Fast Robust Pattern Classification Algorithms for Real Time Neuro-Motor Prosthetic Applications

In this paper, we give a brief review of pattern classification algorithms based on discriminant analysis. We then apply these algorithms to classify movement direction based on multivariate local field potentials recorded from a microelectrode array in the primary motor cortex of a monkey performing a reaching task. We obtain prediction accuracies between 55% and 90% using different methods which are significantly above the chance level of 12.5%.

Urban Sprawl Pattern Analysis Using GIS

Urbanisation has evinced interest from a wide section of the society including experts, amateurs, and novices. The multidisciplinary scope of the subject invokes the interest from ecologists, to urban planners and civil engineers, to sociologists, to administrators and policy makers, students and finally the common man. With the development and infrastructure initiatives mostly around the urban centres, the impacts of urbanisation and sprawl would be on the environment and the natural resources. The wisdom lies in how effectively we plan the urban growth without - hampering the environment, excessively harnessing the natural resources and eventually disturbing the natural set-up. The research on these help urban residents and policymakers make informed decisions and take action to restore these resources before they are lost. Ultimately the power to balance the urban ecosystems rests with regional awareness, policies, administration practices, management issues and operational problems. This publication on urban systems is aimed at helping scientists, policy makers, engineers, urban planners and ultimately the common man to visualise how towns and cities grow over a period of time based on investigations in the regions around the highway and cities. Two important highways in Karnataka, South India, viz., Bangalore - Mysore highway and the Mangalore - Udupi highway, in Karnataka and the Tiruchirapalli - Tanjavore - Kumbakonam triangular road network in Tamil Nadu, South India, were considered in this investigation. Geographic Information System and Remote Sensing data were used to analyse the pattern of urbanisation. This was coupled with the spatial and temporal data from the Survey of India toposheets (for 1972), satellite imageries procured from National Remote Sensing Agency (NRSA) (LANDSAT TM for 1987 and IRS LISS III for 1999), demographic details from the Census of India (1971, 1981, 1991 and 2001) and the village maps from the Directorate of Survey Settlements and Land Records, Government of Karnataka. All this enabled in quantifying the increase in the built-up area for nearly three decades. With intent of identifying the potential sprawl zones, this could be modelled and projected for the future decades. Apart from these the study could quantify some of the metrics that could be used in the study of urban sprawl.

On pattern oriented software architecture for the grid

Precision, sophistication and economic factors in many areas of scientific research that demand very high magnitude of compute power is the order of the day. Thus advance research in the area of high performance computing is getting inevitable. The basic principle of sharing and collaborative work by geographically separated computers is known by several names such as metacomputing, scalable computing, cluster computing, internet computing and this has today metamorphosed into a new term known as grid computing. This paper gives an overview of grid computing and compares various grid architectures. We show the role that patterns can play in architecting complex systems, and provide a very pragmatic reference to a set of well-engineered patterns that the practicing developer can apply to crafting his or her own specific applications. We are not aware of pattern-oriented approach being applied to develop and deploy a grid. There are many grid frameworks that are built or are in the process of being functional. All these grids differ in some functionality or the other, though the basic principle over which the grids are built is the same. Despite this there are no standard requirements listed for building a grid. The grid being a very complex system, it is mandatory to have a standard Software Architecture Specification (SAS). We attempt to develop the same for use by any grid user or developer. Specifically, we analyze the grid using an object oriented approach and presenting the architecture using UML. This paper will propose the usage of patterns at all levels (analysis. design and architectural) of the grid development.

Pattern recognition and cellular immune responses to novel Mycobacterium tuberculosis-antigens in individuals from Belarus

