344 research outputs found
Centralizers of Hamiltonian finite cyclic group actions on rational ruled surfaces
Let be either the product or the non-trivial
bundle over endowed with any symplectic form . Suppose a
finite cyclic group is acting effectively on through
Hamiltonian diffeomorphisms, that is, there is an injective homomorphism
. In this paper, we investigate the homotopy
type of the group of equivariant symplectomorphisms. We
prove that for some infinite families of actions satisfying certain
inequalities involving the order and the symplectic cohomology class
, the actions extends to either one or two toric actions, and
accordingly, that the centralizers are homotopically equivalent to either a
finite dimensional Lie group, or to the homotopy pushout of two tori along a
circle. Our results rely on -holomorphic techniques, on Delzant's
classification of toric actions, on Karshon's classification of Hamiltonian
circle actions on -manifolds, and on the Chen-Wilczy\'nski classification of
smooth -actions on Hirzebruch surfaces.Comment: 36 pages. Initial release. Comments welcom
An end-to-end, interactive Deep Learning based Annotation system for cursive and print English handwritten text
With the surging inclination towards carrying out tasks on computational
devices and digital mediums, any method that converts a task that was
previously carried out manually, to a digitized version, is always welcome.
Irrespective of the various documentation tasks that can be done online today,
there are still many applications and domains where handwritten text is
inevitable, which makes the digitization of handwritten documents a very
essential task. Over the past decades, there has been extensive research on
offline handwritten text recognition. In the recent past, most of these
attempts have shifted to Machine learning and Deep learning based approaches.
In order to design more complex and deeper networks, and ensure stellar
performances, it is essential to have larger quantities of annotated data. Most
of the databases present for offline handwritten text recognition today, have
either been manually annotated or semi automatically annotated with a lot of
manual involvement. These processes are very time consuming and prone to human
errors. To tackle this problem, we present an innovative, complete end-to-end
pipeline, that annotates offline handwritten manuscripts written in both print
and cursive English, using Deep Learning and User Interaction techniques. This
novel method, which involves an architectural combination of a detection system
built upon a state-of-the-art text detection model, and a custom made Deep
Learning model for the recognition system, is combined with an easy-to-use
interactive interface, aiming to improve the accuracy of the detection,
segmentation, serialization and recognition phases, in order to ensure high
quality annotated data with minimal human interaction.Comment: 17 pages, 8 figures, 2 table
Malayalam Handwritten Character Recognition using CNN Architecture
The process of encoding an input text image into a machine-readable format is called optical character recognition (OCR). The difference in characteristics of each language makes it difficult to develop a universal method that will have high accuracy for all languages. A method that produces good results for one language may not necessarily produce the same results for another language. OCR for printed characters is easier than handwritten characters because of the uniformity that exists in printed characters. While conventional methods find it hard to improve the existing methods, Convolutional Neural Networks (CNN) has shown drastic improvement in classification and recognition of other languages. However, there is no OCR model using CNN for Malayalam characters. Our proposed system uses a new CNN architecture for feature extraction and softmax layer for classification of characters. This eliminates manual designing of features that is used in the conventional methods. P-ARTS Kayyezhuthu dataset is used for training the CNN and an accuracy of 99.75% is obtained for the testing dataset meanwhile a collection of 40 real time input images yielded an accuracy of 95%
To Investigate Data Center Performance and Quality of service in IaaS CloudComputing Systems.
Cloud data center management is a key problem due to the numerous and heterogeneous strategies that can be applied, ranging from the VM placement to the federation with other clouds. Performance evaluation of Cloud Computing infrastructures is required to predict and quantify the cost benefit of a strategy portfolio and the corresponding Quality of Service (QoS) experienced by users. Such analyses are not feasible by simulation or on the field experimentation, due to the great number of parameters that have to be investigated. In this paper, we present an analytical model, based on Stochastic Reward Nets (SRNs), that is both scalable to model systems composed of thousands of resources and flexible to represent different policies and cloud specific strategies. Several performance metrics are defined and evaluated to analyze the behavior of a Cloud data center: utilization, availability, waiting time, and responsiveness. A resiliency analysis is also provided to take into account load bursts. Finally, a general approach is presented that, starting from the concept of system capacity, can help system managers to opportunely set the data center parameters under different working conditions
Development of pulmonary hypertension in patients with end stage renal disease
INTRODUCTION
Cardiovascular disease is the leading cause of morbidity and mortality in dialysis patients, accounting for 50%of deaths. Pulmonary hypertension (PHT) comprises a group of clinical and pathophysiological entities with similar features but a variety of underlying causes. There are several etiologies for PHT. Pulmonary hypertension (PHT) can be the result of heart, lung or systemic disorders. Regardless of the etiology, morbidity and mortality from long-standing PHT exceed that expected from the causative condition.
