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Monitoring of timing constraints and streaming events with temporal uncertaintiesLee, Chan-gun 28 August 2008 (has links)
Not available / text
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Joint source-channel distortion modeling for image and video communicationSabir, Muhammad Farooq 28 August 2008 (has links)
Not available / text
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Cooperative Behaviors BetweenTwo Teaming RTS Bots in StarCraftKarlsson, Robin January 2015 (has links)
Context. Video games are a big entertainment industry. Many video games let players play against or together. Some video games also make it possible for players to play against or together with computer controlled players, called bots. Artificial Intelligence (AI) is used to create bots. Objectives. This thesis aims to implement cooperative behaviors between two bots and determine if the behaviors lead to an increase in win ratio. This means that the bots should be able to cooperate in certain situations, such as when they are attacked or when they are attacking. Methods. The bots win ratio will be tested with a series of quantitative experiments where in each experiment two teaming bots with cooperative behavior will play against two teaming bots without any cooperative behavior. The data will be analyzed with a t-test to determine if the data are statistical significant. Results and Conclusions. The results show that cooperative behavior can increase performance of two teaming Real Time Strategy bots against a non-cooperative team with two bots. However, the performance could either be increased or decreased depending on the situation. In three cases there were an increase in performance and in one the performance was decreased. In three cases there was no difference in performance. This suggests that more research is needed for these cases.
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A quantitative real-time PCR assay for Ehrlichia ruminantium using pCS20Steyn, HC, Pretorius, A, McCrindle, CME 10 April 2008 (has links)
Heartwater is a tick borne disease that affects ruminants and wild animals in Africa south of the Sahara. It is caused by
Ehrlichia ruminantium and transmitted by the tick Amblyomma hebraeum. The protocols currently used to detect heartwater
take several days to complete. Here, we describe the development of a pCS20 quantitative real-time PCRTaqMan probe assay to
detect E. ruminantium in livestock blood and ticks from the field. The assay is based on the conserved pCS20 gene region of E.
ruminantium that contains two overlapping genes, rnc and ctaG [Collins, N.E., Liebenberg, J., De Villiers, E.P., Brayton, K.A.,
Louw, E., Pretorius, A., Faber, F.E., Van Heerden, H., Josemans, A., Van Kleef, M., Steyn, H.C., Van Strijp, M.F., Zweygarth, E.,
Jongejan, F., Maillard, J.C., Berthier, D., Botha, M., Joubert, F., Corton, C.H., Thomson, N.R., Allsopp, M.T., Allsopp, B.A.,
2005. The genome of the heartwater agent Ehrlichia ruminantium contains multiple tandem repeats of actively variable copy
number. PNAS 102, 838–843]. The pCS20 quantitative real-time PCRTaqMan probe was compared to the currently used pCS20
PCR and PCR/32P-probe test with regards to sensitivity, specificity and the ability to detect DNA in field samples and in blood
from experimentally infected sheep. This investigation showed that the pCS20 quantitative real-time PCRTaqMan probe was the
most sensitive assay detecting seven copies of DNA/ml of cell culture. All three assays, however, cross react with Ehrlichia canis
and Ehrlichia chaffeensis. The pCS20 real-time PCR detected significantly more positive field samples. Both the PCR and
pCS20 real-time PCR could only detect E. ruminantium parasites in the blood of experimentally infected sheep during the febrile
reaction. The PCR/32P-probe assay, however, detected the parasite DNA 1 day before and during the febrile reaction. Thus,
because this new quantitative pCS20 real-time PCRTaqMan probe assay was the most sensitive and can be performed within 2 h
it is an effective assay for epidemiological surveillance and monitoring of infected animals.
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View update and temporal correctness in real-time database systemsCheng, Chun-kong., 鄭振剛. January 2000 (has links)
published_or_final_version / abstract / toc / Computer Science and Information Systems / Master / Master of Philosophy
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On-line deadline scheduling under relaxed metrics of optimality杜家強, To, Kar-keung. January 2000 (has links)
published_or_final_version / abstract / toc / Computer Science and Information Systems / Doctoral / Doctor of Philosophy
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Broad Range Real Time Polymerase Chain Reaction as Diagnostic Method for Septic Synovitis in HorsesElmas, Colette Remziye 13 September 2012 (has links)
The purpose of this study was first to describe the clinical findings, case management and short-term outcome of horses with septic synovial structures over the last 25 years, and to identify risk factors and treatment modalities associated with specific short-term outcomes. Secondly, we wanted to evaluate a broad range real time polymerase chain reaction (RT PCR) assay for the diagnosis of septic synovitis from synovial fluid (SF) samples of horses, and compare its performance to currently available diagnostic methods.
