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IEEE 5th Annual World AI IoT Congress (AIIoT)

作者： Lin, Tian-Xiao Chen, Zhen Guo, Min Lin, Yu-Xiang Zhang, Yi-Song Gao, Ying Ma, Xiao-Dong Men, Kaiwen Guanglun Elect Technol Beijing Peoples R China Tsinghua Univ Beijing Peoples R China Univ Washington Seattle WA USA

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.

关键词： Internet of Things embedded programming scenario-based programming component-based programming Artificial Intelligence

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scenario-based programming: Reducing the Cognitive Load, Fostering Abstract Thinking 2014

Scenario-Based Programming: Reducing the Cognitive Load, Fos...

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36th International Conference on Software Engineering (ICSE)

作者： Alexandron, Giora Armoni, Michal Gordon, Michal Harel, David Weizmann Inst Sci IL-76100 Rehovot Israel

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.

关键词： Abstraction scenario-based programming

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InterPlay: Horizontal scale-up and transition to design in scenario-based programming

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2006年第7期32卷 467-485页

作者： Barak, Dan Harel, David Marelly, Rami Weizmann Inst Sci IL-76100 Rehovot Israel

We describe InterPlay, a simulation engine coordinator that supports cooperation and interaction of multiple simulation and execution tools, thus helping to scale up the design and development cycle of reactive systems. InterPlay involves a number of related ideas. In the first, we concentrate on the interobject design approach involving live sequence charts (LSCs) and its support tool, the Play-Engine, enabling multiple Play-Engines to run in cooperation. This makes possible the distributed design of large-scale systems by different teams, as well as the refinement of parts of a system using different Play-Engines. The second idea concerns combining the interobject approach with the more conventional intraobject approach, involving, for example, statecharts and Rhapsody. InterPlay makes it possible to run the Play-Engine in cooperation with Rhapsody, and is very useful when some system objects have clear and distinct internal behavior, or in an iterative development process where the design is implementation- oriented and the ultimate goal is to end up with an intraobject implementation. Finally, we have expanded the Play-Engine's ability to delegate some of the system's functionality to complex GUIs. This enables beneficial interaction with "smart" GUIs that have built-in behavior of their own, and which are more naturally implemented in code.

关键词： modeling methodologies scenario-based programming InterPlay play-engine LSCs intraobject interobject transition to design

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A scenario-based mixed integer linear programming model for composite power system expansion planning with greenhouse gas emission controls

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CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY 2014年第6期16卷 1001-1014页

作者： Chang, Mei-Shiang Chung Yuan Christian Univ Dept Civil Engn Taoyuan 32023 Taiwan

In this paper, the influence of uncertain factors in the power supply system is considered by applying scenario-based programming techniques. A multi-period network design model for composite power system expansion planning is formulated as a mixed integer programming model. This model aims to identity the allocations of fossil fuel, cleaner energy sources, and nuclear power as well as the corresponding to construct transmission network to account for all scenarios of the uncertain factors of the power system. Electricity demands, a limitation of greenhouse gas emissions, and other operational constraints are deliberated in this model. This model is solved using CPLEX, and the Taiwan electric power system is used to illustrate the proposed model. Feasibility analysis of nuclear power energy policies and a low carbon power policy is also been conducted. Corporately implementing the low carbon energy policy increases the feasibility that Taiwan will gradually become nuclear free and more environmentally friendly. The cost per ton of carbon dioxide is estimated to be about NT$ 470.

关键词： Composite power system expansion planning Multi-period network design Greenhouse gas emissions control scenario-based programming

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Adaptive Behavioral programming

Adaptive Behavioral Programming

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23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Eitan, Nir Harel, David Weizmann Inst Sci Dept Comp Sci & Appl Math IL-76100 Rehovot Israel

ISBN: (纸本)9780769545967

We introduce a way to program adaptive reactive systems, using behavioral, scenario-based programming. Extending the semantics of live sequence charts with reinforcements allows the programmer not only to specify what the system should do or must not do, but also what it should try to do, in an intuitive and incremental way. By integrating scenario-based programs with reinforcement learning methods, the program can adapt to the environment, and try to achieve the desired goals. Visualization methods and modular learning decompositions, based on the unique structure of the program, are suggested, and result in an efficient development process and a fast learning rate.

