Automatic compiler/interpreter generation from programs for domain-specific languages using semantic inference : doktorska disertacijaŽeljko Kovačević
, 2022, doktorska disertacija
Opis: Presented doctoral dissertation describes a research work on Semantic Inference, which can be regarded as an extension of Grammar Inference. The main task of Grammar Inference is to induce a grammatical structure from a set of positive samples (programs), which can sometimes also be accompanied by a set of negative samples. Successfully applying Grammar Inference can result only in identifying the correct syntax of a language. But, when valid syntactical structures are additionally constrained with context-sensitive information the Grammar Inference needs to be extended to the Semantic Inference. With the Semantic Inference a further step is realised, namely, towards inducing language semantics. In this doctoral dissertation it is shown that a complete compiler/interpreter for small Domain-Specific Languages (DSLs) can be generated automatically solely from given programs and their associated meanings using Semantic Inference. For the purpose of this research work the tool LISA.SI has been developed on the top of the compiler/interpreter generator tool LISA that uses Evolutionary Computations to explore and exploit the enormous search space that appears in Semantic Inference. A wide class of Attribute Grammars has been learned. Using Genetic Programming approach S-attributed and L-attributed have been inferred successfully, while inferring Absolutely Non-Circular Attribute Grammars (ANC-AG) with complex dependencies among attributes has been achieved by integrating a Memetic Algorithm (MA) into the LISA.SI tool.
Ključne besede: Grammatical Inference, Semantic Inference, Genetic Programming, Attribute Grammars, Memetic Algorithm, Domain-Specific Languages
Objavljeno v DKUM: 17.02.2022; Ogledov: 477; Prenosov: 75
Celotno besedilo (3,59 MB)
Visualization of alpha-beta game tree search : magistrsko deloEmilija Taseva
, 2019, diplomsko delo
Opis: Algorithms make up a crucial part of computer science studies. Learning and understanding new algorithms can be quite interesting, but also hard and complex, especially for students. Visualization can significantly help with the understanding of the dynamic behaviour of algorithms by visually displaying each step of the algorithm, its purpose and how it changes the data. Besides faster and more efficient learning, the better understanding can also lead to potential algorithm improvements in the future. The goal of this thesis is visualization of the alpha-beta tree search algorithm for determining the next optimal move in a two-player, zero-sum, complete information game. The algorithm is visualized using two games, Tic-Tac-Toe and Othello. The algorithm operation can also be demonstrated using a custom tree with parameters chosen by the user.
Ključne besede: algorithm visualization, minimax algorithm, alpha-beta pruning, adversarial search
Objavljeno v DKUM: 08.11.2019; Ogledov: 766; Prenosov: 59
Celotno besedilo (1,52 MB)
Določanje sekvence DNK na osnovi Eulerjeve poti z uporabo izboljšanega Hierholzerjevega algoritma : magistrsko deloFilip Mesarić
, 2019, magistrsko delo
Opis: In the master’s thesis we created the algorithm for DNA sequencing based on an Eulerian path
and the improved Hierholzer’s algorithm. The theoretical part explains the graph theory,
existing Eulerian path searching algorithms and Hierholzer's algorithmic implementations.
Additionally, the theoretical part presents DNA sequencing and its most popular methods. The
practical part focuses on the development of an application that shows DNA sequencing based
on an Eulerian path and the improved Hierholzer's algorithm. The results represent an
improvement of sequencing, taking into consideration time and distance measurements, for
our implementation in comparison with the existing Hierholzer’s algorithm.
Ključne besede: DNA, Eulerian path, Hierholzer’s algorithm, DNA sequencing
Objavljeno v DKUM: 15.07.2019; Ogledov: 876; Prenosov: 98
Celotno besedilo (1,33 MB)
Use of a simulation environment and metaheuristic algorithm for human resource management in a cyber-physical systemHankun Zhang
, Borut Buchmeister
, S. Liu
, Robert Ojsteršek
, 2019, samostojni znanstveni sestavek ali poglavje v monografski publikaciji
Ključne besede: simulation modelling, evolutionary computation, cyber-physical system, heuristic kalman algorithm, human resource management
Objavljeno v DKUM: 06.06.2019; Ogledov: 983; Prenosov: 306
Celotno besedilo (1,41 MB)
Implementation aspects of a BDD package supporting general decision diagrams : Revisited slides of a lecture given at JKU Linz on September 19th 2016Robert Meolic
, 2016, predavanje na tuji univerzi
Opis: General decision diagram is a loose term for a superset of different types of decision diagrams - we are interested in joining BDDs, FDDs, and different types of suppressed DDs, e.g. ZBDDs. I will present: The current state of our BDD package Biddy (functionalities and details about the original implementation aspects). Our ideas for efficient implementation of ZBDDs (which could be used for all types of suppressed DDs).New type od decision diagrams called ZFDD (somehow symmetric to ZBDD). A rough draft about the implementation of a package supporting general decision diagrams.
