As the intelligence and connectivity are ubiquitous, the demand for AIoT devices are huge. But the constraint posed by fragmentation in IoT applications not only complicates development, but also increase the developm...
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ISBN:
(纸本)9798350387803;9798350387810
As the intelligence and connectivity are ubiquitous, the demand for AIoT devices are huge. But the constraint posed by fragmentation in IoT applications not only complicates development, but also increase the development costs, and impedes future scalability and maintenance. IoT products developed with great efforts invest with low sales volumes and a low return on investment, which dampens success for businesses to enter the IoT field and hinders the paces of IoT application development. In this paper, a scenario-based programming methodology and an effective IoT developer studio for makers and new beginners are presented, which can reduce the cost dramatically. Some use cases are also introduced to demonstrate the effectiveness of the solution for IoT application fragmentation problem.
We examine how students work in scenario-based and object oriented programming (OOP) languages, and qualitatively analyze the use of abstraction through the prism of the differences between the paradigms. The findings...
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ISBN:
(纸本)9781450327688
We examine how students work in scenario-based and object oriented programming (OOP) languages, and qualitatively analyze the use of abstraction through the prism of the differences between the paradigms. The findings indicate that when working in a scenario-based language, programmers think on a higher level of abstraction than when working with OOP languages. This is explained by other findings, which suggest how the declarative, incremental nature of scenario-based programming facilitates separation of concerns, and how it supports a kind of programming that allows programmers to work with a less detailed mental model of the system they develop. The findings shed light on how declarative approaches can reduce the cognitive load involved in programming, and how scenario-based programming might solve some of the difficulties involved in the use of declarative languages. This is applicable to the design of learning materials, and to the design of programming languages and tools.
PurposeSupply chain management has become critical in today's globalized environment, with growingly intense competition on the international level. The particular characteristics of modern trade have led companie...
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PurposeSupply chain management has become critical in today's globalized environment, with growingly intense competition on the international level. The particular characteristics of modern trade have led companies to globalize and devise increasingly sophisticated supply chains to meet customer demand worldwide. Motivated by the need to address these challenges, we have developed a new model for a global supply chain that incorporates uncertainties in exchange rates, demand fluctuations, and the quantity of ***/methodology/approachThe objective of the proposed model is to maximize supply chain profitability. Our model optimizes several critical decisions in the proposed global supply chain, including the location of domestic and foreign distribution centers, allocating the centers to customers, transportation mode selection, storage temperature, optimal farm purchase quantities, product flows across the network, and the shelf-life of products. scenario-based stochastic programming approach is employed to account for the inherent uncertainties within the model. A pistachio supply chain is examined as a case study in this article, and the efficiency of the proposed model is demonstrated through computational *** model was solved using the CPLEX solver in GAMS and the results, the Sirjan DDC and Turkey FDC have been selected. In general, 40% of demand for customers from FDC (turkey) and 60% of demand from DDC (sirjan) is provided. Changes in the demand of foreign customers make the net profit more effective than changes in the demand for domestic customers. The decrease in exchange rate decreases the network profit with a higher slope and the increase in exchange rate will increase network profit with a relatively stable ***/valueWhile research on GSCs for perishable products has been ongoing for several years, the importance of the subject necessitates continued investigation in this area. This paper aimed to address this gap
Nowadays, oil price fluctuation, fossil fuel depletion, and the potential environmental impact of these energy resources are highly threatening the global economy. Developing renewable resources, hence, is quite unavo...
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Nowadays, oil price fluctuation, fossil fuel depletion, and the potential environmental impact of these energy resources are highly threatening the global economy. Developing renewable resources, hence, is quite unavoidable. Sugarcane, as a source of renewable energy, can be converted to bioethanol. Therefore, this study has proposed a mixed-integer linear programming to design an international network of the sugarcane-to-biofuel supply chain. To deal with uncertainty, the robust optimization approach is employed in order to maximize the profit earned from the bioethanol sales at the foreign/domestic markets, minimize the environmental impacts caused by these supply chain activities, and maximize this network generated employment. The multi-echelon supply chain model involves different production/storage capacities, bio-refineries technologies, and transportation modes. This supply chain configuration has specified the optimal production capacity/technology, the appropriate transportation mode in each route, and the bio-refineries' development capacities. The biofuel export price and the domestic/foreign markets' demands are among the SC uncertain parameters addressed through the robust possibilistic programming. Finally, the tri-objective model has been solved using an approach that considers the decision maker's preferences;the model performance has been verified by a case study performed in Iran. To verify the robust model's efficiency, the DLP realization model is also formulated.
