the blind digital signature protocols play important role in e-commerce applications. In this paper the new blind digital signature scheme with 384-bit signature length is proposed. the latter is achieved by using fin...
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Post-traumatic stress disorder (PTSD) can be a debilitating condition and early intervention can be instrumental in preventing patients' suffering. Identifying patients at risk for PTSD is challenging because of t...
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ISBN:
(纸本)9781450376990
Post-traumatic stress disorder (PTSD) can be a debilitating condition and early intervention can be instrumental in preventing patients' suffering. Identifying patients at risk for PTSD is challenging because of the limitations of the available data set, variations in the symptoms of PTSD for different patients, and misdiagnosis due to symptoms being shared with other conditions. In this preliminary study, we explore a small set of structured primary care data extracted from patients' electronic medical records (EMR) from Manitoba, Canada. this data has a small subset of PTSD positive cases, and is used to assess the feasibility of applying machine learning algorithms to diagnose PTSD. We developed three supervised machine learning models, a multilayered perceptron artificial neural network (ANN) model, a support vector machine (SVM), and a random forest classifier (RF) to identify PTSD patients using 890 patients' records. these methods obtained 0.79, 0.78, and 0.83 AUC respectively, which are better than all of the previous work that used EMR data having comparable size as our data. this study is geared towards understanding the primary care standard for PTSD patients in Canada in general and military-veteran population and developing a case definition for PTSD. this initial result demonstrates that an automated PTSD screening tool can be developed based on historical medical data for further study. In our ongoing work, we are exploring the providers' chart notes from the EMR data, which is unstructured text data, to improve the model accuracy and understand the progression of PTSD.
this paper extends the framework for merging sociologically inspired rational cognitive models of decision making with social media inspired feedback mechanisms. this model, with certain simplifying assumptions, is us...
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the proceedings contain 21 papers. the special focus in this conference is on Mechanisation of Relational Reasoning and Relational Scaling and Preferences. the topics include: A Relation-algebraic approach to graph st...
ISBN:
(纸本)3540003150
the proceedings contain 21 papers. the special focus in this conference is on Mechanisation of Relational Reasoning and Relational Scaling and Preferences. the topics include: A Relation-algebraic approach to graph structure transformation;emptiness relations in property systems;pregroups;dynamic view;interpretability of first-order dynamic logic in a relational calculus;relations in GUHA style data mining;groups in allegories;distributed conceptual structures;fuzzy relational images in computer science;a completeness theorem for extended order dependencies on relational attribute models in dedekind categories;double residuated lattices and their applications;interval bilattices and some other simple bilattices;interactive systems;relational constructions in goguen categories;a subintuitionistic logic and some of its methods;implementation of relational algebra using binary decision diagrams;calculating a relational program for transitive reductions of strongly connected graphs;calculating church-rosser proofs in kleene algebra;on the definition and representation of a ranking and tangent circle algebras.
In this paper we do a systematic investigation of continuous methods for pixel, line pixel and line dejittering. the basis for these investigations are the discrete line dejittering algorithm of Nikolova and the parti...
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this paper presents the comparison of different acoustic adaptation methods in a multilingual speech recognition environment. Baseline multilingual acoustic models were generated using the tree based clustering with c...
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Automatic and accurate brain tumor segmentation from MR images is one of the important problems in cancer research. However, the lack of shape prior and weak contrast at boundary make unsupervised brain tumor segmenta...
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Software libraries for Exact Real Arithmetic implement the theory of computability on non-denumerable sets. Usually they are based on interval arithmetic. We discuss enhancements where the interval arithmetic is augme...
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the proceedings contain 24 papers. the special focus in this conference is on Implementation and Application of Automata. the topics include: Using finite state technology in natural language processing of Basque;subm...
ISBN:
(纸本)3540004009
the proceedings contain 24 papers. the special focus in this conference is on Implementation and Application of Automata. the topics include: Using finite state technology in natural language processing of Basque;submodule construction and supervisory control;counting the solutions of presburger equations without enumerating them;finite automata for compact representation of language models in NLP;scheduling hard sporadic tasks by means of finite automata and generating functions;bounded-graph construction for noncanonical discriminating-reverse parsers;finite-state transducer cascade to extract proper names in texts;compilation methods of minimal acyclic finite-state automata for large dictionaries;improving raster image run-length encoding using data order;enhancements of partitioning techniques for image compression u sing weighted finite automata;on the size of deterministic finite automata;minimal adaptive pattern-matching automata for efficient term rewriting;typographical nearest-neighbor search in a finite-state lexicon and its application to spelling correction;on the software design of cellular automata simulators for ecological modeling and supernondeterministic finite automata.
this paper reinforces numerical iterated integration developed by Muhammad–Mori in the following two points: (1) the approximation formula is modified so that it can achieve a better convergence rate in more general ...
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