Longitudinal performance and reliability of microelectronic structures is strongly influenced by the condition of interconnects. Degradation processes invoke changes, progressive in time, on the surface, in the body o...
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Longitudinal performance and reliability of microelectronic structures is strongly influenced by the condition of interconnects. Degradation processes invoke changes, progressive in time, on the surface, in the body of interconnect layer, in the boundary between interconnect and the Si/SiO2 substrate, and in the area of substrate near Al line. Geometrical scale of these changes may vary in wide range, reaching nanometers. The authors investigate the condition of Al path of a fatigued commercial electronic circuit (memory), using in-house developed scanning thermal microscope (SThM) and commercial high resolution X-ray diffractometer (XRD). Series of SThM images were obtained for varying temperature of Wollaston probe working in active mode. The images, after processing by 2-dimensional spatial FFT, reveal various ingredients of the surface and internal structure of the Al line. FFT power spectrum dispersion is proposed as a measure of the amount of information available from the scan image. This measure may be used to determine the most efficient temperature of Wollaston probe. The result is a preliminary analysis of feasibility of the SThM approach for characterization of degradation process. In general SThM shall be perceived as a new technique for reliability analysis. (C) 2011 Elsevier Ltd. All rights reserved.
The process of rapid urbanization is attended by various adverse effects on the society, the ecology, and the economy. Effective urban and regional planning is the key to minimizing these effects and the impact on the...
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The process of rapid urbanization is attended by various adverse effects on the society, the ecology, and the economy. Effective urban and regional planning is the key to minimizing these effects and the impact on the people who live in cities. For this reason, detailed geospatial information on urban dynamics is needed, which can help to analyze and understand the process of urbanization. Different studies have shown that high-resolution radar imagery is an excellent basis for classifying, monitoring, and analyzing the outline and spatio-temporal development of urban agglomerations. Specifically, the analysis of texture information based on local speckle characteristics has shown its ability to generate large area urban maps. In this study a pixel-based, fully automatic classification approach developed for TerraSAR-X StripMap data was transferred and applied to five RADARSAT-2 images acquired in ultra-fine mode. The algorithm was applied to data from the cities of Mannheim and Ludwigshafen and their rural surroundings in Germany. The classification approach was validated for its multisensoral transferability and robustness. A relative comparison to a TerraSAR-X classification and an absolute comparison to a reference dataset show promising results and allow for the conclusion that the methodology can be fully applied to RADARSAT-2 data.
Conventional adaptive filtering algorithms, typically limited to the control of single or multiple sinusoids, are not appropriate to control modulated vibrations, especially in the presence of rich side band structure...
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Conventional adaptive filtering algorithms, typically limited to the control of single or multiple sinusoids, are not appropriate to control modulated vibrations, especially in the presence of rich side band structures. To overcome this deficiency, a new control algorithm is proposed that introduces a feedback loop with the model predictive sliding mode control (MPSMC) in the adaptive filtering system. Several amplitude and frequency modulation cases are first computationally studied, and conventional and proposed methods are comparatively evaluated in terms of estimation error, performance in time and frequency domains, stability, and uncertainty in the reference signal. To experimentally validate the proposed algorithm, an active strut (with longitudinal vibrations) is constructed. Overall, the proposed adaptive algorithm yields superior reductions at the main frequencies and at side bands;also, good attenuation is found on a broadband basis. (C) 2012 Elsevier Ltd. All rights reserved.
We study a maximization problem: online scheduling on m identical machines to maximize the number of early jobs. The problem is online in the sense that all jobs arrive over time. Each job's characteristics, such ...
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We study a maximization problem: online scheduling on m identical machines to maximize the number of early jobs. The problem is online in the sense that all jobs arrive over time. Each job's characteristics, such as processing time and due date, become known at its arrival time. We consider the preemption-restart model, in which preemption is allowed, while once a job is restarted, it loses all the progress that has been made on this job so far. If in some schedule a job is completed before or at its due date, then it is called early (or on time). The objective is to maximize the number of early jobs. For m identical machines, we prove an upper bound 1 - (1/2m) of competitive ratio and show that ECT (earliest completion time) algorithm is 1/2-competitive.
A cross-layer scheduling algorithm that combines packet scheduling and an efficient bandwidth allocation for orthogonal frequency division multiple access (OFDMA) systems with heterogeneous user's delay requiremen...
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A cross-layer scheduling algorithm that combines packet scheduling and an efficient bandwidth allocation for orthogonal frequency division multiple access (OFDMA) systems with heterogeneous user's delay requirements are proposed. The proposed work employs channel fluctuation and queue states in their decision rules for packet scheduling, which determines the optimum subcarrier allocation policy to maximise the system throughput subject to individual user's delay constraints. The delay sensitive subcarrier allocation strategy has linear complexity with respect to the number of users and number of subcarriers. The cross-layer scheduling algorithm also use an adaptive modulation and coding (AMC) scheme, which adapt according to the channel condition and queue states in terms of signal-to-noise ratio (SNR) constraints to improve the bandwidth usage in an efficient manner. The simulation results show that substantial throughput gain and spectral efficiency improvement are obtained while satisfying the delay constraint when the delay sensitive jointly optimum rate and subcarrier allocation policy with AMC is adopted.
Most computational problems for matrix semigroups and groups are inherently difficult to solve and even undecidable starting from dimension three. The questions about the decidability and complexity of problems for tw...
