The analysis and presentation of patents to support engineering design

This paper explores the role of patents in engineering design, and how the extraction and presentation of patent data could be improved for designers. We propose the use of crowdsourcing as a means to post tasks online for a crowd of people to participate and complete. The is-sues of assessment, searching, clustering and knowledge transfer are evaluated with respect to the literature. Opportunities for potential crowd intervention are then discussed, before the presentation of two initial studies. These related to the categorization and interpretation of patents respectively using an online platform. The initial results establish basic crowd capabilities in understanding patent text and interpreting patent drawings. This has shown that reasonable results can be achieved if tasks of appropriate duration and complexity are set, and if test questions are incorporated to ensure a basic level of understanding exists in the workers

Desenvolvimento de plano de comunicação integrada de marketing para um salão de beleza

This study aimed to develop and implement an Integrated Marketing Communication (CIM) Plan for a small company that provides beauty and aesthetic services. The method employed was qualitative, using bibliographic, documentary, and action research. With the development and application of the CIM plan, it was possible to observe an increase in the customer base, with increased sales and improved organizational commitment for employees. Another result was the increase in brand awareness by potential customers through the revitalization of the brand. The importance of the CIM plan is emphasized as a synergistic enhancer for the different areas of the company, as well as the improvement of the company’s relationship with the target, and improvement of workflow and financial control. The study enabled the use of Service Blueprint as a diagnostic tool for the development of actions planned and employed in the CIM plan. O objetivo deste artigo tecnológico consistiu no desenvolvimento e aplicação de Plano de Comunicação Integrada de Marketing (CIM) para pequena empresa prestadora de serviços de beleza e estética. O método empregado foi de natureza qualitativa, com uso de pesquisa bibliográfica, documental e pesquisa-ação. Com o desenvolvimento e aplicação do plano de CIM foi possível verificar aumento da base de clientes, com aumento do faturamento e melhoria do comprometimento organizacional dos funcionários. Outro resultado foi o aumento do conhecimento da marca pelos clientes potenciais a partir da revitalização da marca. Ressalta-se a importância do plano de CIM como potencializador sinérgico das diversas áreas da empresa bem como o fortalecimento do relacionamento da empresa com o público alvo, e melhoria do fluxo de trabalho e do controle financeiro. O estudo propiciou o uso do Service Blueprint como ferramenta de diagnóstico para o desenvolvimento das ações planejadas e empregadas no plano de CIM

What Made Me the Teacher I Am Today? A Reflection by Selected Leonore Annenberg-Woodrow Wilson Teaching Fellows

The report offers a series of short essays from 18 teachers, each reflecting on what inspired and guided them into the teaching profession. Some of the highlights include:"I've come to realize that my learning process in the classroom actually feels a whole lot like the science I practiced at the bench: engineering experimental procedures, collecting and analyzing data, and formulating questions about next steps. It turns out that my scientific worldview can really improve learning outcomes for my students," said Kristin Milks, a biology and earth science teacher in Bloomington, IN, who enrolled in a teacher preparation program shortly after completing her Ph.D. in biochemistry."What transforms someone from being a good teacher to being a great teacher is the passion to make connections with students, to constantly evaluate and adjust their practice to do what is in the students' best interest," said Catherine Ann Haney, a Virginia Spanish teacher who has recently been teaching in Santiago, Chile."Enrolling in a teacher education program, instead of starting my career as a teacher first and then obtaining my master's degree after, meant I had a cohort of other soon-to-be teachers to learn with as we persevered through a very rigorous and demanding year," said Jeremy Cress, a math teacher in Philadelphia."I realized that being a good math teacher does not mean explaining clearly, making kids like me, or making math fun. Rather, it means giving students the opportunity to solve problems by themselves from start to finish, to struggle and persevere, and to learn from each other's particular strengths," said Brittany Leknes, a math teacher from Sunnyvale, CA."Together my students and I co-create their identities, their sense of themselves, and their understanding of their place in society. Because I believe wholly in my students' own power, I teach to disrupt school cultures that suggest that students need to be anything less than their whole selves," said Kayla Vinson, who taught social students in the Harlem Children's Zone.Created in 2007, the Leonore Annenberg-Woodrow Wilson Teaching Fellowship was designed to serve as the equivalent of a national "Rhodes Scholarship" for teaching. Working with Stanford University, the University of Pennsylvania, the University of Virginia, and the University of Washington, the Woodrow Wilson Foundation provided $30,000 stipends for exceptionally able candidates to complete a yearlong master's degree program. In exchange, the teacher candidates agreed to teach for three years in high-need secondary schools across the country. The Leonore Annenberg Teaching Fellowship was funded through grants from the Annenberg Foundation and Carnegie Corporation of New York. It served as the basis for the Woodrow Wilson Foundation's successful Teaching Fellowship program, which now operates in five states (Georgia, Indiana, Michigan, New Jersey, and Ohio), operating in partnership with 28 universities. Woodrow Wilson Teaching Fellows complete a rigorous yearlong master's degree program, coupled with a robust yearlong clinical experience. Once they earn their degrees, Woodrow Wilson Teaching Fellows teach in high-need STEM classrooms, while receiving three years of coaching and mentoring

