Two Dimensional Principal Component Analysis for Online Tamil Character Recognition

This paper presents a new application of two dimensional Principal Component Analysis (2DPCA) to the problem of online character recognition in Tamil Script. A novel set of features employing polynomial fits and quartiles in combination with conventional features are derived for each sample point of the Tamil character obtained after smoothing and resampling. These are stacked to form a matrix, using which a covariance matrix is constructed. A subset of the eigenvectors of the covariance matrix is employed to get the features in the reduced sub space. Each character is modeled as a separate subspace and a modified form of the Mahalanobis distance is derived to classify a given test character. Results indicate that the recognition accuracy using the 2DPCA scheme shows an approximate 3% improvement over the conventional PCA technique.

Online character recognition using regression techniques

This paper introduces a scheme for classification of online handwritten characters based on polynomial regression of the sampled points of the sub-strokes in a character. The segmentation is done based on the velocity profile of the written character and this requires a smoothening of the velocity profile. We propose a novel scheme for smoothening the velocity profile curve and identification of the critical points to segment the character. We also porpose another method for segmentation based on the human eye perception. We then extract two sets of features for recognition of handwritten characters. Each sub-stroke is a simple curve, a part of the character, and is represented by the distance measure of each point from the first point. This forms the first set of feature vector for each character. The second feature vector are the coeficients obtained from the B-splines fitted to the control knots obtained from the segmentation algorithm. The feature vector is fed to the SVM classifier and it indicates an efficiency of 68% using the polynomial regression technique and 74% using the spline fitting method.

Comparison of HMM and SDTW for Tamil handwritten character recognition

In this paper, we compare the experimental results for Tamil online handwritten character recognition using HMM and Statistical Dynamic Time Warping (SDTW) as classifiers. HMM was used for a 156-class problem. Different feature sets and values for the HMM states & mixtures were tried and the best combination was found to be 16 states & 14 mixtures, giving an accuracy of 85%. The features used in this combination were retained and a SDTW model with 20 states and single Gaussian was used as classifier. Also, the symbol set was increased to include numerals, punctuation marks and special symbols like $, & and #, taking the number of classes to 188. It was found that, with a small addition to the feature set, this simple SDTW classifier performed on par with the more complicated HMM model, giving an accuracy of 84%. Mixture density estimation computations was reduced by 11 times. The recognition is writer independent, as the dataset used is quite large, with a variety of handwriting styles.

Field extension code based dispersion matrices for coherently detected space-time shift keying

Motivated by the recent Coherent Space-Time Shift Keying (CSTSK) philosophy, we construct new dispersion matrices for rotationally invariant PSK signaling sets. Given a specific PSK signal constellation, the dispersion matrices of the existing CSTSK scheme were chosen by maximizing the mutual information over randomly generated sets of dispersion matrices. In this contribution we propose a general method for constructing a set of structured dispersion matrices for arbitrary PSK signaling sets using Field Extension (FE) codes and then study the attainable Symbol Error Rate (SER) performance of some example constructions. We demonstrate that the proposed dispersion scheme is capable of outperforming the existing dispersion arrangement at medium to high SNRs.

Wireless Network-Coded Bidirectional Relaying Using Latin Squares for M-PSK Modulation