PHT was frequently found in patients with chronic renal failure (CRF). Review of literature showed that in one study, PHT was found in 40% of patients with end stage renal disease (ESRD) on chronic hemodialysis therapy via arterio venous access. Adekunle et al. stated that PHT is an independent predictor of mortality in ESRD patients.
PHT involves vasoconstriction and obliteration of the lumen of small vessels in the lungs by plexiform lesions resulting in increased resistance to flow. Proposed mechanisms for the formation of the plexiform lesion included regulation of endothelial growth and angiogenic response to local
triggers. Hormonal and metabolic derangement associated with ESRD might lead to pulmonary arterial vasoconstriction and an increase of the pulmonary vascular resistance.
Pulmonary artery pressure (PAP) may be further increased by high cardiac output resulting from the arterio venousaccess itself and also worsened by commonly occurring anemia and fluid overload. Subclinical left ventriculardysfunction also occurs in patients with ESRD, and is evidenced as abnormal myocardial diastolic rather than systolic dysfunction.
Local vascular tone and function of pulmonary vessels are regulated by the balance between vasodilators, such as nitric oxide, and vasoconstrictors, such as thromboxane. Patients with CRF show an endothelial dysfunction related to defective nitric oxide activity, which is not corrected by hemodialysis (HD). Increased brain natriuretic hormone is associated with age, left ventricular hypertrophy, renal failure, and PHT. N-terminal pro-brain natriuretic peptide (NT-proBNP) is a byproduct of brain natriuretic peptide (BNP) that has been shown to be of prognostic value in PHT.
AIM :
In this study, we aim to find the prevalence of PHT in patients with ESRD and compare the incidence of PHT between those on hemodialysis and those on conservative management. We also compare the biochemical data of the patients with and without PHT to find out any possible associations.
METHODOLOGY :
Study Method :
The study was conducted on patients attending the in-patient/out-patient department of nephrology in PSG hospital. All patients with a diagnosis of ESRD where taken up for the study after the application of the inclusion and exclusion criteria and after obtaining consent. These patients were divided into two groups – those who receive dialysis and those on conservative management.
The biochemical data collected were the average of the last six readings .ECG, CXR and echocardiography to assess PHT were done to those patients who were selected to be included in the study.
Study Place : The study was conducted in PSG Hospitals, Coimbatore.
Study Population : Patients diagnosed with end stage renal disease presenting to PSG hospitals during a time period of 6 months were included in the study after the application of inclusion and exclusion criteria.
Study Period :
The study was conducted during the time period of April 2010 to October 2010. All patients with a diagnosis of ESRD attending the Nephrology department who gave consent to be included in the study were included during this time period. Total of 73 patients were studied.
Inclusion Criteria :
ESRD patients on HD or conservative management were selected. ESRD due to all etiologies and patients of all age groups were selected.
Exclusion Criteria :
COPD, Parenchymal Lung Disease, Chest Wall Disease, Previous history of PHT, Previous pulmonary embolism, Smoker ( >5 pack years), Collagen Vascular Disease, LV EF <50%, Significant mitral/aortic valve disease.
HD patients were being treated with standard bicarbonate dialysis for 4 hours, 3 times a week. Subjects gave their informed consent and the study protocol was approved by the institute’s Committee on Human Research.
RESULTS :
PHT is more common among those on hemodialysis than those who are on conservative management. The cause of a higher PAP in group 1 may be related to the process of HD or the hemodynamic changes caused by AVF. The process of HD itself may be a contributing factor for elevated PAP, but the exact cause is not known and vasoconstrictors such as endothelin may be involved. Microbubble emboli are another cause. In addition, HD causes recurrent episodes of hypoxemia due to partial blockage of the pulmonary capillary bed by white cells or silicone microemboli. Recurrent hypoxemia is associated with elevation of PAP.
CONCLUSION :
This study shows that PHT is very common in ESRD patients.
a. 31.5% of total patients (73) with ESRD had PHT,
b. 35% of 37 patients on HD had PHT,
c. 28% of 36 patients on conservative management had PHT.
Also, PHT is much more common in ESRD patients receiving HD than those on conservative management.
Since pulmonary arterial hypertension usually presents at a very late stage, early diagnosis is a key to proper management and a better outcome.
Estimation and follow-up of PAP using doppler echocardiography may be indicated in all patients with ESRD undergoing HD via an arteriovenous access
Analysis of development of Index Left Ventricular Systolic Dysfunction after revascularization in Acute ST Elevation Myocardial Infarction.
Introduction :
Myocardial infarction is the most cause of heart failure. The incidence of heart failure after MI has been reported as high as 23% in various studies. Characteristics of patients in India who develop heart failure after a myocardial infarction are less well studied. Though presence of higher incidence of reduced LV function with delay in revascularization time is established, rates of reduced LV function after different modes of revascularization and correlation with coronary artery lesion is not well established.
