Introduction of non-topological costs in syntactic analyses: the case of Gulbenkian estate

Space syntax is a set of theories and techniques for analysing urban settlements and buildings. Focused on the study of the configuration of convex spaces, space syntax is based on the concept of topological depth, that is, in the number of steps to go from some space (or axial line) to every other space in a spatial complex. Typically, non-topological costs like stairs, ramps, accentuated slopes or walls are not considered in space syntax analyses, or are incorporated in an insufficient fashion, namely, with the arbitrary introduction of axial lines in order to increase depth. This article proposes an innovative method to deal with these costs that uses logic programming with Prolog language. In this way, it is possible to better understand the relative segregation of the Gulbenkian estate within its urban environment, the city of Odivelas near Lisbon (Portugal), noting that it was the largest public housing estate built within the scope of the resettlement plan for those displaced by the great floods of November 25-26, 1967, established by the Ministry of Public Works and the Calouste Gulbenkian Foundation in the late 1960s.info:eu-repo/semantics/publishedVersio

Penyusunan Aturan Produksi Bahasa Pengganti Query Untuk Basis Data Matakuliah Program Studi Matematika FMIPA UNY

Sebuah aplikasi pemrosesan bahasa alami dalam basis data dapat melahirkan bahasa pengganti query yang digunakan untuk mengakses informasi dari basis data tersebut. Proses pembuatan aplikasi didahului dengan penentuan tata bahasa (grammar) yang menjadi dasar pembentukan kalimat bahasa pengganti query, yang diwujudkan dalam sebuah aturan produksi. Penelitian ini bertujuan untuk membuat aturan produksi dari sebuah bahasa alami pengganti query yang ditujukan untuk mengakses informasi dari basis data matakuliah di program Studi Matematika FMIPA UNY. Proses pembuatan aturan produksi diawali dengan mengidentifikasi keteraturan kalimat-kalimat pertanyaan yang biasa muncul untuk mencari sebuah informasi dari basis data matakuliah. Berdasarkan keteraturan tersebut, dibuat pengelompokan simbol-simbol bahasa yang kemudian direpresentasikan dengan menggunakan notasi Backus Naur Form, sehingga terbentuklah sebuah aturan produksi. Selain itu, aturan produksi yang terbentuk dapat juga disajikan dalam wujud pohon penurunan kalimat. Aturan produksi untuk bahasa pengganti query dalam basis data matakuliah program studi Matematika diawali dengan symbol Æ | <bagian ditanyakan> . Symbol awal tersebut kemudian dikembangkan lebih lanjut untuk mendapatkan tata bahasa yang lebih lengkap. Kata Kunci: Aturan Produksi, Bahasa Pengganti Query, Basis Data Matakulia

Logic programming in the context of multiparadigm programming: the Oz experience

Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (logic, functional, constraint, object-oriented, sequential, concurrent, etc.) with equal ease. This article has two goals: to give a tutorial of logic programming in Oz and to show how logic programming fits naturally into the wider context of multiparadigm programming. Our experience shows that there are two classes of problems, which we call algorithmic and search problems, for which logic programming can help formulate practical solutions. Algorithmic problems have known efficient algorithms. Search problems do not have known efficient algorithms but can be solved with search. The Oz support for logic programming targets these two problem classes specifically, using the concepts needed for each. This is in contrast to the Prolog approach, which targets both classes with one set of concepts, which results in less than optimal support for each class. To explain the essential difference between algorithmic and search programs, we define the Oz execution model. This model subsumes both concurrent logic programming (committed-choice-style) and search-based logic programming (Prolog-style). Instead of Horn clause syntax, Oz has a simple, fully compositional, higher-order syntax that accommodates the abilities of the language. We conclude with lessons learned from this work, a brief history of Oz, and many entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic Programming

PROLOG-CC: um sistema pericial difuso aplicado à ciência do solo

As técnicas da inteligência artificial são ferramentas computacionais apropriadas para modelar processos de transformação que ocorrem na natureza. Tal fato sugere o desenvolvimento de um sistema pericial suportado pelo paradigma da programação em lógica, baseado em regras com raciocínio difuso, possibilitando captar o conhecimento dos peritos. O sistema pericial proposto neste artigo consiste em regras que simulam o conhecimento e o processo de raciocínio do perito humano. São descritos os processos de codificação, inferência e descodificação de um sistema pericial difuso aplicável à análise de fertilidade dos solos. A estimativa do valor final é calculada mediante o mecanismo de agregação de regras denominado Descodificador de Peso Ordenado – DPO. Este sistema pericial é um protótipo que pode ser expandido para sistemas de maior complexidade como, por exemplo, a engenharia de biossistemas, visando automatizar as análises periciais.Artificial intelligence techniques are appropriate computational tools for modelling transformation processes that occur in nature. That fact alone suggests the development of an expert system supported by the logic programming paradigm, based on fuzzy reasoning rules, which enables expert knowledge encoding. The expert system proposed in this paper consists of rules that simulate the knowledge and reasoning processes of an human expert. We describe the encoding, inference and decoding processes of a fuzzy expert system that applies to the analysis of soil fertility. The estimated final value is calculated through the mechanism of rule aggregation called Ordered Weight Decoder - OWD. This expert system is a prototype that can be extended to more complex systems such as, for example, biosystems engineering, aiming to automate the expert analysis

Optimizing inequality joins in Datalog with approximated constraint propagation

Datalog systems evaluate joins over arithmetic (in)equalities as a naive generate-and-test of Cartesian products. We exploit aggregates in a source-to-source transformation to reduce the size of Cartesian products and to improve performance. Our approach approximates the well-known propagation technique from Constraint Programming. Experimental evaluation shows good run time speed-ups on a range of non-recursive as well as recursive programs. Furthermore, our technique improves upon the previously reported in the literature constraint magic set transformation approach

Approximating Constraint Propagation in Datalog

We present a technique exploiting Datalog with aggregates to improve the performance of programs with arithmetic (in)equalities. Our approach employs a source-to-source program transformation which approximates the propagation technique from Constraint Programming. The experimental evaluation of the approach shows good run time speed-ups on a range of non-recursive as well as recursive programs. Furthermore, our technique improves upon the previously reported in the literature constraint magic set transformation approach.Comment: Online Proceedings of the 11th International Colloquium on Implementation of Constraint LOgic Programming Systems (CICLOPS 2011), Lexington, KY, U.S.A., July 10, 201