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Books on the topic 'Signal variation'

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Published: 10 December 2022
Last updated: 29 January 2023

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1

Fulde, Michael. Variation Aware Analog and Mixed-Signal Circuit Design in Emerging Multi-Gate CMOS Technologies. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-3280-5.

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service), SpringerLink (Online, ed. Variation Aware Analog and Mixed-Signal Circuit Design in Emerging Multi-Gate CMOS Technologies. Dordrecht: Springer Netherlands, 2010.

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3

Wang, Ruotong. Sensitivity performance of adder channel collaborative coding multiple access communication systems to signal variation of individual users. [s.l.]: typescript, 1995.

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4

Roquin, Claude. Traitement des données en prospection géochimique: Facteurs de variation du signal et sélection de la composante anomale. Orléans: Editions du Bureau de recherches géologiques et minières, Service géologique national, 1985.

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5

Thráinsson, Höskuldur, Caroline Heycock, Hjalmar P. Petersen, and Zakaris Svabo Hansen, eds. Syntactic Variation in Insular Scandinavian. Amsterdam: John Benjamins Publishing Company, 2017. http://dx.doi.org/10.1075/sigl.1.

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6

Bernstein, Jacob. Seasonality: Systems, strategies, and signals. New York: Wiley, 1998.

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7

Šmídl, Václav. The variational Bayes method in signal processing. Berlin: Springer, 2006.

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8

Kooter, Peter M. De. Variations on autocorrelation matching and the sift localization algorithm. Monterey, Calif: Naval Postgraduate School, 1997.

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9

1943-, Bergman Bo, ed. Robust design methodology for reliability: Exploring the effects of variation and uncertainty. Chichester, U.K: Wiley, 2009.

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10

Six sigma in the pharmaceutical industry: Understanding, reducing, and controlling variation in pharmaceuticals and biologics. Boca Raton, FL: CRC Press/Taylor & Francis, 2007.

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11

Maes, Dominiek, Marina Sibila, and Maria Pieters, eds. Mycoplasmas in swine. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789249941.0000.

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Abstract This book contains 14 chapters that discuss the genetics, epidemiology, prevalence, pathogenesis, clinical signs, diagnosis, treatment, prevention and control of Mycoplasma infections in pigs. Chapter 1 discusses the phylogenetics and classification of Mycoplasma species in pigs; Chapter 2 describes the genomic diversity and antigenic variation of Mycoplasma hyopneumoniae strains; Chapter 3 discusses the pathogenesis, virulence factor and pathogenicity of Mycoplasma hyopneumoniae; Chapter 4 discusses the molecular epidemiology, risk factors, transmission and prevalence of Mycoplasma hyopneumoniae, Chapter 5 discusses the clinical signs and gross lesions of Mycoplasma hyopneumoniae infection; Chapter 6 discusses immune responses against Mycoplasma infections; Chapter 7 describes the interactions of Mycoplasma hyopneumoniae with other pathogens and their economic impact; Chapter 8 discusses the diagnosis of Mycoplasma hyopneumoniae infection and its associated diseases; Chapter 9 describes the general control measures against Mycoplasma hyopneumoniae infections; Chapter 10 describes the selection and efficacy of antimicrobials against Mycoplasma hyopneumoniae infections; Chapter 11 discusses the development and efficacy of vaccines against Mycoplasma hyopneumoniae; Chapter 12 describes the eradication of Mycoplasma hyopneumoniae in pig herds; Chapter 13 describes the epidemiology, prevalence, pathogenesis, clinical signs, diagnosis, treatment, prevention and control of Mycoplasma hyorhinis and Mycoplasma hyosynoviae in pig herds and Chapter 14 discusses the epidemiology, prevalence, transmission, pathogenesis, clinical signs, diagnosis, treatment, prevention, control and economic impact of Mycoplasma suis infection in pigs.
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12

1950-, Montgomery Michael, Johnson Ellen 1959-, and University of Mississippi. Center for the Study of Southern Culture., eds. Language. Chapel Hill: University of North Carolina Press, 2007.

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13

Variation Tolerant Onchip Interconnects. Springer, 2011.

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14

Nigussie, Ethiopia Enideg. Variation Tolerant on-Chip Interconnects. Springer New York, 2014.

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15

Nigussie, Ethiopia Enideg. Variation Tolerant On-Chip Interconnects. Springer, 2011.