Ključne besede: Binary Decision Diagram, Zero-suppressed Binary Decision Diagram, Boolean function, Algorithm, BDD package, Biddy
Objavljeno v DKUM: 26.10.2017; Ogledov: 2319; Prenosov: 93
Celotno besedilo (1,07 MB)
Intra-minute cloud passing forecasting based on a low cost iot sensor - a solution for smoothing the output power of PV power plantsPrimož Sukič
, Gorazd Štumberger
, 2017, izvirni znanstveni članek
Opis: Clouds moving at a high speed in front of the Sun can cause step changes in the output power of photovoltaic (PV) power plants, which can lead to voltage fluctuations and stability problems in the connected electricity networks. These effects can be reduced effectively by proper short-term cloud passing forecasting and suitable PV power plant output power control. This paper proposes a low-cost Internet of Things (IoT)-based solution for intra-minute cloud passing forecasting. The hardware consists of a Raspberry PI Model B 3 with a WiFi connection and an OmniVision OV5647 sensor with a mounted wide-angle lens, a circular polarizing (CPL) filter and a natural density (ND) filter. The completely new algorithm for cloud passing forecasting uses the green and blue colors in the photo to determine the position of the Sun, to recognize the clouds, and to predict their movement. The image processing is performed in several stages, considering selectively only a small part of the photo relevant to the movement of the clouds in the vicinity of the Sun in the next minute. The proposed algorithm is compact, fast and suitable for implementation on low cost processors with low computation power. The speed of the cloud parts closest to the Sun is used to predict when the clouds will cover the Sun. WiFi communication is used to transmit this data to the PV power plant control system in order to decrease the output power slowly and smoothly.
Ključne besede: photovoltaic power plant, cloud passing forecasting, algorithm, sensor, Raspberry Pi, camera, wide-angle lens, optical filters, internet of things
Objavljeno v DKUM: 20.07.2017; Ogledov: 2069; Prenosov: 389
Celotno besedilo (8,15 MB)
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Linear recognition of generalized Fibonacci cubes $Q_h (111)$Yoomi Rho
, Aleksander Vesel
, 2016, izvirni znanstveni članek
Opis: The generalized Fibonacci cube $Q_h(f)$ is the graph obtained from the $h$-cube $Q_h$ by removing all vertices that contain a given binary string $f$ as a substring. In particular, the vertex set of the 3rd order generalized Fibonacci cube $Q_h(111)$ is the set of all binary strings $b_1b_2 ... b_h$ containing no three consecutive 1’s. We present a new characterization of the 3rd order generalized Fibonacci cubes based on their recursive structure. The characterization is the basis for an algorithm which recognizes these graphs in linear time.
Ključne besede: graph theory, Fibonacci cubes, recognition algorithm
Objavljeno v DKUM: 10.07.2017; Ogledov: 836; Prenosov: 150
Celotno besedilo (803,81 KB)
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A question-based design pattern advisement approachLuka Pavlič
, Vili Podgorelec
, Marjan Heričko
, 2014, izvirni znanstveni članek
Opis: Design patterns are a proven way to build flexible software architectures. But the selection of an appropriate design pattern is a difficult task in practice, particularly for less experienced developers. In this paper, a question based design pattern advisement approach will be proposed. This approach primarily assists developers in identifying and selecting the most suitable design pattern for a given problem. We will also propose certain extensions to the existing Object-Oriented Design Ontology (ODOL). In addition to the advisement procedure, a new design pattern advisement ontology will be defined. We have also developed a tool that supports the proposed ontology and question-based advisement (OQBA) approach. The conducted controlled experiment and two surveys have shown that the proposed approach is beneficial to all software developers, especially to those who have less experience with design patterns.
Ključne besede: design patterns, pattern selection, ontology, semantic web, selection algorithm
Objavljeno v DKUM: 06.07.2017; Ogledov: 1130; Prenosov: 380
Celotno besedilo (621,06 KB)
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