Background: Tuberculosis (TB) is an enduring health problem worldwide and the emerging threat of multidrug resistant (MDR) TB and extensively drug resistant (XDR) TB is of particular concern. A better understanding of biomarkers associated with TB will aid to guide the development of better targets for TB diagnosis and for the development of improved TB vaccines. Methods: Recombinant proteins (n = 7) and peptide pools (n = 14) from M. tuberculosis (M.tb) antigens associated with M.tb pathogenicity, modification of cell lipids or cellular metabolism, were used to compare T cell immune responses defined by IFN-gamma production using a whole blood assay (WBA) from i) patients with TB, ii) individuals recovered from TB and iii) individuals exposed to TB without evidence of clinical TB infection from Minsk, Belarus. Results: We identified differences in M.tb target peptide recognition between the test groups, i.e. a frequent recognition of antigens associated with lipid metabolism, e.g. cyclopropane fatty acyl phospholipid synthase. The pattern of peptide recognition was broader in blood from healthy individuals and those recovered from TB as compared to individuals suffering from pulmonary TB. Detection of biologically relevant M.tb targets was confirmed by staining for intracellular cytokines (IL-2, TNF-alpha and IFN-gamma) in T cells from non-human primates (NHPs) after BCG vaccination. Conclusions: PBMCs from healthy individuals and those recovered from TB recognized a broader spectrum of M.tb antigens as compared to patients with TB. The nature of the pattern recognition of a broad panel of M.tb antigens will devise better strategies to identify improved diagnostics gauging previous exposure to M.tb; it may also guide the development of improved TB-vaccines.

PAMAM Dendrimer-Drug Interactions: Effect of pH on the Binding and Release Pattern

Understanding the dendrimer-drug interaction is of great importance to design and optimize the dendrimer-based drug delivery system. Using atomistic molecular dynamics (MD) simulations, we have analyzed the release pattern of four ligands (two soluble drugs, namely, salicylic acid (Sal), L-alanine (Ala), and two insoluble drugs, namely, phenylbutazone (Pbz) and primidone (Prim)), which were initially encapsulated inside the ethylenediamine (EDA) cored polyamidoamine (PAMAM) dendrimer using the docking method. We have computed the potential of mean force (PMF) variation with generation 5 (G5)-PAMAM dendrimer complexed with drug molecules using umbrella sampling. From our calculated PMF values, we observe that soluble drugs (Sal and Ala) have lower energy barriers than insoluble drugs (Pbz and Prim). The order of ease of release pattern for these drugs from G5 protonated PAMAM dendrimer was found to be Ala > Sal > Prim > Pbz. In the case of insoluble drugs (Prim and Pbz), because of larger size, we observe much nonpolar contribution, and thus, their larger energy barriers can be reasoned to van der Waals contribution. From the hydrogen bonding analysis of the four PAMAM drug complexes under study, we found intermolecular hydrogen bonding to show less significant contribution to the free energy barrier. Another interesting feature appears while calculating the PMF profile of G5NP (nonprotonated)-PAMAM Pbz and G5NP (nonprotonated)-PAMAM-Sal complex. The PMF was found to be less when the drug is bound to nonprotonated dendrimer compared to the protonated dendrimer. Our results suggest that encapsulation of the drug molecule into the host PAMAM dendrimer should be carried out at higher pH values (near pH 10). When such complex enters the human body, the pH is around 7.4 and at that physiological pH, the dendrimer holds the drug tightly. Hence the release of drug can occur at a controlled rate into the bloodstream. Thus, our findings provide a microscopic picture of the encapsulation and controlled release of drugs in the case of dendrimer-based host-guest systems.

Insights to urban dynamics through landscape spatial pattern analysis

Urbanisation is a dynamic complex phenomenon involving large scale changes in the land uses at local levels. Analyses of changes in land uses in urban environments provide a historical perspective of land use and give an opportunity to assess the spatial patterns, correlation, trends, rate and impacts of the change, which would help in better regional planning and good governance of the region. Main objective of this research is to quantify the urban dynamics using temporal remote sensing data with the help of well-established landscape metrics. Bangalore being one of the rapidly urbanising landscapes in India has been chosen for this investigation. Complex process of urban sprawl was modelled using spatio temporal analysis. Land use analyses show 584% growth in built-up area during the last four decades with the decline of vegetation by 66% and water bodies by 74%. Analyses of the temporal data reveals an increase in urban built up area of 342.83% (during 1973-1992), 129.56% (during 1992-1999), 106.7% (1999-2002), 114.51% (2002-2006) and 126.19% from 2006 to 2010. The Study area was divided into four zones and each zone is further divided into 17 concentric circles of 1 km incrementing radius to understand the patterns and extent of the urbanisation at local levels. The urban density gradient illustrates radial pattern of urbanisation for the period 1973-2010. Bangalore grew radially from 1973 to 2010 indicating that the urbanisation is intensifying from the central core and has reached the periphery of the Greater Bangalore. Shannon's entropy, alpha and beta population densities were computed to understand the level of urbanisation at local levels. Shannon's entropy values of recent time confirms dispersed haphazard urban growth in the city, particularly in the outskirts of the city. This also illustrates the extent of influence of drivers of urbanisation in various directions. Landscape metrics provided in depth knowledge about the sprawl. Principal component analysis helped in prioritizing the metrics for detailed analyses. The results clearly indicates that whole landscape is aggregating to a large patch in 2010 as compared to earlier years which was dominated by several small patches. The large scale conversion of small patches to large single patch can be seen from 2006 to 2010. In the year 2010 patches are maximally aggregated indicating that the city is becoming more compact and more urbanised in recent years. Bangalore was the most sought after destination for its climatic condition and the availability of various facilities (land availability, economy, political factors) compared to other cities. The growth into a single urban patch can be attributed to rapid urbanisation coupled with the industrialisation. Monitoring of growth through landscape metrics helps to maintain and manage the natural resources. (C) 2012 Elsevier B.V. All rights reserved.

