Space Laser Power Transmission System Studies

Power transmission by laser technique is addressed. Space to Earth and space to space configurations are considered

Hibikino-Musashi@Home 2023 Team Description Paper

This paper describes an overview of the techniques of Hibikino-Musashi@Home, which intends to participate in the domestic standard platform league. The team has developed a dataset generator for the training of a robot vision system and an open-source development environment running on a human support robot simulator. The robot system comprises self-developed libraries including those for motion synthesis and open-source software works on the robot operating system. The team aims to realize a home service robot that assists humans in a home, and continuously attend the competition to evaluate the developed system. The brain-inspired artificial intelligence system is also proposed for service robots which are expected to work in a real home environment

The 'what' and 'how' of learning in design, invited paper

Previous experiences hold a wealth of knowledge which we often take for granted and use unknowingly through our every day working lives. In design, those experiences can play a crucial role in the success or failure of a design project, having a great deal of influence on the quality, cost and development time of a product. But how can we empower computer based design systems to acquire this knowledge? How would we use such systems to support design? This paper outlines some of the work which has been carried out in applying and developing Machine Learning techniques to support the design activity; particularly in utilising previous designs and learning the design process

Achieving Autonomic Computing through the Use of Variability Models at Run-time

Increasingly, software needs to dynamically adapt its behavior at run-time in response to changing conditions in the supporting computing infrastructure and in the surrounding physical environment. Adaptability is emerging as a necessary underlying capability, particularly for highly dynamic systems such as context-aware or ubiquitous systems. By automating tasks such as installation, adaptation, or healing, Autonomic Computing envisions computing environments that evolve without the need for human intervention. Even though there is a fair amount of work on architectures and their theoretical design, Autonomic Computing was criticised as being a \hype topic" because very little of it has been implemented fully. Furthermore, given that the autonomic system must change states at runtime and that some of those states may emerge and are much less deterministic, there is a great challenge to provide new guidelines, techniques and tools to help autonomic system development. This thesis shows that building up on the central ideas of Model Driven Development (Models as rst-order citizens) and Software Product Lines (Variability Management) can play a signi cant role as we move towards implementing the key self-management properties associated with autonomic computing. The presented approach encompass systems that are capable of modifying their own behavior with respect to changes in their operating environment, by using variability models as if they were the policies that drive the system's autonomic recon guration at runtime. Under a set of recon guration commands, the components that make up the architecture dynamically cooperate to change the con guration of the architecture to a new con guration. This work also provides the implementation of a Model-Based Recon guration Engine (MoRE) to blend the above ideas. Given a context event, MoRE queries the variability models to determine how the system should evolve, and then it provides the mechanisms for modifying the system.Cetina Englada, C. (2010). Achieving Autonomic Computing through the Use of Variability Models at Run-time [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/7484Palanci

Applying Software Product Lines to Build Autonomic Pervasive Systems

In this Master Thesis, we have proposed a model-driven Software Product Line (SPL) for developing autonomic pervasive systems. The work focusses on reusing the Variability knowledge from the SPL design to the SPL products. This Variability knowledge enables SPL products to deal with adaptation scenarios (evolution and involution) in an autonomic way.Cetina Englada, C. (2008). Applying Software Product Lines to Build Autonomic Pervasive Systems. http://hdl.handle.net/10251/12447Archivo delegad

Human peroxisomal coenzyme A diphosphatase (NUDT7): a target enabling package (TEP)

In an effort to characterise the human NUDIX family SGC Oxford has expressed recombinant human NUDT7 as part of the SGC chemical probe programme and solved the first crystal structure of this enzyme. This enabled a crystallographic fragment screen which in conjunction with a separate covalent fragment approach yielded a first-in-class small molecule inhibitor of NUDT7 with activity in the single-digit micromolar range in a catalytic assay. This compound paves the way for chemical probe development and further functional exploration of NUDT7 in physiological and disease contexts

A Decision Support System for Selecting Between Designs for Dynamic Software Product Lines