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16

Nigussie, Ethiopia Enideg. Variation Tolerant on-Chip Interconnects. Springer, 2011.

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17

Fulde, Michael. Variation Aware Analog and Mixed-Signal Circuit Design in Emerging Multi-Gate CMOS Technologies. Springer, 2010.

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18

Fulde, Michael. Variation Aware Analog and Mixed-Signal Circuit Design in Emerging Multi-Gate CMOS Technologies. Springer, 2012.

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19

Smídl, Václav, and Anthony Quinn. The Variational Bayes Method in Signal Processing (Signals and Communication Technology). Springer, 2005.

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20

Quinn, Anthony, and Václav Šmídl. The Variational Bayes Method in Signal Processing (Signals and Communication Technology). Springer, 2006.

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21

Ramani, Ramachandran, ed. Functional MRI. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190297763.001.0001.

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Functional MRI with BOLD (Blood Oxygen Level Dependent) imaging is one of the commonly used modalities for studying brain function in neuroscience. The underlying source of the BOLD fMRI signal is the variation in oxyhemoglobin to deoxyhemoglobin ratio at the site of neuronal activity in the brain. fMRI is mostly used to map out the location and intensity of brain activity that correlate with mental activities. In recent years, a new approach to fMRI was developed that is called resting-state fMRI. The fMRI signal from this method does not require the brain to perform any goal-directed task; it is acquired with the subject at rest. It was discovered that there are low-frequency fluctuations in the fMRI signal in the brain at rest. The signals originate from spatially distinct functionally related brain regions but exhibit coherent time-synchronous fluctuations. Several of the networks have been identified and are called resting-state networks. These networks represent the strength of the functional connectivity between distinct functionally related brain regions and have been used as imaging markers of various neurological and psychiatric diseases. Resting-state fMRI is also ideally suited for functional brain imaging in disorders of consciousness and in subjects under anesthesia. This book provides a review of the basic principles of fMRI (signal sources, acquisition methods, and data analysis) and its potential clinical applications.
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22

Schembri, Adam, and Trevor Johnston. Sociolinguistic Variation and Change in Sign Languages. Edited by Robert Bayley, Richard Cameron, and Ceil Lucas. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199744084.013.0025.

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This chapter describes sociolinguistic variation and change in sign languages, the natural language of deaf communities. Factors that drive sociolinguistic variation and change in both spoken- and signed-language communities are broadly similar. Social factors include, for example, a signer’s age group, region of origin, gender, ethnicity, and socioeconomic status. Linguistic factors include phonological processes such as assimilation and reduction, and grammaticalization. Deaf signing communities are invariably minority communities embedded within larger majority communities whose languages are in another entirely different modality, and which may have written systems and extensive written literatures, unlike sign languages. The chapter exemplifies sociolinguistic variation in signed languages at the levels of phonology, lexicon, and grammar.
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23

Hirschberg, Julia. Pragmatics and Prosody. Edited by Yan Huang. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199697960.013.28.

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Variation in prosody can influence the interpretation of linguistic phenomena in many languages. Type and location of prosodic prominence and prosodic phrase boundaries, differences in overall fundamental frequency (f0) contours, and changes in intensity, duration, and speaking rate can serve to inform hearers about syntactic attachment, disambiguate scope of modifiers and negation, signal information status, indicate type of speech act or propositional attitude, and contribute to the licensing of implicatures and to reference resolution. This chapter discusses aspects of prosodic variation and pragmatic meaning which have been explored in linguistics, computational linguistics, and psycholinguistics. It begins by describing some commonly used frameworks for representing prosody, including the ToBI framework, which is used to identify prosodic variation throughout. The pragmatic influence of prosody on the interpretation of syntactic, semantic, and discourse phenomena is then examined. It concludes by suggesting new avenues for research in the relationship between prosody and pragmatic interpretation.
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24

Quinn, Anthony, and Václav Šmídl. The Variational Bayes Method in Signal Processing. Springer, 2010.

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25

The Variational Bayes Method in Signal Processing. Berlin/Heidelberg: Springer-Verlag, 2006. http://dx.doi.org/10.1007/3-540-28820-1.

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26

Bernstein, Jake. Seasonality: Systems, Strategies, and Signals (Wiley Trading). Wiley, 1998.

