Search results for: integral rotor/stator

Authors: P. Ramesh, Aby Joseph, Arya G. Lal, U. S. Aji

Abstract:

Integration of distributed green renewable energy sources in addition with battery energy storage is an inevitable requirement in a smart grid environment. To achieve this, an Intelligent Green Energy Management System (i-GEMS) needs to be incorporated to ensure coordinated operation between supply and load demand based on the hierarchy of Renewable Energy Sources (RES), battery energy storage and distribution grid. A bi-directional energy harvester is an integral component facilitating Intelligent Green Energy Management System (i-GEMS) and it is required to meet the technical challenges mentioned as follows: (1) capability for bi-directional mode of operation (buck/boost) (2) reduction of circuit parasitic to suppress voltage spikes (3) converter startup problem (4) high frequency magnetics (5) higher power density (6) mode transition issues during battery charging and discharging. This paper is focused to address the above mentioned issues and targeted to design, develop and implement a bi-directional energy harvester with galvanic isolation. In this work, the hardware architecture for bi-directional energy harvester rated 3.5 kW is developed with Isolated Full Bridge Boost Converter (IFBBC) as well as Dual Active Bridge (DAB) Converter configuration using modular power electronics hardware which is identical for both solar PV array and battery energy storage. In IFBBC converter, the current fed full bridge circuit is enabled and voltage fed full bridge circuit is disabled through Pulse Width Modulation (PWM) pulses for boost mode of operation and vice-versa for buck mode of operation. In DAB converter, all the switches are in active state so as to adjust the phase shift angle between primary full bridge and secondary full bridge which in turn decides the power flow directions depending on modes (boost/buck) of operation. Here, the control algorithm is developed to ensure the regulation of the common DC link voltage and maximum power extraction from the renewable energy sources depending on the selected mode (buck/boost) of operation. The circuit analysis and simulation study are conducted using PSIM 9.0 in three scenarios which are - 1.IFBBC with passive clamp, 2. IFBBC with active clamp, 3. DAB converter. In this work, a common hardware prototype for bi-directional energy harvester with 3.5 kW rating is built for IFBBC and DAB converter configurations. The power circuit is equipped with right choice of MOSFETs, gate drivers with galvanic isolation, high frequency transformer, filter capacitors, and filter boost inductor. The experiment was conducted for IFBBC converter with passive clamp under boost mode and the prototype confirmed the simulation results showing the measured efficiency as 88% at 2.5 kW output power. The digital controller hardware platform is developed using floating point microcontroller TMS320F2806x from Texas Instruments. The firmware governing the operation of the bi-directional energy harvester is written in C language and developed using code composer studio. The comprehensive analyses of the power circuit design, control strategy for battery charging/discharging under buck/boost modes and comparative performance evaluation using simulation and experimental results will be presented.

Keywords: bi-directional energy harvester, dual active bridge, isolated full bridge boost converter, intelligent green energy management system, maximum power point tracking, renewable energy sources

Procedia PDF Downloads 106

Authors: Pippa Sipanoun, Jo Wray, Kate Oulton, Faith Gibson

Abstract:

Background: With rapidly evolving digital health innovation, there is a need for digital health transformation that is accessible and sustainable, that demonstrates utility for all stakeholders while maintaining data safety. Great Ormond Street Hospital for Children aimed to future-proof the hospital by transitioning to an electronic patient record (EPR) system with a tethered patient portal (MyGOSH) in April 2019. MyGOSH patient portal enables patients 12 years or older (with their parent's consent) to access their digital health data. This includes access to results, documentation, and appointments that facilitate communication with their care team. As part of the Going Digital Study conducted between 2018-2021, data were collected from a sample of all relevant stakeholders before and after EPR and MyGOSH implementation. Data collection reach was wide and included the hospital legal and ethics teams. Aims: This study aims to understand the ethical and legal implications of young people and their parents accessing their digital health data. Methods: A focus group was conducted. Recruited participants were members of the Great Ormond Street Hospital Paediatric Bioethics Centre. Participants included expert and lay members from the Committee from a variety of professional or academic disciplines. Written informed consent was provided by all participants (n=7). The focus group was recorded, transcribed verbatim, and analyzed using thematic analysis. Results: Six themes were identified: access, competence and capacity - granting access to the system; inequalities in access resulting in inequities; burden, uncertainty and responding to change - managing expectations; documenting, risks and data safety; engagement, empowerment and understanding – how to use and manage personal information; legal considerations and obligations. Discussion: If healthcare professionals are to empower young people to be more engaged in their care, the importance of including them in decisions about their health is paramount, especially when they are approaching the age of becoming the consenter for treatment. Complexities exist in assessing competence or capacity when granting system access, when disclosing sensitive information, and maintaining confidentiality. Difficulties are also present in managing clinician burden, managing user expectations whilst providing an equitable service, and data management that meets professional and legal requirements. Conclusion: EPR and tethered-portal implementation at Great Ormond Street Hospital for Children was not only timely, due to the need for a rapid transition to remote consultations during the COVID-19 pandemic, which would not have been possible had EPR/MyGOSH not been implemented, but also integral to the digital health revolution required in healthcare today. This study is highly relevant in understanding the complexities around young people and their parents accessing their digital health data and, although the focus of this research related to portal use and access, the findings translate to young people in the wider digital health context. Ongoing support is required for all relevant stakeholders following MyGOSH patient portal implementation to navigate the ethical and legal complexities. Continued commitment is needed to balance the benefits and burdens, promote inclusion and equity, and ensure portal utility for patient benefit, whilst maintaining an individualized approach to care.

