6 resultados para fuzzy shape configuration

em Brock University, Canada


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View of the progress of the Mackenzie Chown Complex several months into construction.

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The main objective of this research was to examine the relationship between surface electromyographic (SEMG) spike activity and force. The secondary objective was to determine to what extent subcutaneous tissue impacts the high frequency component of the signal, as well as, examining the relationship between measures of SEMG spike shape and their traditional time and frequency analogues. A total of96 participants (46 males and 50 females) ranging in age (18-35 years), generated three 5-second isometric step contractions at each force level of 40, 60, 80, and 100 percent of maximal voluntary contraction (MVC). The presentation of the contractions was balanced across subjects. The right arm of the subject was positioned in the sagittal plane, with the shoulder and elbow flexed to 90 degrees. The elbow rested on a support in a neutral position (mid pronation/mid supination) and placed within a wrist cuff, fastened below the styloid process. The wrist cuff was attached to a load cell (JR3 Inc., Woodland, CA) recording the force produced. Biceps brachii activity was monitored with a pair of Ag/AgCI recording electrodes (Grass F-E9, Astro-Med Inc., West Warwick, RI) placed in a bipolar configuration, with an interelectrode distance (lED) of 2cm distal to the motor point. Data analysis was performed on a I second window of data in the middle of the 5-second contraction. The results indicated that all spike shape measures exhibited significant (p < 0.01) differences as force increase~ from 40 to 100% MVC. The spike shape measures suggest that increased motor unit (MU) recruitment was responsible for increasing force up to 80% MVC. The results suggested that further increases in force relied on MU III synchronization. The results also revealed that the subcutaneous tissue (skin fold thickness) had no relationship (r = 0.02; P > 0.05) with the mean number of peaks per spike (MNPPS), which was the high frequency component of the signal. Mean spike amplitude (MSA) and mean spike frequency (MSF) were highly correlated with their traditional measures root mean square (RMS) and mean power frequency (MPF), respectively (r = 0.99; r = 0.97; P < 0.01).

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Heyting categories, a variant of Dedekind categories, and Arrow categories provide a convenient framework for expressing and reasoning about fuzzy relations and programs based on those methods. In this thesis we present an implementation of Heyting and arrow categories suitable for reasoning and program execution using Coq, an interactive theorem prover based on Higher-Order Logic (HOL) with dependent types. This implementation can be used to specify and develop correct software based on L-fuzzy relations such as fuzzy controllers. We give an overview of lattices, L-fuzzy relations, category theory and dependent type theory before describing our implementation. In addition, we provide examples of program executions based on our framework.

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Indwelling electromyography (EMG) has great diagnostic value but its invasive and often painful characteristics make it inappropriate for monitoring human movement. Spike shape analysis of the surface electromyographic signal responds to the call for non-invasive EMG measures for monitoring human movement and detecting neuromuscular disorders. The present study analyzed the relationship between surface and indwelling EMG interference patterns. Twenty four males and twenty four females performed three isometric dorsiflexion contractions at five force levels from 20% to maximal force. The amplitude measures increased differently between electrode types, attributed to the electrode sensitivity. The frequency measures were different between traditional and spike shape measures due to different noise rejection criteria. These measures were also different between surface and indwelling EMG due to the low-pass tissue filtering effect. The spike shape measures, thought to collectively function as a means to differentiate between motor unit characteristics, changed independent of one another.

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Classical relational databases lack proper ways to manage certain real-world situations including imprecise or uncertain data. Fuzzy databases overcome this limitation by allowing each entry in the table to be a fuzzy set where each element of the corresponding domain is assigned a membership degree from the real interval [0…1]. But this fuzzy mechanism becomes inappropriate in modelling scenarios where data might be incomparable. Therefore, we become interested in further generalization of fuzzy database into L-fuzzy database. In such a database, the characteristic function for a fuzzy set maps to an arbitrary complete Brouwerian lattice L. From the query language perspectives, the language of fuzzy database, FSQL extends the regular Structured Query Language (SQL) by adding fuzzy specific constructions. In addition to that, L-fuzzy query language LFSQL introduces appropriate linguistic operations to define and manipulate inexact data in an L-fuzzy database. This research mainly focuses on defining the semantics of LFSQL. However, it requires an abstract algebraic theory which can be used to prove all the properties of, and operations on, L-fuzzy relations. In our study, we show that the theory of arrow categories forms a suitable framework for that. Therefore, we define the semantics of LFSQL in the abstract notion of an arrow category. In addition, we implement the operations of L-fuzzy relations in Haskell and develop a parser that translates algebraic expressions into our implementation.

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Lattice valued fuzziness is more general than crispness or fuzziness based on the unit interval. In this work, we present a query language for a lattice based fuzzy database. We define a Lattice Fuzzy Structured Query Language (LFSQL) taking its membership values from an arbitrary lattice L. LFSQL can handle, manage and represent crisp values, linear ordered membership degrees and also allows membership degrees from lattices with non-comparable values. This gives richer membership degrees, and hence makes LFSQL more flexible than FSQL or SQL. In order to handle vagueness or imprecise information, every entry into an L-fuzzy database is an L-fuzzy set instead of crisp values. All of this makes LFSQL an ideal query language to handle imprecise data where some factors are non-comparable. After defining the syntax of the language formally, we provide its semantics using L-fuzzy sets and relations. The semantics can be used in future work to investigate concepts such as functional dependencies. Last but not least, we present a parser for LFSQL implemented in Haskell.