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This paper provides an example of using genetic programming for engendering computational creativity in computer generated forces, i.e. simulated entities used to represent own, opponent and neutral forces in military training or decision support applications. We envision that applying computational creativity in the development of computer generated forces may not only reduce development costs but...
This paper presents a data-driven approach towards the modeling of agent behaviors in a full-fledged, commercial off-the-shelf simulation milieu for tactical military training. The modeling approach employs machine learning to identify behavioral rules and patterns in data. Potential advantages of this approach are that it may improve modeling efficiency and, perhaps more importantly, increase the...
Convolutional Neural Networks (CNN) are on the forefront of accurate character recognition. This paper explores CNNs at their maximum capacity by implementing the use of large datasets. We show a near-perfect performance by using a dataset of about 820,000 real samples of isolated handwritten digits, much larger than the conventional MNIST database. In addition, we report a near-perfect performance...
Axial and radial power peaking factors (Fq, Fah) were estimated in Chashma Nuclear Power Plant Unit-1 (C-1) core using artificial Neural Network Technique (ANNT). Position of T4 control bank, axial offsets in four quadrants and quadrant power tilt ratios were taken as input variables in neural network designing. Power Peaking Factors (PPF) were calculated using computer codes FCXS, TWODFD and 3D-NB-2P...
This paper tries to present authors vision on how to transmit knowledge to the current generation of students, using technologies and new methods, so that the future graduates knows how to think and to solve problems, how to propose and implement projects, not only to read and memories what they read without understanding anything. More than that authors try to suggest ideas to help future graduates...
Many theoretical and empirical studies that analyze the factors associated to academic achievement identify gender as a highly significant element. Within the assessment of information literacy skills, the effect of gender seems apparent. However, the contextual nature of gender makes it difficult for the results of the studies to result in specific improvements and innovations in the schools. The...
Decision trees are common algorithms in machine learning. Traditionally, these algorithms make trees recursively and at each step, they inspect data to induce the part of the tree. However decision trees are famous for their instability and high variance in error. In this paper a solution which adds error correction rule to a traditional decision tree algorithm is examined. In fact an algorithm which...
The purpose of this work is to evaluate possible minimisation of the time needed for expansion of the scope of a CNN (convolutional neural network) classifier without the need to fully re-train it. We investigate the effects of applying k-NN (k-Nearest Neighbours) based classification and transfer learning (via fine-tuning) for the purpose of adding new classes to an existing deep convolutional neural...
Information and communication technologies play an increasingly important role in society, in the sense that all areas and professions make use of digital resources. The school can not be brushed off this reality, aim to create full subjects and integrated in society today. Educational software can be used very early in the education of children, but they must be carefully and monitoring. This article...
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...
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