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Most computational problems for matrix semigroups and groups are inherently difficult to solve and even undecidable starting from dimension three. The questions about the decidability and complexity of problems for two-dimensional matrix semigroups remain open and are directly linked with other challenging problems in the field. In this paper we study the computational complexity of the problem of determining whether the identity matrix belongs to a matrix semigroup (the Identity Problem) generated by a finite set of 2 x 2 integral unimodular matrices. The Identity Problem for matrix semigroups is a well-known challenging problem, which has remained open in any dimension until recently. It is currently known that the problem is decidable in dimension two and undecidable starting from dimension four. In particular, we show that the Identity Problem for 2 x 2 integral unimodular matrices is NP-hard by a reduction of the Subset Sum Problem and several new encoding techniques. An upper bound for the nontrivial decidability result by C. Choffrut and J. Karhumaki is unknown. However, we derive a lower bound on the minimum length solution to the Identity Problem for a constructible set of instances, which is exponential in the number of matrices of the generator set and the maximal element of the matrices. This shows that the most obvious candidate for an NP algorithm, which is to guess the shortest sequence of matrices which multiply to give the identity matrix, does not work correctly since the certificate would have a length which is exponential in the size of the instance. Both results lead to a number of corollaries confirming the same bounds for vector reachability, scalar reachability and zero in the right upper corner problems.
Localizing dynamically changing diffuse event sources in real environments is still an open problem in wireless sensor networks (WSN). The dynamism of the environment, the energy limitations of the sensors, and the no...
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Localizing dynamically changing diffuse event sources in real environments is still an open problem in wireless sensor networks (WSN). The dynamism of the environment, the energy limitations of the sensors, and the noise associated to the sensors' measurements pose a challenge that begs a realistic solution. In this article we propose a decentralized approach to detect diffuse event sources in dynamic and noisy environments, using a wireless sensor network infrastructure. Our approach is gradient based and follows a distributed and decentralized algorithm based on local interactions and local knowledge of the environment. Reported experiments show that our approach efficiently adapts in tracking the event sources as they appear, is scalable, and is robust to noise and failures.
An algorithm for stereo-based obstacle detection in a general road scene is proposed. In the proposed algorithm, the vertical obstacles on a horizontal ground surface are defined as billboard planes, and the distant e...
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An algorithm for stereo-based obstacle detection in a general road scene is proposed. In the proposed algorithm, the vertical obstacles on a horizontal ground surface are defined as billboard planes, and the distant environment is modelled using a background wall. During stereo matching, each image pixel has a disparity value which is the distance to the billboard or the slope of the ground surface. The algorithm finally obtains a set of the billboard planes and efficiently manages them using frame coherence. Experimental results show that the use of billboard planes can effectively reduce the search range of disparities. Also, the proposed method produces reliable range data in accordance the KITTI benchmark.
Given the growing computational power of embedded controllers, the use of model predictive control (MPC) strategies on this type of devices becomes more and more attractive. This paper investigates the use of online M...
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Given the growing computational power of embedded controllers, the use of model predictive control (MPC) strategies on this type of devices becomes more and more attractive. This paper investigates the use of online MPC, in which at each step, an optimization problem is solved, on both a programmable automation controller (PAC) and a programmable logic controller (PLC). Three different optimization routines to solve the quadratic program were investigated with respect to their applicability on these devices. To this end, an air heating setup was built and selected as a small-scalemulti-input single-output system. It turns out that the code generator (CVXGEN) is not suited for the PLC as the required programming language is not available and the programming concept with preallocated memory consumes too much memory. The Hildreth and qpOASES algorithms successfully controlled the setup running on the PLC hardware. Both algorithms perform similarly, although it takes more time to calculate a solution for qpOASES. However, if the problem size increases, it is expected that the high number of required iterations when the constraints are hit will cause the Hildreth algorithm to exceed the necessary time to present a solution. For this small heating problem under test, the Hildreth algorithm is selected as most useful on a PLC.
Among the most promising and active research areas in heuristic optimisation is the field of adaptive memetic algorithms (AMAs). These gain much of their reported robustness by adapting the probability with which each...
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Among the most promising and active research areas in heuristic optimisation is the field of adaptive memetic algorithms (AMAs). These gain much of their reported robustness by adapting the probability with which each of a set of local improvement operators is applied, according to an estimate of their current value to the search process. This paper addresses the issue of how the current value should be estimated. Assuming the estimate occurs over several applications of a meme, we consider whether the extreme or mean improvements should be used, and whether this aggregation should be global, or local to some part of the solution space. To investigate these issues, we use the well-established COMA framework that coevolves the specification of a population of memes (representing different local search algorithms) alongside a population of candidate solutions to the problem at hand. Two very different memetic algorithms are considered: the first using adaptive operator pursuit to adjust the probabilities of applying a fixed set of memes, and a second which applies genetic operators to dynamically adapt and create memes and their functional definitions. For the latter, especially on combinatorial problems, credit assignment mechanisms based on historical records, or on notions of landscape locality, will have limited application, and it is necessary to estimate the value of a meme via some form of sampling. The results on a set of binary encoded combinatorial problems show that both methods are very effective, and that for some problems it is necessary to use thousands of variables in order to tease apart the differences between different reward schemes. However, for both memetic algorithms, a significant pattern emerges that reward based on mean improvement is better than that based on extreme improvement. This contradicts recent findings from adapting the parameters of operators involved in global evolutionary search. The results also show that local reward schemes o
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