User-generated experiences: how automated platforms for content creation and sharing has transformed information access

Esitys KDK-käytettävyystyöryhmän järjestämässä seminaarissa: Miten käyttäjien toiveet haastavat metatietokäytäntöjämme? / How users' expectations challenge our metadata practices? 30.9.2014.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Hardware Accelarated Visual Tracking Algorithms. A Systematic Literature Review

Many industrial applications need object recognition and tracking capabilities. The algorithms developed for those purposes are computationally expensive. Yet ,real time performance, high accuracy and small power consumption are essential measures of the system. When all these requirements are combined, hardware acceleration of these algorithms becomes a feasible solution. The purpose of this study is to analyze the current state of these hardware acceleration solutions, which algorithms have been implemented in hardware and what modifications have been done in order to adapt these algorithms to hardware.

Requisites for a successful implementation of an automated inventory replenishment system

Tutkimuksen tavoitteena oli selvittää automaattisten tilausjärjestelmien onnistuneen käyttöönottoon taustalla vaikuttavia tekijöitä vähittäiskaupan toimialalla ja etsiä ratkaisua kyseisten järjestelmien onnistuneeseen käyttöönottoon tässä ympäristössä. Tutkimus analysoi yli sadan kaupan järjestelmän käyttöönottoa ja käyttöönoton tuloksia. Tutkimusta varten haastateltiin niin yhtiön sisältä kuin ulkopuoleltakin mukana olleita hankintajärjestelmän ja jalkautuksen asiantuntijoita. Tämän lisäksi järjestelmän käyttöönottaneisiin kauppoihin lähetettiin kyselyt, joita analysoitiin ryhmissä automaattisen tilausjärjestelmän tietojen pohjalta. Työn tuloksena pystyttiin tunnistamaan tietty joukko taustatekijöitä, jotka tulee ottaa käyttöönotossa huomioon sekä saatuihin tutkimustuloksiin perustuen kehitettiin malli vastaavanlaisten järjestelmien käyttöönotolle vähittäiskaupan alalle.

3D Mesh Simplification. A survey of algorithms and CAD model simplification tests

Simplification of highly detailed CAD models is an important step when CAD models are visualized or by other means utilized in augmented reality applications. Without simplification, CAD models may cause severe processing and storage is- sues especially in mobile devices. In addition, simplified models may have other advantages like better visual clarity or improved reliability when used for visual pose tracking. The geometry of CAD models is invariably presented in form of a 3D mesh. In this paper, we survey mesh simplification algorithms in general and focus especially to algorithms that can be used to simplify CAD models. We test some commonly known algorithms with real world CAD data and characterize some new CAD related simplification algorithms that have not been surveyed in previous mesh simplification reviews.

Data Governance and Automated Marketing – A Case Study of Expected Benefits of Organizing Data Governance in an ICT Company

This research is looking to find out what benefits employees expect the organization of data governance gains for an organization and how it benefits implementing automated marketing capabilities. Quality and usability of the data are crucial for organizations to meet various business needs. Organizations have more data and technology available what can be utilized for example in automated marketing. Data governance addresses the organization of decision rights and accountabilities for the management of an organization’s data assets. With automated marketing it is meant sending a right message, to a right person, at a right time, automatically. The research is a single case study conducted in Finnish ICT-company. The case company was starting to organize data governance and implementing automated marketing capabilities at the time of the research. Empirical material is interviews of the employees of the case company. Content analysis is used to interpret the interviews in order to find the answers to the research questions. Theoretical framework of the research is derived from the morphology of data governance. Findings of the research indicate that the employees expect the organization of data governance among others to improve customer experience, to improve sales, to provide abilities to identify individual customer’s life-situation, ensure that the handling of the data is according to the regulations and improve operational efficiency. The organization of data governance is expected to solve problems in customer data quality that are currently hindering implementation of automated marketing capabilities.

Efficient Algorithms for Coastal Geographic Problems

The increasing performance of computers has made it possible to solve algorithmically problems for which manual and possibly inaccurate methods have been previously used. Nevertheless, one must still pay attention to the performance of an algorithm if huge datasets are used or if the problem iscomputationally difficult. Two geographic problems are studied in the articles included in this thesis. In the first problem the goal is to determine distances from points, called study points, to shorelines in predefined directions. Together with other in-formation, mainly related to wind, these distances can be used to estimate wave exposure at different areas. In the second problem the input consists of a set of sites where water quality observations have been made and of the results of the measurements at the different sites. The goal is to select a subset of the observational sites in such a manner that water quality is still measured in a sufficient accuracy when monitoring at the other sites is stopped to reduce economic cost. Most of the thesis concentrates on the first problem, known as the fetch length problem. The main challenge is that the two-dimensional map is represented as a set of polygons with millions of vertices in total and the distances may also be computed for millions of study points in several directions. Efficient algorithms are developed for the problem, one of them approximate and the others exact except for rounding errors. The solutions also differ in that three of them are targeted for serial operation or for a small number of CPU cores whereas one, together with its further developments, is suitable also for parallel machines such as GPUs.

Automated UI testing. WBCT, a computer-automated user test environment tool.

Today, the user experience and usability in software application are becoming a major design issue due to the adaptation of many processes using new technologies. Therefore, the study of the user experience and usability might be included in every software development project and, thus, they should be tested to get traceable results. As a result of different testing methods to evaluate the concepts, a non-expert on the topic might have doubts on which option he/she should opt for and how to interpret the outcomes of the process. This work aims to create a process to ease the whole testing methodology based on the process created by Seffah et al. and a supporting software tool to follow the procedure of these testing methods for the user experience and usability.