Consensus-Based Data Management within Fog Computing For the Internet of Things

The Internet of Things (IoT) infrastructure forms a gigantic network of interconnected and interacting devices. This infrastructure involves a new generation of service delivery models, more advanced data management and policy schemes, sophisticated data analytics tools, and effective decision making applications. IoT technology brings automation to a new level wherein nodes can communicate and make autonomous decisions in the absence of human interventions. IoT enabled solutions generate and process enormous volumes of heterogeneous data exchanged among billions of nodes. This results in Big Data congestion, data management, storage issues and various inefficiencies. Fog Computing aims at solving the issues with data management as it includes intelligent computational components and storage closer to the data sources. Often, an IoT-enabled infrastructure is shared among many users with various requirements. Sharing resources, sharing operational costs and collective decision making (consensus) among many stakeholders is frequently neglected. This research addresses an essential requirement for adaptive, autonomous and consensus-based Fog computational solutions which are able to support distributed and in-network schemes and policies. These network schemes and policies need to meet the requirements of many users. In this work, innovative consensus-based computational solutions are investigated. These proposed solutions aim to correlate and organise data for effective management and decision making in Fog. Instead of individual decision making, the algorithms aim to aggregate several decisions into a consensus decision representing a collective agreement, benefiting from the individuals variant knowledge and meeting multiple stakeholders requirements. In order to validate the proposed solutions, hybrid research methodology is involved that includes the design of a test-bed and the execution of several experiments. In order to investigate the effectiveness of the paradigm, three experiments were designed and validated. Real-life sensor data and synthetic statistical data was collected, processed and analysed. Bayesian Machine Learning models and Analytics were used to consolidate the design and evaluate the performance of the algorithms. In the Fog environment, the first scenario tests the Aggregation by Distribution algorithm. The solution contribute in achieving a notable efficiency of data delivery obtained with a minimal loss in precision. The second scenario validates the merits of the approach in predicting the activities of high mobility IoT applications. The third scenario tests the applications related to smart home IoT. All proposed Consensus algorithms use statistical analysis to support effective decision making in Fog and enable data aggregation for optimal storage, data transmission, processing and analytics. The final results of all experiments showed that all the implemented consensus approaches surpass the individual ones in different performance terms. Formal results also showed that the paradigm is a good fit in many IoT environments and can be suitable for different scenarios when applying data analysis to correlate data with the design. Finally, the design demonstrates that Fog Computing can compete with Cloud Computing in terms of accuracy with an added preference of locality

Social Innovations in Creative Communities for Sustainable Consumption: is it promising?

