Th. Univ.--Informatique--Paris 6, 1988. / Bibliogr. p. 241-244. Résumé en français.

Program manipulation is the task to perform transformations on program code, and is normally done in order to optimize the code with respect of the utilization of some computer resource. Partial evaluation is the task when partial computations can be performed in a program before it is actually executed. If a parameter to a procedure is constant a specialized version of that procedure can be generated if the constant is inserted instead of the parameter in the procedure body and as much computations in the code as possible are performed. A system is described which works on programs written in INTERLISP, and which performs partial evaluation together with other transformations such as beta-expansion and certain other optimization operations. The system works on full LISP and not only for a "pure" LISP dialect, and deals with problems occurring there involving side-effects, variable assignments etc. An analysis of a previous system, REDFUN, results in a list of problems, desired extensions and new features. This is used as a basis for a new design, resulting in a new implementation, REDFUN-2. This implementation, design considerations, constraints in the system, remaining problems, and other experience from the development and experiments with the system are reported in this paper.

This diploma thesis deals with ways how to represent results of LISp-Miner application on the world wide web. This thesis has three main sections. The first section is dedicated to description of data analysis process including description of newly established study of infography and its application in publishing results found du-ring the DZD process. The second part describes exporting of LISp-Miner as well as exporting formats of each module and its combining with other technologies, afterwards follows summarization of all kind of exports of lispminer and its im-provements or create a whole new templates. Third part is dedicated to develop-ment of a web-based application as a tool of repsentation results generated by lispminer. The very last part is contained of future improvements of this application.

The aim of this work is to describe steps associated with solving analytical questions using the LISp-Miner in the data from water-analyzes of 12 ponds in South Bohemia in the period from year 2007 to 2012. Analytical questions are primarily focused on issues of cyanobacteria, based on instructions of data-owner, Povodí Vltavy, státní podnik. Apart from a description of the application of procedures KL-Miner, CF-Miner and 4ft-Miner on data, the work aims to prepare an automating process based on steps made during using procedures. The theoretical part is a summary of the basic concepts and principles associated with association rules and GUHA method. The practical part follows the CRISP-DM methodology. The result is a proposal of automation process by which it is possible to look for interesting rules in the hydrobiological and hydrochemical data. Then there is a set of recommendations for better utilization of database for KDD, with proposals how to modify and prepare the data.

This thesis deals with data analysis using methods of knowledge discovery in databases. The goal is to select appropriate methods and tools for implementation of a specific project based on real data from Alza.cz product department. Data analysis is performed by using association rules and decision rules in the Lisp-Miner and decision trees in the RapidMiner. The methodology used is the CRISP-DM. The thesis is divided into three main sections. First section is focused on the theoretical summary of information about KDD. There are defined basic terms and described the types of tasks and methods of KDD. In the second section is introduced the methodology CRISP-DM. The practical part firstly introduces company Alza.cz and its goals for this task. Afterwards, the basic structure of the data and preparation for the next step (data mining) is described. In conclusion, the results are evaluated and the possibility of their use is outlined.

The aim of this thesis is to analyze the real data from the restaurant sector in the center of Prague, prove assumptions based on existing knowledge and explore hidden relations. The database management system MySQL was used for the initial transformation of the original data structure. The data after the transformation were converted into a form that it was possible to manipulate with it using the procedure LMDataSource of the system LISp-Miner. The analysis of association of relations were used for the procedure 4ft-Miner of the system LISp-Miner. The MySQL database system was used for the frequency analysis to obtain results, and Microsoft Word and Excel were used to interpret the results. Some of the assumptions in the research were found proven. Furthermore, an interesting combination of relations was discovered. The output of this work allows the owner of the data to use some of the data analysis results for the optimization of internal processes. In addition, this study points out other possible ways to analyze these data.

This thesis is focused on the area of automated data mining and to describe steps associated with solving analytical questions using the LISp-Miner system in the data with road accident records. Analytical tasks were primarily created based on domene knowledge from road accidents statistics in Great Britain and from previous analysis in my semestral project. The aim of this thesis is creation of an automated data mining process for analyze the input data by applying 4ft-Miner, Ac4ft-Miner a SD4ft-Miner procedures, and looking for a new knowledge for every single year of the analyzed period. The implementation language is the LMCL language that enables usage of the LISp-Miner system's functionality in an automated way. These created scripts could be used for analyses of another dataset with the same structure or with some manual changes in initial parameters for the quite different data.