Context: Modern systems require programmers to develop code that dynamically adapts to different contexts, leading to the evolution of new context-oriented programming languages. These languages introduce new software...
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Context: Modern systems require programmers to develop code that dynamically adapts to different contexts, leading to the evolution of new context-oriented programming languages. These languages introduce new software-engineering challenges, such as: how to maintain the separation of concerns of the codebase? how to model the changing behaviors? how to verify the system behavior? and more. Objective: This paper introduces Context-Oriented Behavioral programming (COBP) - a novel paradigm for developing context-aware systems, centered on natural and incremental specification of context-dependent behaviors. As the name suggests, we combine behavioral-programming (BP) - a scenario-based modeling paradigm - with context idioms that explicitly specify when scenarios are relevant and what information they need. The core idea is to connect the behavioral model with a data model that represents the context, allowing an intuitive connection between the models via update and select queries. Combining behavioral-programming with context-oriented programming brings the best of the two worlds, solving issues that arise when using each of the approaches in separation. Methods: We begin with providing abstract semantics for COBP and two implementations for the semantics, laying the foundations for applying reasoning algorithms to context-aware behavioral programs. Next, we exemplify the semantics with formal specifications of systems, including a variant of Conway's Game of Life. Then, we provide two case studies of real-life context-aware systems (one in robotics and another in IoT) that were developed using this tool. Throughout the examples and case studies, we provide design patterns and a methodology for coping with the above challenges. Results: The case studies show that the proposed approach is applicable for developing real-life systems, and presents measurable advantages over the alternatives - behavioral programming alone and context-oriented programming alone. Conclusio
scenario-based programming (SBP) is an approach to modeling and running complex, event-based, system behavior by composing narrower views of overall behavior. In this paper we introduce significant extensions to the s...
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ISBN:
(数字)9783030378738
ISBN:
(纸本)9783030378738;9783030378721
scenario-based programming (SBP) is an approach to modeling and running complex, event-based, system behavior by composing narrower views of overall behavior. In this paper we introduce significant extensions to the strict interfaces by which scenarios in existing SBP frameworks specify what the system must, may, or must not do, and to the mechanisms that execute these scenarios: (i) we allow events with a multitude of variables and parameters;each event can become an entire model, and each event selection can be the selection of a major section of the new state of the system and the environment;(ii) we extend the basic request/block SBP interfaces with a rich set of composable constraints and functions, which can describe desired and undesired variable assignments, where each constraint may relate to all variables or to just a subset thereof;(iii) we introduce a central, application-agnostic mechanism for adding optimization to standard event selection;and (iv) we relate our method to Null-Space Behavior (NSB)-a successful compositional approach in control theory. We demonstrate these language-independent concepts through several use cases that are implemented in a variety of languages and solvers.
Electronic reverse logistics topic has received growing attention because of its environmental and economic impact. In Canada, the province of Ontario has enacted regulations regarding the Waste Electrical and Electro...
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Electronic reverse logistics topic has received growing attention because of its environmental and economic impact. In Canada, the province of Ontario has enacted regulations regarding the Waste Electrical and Electronic Equipment (WEEE) Recycling program. The objective of this study is to develop a novel scenario-based robust possibilistic approach to optimize and configure an electronic reverse logistics network by considering the uncertainty associated with fixed and variable costs, the quantity of demand and return, and the quality of returned products. A Monte Carlo simulation is utilized to analyze the performance of our proposed model. Then, ANOVA test is conducted to statistically verify our model using the simulation results. The mathematical model is extended to the multi-objective optimization by maximising the environmental compliance of the third parties. The efficient solutions of the multi-objective model are computed using the two-phase fuzzy compromise approach. To provide a comprehensive assessment of the problem under investigation, we provide sensitivity analyses on the impact of different factors (e.g., recovery rates, capacity of facilities) on the total expected profit. Several interesting results were obtained, including the fact that increasing the capacity of facilities does not automatically translate into higher profits. Furthermore, by comparing the efficient solutions of deterministic and robust modes, we illustrate the impact of robustness price on the multi-objective model. The application of the proposed model is illustrated using a network in the Greater Toronto Area (GTA) in Canada.
scenario-based programming is a methodology for modeling and constructing complex reactive systems from simple, stand-alone building blocks, called scenarios. These scenarios are designed to model different traits of ...
