Should beat gestures be learned or designed? A benchmarking user study

In this paper, we present a user study on gener-ated beat gestures for humanoid agents. It has been shownthat Human-Robot Interaction can be improved by includingcommunicative non-verbal behavior, such as arm gestures. Beatgestures are one of the four types of arm gestures, and are knownto be used for emphasizing parts of speech. In our user study,we compare beat gestures learned from training data with hand-crafted beat gestures. The first kind of gestures are generatedby a machine learning model trained on speech audio andhuman upper body poses. We compared this approach with threehand-coded beat gestures methods: designed beat gestures, timedbeat gestures, and noisy gestures. Forty-one subjects participatedin our user study, and a ranking was derived from pairedcomparisons using the Bradley Terry Luce model. We found thatfor beat gestures, the gestures from the machine learning modelare preferred, followed by algorithmically generated gestures.This emphasizes the promise of machine learning for generating communicative actions.QC 20190815</p

A dynamic product flow model for a mixed ecological farm - an ICT application for ecological agriculture

Specialised farming systems, which focus on producing one or few products, are characterised by high productivity but also by high amounts of detrimental emissions and low quality residual products that makes them unsustainable. Mixed ecological farming systems, which focus on several products, are characterised by processes with cyclic product flows and low levels of detrimental emissions that makes them more sustainable. In this article, a model is introduced that provides a tool for developing and managing sustainability at mixed ecological farms. This will be done from a quality assurance perspective. The core of the model is the process informatics layer that connects business control and process control. This approach structures and generates data from business processes and physical processes and in this way acts as a decision-making platform or learning environment. The model can form a basis for an operational or tactical decision-support syste

IOF2020: Fostering business and software ecosystems for large-scale uptake of IoT in food and farming

The Internet of Things (IoT) is expected to be a real game changer that will drastically improve productivity and sustainability in food and farming. However, current IoT applications in this domain are still fragmentary and mainly used by a small group of early adopters. The Internet of Food and Farm 2020 Large-Scale Pilot (IoF2020) addresses the organizational and technological challenges to overcome this situation by fostering a large-scale uptake of IoT in the European food and farming domain. The heart of the project is formed by a balanced set of multi-actor trials that reflect the diversity of the food and farming domain. Each trial is composed of well-delineated use cases developing IoT solutions for the most relevant challenges of the concerned subsector. The project conducts 5 trials with a total of 19 use cases in arable, dairy, fruits, vegetables and meat production. IoF2020 embraces a lean multi-actor approach that combines the development of Minimal Viable Products (MVPs) in short iterations with the active involvement of various stakeholders. The architectural approach supports interoperability of multiple use case systems and reuse of IoT components across them. Use cases are also supported in developing business and solving governance issues. The IoF2020 ecosystem and collaboration space is established to boost the uptake of IoT in Food and Farming and pave the way for new innovations

1980 Ruby Yearbook

A digitized copy of the 1980 Ruby, the Ursinus College yearbook.https://digitalcommons.ursinus.edu/ruby/1083/thumbnail.jp

Business Process Modelling in Demand‐Driven Agri‐Food Supply Chains

Agri ‐food companies increasingly participate in demand‐driven supply chains that are able to adapt flexibly to changes in the marketplace. The objective of this presentation is to discuss a process modelling framework, which enhances the interoperability and agility of information systems as required in such dynamic supply chains. The designed framework consists of two parts: an object system definition and a modelling toolbox. The object system definition provides a conceptual definition of business process in demand‐driven supply chains from a systems perspective. It includes an application of the Viable Systems Model of Stafford Beer to supply chains, and classifications of business processes, control systems and coordination mechanisms. The modelling toolbox builds on the terminology and process definitions of SCOR and identifies three types of process models: i) Product Flow Models: visualize the allocation of basic transformations to supply chain actors and the related product flows from input material into end products (including different traceability units based on the GS1 Global Traceability Standard); ii) Thread Diagrams: visualize how order driven and forecast driven processes are decoupled in specific supply chain configurations (positions Customer Order Decoupling Points), and how interdependences between processes are coordinated; iii) Business Process Diagrams: depict the sequence and interaction of control and coordination activities (as identified in Thread Diagrams) in BPMN notation. The framework is applied to several agrifood sectors, in particular potted plants and fruit supply chains. The main benefits are: i) It helps to map supply chain processes, including its control and coordination, in a timely, punctual and coherent way; ii) It supports a seamless translation of high level supply chain designs to detailed information engineering models; iii) It enables rapid instantiation of various supply chain configurations (instead of dictating a single blueprint); iv) It combines sector specific knowledge with reuse of knowledge provided by generic cross industry standards (SCOR, GS1)

Supporting Precision Agriculture by Technology Integration on a Inter and Intra Enterprise Level

Dutch agri-food supply chain network actors can use technologies, (web) services and tools to increase sustainable production and chain transparency in agriculture. Adoption of these (web) services and tools in arable farming is still low. Therefore, the Dutch ministry of agriculture started a public-private project to support more sustainable crop production: the Program Precision Agriculture. In this program, technologies, tools and (web) services are developed. Integrating new tools and (web) services into farm management is difficult and involves different disciplines. Research is involved for supporting integration. This paper provides a brief description of current projects in the Program Precision Agriculture, related to information integration. The projects are classified based on their integration levels and scop