352 research outputs found
Utilizing biomarkers in colorectal cancer: an interview with Ajay Goel
No full text Ajay Goel speaks to Rachel Jenkins, Commissioning Editor. Ajay Goel, PhD, is a Professor and Director, Center for Gastrointestinal Research, and Director, Center for Translational Genomics and Oncology, at the Baylor Scott & White Research Institute, Baylor University Medical Center in Dallas, Texas. Dr Goel has spent more than 20 years researching cancer and has been the lead author or contributor to over 240 scientific articles published in peer-reviewed international journals and several book chapters. He is also a primary inventor on more than 15 international patents aimed at developing various biomarkers for the diagnosis, prognosis and prediction of gastrointestinal cancers. He is currently using advanced genomic and transcriptomic approaches to develop novel DNA- and miRNA-based biomarkers for the early detection of colorectal cancers. In addition, he is researching the prevention of gastrointestinal cancers using integrative and alternative approaches, including botanical products such as curcumin (from turmeric) and boswellia. Dr Goel is a member of the American Association for Cancer Research (AACR) and the American Gastroenterology Association (AGA) and is on the international editorial boards of several journals including Gastroenterology, Clinical Cancer Research, Carcinogenesis, PLoS ONE, Scientific Reports, Epigenomics, Future Medicine, Alternative Therapies in Heath and Medicine and World Journal of Gastroenterology. He is also actively involved in peer-reviewing activities for more than 100 international scientific journals and various grant review panels of various national and international funding organizations. His research has been actively funded by various private and federal organizations, including funding from the National Cancer Institute (NCI) at the NIH, American Cancer Society (ACS) and other state organizations. He has won more than dozen awards and honors, including the Union of European Gastroenterology Federation's Distinguished Researcher Award, multiple Poster of Distinction Awards from the AGA, and Visiting Professorships from various national and international academic institutions and academic bodies. Some of his key research interests include: Understanding the basic genetics and epigenetic basis of gastrointestinal cancers; Use of epigenetic markers, both DNA and RNA, for the early detection of colorectal, pancreatic and other gastrointestinal cancers; Personalized medicine and treatment of gastrointestinal cancers; Chemoprevention, using complementary and alternative approaches using nutraceuticals such as curcumin, green tea, resveratrol and other botanicals. </jats:p
Alternative technique of cervical spinal stabilization employing lateral mass plate and screw and intra-articular spacer fixation
No full textAim: The author discusses an alternative technique of segmental cervical spinal fixation. Material and Methods: The subtleties of the technique are discussed on the basis of experience with 3 cases with a follow-up of between 30 and 36 months. Technique: The technique involves debridement of facetal articular cartilage, distraction of facets, jamming of ′Goel spacer′ into the articular cavity and fortification of the fixation by lateral mass plate and screw fixation. The ′double-insurance′ method of fixation is safe for vertebral artery, nerve roots and spinal neural structures and the fixation is strong. Conclusions: The discussed technique is safe and provides a strong fixation and a ground for ultimate arthrodesis
Author Reply Re: Goel A. Research training during residency. Indian J Urol 2017;33:257-8
No full textAlkali-free bioactive glass composition, U.S. Patent 9,238,044
No full textThe present invention relates to development of bioactive glass/glass-ceramic composition that are able to promote a fast deposition layer of carbonated hydroxyapatite upon immersion in simulated body fluid (SBF) for time periods as short as one hour. Such composition might include fluorides, and a variety of oxides (or their precursor compounds), such as Na2O—Ag2O—SrO—CaO—MgO—ZnO—P2O5—SiO2—Bi2O3—B2O3—CaF2, be prepared by the melt route or by the sol-gel process, with the specific composition and the preparation route selected according to the intended functionalities, which can present controlled biodegradation rate and bactericidal activity. The powders derived from glass melts purred in cold water (frits) may completely densify by sintering at temperatures up to 800° C. without devitrification, resulting in bioglass compacts with high flexural strength (˜85 MPa). The bioactive glass powders prepared by sol-gel densify at lower temperatures due to their higher specific surface area and reactivity
Improving the Accuracy of Recommender Systems Through Annealing
No full textCollaborative filtering (CF) is the most popular approach in recommender systems (RS). It makes use of a user item rating matrix and recommends on the basis of preferences and tastes of other users. It faces a number of issues like cold start problem, shilling attack problem and sparse matrix problems. Matrix Factorization (MF) is an efficient approach to get rid of sparse matrix problems. It is a highly reliable and robust technique that helps to predict those ratings to a user for an item that are not yet rated by him. This is done by mapping items and users to a latent space based on a given number of latent features. Minimization in MF is done by either Alternating Least Squares (ALS) method or Stochastic Gradient Descent (SGD) technique.
In this thesis, SGD is used to perform minimization on the matrix factorization function using the concept of singular value decomposition (SVD) to fill in missing entries in the sparse user item rating matrix. Using this base approach, a factor known as learning rate (η) is varied to determine the accuracy and convergence rate of recommender systems. This is done by using simulated annealing, which decrements the value of learning rate in each iteration and provides an optimal solution to minimize error in the system.
In this thesis, five simulated annealing schedules, along with a new proposed annealing schedule have been chosen to discuss the effect of learning rate on the accuracy of a movie recommender system. These annealing schedules are- exponential annealing, inverse scaling logarithmic cooling, linear multiplicative cooling and quadratic multiplicative cooling. Our proposed annealing schedule is named as Square Root Cooling (SRA). The experimental results on Movielens dataset prove that by employing exponential annealing schedule as the learning rate, minimum mean absolute error can be attained for the system at a lower value of learning rate. For higher learning rate values, SRA works the best. Apache Mahout 0.9 is chosen as the platform for the research
Requirement Engineering in Component Selection
No full textM.E. (Software Engineering)In the COTS selection process, it is unavoidable to encounter mismatches between
system requirements and COTS products’ capabilities. These mismatches are the
result of the lacking COTS attributes or their overmatch with the system
requirements.
