Behavior analysis in Arabic social media

International Journal of Speech Technology - Social media has allowed all individuals, organizations, and businesses to share their opinions, ideas, and inclinations with others. These opinions...     

Unsupervised and simultaneous training of multiple object detectors from unlabeled surveillance video

Object detection is an essential component in automated vision-based surveillance systems. In general, object detectors are constructed using training examples obtained from large annotated data sets. The inevitable limitations of typical training data sets make such supervised methods unsuitable for building generic surveillance systems applicable to a wide variety of scenes and camera setups. In our previous work we proposed an unsupervised method for learning and detecting the dominant object class in a general dynamic scene observed by a static camera. In this paper, we investigate the possibilities to expand the applicability of this method to the problem of multiple dominant object classes. We propose an idea on how to approach this expansion, and perform an evaluation of this idea using two representative surveillance video sequences.     

基于分布式表示技术的推荐算法综述

传统的推荐算法在实际应用中取得不错的效果并得到广泛的使用,同时也面临严重的数据稀疏和冷启动的问题,随着全球数据总量的不断增长,数据结构愈加丰富,如何从这些数据中正确捕获用户偏好成为关键问题,分布式表示技术为此提供了新的解决思路。通过对近些年基于分布式表示技术的推荐算法进行综述,分析算法与传统推荐算法的区别和优势,对这些算法的实际应用场景进行总结,并对基于分布式表示的推荐算法的未来发展趋势进行展望,为后续相关工作提供参考。     

Decentralised controller design based on structured singular values

In this study, structured singular values are used in a different way from those commonly used in the robust control literature. It is shown that subject to conditions based on structured singular values, each local area controller can be designed independently. A MATLAB? program is developed to plot inverse structured singular values of multi input multi output (MIMO) system relative error matrix. This plot can be used to predict the stability of the global system with decentralised controller. Therefore decentralised controller design problem can be translated into an equivalent problem of decentralized controller design for a MIMO control system.     

Spatial division networks for weakly supervised detection

Neural Computing and Applications - With only global image-level annotations, weakly supervised learning of deep convolutional neural networks has shown enough capacity in classification and...     

A hybrid model for spelling error detection and correction for Urdu language

Neural Computing and Applications - Detecting and correcting misspelled words in a written text are of great importance in many natural language processing applications. Errors can be broadly...     

Intelligent non-linear modelling of an industrial winding process using recurrent local linear neuro-fuzzy networks

This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system. A new simulator model is proposed for a winding process using non-linear identification based on a recurrent local linear neuro-fuzzy (RLLNF) network trained by local linear model tree (LOLIMOT), which is an incremental tree-based learning algorithm. The proposed NF models are compared with other known intelligent identifiers, namely multilayer perceptron (MLP) and radial basis function (RBF). Comparison of our proposed non-linear models and associated models obtained through the least square error (LSE) technique (the optimal modelling method for linear systems) confirms that the winding process is a non-linear system. Experimental results show the effectiveness of our proposed NF modelling approach.     

A component‐based framework for radio‐astronomical imaging software systems

This paper describes a component‐based framework for radio‐astronomical imaging software systems. We consider optimal re‐use strategies for packages of disparate architectures brought together within a modern component framework. In this practical case study, the legacy codes include both procedural and object‐oriented architectures. We consider also the special requirements on scientific component middleware, with a specific focus on high‐performance computing. We present an example application in this component architecture and outline future development planned for this project. Copyright © 2007 John Wiley & Sons, Ltd.     

Bottom-Up Association Rule Mining in Relational Databases

Although knowledge discovery from large relational databases has gained popularity and its significance is well recognized, the prohibitive nature of the cost associated with extracting such knowledge, as well as the lack of suitable declarative query language support act as limiting factors. Surprisingly, little or no relational technology has yet been significantly exploited in data mining even though data often reside in relational tables. Consequently, no relational optimization has yet been possible for data mining. We exploit the transitive nature of large item sets and the so called anti-monotonicity property of support thresholds of large item sets to develop a natural least fixpoint operator for set oriented data mining from relational databases. The operator proposed has several advantages including optimization opportunities, and traditional candidate set free large item set generation. We present an SQL3 expression for association rule mining and discuss its mapping to the least fixpoint operator developed in this paper.     

Modified distributed snapshots algorithm for protocol stabilization

This paper assesses the use of Chandy and Lamport's distributed snapshots algorithm (DSA) for stabilizing a communication protocol, a special type of distributed system. We show that when a loss of coordination occurs during the distributed execution of the protocol, DSA is not guaranteed to terminate, and therefore it sometimes fails to obtain a global state or snapshot. We propose some modifications to DSA to solve this problem. Finally, we discuss how, in the case of a loss of coordination, the modified algorithm can be used to stabilize a communication protocol, and we assess the suitability of the global state obtained by DSA as a recovery point to be used later in a backward recovery procedure.