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27

Wackerhage, Henning, Jonathon Smith, and Darren Wisniewski. Molecular exercise physiology. Edited by Neil Armstrong and Willem van Mechelen. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198757672.003.0031.

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Molecular exercise physiology is the study of exercise physiology using molecular biology methods. The development of differentiated cell types is regulated by transcription factors like the muscle-making MyoD that specifies cell type, while others regulate the development of muscle, tendons, and bones. Maternal nutrition and exercise commonly affect embryonic development through epigenetic mechanisms. Adaptation to exercise involves sensor proteins detecting exercise-related signals, the processing of signals by signalling proteins and networks, and the regulation of the actual adaptations by effector proteins. Many sport- and exercise-related traits depend on both common and rare DNA sequence variations, including the muscle mass-increasing myostatin (GDF8) loss-of-function and the haematocrit-increasing EPOR gain-of-function mutations. Additionally, common DNA sequence variations contribute to the inherited variability of development, body height, strength, and endurance. Finally, in addition to ethical concerns, current genetic performance tests only explain a fraction of the variation of sport and exercise-related traits.
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28

Rose, Mary, Robert Bayley, Clayton Valli, and Ceil Lucas. Sociolinguistic Variation in American Sign Language. Gallaudet University Press, 2001.

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29

Kucharski, Fred, and Muhammad Adnan Abid. Interannual Variability of the Indian Monsoon and Its Link to ENSO. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.615.

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The interannual variability of Indian summer monsoon is probably one of the most intensively studied phenomena in the research area of climate variability. This is because even relatively small variations of about 10% to 20% from the mean rainfall may have dramatic consequences for regional agricultural production. Forecasting such variations months in advance could help agricultural planning substantially. Unfortunately, a perfect forecast of Indian monsoon variations, like any other regional climate variations, is impossible in a long-term prediction (that is, more than 2 weeks or so in advance). The reason is that part of the atmospheric variations influencing the monsoon have an inherent predictability limit of about 2 weeks. Therefore, such predictions will always be probabilistic, and only likelihoods of droughts, excessive rains, or normal conditions may be provided. However, even such probabilistic information may still be useful for agricultural planning. In research regarding interannual Indian monsoon rainfall variations, the main focus is therefore to identify the remaining predictable component and to estimate what fraction of the total variation this component accounts for. It turns out that slowly varying (with respect to atmospheric intrinsic variability) sea-surface temperatures (SSTs) provide the dominant part of the predictable component of Indian monsoon variability. Of the predictable part arising from SSTs, it is the El Niño Southern Oscillation (ENSO) that provides the main part. This is not to say that other forcings may be neglected. Other forcings that have been identified are, for example, SST patterns in the Indian Ocean, Atlantic Ocean, and parts of the Pacific Ocean different from the traditional ENSO region, and springtime snow depth in the Himalayas, as well as aerosols. These other forcings may interact constructively or destructively with the ENSO impact and thus enhance or reduce the ENSO-induced predictable signal. This may result in decade-long changes in the connection between ENSO and the Indian monsoon. The physical mechanism for the connection between ENSO and the Indian monsoon may be understood as large-scale adjustment of atmospheric heatings and circulations to the ENSO-induced SST variations. These adjustments modify the Walker circulation and connect the rising/sinking motion in the central-eastern Pacific during a warm/cold ENSO event with sinking/rising motion in the Indian region, leading to reduced/increased rainfall.
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30

Ceil, Lucas, Bayley Robert James, and Valli Clayton, eds. The sociolinguistic variation in American Sign Language. Washongton, DC: Gallaudet University Press, 2001.

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31

Sociolinguistic Variation in American Sign Language (Gallaudet Sociolinguistics). Gallaudet University Press, 2001.

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32

Farag, Aly A. Biomedical Image Analysis: Statistical and Variational Methods. Cambridge University Press, 2014.

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33

Farag, Aly A. Biomedical Image Analysis: Statistical and Variational Methods. Cambridge University Press, 2014.

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34

Farag, Aly A. Biomedical Image Analysis: Statistical and Variational Methods. Cambridge University Press, 2014.

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35

Describing Variation in American Sign Language (Linstok Press Dissertation Series). Linstok Press, Incorporated, 1994.

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36

Palfreyman, Nick. Variation in Indonesian Sign Language: A Typological and Sociolinguistic Analysis. de Gruyter GmbH, Walter, 2019.