Many researchers have proposed various techniques to search and select COTS
components. But only few have worked upon the handling of mismatches. These
techniques have their own advantages and disadvantages.
This thesis work proposes a COTS selection approach that aims at addressing COTS
mismatches among COTS attributes and system requirements during the requirement
engineering phase. In this process COTS evaluation, a core activity of COTS
selection, is performed using the Goal Question Metrics (GQM) based Feature
Analysis technique. GQM based Feature Analysis is an evaluation strategy used for
measuring the compliance of the COTS capabilities with desired features using the
formulated metrics. A case-study is used to illustrate this process and to discuss its
feasibility.CSE
Improving Reliance and Efficiency in Scheduling by Development of Hybrid Intelligent Agent
No full textME, CSEDThe thesis includes the research work where it describes the development of a hybrid
intelligent agent in an android application called scheduler cum emailer. The intelligent
agents are the software programs that do some of the intelligent tasks on the human
behalf and acts as its personal assistants to whom user can rely and trust. The intelligent agents are loyal and perform all the tasks to accomplish its designed goal without any mistake. The hybrid intelligent agent developed is the combination of the three types of agents namely: Task agent, triggering agent and goal based agent. The thesis consists of the detailed study of the different types of agents which has been proposed by different researchers and developers. Also, a number of applications and services have been included to give an overview that how the intelligent agents can facilitate and automate the real life human activities by which users can perform his task more easily, timely and efficiently avoiding repetitive and mindless work. The research work includes the application’s salient features and all the intelligent tasks it performs for the user to make
the application more useful and user friendly. The application developed uses the android platform and run only on the android phones. Also the architecture of the application and the proper flow chart of the processing and execution of the algorithm are given which gives the deep insight of how the application is used and works. The application developed is user friendly, easy to use, reliable, efficient, time saving and reduces efforts
Testing Anomalies in Multiple and Multilevel Inheritance
No full textSoftware testing is an important phase of software development process that can be easily
missed by software developers because of their limited time to complete the project.
Thus, Software testing is a widely used and accepted approach for verification and
validation of a software system. One of the major challenges in software testing is the
generation of test cases that satisfy the given competence criterion. Testing in an object
oriented manner significantly increases software reusability, extendibility,
interoperability, and reliability. Object oriented testing has to deal with the new problems
to deal with the new problems introduced by the new features of Object oriented systems
such as inheritance, polymorphism, method overloading, method overriding etc. Object
oriented testing technique for testing software units that has great potential for improving
the quality of testing and to assure the high reliability of software. In this thesis, we will
focus on the features of object oriented systems that create many binding anomalies
during static and dynamic binding. This shows that a value of the variable changes with
the change in the object if there is given a wrong function call with the object of other
class. To detect such anomalies an approach is discussed that will detect static and
dynamic anomalies in multiple and multilevel inheritance
Speech Emotion Recognition Using EEMD, SVM & ANN
No full textME, CSEDEmotion recognition system from speech is one of most advanced topics in the electronic
media. Emotion detection helps the security system to prevent the data from various
attacks at the cyber world. A lot of research work has already been done into this contrast but the problem of accuracy is always there. This work has been done to categorize three emotions namely HAPPY, FEAR AND SAD using the EEMD, SVM and ANN
algorithms. In this work, noise levels are taken so that the emotion can be identified even though if the voice signal is highly noised. The aim of this work is to check the accuracy of the EEMD algorithm with noisy signals in contrast to the emotion detection. We proceed as detecting the noise level and segmenting the signal for the further processing. There are two segments: first part is the training part in which the system is trained to identify the further proceedings. In this part, samples of each voice category are taken and their features are fetched after successful segmentation of the voice file and further on saved into the database. The second part is the testing part in which a voice sample is
taken and all the required properties are fetched and matched with the saved database
values. The closest match comes out as the category of the voice file
An Approach for Improving Accuracy of Prediction Using Ensemble Modeling
No full textM.E. (CSED)In general terms classification can be divided into two steps. First one is learning step which
consists of the predetermined set of classes or concepts. Second step involves testing, in
which data sets are being tested for the verification. And after the system is trained with data
it can be used for further analysis to be done in future so that future events can be predicted in
advance. For different applications we need to apply these models to predict and note the
accuracy given by each model. The main aim of the research here is to make such a system
which has more accuracy as compared to what previous systems are giving. So to implement
this type of system, a hybrid approach is used i.e. ensemble of classifiers. It is necessary that
one does not weigh one model purely. Other models or methods can also give more efficient
results. In doing so, give weightage to each method and combine these methods to reach final
destination that is most informed one. There are a large number of models available which
are used for classifying the data into various class labels. That is also known under various other names, such as multiple classifier systems, committee of lassifiers, or mixture of experts. The basic aim of ensemble based systems is shown to produce favourable results compared to those of single-expert systems for a broad range of applications and under a variety of scenarios. There are various procedures available through which the individual classifiers can be combined. These procedures are called as combination rules. Each rule has its different functionality which will work according to requirement and application where it is applied. So the study is carried on the prediction by applying methods and ensemble that with variable seed values. The experiment is carried out on the k-fold validation to check the consistency of the system
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