3D Interactive virtual environments for E-learning, teaching and technical support: Multiplayer teaching and learning games for the School of Art, Design & Architecture.

This paper outlines the key stages of a University funded teaching and learning project, the main objective of the project is to build an online 3D virtual Ramsden workshop (RW) game learning environment. Using 3D modeling software and interactive 3D game programming technologies the project team have accurately modeled and simulated the Ramsden workshop (RW) building; The 3D virtual RW workshop has been accurately built to scale and is fitted with virtual furniture, virtual computers, virtual engineering machinery. These components have been developed as an initial range of interactive game based learning tools. In this project the team has also begun to simulate Health and Safety procedures, created software CAD/CAM tutorials and are developing and testing innovative learning support tools for all levels of learners. The 3D Virtual Ramsden workshop (RW) game is part of ongoing research work that applies the use of 3D virtual software for developing appropriate interactive 3D spaces, avatars, objects and simulations for learning, teaching, training, exhibitions, experimental art and practice in virtual environments. Additionally within this project the research team also modelled a virtual Creative Arts Building and a University of Huddersfield virtual campus

A systematic mapping study on testing technique experiments: has the situation changed since 2000?

Context: Empirical Software Engineering (ESE) replication researchers need to store and manipulate experimental data for several purposes, in particular analysis and reporting. Current research needs call for sharing and preservation of experimental data as well. In a previous work, we analyzed Replication Data Management (RDM) needs. A novel concept, called Experimental Ecosystem, was proposed to solve current deficiencies in RDM approaches. The empirical ecosystem provides replication researchers with a common framework that integrates transparently local heterogeneous data sources. A typical situation where the Empirical Ecosystem is applicable, is when several members of a research group, or several research groups collaborating together, need to share and access each other experimental results. However, to be able to apply the Empirical Ecosystem concept and deliver all promised benefits, it is necessary to analyze the software architectures and tools that can properly support it

Social music machine: crowdsourcing for composition & creativity

This poster describes a compositional technique that used crowd-sourced midi clips in order to develop a piece of music, which was later performed. This work in progress highlighted some of the issues facing the designers of systems that enable the ‘crowd’ to compose. INTRODUCTION Can the crowd get creative? And what sort of tools might be used to support this? These are the sorts of questions that we thought about when we initially started to think about these problems. Using software originally developed as part of an Experimental Digital Humanities [1] project, we started to wonder about how such software - “Numbers into Notes” [2] might work in the real world if multiple people used it in creative way, and what lessons might we learn from carrying out such an intervention

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices

Accessible machine learning algorithms, software, and diagnostic tools for energy-efficient devices and systems are extremely valuable across a broad range of application domains. In scientific domains, real-time near-sensor processing can drastically improve experimental design and accelerate scientific discoveries. To support domain scientists, we have developed hls4ml, an open-source software-hardware codesign workflow to interpret and translate machine learning algorithms for implementation with both FPGA and ASIC technologies. We expand on previous hls4ml work by extending capabilities and techniques towards low-power implementations and increased usability: new Python APIs, quantization-aware pruning, end-to-end FPGA workflows, long pipeline kernels for low power, and new device backends include an ASIC workflow. Taken together, these and continued efforts in hls4ml will arm a new generation of domain scientists with accessible, efficient, and powerful tools for machine-learning-accelerated discovery.Comment: 10 pages, 8 figures, TinyML Research Symposium 202

Artifacts - Anycast Agility: Network Playbooks to Fight DDoS

In this document, we provide datasets and software tools related to our paper “Anycast Agility: Network Playbooks to Fight DDoS”. Our artifact contains several datasets generated from our anycast experiments and analysis. Our datasets provide a snapshot of the results that we generated during our experiments. Some of our experimental results are dependent on the current state of the network interconnections and policies. However, due to the anycast stability, we expect to get similar results if we redo the experiments now. Our published datasets support our key results and are publicly available. We also provide tools and scripts that can be useful for other researchers. We provide datasets and tools for measuring anycast agility against DDoS. Our datasets are available upon request. We provide datasets about the traffic distribution after BGP changes in testbeds, attack data from a DNS root server and from the Dutch National Scrubbing Center, other data related to anycast catchment stability, and other supporting data for our software tools. We provide codes for traffic estimation, for reproducing experiments, and for parsing the collected data.This work is supported, in part, by the DHS HSARPA Cyber Security Division via contract number HSHQDC-17-R-B0004-TTA.02-0006-I and Netherlands Organisation for scientific research (4019020199)

Исследование технологических процессов шароструйного бурения наклоннонаправленных скважин

