886,500 research outputs found

    Distributed-Pair Programming can work well and is not just Distributed Pair-Programming

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    Background: Distributed Pair Programming can be performed via screensharing or via a distributed IDE. The latter offers the freedom of concurrent editing (which may be helpful or damaging) and has even more awareness deficits than screen sharing. Objective: Characterize how competent distributed pair programmers may handle this additional freedom and these additional awareness deficits and characterize the impacts on the pair programming process. Method: A revelatory case study, based on direct observation of a single, highly competent distributed pair of industrial software developers during a 3-day collaboration. We use recordings of these sessions and conceptualize the phenomena seen. Results: 1. Skilled pairs may bridge the awareness deficits without visible obstruction of the overall process. 2. Skilled pairs may use the additional editing freedom in a useful limited fashion, resulting in potentially better fluency of the process than local pair programming. Conclusion: When applied skillfully in an appropriate context, distributed-pair programming can (not will!) work at least as well as local pair programming

    New understanding of the shape-memory response in thiol-epoxy click systems: towards controlling the recovery process

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    Our research group has recently found excellent shape-memory response in “thiol-epoxy” thermosets obtained with click-chemistry. In this study, we use their well-designed, homogeneous and tailorable network structures to investigate parameters for better control of the shape-recovery process. We present a new methodology to analyse the shape-recovery process, enabling easy and efficient comparison of shape-memory experiments on the programming conditions. Shape-memory experiments at different programming conditions have been carried out to that end. Additionally, the programming process has been extensively analysed in uniaxial tensile experiments at different shape-memory testing temperatures. The results showed that the shape-memory response for a specific operational design can be optimized by choosing the correct programming conditions and accurately designing the network structure. When programming at a high temperature (T » Tg), under high network mobility conditions, high shape-recovery ratios and homogeneous shape-recovery processes are obtained for the network structure and the programmed strain level (eD). However, considerably lower stress and strain levels can be achieved. Meanwhile, when programming at temperatures lower than Tg, considerably higher stress and strain levels are attained but under low network mobility conditions. The shape-recovery process heavily depends on both the network structure and eD. Network relaxation occurs during the loading stage, resulting in a noticeable decrease in the shape-recovery rate as eD increases. Moreover, at a certain level of strain, permanent and non-recoverable deformations may occur, impeding the completion and modifying the whole path of the shape-recovery process.Postprint (author's final draft

    Reoptimizations in linear programming

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    Replacing a real process which we are concerned in with other more convenient for the study is called modeling. After the replacement, the model is analyzed and the results we get are expanded on that process. Mathematical models being more abstract, they are also more general and so, more important. Mathematical programming is known as analysis of various concepts of economic activities with the help of mathematical modelsReoptimization, linear programming, mathematical model

    SCC: A Service Centered Calculus

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    We seek for a small set of primitives that might serve as a basis for formalising and programming service oriented applications over global computers. As an outcome of this study we introduce here SCC, a process calculus that features explicit notions of service definition, service invocation and session handling. Our proposal has been influenced by Orc, a programming model for structured orchestration of services, but the SCC’s session handling mechanism allows for the definition of structured interaction protocols, more complex than the basic request-response provided by Orc. We present syntax and operational semantics of SCC and a number of simple but nontrivial programming examples that demonstrate flexibility of the chosen set of primitives. A few encodings are also provided to relate our proposal with existing ones

    Concurrent constraint programming with process mobility

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    We propose an extension of concurrent constraint programming with primitives for process migration within a hierarchical network, and we study its semantics. To this purpose, we first investigate a "pure " paradigm for process migration, namely a paradigm where the only actions are those dealing with transmissions of processes. Our goal is to give a structural definition of the semantics of migration; namely, we want to describe the behaviour of the system, during the transmission of a process, in terms of the behaviour of the components. We achieve this goal by using a labeled transition system where the effects of sending a process, and requesting a process, are modeled by symmetric rules (similar to handshaking-rules for synchronous communication) between the two partner nodes in the network. Next, we extend our paradigm with the primitives of concurrent constraint programming, and we show how to enrich the semantics to cope with the notions of environment and constraint store. Finally, we show how the operational semantics can be used to define an interpreter for the basic calculus.

    Block-Based Development of Mobile Learning Experiences for the Internet of Things

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    The Internet of Things enables experts of given domains to create smart user experiences for interacting with the environment. However, development of such experiences requires strong programming skills, which are challenging to develop for non-technical users. This paper presents several extensions to the block-based programming language used in App Inventor to make the creation of mobile apps for smart learning experiences less challenging. Such apps are used to process and graphically represent data streams from sensors by applying map-reduce operations. A workshop with students without previous experience with Internet of Things (IoT) and mobile app programming was conducted to evaluate the propositions. As a result, students were able to create small IoT apps that ingest, process and visually represent data in a simpler form as using App Inventor's standard features. Besides, an experimental study was carried out in a mobile app development course with academics of diverse disciplines. Results showed it was faster and easier for novice programmers to develop the proposed app using new stream processing blocks.Spanish National Research Agency (AEI) - ERDF fund

    Linear Programming for a Cutting Problem in the Wood Processing Industry – A Case Study

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    In this paper the authors present a case study from the wood-processing industry. It focuses on a cutting process in which material from stock is cut down in order to provide the items required by the customers in the desired qualities, sizes, and quantities. In particular, two aspects make this cutting process special. Firstly, the cutting process is strongly interdependent with a preceding handling process, which, consequently, cannot be planned independently. Secondly, if the trim loss is of a certain minimum size, it can be returned into stock and used as input to subsequent cutting processes. In order to reduce the cost of the cutting process, a decision support tool has been developed which incorporates a linear programming model as a central feature. The model is described in detail, and experience from the application of the tool is reported.one-dimensional cutting, linear programming, wood-processing industry

    Comparative study of different approaches to solve batch process scheduling and optimisation problems

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    Effective approaches are important to batch process scheduling problems, especially those with complex constraints. However, most research focus on improving optimisation techniques, and those concentrate on comparing their difference are inadequate. This study develops an optimisation model of batch process scheduling problems with complex constraints and investigates the performance of different optimisation techniques, such as Genetic Algorithm (GA) and Constraint Programming (CP). It finds that CP has a better capacity to handle batch process problems with complex constraints but it costs longer time

    Persistently optimal policies in stochastic dynamic programming with generalized discounting

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    In this paper we study a Markov decision process with a non-linear discount function. Our approach is in spirit of the von Neumann-Morgenstern concept and is based on the notion of expectation. First, we define a utility on the space of trajectories of the process in the finite and infinite time horizon and then take their expected values. It turns out that the associated optimization problem leads to a non-stationary dynamic programming and an infinite system of Bellman equations, which result in obtaining persistently optimal policies. Our theory is enriched by examples.Stochastic dynamic programming, Persistently optimal policies, Variable discounting, Bellman equation, Resource extraction, Growth theory
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