12 resultados para Computational tools
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
Logic courses represent a pedagogical challenge and the recorded number of cases of failures and of discontinuity in them is often high. Amont other difficulties, students face a cognitive overload to understand logical concepts in a relevant way. On that track, computational tools for learning are resources that help both in alleviating the cognitive overload scenarios and in allowing for the practical experimenting with theoretical concepts. The present study proposes an interactive tutorial, namely the TryLogic, aimed at teaching to solve logical conjectures either by proofs or refutations. The tool was developed from the architecture of the tool TryOcaml, through support of the communication of the web interface ProofWeb in accessing the proof assistant Coq. The goals of TryLogic are: (1) presenting a set of lessons for applying heuristic strategies in solving problems set in Propositional Logic; (2) stepwise organizing the exposition of concepts related to Natural Deduction and to Propositional Semantics in sequential steps; (3) providing interactive tasks to the students. The present study also aims at: presenting our implementation of a formal system for refutation; describing the integration of our infrastructure with the Virtual Learning Environment Moodle through the IMS Learning Tools Interoperability specification; presenting the Conjecture Generator that works for the tasks involving proving and refuting; and, finally to evaluate the learning experience of Logic students through the application of the conjecture solving task associated to the use of the TryLogic
Resumo:
LEÃO, Adriano de Castro; DÓRIA NETO, Adrião Duarte; SOUSA, Maria Bernardete Cordeiro de. New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM). Computers in Biology and Medicine, v. 39, p. 853-859, 2009
Resumo:
In this paper artificial neural network (ANN) based on supervised and unsupervised algorithms were investigated for use in the study of rheological parameters of solid pharmaceutical excipients, in order to develop computational tools for manufacturing solid dosage forms. Among four supervised neural networks investigated, the best learning performance was achieved by a feedfoward multilayer perceptron whose architectures was composed by eight neurons in the input layer, sixteen neurons in the hidden layer and one neuron in the output layer. Learning and predictive performance relative to repose angle was poor while to Carr index and Hausner ratio (CI and HR, respectively) showed very good fitting capacity and learning, therefore HR and CI were considered suitable descriptors for the next stage of development of supervised ANNs. Clustering capacity was evaluated for five unsupervised strategies. Network based on purely unsupervised competitive strategies, classic "Winner-Take-All", "Frequency-Sensitive Competitive Learning" and "Rival-Penalize Competitive Learning" (WTA, FSCL and RPCL, respectively) were able to perform clustering from database, however this classification was very poor, showing severe classification errors by grouping data with conflicting properties into the same cluster or even the same neuron. On the other hand it could not be established what was the criteria adopted by the neural network for those clustering. Self-Organizing Maps (SOM) and Neural Gas (NG) networks showed better clustering capacity. Both have recognized the two major groupings of data corresponding to lactose (LAC) and cellulose (CEL). However, SOM showed some errors in classify data from minority excipients, magnesium stearate (EMG) , talc (TLC) and attapulgite (ATP). NG network in turn performed a very consistent classification of data and solve the misclassification of SOM, being the most appropriate network for classifying data of the study. The use of NG network in pharmaceutical technology was still unpublished. NG therefore has great potential for use in the development of software for use in automated classification systems of pharmaceutical powders and as a new tool for mining and clustering data in drug development
Resumo:
The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main types of examinations for the diagnosis of dermatological illnesses of the skin. The field that involves the use of computational tools to help or follow medical diagnosis in dermatological injuries is seen as very recent. Some methods had been proposed for automatic classification of pathology of the skin using images. The present work has the objective to present a new intelligent methodology for analysis and classification of skin cancer images, based on the techniques of digital processing of images for extraction of color characteristics, forms and texture, using Wavelet Packet Transform (WPT) and learning techniques called Support Vector Machine (SVM). The Wavelet Packet Transform is applied for extraction of texture characteristics in the images. The WPT consists of a set of base functions that represents the image in different bands of frequency, each one with distinct resolutions corresponding to each scale. Moreover, the characteristics of color of the injury are also computed that are dependants of a visual context, influenced for the existing colors in its surround, and the attributes of form through the Fourier describers. The Support Vector Machine is used for the classification task, which is based on the minimization principles of the structural risk, coming from the statistical learning theory. The SVM has the objective to construct optimum hyperplanes that represent the separation between classes. The generated hyperplane is determined by a subset of the classes, called support vectors. For the used database in this work, the results had revealed a good performance getting a global rightness of 92,73% for melanoma, and 86% for non-melanoma and benign injuries. The extracted describers and the SVM classifier became a method capable to recognize and to classify the analyzed skin injuries
