Developing robust vision modules for microsystems applications

In this work, several robust vision modules are developed and implemented for fully automated micromanipulation. These are autofocusing, object and end-effector detection, real-time tracking and optical system calibration modules. An image based visual servoing architecture and a path planning algorithm are also proposed based on the developed vision modules. Experimental results are provided to assess the performance of the proposed visual servoing approach in positioning and trajectory tracking tasks. Proposed path planning algorithm in conjunction with visual servoing imply successful micromanipulation tasks.     

Dynamic hierarchical bandwidth allocation using Russian Doll Model in EPON

This paper demonstrates a new hierarchical Dynamic Bandwidth Allocation algorithm using the Russian Doll Model (RDM) to allocate bandwidth for intra-Optical Network Unit (ONU) in an Ethernet Passive Optical Network (EPON). The allocation of bandwidth is based on the classification and prioritization of service. The algorithm addresses the requests of ONUs and provides differentiated services by balancing priority and fairness. The simulation results show that the proposed algorithm performs well in supporting the triple-play services, i.e. video, voice, and data, as well as making effective adjustment in balancing bandwidth sharing between the ONUs compared with two other existing Dynamic Bandwidth Allocation (DBA) algorithm. The proposed algorithms shows significant performance improvements in terms of bandwidth utilization, packet delay and the fairness.     

A method for real power transfer allocation using multivariable regression analysis

A multivariable regression (MVR) approach is proposed to identify the real power transfer between generators and loads. Based on solved load flow results, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then, the results of MNE method and load flow information are utilized to determine suitable regression coefficients using MVR model to estimate the power transfer. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of the MVR output compared to that of the MNE method. The error of the estimate of MVR method ranges from 0.001 4 to 0.007 9. Furthermore, when compared to MNE method, MVR method computes generator contribution to loads within 26.40 ms whereas the MNE method takes 360 ms for the calculation of same real power transfer allocation. Therefore, MVR method is more suitable for real time power transfer allocation.     

Thermal fracture analysis of orthotropic functionally graded materials using an equivalent domain integral approach

A new computational method based on the equivalent domain integral (EDI) is developed for mode I fracture analysis of orthotropic functionally graded materials (FGMs) subjected to thermal stresses. By using the constitutive relations of plane orthotropic thermoelasticity, generalized definition of the J-integral is converted to an equivalent domain integral to calculate the thermal stress intensity factor. In the formulation of the EDI approach, all the required thermomechanical properties are assumed to have continuous spatial variations through the functionally graded medium. Developed methodology is integrated into a fracture mechanics research finite element code FRAC2D using graded finite elements that possess cubic interpolation. Steady-state and transient temperature distribution profiles in orthotropic FGMs are computed using the finite elements based heat transfer analysis software HEAT2D. EDI method is validated and domain independence is demonstrated by comparing the numerical results obtained using EDI to those calculated by an enriched finite element method and to those available in the literature. Single and periodic edge crack problems in orthotropic FGMs are examined in order to study the influences of principal thermal expansion coefficient and thermal conductivity components, relative crack length and crack periodicity on the thermal stress intensity factors. Numerical results show that among the three principal thermal expansion coefficient components, the in-plane component perpendicular to the crack axis has the most significant influence on the mode I stress intensity factor. Gradation profile of the thermal expansion coefficient parallel to the crack axis is shown to have no effect on the outcome of the fracture analysis.     

The effect of heat treatment on high temperature mechanical properties of microalloyed medium carbon steel

In the present work, high temperature tensile properties and abrasive wear performance of a microalloyed medium carbon steel has been examined. Tensile and abrasive wear testing were carried out on as-received and heat treated specimens. The research has shown that microalloyed medium carbon steel was susceptible to dynamic strain ageing due to interaction of mobile dislocations and solid atoms, such as carbon and/or nitrogen. The interaction between dislocations and solid atoms at 200–300 °C changes the work hardening rate and contributes to dynamic strain ageing. These interactions also increased abrasive wear resistance of the microalloyed medium carbon steel at 300 °C. Therefore, the inference can be drawn that dynamic strain ageing caused an improvement on abrasion resistance.     

A knowledge-based decision support system for the management of parts and tools in FMS

Flexible manufacturing systems (FMS) are very complex systems with large part, tool, and information flows. The aim of this work is to develop a knowledge-based decision support system (KBDSS) for short-term scheduling in FMS strongly influenced by the tool management concept to provide a significant operational control tool for a wide range of machining cells, where a high level of flexibility is demanded, with benefits of more efficient cell utilization, greater tool flow control, and a dependable way of rapidly adjusting short-term production requirements. Development of a knowledge-based system to support the decision making process is justified by the inability of decision makers to diagnose efficiently many of the malfunctions that arise at machine, cell, and entire system levels during manufacturing. In this context, this paper proposes three knowledge-based models to ease the decision making process: an expert production scheduling system, a knowledge-based tool management decision support systems, and a tool management fault diagnosis system. The entire system has been created in a hierarchical manner and comprises more than 400 rules. The expert system (ES) was implemented in a commercial expert system shell, Knowledge Engineering System (KES) Production System (PS).     

