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Aiming at reducing the user memory burden , a method is proposed that started with the multi-semantics of the same gesture , and was based on Gaussian statistical model for gesture semantic classification.After implementing the cognitive observation and experiment , a flexible mapping algorithm from gesture to semantics and using Gaussian statistical model was proposed . The main innovations of this...
Various researches on criminology provides us with a key piece of information about criminal psychology that, a criminal doesn't hover around unknown territory rather they commit crimes when opportunity provides in a concentrated or familiar area i.e. hotspots. So, a crime predicting model can be simulated using crime pattern theory which can analyze verified past crime data and predict future criminal...
Multiple-partite networks exist in the real world, such as engineering constructions consisted of workers and machines. We build up random multiple-partite network models and show their topological properties by means of well-known methods appeared in the Barabási-Albert model. We find some new characters of the Barabási-Albert model and BA-type models, and show a connection between the degree distribution...
Planetary rovers navigate in extreme environments for which a Global Positioning System (GPS) is unavailable, maps are restricted to relatively low resolution provided by orbital imagery, and compass information is often lacking due to weak or not existent magnetic fields. However, an accurate rover localization is particularly important to achieve the mission success by reaching the science targets,...
In the paper the novel feature selection method, using wrapper model and ensemble approach, is presented. In the proposed method features are selected dynamically, i.e. separately for each classified object. First, a set of identical one-feature classifiers using different single feature is created and next the ensemble of features (classifiers) is selected as a solution of optimization problem using...
The evolution of cooperation in social dilemmas has always been a subject of considerable concern in various fields, such as economics, sociobiology and social science. Previous studies have shown that reputation can sustain cooperation in multi-player public goods games through indirect reciprocity. Unfortunately, most studies only consider the impact of personal performance, and while the effect...
The recently introduced DeepIR model is proven effective for text classification [1]. In this paper, a modified DeepIR model is proposed by introducing a new document probability. This probability employs composite log likelihood method. An experiment using the modified DeepIR model is conducted on five text classification data sets. The proposed model shows considerable improvements in multi-class...
In power system reliability evaluation, one of the basic data needed is the transition rates between various states of components such as generators, transmission lines and circuit breakers. These data are used to build the transition rate matrix for the components which can then be used to find state probabilities and interstate frequencies. There are some situations when a transition rate matrix...
Time is a good scale for a microblog search. The traditional retrieval model only uses content to query microblog information. Many studies thought that the relevant microblogs most likely appear when it is close to the instant time of query. Through an analysis of microblog data, people find that the relevant information in microblogs possibly appears when it is far from the query time. These two...
Applying language model in lip-reading system can greatly improve the recognition rate. But the traditional statistical language model depended on corpus excessively, so it could not be used in some special occasions with a small vocabulary corpus. In this paper, according to fuzzy mathematical theory, the fuzzy evaluation sets were firstly established. Then the frequencies of words or sentences in...
At recent time, the statistical based language model and neural based language model are still dominating the researches in the field of machine translation. The statistical based machine translation today is the fastest one but it has a weakness in term of accuracy. In contrast, the neural based network has higher accuracy but has a very slow computation process. In this research, a comparison between...
Software-defined networking (SDN) has emerged as one of the future internet technologies. It separates the control plane and the data plane, keeping the data plane simple by assigning the complex computing to the control plane. Active queue management (AQM) has been researched to obtain lower delay and higher throughput. It is noteworthy to have these advantages in SDN. To bring AQM to SDN without...
Efficient spectrum utilization by secondary users (SU) during the inactivity phase of primary users (PU) is of utmost interest for dynamic spectrum access in a cognitive radio environment. In this paper, we investigate the utilization efficiency of cognitive radio users with respect to the realistic estimate of PU duty cycle (DC) in AWGN and generalized κ-µ fading channels for a fixed interference...
Multilabel categorization, which is more difficult but practical than the conventional binary and multiclass categorization, has received a great deal of attention in recent years. This paper proposes a novel probabilistic generative model, label correlation mixture model (LCMM), to depict the multiply labeled documents, which can be used for multilabel spoken document categorization as well as multilabel...
Early warning and intelligent decisions have proved to be important tools to handle the unprecedented events (wildcards) that might emerge in the future. Relying on forecasting techniques only are not enough to shape the future, since they depend only on the historical shape and they generate one image of the future. The Futures Methodologies are capable of overcoming the constraints imposed on the...
This paper focuses on the suitability of three different null-models to motif analysis that all get as an input a desired degree sequence. A graph theoretic null-model is defined as a set of graphs together with a probability function. Here we discuss the configuration model, as the simplest model; a variant of the configuration model where multi-edges are deleted; and the set of all graphs with a...
Often in marketing, political campaigns and social media, two competing products or opinions propagate over a social network. Studying social influence in such competing cascades scenarios enables building effective strategies for maximizing the propagation of one process by targeting the most "influential" nodes in the network. The majority of prior work however, focuses on unsigned networks...
This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labeled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models...
We present and analyze an Electric Vehicle (EV) charging management model for a fast charging station network in a smart grid environment. The proposed model considers a charging station network that provides service to multiple EV charging-classes. The basic feature of the proposed model is when EVs are blocked by their preferred station due to the unavailability of charging outlets, they are prompted...
Terrain-Relative Navigation (TRN) is a technique for localizing a vehicle in GPS-denied environments. TRN augments a dead-reckoned solution with continuous position fixes based on correlations with a pre-stored map. In underwater applications TRN accuracy on the order of 3m has been demonstrated, however convergence to incorrect solutions has been observed when operating for extended periods over...
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