The design of modulation schemes for the physical layer network-coded two-way relaying scenario is considered with a protocol which employs two phases: multiple access (MA) phase and broadcast (BC) phase. It was observed by Koike-Akino et al. that adaptively changing the network coding map used at the relay according to the channel conditions greatly reduces the impact of MA interference which occurs at the relay during the MA phase and all these network coding maps should satisfy a requirement called the exclusive law. We show that every network coding map that satisfies the exclusive law is representable by a Latin Square and conversely, that this relationship can be used to get the network coding maps satisfying the exclusive law. The channel fade states for which the minimum distance of the effective constellation at the relay become zero are referred to as the singular fade states. For M - PSK modulation (M any power of 2), it is shown that there are (M-2/4 - M/2 + 1) M singular fade states. Also, it is shown that the constraints which the network coding maps should satisfy so that the harmful effects of the singular fade states are removed, can be viewed equivalently as partially filled Latin Squares (PFLS). The problem of finding all the required maps is reduced to finding a small set of maps for M - PSK constellations (any power of 2), obtained by the completion of PFLS. Even though the completability of M x M PFLS using M symbols is an open problem, specific cases where such a completion is always possible are identified and explicit construction procedures are provided. Having obtained the network coding maps, the set of all possible channel realizations (the complex plane) is quantized into a finite number of regions, with a specific network coding map chosen in a particular region. It is shown that the complex plane can be partitioned into two regions: a region in which any network coding map which satisfies the exclusive law gives the same best performance and a region in which the choice of the network coding map affects the performance. The quantization thus obtained analytically, leads to the same as the one obtained using computer search for M = 4-PSK signal set by Koike-Akino et al., when specialized for Simulation results show that the proposed scheme performs better than the conventional exclusive-OR (XOR) network coding and in some cases outperforms the scheme proposed by Koike-Akino et al.

Wireless network-coded accumulate-compute and forward two-way relaying

The design of modulation schemes for the physical layer network-coded two way wireless relaying scenario is considered. It was observed by Koike-Akino et al. for the two way relaying scenario, that adaptively changing the network coding map used at the relay according to the channel conditions greatly reduces the impact of multiple access interference which occurs at the relay during the MA Phase and all these network coding maps should satisfy a requirement called exclusive law. We extend this approach to an Accumulate-Compute and Forward protocol which employs two phases: Multiple Access (MA) phase consisting of two channel uses with independent messages in each channel use, and Broadcast (BC) phase having one channel use. Assuming that the two users transmit points from the same 4-PSK constellation, every such network coding map that satisfies the exclusive law can be represented by a Latin Square with side 16, and conversely, this relationship can be used to get the network coding maps satisfying the exclusive law. Two methods of obtaining this network coding map to be used at the relay are discussed. Using the structural properties of the Latin Squares for a given set of parameters, the problem of finding all the required maps is reduced to finding a small set of maps. Having obtained all the Latin Squares, the set of all possible channel realizations is quantized, depending on which one of the Latin Squares obtained optimizes the performance. The quantization thus obtained, is shown to be the same as the one obtained in [7] for the 2-stage bidirectional relaying.

Channel quantization for physical layer network-coded two-way relaying

The design of modulation schemes for the physical layer network-coded two way relaying scenario is considered with the protocol which employs two phases: Multiple access (MA) Phase and Broadcast (BC) phase. It was observed by Koike-Akino et al. that adaptively changing the network coding map used at the relay according to the channel conditions greatly reduces the impact of multiple access interference which occurs at the relay during the MA phase. In other words, the set of all possible channel realizations (the complex plane) is quantized into a finite number of regions, with a specific network coding map giving the best performance in a particular region. We obtain such a quantization analytically for the case when M-PSK (for M any power of 2) is the signal set used during the MA phase. We show that the complex plane can be classified into two regions: a region in which any network coding map which satisfies the so called exclusive law gives the same best performance and a region in which the choice of the network coding map affects the performance, which is further quantized based on the choice of the network coding map which optimizes the performance. The quantization thus obtained analytically, leads to the same as the one obtained using computer search for 4-PSK signal set by Koike-Akino et al., for the specific value of M = 4.

