L-Fuzzy Structured Query Language

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.

Deviance of syntax in oral languages and oral reading behavior

The major hypothesis of this paper is that any deviance in syntax present in oral language will be evident in oral r eading behaviour. Using Lee and Canter's Developmental i 1 Sentence Scoring technique (1971) and Y. Goodman and Burke's Reading Miscue Inventory (1972) linguistic competence was established in t hree male children. ages 10 to 11. patterns of strengths and weaknesses in reading were determined. and the relationships t hat were established, were examined. Results of the study i ndicate that oral language behaviour is closely tied to oral r eading behaviour. This type of approach can be used as a basis for a diagnosis of a reading difficulty and then a prescription for language and reading skills.

The 19th Century Tombstone Database Project Records, 1790-1890 (non-inclusive)

The 19th Century Tombstone Database project was funded by the program Federal Summer Youth Employment scheme in the summer of 1982 and led by Dr. David W. Rupp, a Professor at the Classics Department, Brock University. The main goal of the project was to collect information related to various cemeteries in Niagara region and burials that took place from 1790-1890. Data was collected and presented in the form of data summary forms of persons, tombstone sketches, photographs of tombstones, maps, and computer printouts. The materials created as a result of a research completed for the 19th Century Tombstone Database project are important as a number of the tombstones have been damaged or gone missing since the research was finished. Before Dr. Rupp retired from Brock University, he donated project materials to the Brock University Special Collections and Archives.

Is Library Database Searching a Language Learning Activity?

A qualitative research study that asked international students how they thought of words to enter into a library database to see if language learning was also involved.

An Abstract Algebraic Theory of L-Fuzzy Relations for Relational Databases

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.