Verifying big data topologies by-design: a semi-automated approach

Big data architectures have been gaining momentum in recent years. For instance, Twitter uses stream processing frameworks like Apache Storm to analyse billions of tweets per minute and learn the trending topics. However, architectures that process big data involve many different components interconnected via semantically different connectors. Such complex architectures make possible refactoring of the applications a difficult task for software architects, as applications might be very different with respect to the initial designs. As an aid to designers and developers, we developed OSTIA (Ordinary Static Topology Inference Analysis) that allows detecting the occurrence of common anti-patterns across big data architectures and exploiting software verification techniques on the elicited architectural models. This paper illustrates OSTIA and evaluates its uses and benefits on three industrial-scale case-studies

Database resources of the National Center for Biotechnology Information

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART) and the PubChem suite of small molecule databases. Augmenting many of the web applications is custom implementation of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov

Prometheus: a generic e-commerce crawler for the study of business markets and other e-commerce problems

Dissertação de mestrado em Computer ScienceThe continuous social and economic development has led over time to an increase in consumption, as well as greater demand from the consumer for better and cheaper products. Hence, the selling price of a product assumes a fundamental role in the purchase decision by the consumer. In this context, online stores must carefully analyse and define the best price for each product, based on several factors such as production/acquisition cost, positioning of the product (e.g. anchor product) and the competition companies strategy. The work done by market analysts changed drastically over the last years. As the number of Web sites increases exponentially, the number of E-commerce web sites also prosperous. Web page classification becomes more important in fields like Web mining and information retrieval. The traditional classifiers are usually hand-crafted and non-adaptive, that makes them inappropriate to use in a broader context. We introduce an ensemble of methods and the posterior study of its results to create a more generic and modular crawler and scraper for detection and information extraction on E-commerce web pages. The collected information may then be processed and used in the pricing decision. This framework goes by the name Prometheus and has the goal of extracting knowledge from E-commerce Web sites. The process requires crawling an online store and gathering product pages. This implies that given a web page the framework must be able to determine if it is a product page. In order to achieve this we classify the pages in three categories: catalogue, product and ”spam”. The page classification stage was addressed based on the html text as well as on the visual layout, featuring both traditional methods and Deep Learning approaches. Once a set of product pages has been identified we proceed to the extraction of the pricing information. This is not a trivial task due to the disparity of approaches to create a web page. Furthermore, most product pages are dynamic in the sense that they are truly a page for a family of related products. For instance, when visiting a shoe store, for a particular model there are probably a number of sizes and colours available. Such a model may be displayed in a single dynamic web page making it necessary for our framework to explore all the relevant combinations. This process is called scraping and is the last stage of the Prometheus framework.O contínuo desenvolvimento social e económico tem conduzido ao longo do tempo a um aumento do consumo, assim como a uma maior exigência do consumidor por produtos melhores e mais baratos. Naturalmente, o preço de venda de um produto assume um papel fundamental na decisão de compra por parte de um consumidor. Nesse sentido, as lojas online precisam de analisar e definir qual o melhor preço para cada produto, tendo como base diversos fatores, tais como o custo de produção/venda, posicionamento do produto (e.g. produto âncora) e as próprias estratégias das empresas concorrentes. O trabalho dos analistas de mercado mudou drasticamente nos últimos anos. O crescimento de sites na Web tem sido exponencial, o número de sites E-commerce também tem prosperado. A classificação de páginas da Web torna-se cada vez mais importante, especialmente em campos como mineração de dados na Web e coleta/extração de informações. Os classificadores tradicionais são geralmente feitos manualmente e não adaptativos, o que os torna inadequados num contexto mais amplo. Nós introduzimos um conjunto de métodos e o estudo posterior dos seus resultados para criar um crawler e scraper mais genéricos e modulares para extração de conhecimento em páginas de Ecommerce. A informação recolhida pode então ser processada e utilizada na tomada de decisão sobre o preço de venda. Esta Framework chama-se Prometheus e tem como intuito extrair conhecimento de Web sites de E-commerce. Este processo necessita realizar a navegação sobre lojas online e armazenar páginas de produto. Isto implica que dado uma página web a framework seja capaz de determinar se é uma página de produto. Para atingir este objetivo nós classificamos as páginas em três categorias: catálogo, produto e spam. A classificação das páginas foi realizada tendo em conta o html e o aspeto visual das páginas, utilizando tanto métodos tradicionais como Deep Learning. Depois de identificar um conjunto de páginas de produto procedemos à extração de informação sobre o preço. Este processo não é trivial devido à quantidade de abordagens possíveis para criar uma página web. A maioria dos produtos são dinâmicos no sentido em que um produto é na realidade uma família de produtos relacionados. Por exemplo, quando visitamos uma loja online de sapatos, para um modelo em especifico existe a provavelmente um conjunto de tamanhos e cores disponíveis. Esse modelo pode ser apresentado numa única página dinâmica fazendo com que seja necessário para a nossa Framework explorar estas combinações relevantes. Este processo é chamado de scraping e é o último passo da Framework Prometheus

