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In this paper, a new IMC-based PID controller design is proposed. The model reduction is employed to find the best PID controller approximation to the IMC controller. Compared with the existing IMC-based methods, the proposed design is applicable to a wider range of processes, and yields a control system with performance closer to the more sophisticated IMC counterpart. Furthermore, it can be made...
In this paper we present our evaluation of the Edge Orientation Histograms (EOH) as feature descriptors in an automatic face-based gender classification application. The feature descriptors extracted from an input image are evaluated using estimated arithmetic means of accuracies to select the feature descriptors that play the most important role in classification success. Our experiments show that...
A new efficient hybrid technique is presented, which combines the method of moments (MoM) and the shooting and bouncing ray (SBR) for analyzing scattering of complex large structures. By applying the SBR method for the whole structures, a corrected incident field including not only the direct incident field but also the multi-bounce field from the SBR region contributes to the integral equation in...
Mobile wheeled inverted pendulum mechanical models are benchmark under actuated dynamical systems with inherently unstable dynamics and pose a difficult challenge to control with desired accuracy. This paper seeks to achieve an efficient control scheme based on the notion of sliding modes to achieve the desired response under perturbations. In this work, a mathematical model of a two wheeled inverted...
Segmentation of mathematical equations from document images is already a major research area for improved performance of OCR systems. Though chemical equations are also sharing similar spatial properties as that of non-chemical equations (for example, mathematical equations), efforts to segment those are still to be explored. This paper presents a novel method for segmenting and identifying chemical...
Tag recommendation aims to recommend to a user the most suited tags for a given item. It is an important functionality of resource sharing systems. In this paper we propose a recommendation algorithm, called Fas Tag, that links the relevance of the tags to both their popularity and the opinions of the user's neighbors. Fas Tag assumes that the users are organized in a weighted graph representing,...
This paper presents an efficient Parkinson disease diagnosis system using Least Squares Twin Support Vector Machine (LSTSVM) and Particle Swarm Optimization (PSO). LSTSVM is a promising binary classifier and has shown better generalization ability and faster computational speed. PSO is used for feature selection and parameter optimization. Parkinson disease dataset is taken from UCI repository. The...
This work proposes a dynamic, and adaptive caching mechanism for efficient virtualization in sensor-cloud — one of the first attempts in this direction. The work introduces both internal and external caching techniques to ensure efficiency in resource utilization of the underlying physical network. Conventional data transmission techniques involve periodic packet transmissions to the cloud-end. However,...
To get the accuracy of Wireless Sensor Networkboundary node localization and decrease error, this paperpresent an arithmetic on RSSI (Received Signal StrengthIndicator) weighting circulate localization. This arithmetic isbased on RSSI, combination of least squares estimate localizationalgorithm and weighted centroid circulation method. Thealgorithm firstly is introduced into threshold method forscreening...
Granger Causality (GC) is an effective tool for determining functional connectivity in time-series data. However, application of GC is limited by the curse of dimensionality in many applications, e.g. Gene Regularity Networks (GRN). Various methods have been proposed to overcome this limitation. To the best of our knowledge, there is no detailed comparative study of such methods. We aim to perform...
Because the implicit Runge-Kutta method is hard to use, in addition, there is the lack of precision analysis for the implicit Runge-Kutta methods, three classic four-stage implicit Runge-Kutta methods are used to compare their calculation accuracy and the sensitivity of calculation step, these results provided reference for the selection of four-stage implicit Runge-Kutta methods.
In traditional DV-Hop localization algorithm, the average estimation hop distance is greater influence for the distribution of beacon nodes, which causes high positioning error. A new algorithm is proposed to improve this disadvantage. The new improved algorithm uses the hyperbolic method to locate the unknown node position. This way eliminates the cumulative error and improves the positioning accuracy...
The widespread adoption of ubiquitous devices does not only facilitate the connection of billions of people, but has also fuelled a culture of sharing rich, high resolution locations through check-ins. Despite the profusion of GPS and WiFi driven location prediction techniques, the sparse and random nature of check-in data generation have ushered diverse problems, which have prompted the prediction...
Representational competence (RC), defined as "the ability to simultaneously process and integrate multiple external representations (MERs) in a domain", is a marker of expertise in science and engineering. However, the cognitive mechanisms underlying this ability and how this ability develops in learners, is poorly understood. In this paper, we report a fully controllable interface, designed...
A recently introduced data density based approach to clustering, known as Data Density based Clustering has been presented which automatically determines the number of clusters. By using the Recursive Density Estimation for each point the number of calculations is significantly reduced in offline mode and, further, the method is suitable for online use. The Data Density based Clustering method however...
Labeled data, in real world, is quite scarce compared with unlabeled data. Manual annotation is usually expensive and inefficient. Active learning paradigm is used to handle this problem by identifying the most informative instances to annotate. In this paper, we proposed a new active learning algorithm based on nonparallel support vector machine. Numeric experiment shows the effective performance...
In cognitive radio networks, spectrum sensing plays a crucial role in the discovery of spectrum opportunities for secondary systems (or unlicensed systems). The performance of spectrum sensing is characterized by both accuracy and efficiency, and more importantly the time taken to make a decision and also the complexity involved in doing so. In this work we propose a simple detection technique based...
Localisation is one of the most important applications for wireless sensor networks since the locations of the sensor nodes are critical to both network operations and most application level tasks. Numerous techniques for localisation of sensor nodes that make use of the Received Signal Strength Indicator (RSSI) have been proposed because of the simplicity and low cost of implementation. However,...
Radio Frequency Identification (RFID) technology brings a revolutionary change in warehouse management by automatically monitoring and tracking. Considering the misplaced and newly added tags, fast identifying such unknown tags is of paramount importance, especially in large-scale RFID systems. Unlike existing work, this paper proposes a fast Physical-layer Unknown Tag Identification (PUTI) protocol...
Recommendation systems have become extremely common in recent years due to the ubiquity of information across various applications. Online entertainment (e.g., Netflix), E-commerce (e.g., Amazon, Ebay) and publishing services such as Google News are all examples of services which use recommender systems. Recommendation systems are rapidly evolving in these years, but these methods have fallen short...
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