A Conjecture on Wiener Indices in Combinatorial Chemistry

Drugs and other chemical compounds are often modeled as polygonal shapes, where each vertex represents an atom of the molecule, and covalent bonds between atoms are represented by edges between the corresponding vertices. This polygonal shape derived from a chemical compound is often called its molecular graph, and can be a path, a tree, or in general a graph. An indicator defined over this molecular graph, the Wiener index, has been shown to be strongly correlated to various chemical properties of the compound. The Wiener index conjecture for trees states that for any integer n (except for a finite set), one can find a tree with Wiener index n. This conjecture has been open for quite some time, and many authors have presented incremental progress on this problem. In this paper we present further progress towards proving this conjecture—through the design of efficient algorithms, we show that enumerating all possible trees to verify this conjecture (as done by all the previous approaches) is not necessary, but instead searching in a small special family of trees suffices, thus achieving the first polynomial (in n) time algorithm to verify the conjecture up to integer n. More precisely, we (i) present an infinite family of trees and prove various properties of these trees, (ii) show that a large number of integers, up to at least 10⁸ (compared with the previous best 10⁴) are representable as Wiener indices of trees in this succinct family, (iii) provide several efficient algorithms for computing trees with given Wiener indices, and (iv) implement our algorithms and experimentally show that their performance is asymptotically much better than their theoretical worst-case upper bound.     

Hypergraph Models and Algorithms for Data-Pattern-Based Clustering

In traditional approaches for clustering market basket type data, relations among transactions are modeled according to the items occurring in these transactions. However, an individual item might induce different relations in different contexts. Since such contexts might be captured by interesting patterns in the overall data, we represent each transaction as a set of patterns through modifying the conventional pattern semantics. By clustering the patterns in the dataset, we infer a clustering of the transactions represented this way. For this, we propose a novel hypergraph model to represent the relations among the patterns. Instead of a local measure that depends only on common items among patterns, we propose a global measure that is based on the cooccurences of these patterns in the overall data. The success of existing hypergraph partitioning based algorithms in other domains depends on sparsity of the hypergraph and explicit objective metrics. For this, we propose a two-phase clustering approach for the above hypergraph, which is expected to be dense. In the first phase, the vertices of the hypergraph are merged in a multilevel algorithm to obtain large number of high quality clusters. Here, we propose new quality metrics for merging decisions in hypergraph clustering specifically for this domain. In order to enable the use of existing metrics in the second phase, we introduce a vertex-to-cluster affinity concept to devise a method for constructing a sparse hypergraph based on the obtained clustering. The experiments we have performed show the effectiveness of the proposed framework.     

Power Flattening in ARIES-RS Fusion Breeder Reactor Using Mixed Fuels

This study presents the possibility of the power flattening in the ARIES-RS breeder reactor using mixed (Th,U)C or (Th,U)N fuels. Two different types of mixing, namely, homogeneous mixing (HM) and linear mixing (LM) were used to investigate the uniformity of fission power distribution through the fuel zone. In HM, fraction of uranium content were kept constant in all rows of the fuel zone whereas, in LM the fraction of the uranium were linearly increased from the first to last fuel row in the fuel zone. Neutron transport calculations were performed with the aid of the SCALE4.3 system by solving the Boltzmann transport equation with the XSDRNPM code in 238 neutron groups and a S₈–P₃ approximation. Flat fission power distribution was maintained successfully for the blanket using linearly mixed fuels. However, the fission density profile was not uniform in the blanket with homogeneously mixed fuels. It decreased exponentially form the 1st to 10th fuel row.     

Bloggers’ Responses to the Snowden Affair: Combining Automated and Manual Methods in the Analysis of News Blogging

The Snowden affair gave rise to a huge public debate about not only the legitimacy of the secret surveillance programs he revealed but also about Snowden himself and about the accuracy of the information he leaked. In this paper we present an analysis of how the affair was discussed in the English language blogosphere, based on a corpus of 15,000 blog posts written about Snowden and published from June 2013 to June 2014, as a sub-corpus of a larger corpus of 100,000 blog posts on the topic of surveillance, written during the period 2006–2014. Automated tools are used to identify the topics that characterize the blogging about surveillance and the posts about the Snowden affair. Through an in-depth analysis of the blog posts that commented on Snowden’s revelations of the PRISM program for surveillance of social media users, we chart how bloggers responded to Snowden and his role in this disclosure, whether they found the information credible, and the extent to which they expressed criticism of the surveillance practices. The analysis is used as a basis for discussing the role of blogs in the civic engagement during the first phase of the Snowden affair.