931 resultados para User interfaces (Computer systems)


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The article presents a new method to automatic generation of help in software. Help generation is realized in the framework of the tool for development and automatic generation of user interfaces based on ontologies. The principal features of the approach are: support for context-sensitive help, automatic generation of help using a task project and an expandable system of help generation.

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Resource Space Model is a kind of data model which can effectively and flexibly manage the digital resources in cyber-physical system from multidimensional and hierarchical perspectives. This paper focuses on constructing resource space automatically. We propose a framework that organizes a set of digital resources according to different semantic dimensions combining human background knowledge in WordNet and Wikipedia. The construction process includes four steps: extracting candidate keywords, building semantic graphs, detecting semantic communities and generating resource space. An unsupervised statistical language topic model (i.e., Latent Dirichlet Allocation) is applied to extract candidate keywords of the facets. To better interpret meanings of the facets found by LDA, we map the keywords to Wikipedia concepts, calculate word relatedness using WordNet's noun synsets and construct corresponding semantic graphs. Moreover, semantic communities are identified by GN algorithm. After extracting candidate axes based on Wikipedia concept hierarchy, the final axes of resource space are sorted and picked out through three different ranking strategies. The experimental results demonstrate that the proposed framework can organize resources automatically and effectively.©2013 Published by Elsevier Ltd. All rights reserved.

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Reading scientific articles is more time-consuming than reading news because readers need to search and read many citations. This paper proposes a citation guided method for summarizing multiple scientific papers. A phenomenon we can observe is that citation sentences in one paragraph or section usually talk about a common fact, which is usually represented as a set of noun phrases co-occurring in citation texts and it is usually discussed from different aspects. We design a multi-document summarization system based on common fact detection. One challenge is that citations may not use the same terms to refer to a common fact. We thus use term association discovering algorithm to expand terms based on a large set of scientific article abstracts. Then, citations can be clustered based on common facts. The common fact is used as a salient term set to get relevant sentences from the corresponding cited articles to form a summary. Experiments show that our method outperforms three baseline methods by ROUGE metric.©2013 Elsevier B.V. All rights reserved.

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Михаил Константинов, Весела Пашева, Петко Петков - Разгледани са някои числени проблеми при използването на компютърната система MATLAB в учебната дейност: пресмятане на тригонометрични функции, повдигане на матрица на степен, спектрален анализ на целочислени матрици от нисък ред и пресмятане на корените на алгебрични уравнения. Причините за възникналите числени трудности могат да се обяснят с особеностите на използваната двоичната аритметика с плаваща точка.

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The European Leonardo da Vinci Transfer of Innovation project “Teacher training to improve attractiveness and quality of management education through the simulation tool ‘Emerald Forest’” which emphases on using the computer simulation tool for increasing attractiveness of teaching and learning in economics is presented in this paper. The observation of using computer systems and especially serious games in education is provided as well. “Education is not the filling of a pail, but the lighting of a fire” - William Butler Yeats

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This paper presents an innovative approach for enhancing digital libraries functionalities. An innovative distributed architecture involving digital libraries for effective and efficient knowledge sharing was developed. In the frame of this architecture semantic services were implemented, offering multi language and multi culture support, adaptability and knowledge resources recommendation, based on the use of ontologies, metadata and user modeling. New methods for teacher education using digital libraries and knowledge sharing were developed. These new methods were successfully applied in more than 15 pilot experiments in seven European countries, with more than 3000 teachers trained.

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Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016

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Heuristics, simulation, artificial intelligence techniques and combinations thereof have all been employed in the attempt to make computer systems adaptive, context-aware, reconfigurable and self-managing. This paper complements such efforts by exploring the possibility to achieve runtime adaptiveness using mathematically-based techniques from the area of formal methods. It is argued that formal methods @ runtime represents a feasible approach, and promising preliminary results are summarised to support this viewpoint. The survey of existing approaches to employing formal methods at runtime is accompanied by a discussion of their challenges and of the future research required to overcome them. © 2011 Springer-Verlag.

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In this chapter we provide a comprehensive overview of the emerging field of visualising and browsing image databases. We start with a brief introduction to content-based image retrieval and the traditional query-by-example search paradigm that many retrieval systems employ. We specify the problems associated with this type of interface, such as users not being able to formulate a query due to not having a target image or concept in mind. The idea of browsing systems is then introduced as a means to combat these issues, harnessing the cognitive power of the human mind in order to speed up image retrieval.We detail common methods in which the often high-dimensional feature data extracted from images can be used to visualise image databases in an intuitive way. Systems using dimensionality reduction techniques, such as multi-dimensional scaling, are reviewed along with those that cluster images using either divisive or agglomerative techniques as well as graph-based visualisations. While visualisation of an image collection is useful for providing an overview of the contained images, it forms only part of an image database navigation system. We therefore also present various methods provided by these systems to allow for interactive browsing of these datasets. A further area we explore are user studies of systems and visualisations where we look at the different evaluations undertaken in order to test usability and compare systems, and highlight the key findings from these studies. We conclude the chapter with several recommendations for future work in this area. © 2011 Springer-Verlag Berlin Heidelberg.

