Laying a Foundation for Digital Collections at the Property Information Resource Center

2021 ◽  
Vol 84 (2) ◽  
pp. 256-280
Author(s):  
Alison Anderson ◽  
Kristin Bjork ◽  
Kyle DeCicco-Carey ◽  
Sylvia Welsh
Keyword(s):  
Service Level Agreement ◽  
The United States ◽  
Service Level ◽  
Information Resource ◽  
Architectural Drawings ◽  
Digital Collections ◽  
Resource Center ◽  
Reference Process ◽  
Entire Collection ◽  
Mission Service

ABSTRACT Over a decade ago, the Harvard University Property Information Resource Center (PIRC) began digitizing its entire collection of more than a hundred thousand architectural drawings documenting the construction of the oldest university in the United States. Challenges and successes materialized throughout the project relating to the PIRC's mission, service level, and collection dependencies. Continuing to meet users' demanding needs while learning and revising best practices was ambitious yet ultimately achievable. In addition to producing high-quality images for digital preservation, secondary positive outcomes of the project were the conservation of drawings, improvements to the reference process, and the ability to expand these services beyond the traditional user group. To achieve the project goals, staff created a flexible workflow that ameliorated the condition of physical drawings in the collection while allowing them to uphold an established user service level agreement.

Front-line Healthcare Workers in COVID-19: The Way from Elbow-Bump Greeting to Closing Body Bags

2020 ◽  
Author(s):  
Stefan Bittmann
Keyword(s):  
Health Service ◽  
Healthcare Workers ◽  
Well Being ◽  
The United States ◽  
Angiotensin Ii Receptor ◽  
Front Line ◽  
Resource Center ◽  
Research Activities ◽  
The World ◽  
The Usa

COVID-19 is a serious coronavirus disease that is spreading all over the world. As of the date of this publication, 2.834.134 people have been infected with COVID-19 and 197.924 deaths have been recorded in 185 countries (John Hopkins Corona Resource Center, 25th April 2020) [1]. This overwhelming mortality rate requires intensive research activities around the world. To date, the number of deaths per day in the United States is still killing, indicating an uncontrollable state of infection spread. SARS-CoV-2 binds to the angiotensin II receptor in various tissues of the human body, particularly in the oral cavity and tongue. SARS-CoV-2 requires the cheerful TMPRSS2 to activate this inertia. SARS-CoV-2 uses the ACE2 receptor as a gateway to the lungs. The SARS-CoV-2 virus binds with the spike protein to the ACE2 receptor. COVID-19 is more common among African Americans in the USA (Science 10th April 2020). The comfort and the emotional loading capacity of the employees in the health service are key components for the maintenance of the essential health services during the outbreak of the COVID-19 virus (Coronavirus) [2,3]. Hence, it will be important to anticipate the charges linked with this work and to release support for employees in the health service. The supervision and assessment of the psychic health and the well-being of the employees in the health service will be important, just as the efforts to guarantee a successful reunion with colleagues if they are infected.

Distance Aware VM allocation process to minimize energy consumption in cloud computing

2019 ◽  
Vol 12 ◽  
Author(s):  
Gurpreet Singh ◽  
Manish Mahajan ◽  
Rajni Mohana
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Research Work ◽  
Service Level Agreement ◽  
Service Level ◽  
Physical Machine ◽  
Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

scholarly journals Internet of Things for Mental Health: Open Issues in Data Acquisition, Self-Organization, Service Level Agreement, and Identity Management

2021 ◽  
Vol 18 (3) ◽  
pp. 1327
Author(s):  
Leonardo J. Gutierrez ◽  
Kashif Rabbani ◽  
Oluwashina Joseph Ajayi ◽  
Samson Kahsay Gebresilassie ◽  
Joseph Rafferty ◽  
...  
Keyword(s):  
Mental Health ◽  
Internet Of Things ◽  
Data Acquisition ◽  
Identity Management ◽  
Service Level Agreement ◽  
Service Level ◽  
Self Organization ◽  
Future Research ◽  
Study Results ◽  
Open Issues

The increase of mental illness cases around the world can be described as an urgent and serious global health threat. Around 500 million people suffer from mental disorders, among which depression, schizophrenia, and dementia are the most prevalent. Revolutionary technological paradigms such as the Internet of Things (IoT) provide us with new capabilities to detect, assess, and care for patients early. This paper comprehensively survey works done at the intersection between IoT and mental health disorders. We evaluate multiple computational platforms, methods and devices, as well as study results and potential open issues for the effective use of IoT systems in mental health. We particularly elaborate on relevant open challenges in the use of existing IoT solutions for mental health care, which can be relevant given the potential impairments in some mental health patients such as data acquisition issues, lack of self-organization of devices and service level agreement, and security, privacy and consent issues, among others. We aim at opening the conversation for future research in this rather emerging area by outlining possible new paths based on the results and conclusions of this work.

scholarly journals Supporting SLA via Adaptive Mapping and Heterogeneous Storage Devices in Ceph

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 847
Author(s):  
Sopanhapich Chum ◽  
Heekwon Park ◽  
Jongmoo Choi
Keyword(s):  
Positive Impact ◽  
Distributed Storage ◽  
Storage System ◽  
Hard Disk Drives ◽  
Service Level Agreement ◽  
Service Level ◽  
Cost Ratio ◽  
Solid State Drives ◽  
Storage Devices ◽  
Management Scheme

This paper proposes a new resource management scheme that supports SLA (Service-Level Agreement) in a bigdata distributed storage system. Basically, it makes use of two mapping modes, isolated mode and shared mode, in an adaptive manner. In specific, to ensure different QoS (Quality of Service) requirements among clients, it isolates storage devices so that urgent clients are not interfered by normal clients. When there is no urgent client, it switches to the shared mode so that normal clients can access all storage devices, thus achieving full performance. To provide this adaptability effectively, it devises two techniques, called logical cluster and normal inclusion. In addition, this paper explores how to exploit heterogeneous storage devices, HDDs (Hard Disk Drives) and SSDs (Solid State Drives), to support SLA. It examines two use cases and observes that separating data and metadata into different devices gives a positive impact on the performance per cost ratio. Real implementation-based evaluation results show that this proposal can satisfy the requirements of diverse clients and can provide better performance compared with a fixed mapping-based scheme.

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