In this paper nl approach of an on-chip safety system architecture conforming to the second edition of the standard IEC 61508 is presented. The presented chip considers on-chip redundancy with the presence of diagnost...
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In this paper nl approach of an on-chip safety system architecture conforming to the second edition of the standard IEC 61508 is presented. The presented chip considers on-chip redundancy with the presence of diagnostic units and is designed to meet the highest possible safety integrity level for on-chip systems. The presented on-chip safety system consists of two redundant processor channels, each of which has a processor unit, data memory, program memory, communication interfaces, inputs and outputs. Furthermore, on-chip diagnosis- and monitoring units and a communication core are integrated. The safety-related implementation of the proposed architecture is introduced in this paper. This includes hardware and software implementation methodologies. Finally, a brief evaluation of the presented architecture is presented.
Procedural content generation (PCG) is a research field on the rise, with numerous papers devoted to this topic. This paper presents a PCG method based on a self-adaptive evolution strategy for the automatic generatio...
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Procedural content generation (PCG) is a research field on the rise, with numerous papers devoted to this topic. This paper presents a PCG method based on a self-adaptive evolution strategy for the automatic generation of maps for the real-time strategy (RTS) game Planet Wars. These maps are generated in order to fulfill the aesthetic preferences of the user, as implied by her assessment of a collection of maps used as training set A topological approach is used for the characterization of the maps and their subsequent evaluation: the sphere-of-influence graph (SIG) of each map is built, several graph-theoretic measures are computed on it, and a feature selection method is utilized to determine adequate subsets of measures to capture the class of the map. A multiobjective evolutionary algorithm is subsequently employed to evolve maps, using these feature sets in order to measure distance to good (aesthetic) and bad (non-aesthetic) maps in the training set. The so-obtained results are visually analyzed and compared to the target maps using a Kohonen network.
Since the advent of traditional random access memory (RAM) tests, such as Checkerboard, more sophisticated tests and fault models have evolved, taking the characteristics of memories into account. Thus, given a specif...
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Since the advent of traditional random access memory (RAM) tests, such as Checkerboard, more sophisticated tests and fault models have evolved, taking the characteristics of memories into account. Thus, given a specific type of memory, it would be straightforward to determine suitable state-of-the-art tests. However, the question our research focuses on is: “Which RAM tests do not need to be performed due to the safety architecture?” Even high-performance tests do require execution time. In the range of safety-related systems, diagnostics may consume most of the central processing unit (CPU) time, depending on the architecture. Therefore, this paper depicts how architectural characteristics can be taken into account to reasonably simplify specific RAM tests. This paper introduces our research on RAM tests in the range of safety-related systems. Therefore, key topics are introduced, first: comprehensively and starting from scratch, thus enabling anyone to follow our research. Second, an example is shown on how detecting stuck-at faults of address and data words, as demanded by IEC 61508 Ed.2.0, can be simplified by taking advantage of a 1oo2D safety architecture.
With the release of the second edition of the standard IEC 61508 for functional safety of electrical, electronic and programmable electronic systems, a set of methodologies and implementation techniques was presented,...
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With the release of the second edition of the standard IEC 61508 for functional safety of electrical, electronic and programmable electronic systems, a set of methodologies and implementation techniques was presented, which allows the realization and certification of safety-related solutions with on-chip redundancy. In a broader context, the standard ISO 26262 offers similar methodologies for safety solutions for automotive applications. The main focus of the research work of our institute is laid on the development and certification of safety-chips according to the standard IEC 61508. Together with an industrial partner, we are developing chip-based safety-related solutions for several industrial applications. In the same context, several semiconductor manufacturers addressed the development of such solutions in the last years, mainly with the focus on automotive applications. The present paper provides an overview of existing and planned safety chip architectures. Furthermore, a cursory analysis of the presented safety-chips is carried out with respect to the standard IEC 61508. A deep qualitative and quantitative analysis require experiments and simulations which will be carried out in future work.
Cardiotocography is one of the most widely used technique for recording changes in fetal heart rate (FHR) and uterine contractions. Assessing cardiotocography is crucial in that it leads to iden- tifying fetuses which...
