The Indiana Cooler Injector Synchrotron Project

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

Data Serialization Formats for the Internet of Things

IoT devices rely on data exchange with gateways and cloud servers. However, the performance of today's serialization formats and libraries on embedded systems with energy and memory constraints is not well-documented and hard to predict. We evaluate (de)serialization and transmission cost of mqtt.eclipse.org payloads on 8- to 32-bit microcontrollers and find that Protocol Buffers (as implemented by NanoPB) and the XDR format, dating back to 1987, are most efficient

Compositions, Methods And Kits Relating To Remodel

The invention relates to novel nucleic acids encoding a mammalian adventitia inducible and bone expressed gene designated REMODEL, and proteins encoded thereby, whose expression is increased in certain diseases, disorders, or conditions, including, but not limited to, negative remodeling, arterial restenosis, vessel injury, ectopic ossification, fibrosis, and the like. REMODEL also plays a role in cell-cell and cell-matrix adhesion, bone density, bone formation, dorsal closure, and is associated with spina bifida-like phenotype. The invention further relates to methods of treating and detecting these diseases, disorders or conditions, comprising modulating or detecting REMODEL expression and/or production of REMODEL polypeptide

Electron Cooling System Development

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

Supporting STEM knowledge and skills in engineering education – PELARS project

In this paper we present our proposal for improving education with hands-on, project-based and experimental scenarios for engineering students with the use of learning analytics. We accomplish this through teacher and learner engagement, user studies and evaluated trials, performed at UCV (University of Craiova, Romania) and DTU (Technical University of Denmark). The PELARS project (Practice-based Experiential Learning Analytics Research And Support) provides technological tools and ICT-based methods for collecting activity data (moving image-based and embedded sensing) for learning analytics (data-mining and reasoning) of practice-based and experiential STEM. This data is used to create analytics support tools for teachers, learners and administrators, providing frameworks for evidence-based curriculum design and learning systems. The PELARS project creates behavioral recording inputs, proving a new learning analytic that is scalable in application, and bridge qualitative and quantitative methods through reasoning and feedback from input data. The project serves to better understand learners' knowledge in physical activities in laboratory and workshop environments, as well as informal learning scenarios. PELARS traces and helps assess learner progress through technology enhancement, in novel ways building upon current research. The project results in learning analytics tools for practice-based STEM learning that are appropriate for real-world learning environments

Gamma-Ray Escape-peak Response from a Radiation-Damaged Reverse-Electrode Coaxial Germanium Detectore

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

PhyNetLab: An IoT-Based Warehouse Testbed

Future warehouses will be made of modular embedded entities with communication ability and energy aware operation attached to the traditional materials handling and warehousing objects. This advancement is mainly to fulfill the flexibility and scalability needs of the emerging warehouses. However, it leads to a new layer of complexity during development and evaluation of such systems due to the multidisciplinarity in logistics, embedded systems, and wireless communications. Although each discipline provides theoretical approaches and simulations for these tasks, many issues are often discovered in a real deployment of the full system. In this paper we introduce PhyNetLab as a real scale warehouse testbed made of cyber physical objects (PhyNodes) developed for this type of application. The presented platform provides a possibility to check the industrial requirement of an IoT-based warehouse in addition to the typical wireless sensor networks tests. We describe the hardware and software components of the nodes in addition to the overall structure of the testbed. Finally, we will demonstrate the advantages of the testbed by evaluating the performance of the ETSI compliant radio channel access procedure for an IoT warehouse