Scenario-based approach for project portfolio selection in army engineering and manufacturing development

The decisions concerning portfolio selection for army engineering and manufacturing development projects determine the benefit of those projects to the country concerned.Projects are typically selected based on ex ante estimates of future return values,which are usually difficult to specify or only generated after project launch.A scenario-based approach is presented here to address the problem of selecting a project portfolio under incomplete scenario information and interdependency constraints.In the first stage,the relevant dominance concepts of scenario analysis are studied to handle the incomplete information.Then,a scenario-based programming approach is proposed to handle the interdependencies to obtain the projects,whose return values are multi-criteria with interval data.Finally,an illustrative example of army engineering and manufacturing development shows the feasibility and advantages of the scenario-based multi-objective programming approach.

Scenario-based Participatory Design for Pervasive Computing

Lots of pervasive computing researchers are working on how to realize the user-centered intelligent pervasive computing environment as Mark Weiser figured out.Task abstraction is the fundamentation of configuration for pervasive application.Based on task-oriented and descriptive properties of scenario,a scenario-based participatory design model was proposed to realize the task abstraction.The design model provided users and domain experts a useful mechanism to build the customized applications by separating system model into domain model and design model.In this design model,domain experts,together with users,stakeholders focus on the logic rules(domain model)and programmers work on the implementation(design model).In order to formalize the model description,a human-agent interaction language to transform users' goals and domain rules into executable scenarios was also discussed.An agent platform-describer used to link design and implementation of scenarios was developed to realize the configuration of applications according to different requirements.The demand bus application showed the design process and the usability of this model.

SCENARIO-BASED URBAN FLOOD FORECAST WITH FLOOD INUNDATION MAP

The objective of this study is to introduce how to apply the urban flood forecast with numerous flood inundation map scenario in Korea. In modeling of urban flood, drainage networks 1D model like SWMM(Storm Water Management Model) used to analysis stormwater runoff within drainage pipe system and 2D surface model used to simulate inundation area and depth. This 1D-2D model(drainage network 1D coupled to 2D surface model) is used to make the inundation map of urban flood. The accuracy of the 2D model is highly dependent of the input data resolution. The cell by cell running on these high surface resolution need to be required more computation time. Thus, the 1D-2D models have some limitations in using operational real-time forecast. In this sense, the scenario-based approach can be a good alternative method to forecast urban flood. The flood inundation maps would be completed with 320 rainfall scenarios which are finely divided according to rainfall intensity and duration on the basis of design rainfall. The forecast process is very simple if we use pre-existing scenarios. We use a predicted radar rainfall as input for simulated scenario selection, and then selected inundation map would be serviced to people. In this study, the current results for the scenario-based urban flood forecast with flood inundation map are demonstrated.

Robust energy-efficient train speed profile optimization in a scenario-based position-time-speed network

Train speed profile optimization is an efficient approach to reducing energy consumption in urban rail transit systems.Different from most existing studies that assume deterministic parameters as model inputs,this paper proposes a robust energy-efficient train speed profile optimization approach by considering the uncertainty of train modeling parameters.Specifically,we first construct a scenario-based position-time-speed(PTS)network by considering resistance parameters as discrete scenariobased random variables.Then,a percentile reliability model is proposed to generate a robust train speed profile,by which the scenario-based energy consumption is less than the model objective value at a confidence level.To solve the model efficiently,we present several algorithms to eliminate the infeasible nodes and arcs in the PTS network and propose a model reformulation strategy to transform the original model into an equivalent linear programming model.Lastly,on the basis of our field test data collected in Beijing metro Yizhuang line,a series of experiments are conducted to verify the effectiveness of the model and analyze the influences of parameter uncertainties on the generated train speed profile.

A Creative Approach to Reducing Ambiguity in Scenario-based Software Architecture Analysis

In software engineering, a scenario describes an anticipated usage of a software system. As scenarios are useful to understand the requirements and functionalities of a software system, the scenario-based analysis is widely used in various tasks, especially in the design stage of software architectures. Although researchers have proposed various scenario-based approaches to analyse software architecture, there are still limitations in this research field, and a key limitation is that scenarios are typically not formally defined and thus may contain ambiguities. As these ambiguities may lead to defects, it is desirable to reduce them as many as possible. In order to reduce ambiguity in scenario-based software architecture analysis, this paper introduces a creative computing approach to scenario-based software requirements analysis. Our work expands this idea in three directions. Firstly, we extend an architecture description language(ADL)-based language – Breeze/ADL to model the software architecture. Secondly, we use a creative rule – combinational rule(CR) to combine the vector clock algorithm for reducing the ambiguities in modelling scenarios. Then, another creative rule – transformational rule(TR) is employed to help to transform our Breeze/ADL model to a popular model – unified modelling language(UML) model. We implement our approach as a plugin of Breeze, and illustrate a running example of modelling a poetry to music system in our case study.Our results show the proposed creative approach is able to reduce ambiguities of the software architecture in practice.

Scenario-Based Stochastic Resource Allocation with Uncertain Probability Parameters

The stochastic resource allocation(SRA) problem is an extensive class of combinatorial optimization problems widely existing in complex systems such as communication networks and unmanned systems. In SRA, the ability of a resource to complete a task is described by certain probability,and the objective is to maximize the reward by appropriately assigning available resources to different tasks. This paper is aimed at an important branch of SRA, that is, stochastic SRA(SSRA) for which the probability for resources to complete tasks is also uncertain. Firstly, a general SSRA model with multiple independent uncertain parameters(GSSRA-MIUP) is built to formulate the problem. Then,a scenario-based reformulation which can address multi-source uncertainties is proposed to facilitate the problem-solving process. Secondly, in view of the superiority of the differential evolution algorithm in real-valued optimization, a discrete version of this algorithm was originally proposed and further combined with a specialized local search to create an efficient hybrid optimizer. The hybrid algorithm is compared with the discrete differential evolution algorithm, a pure random sampling method, as well as a restart local search method. Experimental results show that the proposed hybrid optimizer has obvious advantages in solving GSSRA-MIUP problems.

