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Autonomous underwater vehicles (AUV) are important resources to be used in the oil exploration industry in deep waters as well as a platform for scanning devices used in open sea regions of difficult human access. This work aims to analyze through computer simulations the influence of marine currents on the maneuverability of a flatfish shaped AUV. The 3D realistic scale simulations were performed...
Of the examples of clonal competition for antigen among lymphocytes, the recently predicted “Memory anti-Naïve” phenomenon occurs when the challenging antigen is not identical to the priming, and will be consequently bound with lower avidity by preexisting memory cells. In this study we use computer modeling and a systematic schedule of viral injections to disentangle the complex relationship between...
Deep neural networks (DNNs) have made impressive improvements for predictive modeling in various fields. Successful network building for predictive tasks usually requires abundant data, for effectively learning high-level, non-additive information from raw input features. The merit of high-level learning makes DNN promising in clinical research, but the need for abundant data hampers DNN applications...
In this paper, we consider the use of structure learning methods for probabilistic graphical models to identify statistical dependencies in high-dimensional physical processes. Such processes are often synthetically characterized using PDEs (partial differential equations) and are observed in a variety of natural phenomena. In this paper, we present ACLIME-ADMM, an efficient two-step algorithm for...
This research aims at validating the vital factors that affecting the continuous use of cloud computing services through literature review and experts' evaluation. These factors are factors that have an effect on the decision makers to forge ahead in the use of cloud computing services in their various organizations. Semi-structured interviews using email were carried out with twenty-three experts...
Besides the text content, documents and their associated words usually come with rich sets of meta information, such as categories of documents and semantic/syntactic features of words, like those encoded in word embeddings. Incorporating such meta information directly into the generative process of topic models can improve modelling accuracy and topic quality, especially in the case where the word-occurrence...
The hashtag recommendation problem addresses recommending (suggesting) one or more hashtags to explicitly tag a post made on a given social network platform, based upon the content and context of the post. In this work, we propose a novel methodology for hashtag recommendation for microblog posts, specifically Twitter. The methodology, EmTaggeR, is built upon a training-testing framework that builds...
The prevalence of bridging defects makes bridging fault models important to consider during fault simulation and test generation. The large number of bridging faults that can be defined for a circuit led to the development of procedures for selecting subsets of bridging faults that are likely to occur based on the circuit layout, and hard-to-detect bridging faults whose coverage provides a more effective...
Network Planning and Fault Location, Isolation and Supply Restoration (FLISR) are important functions of power distribution automation systems. We model these functions as a combinatorial optimization graph problem called the Capacitated Spanning Forest Problem (CSF), defined as the problem of creating a spanning forest with a capacity constraint on each tree bounding its total weight. We present...
We study the problem of approximating the partition function of the ferromagnetic Ising model in graphs and hypergraphs. Our first result is a deterministic approximation scheme (an FPTAS) for the partition function in bounded degree graphs that is valid over the entire range of parameters β (the interaction) and λ (the external field), except for the case |λ|=1 (the...
Heart sounds are difficult to interpret because a) they are composed by several different sounds, all contained in very tight time windows; b) they vary from physiognomy even if the show similar characteristics; c) human ears are not naturally trained to recognize heart sounds. Computer assisted decision systems may help but they require robust signal processing algorithms. In this paper, we use a...
Stackelberg security games are represented by a Stackelberg model for multiple defenders and attackers. The dynamics of the game involves defenders trying to allocate their limited resources to defend important targets, and attackers observing the behavior of the defenders, look for the most advantageous target to harm. The computation of the equilibrium point is a fundamental issue for Stackelberg...
With the rapid growth of Cloud Computing technologies, enterprises are increasingly deploying their services in the Cloud. Dynamically priced cloud resources such as the Amazon EC2 Spot Instance provides an efficient mechanism for cloud service providers to trade resources with potential buyers using an auction mechanism. With the dynamically priced cloud resource markets, cloud consumers can buy...
In this work we discuss how useful Kalman Temporal Difference (KTD) is for the purpose of improvement of multiple model learning. By KTD we mean a learning framework by combining Kalman Filters and Temporal Difference (TD) to enhance multi-agent environment. In this approach, we have to attack dependency issues against initialization parameters: the results (quality and efficiency) heavily depend...
This paper presents a recursive oblique projector using the Gram-Schmidt process. The recursive construction of oblique projectors allows a receiver to prevail interference and noise environment in direct-sequence code-division multiple-access (DS/CDMA) system. When the number of the interfering users in the system increases or decreases, the oblique projector is recursively updated by the proposed...
Learning styles have been used to explain students' differences in approaching their learning, but there are still deficiencies in interpreting the results of their application, and there are authors that indicate that there are no elements that support their credibility in achievement-based education. For this reason, we proposed a methodology to analyze the results obtained after the application...
The celebrated Time Hierarchy Theorem for Turing machines states, informally, that more problems can be solved given more time. The extent to which a time hierarchy-type theorem holds in the classic distributed LOCAL model has been open for many years. In particular, it is consistent with previous results that all natural problems in the LOCAL model can be classified according to a small constant...
In this paper, we propose a computational modeling method to investigate head-eye coordination in face-to-face behavior. The method looks into probability density of individuals' head orientation during looking at others' face. We conducted experiment under two different scenarios in human-human interaction. Under each scenario, individuals' head orientation could be fitted with one Gaussian distribution...
E-learning is the application of IT and Internet in education to make it easier, spacious, and more efficient. Advantages of e-learning are recognized, but its impact on learning achievement and knowledge transferring are not confirmed clearly. Learning is considered the skills of students and knowledge gained through experience in the training process. Learning achievement has been defined as students'...
The selection of an appropriate sequence of activities is an essential task to keep student motivation and foster engagement. Usually, decisions in this respect are made by taking into account the difficulty of the activities, in relation to the student's level of competence. In this paper, we present a dynamic model that aims to predict the average performance of a group of students at solving a...
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