Control Mechanisms on #-Context-Free Array Grammars

Author(s):  
Rudolf FREUND
2021 ◽  
Vol 181 (2-3) ◽  
pp. 239-271
Author(s):  
Artiom Alhazov ◽  
Rudolf Freund ◽  
Sergiu Ivanov ◽  
Marion Oswald

We extend and refine previous results within the general framework for regulated rewriting based on the applicability of rules in sequential grammars [3]. Besides the well-known control mechanisms as control graphs, matrices, permitting and forbidden rules, partial order on rules, and priority relations on rules we also consider the new variant of activation and blocking of rules as investigated in [1, 2, 4]. Moreover, we exhibit special results for strings and multisets as well as for arrays in the general variant defined on Cayley grids of finitely presented groups. Especially we prove that array grammars defined on Cayley grids of finitely presented groups using #-context-free array productions together with control mechanisms as control graphs, matrices, permitting and forbidden rules, partial order on rules, priority relations on rules, or activation and blocking of rules have the same computational power as such array grammars using arbitrary array productions.


2001 ◽  
Vol 120 (5) ◽  
pp. A502-A502
Author(s):  
R GAUTHIER ◽  
J DROLET ◽  
J REED ◽  
A VEZINA ◽  
P VACHON

2011 ◽  
Author(s):  
Frederick Verbruggen ◽  
Rachel Adams ◽  
Chris Chambers

1966 ◽  
Vol 05 (03) ◽  
pp. 142-146
Author(s):  
A. Kent ◽  
P. J. Vinken

A joint center has been established by the University of Pittsburgh and the Excerpta Medica Foundation. The basic objective of the Center is to seek ways in which the health sciences community may achieve increasingly convenient and economical access to scientific findings. The research center will make use of facilities and resources of both participating institutions. Cooperating from the University of Pittsburgh will be the School of Medicine, the Computation and Data Processing Center, and the Knowledge Availability Systems (KAS) Center. The KAS Center is an interdisciplinary organization engaging in research, operations, and teaching in the information sciences.Excerpta Medica Foundation, which is the largest international medical abstracting service in the world, with offices in Amsterdam, New York, London, Milan, Tokyo and Buenos Aires, will draw on its permanent medical staff of 54 specialists in charge of the 35 abstracting journals and other reference works prepared and published by the Foundation, the 700 eminent clinicians and researchers represented on its International Editorial Boards, and the 6,000 physicians who participate in its abstracting programs throughout the world. Excerpta Medica will also make available to the Center its long experience in the field, as well as its extensive resources of medical information accumulated during the Foundation’s twenty years of existence. These consist of over 1,300,000 English-language _abstract of the world’s biomedical literature, indexes to its abstracting journals, and the microfilm library in which complete original texts of all the 3,000 primary biomedical journals, monitored by Excerpta Medica in Amsterdam are stored since 1960.The objectives of the program of the combined Center include: (1) establishing a firm base of user relevance data; (2) developing improved vocabulary control mechanisms; (3) developing means of determining confidence limits of vocabulary control mechanisms in terms of user relevance data; 4. developing and field testing of new or improved media for providing medical literature to users; 5. developing methods for determining the relationship between learning and relevance in medical information storage and retrieval systems’; and (6) exploring automatic methods for retrospective searching of the specialized indexes of Excerpta Medica.The priority projects to be undertaken by the Center are (1) the investigation of the information needs of medical scientists, and (2) the development of a highly detailed Master List of Biomedical Indexing Terms. Excerpta Medica has already been at work on the latter project for several years.


1986 ◽  
Vol 56 (02) ◽  
pp. 151-154 ◽  
Author(s):  
Christina A Mitchell ◽  
Lena Hau ◽  
Hatem H Salem

SummaryThrombin has been shown to cleave the vitamin K dependent cofactor protein S with subsequent loss of its cofactor activity. This study examines the control mechanisms for thrombin cleavage of protein S.The anticoagulant activity of activated protein C (APC) is enhanced fourteen fold by the addition of protein S. Thrombin cleaved protein S is seven fold less efficient than the native protein, and this loss of activity is due to reduced affinity of cleaved protein S for APC or the lipid surface compared to the intact protein.In the absence of Ca++, protein S is very sensitive to minimal concentrations of thrombin. As little as 1.5 nM thrombin results in complete cleavage of 20 nM protein S in 10 min and loss of cofactor activity. Ca++, in concentrations greater than 0.5 mM, will inhibit this cleavage and in the presence of physiological Ca++ concentrations, no cleavage of protein S could be demonstrated in spite of high concentrations of thrombin (up to 1 μM) and prolonged incubations (up to two hours). The endothelial surface protein thrombomodulin is very efficient in inhibiting the cleavage of protein S by thrombin suggesting that any thrombin formed on the endothelial cell surface is unlikely to cleave protein S, thus allowing the intact protein to act as a cofactor to APC.We conclude that the inhibitory effects of Ca++ and thrombomodulin on thrombin mediated cleavage of protein S imply that this event, by itself, is unlikely to represent a physiological control of the activity of protein S.


2020 ◽  
Vol 39 (6) ◽  
pp. 8463-8475
Author(s):  
Palanivel Srinivasan ◽  
Manivannan Doraipandian

Rare event detections are performed using spatial domain and frequency domain-based procedures. Omnipresent surveillance camera footages are increasing exponentially due course the time. Monitoring all the events manually is an insignificant and more time-consuming process. Therefore, an automated rare event detection contrivance is required to make this process manageable. In this work, a Context-Free Grammar (CFG) is developed for detecting rare events from a video stream and Artificial Neural Network (ANN) is used to train CFG. A set of dedicated algorithms are used to perform frame split process, edge detection, background subtraction and convert the processed data into CFG. The developed CFG is converted into nodes and edges to form a graph. The graph is given to the input layer of an ANN to classify normal and rare event classes. Graph derived from CFG using input video stream is used to train ANN Further the performance of developed Artificial Neural Network Based Context-Free Grammar – Rare Event Detection (ACFG-RED) is compared with other existing techniques and performance metrics such as accuracy, precision, sensitivity, recall, average processing time and average processing power are used for performance estimation and analyzed. Better performance metrics values have been observed for the ANN-CFG model compared with other techniques. The developed model will provide a better solution in detecting rare events using video streams.


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