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Cardiotocography is one of the most widely used technique for recording changes in fetal heart rate (FHR) and uterine contractions. Assessing cardiotocography is crucial in that it leads to iden- tifying fetuses which suffer from lack of oxygen, i.e. hypoxia. This situation is defined as fetal dis- tress and requires fetal intervention in order to prevent fetus death or other neurological disease caused by hypoxia. In this study a computer-based approach for analyzing cardiotocogram in- cluding diagnostic features for discriminating a pathologic fetus. In order to achieve this aim adaptive boosting ensemble of decision trees and various other machine learning algorithms are employed.
This paper presents an approach of textural signature identification for the classification of high resolution satellite image of forest. We are looking for the most appropriate combination of features from texture me...
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This paper presents an approach of textural signature identification for the classification of high resolution satellite image of forest. We are looking for the most appropriate combination of features from texture measures. This combination which forms our signature should allow the discrimination between different types of textures present in the image that will be classified. We improve our signature by a step of weighting features. The weight of each feature reflects its degree of confidence. We finish with an experimental step which is an application of our combined weighted signature for the purposes of classification of high resolution satellite image of forest.
In this work, classification of cellular structures in the high resolutional histopathological images and the discrimination of cellular and non-cellular structures have been investigated. The cell classification is a...
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In this work, classification of cellular structures in the high resolutional histopathological images and the discrimination of cellular and non-cellular structures have been investigated. The cell classification is a very exhaustive and time-consuming process for pathologists in medicine. The development of digital imaging in histopathology has enabled the generation of reasonable and effective solutions to this problem. Morever, the classification of digital data provides easier analysis of cell structures in histopathological data. Convolutional neural network (CNN), constituting the main theme of this study, has been proposed with different spatial window sizes in RGB color spaces. Hence, to improve the accuracies of classification results obtained by supervised learning methods, spatial information must also be considered. So, spatial dependencies of cell and non-cell pixels can be evaluated within different pixel neighborhoods in this study. In the experiments, the CNN performs superior than other pixel classification methods including SVM and k-Nearest Neighbour (k-NN). At the end of this paper, several possible directions for future research are also proposed.
This article focuses on an imperfect production inventory model considering product reliability and reworking of imperfect items in three-layer supply chain under fuzzy rough environment. In the model, the supplier re...
This article focuses on an imperfect production inventory model considering product reliability and reworking of imperfect items in three-layer supply chain under fuzzy rough environment. In the model, the supplier receives the raw materials, all are not of perfect quality, in a lot and delivers the items of superior quality to the manufacturer and the inferior quality items are sold at a reduced price in a single batch by the end of the cent percent screening process. The manufacturer produces a mixture of perfect and imperfect quality items. A portion of the imperfect items is transformed into perfect quality items after rework. Another portion of imperfect items, termed as `less perfect quality items', is sold at a reduced price to the retailer, and the portion which cannot be either transformed to the perfect quality items or sold at a reduce price is being rejected. Here, retailer purchases both the perfect and imperfect quality items from the manufacturer to sell the items to the customers through his/her respective showrooms of finite capacities. A secondary warehouse of infinite capacity is hired by the retailer on rental basis to store the excess quantity of perfect quality items. This model considers the impact of business strategies such as optimal order size of raw materials, production rate, and unit production cost in different sectors in a collaborating marketing system that can be used in the industry, like textile, footwear, and electronics goods. An analytical method has been used to optimize the production rate and raw material order size for maximization of the average profit of the integrated model. Finally, a numerical example is given to illustrate the model.
In this paper we study strong and weak bisimulation equivalences for continuous-time Markov decision processes (CTMDPs) and the logical characterizations of these relations with respect to the continuous-time stochast...
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Sum of squares (SOS) optimization has been a powerful and influential addition to the theory of optimization in the past decade. Its reliance on relatively large-scale semidefinite programming, however, has seriously ...
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Sum of squares (SOS) optimization has been a powerful and influential addition to the theory of optimization in the past decade. Its reliance on relatively large-scale semidefinite programming, however, has seriously challenged its ability to scale in many practical applications. In this paper, we introduce DSOS and SDSOS optimization as more tractable alternatives to sum of squares optimization that rely instead on linear programming and second order cone programming. These are optimization problems over certain subsets of sum of squares polynomials and positive semidefinite matrices and can be of potential interest in general applications of semidefinite programming where scalability is a limitation.
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