5,246 research outputs found
Phase I study evaluating oral panobinostat concurrently with radiotherapy or chemoradiotherapy in inoperable stage IIIA/B non-small cell lung cancer patients
No full textPoster AbstractH. Takhar, N. Singhal, R. Gowda, M. Penniment, M. P. Brow
Efficient Distributed Detection Of Conjunctions Of Local Predicates M. Hurfin M. Mizuno M. Raynal M. Singhal
No full text: Global predicate detection is a fundamental problem in distributed systems and finds applications in many domains such as testing and debugging distributed programs. This paper presents two efficient distributed algorithms to detect conjunctive form global predicates in distributed systems. The algorithms detect the first consistent global state that satisfies the predicate even if the predicate is unstable. The algorithms are based on complementary approaches and are dual of each other. The algorithms are distributed because the predicate detection efforts as well as the necessary information is equally distributed among the processes. We prove the correctness of the algorithms and compare their performance with those of the existing predicate detection algorithms. The proposed algorithms compare very favorably with the existing algorithms in terms of the number of messages exchanged for predicate detection. Key-words: Distributed systems, On the fly global predicate detection (R'..
Organizing for Social Change: A Dialectic Journey of Theory and Praxis
No full textPapa, M. J., Singhal, A., & Papa, W. H. (2006). Organizing for social change : a dialectic journey of theory and praxis. New Delhi ; Thousand Oaks : Sage Publications, 2006
Cytokine levels in major depression are related to childhood trauma but not to recent stressors
No full textAbstract not availableLaura Grosse, Oliver Ambrée, Silke Jörgens, M. Catharine Jawahar, Gaurav Singhal, David Stacey, Volker Arolt, Bernhard T. Baun
sj-docx-1-jct-10.1177_23800844221074354 – Supplemental material for Effect of Overweight and Obesity on Periodontal Treatment Intensity
No full textSupplemental material, sj-docx-1-jct-10.1177_23800844221074354 for Effect of Overweight and Obesity on Periodontal Treatment Intensity by E. Kaye, R. McDonough, A. Singhal, R.I. Garcia and M. Jurasic in JDR Clinical & Translational Research</p
Joint failure recovery, fault prevention, and energy-efficient resource management for real-time SFC in fog-supported SDN
No full textMiddleboxes have become a vital part of modern networks by providing services such as load balancing, optimization of network traffic, and content filtering. A sequence of middleboxes comprising a logical service is called a Service Function Chain (SFC). In this context, the main issues are to maintain an acceptable level of network path survivability and a fair allocation of the resource between different demands in the event of faults or failures. In this paper, we focus on the problems of traffic engineering, failure recovery, fault prevention, and SFC with reliability and energy consumption constraints in Software Defined Networks (SDN). These types of deployments use Fog computing as an emerging paradigm to manage the distributed small-size traffic flows passing through the SDN-enabled switches (possibly Fog Nodes). The main aim of this integration is to support service delivery in real-time, failure recovery, and fault-awareness in an SFC context. Firstly, we present an architecture for Failure Recovery and Fault Prevention called FRFP; this is a multi-tier structure in which the real-time traffic flows pass through SDN-enabled switches to jointly decrease the network side-effects of flow rerouting and energy consumption of the Fog Nodes. We then mathematically formulate an optimization problem called the Optimal Fog-Supported Energy-Aware SFC rerouting algorithm (OFES) and propose a near-optimal heuristic called Heuristic OFES (HFES) to solve the corresponding problem in polynomial time. In this way, the energy consumption and the reliability of the selected paths are optimized, while the Quality of Service (QoS) constraints are met and the network congestion is minimized. In a reliability context, the focus of this work is on fault prevention; however, since we use a reallocation technique, the proposed scheme can be used as a failure recovery scheme. We compare the performance of HFES and OFES in terms of energy consumption, average path length, fault probability, network side-effects, link utilization, and Fog Node utilization. Additionally, we analyze the computational complexity of HFES. We use a real-world network topology to evaluate our algorithm. The simulation results show that the heuristic algorithm is applicable to large-scale networks. (C) 2019 Elsevier B.V. All rights reserved
Understanding the importance of side information in graph matching problem
No full textGraph matching algorithms rely on the availability of seed vertex pairs as side information to deanonymize users across networks. Although such algorithms work well in practice, there are other types of side information available which are potentially useful to an attacker. In this thesis, we consider the problem of matching two correlated graphs when an attacker has access to side information either in the form of community labels or an imperfect initial matching. First, we propose a naive graph matching algorithm by introducing the community degree vectors which harness the information from community labels in an e cient manner. Next, we analyze the basic percolation algorithm for graphs with community structure. Finally, we propose a novel percolation algorithm with two thresholds which uses an imperfect matching as input to match correlated graphs. We also analyze these algorithms and provide theoretical guarantees for matching graphs generated using the Stochastic Block Model.