Aim and Objectives :
To study the incidence of left ventricular dysfunction after the initial episode of myocardial infarction and to determine the difference in rates of development of LV dysfunction depending on time to perform revascularization and based on mode of revascularization and to correlate the development of LV dysfunction with the coronary artery lesion as determined by coronary angiogram.
Methodology :
93 patients admitted in PSG Hospital from 1st March 2013 to 31st December 2013 with a diagnosis of Acute ST Elevation Myocardial Infarction and undergoing reperfusion therapy with either streptokinase or by percutaneous coronary intervention were included. Window period and door to needle/door to balloon time are recorded. Left ventricular ejection fraction, as determined by volumetric method, is measured within first 24 hours and on day 5 by a single person to avoid interpersonal variation. Development of heart failure based on Framingham criteria is noted. Use of diuretics is noted. Coronary artery lesion by coronary angiogram is noted.
Results :
Out of 93 patients included in the study, 32 underwent primary PCI and 61 underwent thrombolysis. Patients with longer reperfusion time showed a significant reduction in LV ejection fraction. Patients retaining a normal ejection fraction when reperfusion times are between 0-3, 3-6, 6-12 and more than 12 were 70%, 59%, 32% and 0 respectively. Patients who underwent primary PCI had more chance of a preserved LVEF compared to those who underwent thrombolysis (82% Vs 44%. p=0.013). Patients with anterior wall STEMI had less number of patients with normal LVEF when reperfusion times were between 3 to 6 hours (41% Vs 93%. p=0.001) compared to non-anterior wall STEMI patients. No significant associations were found between age, presence of diabetes and the number of vessels involved to LVEF.
Conclusion :
Longer reperfusion times are associated with significant reduction in LVEF. Primary PCI leads to better outcome in patients presenting between 3-6 hours when compared with thrombolysis. AW STEMI patients develop significant reduction in LVEF at 3-6 hours compared to non-AW STEMI patients
Distributed Probabilistic Congestion Control in LEO Satellite Networks
Satellite communication in Low Earth Orbiting (LEO) constellations is an
emerging topic of interest. Due to the high number of LEO satellites in a
typical constellation, a centralized algorithm for minimum-delay packet routing
would incur significant signaling and computational overhead. We can exploit
the deterministic topology of the satellite constellation to calculate the
minimum-delay path between any two nodes in the satellite network. But that
does not take into account the traffic information at the nodes along this
minimum-delay path. We propose a distributed probabilistic congestion control
scheme to minimize end-to-end delay. In the proposed scheme, each satellite,
while sending a packet to its neighbor, adds a header with a simple metric
indicating its own congestion level. The decision to route packets is taken
based on the latest traffic information received from the neighbors. We build
this algorithm onto the Datagram Routing Algorithm (DRA), which provides the
minimum delay path, and the decision for the next hop is taken by the
congestion control algorithm. We compare the proposed congestion control
mechanism with the existing congestion control used by the DRA via simulations,
and show improvements over the same.Comment: 9 pages, 10 figures, conferenc
Q-PAC: Automated Detection of Quantum Bug-Fix Patterns
Context: Bug-fix pattern detection has been investigated in the past in the
context of classical software. However, while quantum software is developing
rapidly, the literature still lacks automated methods and tools to identify,
analyze, and detect bug-fix patterns. To the best of our knowledge, our work
previously published in SEKE'23 was the first to leverage classical techniques
to detect bug-fix patterns in quantum code.
Objective: To extend our previous effort, we present a research agenda
(Q-Repair), including a series of testing and debugging methodologies, to
improve the quality of quantum software. The ultimate goal is to utilize
machine learning techniques to automatically predict fix patterns for existing
quantum bugs.
Method: As part of the first stage of the agenda, we extend our initial study
and propose a more comprehensive automated framework, called Q-PAC, for
detecting bug-fix patterns in IBM Qiskit quantum code. In the framework, we
develop seven bug-fix pattern detectors using abstract syntax trees, syntactic
filters, and semantic checks.
Results: To demonstrate our method, we run Q-PAC on a variety of quantum
bug-fix patterns using both real-world and handcrafted examples of bugs and
fixes. The experimental results show that Q-PAC can effectively identify
bug-fix patterns in IBM Qiskit.
Conclusion: We hope our initial study on quantum bug-fix detection can bring
awareness of quantum software engineering to both researchers and
practitioners. Thus, we also publish Q-PAC as an open-source software on
GitHub. We would like to encourage other researchers to work on research
directions (such as Q-Repair) to improve the quality of the quantum
programming.Comment: 16 pages, 2 figure
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