Development of a digital rapid training course for improving the additive manufacturing adoption rate - fused filament fabrication

Thesis (MEng)--Stellenbosch University, 2022.ENGLISH SUMMARY: Additive Manufacturing (AM) technologies, such as Fused Filament Fabrication (FFF), have a slow adoption rate. Training on these AM technologies is typically not included in primary to tertiary education curriculums and studies have shown that the lack of education on it, negatively affects the adoption rate. This issue was addressed in this study by developing a digital rapid training course on FFF. A literature study was first performed to gain a better understanding of the different AM technologies and the adoption thereof. The focus was then shifted to a set of learning methods and platforms that are used in the educational sphere. After completing the literature study, it was concluded that training users in FFF can help improve the adoption rate of the technology. The knowledge gained through the literature study was then used to develop a cross-platform digital training course (Web, iOS, and Android), aimed at introducing users to and educating them in FFF. The course consists of teaching sessions, tests, and questionnaires. The course was made available to the general public (free of charge) for a year with no specific target group, allowing users with and without FFF experience to participate. The training course automatically gathered quantitative and qualitative data by recording users’ answers during tests and questionnaires respectively. The course was completed by 198 participants. This data was then analysed to determine whether the training course increased the users’ knowledge of, confidence to engage with, and likelihood to adopt the FFF technology. From the group of participants, 87% claimed that their level of knowledge and understanding of FFF increased by participating in the course. The majority (94%) of the participants stated they are more likely to interact with the technology after participating. The users with no prior knowledge/experience with the technology were found to have benefited the most from the course. Such individuals can be targeted during the development and deployment of AM courses to have the biggest impact on the adoption rate. It was concluded that the training course increased the majority of users’ knowledge of, confidence to engage with, and likelihood to adopt the FFF technology.AFRIKAANS OPSOMMING: Additive Manufacturing (AM) tegnologieë, soos Fused Filament Fabrication (FFF), het 'n stadige aannemingstempo. Opleiding oor hierdie AM tegnologieë word tipies nie by primêre tot tersiêre onderwyskurrikulums ingesluit nie. Studies het getoon dat die gebrek aan onderrig oor die onderwerp ‘n negatiewe invloed op die annemingsyfer het. Dié kwessie is in hierdie studie aangespreek deur 'n digitale opleidingskursus oor FFF te ontwikkel. 'n Literatuurstudie is eers uitgevoer om 'n beter begrip van die verskillende AM-tegnologieë en die aanneming daarvan te verkry. Die fokus is toe verskuif na 'n stel leermetodes en platforms wat in die opvoedkundige sfeer gebruik word. Na voltooiing van die literatuurstudie, is die gevolgtrekking gemaak dat opleiding van gebruikers in FFF kan help om die aannemingstempo van die tegnologie te verbeter. Die kennis wat deur die literatuurstudie opgedoen is, is toe gebruik om 'n kruis-platform digitale opleidingskursus (Web, iOS en Android) te ontwikkel wat daarop gemik is om gebruikers bekend te stel aan en hulle in FFF op te voed. Die kursus bevat onderrigsessies, toetse en vraelyste. Die kursus is vir 'n jaar beskikbaar gestel aan die algemene publiek (gratis), sonder 'n spesifieke teikengroep. Dit het gebruikers met en sonder FFF-ervaring toegelaat het om deel te neem. Die opleidingskursus het outomaties kwantitatiewe en kwalitatiewe data ingesamel deur gebruikers se antwoorde tydens onderskeidelik toetse en vraelyste aan te teken. Die kursus is deur 198 deelnemers voltooi. Hierdie data is toe ontleed om te bepaal of die opleidingskursus die gebruikers se kennis van, selfvertroue om die FFF-tegnologie te gebruik, en die waarskynlikheid om dit aan te neem, verhoog het. Uit die groep deelnemers beweer 87% van hulle dat hul vlak van kennis en begrip van FFF toegeneem het sedert hulle die kursus voltooi het. Die meerderheid (94%) van die deelnemers het gesê dat hulle meer geneig is om die tegnologie te gebruik nadat hulle deelgeneem het. Daar is gevind dat die gebruikers, met geen vorige kennis van/ervaring met die tegnologie, die meeste by die kursus baat gevind het. Hulle kan geteiken word tydens die ontwikkeling en ontplooiing van AM-kursusse om die grootste impak op die aannemingstempo te hê. Daar is tot die gevolgtrekking gekom dat die opleidingskursus die meerderheid van gebruikers se kennis van, selfvertroue om die FFF-tegnologie te gebruik, en die waarskynlikheid om dit aan te neem, verhoog het.Master