Space-Time Coded Spatial Modulated Physical Layer Network Coding for Two-Way Relaying

Using the spatial modulation approach, where only one transmit antenna is active at a time, we propose two transmission schemes for two-way relay channel using physical layer network coding with space time coding using coordinate interleaved orthogonal designs (CIODs). It is shown that using two uncorrelated transmit antennas at the nodes, but using only one RF transmit chain and space-time coding across these antennas can give a better performance without using any extra resources and without increasing the hardware implementation cost and complexity. In the first transmission scheme, two antennas are used only at the relay, adaptive network coding (ANC) is employed at the relay and the relay transmits a CIOD space time block code (STBC). This gives a better performance compared to an existing ANC scheme for two-way relay channel which uses one antenna each at all the three nodes. It is shown that for this scheme at high SNR the average end-to-end symbol error probability (SEP) is upper bounded by twice the SEP of a point-to-point fading channel. In the second transmission scheme, two transmit antennas are used at all the three nodes, CIOD STBCs are transmitted in multiple access and broadcast phases. This scheme provides a diversity order of two for the average end-to-end SEP with an increased decoding complexity of O(M-3) for an arbitrary signal set and O(M-2 root M) for square QAM signal set. Simulation results show that the proposed schemes performs better than the existing ANC schemes under perfect and imperfect channel state information.

Wireless Network-Coded Accumulate-Compute-and-Forward Two-Way Relaying

For the physical-layer network-coded wireless two-way relaying, it was observed by Koike-Akino et al. that adaptively changing the network coding map used at the relay according to channel conditions greatly reduces the impact of multiple-access interference, which occurs at the relay, and all these network coding maps should satisfy a requirement called exclusive law. We extend this approach to an accumulate-compute-and-forward protocol, which employs two phases: a multiple access (MA) phase consisting of two channel uses with independent messages in each channel use and a broadcast (BC) phase having one channel use. Assuming that the two users transmit points from the same 4-phase-shift keying (PSK) constellation, every such network coding map that satisfies the exclusive law can be represented by a Latin square of side 16, and conversely, this relationship can be used to get the network coding maps satisfying the exclusive law. Two methods of obtaining this network coding map to be used at the relay are discussed. Using the structural properties of the Latin squares for a given set of parameters, the problem of finding all the required maps is reduced to finding a small set of maps for the case. Having obtained all the Latin squares, a criterion is provided to select a Latin square for a given realization of fade state. This criterion turns out to be the same as the one used byMuralidharan et al. for two-stage bidirectional relaying.

Numerical prediction of load-displacement behaviors of adhesively bonded joints at different extension rates and temperatures

The present work focuses on simulation of nonlinear mechanical behaviors of adhesively bonded DLS (double lap shear) joints for variable extension rates and temperatures using the implicit ABAQUS solver. Load-displacement curves of DLS joints at nine combinations of extension rates and environmental temperatures are initially obtained by conducting tensile tests in a UTM. The joint specimens are made from dual phase (DP) steel coupons bonded with a rubber-toughened adhesive. It is shown that the shell-solid model of a DLS joint, in which substrates are modeled with shell elements and adhesive with solid elements, can effectively predict the mechanical behavior of the joint. Exponent Drucker-Prager or Von Mises yield criterion together with nonlinear isotropic hardening is used for the simulation of DLS joint tests. It has been found that at a low temperature (-20 degrees C), both Von Mises and exponent Drucker-Prager criteria give close prediction of experimental load-extension curves. However. at a high temperature (82 degrees C), Von Mises condition tends to yield a perceptibly softer joint behavior, while the corresponding response obtained using exponent Drucker-Prager criterion is much closer to the experimental load-displacement curve.

A Scalable High Throughput Firewall in FPGA

High end network security applications demand high speed operation and large rule set support. Packet classification is the core functionality that demands high throughput in such applications. This paper proposes a packet classification architecture to meet such high throughput. We have implemented a Firewall with this architecture in reconflgurable hardware. We propose an extension to Distributed Crossproducting of Field Labels (DCFL) technique to achieve scalable and high performance architecture. The implemented Firewall takes advantage of inherent structure and redundancy of rule set by using our DCFL Extended (DCFLE) algorithm. The use of DCFLE algorithm results in both speed and area improvement when it is implemented in hardware. Although we restrict ourselves to standard 5-tuple matching, the architecture supports additional fields. High throughput classification invariably uses Ternary Content Addressable Memory (TCAM) for prefix matching, though TCAM fares poorly in terms of area and power efficiency. Use of TCAM for port range matching is expensive, as the range to prefix conversion results in large number of prefixes leading to storage inefficiency. Extended TCAM (ETCAM) is fast and the most storage efficient solution for range matching. We present for the first time a reconfigurable hardware implementation of ETCAM. We have implemented our Firewall as an embedded system on Virtex-II Pro FPGA based platform, running Linux with the packet classification in hardware. The Firewall was tested in real time with 1 Gbps Ethernet link and 128 sample rules. The packet classification hardware uses a quarter of logic resources and slightly over one third of memory resources of XC2VP30 FPGA. It achieves a maximum classification throughput of 50 million packet/s corresponding to 16 Gbps link rate for the worst case packet size. The Firewall rule update involves only memory re-initialization in software without any hardware change.

