Abstraction is a powerful thing. During the 19th century, the industrial revolution was built on many powerful abstractions, such as mass, energy, work, and power. During the 20th century, the information revolution w...
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Abstraction is a powerful thing. During the 19th century, the industrial revolution was built on many powerful abstractions, such as mass, energy, work, and power. During the 20th century, the information revolution was built on many powerful abstractions, such as binary digit or bit, binary coding, and algorithmic complexity. Here, we propose an abstraction that will be important to the service revolution of the 21st century: the service system, which is a configuration of people, technologies, and other resources that interact with other service systems to create mutual value. Many systems can be viewed as service systems, including families, cities, and companies, among many others. In this paper, we show how the service-system abstraction can be used to understand how value is created, in the process unifying concepts from many disciplines and creating the foundation for an integrated science of service.
A hybrid framework of probabilistic atlas and statistical shape and appearance model (SSAM) is proposed to achieve 3D prostate segmentation. An initial 3D segmentation of the prostate is obtained by registering the pr...
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A hybrid framework of probabilistic atlas and statistical shape and appearance model (SSAM) is proposed to achieve 3D prostate segmentation. An initial 3D segmentation of the prostate is obtained by registering the probabilistic atlas to the test dataset with deformable Demons registration. the initial results obtained are used to initialize multiple SSAMs corresponding to the apex, central and base regions of the prostate gland to incorporate local variabilities. Multiple mean parametric models of shape and appearance are derived from principal component analysis of prior shape and intensity information of the prostate from the training data. the parameters are then modified withthe prior knowledge of the optimization space to achieve 2D segmentation. the 2D labels are registered to the 3D labels generated using probabilistic atlas to constrain the pose variation and generate valid 3D shapes. the proposed method achieves a mean Dice similarity coefficient value of 0.89±0.11 and mean Hausdorff distance of 3.05±2.25 mm when validated with 15 prostate volumes of a public dataset in a leave-one-out validation framework.
We study the synthesis of policies for multi-agent systems to implement spatial-temporal tasks. We formalize the problem as a factored Markov decision process subject to so-called graph temporal logic specifications. ...
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ISBN:
(纸本)9781450375184
We study the synthesis of policies for multi-agent systems to implement spatial-temporal tasks. We formalize the problem as a factored Markov decision process subject to so-called graph temporal logic specifications. the transition function and the spatial-temporal task of each agent depend on the agent itself and its neighboring agents. the structure in the model and the specifications enable to develop a distributed algorithm that, given a factored Markov decision process and a graph temporal logic formula, decomposes the synthesis problem into a set of smaller synthesis problems, one for each agent. We prove that the algorithm runs in time linear in the total number of agents. the size of the synthesis problem for each agent is exponential only in the number of neighboring agents, which is typically much smaller than the number of agents. We demonstrate the algorithm in case studies on disease control and urban security. the numerical examples show that the algorithm can scale to hundreds of agents.
Lately, rapid advances in intelligent agents and agent-based systems have been attracting the attention of academicians and practitioners. Intelligent agents have attractive properties including: autonomy;proactivenes...
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Lately, rapid advances in intelligent agents and agent-based systems have been attracting the attention of academicians and practitioners. Intelligent agents have attractive properties including: autonomy;proactiveness;intelligence;social ability and other useful features. the field of DSS can benefit significantly by focusing on the above concerns through employment of agent-based technologies. this work proposes a framework for a single decision task DSS based on multi-agent architecture. the agents in the DSS employ fuzzy rules and fuzzy objectives when generating alternative decisions. the approach is demonstrated using the investment Multi-Agent DSS (MADSS) prototype. the experiments show that the fuzzy MADSS outperforms the traditional model plus data based DSS.
High level symbolic music notations and performance practices are all related to particular cultural traditions. For example, Gregorian Chant, Elizabethan Lute music, 19th century Romantic, and 20th century Avant-Gard...
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High level symbolic music notations and performance practices are all related to particular cultural traditions. For example, Gregorian Chant, Elizabethan Lute music, 19th century Romantic, and 20th century Avant-Garde musics all relate to different philosophies of space and time. A universal standard for music notation or its performance is therefore neither possible nor desirable. the Web should, in contrast, allow aural and written traditions to develop freely and independently. Specialists in particular traditions should be allowed to communicate efficiently withtheir peers, using scores and recordings which reflect those traditions, and which do not distort the subject matter. Living traditions should be allowed to develop. this paper approaches the problem by isolating and describing concepts shared by all music notations, using the architecture of a proposed, general purpose music editor as a framework. the editor uses nested levels of freely definable symbols and interchangeable software libraries to encapsulate information about each individual notation and performance tradition.
the coordinate operating process of a supply chain is considered. the supply chain is consisting of a manufacturer, a supplier and several customers, the semi- finished products of the supplier are raw materials of th...
