Obtaining mode mixity for a bimaterial interface crack using the virtual crack closure technique

We review, unify and extend work pertaining to evaluating mode mixity of interfacial fracture utilizing the virtual crack closure technique (VCCT). From the VCCT, components of the strain energy release rate (SERR) are obtained using the forces and displacements near the crack tip corresponding to the opening and sliding contributions. Unfortunately, these components depend on the crack extension size, Δ, used in the VCCT. It follows that a mode mixity based upon these components also will depend on the crack extension size. However, the components of the strain energy release rate can be used for determining the complex stress intensity factors (SIFs) and the associated mode mixity. In this study, we show that several—seemingly different—suggested methods presented in the literature used to obtain mode mixity based on the stress intensity factors are indeed identical. We also present an alternative, simpler quadratic equation to this end. Moreover, a Δ-independent strain energy release based mode mixity can be defined by introducing a “normalizing length parameter.” We show that when the reference length (used for the SIF-based mode mixity) and the normalizing length (used for Δ-independent SERR-based mode mixity) are equal, the two mode mixities are only shifted by a phase angle, depending on the bimaterial parameter ε.     

Scalable and QoS-Aware Dynamic Slot Assignment and Piconet Partitioning to Enhance the Performance of Bluetooth Ad Hoc Networks

Bluetooth is a radio technology for Wireless Personal Area Networks in the 2.4 GHz ISM frequency band and allows short-range devices to be connected in the form of ad hoc networks. The Bluetooth medium access control protocol is based on a strict master/slave concept wherein any communication between slave devices has to go through the master. While this model is simple, the use of such a nonoptimal packet forwarding scheme incurs much longer delays between any two slave-devices as double the bandwidth is used by the master. In addition, if two or more devices want to communicate as a group, this can only be achieved by either multiple unicast transmissions or a piconet-wide broadcast from the master. To handle these issues efficiently, we propose a novel combination of Dynamic Slot Assignment (DSA) and piconet partitioning. With DSA, the piconet master dynamically assigns slots to slaves so as to allow them to communicate directly with each other without any intervention from the master. Our proposed communication architecture provides for enhanced Quality of Service (QoS), better admission control, and multidevice conversation, which make a multicast-like communication feasible within the piconet. To widen the scope of DSA, we propose a QoS-aware Enhanced DSA (EDSA) version where dynamic piconet partitioning and scatternet support are exploited by grouping devices into piconets as per their connection endpoints, enabling it to be employed over a scatternet. We have performed extensive simulations and observe that these schemes drastically enhance Bluetooth performance in terms of the delay and the throughput, while significantly reducing the network power consumption.     

Incorporating Ancestors' Influence in Genetic Algorithms

A new criterion of fitness evaluation for Genetic Algorithms is introduced where the fitness value of an individual is determined by considering its own fitness as well as those of its ancestors. Some guidelines for selecting the weighting coefficients for quantifying the importance to be given to the fitness of the individual and its ancestors are provided. This is done both heuristically and automatically under fixed and adaptive frameworks. The Schema Theorem corresponding to the proposed concept is derived. The effectiveness of this new methodology is demonstrated extensively on the problems of optimizing complex functions including a noisy one and selecting optimal neural network parameters.     

The OODB path-method generator (PMG) using access weights and precomputed access relevance

A path-method is used as a mechanism in object-oriented databases (OODBs) to retrieve or to update information relevant to one class that is not stored with that class but with some other class. A path-method is a method which traverses from one class through a chain of connections between classes and accesses information at another class. However, it is a difficult task for a casual user or even an application programmer to write path-methods to facilitate queries. This is because it might require comprehensive knowledge of many classes of the conceptual schema that are not directly involved in the query, and therefore may not even be included in a user's (incomplete) view about the contents of the database. We have developed a system, called path-method generator (PMG), which generates path-methods automatically according to a user's database-manipulating requests. The PMG offers the user one of the possible path-methods and the user verifies from his knowledge of the intended purpose of the request whether that path-method is the desired one. If the path method is rejected, then the user can utilize his now increased knowledge about the database to request (with additional parameters given) another offer from the PMG. The PMG is based on access weights attached to the connections between classes and precomputed access relevance between every pair of classes of the OODB. Specific rules for access weight assignment and algorithms for computing access relevance appeared in our previous papers [MGPF92, MGPF93, MGPF96]. In this paper, we present a variety of traversal algorithms based on access weights and precomputed access relevance. Experiments identify some of these algorithms as very successful in generating most desired path-methods. The PMG system utilizes these successful algorithms and is thus an efficient tool for aiding the user with the difficult task of querying and updating a large OODB. Received July 19, 1993 / Accepted May 16, 1997     

Dynamic Modeling and Simulation of Impact in Tether Net/Gripper systems

The objective of this paper is to study the dynamic modeling andsimulation of a tether-net/gripper system during an impact, while it isbeing deployed or retrieved by a winch on a satellite orbiting aroundearth. We stick to Tether-Net system but the analysis is applicable toTether-Gripper systems too. We assume that the net is deployed from thesatellite in orbit and the motion is restricted to the orbital plane.This net captures a second satellite and tows it. The motion of atether-net system can be broken down into the following phases: (i)Phase 1: Net is shot out from the satellite with the tether completelyslack, (ii) Phase 2: Net comes to a location where the tether is tautwhile the drum on the orbiter is locked, (iii) Phase 3: Drum is unlockedand the net moves with the tether, (iv) Phase 4: Net captures a body.The continua (tether) is modeled using mode functions and coordinates.The theory of impulse and momentum can be used to model Phases 1, 2, and4 of motion of the tether-net system. The dynamics of the motion of thesystem in phase 3 is characterized by differential and algebraicequations (DAEs). Matlab ODE solvers were used to solve these DAEs.     

