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Pupillary behaviour and dilation have been considered in the literature as an effective input for the measurement of cognitive workload and stress. In this work, we explore the correlation between pupil dilation and features extracted from low quality video frames that have been captured using a normal webcam during a set of computer-based tasks. The methodology presented herein attempts to develop...
In this paper, a novel firefly algorithm (FA) is presented to reduce the dependency on parameters. The new FA algorithm is called dynamic step factor based FA (DSFFA), in which the step factor is not fixed and it is dynamically updated during the evolution. Experimental study on several classical benchmark functions show that DSFFA is superior to the basic FA and three other FAs.
Deep learning is a hot research topic at home and abroad. In view of the massive 3D model data, a 3D model identification method based on topographic sparse coding is proposed. Firstly, the 3D model is projected to get its three views, and the feature vector is used as the training sample. A complete dictionary is constructed by using the greedy algorithm to train the dictionary, which makes the normal...
We present a distributed and asynchronous versioning mechanism (DAVM) in this paper to identify consistent replicas for each encoding block in BW-RAID, which uses "mirroring and RAID4" encoding scheme to improve the system performance and disk space utilization. DAVM has three advantages: Firstly, it is distributed and asynchronous in management. Secondly, it is correct and workable in any...
An algorithm of sound source localization using range differences of arrival and energy ratios of arrival is proposed. This algorithm can localize the sound source using only two or three microphones. The problem is converted into a nonlinear least square optimization problem, which is solved by Levenberg-Marquardt method. The performance of this algorithm against noise is analyzed in this paper.
The DIBR is a novel technology used for generating virtual views has been widely used recently. However, due to imperfect depth maps, annoying artifacts appear in the virtual view images. To generate high quality intermediate virtual view images, this paper proposes a spatial weighting based interpolation method. The weighted average of mapped pixels near the integer pixel is adopted as the final...
The availability of modern technologies depends on the intellectual property licensing transactions. Patent pools, in particular, have emerged as important tools for organizing licensing activities. Traditionally, a patent pool aggregates the patents necessarily to practice a technology and avoids the transactional cost of separately negotiating licenses with multiple patent holders. More recently,...
Campaigns with commercial and spam purposes have flooded the Twitter community. To understand what scale of audience a campaign could reach, we first perform a measurement study by collecting a dataset of about 10 million tweets via streaming API and one million search tweets for targeting topics, as well as 37,313 user accounts that are suspended by Twitter. From the dataset, we extract a spam campaign...
MIMO techniques can significantly improve the diversity gain and spectrum utilization. Physical-layer Network Coding (PNC) is also a new technique to increase the spectrum utilization of wireless networks. The novel VBLAST PNC scheme combined these two techniques to improve the performance further. In this paper, we analyze the Bit Error Rate (BER) performance of the new scheme based on QPSK modulation...
A novel approach to detect vehicles in night outdoor scenes is proposed in this paper. By using online subspace learning, the preliminary foreground is obtained based on spatio-temporal bricks. Meanwhile, a new operator named 3DLBP is proposed to describe the local features of bricks. The final foreground is acquired by region-grow with 3DLBP and preliminary foreground. The results of experiment indicate...
Under-segmentation of an image with multiple objects is a common problem in image segmentation algorithms. This paper presents a novel approach for the splitting of clumps formed by multiple objects due to under-segmentation. The algorithm includes two steps: finding a pair of points for clump splitting, and joining the pair of selected points. In the first step, a pair of points for splitting is...
The fundamental problem in robotic exploration and mapping of an unknown environment is answering the question ‘have I been here before?’, which involves disambiguating the robot's current location from previously visited or known locations. One approach to answering this problem in embedded topological worlds is to resort to the use of an external aid that can help the robot disambiguate places....
It is a common sense that drowsiness during driving could cause traffic accidents. Related researches show that drowsiness occurs when the parasympathetic nerve system predominates over others, and the high frequency (HF) component of heart rate variability (HRV) on an electrocardiogram (ECG) is closely related with the parasympathetic nerve activity, so it is reasonable to evaluate drowsiness based...
Literature and folklore is rife with a range of oracles that have been used by explorers to explore unknown environments. But how effective are these various oracles? This paper considers the power of string and string-like oracles to map an unknown embedded topological environment. We demonstrate that for undirected graphs, even very short strings can be used to explore an unknown environment but...
In this paper, we propose a novel method to adaptively apply shape prior in graph cut segmentation. By incorporating shape priors in an adaptive way, we introduce a robust way to harness shape prior in graph cut segmentation. Since traditional graph cut approaches with shape prior may fail in cases where parameters for shape prior term are not set appropriately, incorporation of shape priors adaptively...
Affinity propagation (AP) is a new powerful clustering algorithm based message passing between data points. One of the major problems in clustering is the determination of the optimal number of clusters. In this paper, we propose a new approach called Affinity Propagation Clustering based Particle Swarm Optimization (PSO-AP), which using Particle Swarm Optimization (PSO) algorithm to determination...
The availability of large volumes of Semantic Web data has created the potential of discovering vast amount of knowledge, among which semantic relation discovery fundamentally changes the way we acquire and use knowledge. Due to the decentralized and distributed nature of Semantic Web development, semantic data tend to be created and stored independently in different organizations; under such circumstances,...
In this paper a scalability test over eleven scalable benchmark functions, provided by the current workshop (Evolutionary Algorithms and other Metaheuristics for Continuous Optimization Problems-A Scalability Test), are conducted for accelerated DE using generalized opposition-based learning (GODE). The average error of the best individual in the population has been reported for dimensions 50, 100,...
Since many differences may arise in cognition, abstraction and representation during multi-scale road network compositive modeling, this paper proposes an hierarchical ontology-based multi-scale entity-Relation modeling strategy, it considers ontology integration from the bottom level-general ontology in geographical science, to task ontology for road network features cognition, definition,abstraction,...
XML documents are tree-structured, and measuring the similarity of such tree structures plays a key role in XML clustering. In order to maximally capture common information for XML clustering, this paper investigates a novel similarity measurement - counting all common embedded subtrees of two trees, and its use for discovering latent hierarchical information for XML clustering. An efficient dynamic...
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