Eco-efficient supply chain networks: Development of a design framework and application to a real case study

© 2015 Taylor & Francis. This paper presents a supply chain network design framework that is based on multi-objective mathematical programming and that can identify 'eco-efficient' configuration alternatives that are both efficient and ecologically sound. This work is original in that it encompasses the environmental impact of both transportation and warehousing activities. We apply the proposed framework to a real-life case study (i.e. Lindt & Sprüngli) for the distribution of chocolate products. The results show that cost-driven network optimisation may lead to beneficial effects for the environment and that a minor increase in distribution costs can be offset by a major improvement in environmental performance. This paper contributes to the body of knowledge on eco-efficient supply chain design and closes the missing link between model-based methods and empirical applied research. It also generates insights into the growing debate on the trade-off between the economic and environmental performance of supply chains, supporting organisations in the eco-efficient configuration of their supply chains

Socially communicative characters for interactive applications

Interactive Face Animation - Comprehensive Environment (iFACE) is a general-purpose software framework that encapsulates the functionality of “face multimedia object” for a variety of interactive applications such as games and online services. iFACE exposes programming interfaces and provides authoring and scripting tools to design a face object, define its behaviours, and animate it through static or interactive situations. The framework is based on four parameterized spaces of Geometry, Mood, Personality, and Knowledge that together form the appearance and behaviour of the face object. iFACE can function as a common “face engine” for design and runtime environments to simplify the work of content and software developers

Interpretable task planning and learning for autonomous robotic surgery with logic programming

This thesis addresses the long-term goal of full (supervised) autonomy in surgery, characterized by dynamic environmental (anatomical) conditions, unpredictable workflow of execution and workspace constraints. The scope is to reach autonomy at the level of sub-tasks of a surgical procedure, i.e. repetitive, yet tedious operations (e.g., dexterous manipulation of small objects in a constrained environment, as needle and wire for suturing). This will help reducing time of execution, hospital costs and fatigue of surgeons during the whole procedure, while further improving the recovery time for the patients. A novel framework for autonomous surgical task execution is presented in the first part of this thesis, based on answer set programming (ASP), a logic programming paradigm, for task planning (i.e., coordination of elementary actions and motions). Logic programming allows to directly encode surgical task knowledge, representing emph{plan reasoning methodology} rather than a set of pre-defined plans. This solution introduces several key advantages, as reliable human-like interpretable plan generation, real-time monitoring of the environment and the workflow for ready adaptation and failure recovery. Moreover, an extended review of logic programming for robotics is presented, motivating the choice of ASP for surgery and providing an useful guide for robotic designers. In the second part of the thesis, a novel framework based on inductive logic programming (ILP) is presented for surgical task knowledge learning and refinement. ILP guarantees fast learning from very few examples, a common drawback of surgery. Also, a novel action identification algorithm is proposed based on automatic environmental feature extraction from videos, dealing for the first time with small and noisy datasets collecting different workflows of executions under environmental variations. This allows to define a systematic methodology for unsupervised ILP. All the results in this thesis are validated on a non-standard version of the benchmark training ring transfer task for surgeons, which mimics some of the challenges of real surgery, e.g. constrained bimanual motion in small space

A Management Science Approach to Contingency Models of Organizational Structure

This study demonstrates the applicability of a quantitative modeling approach, specifically goal programming, in operationalizing the relationship between environmental variables and specific organizational structural variables for optimal goal attainment. A goal programming model is developed to analyze and determine the optimal relationships for goal attainment. The contingency approach has emerged in recent years as the dominant theoretical framework for viewing organizational structure and design. Although open systems analysis (Katz & Kahn, 1966) emphasized the input of the external environment into organization structuring, the contingency approach attempts to establish functional relationships between environmental variables and organizational variables. Over the past decade and a half, contingency theorists have demonstrated the apparent interaction between the environment and organization variables. For example, more than 15 years ago the pioneering contingency theorist Joan Woodward (1965) found that the environmental variable of technology seemed to have a relationship with structural variables. Although she dealt with relatively narrow production oriented (unit, mass/batch, and process) technology, Perrow (1970) and others have since suggested that other technological classifications such as knowledge based variables are related to organizational structure variables

End-User Visual Design of Web-Based Interactive Applications Making Use of Geographical Information: the WINDMash Approach

International audienceVisual instructional design languages currently provide notations for representing the intermediate and final results of a knowledge engineering process. This paper reports on a visual framework (called WIND - Web INteraction Design) that focuses on both designers' creativity and model executability. It only addresses Active Reading Learning Scenarios making use of localized documents (travel stories, travel guides). Our research challenge is to enable the teachers to design by themselves interaction scenarios for such a domain, avoiding any programmer intervention. The WIND framework provides a conceptual model and its associated Application Programming Interface (API). The WIND interaction scenarios are encoded as XML documents which are automatically transformed into code thanks to the provided API, thus providing designers with a real application that they can immediately assess and modify (prototyping techniques). The WIND conceptual model only provides designers with an abstract syntax and a semantics. Users of such a Domain Specific Language (DSL) need a concrete syntax. Our choice is to produce a Web-Based Mashup Environment providing designers with visual functionality