Suite of tools for statistical N-gram language modeling for pattern mining in whole genome sequences

Genome sequences contain a number of patterns that have biomedical significance. Repetitive sequences of various kinds are a primary component of most of the genomic sequence patterns. We extended the suffix-array based Biological Language Modeling Toolkit to compute n-gram frequencies as well as n-gram language-model based perplexity in windows over the whole genome sequence to find biologically relevant patterns. We present the suite of tools and their application for analysis on whole human genome sequence.

Pattern clustering using cooperative game theory

In this paper, we approach the classical problem of clustering using solution concepts from cooperative game theory such as Nucleolus and Shapley value. We formulate the problem of clustering as a characteristic form game and develop a novel algorithm DRAC (Density-Restricted Agglomerative Clustering) for clustering. With extensive experimentation on standard data sets, we compare the performance of DRAC with that of well known algorithms. We show an interesting result that four prominent solution concepts, Nucleolus, Shapley value, Gately point and \tau-value coincide for the defined characteristic form game. This vindicates the choice of the characteristic function of the clustering game and also provides strong intuitive foundation for our approach.

Efficient Regular Expression Pattern Matching for Network Intrusion Detection Systems using Modified Word-based Automata

Network Intrusion Detection Systems (NIDS) intercept the traffic at an organization's network periphery to thwart intrusion attempts. Signature-based NIDS compares the intercepted packets against its database of known vulnerabilities and malware signatures to detect such cyber attacks. These signatures are represented using Regular Expressions (REs) and strings. Regular Expressions, because of their higher expressive power, are preferred over simple strings to write these signatures. We present Cascaded Automata Architecture to perform memory efficient Regular Expression pattern matching using existing string matching solutions. The proposed architecture performs two stage Regular Expression pattern matching. We replace the substring and character class components of the Regular Expression with new symbols. We address the challenges involved in this approach. We augment the Word-based Automata, obtained from the re-written Regular Expressions, with counter-based states and length bound transitions to perform Regular Expression pattern matching. We evaluated our architecture on Regular Expressions taken from Snort rulesets. We were able to reduce the number of automata states between 50% to 85%. Additionally, we could reduce the number of transitions by a factor of 3 leading to further reduction in the memory requirements.

Differential cellular recognition pattern to M. tuberculosis targets defined by IFN-gamma and IL-17 production in blood from TB plus patients from Honduras as compared to health care workers: TB and immune responses in patients from Honduras

Background: A better understanding of the quality of cellular immune responses directed against molecularly defined targets will guide the development of TB diagnostics and identification of molecularly defined, clinically relevant M.tb vaccine candidates. Methods: Recombinant proteins (n = 8) and peptide pools (n = 14) from M. tuberculosis (M.tb) targets were used to compare cellular immune responses defined by IFN-gamma and IL-17 production using a Whole Blood Assay (WBA) in a cohort of 148 individuals, i.e. patients with TB + (n = 38), TB- individuals with other pulmonary diseases (n = 81) and individuals exposed to TB without evidence of clinical TB (health care workers, n = 29). Results: M.tb antigens Rv2958c (glycosyltransferase), Rv2962c (mycolyltransferase), Rv1886c (Ag85B), Rv3804c (Ag85A), and the PPE family member Rv3347c were frequently recognized, defined by IFN-gamma production, in blood from healthy individuals exposed to M.tb (health care workers). A different recognition pattern was found for IL-17 production in blood from M.tb exposed individuals responding to TB10.4 (Rv0288), Ag85B (Rv1886c) and the PPE family members Rv0978c and Rv1917c. Conclusions: The pattern of immune target recognition is different in regard to IFN-gamma and IL-17 production to defined molecular M.tb targets in PBMCs from individuals frequently exposed to M.tb. The data represent the first mapping of cellular immune responses against M.tb targets in TB patients from Honduras.

