improved and financial benefits also increased. Six Sigma management uses statistical process control to relentlessly and rigorously pursue the reduction of variation in all critical processes to achieve continuous and breakthrough improvements that impact the bottom-line and/or top-line of the organization and increase customer satisfaction. In this paper author reviewed some of the significant previous published papers and focused on the general overview of publication in casting industries.
Landscape architects, who guide planning and design decisions by understanding the socio-cultural expectations, functional needs, and social behaviors of the community, create ideal spaces for people by integrating natural, social, cultural, and aesthetic factors with a holistic design approach in urban public areas. Public open green spaces are important urban areas that have a positive impact on people’s physical, mental, and emotional health. In this context, the concept of personal space, its impact on individuals, and related perception studies have been examined. In landscape design, criteria that affect individuals’ personal space distances and personal space perceptions have been identified, providing a basis for sustainable landscape design projects in public open and green spaces.
Unmanned Aerial Vehicles (UAVs) have gained spotlighted attention in the recent past and has experienced exponential advancements. This research focuses on UAV-based data acquisition and processing to generate highly accurate outputs pertaining to orthomosaic imagery, elevation, surface and terrain models. The study addresses the challenges inherent in the generation and analysis of orthomosaic images, particularly the critical need for correction and enhancement to ensure precise application in fields like detailed mapping and continuous monitoring. To achieve superior image quality and precision, the study applies advanced image processing techniques encompassing Fuzzy Logic and edge-detection techniques. The study emphasizes on the necessity of an approach for countering the loss of information while mapping the UAV deliverables. By offering insights into both the challenges and solutions related to orthomosaic image processing, this research lays the groundwork for future applications that promise to further increase the efficiency and effectiveness of UAV-based methods in geomatics, as well as in broader fields such as engineering and environmental management.
Intellectual capital is one of the most crucial determinants of long-term economic development. The countries compete for highly skilled labor and talented youth. State regulatory interventions aim to, on the one hand, facilitate the retention of foreign high-productivity intellectual capital in the host country, transforming ‘educational’ and ‘scientific’ migrants into residents, and on the other hand, prevent the outflow of their own qualified workforce. The paper aims to outline the role of the nation’s higher education system in the influx and outflow of labor resources. A two-stage approach is applied: 1) maximum likelihood—to cluster the EU countries and the potential candidates to become members of EU countries based on the integrated competitiveness of their higher education systems, considering quantitative, qualitative, and internationalization aspects; 2) logit and probit models—to estimate the likelihood of net migration flow surpassing baseline cluster levels and the probability of migration intensity changes for each cluster. Empirical findings allow the identification of four country clusters. Forecasts indicate the highest likelihood of increased net migration flow in the second cluster (66.7%) and a significant likelihood in the third cluster (23.4%). However, the likelihood of such an increase is statistically insignificant for countries in the first and fourth clusters. The conclusions emphasize the need for regulatory interventions that enhance higher education quality, ensure equal access for migrants, foster population literacy, and facilitate lifelong learning. Such measures are imperative to safeguard the nation’s intellectual potential and deter labor emigration.
Organisational culture stands as a fundamental prerequisite for the efficacious operation of any given organisation. The primary aim of this study is to discern potential alterations within the dimensions of organisational culture across the pre-COVID-19, contemporary, and favoured paradigms within the realm of public administration. The data set was obtained from a cohort of 1189 officials in the Czech Republic. The Organisational Culture Assessment Instrument (OCAI) was deployed for the purposes of conducting an online survey. The dominance of the clan archetype across all examined time frames has been corroborated. In addition, a statistically significant manifestation of these dimensions has been determined. In relation to pertinent variables, specifically gender, age, tenure, manager gender, and the dimensions typifying organisational culture, no statistically significant correlations have emerged. Respondents have not reported a sense of work-life imbalance in the aftermath of the pandemic. In summary, it is deduced that the pandemic has not exerted a drastic influence on the metamorphosis of organisational culture within the ambit of public administration. This study provides invaluable information on the repercussions of the pandemic within a sphere that, as an intangible constituent, often goes under-recognised. Mastery of the positioning of dimensions across diverse archetypes is of paramount significance for managers, as it can provide guidance in the cultivation of an apt organisational culture.
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