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This paper presents an alternative energy-based algorithm to provide speech/silence classification. The algorithm is capable to track non-stationary signals and dynamically calculate instantaneous value for threshold using adaptive scaling parameter. It is based on the observation of a noise power estimation used for computation of the threshold can be obtained using minimum and maximum values of a short-term energy estimate. The paper presents this novel voice activity detection algorithm, its performance, its limitations, and some other techniques which deal with energy estimation as well. [ABSTRACT FROM AUTHOR]

The widespread popularity of mobile computing devices, such as Laptops, handheld devices and cell phones, as well as recent advances in the wireless communication technologies have motivated researchers to provide novel solutions and applications for the users that were previously not feasible. The users of these mobile computing devices expect the same features and services from these devices as were previously available from conventional desktop computers. However to provide mobility and reduction of size of these mobile devices, the battery life is a major concern; several hardware based techniques have been proposed which results in more energy efficient systems as compared to the earlier systems. Even after these hardware improvement based techniques the problem still persists and it is believed that software based techniques have enough potential to reduce the energy demand to overcome the problems faced due to energy limitation. In this paper, we look into the problem of distributing the computational tasks among different devices in hybrid network environment. By hybrid networks we mean a network containing both wired as well as wireless handheld devices. The reason of selecting hybrid network environment is because most of the applications of mobile devices require accessing resources on the high bandwidth unlimited energy devices connected on wired network to help conserve the energy utilization of the energy limited wireless handheld devices. We have proposed a novel energy-aware scheduling algorithm to solve the problems of resource constrained mobile devices. Our scheduling algorithm schedules a set of computational tasks which may have operational and communication dependencies, into the set of heterogeneous devices so as to minimize both the energy consumption and time taken by the tasks to be completed. Experiments show that significant improvement in the over all performance in terms of energy consumption and execution time of the handheld devices can be achieved by using our algorithm. [ABSTRACT FROM AUTHOR]

The continued advancement of software-defined radio (SDR) technology has been a key factor in furthering research about the implementation of most signal processing algorithms at baseband. Traditionally, most algorithms have been carried out at radio frequency (RF). With the coming of SDR, the processing can be done at baseband frequencies which are more compatible with the fast developing software radio technology. This paper looks at matched filter detection and investigates the possibility and benefits of carrying out the detection process at quadrature baseband (QBB). A simple chirp signal is considered for the analysis. The analysis is carried out using MatLab simulations at RF and QBB and the results do show the possibility of carrying out the detection process at QBB with the expected benefits as compared to carrying out the process at RF. [ABSTRACT FROM AUTHOR]

Emergence of modern techniques for scientific data collection has resulted in large scale accumulation of data pertaining to diverse fields. Conventional database querying methods are inadequate to extract useful information from huge data banks. Cluster analysis is one of the major data analysis methods and the k-means clustering algorithm is widely used for many practical applications. But the original k-means algorithm is computationally expensive and the quality of the resulting clusters heavily depends on the selection of initial centroids. Several methods have been proposed in the literature for improving the performance of the k-means clustering algorithm. This paper proposes a method for making the algorithm more effective and efficient, so as to get better clustering with reduced complexity. [ABSTRACT FROM AUTHOR]

Line Spectrum Frequencies (LSF) have been the current parameter set to represent LPC coefficients in speech coding. Extensive research has been performed to exploit their interframe and intraframe correlations and quantize them more efficiently. Interframe coding of LSF's can cause error propagation when frame erasures occur. Since most LSF quantizers were designed with the primary concerns of bit-rate and complexity, less attention was paid to error propagation. In this paper, we consider the erasure performance of LSF differential scalar quantizer (DSQ) and compare it with the interframe coding method embedded in the standard G723.1 of the ITU. Our results show that with only 5% extra bit-rate, DSQ algorithm is much more robust to frame erasures and improvements in terms of spectral distortion and Enhanced modified bark spectral distortion (EMBSD) tests under various packet loss conditions are obtained. [ABSTRACT FROM AUTHOR]

An ad hoc network (MANET) has no fixed networking infrastructure, and consists of mobile nodes that communicate with each other. Since nodes are mobile, Routing in ad hoc network is a challenging task. Efficient routing protocols can make better performance in such networks. Many protocols have been proposed for ad hoc networks which the most common types are: Ad hoc on-demand Distance Vector (AODV), Dynamic Source Routing (DSR), Optimized Link State Routing (OLSR). In this paper, we introduce a new Position and Neighborhood based Routing (PNR) algorithm for mobile ad hoc networks which uses GPS and new algorithm to reduce the overhead caused by position update messages. We also compare our scheme with DSR, AODV, OLSR for two metrics: packet delivery ratio and end-to-end delay. We use GlomoSim [1] to evaluate these protocols. [ABSTRACT FROM AUTHOR]

Autonomous navigation in unknown cluttered environments is one of the main challenges for search and rescue robots inside collapsed buildings. Being able to compare different search strategies in various search fields is crucial to attain fast victim localization. Thus we discuss an algorithmic development and proliferation of realistic after--disaster test fields for search and rescue simulated robots. In this paper we characterized our developed search environments by their fractal dimensions. This index has shown to be a discriminative index for narrow pathways inside confined and cluttered spaces in our simulation test fields. In this approach a simulation of challenging parts of NIST red course is constructed and a benchmark for search strategies has been evaluated. [ABSTRACT FROM AUTHOR]