We present two results on text compression. One is a general framework incorporating the context sorting algorithm and the LZ77 algorithm. The other is a pre-processor to block sorting which improves its performance w...
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We present two results on text compression. One is a general framework incorporating the context sorting algorithm and the LZ77 algorithm. The other is a pre-processor to block sorting which improves its performance when small block sizes are used.
Speech level measurements were made for a collection of Diagnostic Rhyme Test (DRT) word lists as used for intelligibility testing of voice communications systems. These measurements were used in the generation of a s...
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Speech level measurements were made for a collection of Diagnostic Rhyme Test (DRT) word lists as used for intelligibility testing of voice communications systems. These measurements were used in the generation of a subsequent set of DRT source tapes for which all DRT list segments on the tapes were equalized with respect to speech level. The effects of this equalization on intelligibility scores was evaluated for unprocessed and processed speech (both parametric and waveform coding algorithms). The manipulation of the speech levels for the DRT lists did not result in significant, predictable, and replicable effects on either system mean scores or on the DRT score variability across lists. The absence of effects was noted for all speech processing conditions and for both male and female speakers. Practical advantages in the use of the equalized word lists are discussed.
In this paper we present an on-line platform, called ***, designed to help standardization bodies and communities to benchmark compression algorithms for still 3D objects. Based on MPEG standards, this platform provid...
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In this paper we present an on-line platform, called ***, designed to help standardization bodies and communities to benchmark compression algorithms for still 3D objects. Based on MPEG standards, this platform provides an easy-to-use API to integrate the algorithms to be evaluated. The platform automatically benchmarks them from the platform extensible 3D database. When uploading new 3D contents, benchmark results for the various available compression schemes are automatically updated. Filtering tools are provided to help performance assessment at scales ranging from individual 3D content to database subsets.
Trajectory compression algorithms eliminate redundant information in the history of a moving object. Such compression enables efficient transmission, storage, and processing of trajectory data. Although a number of co...
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Trajectory compression algorithms eliminate redundant information in the history of a moving object. Such compression enables efficient transmission, storage, and processing of trajectory data. Although a number of compression algorithms have been proposed in the literature, no common benchmarking platform for evaluating their effectiveness exists. This paper presents a benchmarking framework for efficiently, conveniently, and accurately comparing trajectory compression algorithms. This framework supports various compression algorithms and metrics defined in the literature, as well as three synthetic trajectory generators that have different trade-offs. It also has a highly extensible architecture that facilitates the incorporation of new compression algorithms, evaluation metrics, and trajectory data generators. This paper provides a comprehensive overview of trajectory compression algorithms, evaluation metrics and data generators in conjunction with detailed discussions on their unique benefits and relevant application scenarios. Furthermore, this paper describes challenges that arise in the design and implementation of the above framework and our approaches to tackling these challenges. Finally, this paper presents evaluation results that demonstrate the utility of the benchmarking framework.
Text compression algorithms are normally defined in terms of a source alphabet Sigma of 8-bit ASCII codes. The authors consider choosing Sigma to be an alphabet whose symbols are the words of English or, in general, a...
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Text compression algorithms are normally defined in terms of a source alphabet Sigma of 8-bit ASCII codes. The authors consider choosing Sigma to be an alphabet whose symbols are the words of English or, in general, alternate maximal strings of alphanumeric characters and nonalphanumeric characters. The compression algorithm would be able to take advantage of longer-range correlations between words and thus achieve better compression. The large size of Sigma leads to some implementation problems, but these are overcome to construct word-based LZW, word-based adaptive Huffman, and word-based context modelling compression algorithms.< >
Automotive stereo-based camera systems are at the focus of new vehicle functions development. Advantageous interconnections between automotive cameras and electronic control units are possible using IP-based technolog...
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Automotive stereo-based camera systems are at the focus of new vehicle functions development. Advantageous interconnections between automotive cameras and electronic control units are possible using IP-based technology in the vehicles. Because automotive implementation of this technology allows only limited data rates camera stream compression is necessary to transmit over such a medium. The image processing algorithms can be applied after a decompressing of the camera streams. This paper introduces a method for comparing the impact of different image compression algorithms on automotive stereo algorithms. We propose a comparison metric based on disparity error to compare the effects as a function of image compression algorithms, compression ratio and vehicle velocity.
In the recent years, wireless sensor networks have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery powered devices, it is essential to minimize the ...
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In the recent years, wireless sensor networks have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery powered devices, it is essential to minimize the energy consumption of the nodes so that the network lifetime can be extended. Most of the energy is consumed in the processing and transmission of data. Applying compression algorithms on the wireless sensor data prior to transmission is one of the efficient ways to save energy. In this paper we propose data compression algorithms based on Huffman and Lempel-Ziv techniques and compare the efficiency of different algorithms in a wireless sensor network scenario.
With the availability of low-cost sensor nodes there have been many standards developed to integrate and network these nodes to form a reliable network allowing many different types of hardware vendors to coexist. Mos...
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ISBN:
(纸本)9780769531588;9780769534114
With the availability of low-cost sensor nodes there have been many standards developed to integrate and network these nodes to form a reliable network allowing many different types of hardware vendors to coexist. Most of these solutions however have aimed at industry-specific interoperability but not the size of the sensor network and the large amount of data which is collected in course of its lifetime. In this paper we use well studied data compression algorithms which optimize on bringing down the data redundancy which is related to correlated sensor readings and using a probability model to efficiently compress data at the cluster heads. As in the case of sensor networks the data reliability goes down as the network resource depletes and these types of networks lacks any central synchronization making it even more a global problem to compare different reading at the central coordinator. The complexity of calibrating each sensor and using an adaptable measured threshold to correct the reading from sensors is a severe drain in terms of network resources and energy consumption. In this paper we separate the task of comparative global analysis to a central coordinator and use a reference PMax which is a normalized probability of individual source which reflects the current lifetime reliability of the sensors calculated at the cluster heads which then is compared with the current global reliability index based on all the PMax of cluster heads. As this implementation does not need any synchronization at the local nodes it uses compress once and stamp locally without any threshold such as application specific calibration values (0-42degF) and the summarization can be application Independent making It more a sensor network reliability Index and using It independent of the actual measured values.
WebSocket protocol is a part of HTML5 standard, which is suitable for real-time and full duplex web applications such as online chat, notification server, and online game systems. A compression algorithm for WebSocket...
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ISBN:
(纸本)9781479929948
WebSocket protocol is a part of HTML5 standard, which is suitable for real-time and full duplex web applications such as online chat, notification server, and online game systems. A compression algorithm for WebSocket protocol has yet to be defined as a standard. There is a proposal to use Deflate algorithm, a lossless compression algorithm for WebSocket, but other compression algorithms are also available. In this paper, Deflate algorithm is compared with other lossless algorithms, i.e. Huffman, LZ77 and LZW algorithms in order to find a suitable compression algorithm for WebSocket protocol. A compression library is developed using JavaScript for studying and analyzing such compression algorithms for different data formats. In addition, an instant messaging system and an online game are developed and studied as the examples of WebSocket real-time and full duplex web applications. The performance metrics for this study are a compression ratio, compression and decompression speeds and overall time. In our experiments, the deflate compression algorithm gains the best result in terms of overall time and compression ratio for WebSocket protocol.
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