In the current discourse on sustainable consumption, there have been major interventions by the businesses and governments, focusing on changing consumer behavior through greening products and services. However, the problem of consumption is not limited to greening products and environmental impacts, but it is also a social issue. Together with the increasing consumption around the world and materialistic aspirations, a decline in well being and happiness can also be observed, particularly in industrialized countries. Recently, the sustainable consumption process has started to draw attention to individual value shifts reflected on peoples consumption patterns and social behavior. To examine and explain phenomenon, examples from creative communities are being analysed. According to some experts on sustainable production and consumption, these creative communities are showing promising outcomes through increasing well being and developing sustainable lifestyles. Still, they have been unable to disseminate their practices to the mainstream markets. This indicates a need for developing strategies to explore the creative communities in terms their values, principles, social innovation strategies, practices and their perspectives of sustainability. Unless these are well understood and an exchange platform is established between relevant actors including citizens, it is unlikely that creative community practices (i.e. sustainable lifestyle cases) will be incorporated the society as a whole. This research addresses the challenges and opportunities facing creative communities, their behaviours and social innovation solutions using both theoretical and empirical studies. The results are based on five field case study communities from the US, Scotland, Sweden and Italy, each with different types of social innovations. The main findings on individual value orientation and action incurring benefits demonstrate the potential of the communities or their practices to be adapted by wider society. Moreover, the nature of their practices, which highly depend on ethical responsibility, transfer of knowledge and networking relations, have shown the potential of linking between creative communitycitizens, external actors-community and between individuals. This can be established through creating relational spaces, which can take varied forms to stimulate social innovation in the agenda of sustainable consumption

Living labs managing the intra-organizational knowledge exchange process when transitioning from closed to open innovation

C

Casco Bay Weekly : 26 March 1998

https://digitalcommons.portlandlibrary.com/cbw_1998/1014/thumbnail.jp

Algorithmic Decision Support for Shunt Planning

Eén van de laatste onderdelen van het planningsproces voor het vervoeren van treinreizigers is operationele rangeerplanning. Rangeerplanning richt zich op de logistiek binnen een station en de directe omgeving ervan. De vraag naar transport varieert gedurende de dag en daarom heeft een spoorvervoerder buiten de spits vaak rollend materieel over. Vaak wordt dit overtollig materieel tijdelijk opgesteld op een rangeerterrein zodat de hoofdinfrastructuur gebruikt kan worden door andere treinen. Het toewijzen van aankomend materieel aan vertrekkend materieel, het routeren van materieel door stations, het reinigen van materieel, en personeelsplanning zijn, naast het opstellen, onderdelen van rangeerplanning. "Algoritmische Beslissingsondersteuning voor Rangeerplanning” introduceert de karakteristieken van rangeren en zet een eerste stap in de richting van kwantitatieve modellen en algoritmen voor het ondersteunen van de rangeerplanning. Verschillende algoritmen voor het oplossen van verschillende kwantitatieve modellen lijken in meerdere en mindere mate op de huidige praktijk van rangeerplanners. Rekenresultaten gebaseerd op realistische data laten zien dat goede oplossingen vaak binnen enkele minuten rekentijd worden gevonden. Daarnaast zijn deze algoritmen ontworpen om interactie met rangeerplanners te stimuleren. De algoritmen vormen een solide basis voor een geavanceerd beslissingsondersteunend systeem voor rangeerplanners.One of the last elements of the planning process of a passenger railway operator is operational shunt planning. It focuses on the logistics within a station and its surroundings. Since demand for transportation fluctuates over a day, a railway operator typically has a surplus of rolling stock outside the rush hours, and especially during the night. In general, the idle rolling stock is parked at a shunt yard, thereby keeping the main railway infrastructure available for other train services. Besides parking of rolling stock, matching of arriving to departing rolling stock, routing over local railway infrastructure, cleaning of rolling stock, and crew planning are part of shunt planning. "Algorithmic Decision Support for Shunt Planning" introduces relevant aspects of shunting and provides a first step for quantitative models and algorithms to support shunt planning. The algorithms for solving the models contain algorithms that resemble the current practice of shunt planners as well as algorithms that are somewhat farther away from current practice. Computational tests on real-life data show that high-quality solutions are typically found within minutes of computation time. In addition, these algorithms are designed to interact with shunt planners. They provide a firm basis for an advanced planning system to support shunt planners