A framework for systems analysis for decision support systems

Comprehensive and elaborate systems analysis techniques have been developed in the past of routine and operational information systems. Developing support systems for organizational decision-making requires new tools and methodologies. We present a new framework for data collection and decision analysis which is useful for developing decision support systems. This task analysis methodology encompasses (1) event analysis, (2) participant analysis, and (3) decision content analysis. With a proper coding manual, it provides a framework for collecting relevant and detailed information required for decision support design and implementation. Further research is suggested for application and evaluation of the methodology in real-life DSS environments.     

Knowledge management systems and organizational knowledge processing challenges: A field experiment

This paper investigates the appropriateness of knowledge management system (KMS) designs for different organizational knowledge processing challenges. Building on the theory of task-technology fit (TTF), we argue that different KMS designs are more effective for different knowledge tasks. An exploratory field experiment was conducted in the context of Internet-based knowledge sharing services to provide empirical support for our hypotheses. The results of our experiment show that a KMS designed to support the goal GENERATE is more appropriate for divergent type knowledge problems because of its affordances for iterative brainstorming processes. Conversely, for convergent type knowledge processing challenges, a KMS with the goal CHOOSE that supports the ability to clarify and to analyze is more effective.     

A web-based screening model for climate risk to water supply systems in the northeastern United States

The aim of this study is to describe the development and application of a web-based decision support tool (ViRTUE) for performing climate risk evaluations of water supply systems. The tool is designed for small-scale water utilities in the northeastern United States that may lack the resources for detailed climate change risk investigations. Development of this tool demonstrates a relatively new approach to web application development using the Shiny framework for the R programming language to create an interactive environment for stakeholders and water managers to explore climate vulnerabilities. Using a decision-scaling framework, the tool allows the user to perform a climate stress test to evaluate the performance and vulnerability to water supply shortfalls of local reservoir systems over a wide range of potential climate change scenarios using a generic systems model. Probabilities of future climate conditions derived from climate projections then help inform utility operators of impending risk.     

A review of essential standards and patent landscapes for the Internet of Things: A key enabler for Industry 4.0

This paper is a formal overview of standards and patents for Internet of Things (IoT) as a key enabler for the next generation advanced manufacturing, referred as Industry 4.0 (I 4.0). IoT at the fundamental level is a means of connecting physical objects to the Internet as a ubiquitous network that enables objects to collect and exchange information. The manufacturing industry is seeking versatile manufacturing service provisions to overcome shortened product life cycles, increased labor costs, and fluctuating customer needs for competitive marketplaces. This paper depicts a systematic approach to review IoT technology standards and patents. The thorough analysis and overview include the essential standard landscape and the patent landscape based on the governing standards organizations for America, Europe and China where most global manufacturing bases are located. The literature of emerging IoT standards from the International Organization for Standardization (ISO), the International Electrotechnical Commission (IEC) and the Guobiao standards (GB), and global patents issued in US, Europe, China and World Intellectual Property Organization (WIPO) are systematically presented in this study.     

OpenClinical.net: A platform for creating and sharing knowledge and promoting best practice in healthcare

It is well known that medical knowledge is growing so rapidly that it is difficult or impossible for healthcare professionals to keep up. More and more techniques for diagnosing and treating diseases are becoming available, yet new research findings and clinical practices are slow to spread. Information technology and the internet are providing important new ways of disseminating knowledge in healthcare as in many other domains. Knowledge engineering techniques for supporting decision-making and process management are also becoming available, and can be used to support busy clinicians, helping to ensure that their decisions are consistent with current knowledge and clinical procedures are carried out in a timely, efficient and safe way. The OpenClinical.net project is building on these techniques to demonstrate a new paradigm for disseminating knowledge and promoting best practice. The key idea is that much professional expertise can be modelled as computer-interpretable knowledge and used to assist decision-making, workflow management, communication and coordination of care and many other professional tasks. The central goal of OpenClinical.net is to demonstrate how this might be done at scale, through a form of “crowd sourcing”, in order to create and maintain a sharable knowledge base that is available in an open access and open source repository. This paper provides an overview of the project and a summary of progress to date.     