Experiments and zero D modeling studies using specific Wiebe coefficients for producer gas as fuel in spark-ignited engines

The paper addresses experiments and modeling studies on the use of producer gas, a bio-derived low energy content fuel in a spark-ignited engine. Producer gas, generated in situ, has thermo-physical properties different from those of fossil fuel(s). Experiments on naturally aspirated and turbo-charged engine operation and subsequent analysis of the cylinder pressure traces reveal significant differences in the heat release pattern within the cylinder compared with a typical fossil fuel. The heat release patterns for gasoline and producer gas compare well in the initial 50% but beyond this, producer gas combustion tends to be sluggish leading to an overall increase in the combustion duration. This is rather unexpected considering that producer gas with nearly 20% hydrogen has higher flame speeds than gasoline. The influence of hydrogen on the initial flame kernel development period and the combustion duration and hence on the overall heat release pattern is addressed. The significant deviations in the heat release profiles between conventional fuels and producer gas necessitates the estimation of producer gas-specific Wiebe coefficients. The experimental heat release profiles are used for estimating the Wiebe coefficients. Experimental evidence of lower fuel conversion efficiency based on the chemical and thermal analysis of the engine exhaust gas is used to arrive at the Wiebe coefficients. The efficiency factor a is found to be 2.4 while the shape factor m is estimated at 0.7 for 2% to 90% burn duration. The standard Wiebe coefficients for conventional fuels and fuel-specific coefficients for producer gas are used in a zero D model to predict the performance of a 6-cylinder gas engine under naturally aspirated and turbo-charged conditions. While simulation results with standard Wiebe coefficients result in excessive deviations from the experimental results, excellent match is observed when producer gas-specific coefficients are used. Predictions using the same coefficients on a 3-cylinder gas engine having different geometry and compression ratio(s) indicate close match with the experimental traces highlighting the versatility of the coefficients.

Modified particle swarm optimization for pattern clustering

Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning and data mining. Clustering is grouping of a data set or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait according to some defined distance measure. In this paper we present the genetically improved version of particle swarm optimization algorithm which is a population based heuristic search technique derived from the analysis of the particle swarm intelligence and the concepts of genetic algorithms (GA). The algorithm combines the concepts of PSO such as velocity and position update rules together with the concepts of GA such as selection, crossover and mutation. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The performance of our method is better than k-means and PSO algorithm.

Polyvinylidene fluoride film based nasal sensor to monitor human respiration pattern: An initial clinical study

Design and development of a piezoelectric polyvinylidene fluoride (PVDF) thin film based nasal sensor to monitor human respiration pattern (RP) from each nostril simultaneously is presented in this paper. Thin film based PVDF nasal sensor is designed in a cantilever beam configuration. Two cantilevers are mounted on a spectacle frame in such a way that the air flow from each nostril impinges on this sensor causing bending of the cantilever beams. Voltage signal produced due to air flow induced dynamic piezoelectric effect produce a respective RP. A group of 23 healthy awake human subjects are studied. The RP in terms of respiratory rate (RR) and Respiratory air-flow changes/alterations obtained from the developed PVDF nasal sensor are compared with RP obtained from respiratory inductance plethysmograph (RIP) device. The mean RR of the developed nasal sensor (19.65 +/- A 4.1) and the RIP (19.57 +/- A 4.1) are found to be almost same (difference not significant, p > 0.05) with the correlation coefficient 0.96, p < 0.0001. It was observed that any change/alterations in the pattern of RIP is followed by same amount of change/alterations in the pattern of PVDF nasal sensor with k = 0.815 indicating strong agreement between the PVDF nasal sensor and RIP respiratory air-flow pattern. The developed sensor is simple in design, non-invasive, patient friendly and hence shows promising routine clinical usage. The preliminary result shows that this new method can have various applications in respiratory monitoring and diagnosis.