124 research outputs found
Life-Add: Lifetime Adjustable Design for WiFi Networks with Heterogeneous Energy Supplies
WiFi usage significantly reduces the battery lifetime of handheld devices
such as smartphones and tablets, due to its high energy consumption. In this
paper, we propose "Life-Add": a Lifetime Adjustable design for WiFi networks,
where the devices are powered by battery, electric power, and/or renewable
energy. In Life-Add, a device turns off its radio to save energy when the
channel is sensed to be busy, and sleeps for a random time period before
sensing the channel again. Life-Add carefully controls the devices' average
sleep periods to improve their throughput while satisfying their operation time
requirement. It is proven that Life-Add achieves near-optimal proportional-fair
utility performance for single access point (AP) scenarios. Moreover, Life-Add
alleviates the near-far effect and hidden terminal problem in general multiple
AP scenarios. Our ns-3 simulations show that Life-Add simultaneously improves
the lifetime, throughput, and fairness performance of WiFi networks, and
coexists harmoniously with IEEE 802.11.Comment: This is the technical report of our WiOpt paper. The paper received
the best student paper award at IEEE WiOpt 2013. The first three authors are
co-primary author
Managing a Fleet of Autonomous Mobile Robots (AMR) using Cloud Robotics Platform
In this paper, we provide details of implementing a system for managing a
fleet of autonomous mobile robots (AMR) operating in a factory or a warehouse
premise. While the robots are themselves autonomous in its motion and obstacle
avoidance capability, the target destination for each robot is provided by a
global planner. The global planner and the ground vehicles (robots) constitute
a multi agent system (MAS) which communicate with each other over a wireless
network. Three different approaches are explored for implementation. The first
two approaches make use of the distributed computing based Networked Robotics
architecture and communication framework of Robot Operating System (ROS) itself
while the third approach uses Rapyuta Cloud Robotics framework for this
implementation. The comparative performance of these approaches are analyzed
through simulation as well as real world experiment with actual robots. These
analyses provide an in-depth understanding of the inner working of the Cloud
Robotics Platform in contrast to the usual ROS framework. The insight gained
through this exercise will be valuable for students as well as practicing
engineers interested in implementing similar systems else where. In the
process, we also identify few critical limitations of the current Rapyuta
platform and provide suggestions to overcome them.Comment: 14 pages, 15 figures, journal pape
When Queueing Meets Coding: Optimal-Latency Data Retrieving Scheme in Storage Clouds
In this paper, we study the problem of reducing the delay of downloading data
from cloud storage systems by leveraging multiple parallel threads, assuming
that the data has been encoded and stored in the clouds using fixed rate
forward error correction (FEC) codes with parameters (n, k). That is, each file
is divided into k equal-sized chunks, which are then expanded into n chunks
such that any k chunks out of the n are sufficient to successfully restore the
original file. The model can be depicted as a multiple-server queue with
arrivals of data retrieving requests and a server corresponding to a thread.
However, this is not a typical queueing model because a server can terminate
its operation, depending on when other servers complete their service (due to
the redundancy that is spread across the threads). Hence, to the best of our
knowledge, the analysis of this queueing model remains quite uncharted.
Recent traces from Amazon S3 show that the time to retrieve a fixed size
chunk is random and can be approximated as a constant delay plus an i.i.d.
exponentially distributed random variable. For the tractability of the
theoretical analysis, we assume that the chunk downloading time is i.i.d.
exponentially distributed. Under this assumption, we show that any
work-conserving scheme is delay-optimal among all on-line scheduling schemes
when k = 1. When k > 1, we find that a simple greedy scheme, which allocates
all available threads to the head of line request, is delay optimal among all
on-line scheduling schemes. We also provide some numerical results that point
to the limitations of the exponential assumption, and suggest further research
directions.Comment: Original accepted by IEEE Infocom 2014, 9 pages. Some statements in
the Infocom paper are correcte
GLP-1 Receptor Agonists Critical Review: Revisiting Its Positioning for Type 2 Diabetes Mellitus in Routine Clinical Practice in India
Objective: Despite the benefit–risk ratio favoring glucagon-like peptide-1 receptor agonists (GLP-1 RAs), knowledge and awareness is lacking among patients and physicians, particularly in India. The current review provides an overview of GLP-1 RAs and the opinion of a group of healthcare practitioners (HCPs) and independent consultants across India on the evidence for using GLP-1 RAs and its applicability to the Indian population. Materials and methods: A panel of eight HCPs met virtually on December 12–13, 2020 met as part of the Diabetes Research Society (DIABAID). They examined and critically discussed the current research on the use of GLP-1 RAs in the management of T2DM. Results: The panel observed that recent diabetes guidelines and recommendations have shifted toward a more individualised and CV risk-focused approach to T2DM management. They proposed that 1) GLP-1 RAs are ideal cardio-metabolic drugs that address multiple aspects of the T2DM; 2) to bring up GLP-1 RAs as early treatment option in discussions with patients; 3) in T2DM patients with a high CV risk or established ASCVD, CKD, or HF, GLP-1 RAs with proven CVD benefits should be initiated; 4) including oral semaglutide in international treatment recommendation guidelines to improve patient and HCP understanding and adaptability; and 5) patient-physician dialogues will be critical in incorporating GLP-1 RAs earlier in the treatment paradigm for effective T2DM management. Conclusions: The recommendations on using GLP-1 RAs and the associated benefits and risks of these drugs comprise essential considerations for using such medications in the Indian population
Non-Hodgkin lymphoma response evaluation with MRI texture classification
<p>Abstract</p> <p>Background</p> <p>To show magnetic resonance imaging (MRI) texture appearance change in non-Hodgkin lymphoma (NHL) during treatment with response controlled by quantitative volume analysis.</p> <p>Methods</p> <p>A total of 19 patients having NHL with an evaluable lymphoma lesion were scanned at three imaging timepoints with 1.5T device during clinical treatment evaluation. Texture characteristics of images were analyzed and classified with MaZda application and statistical tests.</p> <p>Results</p> <p>NHL tissue MRI texture imaged before treatment and under chemotherapy was classified within several subgroups, showing best discrimination with 96% correct classification in non-linear discriminant analysis of T2-weighted images.</p> <p>Texture parameters of MRI data were successfully tested with statistical tests to assess the impact of the separability of the parameters in evaluating chemotherapy response in lymphoma tissue.</p> <p>Conclusion</p> <p>Texture characteristics of MRI data were classified successfully; this proved texture analysis to be potential quantitative means of representing lymphoma tissue changes during chemotherapy response monitoring.</p
Deep phenotyping and genomic data from a nationally representative study on dementia in India
The Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD) is a nationally representative in-depth study of cognitive aging and dementia. We present a publicly available dataset of harmonized cognitive measures of 4,096 adults 60 years of age and older in India, collected across 18 states and union territories. Blood samples were obtained to carry out whole blood and serum-based assays. Results are included in a venous blood specimen datafile that can be linked to the Harmonized LASI-DAD dataset. A global screening array of 960 LASI-DAD respondents is also publicly available for download, in addition to neuroimaging data on 137 LASI-DAD participants. Altogether, these datasets provide comprehensive information on older adults in India that allow researchers to further understand risk factors associated with cognitive impairment and dementia.Peer reviewe
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