Software maintenance: An approach to impact analysis of objects change

The maintenance of a software system requires a tool for impact analysis and the propagation of change. This paper presents a knowledge-based model for both. This model is generic because it is not based on any language or design method. Therefore, it can be applied on the basis of ‘problem’ to be solved. It also captures four life-cycle phases: requirement, specification, design and programming. We also provide a domain-specific view that allows the dependency analysis of fine-grain objects. Two kinds of dependencies are identified: inter-phase dependencies, these are dependency relations between the objects of the one phase and another; and intra-phase dependencies, these are dependency relations between the objects of the same phase. In order to validate this model, we also present a prototype based on two life-cycle phases: design and programming.     

A survey of tools for the validation and verification of knowledge-based systems: 1985-1995

This paper presents the findings of a survey of software tools built to assist in the verification and validation of knowledge-based systems. The tools were identified from literature sources from the period 1985-1995. The tool builders were contacted and asked to complete and return a survey that identified which testing and analysis techniques were utilised and covered by their tool. From these survey results it is possible to identify trends in tool development, technique coverage and areas for future research.     

Development of a Composite Knowledge Manipulation Tool: K-Expert

A goal of this study is to develop a Composite Knowledge Manipulation Tool (CKMT). Some of traditional medical activities are rely heavily on the oral transfer of knowledge, with the risk of losing important knowledge. Moreover, the activities differ according to the regions, traditions, experts’ experiences, etc. Therefore, it is necessary to develop an integrated and consistent knowledge manipulation tool. By using the tool, it will be possible to extract the tacit knowledge consistently, transform different types of knowledge into a composite knowledge base (KB), integrate disseminated and complex knowledge, and complement the lack of knowledge. For the reason above, I have developed the CKMT called as K-Expert and it has four advanced functionalities as follows. Firstly, it can extract/import logical rules from data mining (DM) with the minimum of effort. I expect that the function can complement the oral transfer of traditional knowledge. Secondly, it transforms the various types of logical rules into database (DB) tables after the syntax checking and/or transformation. In this situation, knowledge managers can refine, evaluate, and manage the huge-sized composite KB consistently with the support of the DB management systems (DBMS). Thirdly, it visualizes the transformed knowledge in the shape of decision tree (DT). With the function, the knowledge workers can evaluate the completeness of the KB and complement the lack of knowledge. Finally, it gives SQL-based backward chaining function to the knowledge users. It could reduce the inference time effectively since it is based on SQL query and searching not the sentence-by-sentence translation used in the traditional inference systems. The function will give the young researchers and their fellows in the field of knowledge management (KM) and expert systems (ES) more opportunities to follow up and validate their knowledge. Finally, I expect that the approach can present the advantages of mitigating knowledge loss and the burdens of knowledge transformation and complementation.     

A general methodology for data-based rule building and its application to natural disaster management

Risks derived from natural disasters have a deeper impact than the sole damage suffered by the affected zone and its population. Because disasters can affect geostrategic stability and international safety, developed countries invest a huge amount of funds to manage these risks. A large portion of these funds are channeled through United Nations agencies and international non-governmental organizations (NGOs), which at the same time are carrying out more and more complex operations. For these reasons, technological support for these actors is required, all the more so because the global economic crisis is placing emphasis on the need for efficiency and transparency in the management of (relatively limited) funds. Nevertheless, currently available sophisticated tools for disaster management do not fit well into these contexts because their infrastructure requirements usually exceed the capabilities of such organizations. In this paper, a general methodology for inductive rule building is described and applied to natural-disaster management. The application is a data-based, two-level knowledge decision support system (DSS) prototype which provides damage assessment for multiple disaster scenarios to support humanitarian NGOs involved in response to natural disasters. A validation process is carried out to measure the accuracy of both the methodology and the DSS.     

A multi-stakeholder portfolio optimization framework applied to stormwater best management practice (BMP) selection

In this paper, an optimization framework for complex environmental management problems involving multiple stakeholders is developed and illustrated. In the framework, problems are represented as a series of smaller, interconnected optimization problems, reflecting individual stakeholders’ interests. The framework uses interactive visual analytics to explore and analyse optimization results, and the concept of Best Alternatives to a Negotiated Agreement (BATNAs) and an approach to reframe visualizations to encourage stakeholder negotiation. To demonstrate the utility of the framework, it is applied to a realistic case study involving multiple stakeholder groups funding different stormwater best management practices (BMPs) for a catchment management plan for a region of a large city in Australia. The problem features a total of sixteen objectives for four stakeholders. The results indicate that the proposed framework enables the identification of solutions that provide optimal trade-offs between many objectives and provides an effective and efficient means of assisting stakeholders with identifying acceptable solutions.     

