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

Natural Language Processing in-and-for Design Research

We review the scholarly contributions that utilise Natural Language Processing (NLP) methods to support the design process. Using a heuristic approach, we collected 223 articles published in 32 journals and within the period 1991-present. We present state-of-the-art NLP in-and-for design research by reviewing these articles according to the type of natural language text sources: internal reports, design concepts, discourse transcripts, technical publications, consumer opinions, and others. Upon summarizing and identifying the gaps in these contributions, we utilise an existing design innovation framework to identify the applications that are currently being supported by NLP. We then propose a few methodological and theoretical directions for future NLP in-and-for design research

Forecasting of emerging therapeutic monoclonal antibodies patents based on a decision model

Therapeutic monoclonal antibodies (mAbs) market is strongly contributing to the rising growth of the biotechnology industry. Despite the increasing number of inventions over time, a few therapeutic mAbs are currently marketed. This paper focuses on developing an emerging score to select/rank promising therapeutic mAbs patents, based on a hierarchical decision model using expert's opinion. Six attributes related to each factor concerning patent status, patent owner's profile and mAbs medical relevance were analyzed. The desirability levels of each attribute were also assessed. Our data shows the medical relevance factor as the most important, contributing 50% of the emerging score. Among the attributes, the most important under patent status was proper geographic coverage and wider patent scope; for organization's profile was the preexistence of approved drugs; and for medical relevance, the clinical phase performance. A group of 1053 patents related to therapeutic mAb were scored, and the most promising were concerning combination therapy using immune checkpoint inhibitors. The study has managerial implications related to patent portfolio management and patent valuation, and provides instructions to rank mAbs patents according to the emerging score defined by attribute's importance in order to improve the identification of future innovations pathways

Bioinspired metaheuristic algorithms for global optimization

This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF

Towards Populating Generalizable Engineering Design Knowledge

Aiming to populate generalizable engineering design knowledge, we propose a method to extract facts of the form head entity :: relationship :: tail entity from sentences found in patent documents. These facts could be combined within and across patent documents to form knowledge graphs that serve as schemes for representing as well as storing design knowledge. Existing methods in engineering design literature often utilise a set of predefined relationships to populate triples that are statistical approximations rather than facts. In our method, we train a tagger to identify both entities and relationships from a sentence. Given a pair of entities thus identified, we train another tagger to identify the relationship tokens that specifically denote the relationship between the pair. For training these taggers, we manually construct a dataset of 44,227 sentences and corresponding facts. We also compare the performance of the method against typically recommended approaches, wherein, we predict the edges among tokens by pairing the tokens independently and as part of a graph. We apply our method to sentences found in patents related to fan systems and build a domain knowledge base. Upon providing an overview of the knowledge base, we search for solutions relevant to some key issues prevailing in fan systems. We organize the responses into knowledge graphs and hold a comparative discussion against the opinions from ChatGPT

Diseño de un prototipo de prótesis mandibular, a partir de modelos anatómicos 3d, caso de estudio

Este proyecto propone el diseño de una prótesis de mandíbula para tratar una alteración congénita denominada Microsomia Hemifacial (MH), en cuya deformidad se ve comprometida la integridad de la Articulación Temporomandibular (ATM), ya sea de uno de los lados de la mandíbula o incluso ambos, que afecta la simetría facial del usuario que la padece. Para el desarrollo del proyecto se investigó sobre esta anomalía congénita con el fin de entender mejor la problemática del caso de estudio de este proyecto. Para el desarrollo del prototipo de prótesis de mandíbula a partir de modelos anatómicos 3D, primero se investigó los programas que existen en el mercado y que permitieron realizar la reconstrucción tridimensional a partir de imágenes médicas en formato Dicom, las cuales provienen de equipos de Tomografía Computarizada y/o Resonancia Magnética. Además se diseñó un Phantom para validar experimentalmente el funcionamiento y la interacción de cada software con el diseñador, igualmente, esta herramienta sirvió para evaluar la eficiencia y la precisión de cada uno de los programas, ya que se generó una tabla comparativa que permitió detectar las ventajas y desventajas de cada uno. El proceso incluyó la consulta de materiales que se utilizan para la fabricación de los Phantom, los cuales están muy ligados a que sus características simulen la densidad de los tejidos humanos. La selección de medidas y geometría de cada material también fue referenciada y se utilizó para verificar cada valor con cada uno de los software previamente seleccionados. Con dicha actividad se generó una tabla comparativa con la cual se logró evidenciar que el programa con los mejores resultados es Invesalius, programa que se usó para procesar y generar el modelo tridimensional a partir de las imágenes tomográficas del caso de estudio de este proyecto. Al concluir con la reconstrucción 3D, se encontró zonas afectadas por ruidos provenientes de diferentes fuentes. Por esta razón el modelo tridimensional fue exportado a otro software, para eliminar el ruido de la malla, con lo cual se pudo limpiar y reducir las zonas afectadas, lo cual permitió realizar el diseño del prototipo de prótesis de mandíbula con base en la anatomía del usuario. Además se realizó una tabla comparativa la cual permitió observar el cambio de las diferentes propiedades de malla según el tipo de filtro aplicado. Con base en estos datos se seleccionó el número de iteraciones y el tipo de filtro que requiere ser implementado teniendo en cuenta los tipos de ruido que contienen los datos del caso de estudio. Finalmente se pudo desarrollar un modelo 3D adecuado (sin ruido) para continuar con las otras fases de diseño. Como el tipo de MH del caso de estudio, solo afecta un lado de la mandíbula del usuario, al tener un modelo tridimensional libre de zonas de ruido, se generó un conjunto de superficies de la parte anatómica que no es afectada por la MH, con las cuales se generó el sólido de los componentes que van a ser empleados para reemplazar el cóndilo y la fosa, dos componentes esenciales de la articulación temporomandibular y recuperar con esto la simetría facial. Una vez obtenido el prototipo de prótesis de mandíbula, se procedió a realizar un análisis computacional FEA con el cual se verificó el comportamiento y se logró concluir que el esfuerzo Von Mises máximo registrado en el modelo es de 124,8 MPa, por otro lado el desplazamiento máximo registrado fue de 0,02 mm. Datos similares a lo reportado en la literatura. Igualmente se pudo otorgar un factor de seguridad global del prototipo de 1,4PregradoIngeniero(a) Biomédico(a

The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approaches

This paper presents a new crowdsourcing approach to the construction of patent clusters, and systematically benchmarks it against previous expert and algorithmic approaches. Patent databases should be rich sources of inspiration which could lead engineering designers to novel solutions for creative problems. However, the sheer volume and complexity of patent information means that this potential is rarely realised. Rather than the keyword driven searches common in commercial systems, designers need tools that help them to understand patents in the context of the problem they are considering. This paper presents an approach to address this problem by using crowd intelligence for effective generation of patent clusters at lower cost and with greater rationale. A systematic study was carried out to compare the crowd’s efficiency with both expert and algorithmic patent clusters, with the results indicating that the crowd was able to create 80% more patent pairs with appropriate rationale

Investigation of mobile devices usage and mobile augmented reality applications among older people

Mobile devices such as tablets and smartphones have allow users to communicate, entertainment, access information and perform productivity. However, older people are having issues to utilise mobile devices that may affect their quality of life and wellbeing. There are some potentials of mobile Augmented Reality (AR) applications to increase older users mobile usage by enhancing their experience and learning. The study aims to investigate mobile devices potential barriers and influence factors in using mobile devices. It also seeks to understand older people issues in using AR applications