A Global Online Handwriting Recognition Approach Based on Frequent Patterns

In this article, the handwriting signals are represented based on geometric and spatio-temporal characteristics to increase the feature vectors relevance of each object. The main goal was to extract features in the form of a numeric vector based on the extraction of frequent patterns. We used two types of frequent motifs (closed frequent patterns and maximal frequent patterns) that can represent handwritten characters pertinently. These common features patterns are generated from a raw data transformation method to achieve high relevance. A database of words consisting of two different letters was created. The proposed application gives promising results and highlights the advantages that frequent pattern extraction algorithms can achieve, as well as the central role played by the “minimum threshold” parameter in the overall description of the characters

Three dimensional surface reconstruction of lower limb prosthetic model using infrared sensor array

This thesis addresses the development of a shape detector device using infrared sensor to reconstruct a three-dimensional image of an object. The threedimension image is produced based on the object surface using image processing technique. Conventionally, infrared sensors are used for detection of an obstacle and distance measurement to avoid collisions. However, it is not common to use infrared sensors to measure the size of an object. Hence, this research aims to investigate the feasibility of infrared sensors in measuring the object dimension for three-dimension image reconstruction. Experiments were executed to study the minimum distance range utilising GP2D120 infrared sensor. From the experiment, the distance between the sensor and object surface should be more than 5 cm. The scanning device consists of the infrared sensor array was placed in a black box with the object in the center. The scanning process required the object to turn 360 ° clockwise in an xy plane and the resolution for z-axis is 2 mm, in order to obtain data for the image reconstruction. Reference polygon shape models with various dimensions were used as scanning objects in the experiments. The device scans object diameter every 2 mm in thickness, 100 mm in height, and the total time required to collect data for each layer is 60 seconds. The reconstructed object accuracy is above 80 % based on the comparison between a solid and printed model dimension. Four different lower limb prosthetic models with different shapes were used as the object in the scanning experiments. The experimental findings show that the prosthetic shapes reconstructed with an average accuracy of 97 %. This system shows good reproducibility where the collected data using the infrared sensor device need further improvement so that it can be applied in medical field for orthotics and prosthetics purpose

Investigating business process elements: a journey from the field of Business Process Management to ontological analysis, and back

Business process modelling languages (BPMLs) typically enable the representation of business processes via the creation of process models, which are constructed using the elements and graphical symbols of the BPML itself. Despite the wide literature on business process modelling languages, on the comparison between graphical components of different languages, on the development and enrichment of new and existing notations, and the numerous definitions of what a business process is, the BPM community still lacks a robust (ontological) characterisation of the elements involved in business process models and, even more importantly, of the very notion of business process. While some efforts have been done towards this direction, the majority of works in this area focuses on the analysis of the behavioural (control flow) aspects of process models only, thus neglecting other central modelling elements, such as those denoting process participants (e.g., data objects, actors), relationships among activities, goals, values, and so on. The overall purpose of this PhD thesis is to provide a systematic study of the elements that constitute a business process, based on ontological analysis, and to apply these results back to the Business Process Management field. The major contributions that were achieved in pursuing our overall purpose are: (i) a first comprehensive and systematic investigation of what constitutes a business process meta-model in literature, and a definition of what we call a literature-based business process meta-model starting from the different business process meta-models proposed in the literature; (ii) the ontological analysis of four business process elements (event, participant, relationship among activities, and goal), which were identified as missing or problematic in the literature and in the literature-based meta-model; (iii) the revision of the literature-based business process meta-model that incorporates the analysis of the four investigated business process elements - event, participant, relationship among activities and goal; and (iv) the definition and evaluation of a notation that enriches the relationships between activities by including the notions of occurrence dependences and rationales

A Digital Game Maturity Model

Game development is an interdisciplinary concept that embraces artistic, software engineering, management, and business disciplines. Game development is considered as one of the most complex tasks in software engineering. Hence, for successful development of good-quality games, the game developers must consider and explore all related dimensions as well as discussing them with the stakeholders involved. This research facilitates a better understanding of important dimensions of digital game development methodology. The increased popularity of digital games, the challenges faced by game development organizations in developing quality games, and severe competition in the digital game industry demand a game development process maturity assessment. Consequently, this study presents a Digital Game Maturity Model to evaluate the current development methodology in an organization. The objective is first to identify key factors in the game development process, then to classify these factors into target groups, and eventually to use this grouping as a theoretical basis for proposing a maturity model for digital game development. In doing so, the research focuses on three major stakeholders in game development: developers, consumers, and business management. The framework of the proposed model consists of assessment questionnaires made up of key identified factors from three empirical studies, a performance scale, and a rating method. The main goal of the questionnaires is to collect information about current processes and practices. This research contributes towards formulating a comprehensive and unified strategy for game development process maturity assessment. The proposed model was evaluated with two case studies from the digital game industry

