the problem of representing and learning complex visual stimuli in the context of modeling the process of conditional reflex formation is considered. the generative probabilistic framework is chosen which has been rec...
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the problem of representing and learning complex visual stimuli in the context of modeling the process of conditional reflex formation is considered. the generative probabilistic framework is chosen which has been recently successfully applied to cognitive modeling. A model capable of learning different visual stimuli is developed in the form of a program in Church (probabilistic programming language). NAO robot is programmed to detect visual stimuli, to point at selected stimuli in a sequence of trials, and to receive reinforcement signals for correct choices. Conducted experiments showed that the robot can learn stimuli of different types showing different decision-making behavior in a series of trial that could help arranging psychophysiological experiments.
A predictor-corrector smoothing Newton method is presented for solving the symmetric conic linear programming (SCLP). the proposed algorithm reformulates the SCLP as a nonlinear system of equations and then applies Ne...
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In recent years, high power consumption in the cloud data center environment become major issue. Ever increasing resource demands increase the power consumption in cloud environment. High power consumption increase th...
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ISBN:
(纸本)9781450341790
In recent years, high power consumption in the cloud data center environment become major issue. Ever increasing resource demands increase the power consumption in cloud environment. High power consumption increase the operating budget, it responsible for co2 emissions which harmful to environment. So, we need to minimize the power consumption. Although several algorithms have been suggested to solve this problem, in this paper we present exhibit energy utilization assessment on the impacts of live migration of VMs. We proposed framework which objective is to combine the most extreme number of Virtual machines (VMs) on least number of Hosts. We used linear programming for optimal Virtual machine (VM) reallocation. As appeared by experimental results, minimize power consumption in cloud data center environment. Experiment performed using CloudSim Toolkit.
Graphical user interfaces (GUIs) are hard to combine withfunctionalprogramming. Using a suitable combination of monads, we are able to tame the imperative aspects of graphical I/O in a straightforward and elegant wa...
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ISBN:
(纸本)354060359X
Graphical user interfaces (GUIs) are hard to combine withfunctionalprogramming. Using a suitable combination of monads, we are able to tame the imperative aspects of graphical I/O in a straightforward and elegant way. We present a concept to integrate lightweight GUIs into the functional framework, together with a library of basic functions and layout combinators to manipulate the GUI. An implementation of this library, using a set of high-level graphical I/O routines, is outlined. Examples demonstrate the simple way in which applications can be written.
A bi-level programming model is constructed for the oilfield development in this paper withthe objective to maximize the total benefit. the management level of the oil company is regarded as the leader in this model,...
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A bi-level programming model is constructed for the oilfield development in this paper withthe objective to maximize the total benefit. the management level of the oil company is regarded as the leader in this model, which makes the global programming and assigns the allocated investments to four oilfield development modes (the follower). the lower levels work out their own optimized plans according to the tasks and the investment constraints, and then feed back to the upper level. To solve this mixed integer nonlinear programming problem, the Interactive Intuitionistic Fuzzy methods are employed to obtain the solution by combining withthe intuitionistic fuzzy sets and establishing a scoring function. A practical example from some Oilfield in China is used to illustrate the application of the method for the "14th Five-year Plan". (C) 2020 the Authors. Published by Elsevier B.V. this is an open access article under the CC BY-NC-ND license (http://***/licenses/by-ne-nd/4.0/) Peer-review under responsibility of the scientific committee of the 7thinternationalconference on Information Technology and Quantitative Management (ITQM 2019)
the separation of concerns as a conceptual paradigm, aims to manage the complexity of the software systems by dividing them into different concerns and aspects. the benefits of this paradigm such as adaptability, reus...
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ISBN:
(纸本)9781450361019
the separation of concerns as a conceptual paradigm, aims to manage the complexity of the software systems by dividing them into different concerns and aspects. the benefits of this paradigm such as adaptability, reuse and maintenance, have been key drivers of its adoption and usability. these quality attributes have been discussed in aspect-oriented programming (AOP) which is a complement to traditional programming methods, whether object-oriented programming or procedural programming. the main concept of AOP is to gather the treatments related to a specific concern (problem) in a centralized unit called aspect. In this paper, two case studies of AOP are conducted with AspectJ: i) through three different implementations, addressing three distinct issues: Logging, Adding features and Using the Observer design pattern, and ii) through the design of aspect mobile application that is easy to use and quickly accessible and especially through Android devices. Also, the different technologies of AspectJ are used to design our application and illustrate the modularity and the composition of components (database manager, development software, and plugins). For each case study, we present the advantages and disadvantages to better understand and decompose the applications using this programming paradigm. Potential implementation examples are provided to support the explanation of the different situations and justify the use of the AOP to solve these issues. OSGi framework can also be used in the future work to offer dynamic manner of mobile applications.
We investigate the possibility of extending some results of Pazman and Pronzato (Ann Stat 42(4):1426-1451, 2014) to a larger set of optimality criteria. Namely, the problems of computing D-, A-, and -optimal designs i...
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We investigate the possibility of extending some results of Pazman and Pronzato (Ann Stat 42(4):1426-1451, 2014) to a larger set of optimality criteria. Namely, the problems of computing D-, A-, and -optimal designs in a linear regression model are reformulated here as "infinite-dimensional" linear programming problems. the same approach is applied to combination of these optimality criteria and to the "criterion robust" problem of Harman (Metrika 60:137-153, 2004). Approximate optimum designs can then be computed by a relaxation method (Shimizu and Aiyoshi in IEEE Trans Autom Control 25(1):62-66, 1980), and this is illustrated on various examples.
Instruction scheduling is an important issue in the compiler optimization for embedded systems. the instruction scheduling problem is mainly solved heuristically since finding an optimal solution requires significant ...
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ISBN:
(纸本)9781424425389
Instruction scheduling is an important issue in the compiler optimization for embedded systems. the instruction scheduling problem is mainly solved heuristically since finding an optimal solution requires significant computational resources and, in general, the problem of optimally scheduling instructions is known to be NP-Complete. the development of processors with pipelines and multiple functional units has increased the demands on compiler writers to write complex instruction scheduling algorithms. these algorithms are required to ensure that the most efficient use of resources, i.e. the functional units and pipelines of the processor, is made due to the increased complexity of processor architectures. In this paper, the specific problem of automatically creating instruction scheduling heuristics is addressed.
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