Exponential p-stability of singularly perturbed impulsive stochastic delay differential systems

In this paper, we study singularly perturbed impulsive stochastic delay differential systems (SPISDDSs). By establishing an L-operator delay differential inequality and using the stochastic analysis technique, we obtain some sufficient conditions ensuring the exponential p-stability of any solution of SPISDDSs for sufficiently small ɛ > 0. The results extend and improve the earlier publications. An example is also discussed to illustrate the efficiency of the obtained results.     

New delay-range-dependent exponential estimates for singular systems with time-varying delay

This paper considers the problem of exponential stability for continuous-time singular systems with interval time-varying delay. By defining a novel Lyapunov-Krasovskii function and giving a tighter upper bound of its derivative, a new delay-range-dependent exponential admissibility criterion, which not only guarantees the regularity, absence of impulses and exponential stability of the system but also gives the estimates of decay rate and decay coefficient, is established in terms of linear matrix inequality (LMI). The resulting criterion has advantages over the result previously reported by Haidar et al. [17] in that it involves fewer matrix variables but has less conservatism, which is established theoretically. Examples are provided to demonstrate the advantage of the proposed criterion.     

Expert-driven genetic algorithms for simulating evaluation functions

In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an appropriate expert (or mentor), we can evolve a program that is on par with top tournament-playing chess programs, outperforming a two-time World Computer Chess Champion. This performance gain is achieved by evolving a program that mimics the behavior of a superior expert. The resulting evaluation function of the evolved program consists of a much smaller number of parameters than the expert’s. The extended experimental results provided in this paper include a report on our successful participation in the 2008 World Computer Chess Championship. In principle, our expert-driven approach could be used in a wide range of problems for which appropriate experts are available.     

Visual quality assessment algorithms: what does the future hold?

Creating algorithms capable of predicting the perceived quality of a visual stimulus defines the field of objective visual quality assessment (QA). The field of objective QA has received tremendous attention in the recent past, with many successful algorithms being proposed for this purpose. Our concern here is not with the past however; in this paper we discuss our vision for the future of visual quality assessment research. We first introduce the area of quality assessment and state its relevance. We describe current standards for gauging algorithmic performance and define terms that we will use through this paper. We then journey through 2D image and video quality assessment. We summarize recent approaches to these problems and discuss in detail our vision for future research on the problems of full-reference and no-reference 2D image and video quality assessment. From there, we move on to the currently popular area of 3D QA. We discuss recent databases, algorithms and 3D quality of experience. This yet-nascent technology provides for tremendous scope in terms of research activities and we summarize each of them. We then move on to more esoteric topics such as algorithmic assessment of aesthetics in natural images and in art. We discuss current research and hypothesize about possible paths to tread. Towards the end of this article, we discuss some other areas of interest including high-definition (HD) quality assessment, immersive environments and so on before summarizing interesting avenues for future work in multimedia (i.e., audio-visual) quality assessment.     

Probabilistic Grammars and Languages

Using an asymptotic characterization of probabilistic finite state languages over a one-letter alphabet we construct a probabilistic language with regular support that cannot be generated by probabilistic CFGs. Since all probability values used in the example are rational, our work is immune to the criticism leveled by Suppes (Synthese 22:95–116, 1970) against the work of Ellis (1969) who first constructed probabilistic FSLs that admit no probabilistic FSGs. Some implications for probabilistic language modeling by HMMs are discussed.     

A simulated annealing algorithm approach to hybrid flow shop scheduling with sequence-dependent setup times

One of the scheduling problems with various applications in industries is hybrid flow shop. In hybrid flow shop, a series of n jobs are processed at a series of g workshops with several parallel machines in each workshop. To simplify the model construction in most research on hybrid flow shop scheduling problems, the setup times of operations have been ignored, combined with their corresponding processing times, or considered non sequence-dependent. However, in most real industries such as chemical, textile, metallurgical, printed circuit board, and automobile manufacturing, hybrid flow shop problems have sequence-dependent setup times (SDST). In this research, the problem of SDST hybrid flow shop scheduling with parallel identical machines to minimize the makespan is studied. A novel simulated annealing (NSA) algorithm is developed to produce a reasonable manufacturing schedule within an acceptable computational time. In this study, the proposed NSA uses a well combination of two moving operators for generating new solutions. The obtained results are compared with those computed by Random Key Genetic Algorithm (RKGA) and Immune Algorithm (IA) which are proposed previously. The results show that NSA outperforms both RKGA and IA.     

Distributed production planning based on ATC and MOILP considering different coordination patterns

This paper is aimed at employing analytical target cascading (ATC) to solve the distributed production planning problem. In the ATC hierarchy, by setting a parent element to the core enterprise and a child element to each manufacturer, the core enterprise can negotiate the plans with the manufactures. Individual manufactures are able to make production plans autonomously, and finally achieve the global objective under the coordination of the core enterprise. ATC offers an independent decision making ability to each member, a decentralize coordination strategy to the core enterprise and a parallel computing method to the planning model. In order to obtain the concrete production quantities and balance the costs and the service levels, a multi-objective integer linear programming has also been introduced in the model, where different costs have different weights. By setting different weights to different optimization objectives, the core enterprise can obtain the lowest overall cost or the best service quantity. Meanwhile, from a strategic point of view, two coordination patterns, competitive and cooperative, through modifying the iterative mode of ATC, are addressed here. The competitive pattern make the core enterprise achieve a lower cost, while the cooperative pattern make the core enterprise maintain a better relationship with the manufactures. A series of comparative analyses are conducted to identify the strengths of the ATC method and demonstrate the effectiveness of the proposed coordination patterns. In particular, one of these experiments, which considers the quantity discount, has been done to further verify the effectiveness of the ATC based coordination mechanism while encountering the newly added decision-making factors.     

An effective algorithm to detect both smoke and flame using color and wavelet analysis

Fire detection is an important task in many applications. Smoke and flame are two essential symbols of fire in images. In this paper, we propose an algorithm to detect smoke and flame simultaneously for color dynamic video sequences obtained from a stationary camera in open space. Motion is a common feature of smoke and flame and usually has been used at the beginning for extraction from a current frame of candidate areas. The adaptive background subtraction has been utilized at a stage of moving detection. In addition, the optical flow-based movement estimation has been applied to identify a chaotic motion. With the spatial and temporal wavelet analysis, Weber contrast analysis and color segmentation, we achieved moving blobs classification. Real video surveillance sequences from publicly available datasets have been used for smoke detection with the utilization of our algorithm. We also have conducted a set of experiments. Experiments results have shown that our algorithm can achieve higher detection rate of 87% for smoke and 92% for flame.     

An algorithm for detection and phase estimation of protective elements periodic lattice on document image

Various periodic security elements, such as holograms, watermarks, and guilloches, are applied to documents in order to protect against counterfeiting. These elements can be detected and used to automatically check the authenticity of a document and to identify its type. They also make it possible to use special OCR system parameters in areas of security elements. This paper is devoted to developing methods for the detection and localization of periodic background patterns based on two-dimensional discrete Fourier transform. The model of a document image with a periodic background structure is considered. Algorithms for the detection and localization of background structures that follow from the model are discussed. The behavior and accuracy characteristics of the algorithms are tested on samples of Russian passport images. Their tolerance to errors in document boundary detection are experimentally analyzed. Modified detection and localization algorithms that improve the separating detection capability and reduce localization error twofold are proposed such as masking and replacement of noisy parts of document images, background spectrum suppression, and estimation of phase components of a single periodic element.