Paralleelmehhanismide kinetostaatiliste jõudlusindeksite uuring ning võrdlus

Nii kaua, kui on kasutusel olnud robotid, on käinud teadusuuringud nende kasutamiseks ning töö optimeerimiseks meie igapäevases elus. Samal ajal, kui meie teadmised robotite teemal on suuresti arenenud, on kasvanud ka vastavate struktuuride keerukus. Seega on arendatud mitmeid meetodeid ja indekseid, aitamaks disaneritel ning inseneridel välja selgitada parimad seadmed vastavate ülesannete lahendamiseks. Lisaks on huvi paralleelmehhanismide suunas viimaste aastate jooksul märgatavalt kasvanud. Peamiseks põhjuseks on paljudes valdkondades märgatavalt parem sooritusvõime võrreldes seriaalmanipulaatoritega. Ometi pole arendatud veel ühtegi globaalset jõudlusindeksit, mis võimaldaks täpsuse perspektiivis paralleelmanipulaatorite omavahelise võrdluse. Käesoleva lõputöö fookuseks on kintestaatilise jõuldusindeksi arendustööst ülevaate pakkumine. Uuritav indeks peab robustselt suutma hinnata läbi vastava indeksi paralleelmanipulaatorite täpsust.For as long as we have used robots there has also been ongoing research to allow us to use and improve efficiency of automation in our daily lives. As our knowledge about robots has largely improved, so has the complexity of their structures. Thus, various methods and indices have been developed to help designers and engineers determine the best manipulator for a specific task. In addition, the interest towards parallel manipulators has seen growth in the last couple of years due to significantly better performance in various areas in comparison to serial mechanisms. However, no global performance index to evaluate accuracy and allow comparison in that perspective between parallel mechanisms has been developed. This thesis focuses on giving an overview on the developments towards finding a robust kinematic sensitivity index to measure accuracy performance of parallel manipulators

Reverse k Nearest Neighbor Search over Trajectories

GPS enables mobile devices to continuously provide new opportunities to improve our daily lives. For example, the data collected in applications created by Uber or Public Transport Authorities can be used to plan transportation routes, estimate capacities, and proactively identify low coverage areas. In this paper, we study a new kind of query-Reverse k Nearest Neighbor Search over Trajectories (RkNNT), which can be used for route planning and capacity estimation. Given a set of existing routes DR, a set of passenger transitions DT, and a query route Q, a RkNNT query returns all transitions that take Q as one of its k nearest travel routes. To solve the problem, we first develop an index to handle dynamic trajectory updates, so that the most up-to-date transition data are available for answering a RkNNT query. Then we introduce a filter refinement framework for processing RkNNT queries using the proposed indexes. Next, we show how to use RkNNT to solve the optimal route planning problem MaxRkNNT (MinRkNNT), which is to search for the optimal route from a start location to an end location that could attract the maximum (or minimum) number of passengers based on a pre-defined travel distance threshold. Experiments on real datasets demonstrate the efficiency and scalability of our approaches. To the best of our best knowledge, this is the first work to study the RkNNT problem for route planning.Comment: 12 page

An incremental database access method for autonomous interoperable databases

We investigated a number of design and performance issues of interoperable database management systems (DBMS's). The major results of our investigation were obtained in the areas of client-server database architectures for heterogeneous DBMS's, incremental computation models, buffer management techniques, and query optimization. We finished a prototype of an advanced client-server workstation-based DBMS which allows access to multiple heterogeneous commercial DBMS's. Experiments and simulations were then run to compare its performance with the standard client-server architectures. The focus of this research was on adaptive optimization methods of heterogeneous database systems. Adaptive buffer management accounts for the random and object-oriented access methods for which no known characterization of the access patterns exists. Adaptive query optimization means that value distributions and selectives, which play the most significant role in query plan evaluation, are continuously refined to reflect the actual values as opposed to static ones that are computed off-line. Query feedback is a concept that was first introduced to the literature by our group. We employed query feedback for both adaptive buffer management and for computing value distributions and selectivities. For adaptive buffer management, we use the page faults of prior executions to achieve more 'informed' management decisions. For the estimation of the distributions of the selectivities, we use curve-fitting techniques, such as least squares and splines, for regressing on these values

Gromita: A Fully Integrated Graphical User Interface to Gromacs 4

Gromita is a fully integrated and efficient graphical user interface (GUI) to the recently updated molecular dynamics suite Gromacs, version 4. Gromita is a cross-platform, perl/tcl-tk based, interactive front end designed to break the command line barrier and introduce a new user-friendly environment to run molecular dynamics simulations through Gromacs. Our GUI features a novel workflow interface that guides the user through each logical step of the molecular dynamics setup process, making it accessible to both advanced and novice users. This tool provides a seamless interface to the Gromacs package, while providing enhanced functionality by speeding up and simplifying the task of setting up molecular dynamics simulations of biological systems. Gromita can be freely downloaded from http://bio.demokritos.gr/gromita/

VIEWCACHE: An incremental pointer-base access method for distributed databases. Part 1: The universal index system design document. Part 2: The universal index system low-level design document. Part 3: User's guide. Part 4: Reference manual. Part 5: UIMS test suite

The goal of the Universal Index System (UIS), is to provide an easy-to-use and reliable interface to many different kinds of database systems. The impetus for this system was to simplify database index management for users, thus encouraging the use of indexes. As the idea grew into an actual system design, the concept of increasing database performance by facilitating the use of time-saving techniques at the user level became a theme for the project. This Final Report describes the Design, the Implementation of UIS, and its Language Interfaces. It also includes the User's Guide and the Reference Manual