Keywords: patient portal, young people and their parents, ethical, legal

Procedia PDF Downloads 91

Authors: Lolwa Alansari, Hanen Mrabet, Kholoud Khaled, Abdelhamid Azhaghdani, Sufia Athar, Aska Kaima, Zaineb Mhamdia, Zubaria Altaf, Almunzer Zakaria, Tamara Alshadafat

Abstract:

Introduction: The Obstetrics and Gynecology Emergency Department at Alwakra Hospital has faced significant challenges, which have been further worsened by the impact of the COVID-19 pandemic. These challenges involve issues such as overcrowding, extended wait times, and a notable surge in demand for emergency care services. Moreover, prolonged waiting times have emerged as a primary factor contributing to situations where patients leave without receiving attention, known as left without being seen (LWBS), and unexpectedly abscond. Addressing the issue of insufficient patient mobility in the obstetrics and gynecology emergency department has brought about substantial improvements in patient care, healthcare administration, and overall departmental efficiency. These changes have not only alleviated overcrowding but have also elevated the quality of emergency care, resulting in higher patient satisfaction, better outcomes, and operational rewards. Methodology: The COVID-19 pandemic has served as a catalyst for substantial transformations in the obstetrics and gynecology emergency, aligning seamlessly with the strategic direction of Hamad Medical Corporation (HMC). The fundamental aim of this initiative is to revolutionize the operational efficiency of the OB-GYN ED. To accomplish this mission, a range of transformations has been initiated, focusing on essential areas such as digitizing systems, optimizing resource allocation, enhancing budget efficiency, and reducing overall costs. The project utilized the Plan-Do-Study-Act (PDSA) model, involving a diverse team collecting baseline data and introducing throughput improvements. Post-implementation data and feedback were analysed, leading to the integration of effective interventions into standard procedures. These interventions included optimized space utilization, real-time communication, bedside registration, technology integration, pre-triage screening, enhanced communication and patient education, consultant presence, and a culture of continuous improvement. These strategies significantly reduced waiting times, enhancing both patient care and operational efficiency. Results: Results demonstrated a substantial reduction in overall average waiting time, dropping from 35 to approximately 14 minutes by August 2023. The wait times for priority 1 cases have been reduced from 22 to 0 minutes, and for priority 2 cases, the wait times have been reduced from 32 to approximately 13.6 minutes. The proportion of patients spending less than 8 hours in the OB ED observation beds rose from 74% in January 2022 to over 98% in 2023. Notably, there was a remarkable decrease in LWBS and absconded patient rates from 2020 to 2023. Conclusion: The project initiated a profound change in the department's operational environment. Efficiency became deeply embedded in the unit's culture, promoting teamwork among staff that went beyond the project's original focus and had a positive influence on operations in other departments. This effectiveness not only made processes more efficient but also resulted in significant cost reductions for the hospital. These cost savings were achieved by reducing wait times, which in turn led to fewer prolonged patient stays and reduced the need for additional treatments. These continuous improvement initiatives have now become an integral part of the Obstetrics and Gynecology Division's standard operating procedures, ensuring that the positive changes brought about by the project persist and evolve over time.

Keywords: overcrowding, waiting time, person centered care, quality initiatives

Procedia PDF Downloads 41

Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

Abstract:

The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

Procedia PDF Downloads 91