A Scalable High Throughput Firewall in FPGA

High end network security applications demand high speed operation and large rule set support. Packet classification is the core functionality that demands high throughput in such applications. This paper proposes a packet classification architecture to meet such high throughput. We have Implemented a Firewall with this architecture in reconfigurable hardware. We propose an extension to Distributed Crossproducting of Field Labels (DCFL) technique to achieve scalable and high performance architecture. The implemented Firewall takes advantage of inherent structure and redundancy of rule set by using, our DCFL Extended (DCFLE) algorithm. The use of DCFLE algorithm results In both speed and area Improvement when It is Implemented in hardware. Although we restrict ourselves to standard 5-tuple matching, the architecture supports additional fields.High throughput classification Invariably uses Ternary Content Addressable Memory (TCAM) for prefix matching, though TCAM fares poorly In terms of area and power efficiency. Use of TCAM for port range matching is expensive, as the range to prefix conversion results in large number of prefixes leading to storage inefficiency. Extended TCAM (ETCAM) is fast and the most storage efficient solution for range matching. We present for the first time a reconfigurable hardware Implementation of ETCAM. We have implemented our Firewall as an embedded system on Virtex-II Pro FPGA based platform, running Linux with the packet classification in hardware. The Firewall was tested in real time with 1 Gbps Ethernet link and 128 sample rules. The packet classification hardware uses a quarter of logic resources and slightly over one third of memory resources of XC2VP30 FPGA. It achieves a maximum classification throughput of 50 million packet/s corresponding to 16 Gbps link rate for file worst case packet size. The Firewall rule update Involves only memory re-initialiization in software without any hardware change.

An Algorithm to Decide Feasibility of Linear Integer Constraints Occurrng in Decision Tables

Abstract-To detect errors in decision tables one needs to decide whether a given set of constraints is feasible or not. This paper describes an algorithm to do so when the constraints are linear in variables that take only integer values. Decision tables with such constraints occur frequently in business data processing and in nonnumeric applications. The aim of the algorithm is to exploit. the abundance of very simple constraints that occur in typical decision table contexts. Essentially, the algorithm is a backtrack procedure where the the solution space is pruned by using the set of simple constrains. After some simplications, the simple constraints are captured in an acyclic directed graph with weighted edges. Further, only those partial vectors are considered from extension which can be extended to assignments that will at least satisfy the simple constraints. This is how pruning of the solution space is achieved. For every partial assignment considered, the graph representation of the simple constraints provides a lower bound for each variable which is not yet assigned a value. These lower bounds play a vital role in the algorithm and they are obtained in an efficient manner by updating older lower bounds. Our present algorithm also incorporates an idea by which it can be checked whether or not an (m - 2)-ary vector can be extended to a solution vector of m components, thereby backtracking is reduced by one component.

Modeling growth of hydrogen bubbles in aluminum castings using the level-set method

A new approach is proposed to solve for the growth as well as the movement of hydrogen bubbles during solidification in aluminum castings. A level-set methodology has been adopted to handle this multiphase phenomenon. A microscale domain is considered and the growth and movement of hydrogen bubbles in this domain has been studied. The growth characteristics of hydrogen bubbles have been evaluated under free growth conditions in a melt having a hydrogen input caused b solidification occurring around the microdomain.