Challenges in Developing Applications for Aging Populations

Elderly individuals can greatly benefit from the use of computer applications, which can assist in monitoring health conditions, staying in contact with friends and family, and even learning new things. However, developing accessible applications for an elderly user can be a daunting task for developers. Since the advent of the personal computer, the benefits and challenges of developing applications for older adults have been a hot topic of discussion. In this chapter, the authors discuss the various challenges developers who wish to create applications for the elderly computer user face, including age-related impairments, generational differences in computer use, and the hardware constraints mobile devices pose for application developers. Although these challenges are concerning, each can be overcome after being properly identified

Development and Testing of a Methane/Oxygen Catalytic Microtube Ignition System for Rocket Propulsion

This study sought to develop a catalytic ignition advanced torch system with a unique catalyst microtube design that could serve as a low energy alternative or redundant system for the ignition of methane and oxygen rockets. Development and testing of iterations of hardware was carried out to create a system that could operate at altitude and produce a torch. A unique design was created that initiated ignition via the catalyst and then propagated into external staged ignition. This system was able to meet the goals of operating across a range of atmospheric and altitude conditions with power inputs on the order of 20 to 30 watts with chamber pressures and mass flow rates typical of comparable ignition systems for a 100 lbf engine

Scalable Model-Based Management of Correlated Dimensional Time Series in ModelarDB+

To monitor critical infrastructure, high quality sensors sampled at a high frequency are increasingly used. However, as they produce huge amounts of data, only simple aggregates are stored. This removes outliers and fluctuations that could indicate problems. As a remedy, we present a model-based approach for managing time series with dimensions that exploits correlation in and among time series. Specifically, we propose compressing groups of correlated time series using an extensible set of model types within a user-defined error bound (possibly zero). We name this new category of model-based compression methods for time series Multi-Model Group Compression (MMGC). We present the first MMGC method GOLEMM and extend model types to compress time series groups. We propose primitives for users to effectively define groups for differently sized data sets, and based on these, an automated grouping method using only the time series dimensions. We propose algorithms for executing simple and multi-dimensional aggregate queries on models. Last, we implement our methods in the Time Series Management System (TSMS) ModelarDB (ModelarDB+). Our evaluation shows that compared to widely used formats, ModelarDB+ provides up to 13.7 times faster ingestion due to high compression, 113 times better compression due to the adaptivity of GOLEMM, 630 times faster aggregates by using models, and close to linear scalability. It is also extensible and supports online query processing.Comment: 12 Pages, 28 Figures, and 1 Tabl

Employment of Real-Time/FPGA Architectures for Test and Control of Automotive Engines

Nowadays the production of increasingly complex and electrified vehicles requires the implementation of new control and monitoring systems. This reason, together with the tendency of moving rapidly from the test bench to the vehicle, leads to a landscape that requires the development of embedded hardware and software to face the application effectively and efficiently. The development of application-based software on real-time/FPGA hardware could be a good answer for these challenges: FPGA grants parallel low-level and high-speed calculation/timing, while the Real-Time processor can handle high-level calculation layers, logging and communication functions with determinism. Thanks to the software flexibility and small dimensions, these architectures can find a perfect collocation as engine RCP (Rapid Control Prototyping) units and as smart data logger/analyser, both for test bench and on vehicle application. Efforts have been done for building a base architecture with common functionalities capable of easily hosting application-specific control code. Several case studies originating in this scenario will be shown; dedicated solutions for protype applications have been developed exploiting a real-time/FPGA architecture as ECU (Engine Control Unit) and custom RCP functionalities, such as water injection and testing hydraulic brake control

Performance Evaluation Analysis of Spark Streaming Backpressure for Data-Intensive Pipelines

A significant rise in the adoption of streaming applications has changed the decisionmaking processes in the last decade. This movement has led to the emergence of several Big Data technologies for in-memory processing, such as the systems Apache Storm, Spark, Heron, Samza, Flink, and others. Spark Streaming, a widespread open-source implementation, processes data-intensive applications that often require large amounts of memory. However, Spark Unified Memory Manager cannot properly manage sudden or intensive data surges and their related inmemory caching needs, resulting in performance and throughput degradation, high latency, a large number of garbage collection operations, out-of-memory issues, and data loss. This work presents a comprehensive performance evaluation of Spark Streaming backpressure to investigate the hypothesis that it could support data-intensive pipelines under specific pressure requirements. The results reveal that backpressure is suitable only for small and medium pipelines for stateless and stateful applications. Furthermore, it points out the Spark Streaming limitations that lead to in-memory-based issues for data-intensive pipelines and stateful applications. In addition, the work indicates potential solutions.N/

Hardware Pioneers: Harnessing the Impact Potential of Technology Entrepreneurs

Billions of households across the world live without conveniences such as electric lighting, flush toilets, and sanitary sewerage systems. Products such as milk chilling machines and solar home systems can have a significant impact on lives and livelihoods of people living in poverty in developing countries. Hardware pioneers—inventors and entrepreneurs creating breakthrough products tailored to the needs of these populations—are pushing the frontiers of technology and business to create and scale innovative hardware technologies.Numerous case studies within the report illustrate how these pioneers face many of the same challenges of any entrepreneur but with the added complexity of developing hardware and scaling in remote areas with scarce resources. There is a significant opportunity for actors across sectors to strategically leverage their resources in order to support the journeys of these hardware pioneers, from initial inspiration to ultimate impact at scale.Top TakeawaysHardware pioneers lack the right supports in the critical Pioneer Gap stages when they are blueprinting, validating, and preparing their models. In the early stages, these needs range from patient capital to prototyping facilities. Later on, issues such as distribution, financing, servicing, and quality standards become more important.Critically, because the success of hardware pioneers depends on the successful blending of both business and technology skills, those working closely with pioneer teams also need to bring the right combination of these skills, and this unfortunately is rare in the impact enterprise ecosystem.There is need to not just support hardware pioneers directly but also to assemble the other needed parts of the ecosystem, from last-mile specialist companies that help pioneers reach and serve their target markets to the programs and institutions that are helping to spark the initial impulse that gets pioneers started on their journey in the right way.New ideas can have an ultimate impact that is much greater than that of the original pioneer alone through a transfer of the idea to a more scale-ready partner or just through adoption and adaptation of the idea by follower entrepreneurs. We believe that there is great impact potential in supporting these more networked pathways for scaling