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The purpose of this study was to determine the impact of selected factors on nurses' attitudes toward bedside computers. Bedside computer systems, also referred to as point-of-care systems, are clinical information systems that allow documentation of patient care and retrieval of data at the patient's bedside, or in close proximity to where care is delivered. The adoption of bedside computer systems appears to be increasing among U.S. institutions. As healthcare institutions undertake automation projects, they face many challenges associated with implementing large-scale change. ^ The study explored four factors and their relationship to nurses' attitudes toward bedside computers. A pre-bedside implementation survey of 184 staff nurses did not demonstrate a relationship between previous computer experience and nurses' attitudes toward bedside computers (p > .05). The data did not indicate a relationship between nurses' formal education and their attitude toward bedside computers (p > .05). The data did support a relationship between nurses' previous computer experience and their comfort in the use of bedside computers (p < .0005). Using a quasi-experimental control group design, attitudes of nurses were studied over an 18 month period. The Pre versus Post Survey data indicated that nurses who used bedside computers, the experimental group, had more positive attitudes than the nurses who did not use bedside computers, the control group (p < .0005). ^ The findings are significant to institutions implementing bedside computers, to the human resource development staff overseeing bedside computer training, and to the practice of clinical nursing. ^

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The solution of partial differential equation of seepage problems is difficult to find analytically, especially for situations that involve great complexity. To overcome this problem, software based on finite differences and finite elements are usually used. This work presents the use of a finite element software, the GEO5, to solve the seepage problem at a dam of very complex section, the dam Eng. Armando Ribeiro Gonçalves, which at the end of its construction suffered rupture of the upstream slope at the central dam and then went through a process of reconstruction and auscultation. The analyses were performed for the operating condition of the reservoir, with an established flow. A numerical model was developed based on the level readings of the reservoir water and their piezometric readings as a proposal for the evaluation and future behavior prediction of the dam on established flow conditions. The use of constitutive models with the aid of computer systems is reflected in a way to predict future risk situations so they can be prevented

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Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

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Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

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Category hierarchy is an abstraction mechanism for efficiently managing large-scale resources. In an open environment, a category hierarchy will inevitably become inappropriate for managing resources that constantly change with unpredictable pattern. An inappropriate category hierarchy will mislead the management of resources. The increasing dynamicity and scale of online resources increase the requirement of automatically maintaining category hierarchy. Previous studies about category hierarchy mainly focus on either the generation of category hierarchy or the classification of resources under a pre-defined category hierarchy. The automatic maintenance of category hierarchy has been neglected. Making abstraction among categories and measuring the similarity between categories are two basic behaviours to generate a category hierarchy. Humans are good at making abstraction but limited in ability to calculate the similarities between large-scale resources. Computing models are good at calculating the similarities between large-scale resources but limited in ability to make abstraction. To take both advantages of human view and computing ability, this paper proposes a two-phase approach to automatically maintaining category hierarchy within two scales by detecting the internal pattern change of categories. The global phase clusters resources to generate a reference category hierarchy and gets similarity between categories to detect inappropriate categories in the initial category hierarchy. The accuracy of the clustering approaches in generating category hierarchy determines the rationality of the global maintenance. The local phase detects topical changes and then adjusts inappropriate categories with three local operations. The global phase can quickly target inappropriate categories top-down and carry out cross-branch adjustment, which can also accelerate the local-phase adjustments. The local phase detects and adjusts the local-range inappropriate categories that are not adjusted in the global phase. By incorporating the two complementary phase adjustments, the approach can significantly improve the topical cohesion and accuracy of category hierarchy. A new measure is proposed for evaluating category hierarchy considering not only the balance of the hierarchical structure but also the accuracy of classification. Experiments show that the proposed approach is feasible and effective to adjust inappropriate category hierarchy. The proposed approach can be used to maintain the category hierarchy for managing various resources in dynamic application environment. It also provides an approach to specialize the current online category hierarchy to organize resources with more specific categories.

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Recently honeycomb meshes have been considered as alternative candidates for interconnection networks in parallel and distributed computer systems. This paper presents a solution to one of the open problems about honeycomb meshes—the so-called three disjoint path problem. The problem requires minimizing the length of the longest of any three disjoint paths between 3-degree nodes. This solution provides information on the re-routing of traffic along the network in the presence of faults.