A Cyber-physical system (CPS) is an engineering system made of computational components, i.e. cyber elements, and physical elements, that are connected by a communication network. CPSs have emerged as the contemporari...
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ISBN:
(纸本)9781509011025
A Cyber-physical system (CPS) is an engineering system made of computational components, i.e. cyber elements, and physical elements, that are connected by a communication network. CPSs have emerged as the contemporarily leading technology in major industry sectors such as manufacture, aerospace, automotive, etc. Nowadays CPS is almost the synonym of control systems for large and complex engineering systems. In addition, CPSs have inevitably interweaved with new technologies like Internet of things, cloud computing, ubiquitous computing, and big data processing. Taming the complexity has been the key challenge in CPS design. A novel declarative computing based platform was proposed in our previous paper to unify modeling and design of both cyber and physical components in CPSs. In this paper, the concepts and principles of the proposed declarative platform are depicted in details. In addition, modeling techniques of declarative networking and declarative control are showcased with concrete simulation examples.
the proceedings contain 76 papers. the special focus in this conference is on Evolutionary Algorithms and Intelligent Simulation Algorithms. the topics include: A hybrid group search optimizer with opposition-based le...
ISBN:
(纸本)9789811003554
the proceedings contain 76 papers. the special focus in this conference is on Evolutionary Algorithms and Intelligent Simulation Algorithms. the topics include: A hybrid group search optimizer with opposition-based learning and differential evolution;a new firefly algorithm with local search for numerical optimization;a new trend peak algorithm with x-ray image for wheel hubs detection and recognition;community detection based on an improved genetic algorithm;selecting training samples from large-scale remote-sensing samples using an active learning algorithm;coverage optimization for wireless sensor networks by evolutionary algorithm;combining dynamic constrained many-objective optimization with DE to solve constrained optimization problems;executing time and cost-aware task scheduling in hybrid cloud using a modified DE algorithm;a novel differential evolution algorithm based on JADE for constrained optimization;a new ant colony classification mining algorithm;a dynamic search space strategy for swarm intelligence;adaptive mutation opposition-based particle swarm optimization;quick convergence algorithm of ACO based on convergence grads expectation;a new GEP algorithm and its applications in vegetable price forecasting modeling problems;an optimized clustering algorithm using improved gene expression programming;predicting acute hypotensive episodes based on multi GP;research on evolution mechanism in different-structure module redundancy fault-tolerant system;application of neural network for human actions recognition;the improved evaluation of virtual resources’ performance algorithm based on computer clusters;bayesian optimization algorithm based on incremental model building and an improved DBOA based on estimation of model similarity.
Gamification and in particular game-based learning is significantly gaining ground during the latest decades. It expresses a different approach to education that is mixing education with gaming, aiming to enhance the ...
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ISBN:
(纸本)9781509034307
Gamification and in particular game-based learning is significantly gaining ground during the latest decades. It expresses a different approach to education that is mixing education with gaming, aiming to enhance the learning experience with game mechanics and rules and to provide stronger motivations for lifelong learning. Many works have illustrated the benefits of learning while playing. this work presents such a game-based approach that has been adopted and used in the development of an online multiplayer platform game, with a purpose to teach or train programming with JavaScript. In effect it is like what is usually called a serious game, or a game with a purpose. the game, jLegends, is online and available for everyone to train and test knowledge on programming and logic, within a role-playing gaming approach. jLegends is built with source-code scalability in mind, in order to be expandable or even become open-sourced in the future.
Reliability and stability of power system are the main concern of power industry. However, increasing demands for energy increases the risk factor due to non-linearity of the power system. Sometimes, a small disturban...
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ISBN:
(纸本)9781467389624
Reliability and stability of power system are the main concern of power industry. However, increasing demands for energy increases the risk factor due to non-linearity of the power system. Sometimes, a small disturbance may create the chain of disturbances and results in a blackout. To avoid this eventuality, intensely islanding is the key option in which some area of the power system is detached from the affected area. this paper proposed a Mixed Integer Linear programming (MILP) based optimal placement of Phasor Measurement Units (PMUs) which provides the full observability of power system before and after the islanding of system. Maximum redundancy of the optimal number of PMUs is the additional feature of proposed method which increases the performance of state estimation. Single PMU outage case has been considered as a contingency in this paper, and the presence of zero injection buses has also been considered. All the simulations have been performed in Matlab and tested on IEEE 14-bus, IEEE 30-bus, IEEE 118-bus and New England 39-bus test systems. To check the effectiveness of proposed method, results have been compared with methods available in the literature.
Interval cost feature selection problems (ICFS) are popular in real-world. However, since the optimized objectives not only are multiple but also contain interval coefficients, there have been few solving methods. thi...
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ISBN:
(纸本)9783319410005;9783319409993
Interval cost feature selection problems (ICFS) are popular in real-world. However, since the optimized objectives not only are multiple but also contain interval coefficients, there have been few solving methods. this paper first transforms the ICFS into a multi-objective one with exact coefficients by the linear interval programming. Second, by combining a multi-objective particle swarm algorithm (which has a good performance in exploration) with a powerful problem-specific local search (which is good at exploitation), we propose a memetic multi-objective feature selection algorithm (MMFS-PSO). Finally, experimental results confirmed the advantages of our method.
the article analyses the prospects of optimizing the architecture and the execution logic of selected scripts available in MPD Root project. We considered the option of porting the scripts to allow execution on massiv...
