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This article includes the details of the experiment conducted at the University of the Balearic Islands related to organize a hackathon which involves interdisciplinary, Service-learning and enterprise internship. The goal of the activity is to increase the student motivation and their knowledges and skills. Results are analysed through post-test surveys.
Computers cause an impact in almost every single aspect of our lives, however, unfortunately, schools have not been able to keep up with this irreversible evolution. The simple use of technological apparatuses in the classroom does not guarantee the improvement of the learning process, however it can be the medium through which the students find the alternatives for the solution of complex problems...
In order to be able to successfully defend an IT system it is useful to have an accurate appreciation of the cyber threat that goes beyond stereotypes. To effectively counter potentially decisive and skilled attackers it is necessary to understand, or at least model, their behavior. Although the real motives for untraceable anonymous attackers will remain a mystery, a thorough understanding of their...
An important and widespread topic in cloud computing is text analyzing. People often use topic model which is a popular and effective technology to deal with related tasks. Among all the topic models, sLDA is acknowledged as a popular supervised topic model, which adds a response variable or category label with each document, so that the model can uncover the latent structure of a text dataset as...
The imbalanced learning problem is becoming pervasive in today's data mining applications. This problem refers to the uneven distribution of instances among the classes which poses difficulty in the classification of rare instances. Several undersampling as well as oversampling methods were proposed to deal with such imbalance. Many undersampling techniques do not consider distribution of information...
Class imbalance is a common problem in defect prediction data sets. In order to cope with this problem, over-sampling and under sampling methods are employed. However, these methods are designed for instance based alteration and not specialized for feature space. Also there is not any distinctive approach to cope with class imbalance in defect prediction data sets. We develop HSDD (hybrid sampling...
Simulation Balancing is an optimization algorithm to automatically tune the parameters of a playout policy used inside a Monte Carlo Tree Search. The algorithm fits a policy so that the expected result of a policy matches given target values of the training set. Up to now it has been successfully applied to Computer Go on small 9 × 9 boards but failed for larger board sizes like 19 × 19. On these...
Persons are often asked to provide information about themselves. These data are very heterogeneous and result in as many “profiles” as contexts. Sorting a large amount of profiles from different contexts and assigning them back to a specific individual is quite a difficult problem. Semantic processing and machine learning are key tools to achieve this goal. This paper describes a framework to address...
In order to improve the quality of graduate dissertation and examine the quality of graduate education, the mechanism of graduate dissertation random inspection evaluation in Shanghai has been operated for more than ten years. Evaluation experts evaluate the quality of dissertation by using subitem evaluation method rather than comprehensive evaluation method to reduce the risk of misjudgment. Decision...
In recent years, computer system capability training becomes an important research issue for teaching reforms of computer major. This paper propose a new system ability training scheme via analyzing the existing reform methods. By establishing core courses and optimizing experimental teaching system, our reform completes the teaching target that let undergraduate students to develop a CPU, an operating...
Feature selection aims to seek some relevant features from the whole feature space to construct a feature subset and it can help us to handle clustering, classification and retrieval. This paper considers feature selection for text categorization. We put forward a filter feature selection scheme based on class difference measure. The key idea of our proposed algorithm is difference between the frequencies...
Melanoma, most threatening type of skin cancer, is on the rise. In this paper an implementation of a deep-learning system on a computer server, equipped with graphic processing unit (GPU), is proposed for detection of melanoma lesions. Clinical (non-dermoscopic) images are used in the proposed system, which could assist a dermatologist in early diagnosis of this type of skin cancer. In the proposed...
Class imbalance is a common problem in defect prediction data sets. In order to cope with this problem, over- sampling and undersampling methods are employed. However, these methods are designed for instance based alteration and not specialized for feature space. Also there is not any distinctive approach to cope with class imbalance in defect prediction data sets. We develop HSDD (hybrid sampling...
Postural instability affects a large number of people and can compromise even simple activities of the daily routine. Therapies for balance training can strongly benefit from auxiliary devices specially designed for this purpose. In this paper, we present a system for balance training that uses the metaphor of a game, what contributes to the motivation and engagement of the patients during a treatment...
Feature selection is a major pre-processinş technique which aims to pick out distinctive features from whole dataset. In this way it is intended to reduce computational cost o the classification process. Artificial Bee Colony (ABC) algorithm is an evolutionary based swarm intelligence optimization method In this study, some of the variants of binary ABC algorithms are implemented to the feature selection...
‘Ecole-Numerique’ or Digital Schooling has become an emerging trend for primary schooling worldwide. This paper attempts to assess the readiness of educators and schools in the migration from “Informatique” to “ÉcoleNumerique” for young learners at primary levels. A case study was drawn from two french private schools X and Y in Mauritius. To achieve this aim, the TAM model was adapted as guideline...
The aim of this presentation is to show how various ideas coming from the nonlinear stability theory of functional differential systems, stochastic modeling, and machine learning, can be put together in order to create an approximating model that explains the working mechanisms behind a certain type of reservoir computers. Reservoir computing is a recently introduced brain-inspired machine learning...
To facilitate self-monitoring interventions developed by the Faculty of Computer Science, Universitas Indonesia, a web-based self-monitoring tool was created. This study aims to evaluate the tool's usability and the user experience prior to its wide adoption. The User Experience Questionnaire and the System Usability Scale were used to evaluate the self-monitoring tool. The tool was used in a Human-Computer...
As the attackers nowadays are getting craftier it is deemed important to have a security system which is easy to maintain and economically affordable and gives suitable defense against attacks both known and novel. In this paper, the concept of genetic programming is applied to recreate open network conditions, using records obtained from KDD Cup'99 dataset. Then the newly created records (network...
Handwriting disability is one type of learning disability that is difficult to be detected as it may requires experts and professionals to diagnose. Owing to this matter, a computerized character recognition application is very much in need to ease the process of detecting children with learning disability based on handwriting. For any character recognition method, it's critical to extract the class...
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