Anotación Automática de Imágenes Médicas Usando la Representación de Bolsa de Características

La anotación automática de imágenes médicas se ha convertido en un proceso necesario para la gestión, búsqueda y exploración de las crecientes bases de datos médicas para apoyo al diagnóstico y análisis de imágenes en investigación biomédica. La anotación automática consiste en asignar conceptos de alto nivel a imágenes a partir de las características visuales de bajo nivel. Para esto se busca tener una representación de la imagen que caracterice el contenido visual de ésta y un modelo de aprendizaje entrenado con ejemplos de imágenes anotadas. Este trabajo propone explorar la Bolsa de Características (BdC) para la representación de las imágenes de histología y los Métodos de Kernel (MK) como modelos de aprendizaje de máquina para la anotación automática. Adicionalmente se exploró una metodología de análisis de colecciones de imágenes para encontrar patrones visuales y sus relaciones con los conceptos semánticos usando Análisis de Información Mutua, Selección de Características con Máxima-Relevancia y Mínima-Redundancia (mRMR) y Análisis de Biclustering. La metodología propuesta fue evaluada en dos bases de datos de imágenes, una con imá- genes anotadas con los cuatro tejidos fundamentales y otra con imágenes de tipo de cáncer de piel conocido como carcinoma basocelular. Los resultados en análisis de imágenes revelan que es posible encontrar patrones implícitos en colecciones de imágenes a partir de la representación BdC seleccionan- do las palabras visuales relevantes de la colección y asociándolas a conceptos semánticos mientras que el análisis de biclustering permitió encontrar algunos grupos de imágenes similares que comparten palabras visuales asociadas al tipo de tinción o conceptos. En anotación automática se evaluaron distintas configuraciones del enfoque BdC. Los mejores resultados obtenidos presentan una Precisión de 91 % y un Recall de 88 % en las imágenes de histología, y una Precisión de 59 % y un Recall de 23 % en las imágenes de histopatología. La configuración de la metodología BdC con los mejores resultados en ambas colecciones fue obtenida usando las palabras visuales basadas en DCT con un diccionario de tamaño 1,000 con un kernel Gaussiano. / Abstract. The automatic annotation of medical images has become a necessary process for managing, searching and exploration of growing medical image databases for diagnostic support and image analysis in biomedical research. The automatic annotation is to assign high-level concepts to images from the low-level visual features. For this, is needed to have a image representation that characterizes its visual content and a learning model trained with examples of annotated images. This paper aims to explore the Bag of Features (BOF) for the representation of histology images and Kernel Methods (KM) as models of machine learning for automatic annotation. Additionally, we explored a methodology for image collection analysis in order to _nd visual patterns and their relationships with semantic concepts using Mutual Information Analysis, Features Selection with Max-Relevance and Min- Redundancy (mRMR) and Biclustering Analysis. The proposed methodology was evaluated in two image databases, the _rst have images annotated with the four fundamental tissues, and the second have images of a type of skin cancer known as Basal-cell carcinoma. The image analysis results show that it is possible to _nd implicit patterns in image collections from the BOF representation. This by selecting the relevant visual words in the collection and associating them with semantic concepts, whereas biclustering analysis allowed to _nd groups of similar images that share visual words associated with the type of stain or concepts. The Automatic annotation was evaluated in di_erent settings of BOF approach. The best results have a Precision of 91% and Recall of 88% in the histology images, and a Precision of 59% and Recall of 23% in histopathology images. The con_guration of BOF methodology with the best results in both datasets was obtained using the DCT-based visual words in a dictionary size of 1; 000 with a Gaussian kernel.Maestrí

Transition and Opportunity

This book is open access under a CC BY-NC-ND 4.0 license. Multinational corporations (MNCs) have long played a crucial role in the Chinese economy. This role is one that is set to continue in the post-pandemic era as China works to transit to a high-quality growth model that is more sustainable and innovation-driven. With global experience and front-line involvement in some of the most pressing economic, technological, and environmental issues of our day, leading figures in MNCs and chambers of commerce are well placed to share insights that could potentially contribute to policymaking and development strategies so that everyone can “make the most” of China’s future. This collection of essay aims to share these invaluable insights with a wider audience, offering balanced and diverse perspectives from companies and advocacy groups working on a range of issues related to China’s domestic development, international economic cooperation, and China-US competition. These insights are useful not only for the wider business community, but also for academics, policymakers, students, and anyone trying to deepen their understanding of this exciting period of “transition and opportunity,” and make the most of China’s bright future