Spelling suggestions: "subject:"subsample"" "subject:"subsamples""
21 |
Evaluation of performance of MSI detection tools using targeted sequencing dataKolluri, Satya Krishna Prasanna January 2021 (has links)
In recent years, digitalization and computer-based technologies have greatly revolutionized the field of bioinformatics. Advance research and development of computer-based programs have enhanced various DNA sequencing technologies. This advancement has significantly broadened our understanding of genomic evolution and has widely contributed to the application of clinical genomics. Cancer has been one of the major causes of death across the world. Cancer is mainly caused due to the damage or changes in DNA that affect the function of genes which contain a set of instructions that control various functions of cells. This damage in genes that maintain DNA repair mechanism may lead towards genome instability allowing rapid growth of cancer. Microsatellite instability (MSI) is one such condition characterized due to genomic alteration leading towards the failure of DNA repair mechanism in cancerous cells. MSI is found in various types of cancer but is most often found in colorectal cancer, gastric cancer, and endometrial cancer. Hence, detection of this MSI can greatly contribute towards cancer therapies and enable to plan for the best treatment. This study mainly focuses on evaluating the performance of MSI calling algorithms using targeted sequencing methods. The literature provides a detailed outline of various topics related to MSI detection. Moreover, different computational methods like MSIsensor, MSIsensor-ct, MSIsensor-pro, MSings, MiMSI, and MSIsensor2 were used in this study for the detection of MSI in selected samples are thoroughly discussed in the methodology section. Finally, the findings of this study conclude that the MSI calling algorithms mentioned above provide accurate detection of MSI in the chosen samples. Also, these algorithms enable us to determine the MSI status of the chosen samples more precisely
|
22 |
Subsampling Strategies for Bayesian Variable Selection and Model Averaging in GLM and BGNLMLachmann, Jon January 2021 (has links)
Bayesian Generalized Nonlinear Models (BGNLM) offer a flexible alternative to GLM while still providing better interpretability than machine learning techniques such as neural networks. In BGNLM, the methods of Bayesian Variable Selection and Model Averaging are applied in an extended GLM setting. Models are fitted to data using MCMC within a genetic framework in an algorithm called GMJMCMC. In this thesis, we present a new implementation of the algorithm as a package in the programming language R. We also present a novel algorithm called S-IRLS-SGD for estimating the MLE of a GLM by subsampling the data. Finally, we present some theory combining the novel algorithm with GMJMCMC/MJMCMC/MCMC and a number of experiments demonstrating the performance of the contributed algorithm.
|
23 |
Vodoznačení statických obrazů / Watermarking of static imagesBambuch, Petr January 2008 (has links)
The thesis deals with the security of static images. The main aim is to embed the watermark into the original data so effectively, to avoid removal of the watermark with the use of simple and fast attacks methods. With developing of the watermarking techniques the technique of attacks are improved and developed also. The main aim of the attacks is to remove and devalue the hidden watermark in the image. The goal of the thesis is to check current techniques of static image watermarking and implement two methods of watermarking, which are to be tested for robustness against attacks.
|
24 |
Handling Complexity via Statistical MethodsEvidence S Matangi (8082623) 05 December 2019 (has links)
<p>Phenomena investigated from complex systems are
characteristically dynamic, multi-dimensional, and nonlinear. Their traits can be captured through data
generating mechanisms (<i>DGM</i>) that
explain the interactions among the systems’ components. Measurement is fundamental to advance science,
and complexity requires deviation from linear thinking to handle. Simplifying the measurement of complex and
heterogeneous data in statistical methodology can compromise their accuracy. In particular, conventional statistical methods
make assumptions on the DGM that are rarely met in real world, which can make inference
inaccurate. We posit that causal
inference for complex systems phenomena requires at least the incorporation of
subject-matter knowledge and use of dynamic metrics in statistical methods to improve
on its accuracy.</p>
<p>This thesis consists of two separate topics on handling data
and data generating mechanisms complexities, the evaluation of bundled
nutrition interventions and modeling atmospheric data.</p>
<p>Firstly, when a public health problem requires multiple ways
to address its contributing factors, bundling of the approaches can be cost-effective. Scaling up bundled interventions geographically
requires a hierarchical structure in implementation, with central coordination
and supervision of multiple sites and staff delivering a bundled intervention. The experimental design to evaluate such an
intervention becomes complex to accommodate the multiple intervention
components and hierarchical implementation structure. The components of a bundled intervention may
impact targeted outcomes additively or synergistically. However, noncompliance
and protocol deviation can impede this potential impact, and introduce data
complexities. We identify several statistical considerations and recommendations
for the implementation and evaluation of bundled interventions. </p>
<p>The simple aggregate metrics used in clustering randomized
controlled trials do not utilize all available information, and findings are
prone to the ecological fallacy problem, in which inference at the aggregate
level may not hold at the disaggregate level.