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37

Palfreyman, Nick. Variation in Indonesian Sign Language: A Typological and Sociolinguistic Analysis. De Gruyter, Inc., 2019.

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38

Palfreyman, Nick. Variation in Indonesian Sign Language: A Typological and Sociolinguistic Analysis. De Gruyter, Inc., 2019.

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39

Steinbach, Markus, Roland Pfau, and Pamela M. Perniss. Visible Variation: Comparative Studies on Sign Language Structure. De Gruyter, Inc., 2008.

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40

Steinbach, Markus, Roland Pfau, Pamela M. Perniss, and Pamela M. Perniss. Visible Variation: Comparative Studies on Sign Language Structure. De Gruyter, Inc., 2007.

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41

1974-, Perniss Pamela, Pfau Roland, and Steinbach Markus, eds. Visible variation: Comparative studies on sign language structure. New York: Mouton de Gruyter Berlin, 2007.

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42

What's Your Sign for Pizza?: An Introduction to Variation in American Sign Language. Gallaudet University Press, 2003.

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43

Bayley, Robert, Clayton Valli, and Ceil Lucas. What's Your Sign for Pizza?: An Introduction to Variation in American Sign Language. Gallaudet University Press, 2019.

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44

Bayley, Robert, Clayton Valli, and Ceil Lucas. What's Your Sign for Pizza?: An Introduction to Variation in American Sign Language. Gallaudet University Press, 2014.

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45

National Aeronautics and Space Administration (NASA) Staff. Global and Regional Axial Ocean Angular Momentum Signals and Length-Of-Day Variations (1985-1996). Independently Published, 2018.

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46

1943-, Bergman Bo, ed. Robust design methodology for reliability: Exploring the effects of variation and uncertainty. Chichester, West Sussex, U.K: Wiley, 2009.

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47

Nakamura, Karen, Constanze Schmaling, Leila Monaghan, and Graham H. Turner. Many Ways to Be Deaf: International Variation in Deaf Communities. Gallaudet University Press, 2014.

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48

Nakamura, Karen, Constanze Schmaling, Leila Monaghan, and Graham H. Turner. Many Ways to Be Deaf: International Variation in Deaf Communities. Gallaudet University Press, 2014.

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49

Many Ways to Be Deaf: International Variation in Deaf Communities. Gallaudet University Press, 2003.

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50

Rosati, Alexandra G. Ecological variation in cognition: Insights from bonobos and chimpanzees. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198728511.003.0011.

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Bonobos and chimpanzees are closely related, yet they exhibit important differences in their wild socio-ecology. Whereas bonobos live in environments with less seasonal variation and more access to fallback foods, chimpanzees face more competition over spatially distributed, variable resources. This chapter argues that bonobo and chimpanzee cognition show psychological signatures of their divergent wild ecology. Current evidence shows that despite strong commonalities in many cognitive domains, apes express targeted differences in specific cognitive skills critical for wild foraging behaviours. In particular, bonobos exhibit less accurate spatial memory, reduced levels of patience and greater risk aversion than do chimpanzees. These results have implications for understanding the evolution of human cognition, as studies of apes are a critical tool for modelling the last common ancestor of humans with nonhuman apes. Linking comparative cognition to species’ natural foraging behaviour can begin to address the ultimate reason for why differences in cognition emerge across species. Les bonobos et les chimpanzés sont prochement liés, pourtant ils montrent d’importantes différences dans leur sociologie naturelle. Alors que les bonobos vivent dans des environnements avec peu de diversité de climat entre saisons et plus d’accès à des ressources de nourriture alternatives, les chimpanzés ménagent une compétition étalée spatialement et des ressources plus variées. Je soutiens que la cognition des chimpanzés et bonobos montre les signatures psychologiques de leur écologie naturelle divergente. Les témoignages courants montrent que, malgré les forts points communs dans en cognition, les grands singes expriment des différences au niveau de compétences cognitives importantes au butinage. En particulier, les bonobos démontrent une mémoire spatial moin précise, moin de patience, et plus d’aversion de risques que les chimpanzés. Ces résultats fournissent des signes dans l’étude de l’évolution de la cognition humaine. Les études des grands singe sont un outil d’importance majeure dans la modélisation du dernier ancêtre commun des humains et grands singes non-humains. Faire des liens cognitives comparatives entre le butinage des différentes espèces peut commencer à dévoiler les raisons pour les différences de cognition entre espèces.
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