Integrating scientific modeling and supporting dynamic hazard management with a GeoAgent-based representation of human–environment interactions: A drought example in Central Pennsylvania, USA

Recent natural disasters indicate that modern technologies for environmental monitoring, modeling, and forecasting are not well integrated with cross-level social responses in many hazard-management systems. This research addresses this problem through a Java-based multi-agent prototype system, GeoAgent-based Knowledge System (GeoAgentKS). This system allows: (1) computer representation of institutional regulations and behavioral rules used by multiple social institutions and individuals in cross-level human–environment interactions, (2) integration of this representation with scientific modeling of dynamic hazard development, and (3) application of automated reasoning that suggests to users the appropriate actions for supporting cooperative social responses. This paper demonstrates the software architecture of GeoAgentKS and presents such an integrated approach by modeling the drought management processes in Central Pennsylvania, USA. The results show that it is possible to use GeoAgentKS to represent multilevel human–environment interactions and to use those interactions as input to decision making in hazard management.     

Workflow Systems: Occasions for Success and Failure

Workflow technologies have created considerable discussion within the computer supported cooperative work community. Although a number of theoretical and empirical warnings about the difficulties of workflow systems have appeared, the technologies continue to be built and sold. This paper examines the use of one workflow-like system and outlines three cases when the technology supported the work of its users. Comparing these successful occasions with some reports of difficulties, this paper draws conclusions about the circumstances that led to tool usage.     

A Comprehensive Overview of Cyber-Physical Systems: From Perspective of Feedback System

Cyber-physical systems (CPS) are characterized by integrating cybernetic and physical processes. The theories and applications of CPS face the enormous challenges. The aim of this paper is to provide a latest understanding of this emerging multi-disciplinary methodology. First, the features of CPS are described, and the research progresses are summarized from different components in CPS, such as system modeling, information acquisition, communication, control and security. Each part is also followed by the future directions. Then some typical applications are given to show the prospects of CPS.      

Towards best practice implementation and application of models for analysis of water resources management scenarios

Water resources management models are widely used to evaluate planning or operational scenarios to support water resource management decision-making. However, the approaches to modelling used in the past have led to problems, such as modellers having difficulty establishing the credibility of their model with stakeholders, and stakeholders having difficulty understanding and trusting model results. A best practice approach to the implementation and application of water resources management models based on a quality assurance procedure is an appropriate means of overcoming these difficulties, and there are a number of guidelines and papers available promoting this approach. However, guidance in these on the use of models to analyse water resource planning scenarios is limited or not provided. This paper therefore provides guidance on the implementation and application of water resources management models with an emphasis on scenario analysis. This guidance is principally intended for practising modellers, and also for peer reviewers and stakeholders such as managers, decision makers, and community-based groups. Adoption strategies and recommendations for future directions are also discussed.     

Aeroelastic modeling and stability analysis: A robust approach to the flutter problem

In this paper, a general approach to address modeling of aeroelastic systems, with the final goal to apply μ analysis, is discussed. The chosen test bed is the typical section with unsteady aerodynamic loads, which enables basic modeling features to be captured and so extend the gained knowledge to practical problems treated with modern techniques. The aerodynamic operator has a nonrational dependence on the Laplace variable s, and hence, 2 formulations for the problem are available: frequency domain or state‐space (adopting rational approximations). The study attempts to draw a parallel between the 2 consequent linear fractional transformation modeling processes, emphasizing critical differences and their effect on the predictions obtained with μ analysis. A peculiarity of this twofold formulation is that aerodynamic uncertainties are inherently treated differently and therefore the families of plants originated by the possible linear fractional transformation definitions are investigated. One of the main results of the paper is to propose a unified framework to address the robust modeling task, which enables the advantages of both the approaches to be retained. On the analysis side, the application of μ analysis to the different models is shown, emphasizing its capability to gain insight into the problem.     