Further, implementation heterogeneity impedes statistical power and
consequently the accuracy of the inference from conventional comparison with a control
arm. The intention-to-treat analysis can be inadequate for bundled
interventions. We developed novel process-driven,
disaggregated participation metrics to examine the mechanisms of impact of the
Agriculture to Nutrition (ATONU) bundled intervention (ClinicalTrials.gov
Identifier: NCT03152227). Logistic and beta-logistic hierarchical models were
used to characterize these metrics, and generalized mixed models were employed
to identify determinants of the study outcome, dietary diversity for women of
reproductive age. Mediation analysis was
applied to explore the underlying determinants by which the intervention affects
the outcome through the process metrics. The determinants of greater participation
should be the targets to improve implementation of future bundled interventions.</p>
<p>Secondly, observed atmospheric records are often
prohibitively short with only one record typically available for study. Classical
nonlinear time series models applied to explain the nonlinear DGM exhibit some
statistical properties of the phenomena being investigated, but have nothing to
do with their physical properties. The data’s complex dependent structure
invalidates inference from classical time series models involving strong
statistical assumptions rarely met in real atmospheric and climate data. The subsampling method may yield valid statistical
inference. Atmospheric records, however, are typically too short to satisfy<i> </i>asymptotic conditions for the method’s
validity, which necessitates enhancements of subsampling with the use of
approximating models (those sharing statistical properties with the series
under study). </p>
<p>Gyrostat models (<i>G-models</i>)
are physically sound low-order models generated from the governing equations
for atmospheric dynamics thus retaining some of their fundamental statistical
and physical properties. We have demonstrated statistic that using G-models as
approximating models in place of traditional time series models results in more
precise subsampling confidence intervals with improved coverage probabilities.
Future works will explore other types of G-models as approximating models for
inference on atmospheric data. We will adopt this technique for inference on phenomena
for AstroStatistics and pharmacokinetics. </p>
|
25 |
Collective Spiking Dynamics in Cortical NetworksWilting, Jens 24 September 2020 (has links)
No description available.
|
26 |
Towards Building a High-Performance Intelligent Radio Network through Deep Learning: Addressing Data Privacy, Adversarial Robustness, Network Structure, and Latency Requirements.Abu Shafin Moham Mahdee Jameel (18424200) 26 April 2024 (has links)
<p dir="ltr">With the increasing availability of inexpensive computing power in wireless radio network nodes, machine learning based models are being deployed in operations that traditionally relied on rule-based or statistical methods. Contemporary high bandwidth networks enable easy availability of significant amounts of training data in a comparatively short time, aiding in the development of better deep learning models. Specialized deep learning models developed for wireless networks have been shown to consistently outperform traditional methods in a variety of wireless network applications.</p><p><br></p><p dir="ltr">We aim to address some of the unique challenges inherent in the wireless radio communication domain. Firstly, as data is transmitted over the air, data privacy and adversarial attacks pose heightened risks. Secondly, due to the volume of data and the time-sensitive nature of the processing that is required, the speed of the machine learning model becomes a significant factor, often necessitating operation within a latency constraint. Thirdly, the impact of diverse and time-varying wireless environments means that any machine learning model also needs to be generalizable. The increasing computing power present in wireless nodes provides an opportunity to offload some of the deep learning to the edge, which also impacts data privacy.</p><p><br></p><p dir="ltr">Towards this goal, we work on deep learning methods that operate along different aspects of a wireless network—on network packets, error prediction, modulation classification, and channel estimation—and are able to operate within the latency constraint, while simultaneously providing better privacy and security. After proposing solutions that work in a traditional centralized learning environment, we explore edge learning paradigms where the learning happens in distributed nodes.</p>
|
27 |
Pricing of bonds and credit default swaps: Evidence from a panel of European companiesSmotlachová, Eva January 2016 (has links)
The aim of the thesis is to investigate determinants of corporate bond and CDS contract pricing using a sample of 34 European companies over the period 2008-2014. This work extends existing literature by studying differences in determinants of bond and CDS spreads not only for different time periods, but also for different sets of companies grouped by geography, industry, and profitability. The results reveal that bond and CDS spreads are generally influenced by similar factors, with a company's credit rating being the most influential factor. Nevertheless, the investigation of time-specific estimations suggests that firm-specific factors play a more significant role in pricing bonds, whereas market factors have a higher impact on CDS spreads. The analysis of the subsamples reveals substantial differences in regression results for individual groups of companies, which suggests a presence of idiosyncratic factors. Our conclusion is that the pricing of bonds and CDS contracts is not only time-dependent, but also unique for different groups of companies, which implies a necessity to use different pricing models for individual contracts.