FRAPP: a framework for high-accuracy privacy-preserving mining

To preserve client privacy in the data mining process, a variety of techniques based on random perturbation of individual data records have been proposed recently. In this paper, we present FRAPP, a generalized matrix-theoretic framework of random perturbation, which facilitates a systematic approach to the design of perturbation mechanisms for privacy-preserving mining. Specifically, FRAPP is used to demonstrate that (a) the prior techniques differ only in their choices for the perturbation matrix elements, and (b) a symmetric positive-definite perturbation matrix with minimal condition number can be identified, substantially enhancing the accuracy even under strict privacy requirements. We also propose a novel perturbation mechanism wherein the matrix elements are themselves characterized as random variables, and demonstrate that this feature provides significant improvements in privacy at only a marginal reduction in accuracy. The quantitative utility of FRAPP, which is a general-purpose random-perturbation-based privacy-preserving mining technique, is evaluated specifically with regard to association and classification rule mining on a variety of real datasets. Our experimental results indicate that, for a given privacy requirement, either substantially lower modeling errors are incurred as compared to the prior techniques, or the errors are comparable to those of direct mining on the true database. A partial and preliminary version of this paper appeared in the Proc. of the 21st IEEE Intl. Conf. on Data Engineering (ICDE), Tokyo, Japan, 2005, pgs. 193–204.     

Electrical conduction mechanism in solution grown doped polyvinyl pyrrolidone films

A detailed study of electrical conduction mechanism in bimetallized ferrocene-doped polyvinyl pyrrolidone films was carried out. The measurements were carried out on films of about 20 μm thick, in the field range of (2.0–8.0) x 10⁴ V/cm at temperatures ranging from 363 to 423 K. An investigation of the effect of impurity such as ferrocene in the polymer matrix was undertaken. Lowering of activation energy and increase in current due to doping were observed. The results showed that the charge carriers were generated by field-assisted lowering of coulombic barriers at the traps and were conducted through the bulk of the material by a hopping process between the localized states by a Jonscher-Ansari modified Poole-Frenkel mechanism. The dependence of current and activation energy on the ferrocene concentration is explained on the basis of charge transfer type of interaction between dopant and polymeric material.     

Structural properties of GaN grown on AlGaN/AlN stress mitigating layers on 100-mm Si (111) by ammonia molecular beam epitaxy

The structural properties of GaN grown on AlGaN/AlN stress mitigating layers on 100-mm diameter Si (111) substrate by ammonia molecular beam epitaxy have been reported. High resolution X-ray diffraction, micro-Raman spectroscopy, transmission electron microscopy and secondary ion mass spectroscopy have been used to study the influence of AlN thickness and AlGaN growth temperature on the quality of GaN. GaN grown on thicker AlN showed reduced dislocation density and lesser tensile strain. Three-dimensional growth regime was observed for GaN grown at lower AlGaN growth temperature while higher AlGaN growth temperature resulted in two-dimensional growth mode. The dislocation bending and looping at the AlGaN/AlN interface was found to have significant influence on the dislocation density and strain in the GaN layer. The evolution and interaction of threading dislocations play a major role in determining the quality and the strain states of GaN.     

Exploring spatial datasets with histograms

As online spatial datasets grow both in number and sophistication, it becomes increasingly difficult for users to decide whether a dataset is suitable for their tasks, especially when they do not have prior knowledge of the dataset. In this paper, we propose browsing as an effective and efficient way to explore the content of a spatial dataset. Browsing allows users to view the size of a result set before evaluating the query at the database, thereby avoiding zero-hit/mega-hit queries and saving time and resources. Although the underlying technique supporting browsing is similar to range query aggregation and selectivity estimation, spatial dataset browsing poses some unique challenges. In this paper, we identify a set of spatial relations that need to be supported in browsing applications, namely, the contains, contained and the overlap relations. We prove a lower bound on the storage required to answer queries about the contains relation accurately at a given resolution. We then present three storage-efficient approximation algorithms which we believe to be the first to estimate query results about these spatial relations. We evaluate these algorithms with both synthetic and real world datasets and show that they provide highly accurate estimates for datasets with various characteristics. Recommended by: Sunil Prabhakar Work supported by NSF grants IIS 02-23022 and CNF 04-23336. An earlier version of this paper appeared in the 17th International Conference on Data Engineering (ICDE 2001).     

Consideration of Trends in Evaluating Inter-basin Water Transfer Alternatives within a Fuzzy Decision Making Framework

Evaluation of water supply schemes is an essential task for meeting the goals of inter-basin water transfer project system management. In general, water supply operation involves multi-objective and multifactor optimization and decision. In recent years, multicriterion decision making (MCDM) has emerged as an effective methodology due to its ability to combine quantitative and qualitative criteria for selection of the best alternative. This paper presents a new optimization method using fuzzy pattern recognition to appraise the water supply decision schemes in inter-basin diversion systems. The proposed method is capable to incorporate not only the will of the decision-makers but also the future development trend of water resources and water supply demand and makes the optimization results more reasonable and applicable. One case study for the Xi-River-to -Tanghe Reservoir Water Transfer Project System in China is presented to demonstrate the application of this method.