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the proceedings contain 35 papers. the special focus in this conference is on Fuzzy Systems and Its Applications. the topics include: Analytic representation theorem of fuzzy-valued function based on methods of fuzzy ...
ISBN:
(纸本)9783319191041
the proceedings contain 35 papers. the special focus in this conference is on Fuzzy Systems and Its Applications. the topics include: Analytic representation theorem of fuzzy-valued function based on methods of fuzzy structured element;posynomial geometric programming with intuitionistic fuzzy coefficients;generalized multi-fuzzy soft set and its application in decision making;distance measures for interval-valued intuitionistic hesitant fuzzy sets;fuzzy inference modeling method based on t-s fuzzy system;econometric study on the influencing factors of china life insurance product demand based on fuzzy variable time series;sufficient conditions of cut sets on intuitionistic fuzzy sets;on the fuzzy fractional posynomial geometric programming problems;generalized fuzzy imaginary ideals of complemented semirings;statistical approximation of the q-bernstein-durrmeyer type operators;a new similarity measure between vague sets;distributivity equations between semi-t-operators over semi-uninorms;complex fuzzy set-valued complex fuzzy integral and its convergence theorem;complex fuzzy matrix and its convergence problem research;rough fuzzy concept lattice and its properties;dual hesitant fuzzy soft set and its properties;three-valued random fuzzy sets;improved interval-valued intuitionistic fuzzy entropy and its applications in multi-attribute decision making problems;approach to group decision making based on intuitionistic uncertain linguistic aggregation operators;statistical diagnostic of center fuzzy linear regression model based on fuzzy decentring degree;a new method of multiple attributes evaluation and selection in fuzzy environment;controlled remote information concentration via GHZ-type states and a new precipitable water vapor starma model based on newton's method.
Denotational semantics is an approach for giving a mathematical meaning to programming languages and systems. It gives the language designers a tool for high level abstract definitions. In aspect oriented programming,...
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ISBN:
(纸本)9781467386159
Denotational semantics is an approach for giving a mathematical meaning to programming languages and systems. It gives the language designers a tool for high level abstract definitions. In aspect oriented programming, advice is weaved in designated locations of an underlying program specified by a pointcut expression. It is the job of the language implementer to specify how weaved code gets to be inserted into the proper location. Current denotational semantics of languages do not have the necessary constructs for accepting this weaved code. In this paper, we preset a denotational semantics formal description that embodies the representation of constructs to be woven by some aspect. It illustrates the a formal description of the mechanism of where and how woven advice is inserted. the semantics presented are intended to be a general baseline for the use of any advice in any random joinpoint.
Cache Coherent NUMA (ccNUMA) architectures are a widespread paradigm due to the benefits they provide for scaling core count and memory capacity. Also, the flat memory address space they offer considerably improves pr...
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ISBN:
(纸本)9781450341219
Cache Coherent NUMA (ccNUMA) architectures are a widespread paradigm due to the benefits they provide for scaling core count and memory capacity. Also, the flat memory address space they offer considerably improves programmability. However, ccNUMA architectures require sophisticated and expensive cache coherence protocols to enforce correctness during parallel executions, which trigger a significant amount of on-and off-chip traffic in the system. this paper analyses how coherence traffic may be best constrained in a large, real ccNUMA platform through the use of a joint hardware/software approach. For several benchmarks, we study coherence traffic in detail under the influence of an added hierarchical cache layer in the directory protocol combined with runtime managed NUMA-aware scheduling and data allocation techniques to make most efficient use of the added hardware. the effectiveness of this joint approach is demonstrated by speedups of 1.23x to 2.54x and coherence traffic reductions between 44% and 77% in comparison to NUMA-oblivious scheduling and data allocation. Furthermore, we show that the NUMA-aware techniques we employ at the runtime level are crucial to ensure the added hierarchical layer in the directory coherence protocol does not introduce significant coherence traffic to the system.
In this paper, Gene Expression programming (GEP) based a wind turbine healthy condition identification model is proposed using generator current signals. Proposed GEP approach is capable to achieve very high classific...
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ISBN:
(纸本)9781509045303
In this paper, Gene Expression programming (GEP) based a wind turbine healthy condition identification model is proposed using generator current signals. Proposed GEP approach is capable to achieve very high classification accuracy. this is the first attempt to design such type of classifier using GEP for health condition identification of wind turbine. the beauty of proposed approach is to analyze the faults accurately with less process time. Moreover, proposed approach can also perform the self optimization process as it uses the function of both GA and GP in combine manner. Raw data of permanent magnet synchronous generator (PMSG) stator current is preprocessed through empirical mode decomposition (EMD) method to develop Intrinsic Mode functions (IMFs). Classifier uses the decision tree to further prune these IMFs to most relevant input variables which serve as input to GEP fault classifier. We compare performance of proposed GEP classifier with other AI based classifiers such as ANN and SVM. Obtained results and performance comparison shows that our proposed GEP based classifier could serve as an important tool for wind turbine fault diagnosis.
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