A Comparative Study of Suitability of Certain Features in Classification of Bharatanatyam Mudra Images Using Artificial Neural Network

Neural Processing Letters - Bharatanatyam is an Indian classical dance, which is composed of various body postures and hand gestures. This ancient art of dance has to be studied under the...     

An espoused cultural perspective to understand continued intention to use mobile applications: a four-country study of mobile social media application usability

As most mobile applications are tailored for worldwide consumption, it is a significant challenge to develop applications that satisfy individuals with various cultural backgrounds. To address this issue, we drew on a recently developed conceptualization and associated instrument of mobile application usability to develop a model examining the impact of mobile social media application usability on continued intention to use. Drawing on Hofstede’s five cultural values, we incorporated espoused cultural values of masculinity/femininity, individualism/collectivism, power distance, uncertainty avoidance, and long-term orientation into our model as moderators. To test the model, we collected data from 1,844 consumers in four countries – the U.S., Germany, China, and India – who use mobile social media applications on their smartphones. The results provided support for the role of espoused national cultural values in moderating the impact of mobile social media application usability on continued intention to use and the model, with espoused cultural values explaining significantly more variance in continued intention to use (i.e., 38%) than the main effects-only model (i.e., 19%). Interestingly, our results demonstrated that culture at the national level did not play a significant role in affecting the relationship between usability constructs and continued intention to use, thus underscoring the importance of espoused culture.     

Comparing ladder logic diagrams and Petri nets for sequencecontroller design through a discrete manufacturing system

Design methods for sequence controllers play a very important role in advancing industrial automation. The increasing complexity and varying needs of modern discrete manufacturing systems have challenged the traditional design methods such as the use of ladder logic diagrams (LLDs) for programmable logic controllers. The methodologies based on research results in computer science have recently received growing attention by academic researchers and industrial engineers in order to design flexible, reusable, and maintainable control software. Particularly, Petri nets are emerging as a very important tool to provide an integrated solution for modeling, analysis, simulation, and control of industrial automated systems. This paper identifies certain criteria to compare LLDs and Petri nets in designing sequence controllers and responding to the changing control requirements. The comparison is performed through a practical system after introducing “real-time Petri nets” for discrete-event control purposes. The results reported in this paper will help: (a) further establish Petri net based techniques for discrete-event control of industrial automated systems; and (b) effectively convince industrial practitioners and researchers that it is worthy and timely to consider and promote the applications of Petri nets to their particular discrete-event control problems     

On reliable computation with formal neurons

The authors investigate the computing capabilities of formal McCulloch-Pitts neurons when errors are permitted in decisions. They assume that m decisions are to be made on a randomly specified m set of points in n space and that an error tolerance of ϵm decision errors is allowed, with 0⩽ϵ<1/2. The authors are interested in how large an m can be selected such that the neuron makes reliable decisions within the prescribed error tolerance. Formal results for two protocols for error-tolerance-a random error protocol and an exhaustive error protocol-are obtained. The results demonstrate that a formal neuron has a computational capacity that is linear in n and that this rate of capacity growth persists even when errors are tolerated in the decisions     

Modified butterfly structure for efficient implementation of prunedfast cosine transform

In the computation of pruned fast cosine transforms (FCTs), overheads are unavoidable in order to keep track of the complete and incomplete butterflies in each stage. The authors present a modification to the FCT butterfly structure proposed to reduce these overheads. Using this modified structure, the computation of the coefficients can be stopped at any point and resumed from the same point without any overhead. This structure also performs well for complete computation of FCTs     

Necessary and sufficient conditions for robust identification of uncertain LTI systems

Robust identification of uncertain systems arises whenever a chosen family of models does not completely describe reality. In these situations the issue of unmodeled dynamics gains significance in addition to random measurement noise. To deal with such mixed stochastic/deterministic settings we introduce a novel notion for robust consistency, which requires that the expectation (with respect to noise) of the worst-case (with respect to unmodeled dynamics) identification error asymptotically approach zero. It turns out that this notion leads to transparent necessary and sufficient conditions. We show that robust consistency holds, if and only if there is an instrument-input-pair capable of annihilating the residual error as well as stochastic noise. An extension of this result to the well-known “bounded but unknown” noise model shows that if we were to remove a set of Lebesgue measure zero, the error bound asymptotically approaches zero.     

Object-Oriented Framework for Genetic Algorithms with Application to Space Truss Optimization

Genetic algorithms have been shown to be very effective optimization tools for a number of engineering problems. Since the genetic processes typically operate independent of the actual problem, a core genetic algorithm library consisting of all the genetic operators having an interface to a generic objective function can serve as a very useful tool for learning as well as for solving a number of practical optimization problems. This paper discusses the object-oriented design and implementation of such a core library. Object-oriented design, apart from giving a more natural representation of information, also facilitates better memory management and code reusability. Next, it is shown how classes derived from the implemented libraries can be used for the practical size optimization of large space trusses, where several constructibility aspects have been incorporated to simulate real-world design constraints. Strategies are discussed to model the chromosome and to code genetic operators to handle such constraints. Strategies are also suggested for member grouping for reducing the problem size and implementing move-limit concepts for reducing the search space adaptively in a phased manner. The implemented libraries are tested on a number of large previously fabricated space trusses, and the results are compared with previously reported values. It is concluded that genetic algorithms implemented using efficient and flexible data structures can serve as a very useful tool in engineering design and optimization.     

Monitoring machine based synthesis technique for concurrent error detection in finite state machines

This paper discusses a new design methodology for concurrent error detection in synchronous sequential circuits based on the use of monitoring machines. In this approach, an auxiliary sequential circuit, called the monitoring machine, operates in lock-step with the main machine, such that any fault in either of the two machines is immediately detected. This methodology is independent of the fault model. It can be applied to FSMs with pre-encoded states and can also be used for ones being synthesised. It also provides a systematic framework for the combined optimisation of the main and monitoring machines, and for exploring tradeoffs in their implementation. The design of monitored sequential circuits is a two-fold problem; namely one of designing an optimal monitoring machine given the main machine, and the other of encoding the main machine states so that the resulting monitoring machine is minimal. This paper formally discusses the design of both the main and monitoring machines and techniques for their combined optimisation. Tradeoffs in their implementation based on selective fault detection are also examined. Through experimental results, it is shown that the proposed synthesis technique is eminently suitable for the design of low-cost sequential circuits with concurrent error detection. The monitoring machine is less costly than the main machine. It is also not identical to it. As a result, a monitored sequential circuit has significantly lower hardware cost and improved fault coverage than previous implementations. Presently at Texas Instruments (India) Ltd., Bangalore, India.