For the retrospective study, 367 cases met the inclusion criteria. Lavage of the synovial structure and endoscopic surgery were associated with an increased likelihood of discharge from hospital, however, none of the local antimicrobial delivery modalities were associated with a significant change in outcome. No significant improvement in hospital outcome of horses with septic synovitis was identified over the past 25 years.
For the RT PCR study, 48 SF samples from horses with suspected septic synovitis were included, and RT PCR and microbial culture was performed on all samples. One additional RT PCR assay was performed on samples with discordant results or identification of dissimilar organisms. Thirty-eight percent of SF samples had positive culture results, and 42% of SF samples had positive RT PCR results. Sensitivity and specificity for the RT PCR assay relative to agreement of observers on the likelihood of infection were 87% and 72%, respectively, whereas for culture they were 56% and 86%, respectively (P=0.001). The combination of culture and RT PCR assay resulted in sensitivity and specificity of 85% and 81%, respectively.
The broad range RT PCR assay was more sensitive than culture for identification of horses with septic synovitis. Further refinement of the RT PCR assay technique may facilitate use in a clinical setting. / Equine Guelph, University of Guelph
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Detection and quantification of Cryptosporidium oocysts in environmental samplesDuggal, Megha 30 August 2013 (has links)
A PCR Differentiation Method, a hybrid of the US EPA and MOE methods, for quantifying human infectious C. parvum/C. hominis as a group and non-human infectious C. andersoni/C. muris was developed. Primers and probe sets targeting the hsp70 gene were designed for C. andersoni/C. muris; those for C. parvum/C. hominis were obtained from the MOE method. Results showed that C, andersoni/C. muris primers were specific for C. andersoni/C. muris oocysts, while those for C. parvum/hominis primers detected C. parvum/hominis and C. meleagridis. All primers were then used to quantify oocysts from urban and agricultural environmental water samples in Kitchener/Waterloo. Human infectious Giardia lamblia was also incorporated into this study. C. parvum/C. hominis and Giardia lamblia were detected at urban and agricultural areas, whereas C. andersoni/C. muris was only detected at agricultural sites. The PCR Differentiation Method is a reliable method for quantifying Cryptosporidium and Giardia lamblia in environmental water samples. / Best in Science Program of the Ontario Ministry of the Environment, Natural Sciences and Engineering Council (NSERC) of Canada Discovery Grants
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Mining, Modeling, and Analyzing Real-Time Social TrailsKamath, Krishna Y 16 December 2013 (has links)
Real-time social systems are the fastest growing phenomena on the web, enabling millions of users to generate, share, and consume content on a massive scale. These systems are manifestations of a larger trend toward the global sharing of the real-time interests, affiliations, and activities of everyday users and demand new computational approaches for monitoring, analyzing, and distilling information from the prospective web of real-time content.
In this dissertation research, we focus on the real-time social trails that reflect the digital footprints of crowds of real-time web users in response to real-world events or online phenomena. These digital footprints correspond to the artifacts strewn across the real-time web like posting of messages to Twitter or Facebook; the creation, sharing, and viewing of videos on websites like YouTube; and so on. While access to social trails could benefit many domains there is a significant research gap toward discovering, modeling, and leveraging these social trails. Hence, this dissertation research makes three contributions:
• The first contribution of this dissertation research is a suite of efficient techniques for discovering non-trivial social trails from large-scale real-time social systems. We first develop a communication-based method using temporal graphs for discovering social trails on a stream of conversations from social messaging systems like instant messages, emails, Twitter directed or @ messages, SMS, etc. and then develop a content-based method using locality sensitive hashing for discovering content based social trails on a stream of text messages like Tweet stream, stream of Facebook messages, YouTube comments, etc.
• The second contribution of this dissertation research is a framework for modeling and predicting the spatio-temporal dynamics of social trails. In particular, we develop a probabilistic model that synthesizes two conflicting hypotheses about the nature of online information spread: (i) the spatial influence model, which asserts that social trails propagates to locations that are close by; and (ii) the community affinity influence model, which asserts that social trail prop- agates between locations that are culturally connected, even if they are distant.
• The third contribution of this dissertation research is a set of methods for social trail analytics and leveraging social trails for prognostic applications like real-time content recommendation, personalized advertising, and so on. We first analyze geo-spatial social trails of hashtags from Twitter, investigate their spatio-temporal dynamics and then use this analysis to develop a framework for recommending hashtags. Finally, we address the challenge of classifying social trails efficiently on real-time social systems.
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Support for multi-weight object, invocations and atomicity in real-time systemsGheith, Ahmed M. January 1990 (has links)
No description available.
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