Development of method of matched morphological filtering of biomedical signals and images

Formalized approach to the analysis of biomedical signals and images with locally concentrated features is developed on the basis of matched morphological filtering taking into account the useful signal models that allowed generalizing the existing methods of digital processing and analysis of biomedical signals and images with locally concentrated features. The proposed matched morphological filter has been adapted to solve such problems as localization of the searched structural elements on biomedical signals with locally concentrated features, estimation of the irregular background aimed at the visualization quality improving of biological objects on X-ray biomedical images, pathologic structures selection on mammogram. The efficiency of the proposed methods of matched morphological filtration of biomedical signals and images with locally concentrated features is proved by experiments

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Visual analytics for supply network management: system design and evaluation

We propose a visual analytic system to augment and enhance decision-making processes of supply chain managers. Several design requirements drive the development of our integrated architecture and lead to three primary capabilities of our system prototype. First, a visual analytic system must integrate various relevant views and perspectives that highlight different structural aspects of a supply network. Second, the system must deliver required information on-demand and update the visual representation via user-initiated interactions. Third, the system must provide both descriptive and predictive analytic functions for managers to gain contingency intelligence. Based on these capabilities we implement an interactive web-based visual analytic system. Our system enables managers to interactively apply visual encodings based on different node and edge attributes to facilitate mental map matching between abstract attributes and visual elements. Grounded in cognitive fit theory, we demonstrate that an interactive visual system that dynamically adjusts visual representations to the decision environment can significantly enhance decision-making processes in a supply network setting. We conduct multi-stage evaluation sessions with prototypical users that collectively confirm the value of our system. Our results indicate a positive reaction to our system. We conclude with implications and future research opportunities.The authors would like to thank the participants of the 2015 Businessvis Workshop at IEEE VIS, Prof. Benoit Montreuil, and Dr. Driss Hakimi for their valuable feedback on an earlier version of the software; Prof. Manpreet Hora for assisting with and Georgia Tech graduate students for participating in the evaluation sessions; and the two anonymous reviewers for their detailed comments and suggestions. The study was in part supported by the Tennenbaum Institute at Georgia Tech Award # K9305. (K9305 - Tennenbaum Institute at Georgia Tech Award)Accepted manuscrip

PROPOSED OF DECISION POLICY MODEL DEVELOPMENT FOR CITY LOGISTICS STAKEHOLDERS

City Logistics and urban freight transport has become an important issue in urban planning. Challenges City Logistics is a matter of planning, scheduling, integrated short-term operation and resoureces management, for the general case involving two level distribution structure. The complexity of the matter distribution arrangements and conflicts between key stakeholder groups (government, corporate transport or logistics service providers, customers, the environment, and business) requires the solution of various approaches (Thompson and Taniguchi, 2001). There are four key stakeholders City Logistics system which has a complexity of issues and conflicts distribution arrangements between key stakeholder groups (Thompson, 2001), are : (1) shippers, (2) freight carriers, (3) residents, (4) administrators / Governments. Each group has its own specific purpose and has different habits and behaviors and needs that must be considered. Consolidation and coordination is a fundamental concept of City Logistics (Taniguchi, 2000). Complexity in the logistical demands of integrated decision-making authority between actors are autonomous and decentralized without disturbing the overall total activity. Key words: City Logistics, Stakeholders, Policy Model, integrated decision makin

Model predictive control of dynamically substructured systems with application to a servohydraulically-actuated mechanical plant

Copyright ©2010 Institution of Engineering and Technology (IET). This paper is a postprint of a paper submitted to and accepted for publication in IET Control Theory and Applications and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library.Dynamically substructured systems (DSS) are increasingly used by the dynamics testing community. DSS involves the physical testing of full-size critical components in parallel with numerical testing of the remaining components. This has certain advantages over other testing methods. However, the synchronisation of the signals at the interface between the physical and numerical substructures of DSS requires a high fidelity controller. In practice, the performance of the DSS testing can be degraded by input saturation of the actuators. In this study, the authors use model predictive control (MPC) to cope with the saturation problem in DSS. To facilitate the MPC and observer design for DSS, a modified DSS framework based on an existing one is proposed. As a case study, a quasi-motorcycle (QM) system is converted into the modified DSS framework and a traditional on-line MPC control strategy is implemented in real time