Detecting sources

Xem 1-20 trên 97 kết quả Detecting sources
  • • Network errors are in the form of corrupted data or lost data. • Network errors occur naturally on all networks due to electrical noise and distortion and must be detected and corrected by either hardware or software. • Bit Error Rates (BERs) are calculated as the number of bits in error divided by the number of bits transmitted. A BER of 1 in 100,000 might be shown as 1:105 or simply as a BER of 10-5 . • Errors often occur in bursts where many bits in a sequence will be in...

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  • Networks must be able to transfer data from one device to another with complete accuracy. Data can be corrupted during transmission. For reliable communication, errors must be detected and corrected.Single bit errors are the least likely type of errors in serial data transmission because the noise must have a very short duration which is very rare. However this kind of errors can happen in parallel transmission.

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  • Data can be corrupted during transmission. For reliable communication, error must be detected and corrected are implemented either at the data link layer or the transport layer of the OSI model.Error detection uses the concept of redundancy, which means adding extra bits for detecting errors at the destination

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  • This paper proposes a novel reordering model for statistical machine translation (SMT) by means of modeling the translation orders of the source language collocations. The model is learned from a word-aligned bilingual corpus where the collocated words in source sentences are automatically detected.

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  • Data transmission can contain errors. – Single-bit. – Burst errors of length n. (n: distance between the first and last errors in data block) • How to detect errors. – If only data is transmitted, errors cannot be detected. Send more information with data that satisfies a special relationship. -Add redundancy

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  • We present Subgroup Detector, a system for analyzing threaded discussions and identifying the attitude of discussants towards one another and towards the discussion topic. The system uses attitude predictions to detect the split of discussants into subgroups of opposing views. The system uses an unsupervised approach based on rule-based opinion target detecting and unsupervised clustering techniques. The system is open source and is freely available for download.

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  • Sentence boundary detection in speech is important for enriching speech recognition output, making it easier for humans to read and downstream modules to process. In previous work, we have developed hidden Markov model (HMM) and maximum entropy (Maxent) classifiers that integrate textual and prosodic knowledge sources for detecting sentence boundaries.

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  • We have analyzed 607 sentences of spontaneous human-computer speech data containing repairs, drawn from a total corpus of 10,718 sentences. We present here criteria and techniques for automatically detecting the presence of a repair, its location, and making the appropriate correction. The criteria involve integration of knowledge from several sources: pattern matching, syntactic and semantic analysis, and acoustics. INTRODUCTION Spontaneous spoken language often includes speech that is not intended by the speaker to be part of the content of the utterance. ...

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  • We investigate the potential of Tree Substitution Grammars as a source of features for native language detection, the task of inferring an author’s native language from text in a different language. We compare two state of the art methods for Tree Substitution Grammar induction and show that features from both methods outperform previous state of the art results at native language detection.

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  • Weblogs are a source of human activity knowledge comprising valuable information such as facts, opinions and personal experiences. In this paper, we propose a method for mining personal experiences from a large set of weblogs. We define experience as knowledge embedded in a collection of activities or events which an individual or group has actually undergone.

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  • A method was proposed for locating possible sources of oil pollution in the East Vietnam Sea. The method includes two stages. The first stage is called the raw stage. In this stage, based on the history of oil pollution at the Vietnamese coast and oil pollution footprint detected byremote sensing technique, numerical computation of wind and flow field in the sea was carried out.

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  • This book is intended for courses at least at Masters level to provide an introduction to the field of signal processing in telecommunications. The text therefore deals mainly with source coding, channel coding, modulation and demodulation. Adaptive channel equalisation, the signal processing aspects of adaptive antennas as well as multi-user detectors for CDMA are also included. Shorter sections on link budget, synchronising and cryptography are also included. Network aspects are not discussed and very little is given about wave propagation.

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  • Electrochemistry has been used extensively in the past three decades to determine the chemical composition of environmental samples from the water column, sediments, soils, biofilms, and microbial mats.

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  • Why Qt? Why do programmers like us choose Qt? Sure, there are the obvious answers: Qt’s single-source compatibility, its feature richness, its C++ performance, the availability of the source code, its documentation, the high-quality technical support,and all the other items mentioned in Trolltech’s glossy marketing materials. This is all very well, but it misses the most important point: Qt is successful because programmers like it.

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  • The contamination of metals is a major environmental problem and especially in the aquatic environment. Some metals are potentially toxic or carcinogenic even at very low concentration and are thus, hazardous to human if they enter the food chain. Metals are usually dissolved into the aquatic system through natural or anthropogenic sources. Metal ions are distributed thoroughly during their transport in different compartments of the aquatic ecosystems, in biotic or abiotic compartment such as fishes, water, sediment, plant.

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  • The processing of signals received by sensor arrays generally can be separated into two problems: (1) detecting the number of sources and (2) isolating and analyzing the signal produced by each source.

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  • distortion in the cell organelles and inhibit the activity of various enzymes (Valarmathi & Azariah, 2003; Yadav et al., 2007), which may greatly disturb the physiological state of the exposed living organism. The heavy metals present in the fertilizer industry discharge are usually in dissolved state which could easily be uptaken by fish and enter human food chain. There have been studies showed that metals will cause damage to the human kidney and liver even at low concentration.

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  • Các liên kết IP có mặt trong cột Source IP sẽ đưa bạn đến một trang dis chơi một bản tóm tắt của chữ ký kích hoạt bởi lưu lượng truy cập từ trang tóm tắt cụ thể source.This cũng chứa các liên kết đó sẽ giúp bạn phát hiện ra địa chỉ IP này thuộc whois tra cứu , tra cứu DNS, và vv.

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  • However, some scientists are working on earthquake precursors and forecasting research and this is a big challenge. Chapter in this book will be devoted to different aspects of the Earthquake Research and analysis, from theoretical advances for practical applications. The first two chapters for statistical analysis. About ten chapters in Part II focus on research precursors of earthquakes and forecasting. Some proposed new methods for early detection, as well as observations of earthquakes through the use of social sensors....

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  • SAS defines data mining as the process of uncovering hidden patterns in large amounts of data. Many industries use data mining to address business problems and opportunities such as fraud detection, risk and affinity analyses, database marketing, householding, customer churn, bankruptcy prediction, and portfolio analysis.The SAS data mining process is summarized in the acronym SEMMA, which stands for sampling, exploring, modifying, modeling, and assessing data.

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