A Makeover for the Habitat for Humanity MetroWest/Greater Worcester ReStore Website

Habitat for Humanity MetroWest/Greater Worcester (MW/GW) ReStore works in collaboration with the Habitat for Humanity MW/GW affiliate to fund their mission to eliminate substandard housing. The goal of our project was to help update the Habitat for Humanity MW/GW ReStore website and market it to help attract new members to shop, donate and volunteer at ReStore. By instituting multiple data collection techniques on the former ReStore website along with other successful websites, we identified the key attributes that make a website successful. We used the data to develop findings that influenced our design of the new ReStore website. By identifying the Restore’s target audience, we were able to create various marketing strategies to develop a marketing plan as well as implement some of them

NGS-based genotyping, high-throughput phenotyping and genome-wide association studies laid the foundations for next-generation breeding in horticultural crops

Demographic trends and changes to climate require a more efficient use of plant genetic resources in breeding programs. Indeed, the release of high-yielding varieties has resulted in crop genetic erosion and loss of diversity. This has produced an increased susceptibility to severe stresses and a reduction of several food quality parameters. Next generation sequencing (NGS) technologies are being increasingly used to explore “gene space” and to provide high-resolution profiling of nucleotide variation within germplasm collections. On the other hand, advances in high-throughput phenotyping are bridging the genotype-to-phenotype gap in crop selection. The combination of allelic and phenotypic data points via genome-wide association studies is facilitating the discovery of genetic loci that are associated with key agronomic traits. In this review, we provide a brief overview on the latest NGS-based and phenotyping technologies and on their role to unlocking the genetic potential of vegetable crops; then, we discuss the paradigm shift that is underway in horticultural crop breeding

Attracting more international talents to work in Finland – mixed-method user research

This thesis investigates the mixed-method user research throughout the Work in Finland website redesign project, aiming to enhance Finland's visibility and attractiveness to international specialists. The study employs qualitative and quantitative data analysis, including semi-structured interviews, thematic analysis, web analytics, tree testing, usability testing, and User Acceptance Testing. The project follows the "double diamond" design framework, comprising four key phases: Discovery, Describe, Design, and Build. Initially, user research was conducted to gain insights into the needs, preferences, and pain points of international talent working in Finland. Based on the findings, a comprehensive design solution was developed, incorporating Promotional, Call-to-action, and Informational user journeys. Subsequently, user testing was conducted to evaluate and validate the solution, gathering feedback from target users on various aspects, including structure, design, and implementation. The outcomes of these user tests demonstrated a positive reception of the Work in Finland project. The utilization of mixed-method user research proved instrumental in facilitating effective communication between the Work in Finland project team and the target audience. It established a user-friendly foundation for the concept and design, contributing to the project's widespread acceptance