Computationally highly efficient mixture of adaptive filters

We introduce a new combination approach for the mixture of adaptive filters based on the set-membership filtering (SMF) framework. We perform SMF to combine the outputs of several parallel running adaptive algorithms and propose unconstrained, affinely constrained and convexly constrained combination weight configurations. Here, we achieve better trade-off in terms of the transient and steady-state convergence performance while providing significant computational reduction. Hence, through the introduced approaches, we can greatly enhance the convergence performance of the constituent filters with a slight increase in the computational load. In this sense, our approaches are suitable for big data applications where the data should be processed in streams with highly efficient algorithms. In the numerical examples, we demonstrate the superior performance of the proposed approaches over the state of the art using the well-known datasets in the machine learning literature.     

Automatic detection and quantification of tree-in-bud (TIB) opacities from CT scans

This study presents a novel computer-assisted detection (CAD) system for automatically detecting and precisely quantifying abnormal nodular branching opacities in chest computed tomography (CT), termed tree-in-bud (TIB) opacities by radiology literature. The developed CAD system in this study is based on 1) fast localization of candidate imaging patterns using local scale information of the images, and 2) M?bius invariant feature extraction method based on learned local shape and texture properties of TIB patterns. For fast localization of candidate imaging patterns, we use ball-scale filtering and, based on the observation of the pattern of interest, a suitable scale selection is used to retain only small size patterns. Once candidate abnormality patterns are identified, we extract proposed shape features from regions where at least one candidate pattern occupies. The comparative evaluation of the proposed method with commonly used CAD methods is presented with a dataset of 60 chest CTs (laboratory confirmed 39 viral bronchiolitis human parainfluenza CTs and 21 normal chest CTs). The quantitative results are presented as the area under the receiver operator characteristics curves and a computer score (volume affected by TIB) provided as an output of the CAD system. In addition, a visual grading scheme is applied to the patient data by three well-trained radiologists. Interobserver and observer-computer agreements are obtained by the relevant statistical methods over different lung zones. Experimental results demonstrate that the proposed CAD system can achieve high detection rates with an overall accuracy of 90.96%. Moreover, correlations of observer-observer (R(2)=0.8848, and observer-CAD agreements (R(2)=0.824, validate the feasibility of the use of the proposed CAD system in detecting and quantifying TIB patterns.     

Completeness in Two-Party Secure Computation: A Computational View

A Secure Function Evaluation (SFE) of a two-variable function f(·,·) is a protocol that allows two parties with inputs x and y to evaluate f(x,y) in a manner where neither party learns "more than is necessary". A rich body of work deals with the study of completeness for secure two-party computation. A function f is complete for SFE if a protocol for securely evaluating f allows the secure evaluation of all (efficiently computable) functions. The questions investigated are which functions are complete for SFE, which functions have SFE protocols unconditionally and whether there are functions that are neither complete nor have efficient SFE protocols. The previous study of these questions was mainly conducted from an information theoretic point of view and provided strong answers in the form of combinatorial properties. However, we show that there are major differences between the information theoretic and computational settings. In particular, we show functions that are considered as having SFE unconditionally by the combinatorial criteria but are actually complete in the computational setting. We initiate the fully computational study of these fundamental questions. Somewhat surprisingly, we manage to provide an almost full characterization of the complete functions in this model as well. More precisely, we present a computational criterion (called computational row non-transitivity) for a function f to be complete for the asymmetric case. Furthermore, we show a matching criterion called computational row transitivity for f to have a simple SFE (based on no additional assumptions). This criterion is close to the negation of the computational row non-transitivity and thus we essentially characterize all "nice" functions as either complete or having SFE unconditionally.     

Polymeric Nanoparticles as a Self-Adjuvanting Peptide Vaccine Delivery System: The Role of Shape

Antigens incorporated in subunit vaccines are typically poorly immunogenic, so a strong immunostimulant (adjuvant) and/or delivery system is required to boost immunogenicity. In this work, the various functional polymer nanostructures, that is, rods, worms, spheres, and tadpoles are used to develop potent peptide antigen delivery systems. The antigen PADRE-J8 (PJ8), derived from Group A Streptococcus (GAS) M-protein, is either physically mixed or chemically conjugated to polymeric nanoparticles of different shapes. The physical mixture of polymeric nanoparticles and antigen is more effective in inducing antibody production than their chemical conjugates. Moreover, rod-shaped polymeric nanoparticles in physical mixture with PJ8 elicited higher and more opsonic antibody titers than powerful complete Freund's adjuvant (CFA)-adjuvanted antigen. Herein, for the first time it is demonstrated that a) the block copolymer, in nanoparticle form, can act as an immune adjuvant, b) nanoparticle shape plays a crucial role in their immunogenicity, and c) antigen conjugation is not required, nor is antigen encapsulation or absorption.     

A 2-D orientation-adaptive prediction filter in lifting structures for image coding.

Lifting-style implementations of wavelets are widely used in image coders. A two-dimensional (2-D) edge adaptive lifting structure, which is similar to Daubechies 5/3 wavelet, is presented. The 2-D prediction filter predicts the value of the next polyphase component according to an edge orientation estimator of the image. Consequently, the prediction domain is allowed to rotate +/-45 degrees in regions with diagonal gradient. The gradient estimator is computationally inexpensive with additional costs of only six subtractions per lifting instruction, and no multiplications are required.     

Determining optimum carob powder adsorbtion for cleaning wastewater: intelligent optimization with electro-search algorithm

Wireless Networks - In this study, effective and fast removal efficiency of carob powder (as an absorbent material from liquid phase) was investigated by focusing on the dangerous paint methylene...     

Analysis of individual platelet-derived microparticles,comparing flow cytometry and capillary electrophoresis with laser-induced fluorescence detection

Platelet-derived microparticles (PMPs) formed by vesiculation during platelet activation seem to play a role in blood coagulation and in pathological disease states. Flow cytometry is currently the gold standard to characterize platelets and PMPs. Using this technique we distinguished between platelets and PMPs based on size and the presence of phosphatidyl serine (PS); PMPs were arbitrarily defined to be smaller than one micrometer and capable of forming a stable complex with fluorescently-labeled Annexin V, a protein that forms a calcium-dependent complex with PS. Further confirmation of PMP and platelet identity was done by use of fluorescently-labeled antibodies against CD41a, a glycoprotein found on the surface of both platelets and PMPs. In this report we also introduce the use of capillary electrophoresis with post-column laser-induced fluorescence detection (CE-LIF) for the analysis of fluorescently labeled platelets and PMPs. While both flow cytometry and CE-LIF can measure individual fluorescent events, only CE-LIF allowed us to calculate individual electrophoretic mobilities of activated platelets and PMPs that were then represented as distributions. A comparison between distributions suggests that PMPs have less negative mobilities. The fact that activated platelet preparations include PMPs partially obscure the interpretation of the data. While PMP and platelet number ml(-1) determined by flow cytometry is lower than the same parameter determined by CE-LIF, signal-to-noise ratio was 20 fold better for flow cytometry than for CE-LIF. This is the first time that a direct comparison between these two techniques is reported.