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ISBN:
(纸本)9789897583582
scenario-based programming is a methodology for modeling and constructing complex reactive systems from simple, stand-alone building blocks, called scenarios. These scenarios are designed to model different traits of the system, and can be interwoven together and executed to produce cohesive system behavior. Existing execution frameworks for scenario-based programs allow scenarios to specify their view of what the system must, may, or must not do only through very strict interfaces. This limits the methodology's expressive power and often prevents users from modeling certain complex requirements. Here, we propose to extend scenario-based programming's execution mechanism to allow scenarios to specify how the system should behave using rich logical constraints. We then leverage modern constraint solvers (such as SAT or SMT solvers) to resolve these constraints at every step of running the system, towards yielding the desired overall system behavior. We provide an implementation of our approach and demonstrate its applicability to various systems that could not be easily modeled in an executable manner by existing scenario-based approaches.
scenario-based specification approaches offer system engineering advantages with their intuitiveness, executability, and amenability to formal verification and synthesis. However, many engineering tasks such as debugg...
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ISBN:
(纸本)9789897582837
scenario-based specification approaches offer system engineering advantages with their intuitiveness, executability, and amenability to formal verification and synthesis. However, many engineering tasks such as debugging or maintenance are still far from trivial even when using such specifications. Specifically, it is hard to find out why a complex system behaves as it does, or how it would behave under certain conditions. Here, we present work in progress towards the (semi-)automatic analysis of event traces emanating from simulation runs and actual executions. These traces may be large, yet developers are often interested only in specific properties thereof, like is any specification property violated? are particular properties demonstrated? is there a smaller sub-sequence of events that violates or demonstrates the same properties? which trace properties are common to multiple traces and which are unique? etc. Our approach includes automatic techniques for discovering and distilling relevant properties of traces, analyzing properties of sets of traces, using (sets of) execution traces for understanding specified and actual system behavior and problems therein, planning system enhancement and repair, and more. Our work leverages and extends existing work on trace summarization, formal methods for model analysis, specification mining from execution traces, and others, in the context of scenario-based specifications. A key guiding perspective for this research is that interesting properties of a trace often can be associated with one or very few concise scenarios, depicting desired or forbidden behavior, which are already in the specification, or should be added to it.
The need for the development of clean but still profitable processes and the study of low environmental impact and economically convenient management policies for them are two challenges for the years to come. This pa...
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The need for the development of clean but still profitable processes and the study of low environmental impact and economically convenient management policies for them are two challenges for the years to come. This paper tries to give a first answer to the second of these needs, limited to the area of discontinuous productions. It deals with the development of a robust methodology for the profitable and clean management of (fed-)batch units under uncertainty, which can be referred to as a robust sustainability-oriented model-based optimization & control strategy. This procedure is specifically designed to ensure elevated process performances along with low-cost utilities usage reduction in real-time, simultaneously allowing for the effect of any external perturbation. In this way, conventional offline methods for process sustainable optimization can be easily overcome since the most suitable management policy, aimed at process sustainability, can be dynamically determined and applied in any operating condition. This leads to a significant step forward with respect to the nowadays options in terms of sustainable process management, that drives towards a cleaner and more energy-efficient future. The proposed theoretical framework is validated and tested on a case study based on the well-known fed-batch version of the Williams-Otto process to demonstrate its tangible benefits. The results achieved in this case study are promising and show that the framework is very effective in case of typical process operation while it is partially effective in case of unusual/unlikely critical process disturbances. Future works will go towards the removal of this weakness and further improvement in the algorithm robustness. (C) 2015 Elsevier Ltd. All rights reserved.
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