关键词： scenario-based programming adaptive systems reinforcement learning behavior-based LSC BPJ

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Global supply chain network design for shelf-life products under uncertainty: a case study of pistachios

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KYBERNETES 2024年

作者： Mostaghimi, Fatemeh Jabalameli, Mohammad Saeed Bozorgi-Amiri, Ali Iran Univ Sci & Technol Dept Ind Engn Tehran Iran Univ Tehran Coll Engn Sch Ind Engn Tehran Iran

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

关键词： Global supply chain network design Shelf-life products scenario-based programming Pistachio supply chain

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Synthesis from scenario-based specifications

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JOURNAL OF COMPUTER AND SYSTEM SCIENCES 2012年第3期78卷 970-980页

作者： Harel, David Segall, Itai Weizmann Inst Sci Dept Comp Sci & Appl Math IL-76100 Rehovot Israel

We consider the problem of the automatic generation of reactive systems from specifications given in the scenario-based language of live sequence charts (LSCs). We start by extending the language so that it becomes more suitable for synthesis. We then translate a system specification given in the language into a two-player game between the system and the environment. By solving the game, we generate a winning strategy for the system, which corresponds to a correct implementation of the specification. We also define two notions of system correctness, and show how each can be synthesized. (C) 2011 Elsevier Inc. All rights reserved.

关键词： Synthesis Live sequence charts LSC Specification scenario-based programming

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A robust sustainable optimization & control strategy (RSOCS) for (fed-)batch processes towards the low-cost reduction of utilities consumption

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JOURNAL OF CLEANER PRODUCTION 2016年第PartA期111卷 181-192页

作者： Rossi, Francesco Manenti, Flavio Pirola, Carlo Mujtaba, Iqbal Politecn Milan Dipartimento Chim Mat & Ingn Chim Giulio Natta I-20133 Milan Italy Purdue Univ Sch Chem Engn W Lafayette IN 47907 USA Univ Milan Dipartimento Chim I-20133 Milan Italy Univ Bradford Sch Engn & Informat Bradford BD7 1DP W Yorkshire England

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.

关键词： Dynamic optimization Non-linear model-predictive control scenario-based programming (Fed-)batch processes sustainable management Low-cost utilities usage reduction

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scenario-based Optimal Bidding Strategies of GENCOs in the Incomplete Information Electricity Market Using a New Improved Prey-Predator Optimization Algorithm

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IEEE SYSTEMS JOURNAL 2015年第4期9卷 1485-1495页

作者： Bahmani-Firouzi, Bahman Sharifinia, Sajjad Azizipanah-Abarghooee, Rasoul Niknam, Taher Islamic Azad Univ Coll Engn Dept Elect Engn Marvdasht Branch Marvdasht *** Iran Shiraz Univ Technol Dept Elect & Elect Engn Shiraz *** Iran

In order to find out the optimal bidding strategies (BSs) of generating companies (GENCOs) in a competitive electricity market, it is necessary to solve a bilevel optimization problem. The first level of the problem relates to the GENCOs to strategically bid, and the second level solves the independent system operator's market clearing problem based on the maximization of social welfare. In order to model the incomplete information of participants in the market about cost coefficients of opponents and their forecast errors, a scenario-based programming framework is presented. In addition, a roulette wheel mechanism is used for scenario-generation process so that the forecast errors of coefficients are considered as random variables with known probability distribution functions. Then, each GENCO solves the bilevel optimization problem and maximizes its expected profit function. These bilevel problems are nonconvex, and the mathematical-based optimization technique is unable to handle the problem and obtain the nearly global optima. In order to resolve this issue, a novel prey-predator optimization algorithm is suggested to solve the first level of the bilevel problem and using the iterative method to find out the supply function equilibrium that is the optimal BSs of GENCOs. Applying to the IEEE 57- and 118-bus test systems with incomplete information studies, the performance of the proposed approach is successfully approved.

关键词： Bilevel optimization problem generating company (GENCO) Nash equilibrium (NE) optimal bidding strategies (BSs) prey-predator algorithm scenario-based programming

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A multi-objective robust optimization model to design sustainable sugarcane-to-biofuel supply network: the case of study

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BIOMASS CONVERSION AND BIOREFINERY 2021年第6期11卷 2521-2542页

作者： Gilani, H. Sahebi, H. Iran Univ Sci & Technol Sch Ind Engn Tehran Iran

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.

关键词： International supply chain Sustainable supply chain Robust optimization Sugarcane-to-biofuel scenario-based programming Disruptions

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