Participatory Framework for Assessment and Improvement of Tools (ParFAIT): Increasing the impact and relevance of water management decision support research

This paper proposes the Participatory Framework for Assessment and Improvement of Tools (ParFAIT) as a way to address low uptake of Water Resources Systems Optimization (WRSO) tools. ParFAIT is a transdisciplinary process conducted in five stages, two of which are participatory modeling (PM) exercises. Herein we describe the framework, introduce our candidate tool- Multiobjective Evolutionary Algorithm (MOEA)-assisted optimization, and present the results of our first PM workshop. MOEA-assisted optimization has been put forth as a planning and decision making aid for utilities facing a large number of decisions and highly uncertain futures. The PM workshop, designed to solicit input on a tool testbed, was held in February 2015 with representatives from six Front Range, Colorado, water utilities. Our results include an expanded characterization of the decision making landscape, feedback on water utility decisions and performance goals commonly employed in WRSO studies, and new questions that warrant future investigation by researchers.     

Decision support in pre-hospital stroke care operations: A case of using simulation to improve eligibility of acute stroke patients for thrombolysis treatment

Stroke is the third most common cause of death and the sixth most common cause of disability worldwide. Treating acute ischemic stroke with thrombolytic therapy within 4.5 hours from symptom onset is effective in improving patient outcomes. The time from stroke onset to arrival to hospital has been identified as the single most important issue in determining patients' eligibility for stroke thrombolysis. There is a need for simultaneous systemic evaluation of multi-factorial interventions in pre-hospital acute care systems, aimed at increasing patients' eligibility for stroke thrombolysis. In this paper an OR solution is proposed in the form of a simulation model that provides clear measure of the relative benefit of alternative potential interventions, demonstrating how OR modeling can be used for providing decision support in pre-hospital stroke care operations and contributing to health OR literature.     

A decision support system for updating and incorporating climate change impacts into rainfall intensity-duration-frequency curves: Review of the stakeholder involvement process

Stakeholder involvement can serve to increase the quality of decision support systems (DSSs) and increase the perceived legitimacy of DSS outputs. Involving those who are ultimately affected by the outputs of DSSs in system design and development also reflects democratic principles. Importantly, stakeholder involvement can help ensure that the outputs of DSSs are used in decision-making processes. However, DSSs often fail due to poor engagement of stakeholder and end-user communities in the development and design of systems. The stakeholder engagement process applied in the development of the Computerized Tool for the Development of Intensity Duration Frequency Curves under Climate Change described here followed many of the tenants of best practices identified in the literature. While the engagement strategy was generally considered successful, over- and under-representation of some stakeholder groups and long term funding issues were weaknesses in the engagement process.     

Movie forecast Guru: A Web-based DSS for Hollywood managers

Herein we describe a Web-based DSS to help Hollywood managers make better decisions on important movie characteristics, such as, genre, super stars, technical effects, release time, etc. These parameters are used to build prediction models to classify a movie in one of nine success categories, from a “flop” to a “blockbuster”. The system employs a number of traditional and non-traditional prediction models as distributed independent experts, implemented as Web services. The paper describes the purpose and the architecture of the system, the development environment, the user assessment results, and the lessons learned as they relate to Web-based DSS development.     

Decision support for moving from a single product to a product portfolio in evolving software systems

Successful software systems continuously evolve to accommodate ever-changing needs of customers. Accommodating the feature requests of all the customers in a single product increases the risks and costs of software maintenance. A possible approach to mitigate these risks is to transition the evolving software system (ESS) from a single system to a portfolio of related product variants, each addressing a specific customers’ segment. This evolution should be conducted such that the extent of modifications required in ESS's structure is reduced. The proposed method COPE+ uses preferences of customers on product features to generate multiple product portfolios each containing one product variant per segment of customers. Recommendations are given to the decision maker to update the product portfolios based on structural analysis of ESS. Product portfolios are compared with the ESS using statechart representations to identify the level of similarity in their behaviors. A proof of concept is presented by application to an open-source text editing system. Structural and behavioral analysis of candidate portfolios helped the decision maker to select one portfolio out of three candidates.