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the coordinate operating process of a supply chain is considered. the supply chain is consisting of a manufacturer, a supplier and several customers, the semi- finished products of the supplier are raw materials of the manufacturer, demands of customers are uncertain, and the uncertainties of demands are described as fuzzy sets. A multi-objective fuzzy programming model for coordinate operations of the supply chain is constructed and a numerical example is proposed. the results of the numerical example shows that decision makers can obtain an optimal operations strategy by using the model proposed in this paper according to the level of uncertainties of demands, and the operation strategy possesses robustness in same ways.
Center location selection of coal bunker is an important and practical problem in coal mine production. Because of the complex relationship between influence variables and optimization goal, it is frequently to reach ...
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Center location selection of coal bunker is an important and practical problem in coal mine production. Because of the complex relationship between influence variables and optimization goal, it is frequently to reach a local optimization point rather than the global one by using linear programming. this paper combines nonlinear programming model and the algorithm of particle swarm optimization (PSO) to optimize the location selection of coal bunker in the coal mine transportation system. Firstly the coal bunker' center location selection problem is formalized and thereby the nonlinear programming model is constructed by minimizing the entire cost of the system. Secondly, the optimization model is solved by using the PSO algorithm and therefore the global optimization is reached. Finally the method mentioned above is verified by a typical coal bunker location selection example.
this paper presents the design of an adaptive hybrid controller for linear switched reluctance motor (LSRM) to be used in pick and place industrial applications. the hybrid controller consists of two main controllers,...
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ISBN:
(纸本)9781538609903
this paper presents the design of an adaptive hybrid controller for linear switched reluctance motor (LSRM) to be used in pick and place industrial applications. the hybrid controller consists of two main controllers, the proportional derivative controller (PDC) and the fuzzy logic controller (FLC). In this paper, the proposed Adaptive hybrid PD-fuzzy logic controller (AHPDFLC) uses, at the beginning, the adaptive PDC (APDC) for coarse position error while for fine position error the position control process is achieved using conventional FLC. this hybrid controller exploits the advantages of both controllers, APDC which can vary its gains online to avoid the overshoot problems and FLC which can decrease the steady-state error to roughly zero value to get an acceptable position tracking response of the underlying LSRM. the adaptivity of the hybrid controller refers to the variation of PDC's proportional and derivative gains to adapt a wide range of loading conditions i.e. a specific reference position signal, load force, mover mass, friction constant, applied dc voltage and phase resistance. PDC gain scheduling is achieved online based on fuzzy rules and reasoning. the results of AHPDFLC are compared withthe results of non-adaptive position controllers. this comparison between different position controllers' response verifies the simplicity and the effectiveness of the proposed adaptive hybrid position controller for a wide range of variable loading conditions. Finite Element Method Magnetics (FEMM) and MAT LAB/Simulink simulation programs are used throughout the paper to model the different modules of LSRM to prove the validity of this position controller approach on simulation environment.
the primary objective of this study is to assess the performance of hotels in Oman by developing an AI based model using a new approach that we refer to as Linear Genetic programming for Optimization Decision Tree (LG...
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the primary objective of this study is to assess the performance of hotels in Oman by developing an AI based model using a new approach that we refer to as Linear Genetic programming for Optimization Decision Tree (LGPDT). the LGPDT algorithm seeks to optimize decision trees, automatically select relevant input attributes, and adjust hyperparameters to improve prediction accuracy. the research findings demonstrate promise after testing the model with datasets from literature and the tourism sector. this approach has the potential to improve the assessment of hotel performance in Oman by providing accurate predictions of customer satisfaction, empowering managers to enhance their services and meet customers' demands more effectively.
Nanosecond scale pulsed high voltage discharges in air/fuel mixtures can generate radicals which in turn have been shown to improve combustion efficiency in gasoline fueled internal combustion engines. We are explorin...
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Nanosecond scale pulsed high voltage discharges in air/fuel mixtures can generate radicals which in turn have been shown to improve combustion efficiency in gasoline fueled internal combustion engines. We are exploring the possibility to extend such transient plasma generation and expected radical species generation to the range of pressures encountered in compression-ignition (diesel) engines having compression ratios of ~20:1, thereby improving lean burning efficiency and extending the range of lean combustion. Our preliminary experiments on streamer propagation velocities have shown deviations from simple (pd = const.) based similarity law in the pressure range of 1-8 bar in synthetic air [1]. Here we report the results of streamer propagation experiments in the extended range of air pressures, 6-18 bar. In order to extend our work to 18 bar, the gap size is reduced to 1.75 mm. Optical data obtained from PI-MAX 3 ICCD camera is complemented with electrical measurements to deduce average streamer velocities.
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