Fuzzy triangulation signature for detection of change in human emotion from face video image sequence

The present article proposes a geometry-based fuzzy relational technique for capturing gradual change in human emotion over time available from relevant face image sequences. As associated features, we make use of fuzzy membership arising out of five triangle signatures such as - (i) Fuzzy Isosceles Triangle Signature (FIS), (ii) Fuzzy Right Triangle Signature (FRS), (iii) Fuzzy Right Isosceles Triangle Signature (FIRS), (iv) Fuzzy Equilateral Triangle Signature (FES), and (v) Other Fuzzy Triangles Signature (OFS) to achieve the task of appropriate classification of facial transition from neutrality to one among the six expressions viz. anger (AN), disgust (DI), fear (FE), happiness (HA), sadness (SA) and surprise (SU). The effectiveness of the Multilayer Perceptron (MLP) classifier is tested and validated through 10 fold cross-validation method on three benchmark image sequence datasets namely Extended Cohn-Kanade (CK+), M&M Initiative (MMI), and Multimedia Understanding Group (MUG). Experimental outcomes are found to have achieved accuracy to the tune of 98.47%, 93.56%, and 99.25% on CK+, MMI, and MUG respectively vindicating the effectiveness by exhibiting the superiority of our proposed technique in comparison to other state-of-the-art methods in this regard.

     

A pluggable service platform architecture for e-commerce

In the beginning of the e-commerce era, retailers mostly adopted vertically integrated solutions to control the entire e-commerce value chain. However, they began to realize that to achieve agility, a better approach would be to focus on certain core capabilities and then create a partner ecosystem around them. From a technical point of view, this means it is advised to have a lightweight platform architecture with small core e-commerce functionality which can be extended by additional services from third party providers. In a typical e-commerce ecosystem with diverse information systems of network partners, integration and interoperability become critical factors to enable seamless coordination among the partners. Furthermore an increasing adoption of cloud computing technology could be observed resulting in more challenging integration scenarios involving cloud services. Thus, an e-commerce platform is required that suites the advanced needs for flexible and agile service integration. Therefore, this paper aims to present a reference architecture of a novel pluggable service platform for e-commerce. We investigate on currently available online shop platform solutions and integration platforms in the market. Based on the findings and motivated by literature on service-oriented design, we develop an architecture of a service-based pluggable platform for online retailers. This design is then instantiated by means of a prototype for an e-commerce returns handling scenario to demonstrate the feasibility of our architecture design.     

High-speed target tracking by fuzzy hostility-induced segmentation of optical flow field

A time efficient technique for real-time tracking of high-speed objects in a video sequence is presented in this article. The technique is primarily based on the segmentation of the optical flow field computed between the successive image frames of a video sequence, followed by the tracking of a detected point of interest (POI) within the segmented flow field. In the initial phase of the technique, the optical flow field between the first two successive image frames acquired from a video sequence, is computed. A fuzzy hostility index indicative of the degree of coherence of the moving objects in the image frames, is used to segment the optical flow field. This yields different coherent regions of interest (ROIs) in the segmented flow field. A POI is then detected in the different ROIs obtained. Tracking of the moving object is then carried out by computing the flow fields between predefined ROIs in the neighborhood of the detected POI in the subsequent image frames.Since the selected ROIs are smaller than the image frames, a fair amount of reduction in the time required for the computation of the optical flow field is achieved, thereby facilitating real-time operation. An application of the proposed technique is demonstrated on three video sequences of high-speed flying fighter aircrafts.     

Energy and Velocity Based Tree Multicast Routing in Mobile Ad-Hoc Networks

Wireless Personal Communications - Nodes in ad hoc networks are mostly mobile, moving with arbitrary velocity and direction. Therefore, it is always beneficial if nodes are equipped with...     