|
28 |
Technologies and design methods for a highly integrated AIS transponder / Teknologier och design metoder för en högintegrerad AIS transponderRamquist, Henrik January 2003 (has links)
<p>The principle of universal shipborne automatic identification system (AIS) is to allow automatic exchange of shipboard information between one vessel and another. Saab TransponderTech AB has an operating AIS transponder on the market and the purpose of this report is to investigate alternative technologies that could result in a highly integrated replacement for the existing hardware. </p><p>Design aspects of a system-on-chip are discussed, such as: available system-on- chip technologies, intellectual property, on-chip bus structures and development tools. This information is applied to the existing hardware and the integration possibilities of the various parts of the AIS transponder is investigated. </p><p>The focus will be on two main transponder parts that are possible to replace with highly integrated circuits. The first of these parts is the so-called digital part where system-on-chip platforms for different technologies have been investigated with a special interest in a highly integrated FPGA implementation. The second part is the radio frequency receivers where alternatives to the existing superheterodyne receiver are discussed. </p><p>The conclusion drawn is that there exist technologies for developing a highly integrated AIS transponder. An attractive highly integrated transponder could consist of a FPGA system-on-chip platform with subsampling digital receivers and additional components that are unsuitable for integration.</p>
|
29 |
Technologies and design methods for a highly integrated AIS transponder / Teknologier och design metoder för en högintegrerad AIS transponderRamquist, Henrik January 2003 (has links)
The principle of universal shipborne automatic identification system (AIS) is to allow automatic exchange of shipboard information between one vessel and another. Saab TransponderTech AB has an operating AIS transponder on the market and the purpose of this report is to investigate alternative technologies that could result in a highly integrated replacement for the existing hardware. Design aspects of a system-on-chip are discussed, such as: available system-on- chip technologies, intellectual property, on-chip bus structures and development tools. This information is applied to the existing hardware and the integration possibilities of the various parts of the AIS transponder is investigated. The focus will be on two main transponder parts that are possible to replace with highly integrated circuits. The first of these parts is the so-called digital part where system-on-chip platforms for different technologies have been investigated with a special interest in a highly integrated FPGA implementation. The second part is the radio frequency receivers where alternatives to the existing superheterodyne receiver are discussed. The conclusion drawn is that there exist technologies for developing a highly integrated AIS transponder. An attractive highly integrated transponder could consist of a FPGA system-on-chip platform with subsampling digital receivers and additional components that are unsuitable for integration.
|
30 |
Direktsamplande digital transciever / Direct sampling digital transceiverKarlsson, Magnus January 2002 (has links)
<p>Master thesis work at ITN (Department of Science and Technology) in the areas of A/D-construction and RF-circuit design. Major goal of project were to research suitable possibilities for implementations of direct conversion in transceivers operating in the 160MHz band, theoretic study followed by development of components in the construction environment Cadence. Suitable A/D- converter and other important parts were selected at the end of the theoretic study. Subsampling technique was applied to make A/D sample requirements more realistic to achieve. Besides lowering requirements on A/D-converter it allows a more simple construction, which saves more components than subsampling adds. Subsampling add extra noise, because of that an A/D-converter based on the RSD algorithm was chosen to improve error rate. To achieve high bit-processing rate compared to the used number of transistors, pipeline structure were selected as conversion method. The receiver was that part which gained largest attention because it’s the part which is most interesting to optimise. A/D-conversion is more difficult to construct than D/A conversion, besides there’s more to gain from eliminating mixers in the receiver than in the transmitter.</p>
|
Page generated in 0.0674 seconds