Целью работы является проведение исследования влияния зенитного угла скважины на эффективность шароструйного бурения. В работе изложены результаты теоретических и экспериментальных исследований технологических процессов наклонно-направленного шароструйного бурения с использованием программного компьютерного сопровождения и современных методических средств. На проводившихся экспериментальных исследованиях разработаны методики инженерного расчета процессов шароструйного бурения и исследования влияния зенитного угла скважины на эффективность шароструйного бурения.The aim of the work is to study the influence of the zenith angle of the well on the efficiency of ball-jet drilling. The paper presents the results of theoretical and experimental studies of the technological processes of directional ball-jet drilling using computer software support and modern methodological tools. Experimental studies have developed techniques for the engineering calculation of ball-jet drilling processes and studies of the influence of the zenith angle of the well on the efficiency of ball-jet drilling

Automated recognition of design patterns for framework understanding

System design is one of the most important tasks in the software development cycles but it is also one of the most complex and time-consuming tasks. Thus, reuse of existing designs becomes very important. Object-oriented frameworks are generic designs for specific application domains that enable the reuse of designs and domain expert experience. In spite of this, frameworks are not simple to reuse because they are difficult to comprehend, mainly due to a lack of good documentation and supporting tools. In this work, an approach to framework comprehension based on the automated recognition and visualization of design patterns is presented. A tool was built to support this approach, by trying to automatically identify and explain the potentia~ patterns existing in a given designo Experimental results and conclusions of tool utilization are also presented

Reviewing technical approaches for sharing and preservation of experimental data

Empirical Software Engineering (ESE) replication researchers need to store and manipulate experimental data for several purposes, in particular analysis and reporting. Current research needs call for sharing and preservation of experimental data as well. In a previous work, we analyzed Replication Data Management (RDM) needs. A novel concept, called Experimental Ecosystem, was proposed to solve current deficiencies in RDMapproaches. The empirical ecosystem provides replication researchers with a common framework that integrates transparently local heterogeneous data sources. A typical situation where the Empirical Ecosystem is applicable, is when several members of a research group, or several research groups collaborating together, need to share and access each other experimental results. However, to be able to apply the Empirical Ecosystem concept and deliver all promised benefits, it is necessary to analyze the software architectures and tools that can properly support it

Development of computer software for simulation of transmission line dynamic behavior

Structural failure of transmission line systems is often attributed to dynamic effects such as a broken conductor, a broken insulator, or conductor galloping. The focus of this research was to develop a computer program, DYNTRN, that can analyze the structural response of a transmission line system due to dynamic effects, and present the response in a graphical form. The program uses the stiffness method to analyze a system consisting of conductors, insulators, and support structures. Four types of elements can be used to model the transmission line components: beam elements, cable elements, truss elements, and spring elements. A dynamic condensation method was introduced to efficiently model cable elements. Geometric nonlinearities were accounted for using the Newton-Raphson method. State-of-the-art software tools and object oriented design were used to develop a program that is modular and interactive. An object oriented method was developed to efficiently store and solve the stiffness matrix of the structure. Results obtained from the program were verified using commercial finite element software. The program was also validated using published experimental work. The final product of this research is a computer program that can graphically simulate dynamic behavior of transmission lines

CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources

International audienceBACKGROUND: The functions of proteins are strongly related to their localization in cell compartments (for example the cytoplasm or membranes) but the experimental determination of the sub-cellular localization of proteomes is laborious and expensive. A fast and low-cost alternative approach is in silico prediction, based on features of the protein primary sequences. However, biologists are confronted with a very large number of computational tools that use different methods that address various localization features with diverse specificities and sensitivities. As a result, exploiting these computer resources to predict protein localization accurately involves querying all tools and comparing every prediction output; this is a painstaking task. Therefore, we developed a comprehensive database, called CoBaltDB, that gathers all prediction outputs concerning complete prokaryotic proteomes. DESCRIPTION: The current version of CoBaltDB integrates the results of 43 localization predictors for 784 complete bacterial and archaeal proteomes (2.548.292 proteins in total). CoBaltDB supplies a simple user-friendly interface for retrieving and exploring relevant information about predicted features (such as signal peptide cleavage sites and transmembrane segments). Data are organized into three work-sets ("specialized tools", "meta-tools" and "additional tools"). The database can be queried using the organism name, a locus tag or a list of locus tags and may be browsed using numerous graphical and text displays. CONCLUSIONS: With its new functionalities, CoBaltDB is a novel powerful platform that provides easy access to the results of multiple localization tools and support for predicting prokaryotic protein localizations with higher confidence than previously possible. CoBaltDB is available at http://www.umr6026.univ-rennes1.fr/english/home/research/basic/software/cobalten