When commissioning a system, a myriad of potential designs can successfully fulfill the system\u27s goals. Deciding among the candidate designs requires an understanding of how the design affects the system\u27s quality attributes and how much effort is needed to realize the design. The difficulty of the process compounds if the system to be designed includes dynamic run-time self- adaptivity, the ability for the system to self-modify its architecture at run-time in response to either external or internal stimuli, as the type and location of the dynamic self-adaptivity within the architecture must be co-decided. In this proposal, we introduce a Decision Support System, which contains a new Dynamic Software Product Line-centric cost / effort estimation technique, the Structured Intuitive Model for Dynamic Adaptive System Economics (SIMDASE), that will allow system designers / architects to select the most appropriate design for systems where the candidates can be structured as a Dynamic Software Product Line. We will focus on using the Decision Support System to select designs for a system where at least one component of the system is a low-level embedded system for use within the Internet of Things (IoT), particularly embedded systems whose purpose is to exist as things (either intelligent sensors or actuators). The Decision Support System we introduce is a multi-step process that begins with a high- level system architecture generated from the system requirements and goals. Candidate designs that can fulfill all goals / requirements of the high-level architecture are selected. Each design is then annotated using SIMDASE so that the effort, risk, cost and return on investment that can be expected from the realization of the design(s) can be compared in order to select the best design for a given organization

ICSEA 2022: the seventeenth international conference on software engineering advances

The Seventeenth International Conference on Software Engineering Advances (ICSEA 2022), held between October 16th and October 20th, 2022, continued a series of events covering a broad spectrum of software-related topics. The conference covered fundamentals on designing, implementing, testing, validating and maintaining various kinds of software. Several tracks were proposed to treat the topics from theory to practice, in terms of methodologies, design, implementation, testing, use cases, tools, and lessons learned. The conference topics covered classical and advanced methodologies, open source, agile software, as well as software deployment and software economics and education. Other advanced aspects are related to on-time practical aspects, such as run-time vulnerability checking, rejuvenation process, updates partial or temporary feature deprecation, software deployment and configuration, and on-line software updates. These aspects trigger implications related to patenting, licensing, engineering education, new ways for software adoption and improvement, and ultimately, to software knowledge management. There are many advanced applications requiring robust, safe, and secure software: disaster recovery applications, vehicular systems, biomedical-related software, biometrics related software, mission critical software, E-health related software, crisis-situation software. These applications require appropriate software engineering techniques, metrics and formalisms, such as, software reuse, appropriate software quality metrics, composition and integration, consistency checking, model checking, provers and reasoning. The nature of research in software varies slightly with the specific discipline researchers work in, yet there is much common ground and room for a sharing of best practice, frameworks, tools, languages and methodologies. Despite the number of experts we have available, little work is done at the meta level, that is examining how we go about our research, and how this process can be improved. There are questions related to the choice of programming language, IDEs and documentation styles and standard. Reuse can be of great benefit to research projects yet reuse of prior research projects introduces special problems that need to be mitigated. The research environment is a mix of creativity and systematic approach which leads to a creative tension that needs to be managed or at least monitored. Much of the coding in any university is undertaken by research students or young researchers. Issues of skills training, development and quality control can have significant effects on an entire department. In an industrial research setting, the environment is not quite that of industry as a whole, nor does it follow the pattern set by the university. The unique approaches and issues of industrial research may hold lessons for researchers in other domains. We take here the opportunity to warmly thank all the members of the ICSEA 2022 technical program committee, as well as all the reviewers. The creation of such a high-quality conference program would not have been possible without their involvement. We also kindly thank all the authors who dedicated much of their time and effort to contribute to ICSEA 2022. We truly believe that, thanks to all these efforts, the final conference program consisted of top-quality contributions. We also thank the members of the ICSEA 2022 organizing committee for their help in handling the logistics of this event. We hope that ICSEA 2022 was a successful international forum for the exchange of ideas and results between academia and industry and for the promotion of progress in software engineering advances