Is there research on edge work?
Best insight from top research papers
Research on edge work exists in various domains. One study delves into the concept of edge computing, emphasizing its importance in processing large-scale data quickly to support technologies like the Internet of Everything (IoE) . Another research focuses on improving surface defect detection in manufacturing through an enhanced defect edge detection algorithm based on the Sobel operator, showcasing advancements in accuracy and efficiency . Additionally, a study explores scientific workflow scheduling in uncertain edge environments using fuzzy theory and a novel optimization algorithm, highlighting the significance of adapting to fluctuations in CPU load and bandwidth for efficient task execution . Furthermore, a paper discusses the application of Stephen Lyng's concept of 'edgework' in understanding full-contact combat sports like mixed martial arts (MMA), shedding light on the motivations and experiences of participants within a social-psychological framework .
Answers from top 5 papers
More filters
| Papers (5) | Insight |
|---|---|
23 Mar 2020 12 Citations | Yes, the paper discusses how Stephen Lyng's concept of 'edgework' is applied to understand the motivations and experiences of participants in full-contact combat sports, specifically mixed martial arts (MMA). |
04 Mar 2022 3 Citations | Yes, the research paper focuses on an improved defect edge detection algorithm for work piece defect detection in machine vision systems, enhancing accuracy and efficiency in defect detection. |
| Yes, the research paper reviews edge computing, highlighting its purpose, necessity, differences from cloud computing, advantages of architectures, and new initiatives in the field of edge computing. | |
07 Nov 2020 | Yes, the research paper focuses on scientific workflow scheduling based on fuzzy theory in uncertain edge environments, addressing factors like CPU load and bandwidth fluctuations on servers. |
04 Mar 2022 1 Citations | Yes, the research paper focuses on an improved defect edge detection algorithm for workpiece defect detection in machine vision systems, enhancing accuracy and efficiency in defect detection. |
Related Questions
What are the recent advances in edge resource autoscaling?5 answersRecent advances in edge resource autoscaling include innovative mechanisms like Intelligent Horizontal Proactive Autoscaling (IHPA), Proximal Policy Optimization (PPO) based autoscaling, and Chance-Constrained Programming for resource control. These approaches aim to optimize resource allocation by leveraging deep learning architectures, dynamic resource adjustments, and centralized decision-making to meet Quality of Service (QoS) requirements while minimizing costs and maintaining processing times below set thresholds. Additionally, proactive horizontal auto-scaling frameworks have been developed to anticipate user service requests, manage energy consumption, and dynamically allocate resources based on workload intensities. These advancements showcase a shift towards more intelligent, efficient, and adaptive edge resource autoscaling strategies in next-generation wireless and edge computing environments.
Is there research on edge work in voilence?4 answersResearch on edge work primarily focuses on edge computing, which involves processing data closer to the data source and end-users, enhancing response speed and bandwidth load. While edge computing has gained attention for moving latency-critical services closer to users and saving network bandwidth, recent trends suggest that the cloud may already be sufficiently close for most applications. Additionally, edge-cloud cooperation models have been developed to optimize tasks based on computational intensity and real-time requirements, such as detecting safety helmets in worksite videos efficiently. These studies highlight the evolving landscape of edge computing, its advantages over traditional cloud computing, and the potential for specialized applications in specific niches rather than a general-purpose solution.
Is there research on edge work and intersectionality?5 answersThere is research on intersectionality in various fields. Ryan and Briggs discuss the need for an intersectional approach in work-life research, highlighting the problems of a single-identity focus and the advantages of considering multiple identities. Winchester, Boyd, and Johnson explore intersectionality in software development and use, emphasizing the lack of representation and the need for equitable outcomes for complex social identities. Additionally, there is research on intersectionality in the context of dirty work, with a focus on how individuals construct meaning at the intersection of multiple sources of taint. However, there is no specific mention of research on edge work and intersectionality in the provided abstracts.
Can the very high at both ends of time series data be attributed to edge effects?5 answersYes, the high values at both ends of time series data can be attributed to edge effects. The edge effect refers to the distortion or artifacts that occur at the boundaries of a time series when applying certain analysis techniques. In the context of wavelet time-frequency spectrum analysis, the application of the leap-step time series analysis (LSTSA) model effectively reduces the edge effect and improves the ability to detect low-frequency signals. Similarly, in the case of Dynamic Time Warping (DTW) algorithm, the lack of warping invariance at the "head" and "tail" of the time series can lead to incorrect classifications, as tiny differences at the beginning or end of the series contribute disproportionately to the estimated similarity. Therefore, it is important to consider and address edge effects when analyzing time series data.
What is empirical work?5 answersEmpirical work refers to research that is based on the collection of first-hand data through experimentation or observation. It involves the application of qualitative or quantitative methodology to gather empirical evidence. Empirical research can provide valuable insights and contribute to the correct application of scientific principles. It can be conducted in various fields, such as sociology, economics, and group work practice. In economics, empirical work often involves analyzing abundant data to study auctions and their various types. However, there are challenges in conducting empirical work, such as data mining, the need for clear hypothesis testing, and potential aggregation biases. Despite these challenges, empirical research plays a crucial role in advancing knowledge and understanding in different disciplines.
What are elements of a companies edge?2 answersCompanies gain a competitive edge by implementing various elements. These elements include price management, segmentation, promotion, channel-based strategy, product management, influencing development, and the marketing plan. Additionally, companies can achieve a competitive advantage by hiring leaders and team members with cross-industry knowledge, who can transfer successful experiences, processes, and tools from other industries. Strategic decision-making and data collection are crucial for assessing a firm's position and developing market-based and non-market strategies. Furthermore, customer-supplier alliances can greatly increase a company's competitiveness, market share, and financial strength by enabling cost reduction, quality improvement, and value enhancement. These elements collectively contribute to a company's edge in the business environment.