Desired Versus Actual Training for Online Instructors in Community Colleges

The growth of distance education and the demand for instructors has developed over the past ten to fifteen years. There is a perception that the type and amount of instructor preparation is highly variable between institutions. Of the faculty members at two year institutions surveyed, nearly half did not attend training over the previous year. With technology changing rapidly, there is a need for training annually to assure faculty members who teach online are prepared. Distance education administrators need to evaluate their distance education programs and develop a consistent and current infrastructure to assure that their faculty members are being properly trained to teach online

Energy-efficient and Privacy-aware Social Distance Monitoring with Low-resolution Infrared Sensors and Adaptive Inference

Low-resolution infrared (IR) Sensors combined with machine learning (ML) can be leveraged to implement privacy-preserving social distance monitoring solutions in indoor spaces. However, the need of executing these applications on Internet of Things (IoT) edge nodes makes energy consumption critical. In this work, we propose an energy-efficient adaptive inference solution consisting of the cascade of a simple wake-up trigger and a 8-bit quantized Convolutional Neural Network (CNN), which is only invoked for difficult-to-classify frames. Deploying such adaptive system on a IoT Microcontroller, we show that, when processing the output of a 8×8 low-resolution IR sensor, we are able to reduce the energy consumption by 37-57% with respect to a static CNN-based approach, with an accuracy drop of less than 2% (83% balanced accuracy)

Do managed clinical networks improve quality of diabetes care? : Evidence from a retrospective mixed methods evaluation

Peer reviewedPostprin

Design and development of a peristaltic pump for constant flow applications

In wide-ranging areas, including hydraulics, biomedical, automotive, and aerospace, there is often a need to move a fluid with a constant flow rate. This is difficult to achieve with any type of pump and usually other elements are inserted to regularize the output. This study focused on the peristaltic pump because there are few studies on it and it has some interesting features, such as extreme simplicity, a small number of components, and the extreme compactness of the whole system. The first part of this study is focused on analyzing the classical geometry of the peristaltic pump to understand the origin of the discontinuity in the flow rate; the second part proposes a new geometry that mitigates the flow irregularity by more than 200%. In this way, it is possible to use it in all the sectors where a constant flow rate is required but where insulation between the fluid and the machine is required. Together with the flow study, an analysis of how the main geometric parameters affect the operation of the pump is provided, complete with explanatory graphs and tables. A prototype made through additive manufacturing technologies is also proposed

The ethics of people analytics: risks, opportunities and recommendations

Purpose: This research analyzed the existing academic and grey literature concerning the technologies and practices of people analytics (PA), to understand how ethical considerations are being discussed by researchers, industry experts and practitioners, and to identify gaps, priorities and recommendations for ethical practice. Design/methodology/approach: An iterative “scoping review” method was used to capture and synthesize relevant academic and grey literature. This is suited to emerging areas of innovation where formal research lags behind evidence from professional or technical sources. Findings: Although the grey literature contains a growing stream of publications aimed at helping PA practitioners to “be ethical,” overall, research on ethical issues in PA is still at an early stage. Optimistic and technocentric perspectives dominate the PA discourse, although key themes seen in the wider literature on digital/data ethics are also evident. Risks and recommendations for PA projects concerned transparency and diverse stakeholder inclusion, respecting privacy rights, fair and proportionate use of data, fostering a systemic culture of ethical practice, delivering benefits for employees, including ethical outcomes in business models, ensuring legal compliance and using ethical charters. Research limitations/implications: This research adds to current debates over the future of work and employment in a digitized, algorithm-driven society. Practical implications: The research provides an accessible summary of the risks, opportunities, trade-offs and regulatory issues for PA, as well as a framework for integrating ethical strategies and practices. Originality/value: By using a scoping methodology to surface and analyze diverse literatures, this study fills a gap in existing knowledge on ethical aspects of PA. The findings can inform future academic research, organizations using or considering PA products, professional associations developing relevant guidelines and policymakers adapting regulations. It is also timely, given the increase in digital monitoring of employees working from home during the Covid-19 pandemic

Mobile health for cancer in low to middle income countries: priorities for research and development.

The is the accepted manuscript of an article published in the European Journal of Cancer Care (Holeman, I., Evans, J., Kane, D., Grant, L., Pagliari, C. and Weller, D. (2014), Mobile health for cancer in low to middle income countries: priorities for research and development. European Journal of Cancer Care, 23: 750–756. doi: 10.1111/ecc.12250)Many current global health opportunities have less to do with new biomedical knowledge than with the coordination and delivery of care. While basic research remains vital, the growing cancer epidemic in countries of low and middle income warrants urgent action - focusing on both research and service delivery innovation. Mobile technology can reduce costs, improve access to health services, and strengthen health systems to meet the interrelated challenges of cancer and other noncommunicable diseases. Experience has shown that even very poor and remote communities that only have basic primary health care can benefit from mobile health (or 'mHealth') interventions. We argue that cancer researchers and practitioners have an opportunity to leverage mHealth technologies that have successfully targeted other health conditions, rather than reinventing these tools. We call for particular attention to human centred design approaches for adapting existing technologies to suit distinctive aspects of cancer care and to align delivery with local context - and we make a number of recommendations for integrating mHealth delivery research with the work of designers, engineers and implementers in large-scale delivery programmes

The Immune Response to Tumors as a Tool toward Immunotherapy

Until recently cancer medical therapy was limited to chemotherapy that could not differentiate cancer cells from normal cells. More recently with the remarkable mushroom of immunology, newer tools became available, resulting in the novel possibility to attack cancer with the specificity of the immune system. Herein we will review some of the recent achievement of immunotherapy in such aggressive cancers as melanoma, prostatic cancer, colorectal carcinoma, and hematologic malignancies. Immunotherapy of tumors has developed several techniques: immune cell transfer, vaccines, immunobiological molecules such as monoclonal antibodies that improve the immune responses to tumors. This can be achieved by blocking pathways limiting the immune response, such as CTLA-4 or Tregs. Immunotherapy may also use cytokines especially proinflammatory cytokines to enhance the activity of cytotoxic T cells (CTLs) derived from tumor infiltrating lymphocytes (TILs). The role of newly discovered cytokines remains to be investigated. Alternatively, an other mechanism consists in enhancing the expression of TAAs on tumor cells. Finally, monoclonal antibodies may be used to target oncogenes

Locally linear embedding-based prediction for 3D holoscopic image coding using HEVC

Holoscopic imaging is a prospective acquisition and display solution for providing true 3D content and fatigue-free 3D visualization. However, efficient coding schemes for this particular type of content are needed to enable proper storage and delivery of the large amount of data involved in these systems. Therefore, this paper proposes an alternative HEVC-based coding scheme for efficient representation of holoscopic images. In this scheme, some directional intra prediction modes of the HEVC are replaced by a more efficient prediction framework based on locally linear embedding techniques. Experimental results show the advantage of the proposed prediction for 3D holoscopic image coding, compared to the reference HEVC standard as well as previously presented approaches in this field.info:eu-repo/semantics/submittedVersio