Resumo:
Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated
Resumo:
The use of non-human primates in scientific research has contributed significantly to the biomedical area and, in the case of Callithrix jacchus, has provided important evidence on physiological mechanisms that help explain its biology, making the species a valuable experimental model in different pathologies. However, raising non-human primates in captivity for long periods of time is accompanied by behavioral disorders and chronic diseases, as well as progressive weight loss in most of the animals. The Primatology Center of the Universidade Federal do Rio Grande do Norte (UFRN) has housed a colony of C. jacchus for nearly 30 years and during this period these animals have been weighed systematically to detect possible alterations in their clinical conditions. This procedure has generated a volume of data on the weight of animals at different age ranges. These data are of great importance in the study of this variable from different perspectives. Accordingly, this paper presents three studies using weight data collected over 15 years (1985-2000) as a way of verifying the health status and development of the animals. The first study produced the first article, which describes the histopathological findings of animals with probable diagnosis of permanent wasting marmoset syndrome (WMS). All the animals were carriers of trematode parasites (Platynosomum spp) and had obstruction in the hepatobiliary system; it is suggested that this agent is one of the etiological factors of the syndrome. In the second article, the analysis focused on comparing environmental profile and cortisol levels between the animals with normal weight curve evolution and those with WMS. We observed a marked decrease in locomotion, increased use of lower cage extracts and hypocortisolemia. The latter is likely associated to an adaptation of the mechanisms that make up the hypothalamus-hypophysis-adrenal axis, as observed in other mammals under conditions of chronic malnutrition. Finally, in the third study, the animals with weight alterations were excluded from the sample and, using computational tools (K-means and SOM) in a non-supervised way, we suggest found new ontogenetic development classes for C. jacchus. These were redimensioned from five to eight classes: infant I, infant II, infant III, juvenile I, juvenile II, sub-adult, young adult and elderly adult, in order to provide a more suitable classification for more detailed studies that require better control over the animal development
Resumo:
The use of technology tools for teaching and learning has grown increasingly in our daily life. In this context, a branch that has had tremendous growth is the area of teaching and learning language through computational tools. The study of CALL (Computer Assisted Language Learning), accomplished in this research, aims to evaluate existing tools in this context, focused specifically on the Japanese language; and from this study, accomplish the development of a new computational tool that can assist teaching/learning of the Japanese language. As results, we present a wide survey on the subject in various technologies/devices, as well as the complete development process of a new tool, the Karuchā Ships Invaders game, that proposes to teach basic concepts of the language, blended with entertainment, and still, focusing on the Brazilian students of Japanese language audience. We will present all the concept phases of the game and its evolution through the research, as well as an interface evaluation. Still, we present proposal and validation of a method to evaluate motivational aspects of computational tools with educational focus, and results extracted from an experiment accomplished with prospective users
Resumo:
Geographic Information System (GIS) are computational tools used to capture, store, consult, manipulate, analyze and print geo-referenced data. A GIS is a multi-disciplinary system that can be used by different communities of users, each one having their own interest and knowledge. This way, different knowledge views about the same reality need to be combined, in such way to attend each community. This work presents a mechanism that allows different community users access the same geographic database without knowing its particular internal structure. We use geographic ontologies to support a common and shared understanding of a specific domain: the coral reefs. Using these ontologies' descriptions that represent the knowledge of the different communities, mechanisms are created to handle with such different concepts. We use equivalent classes mapping, and a semantic layer that interacts with the ontologies and the geographic database, and that gives to the user the answers about his/her queries, independently of the used terms
Resumo:
The northern coast of Rio Grande do Norte State (RN) shows areas of Potiguar basin with high activity in petroleum industry. With the goal of avoiding and reducing the accident risks with oil it is necessary to understand the natural vulnerability, mapping natural resources and monitoring the oil spill. The use of computational tools for environmental monitoring makes possible better analyses and decisions in political management of environmental preservation. This work shows a methodology for monitoring of environment impacts, with purpose of avoiding and preserving the sensible areas in oil contact. That methodology consists in developing and embedding an integrated computational system. Such system is composed by a Spatial Decision Support System (SDSS). The SDSS shows a computational infrastructure composed by Web System of Geo-Environmental and Geographic Information - SWIGG , the System of Environmental Sensibility Maps for Oil Spill AutoMSA , and the Basic System of Environmental Hydrodynamic ( SisBAHIA a System of Modeling and Numerical Simulating SMNS). In a scenario of oil spill occurred coastwise of Rio Grande do Norte State s northern coast, the integration of such systems will give support to decision agents for managing of environmental impacts. Such support is supplied through a system of supporting to spatial decisions
Resumo:
This paper presents a study of the integration of filters and microstrip antennas, yielding devices named as filtennas for applications in wireless communications systems. The design of these structures is given from the observation of filtennas based integration between horn antennas and frequency selective surfaces (FSS), used in the band X. The choice of microstrip line structures for the development of a new configuration filtennas justifies the wide application of these transmission lines, in recent decades, always resulting in the production of circuit structures with planar light-weight, compact size, low cost, easy to construct and particularly easy to integrate with other microwave circuits. In addition, the antenna structure considered for the composition of filtennas consists of a planar monopole microstrip to microstrip filters integrated in the feed line of the antenna. In particular, are considered elliptical monopole microstrip (operating in UWB UWB) microstrip filters and (in structures with associated sections in series and / or coupled). In addition, the monopole microstrip has a proper bandwidth and omnidirectional radiation pattern, such that its integration with microstrip filters results in decreased bandwidth, but with slight changes in the radiation pattern. The methods used in the analysis of monopoles, and filters were filtennas finite elements and moments by using commercial software Ansoft Designer and HFSS Ansoft, respectively. Specifically, we analyze the main characteristics of filtennas, such as radiation pattern, gain and bandwidth. Were designed, constructed and measures, several structures filtennas, for validation of the simulated results. Were also used computational tools (CAD) in the process of building prototypes of planar monopoles, filters and filtennas. The prototypes were constructed on substrates of glass-fiber (FR4). Measurements were performed at the Laboratory for Telecommunications UFRN. Comparisons were made between simulated and measured, and found good agreement in the cases considered
Resumo:
The integration between architectural design and structur al systems consi sts, in academic education, one of the main challenges to the architectural design education . Recent studies point to the relevance of the use of computational tools in academic settings as an important strategy for such integration. Although in recent yea rs teaching experience using BIM (BuildingInformationModeling) may be incorporated by the a rchitecture schools , notes the need for further didactic and pedagogical practices that promote the architectural design and structur al integration teaching. This pa per analyzes experiences developed within the UFRN and UFPB, seeking to identify tools, processes and products used, pointing limitations and potentials in subjects taught in these institutions. The research begins with a literature review on teaching BIM and related aspects to the integration of architectural design and stru c tur e . It has been used as data collection techniques in studio the direct observation, the use of questionnaires and interviews with students and teachers, and mixed method, qualitativ e and quantitative analysis . In UFRN, the scope of the Integrated Workshop as a compulsory subject in the curriculum, favors the integration of disciplines studied here as it allows teachers from different disciplines at the same project studio . Regarding the use of BIM form initial users, BIM modelers, able to extract quantitative and automatically speed up production, gaining in quality in the products, however learn the tool and design in parallel cause some difficulties. UFPB, lack of required courses o n BIM, generates lack of knowledge and confidence in using the tool and processes, by most students. Thus we see the need for greater efforts by school to adopt BIM skills and training. There is a greater need for both BIM concept, in order to promote BIM process and consequent better use of tools, and obsolete avoiding impairment of technology, merely a tool. It is considered the inclusion of specific subjects with more advanced BIM skills, through partnerships with engineering degrees and the promotion of trans disciplinary integration favoring the exchange of different cultures from the academic environment.
Resumo:
LEÃO, Adriano de Castro; DÓRIA NETO, Adrião Duarte; SOUSA, Maria Bernardete Cordeiro de. New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM). Computers in Biology and Medicine, v. 39, p. 853-859, 2009