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Whole brain tractography generates a very huge dataset composed by various tracts of different shapes, lengths, positions. Then clustering them into anatomically meaningful bundles is a challenge. Until now, several clustering methods have been proposed such as methods based on similarity measures or methods based on anatomical information, but no optimal clustering criteria were found yet. All methods...
Recent years have witnessed the explosive growth of recommender systems in various exciting application domains such as electronic commerce, social networking, and location-based services. A great many algorithms have been proposed to improve the accuracy of recommendation, but until recently the long tail problem rising from inadequate recommendation of niche items is recognized as a real challenge...
We verified the accuracy of a website that supports health by calculating nutritive value according to the selection of a food name. As a result, since the error in the quantity of fat or salt was large, it became clear that it is not suitable for those who need strict meal control. However, such a system is useful to help users identify dietary tendencies and improve eating habits.
People play different roles in various social networks. Even in a single network, people may interact with others based on different roles, and there are various relationships among them. However, current research usually treats all relationships homogeneously (i.e. friendship). In this paper, we try to identify different types of relationship (family, colleague, and social) within social networks...
This paper presents a real-time human action recognition method based on a modified Deep Belief Network (DBN) model. To recognize human actions, the positions of human joints are taken into account. Each action is made of a sequence of human joint positions. Since the classic DBN cannot deal with temporal information, the proposed method employs the conditional Restricted Boltzmann Machine (cRBM)...
Vehicle Tracking and positioning in GSM networkwith greater accuracy is one of the major popular research topics of Intelligence transportation System and it pass on with the evolution of techniques and methods which enable the data processor to learn and execute activities with the help of Machine learning. Support Vector Machine (SVM) is an isolated classifier which deals with both linear and nonlinear...
Machine translation (MT) research in Indian languages is still in its infancy. Not much work has been done in proper transliteration of name entities in this domain. In this paper we address this issue. We have used English-Hindi language pair for our experiments and have used a hybrid approach. At first we have processed English words using a rule based approach which extracts individual phonemes...
To deal with the existence of malicious secondary users bring damage to the performance of cooperative spectrum sensing, a trust game model named FRTrust is proposed. In FRTrust, the reputation status is used to describe the performance of a secondary user in cooperative spectrum sensing process. It encourages secondary users to choose positive and honest behavior strategies for greater and long term...
Data mining research has produced a significant repertoire of algorithms to predict the classification of data instances with reasonable accuracy. However, data quantity and availability is continuing to rapidly expand such that we no longer have fixed and manageable data sets, but rather continual streams of data. Mining streaming data becomes challenging when using a piece-wise or online approach,...
We present a novel security monitoring framework for intrusion detection in IaaS cloud infrastructures. The framework uses statistical anomaly detection techniques over data monitored both inside and outside each Virtual Machine instance. We present the architecture of our monitoring framework and describe the implementation of the real-time monitors and detectors. We also describe how the framework...
People express their opinion about many things like products, political parties, ideas using the facilities of social media. The analysis of these opinions is a gold mine for marketing experts and for humanities research as well. We introduce a system for opinion mining from the textual content of tweets and discuss the differences between tweet-level and target-oriented opinion mining.
By means of digital statistical simulation we analyze effect of input parameters estimates errors on the accuracy of determination of temporal position of seismic signal caused in ground by moving human.
Sequence-based localization is a novel RF localization technique. The algorithm is achieved by constituting RSSI-based constraint tables and comparing data between two tables. But, the definitions of the constraint relation and the centroid in the algorithm are imperfect. In this paper, we present a new sequence localization method that involves with correlation metric and centroid. First, we use...
Motor imagery based brain-computer interface (BCI) translates subject's motor intention into a control signal through electroencephalogram (EEG) pattern classification. In this paper, a large margin nearest neighbor (LMNN) method is applied for the classification of multi-class BCI based on motor imagery. The main idea of LMNN is to learn a Mahalanobis distance that tries to collapse examples in the...
Word Sense Disambiguation (WSD) is the task of choosing the most appropriate sense of a word having multiple senses in a given context. Collocational features acquired from the words in neighborship with the ambiguous word are one of the important knowledge sources in this area. This paper explores the effective sets of collocational features in Turkish in order to obtain better Turkish WSD systems...
Data process in Cloud or IoT (Internet of Things) sometimes implies continuous real-time queries as data streams. In order to acquire extreme value of data stream over time-based sliding window, traditional approaches computed the exact solution through vast space especially under ultra circumstances like high-rate or high-concurrency. In this paper, we design space-bounded synopsis data structure...
In this talk the author will discuss how parallel and/or distributed compute resources can be used differently: instead of focusing on speeding up algorithms, we propose to focus on improving accuracy. In a nutshell, the goal is to tune data mining algorithms to produce better results in the same time rather than producing similar results a lot faster. He will discuss a number of generic ways of tuning...
Our research group is examining how first year engineering students develop problem-solving skills. It is important to select and design problems such that they promote self-efficacy and build effective problem solving skills. However, it is a challenge for engineering educators to determine the appropriate difficulty or rigor of assignments or assessments that will accomplish this, especially in...
Locality sensitive hashing (LSH) is quite popular in high dimensional data indexing. However, most of existing methods perform hashing in an unsupervised way, that is to say, hash functions are randomly generated without the prior information of the data. In this paper, we propose two improved LSH algorithms based on weakly supervised learning technique, which need only small quantities of labeled...
Extracting specific content from certain types of documents can be a very challenging task, especially when developing a not so tailored solution and refraining from using explicit contextual information. In this paper, we address the problem of automatically extracting data from semi-structured documents through an unsupervised process based on an analysis of the document's own morphological composition...
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