Energy Management of Networked Smart Railway Stations Considering Regenerative Braking, Energy Storage System, and Photovoltaic Units

The networking of microgrids has received significant attention in the form of a smart grid.In this paper,a set of smart railway stations,which is assumed as microgrids,is connected together.It has been tried to manage the energy exchanged between the networked microgrids to reduce received energy from the utility grid.Also,the operational costs of stations under various conditions decrease by applying the proposed method.The smart railway stations are studied in the presence of photovoltaic(PV)units,energy storage systems(ESSs),and regenerative braking strategies.Studying regenerative braking is one of the essential contributions.Moreover,the stochastic behaviors of the ESS’s initial state of energy and the uncertainty of PV power generation are taken into account through a scenario-based method.The networked microgrid scheme of railway stations(based on coordinated operation and scheduling)and independent operation of railway stations are studied.The proposed method is applied to realistic case studies,including three stations of Line 3 of Tehran Urban and Suburban Railway Operation Company(TUSROC).The rolling stock is simulated in the MATLAB environment.Thus,the coordinated operation of networked microgrids and independent operation of railway stations are optimized in the GAMS environment utilizing mixed-integer linear programming(MILP).

An Evaluation of Value-Oriented Review for Software Requirements Specification

A software requirements specification(SRS)is a detailed description of a software system to be developed.This paper proposes and evaluates a lightweight review approach called value-oriented review(VOR)to detect defects in SRS.This approach comprises setting core values based on SRS and detecting the defects disturbing the core values.To evaluate the effectiveness of the proposed approach,we conducted a controlled experiment to investigate whether reviewers could identify and record the core values based on SRS and find defects disturbing the core values.Results of the evaluation with 56 software engineers showed that 91%of the reviewers identified appropriate core values and 82%of the reviewers detected defects based on the identified core values.Furthermore,the average number of defects detected using the proposed approach was slightly smaller than that detected using perspective-based reading(PBR);however,PBR requires defining review scenarios before attempting to detect any defects.The results also demonstrated that the proposed approach helped reviewers detect the omission defects,which are more difficult to detect from SRS than defects because of ambiguity or incorrect requirements.

A scenario relaxation algorithm for finite scenario based robust assembly line balancing

A balancing problem for a mixed model assembly line with uncertain task processmg Ume anO daily model mixed changes is considered, and the objective is to minimize the work variances between stations in the line. For the balancing problem for the scenario-based robust assembly line with a finitely large number of potential scenarios, the direct solution methodology considering all potential scenarios is quite time-consuming. A scenario relaxation algorithm that embeds genetic al- gorithm is developed. This new algorithm guarantees termination at an optimal robust solution with relatively short running time, and makes it possible to solve robust problems with large quantities of potential scenarios. Extensive computational results are reported to show the efficiency and effectiveness of the proposed algorithm.

Co-optimization of integrated energy systems in the presence of renewable energy,electric vehicles,power-to-gas systems and energy storage systems with demand-side management

With the widespread penetration of renewable energy sources and energy storage systems,the problem of energy management has received increasing attention.One of the systems that network owners consider today is the power-to-gas(P2G)system.This system causes surplus electricity generated from renewable energy resources or batteries in the network to be converted into gas and sold to the gas network.Two reasons for the existence of gas distributed generation resources and P2G systems cause the two power and gas networks to interact.Energy management and profit making considering these two networks,as a co-optimization of integrated energy systems,is a topic that has been discussed in this study to achieve the best optimal answer.Since the production of renewable energy resources and the purchase price of energy are uncertain,a scenario-based method has been chosen for modelling.Demand-side management is also one of the important problems in optimal operation of the electricity network,which can have a significant impact on reducing peak load and increasing profits.In this paper,a mixed-integer quadratic programming model for co-optimization of electric distribution and gas networks in the presence of distributed generation resources,P2G systems,storage facilities,electric vehicles and demand-side management is presented.The 33-bus distribution network is intended to analyse the proposed model.The results of different scenarios show the efficiency of the proposed model.Several key points are deduced from the obtained results:(i)demand-side management is able to reduce the peak load of the network,(ii)the presence of renewable resources and batteries can cause the network to convert excess electricity into gas and sell it to the gas network in the market and(iii)distributed generation can reduce the purchase of energy from the upstream network and cause a 36% reduction in the cost function.

翻转课堂和情景式教学在免疫学实验课中的设计与应用

目的 探讨翻转课堂（flipped classroom）和情景式教学（scenario-based learning module,SBL）在免疫学实验课中的设计和应用效果.方法 采用情景式教学模式,通过翻转课堂的教学形式,在183名医学本科生中进行了免疫学实验教学探索.发放调查问卷,以了解学生对这种实验课教学模式的态度和收获.同时,比较传统实验教学法和新模式教学法的教学成本.结果 新的教学模式能够充分调动学生学习的积极性,培养学生的科学实验思维,并增强学生的表达能力和团队合作精神.94.4％的学生认为新的教学模式让实验课变得有趣和容易理解;97.2％的学生同意新的教学模式对他们理解实验内容很有帮助;92.7％的学生认为新的教学模式帮助他们认识到应该如何科学地开展医学实验;94.4％的学生认为新的教学模式提高了他们的表达能力;91.6％的学生同意新的教学模式使他们的合作能力得到增强.数据还表明,新的教学模式在很大程度上降低了实验教学费用.结论 翻转课堂和情景式教学模式是适合免疫学实验教学的新型实验教学模式。