Identifying hazardousness of sewer pipeline gas mixture using classification methods: a comparative study

In this work, we formulated a real-world problem related to sewer pipeline gas detection using the classification-based approaches. The primary goal of this work was to identify the hazardousness of sewer pipeline to offer safe and non-hazardous access to sewer pipeline workers so that the human fatalities, which occurs due to the toxic exposure of sewer gas components, can be avoided. The dataset acquired through laboratory tests, experiments, and various literature sources was organized to design a predictive model that was able to identify/classify hazardous and non-hazardous situation of sewer pipeline. To design such prediction model, several classification algorithms were used and their performances were evaluated and compared, both empirically and statistically, over the collected dataset. In addition, the performances of several ensemble methods were analyzed to understand the extent of improvement offered by these methods. The result of this comprehensive study showed that the instance-based learning algorithm performed better than many other algorithms such as multilayer perceptron, radial basis function network, support vector machine, reduced pruning tree. Similarly, it was observed that multi-scheme ensemble approach enhanced the performance of base predictors.

     

A QCA design and energy analysis of binary semaphore with a comprehensive case study

Innovations in Systems and Software Engineering - Quantum dot cellular automata appeared as a comprehensive solution to the shortfalls CMOS technology is facing in case of nanoscale...     

Multilevel image segmentation with adaptive image context based thresholding

Neural network based image segmentation techniques primarily focus on the selection of appropriate thresholding points in the image feature space. Research initiatives in this direction aim at addressing this problem of effective threshold selection for activation functions. Multilevel activation functions resort to fixed and uniform thresholding mechanisms. These functions assume homogeneity of the image information content. In this paper, we propose a collection of adaptive thresholding approaches to multilevel activation functions. The proposed thresholding mechanisms incorporate the image context information in the thresholding process. Applications of these mechanisms are demonstrated on the segmentation of real life multilevel intensity images using a self-supervised multilayer self-organizing neural network (MLSONN) and a supervised pyramidal neural network (PyraNet).We also present a bi-directional self-organizing neural network (BDSONN) architecture suitable for multilevel image segmentation. The architecture uses an embedded adaptive thresholding mechanism to a characteristic multilevel activation function.The segmentation efficiencies of the thresholding mechanisms evaluated using four unsupervised measures of merit, are reported for the three neural network architectures considered.     

Comprehensive study on the performance comparison of logically reversible and irreversible parity generator and checker designs using two-dimensional two-dot one-electron QCA

The limitations of CMOS technology led to the discoveries of new technologies, one of which is quantum-dot cellular automata. This upcoming technology is making its way because of high efficiency, high speed and small space requirement. Two-dot one-electron cells are used to design a parity generator and checker. Parity generator and checker aids in flawless binary data transmission from the source to the destination. Both irreversible as well as reversible parity generators and checkers are designed. It is seen that the amount of energy and power needed to drive these architectures is very low.

     

Design of an arithmetic circuit using non-reversible adders in 2 dot 1 electron QCA

Microsystem Technologies - Quantum-dot cellular automata (QCA) appeared as an alternative nanotechnology which is capable of overcoming the shortfalls of the existing CMOS technologies. This energy...     

The Temporal Effect of Mobility on Path Length in MANET

Ad hoc network consists of a set of identical nodes that move freely and independently and communicate among themselves via wireless links. The most interesting feature of this network is that they do not require any existing infrastructure of central administration and hence is very suitable for temporary communication links in an emergency situation. This flexibility, however, is achieved at a price of communication uncertainty induced due to frequent topology changes. In this article, we have tried to identify the system dynamics using the proven concepts of time series modeling. Here, we have analyzed variation of path length between a particular source destination pair nodes over a fixed area for different mobility patterns under different routing algorithm. We have considered four different mobility models—(i) Gauss-Markov mobility model, (ii) Manhattan Grid mobility model and (iii) Random Way Point mobility model and (iv) Reference Point Group mobility model. The routing protocols under which, we carried out our experiments are (i) Ad hoc On demand Distance Vector routing (AODV), (ii) Destination Sequenced Distance Vector routing (DSDV) and (iii) Dynamic Source Routing (DSR). The path length between two particular nodes behaves as a random variable for all mobility models for all routing algorithms. The pattern of path length for every combination of mobility model and for every routing protocol can be well modeled as an autoregressive model of order p i.e. AR(p). The order p is estimated and it is found that most of them are of order unity only. We also calculate the average path length for all mobility models and for all routing algorithms.