Compression based clustering technique for enhancing accuracy in web scale videos

Multimedia Tools and Applications - Detection and clustering of commercial advertisements plays an important role in multimedia indexing also in the creation of personalized user content. In...     

A Polynomial Time Solution to Minimum Forwarding Set Problem in Wireless Networks under Unit Disk Coverage Model

Network-wide broadcast (simply broadcast) is a frequently used operation in wireless ad hoc networks (WANETs). One promising practical approach for energy-efficient broadcast is to use localized algorithms to minimize the number of nodes involved in the propagation of the broadcast messages. In this context, the minimum forwarding set problem (MFSP) (also known as multipoint relay (MPR) problem) has received a considerable attention in the research community. Even though the general form of the problem is shown to be NP-complete, the complexity of the problem has not been known under the practical application context of ad hoc networks. In this paper, we present a polynomial time algorithm to solve the MFSP for wireless network under unit disk coverage model. We prove the existence of some geometrical properties for the problem and then propose a polynomial time algorithm to build an optimal solution based on these properties. To the best of our knowledge, our algorithm is the first polynomial time solution to the MFSP under the unit disk coverage model. We believe that the work presented in this paper will have an impact on the design and development of new algorithms for several wireless network applications including energy-efficient multicast, broadcast, and topology control protocols for WANETs and sensor networks.     

Using genetic algorithm to select the presentation order of training patterns that improves simplified fuzzy ARTMAP classification performance

The presentation order of training patterns to a simplified fuzzy ARTMAP (SFAM) neural network affects the classification performance. The common method to solve this problem is to use several simulations with training patterns presented in random order, where voting strategy is used to compute the final performance. Recently, an ordering method based on min–max clustering was introduced to select the presentation order of training patterns based on a single simulation. In this paper, another single simulation method based on genetic algorithm is proposed to obtain the presentation order of training patterns for improving the performance of SFAM. The proposed method is applied to a 40-class individual classification problem using visual evoked potential signals and three other datasets from UCI repository. The proposed method has the advantages of improved classification performance, smaller network size and lower training time compared to the random ordering and min–max methods. When compared to the random ordering method, the new ordering scheme has the additional advantage of requiring only a single simulation. As the proposed method is general, it can also be applied to a fuzzy ARTMAP neural network when it is used as a classifier.     

Video personalization in heterogeneous and resource-constrained environments

Access to multimedia data and multimedia services is becoming increasingly common in networked mobile environments. In such environments, both the mobile client devices and multimedia servers are typically resource constrained. Moreover, the mobile client population is often heterogeneous in terms of the clients’ preferences with regard to multimedia content, the clients’ quality of service requirements and system-level resource constraints. In order to provide a resource-constrained mobile client with its desired video content, it is often necessary to personalize the requested multimedia content in a manner that satisfies simultaneously the various client-specified content preferences and the system-level resource constraints. Also, in order to simultaneously reduce the client-experienced latency, provide optimal quality of service to the clients and ensure efficient utilization of server and network resources, it is necessary to perform client request aggregation on the server end. To this end, a video personalization strategy is proposed to provide mobile, resource-constrained clients with personalized video content that is most relevant to the clients’ requests while satisfying simultaneously multiple client-side system-level resource constraints. A client request aggregation strategy is also proposed to cluster client requests with similar video content preferences and similar client-side resource constraints such that the number of requests the server needs to process and service, and the client-experienced latency are both reduced simultaneously. The primary contributions of the paper are: (1) the formulation and implementation of a Multiple-choice Multi-dimensional Knapsack Problem (MMKP)-based video personalization strategy; and (2) the design and implementation of a client request aggregation strategy based on a multi-stage clustering algorithm. Experimental results comparing the proposed MMKP-based video personalization strategy to existing 0/1 Knapsack Problem (0/1KP)-based and the Fractional Knapsack Problem (FKP)-based video personalization strategies are presented. It is observed that: (1) the proposed MMKP-based personalization strategy includes more relevant video content in response to the client’s request compared to the existing 0/1KP-based and FKP-based personalization strategies; and (2) in contrast to the 0/1KP-based and FKP-based personalization strategies which can satisfy only a single client-side resource constraint at a time, the proposed MMKP-based personalization strategy is capable of satisfying multiple client-side resource constraints simultaneously. Experimental results comparing the client-experienced latency with and without the proposed server-side client request aggregation strategy are also presented. It is shown that the proposed client request aggregation strategy reduces the mean client-experienced latency without significant reduction in the average relevance of the delivered video content and without significant deviation in the client-side resources actually consumed by the delivered video content from the client-specified resource constraints.     

Selective oxidation reactions over titanium and vanadium metallosilicate molecular sieves

Selective oxidation reactions like the oxyfunctionalization of alkanes, hydroxylation of aromatics and sulfoxidation of thioethers have been carried out with dilute hydrogen peroxide over titanium and vanadium metallosilicate molecular sieves with MEL topology, viz., TS-2 and VS-2. Though both the catalysts possess similar activities, substantial differences in the product distribution are observed. The oxyfunctionalization of the primary carbon atoms of the alkanes and the oxidation of the methyl substituents of the aromatic hydrocarbons distinguish VS-2 from TS-2. Both the catalysts are found to be equally active in the hydroxylation of phenol, though they possess different activities in different solvents. In general, the oxidations are deeper over VS-2 than on TS-2.     

Utilizing gamma band to improve mental task based brain-computer interface design.

A common method for designing brain-computer Interface (BCI) is to use electroencephalogram (EEG) signals extracted during mental tasks. In these BCI designs, features from EEG such as power and asymmetry ratios from delta, theta, alpha, and beta bands have been used in classifying different mental tasks. In this paper, the performance of the mental task based BCI design is improved by using spectral power and asymmetry ratios from gamma (24-37 Hz) band in addition to the lower frequency bands. In the experimental study, EEG signals extracted during five mental tasks from four subjects were used. Elman neural network (ENN) trained by the resilient backpropagation algorithm was used to classify the power and asymmetry ratios from EEG into different combinations of two mental tasks. The results indicated that ((1) the classification performance and training time of the BCI design were improved through the use of additional gamma band features; (2) classification performances were nearly invariant to the number of ENN hidden units or feature extraction method.     

A flexible and recoverable client/server database event notification system

A software architecture is presented that allows client application programs to interact with a DBMS server in a flexible and powerful way, using either direct, volatile messages, or messages sent via recoverable queues. Normal requests from clients to the server and replies from the server to clients can be transmitted using direct or recoverable messages. In addition, an application event notification mechanism is provided, whereby client applications running anywhere on the network can register for events, and when those events are raised, the clients are notified. A novel parameter passing mechanism allows a set of tuples to be included in an event notification. The event mechanism is particularly useful in an active DBMS, where events can be raised by triggers to signal running application programs. Received July 21, 1995 / Accepted May 30, 1996     

Correlation between central receiver size and solar field using flat heliostats

In Central Receiver Systems (CRSs), thousands of heliostats track the sunrays and reflect beam radiation on to a receiver surface. The size of the reflected image and the extent of reflection from the heliostats are one of the important criteria that need to be taken into account while designing a receiver, since spillage losses may vary from 2 to 16% of the total losses. The present study aims to determine the size of an external cylindrical receiver, such that the rays reflected from all the heliostats in the field are intercepted. A dimensionless correlation with respect to tower height and receiver size (diameter and height) as a function of heliostat size and its position is discussed in the paper. This correlation could be used as a first-order approximation to estimate the receiver dimensions. When applied to the Ivanpah Solar Electricity Generating Station (ISEGS) plant, the correlation yields satisfactory estimation of receiver dimensions.