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We describe a matrix-based visualization technique for algorithmically and visually comparing metrics in eye movement data. To reach this goal, a set of scanpath trajectories is first preprocessed andtransformedintoasetofmetricsdescribingcommonalitiesand differences of eye movement trajectories. To keep the generated diagrams simple, understandable, and free of visual clutter we visuallyencodethegenerateddatasetintothecellsofamatrix...
Massive Open Online Courses (MOOCs) offer the ability to educate large numbers of diverse learners who might not have access, time, or the financial resources necessary for more formal coursework. While some studies have focused primarily on understanding MOOC learners purely through their access rates to course materials, others have sought to understand learners through surveys. We combined these...
In this paper, we propose a scene clustering algorithm which uses straight line features. Scenes are represented as nodes in the graph, and each connectivity between nodes is calculated by a pre-trained vocabulary tree. By applying a spectral clustering algorithm to the constructed graph, the scenes are partitioned into k groups where k is determined by the proposed estimation method. Instead of using...
The flood of real time social data, generated by various social media applications and sensors, is enabling researchers to gain critical insights into important social modeling and analysis problems such as the evolution of social relationships and analysis of emergent social processes. However, current computational tools have to address the grand challenge of analyzing large and dynamic social networks...
The selection of a model for academic risk prediction systems is usually based on the global performance of the model. However, this global performance is not an important factor for the end-user of the system. For the end-user, the performance of the model for his or her specific case is the most important aspect of that model. Given that the model is usually selected at design time, the end-user...
Recent years, Vehicular ad hoc Network (VANET) attracts tremendous attention due to its broad application prospects. However, channel fading, frangible link, unstable network topology caused by vehicles' high mobility and strict requirements to the quality of service (QoS) have become major challenges of VANET. Many algorithms have been proposed to ensure a stable network topology and it has been...
Semi-supervised clustering is one of the most active research area in machine learning and pattern recognition, which can improve the performance of unsupervised clustering efficiently. This paper focuses on exploiting both the label information of a few labeled samples and the spatial distribution information of large amount of unlabeled samples. We proposed a new semi-supervised clustering method,...
In automatic videosurveillance system, the first step is the extraction of moving objects. In this work, we investigate a new approach for foreground-background segmentation by using a modified Codebook algorithm. This approach exploit the perceptual information to optimize the detection. It is an adaptive strategy which is proposed to to reduce the computational complexity of the foreground detection...
Hierarchical clustering has been well-studied in the community of machine learning. Hierarchical clustering algorithms are deterministic, stable, and do not need a pre-determined number of clusters as input. However, they are not scalable for very large data due to their non-linear complexity. In this paper, a new approach is proposed to reduce the complexity of Hierarchical Clustering, improve the...
Healthcare spending has been increasing in the last few decades. One of the main reasons for this increase is hospital readmissions, which is defined as a re-hospitalization of a patient after being discharged from a hospital within a short period of time. The excessive amount of money spent every year on hospital readmissions and the urge to enhance healthcare quality make reducing hospital readmissions...
Driven by the proliferation of data traffic and requirement of user experience improvement, mobile wireless network is evolving towards heterogeneous networks (HetNet). The telecom operator is experiencing unprecedented challenges on service maintenance and operational expenditure, which drives the demand for realizing automation in current heterogeneous networks. Cell outage detection is a functionality...
Wireless Sensor Network (WSN) is considered as one of the networks that are usually used in a harsh environment. In most cases, a WSN consists of a large number of sensor nodes, which are deployed in a particular environment for the gathering of information, and for sending it to a base station (BS). Usually, sensor nodes have limited energy resources since it is impossible to recharge and change...
This paper presents a distributed clustering algorithm, called DCEV, which constructs multi-hop clusters. DCEV places vehicles into non-overlapping clusters which have adaptive size based on their relative mobility. The cluster formation is based on a D-hop clustering scheme where each node selects its cluster head in at most D-hop distance. To create clusters, DCEV uses a new metric to let vehicles...
Fountain codes are a type of erasure codes which are characterized by their global acknowledgement and used as a solution to reduce the use of feedback channel as well as the number of transmissions and then minimize the energy consumption. With the multi-hop transmission, fountain codes raise the problem of overflow leading to a waste of energy, the most critical issue and the big challenge in the...
The traffic profile of future mobile networks is foreseen as becoming more variable both in time and among base stations (BSs) due to the widespread heterogeneity in applications and services. Dynamic time division duplex (TDD) has been recognized as an important enabler to cope with this traffic variability, especially in dense networks with many BSs and a small number of user equipments (UEs) served...
Cooperative localization has become a promising solution for location-enabled technologies in Wireless Sensor Networks (WSNs). However, it suffers from great energy consumption problem due to the energy-constrained characteristic of the networks. To alleviate this problem, we propose a cluster nodes selection strategy based on the Cramer-Rao lower bound (CRLB) for the cooperative localization algorithm...
The methodology of semantic clustering analysis of customer's text-opinions collection is developed. The author's version of the mathematical models of formalization and practical realization of short textual messages semantic clustering procedure is proposed, based on the customer's text-opinions collection Latent Semantic Analysis knowledge extracting method. An algorithm for semantic clustering...
When users search in Twitter, they are overloaded with a mass of microblog posts every time, which are not particularly informative and lack of meaningful organization. Therefore, it is helpful to produce a summarized tweet timeline about the topic. The tweet timeline generation is such a task aiming at selecting a small set of representative tweets to generate meaningful timeline. In this paper,...
Acne can lead to severe physical and psychological implications on chronic sufferers if not treated promptly and properly. Ramli et al. proposed a k-means cluster based algorithm to provide computer-assisted support for the manual grading of digital images. We propose an improved, automated, and more objective, grading method which involves optimizing the k-means clustering algorithm by identifying...
This paper presents a new procedure for software service selection based on clustering of software quality data accumulated during the service monitoring. Subtractive clustering is explored as efficient method for quality estimation. It was adapted to deal with the specificity of the selection task. Experimental results on real data web service monitoring are obtained and discussed to prove the proposed...
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