We evaluate the proposed algorithms on synthetic as well as real world datasets using various experiments. The experimental results demonstrate the importance of communities as side information especially when the number of seeds is small and the networks are weakly correlated. These results motivate the study of other types of potential side information available to the attacker. Such studies could assist in devising mechanisms to counter the effects of side information in network deanonymization.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2018-12-01The student, Kushagra Singhal, accepted the attached license on 2016-11-22 at 11:10.The student, Kushagra Singhal, submitted this Thesis for approval on 2016-11-22 at 11:16.This Thesis was approved for publication on 2016-11-22 at 12:00.DSpace SAF Submission Ingestion Package generated from Vireo submission #10224 on 2017-02-28 at 14:36:15Made available in DSpace on 2017-03-01T16:36:46Z (GMT). No. of bitstreams: 2
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Previous issue date: 2016-11-22Embargo set by: Seth Robbins for item 98583
Lift date: 2019-03-01T16:37:19Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Only Restriction Lifted for Item 98583 on 2019-03-02T10:15:33Z
Heat resistant steels in steam turbine
No full textThe production of large capacity steam turbines is a recent development in the Indian industries and the metallurgical industry is not yet geared up to meet the special requirements of steam turbine materials. The present difficulties in procuring the turbine materials from foreign sources and recent unfavourable trends of international markets pose a real problem to turbine manufacturers. By and large the necessity of developing the turbine materials within the country is being felt very strongly. The paper deals with the functional and technical requirements and selection criteria of heat resistant steels for steam turbines. To facilitate the development of materials, a brief account of metallurgical aspects is also given in the paper. (K.K. Gupta, K.M. Singhal, M/s Bharat Heavy Electricals Ltd. Hardwar
A new framework of optimizing keyword weights in text categorization and record querying
No full textIn text mining research, the Vector Space Model (VSM) has been commonly used to represent text documents as a vector where each component is associated with a particular word in the documents. Assigning appropriate keyword weights in VSM has been critical in Information Retrieval (IR) and Text Categorization (TC).
Traditionally keyword weighting processes are unsupervised; that is, the knowledge of document's category is not leveraged to label the documents. Typically, each keyword weight is assigned using the term frequency -- inverse document frequency (TFIDF) measure. Although the TFIDF measure has been proven effective in several text mining problems, it might not give the optimal classification power for IR and TC. In this thesis, we propose a new optimization framework to find the best keyword weights based on the proposed inter-class and intra-class similarity concept.
The optimal keyword weight can be viewed as the feature space projection where documents from the same category are best clustered together and separated from other categories. Subsequently, the category average (centroid) classification is employed to categorize text documents. The proposed approach is tested on two practical applications: record query and text categorization. The record query application is slightly different from traditional IR problems as the goal is to find correlated (duplicate and master) text records. This problem was initiated by a telecommunication company where service engineers attempt to look for associations of the current defect problem in previously recorded problems in the database. Extensive experiments demonstrate that the proposed framework significantly improves the classification accuracy and provides balanced performance as measured on all text categories when compared to the standard TFIDF search. The text categorization application is tested on the Reuters news data set which is a gold-standard benchmark data set. The results show that our framework improves performance for the two applications considered, namely Information Retrieval and Text Categorization.M.S.Includes bibliographical references (p. 80-83)
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