In past years, great attention has been paid to evolutionary algorithms and they have been utilized in wide range of industries including data mining field, which nowadays presents a highly demanded product for many commercial institutions. Both mentioned topics are combined in this work. Main thesis subject is testing of new Reverse-Miner module, which can generate data with hidden properties using evolutionary algorithms while using also other modules of LISp-Miner system, commonly used for the purposes of data mining. Main goal lies in generation of two databases by the module in such way so they would meet explicitly set requirements. Other goals are also set within the thesis in the form of understanding the domain necessary for subsequent modeling. The result of the practical part of the thesis is represented not only by two successfully generated databases, but also by description of steps, methods and techniques used. The common recommendations for data preparation by module Reverse-Miner are later summarized, based on experience with modeling. Previous thesis outputs are furthermore contemplating the conclusion of analysis of technical means used for generation and they also provide several suggestions for possible future extensions.

This thesis is focused on the area of automated data mining. The aim of this thesis is a description of the area of automated data mining, creation of a design of an automated data mining tasks creation process for verification of set domain knowledge and new knowledge search, and also an implementation of verification of set domain knowledge of attribute dependency type influence with search space adjustments. The implementation language is the LMCL language that enables usage of the LISp-Miner system's functionality in an automated way. These data analyses were performed on data from air pollution monitoring. The design and implementation were successful and the created scripts could be used (with some manual changes in initial parameters) for analyses of another dataset as well.

La dépendance des différentes infrastructures vis-à-vis du réseau Internet va croissant. D’abord la convergence des médias mais bientôt l’Internet des objets ou les véhicules autonomes peut-être vont contribuer à augmenter la criticité d’Internet. Il est donc important de résoudre les problèmes liés à l’infrastructure actuelle, en terme de passage à l’échelle, de confidentialité ou bien de fiabilité. Les communications multichemins font partie des possibilités pour attaquer ce défi. Pour autant la transition vers ces technologies n’est pas sans difficulté. En effet certains équipements bloquent les protocoles inconnus, empêchant ainsi l’émergence de nouvelles technologies. C’est un phénomène en partie responsable de l’ossification d’internet. D’autres considérations techniques limitent l’intérêt de recourir à des technologies multichemins dans certains cas, puisque celles-ci peuvent alors présenter des performances moindres que les technologies monochemins. Dans le cadre de cette thèse, nous proposons des réponses à certains de ces cas afin de maximiser le spectre d’application des technologies multichemins, en particulier du protocole Multipath TCP (MPTCP). Plus précisémement, après une revue détaillée du domaine des communications multichemins, nous proposons une réponse au problème de découverte des chemins. De plus, motivés par l’intuition que les ordonnanceurs peuvent s’appuyer sur les latences unidirectionelles, afin de lutter contre l’arrivé de paquets dans le désordre, nous proposons une technique qui ne modifie que l’envoyeur de données pour estimer cette métrique. En outre, nous proposons un outil qui maximise le débit tout en prenant en compte des politiques utilisateur par exemple pour forcer l’envoi d’une partie du trafic sur un chemin peu performant mais qui va coûter moins cher à l’utilisateur. Finalement, nous développons et évaluons un modèle de MPTCP. / The criticity of the Internet keeps increasing with a very high number of services depending on its infrastructure. The Internet is expected to support services with an increasing tangible impact on the physical world such as the Internet of Things (IoT) or autonomous vehicles. It is thus important to address the current infrastructure shortcomings in terms of scalability, confidentiality and reliability. Multipath communications are one possible solution to address this challenge. The transition towards multipath technologies is not obvious, there are several challenges ahead. Some network devices block unknown protocols, thus preventing the emergence of new technologies, which plays a part in what is often referred to as the ossification of the Internet. Moreover, due to technical reasons, there are cases for which multipath technologies perform worse than their single path counterpart. In this thesis, we are interested in addressing some of these cases and limit their impact, so that multipath communications perform better than single path communications as often as possible. More specifically, we propose enhancements to Multipath TCP (MPTCP). After a detailed survey of multipath communications across all layers, we propose an answer as to the question of how many paths to use and how to ensure proper forwarding. Moreover, motivated by the intuition that packet arrival disorder can be mitigated by the knowledge of one way latencies, we propose a latency estimator with sender-side modifications only. Furthermore, as throughput maximization is in general solved regardless of the interface cost or user preferences, we elaborate a framework capable of presenting more complex strategies if for instance the user wants to enforce throughput even on less efficient paths. Finally, we develop and present a complete simulation model of MPTCP.