175 research outputs found
Transoral Incisionless Fundoplication for Refractory Gastroesophageal Reflux Disease: Where Do We Stand?
No full textGastroesophageal reflux disease (GERD) is a chronic, progressive, and costly medical condition affecting a substantial proportion of the world population, predominantly the Western population. The available treatment options for patients with refractory GERD symptoms are limited to either laparoscopic surgery with significant sequelae or potentially lifelong, high-dose proton pump inhibitor therapy. The restoration of the antireflux competence of the gastroesophageal junction at the anatomic and physiologic levels is critical for the effective long-term treatment of GERD. Transoral incisionless fundoplication (TIF) surgery is a safe, well-tolerated, and effective treatment that has yielded significant symptomatic improvement in patients with medically refractory GERD symptoms. In this review article, we have summarized case series and reports describing the role of TIF for patients with gastroesophageal reflux symptoms. The reported indications, techniques, complications, and success rates are also discussed
Esophageal Stricture Prevention after Endoscopic Submucosal Dissection
No full textAdvances in diagnostic modalities and improvement in surveillance programs for Barrett esophagus has resulted in an increase in the incidence of superficial esophageal cancers (SECs). SEC, due to their limited metastatic potential, are amenable to non-invasive treatment modalities. Endoscopic ultrasound, endoscopic mucosal resection, and endoscopic submucosal dissection (ESD) are some of the new modalities that gastroenterologists have used over the last decade to diagnose and treat SEC. However, esophageal stricture (ES) is a very common complication and a major cause of morbidity post-ESD. In the past few years, there has been a tremendous effort to reduce the incidence of ES among patients undergoing ESD. Steroids have shown the most consistent results over time with minimal complications although the preferred mode of delivery is debatable, with both systemic and local therapy having pros and cons for specific subgroups of patients. Newer modalities such as esophageal stents, autologous cell sheet transplantation, polyglycolic acid, and tranilast have shown promising results but the depth of experience with these methods is still limited. We have summarized case reports, prospective single center studies, and randomized controlled trials describing the various methods intended to reduce the incidence of ES after ESD. Indications, techniques, outcomes, limitations, and reported complications are discussed
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
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)
Evaluation of UML based wireless network virtualization
No full textVirtualization of wireless networks is recognized to be a difficult problem due to the fact that radios interact with their neighbors at various layers of the protocol stack, making strict isolation of virtual networks ("or slices") quite challenging. The goal of virtualization is to support concurrent experiments, both long-running services as well as short-term experiments on shared wireless network. In a wireless network, the radio resources that can be shared and hence virtualized are in time, space and frequency. Efforts have been going on to modify the ORBIT control structure to accommodate different forms of virtualization including VMAC, SDMA, FDMA and TDMA. Among different possible wireless virtualization techniques, this work is focused on allowing a node to run more than one experiment simultaneously using different frequencies i.e. Frequency Division Multiplexing (FDM). Each node in the ORBIT test bed is provided with two physical wireless cards. FDMA virtualization is achieved by running two concurrent User Level Operating Systems (ULOS) on each node and providing each operating system access to a radio card. Thus an experimental end user would view a single node as two virtual nodes, each equipped with one wireless card.
Experimental results are provided to compare the performance of a virtualized radio node with the non virtualized one for basic point-to-point experiments using TCP and UDP. Bounds on performance metrics of throughput, delay and jitter are determined and cross-coupling effects between two virtualized experiments are examined. We also look at transient behavior associated with sudden changes in traffic on one of the virtual networks. Finally, the uncertainty in performance measurements for a few typical usage scenarios is investigated, leading to guidelines for use of virtualized radio nodes for simultaneous ORBIT experiments.M.S.Includes bibliographical references (p. 44-45)
Colonoscopy for Colorectal Cancer Screening Above Age 75: Outcomes in Symptomatic African American and Hispanic Adults
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