Tallinn University of Technology

About: Tallinn University of Technology is a education organization based out in Tallinn, Estonia. It is known for research contribution in the topics: European union & Computer science. The organization has 3688 authors who have published 10313 publications receiving 145058 citations. The organization is also known as: Tallinn Technical University & Tallinna Tehnikaülikool.

The Role of Private Actors in Public Sector Innovation

Abstract: The changing forms of governance stemming from the rise of New Public Management (NPM) and New Public Governance (NPG) have brought about significant changes in the relationship between the public and private sectors (Christensen and Laegreid 2007; Torfing and Triantafillou 2013). Not only have we witnessed a gradual increase in the involvement of private actors in the provision of public services, but we have also seen an upsurge of new forms of public–private interaction based on quasi-markets, partnerships and networks.This development, which has unfolded over the past four decades, entails two parallel but distinct trends. First, the gradual replacement of public with private solutions across a broad range of services, such as health, eldercare, employment services and childcare, many of which are services that have traditionally been seen as the family silver of the modern welfare state. While this trend has developed incrementally, it has nonetheless resulted in significant transfers of activities from the public to the private domain (Petersen and Hjelmar 2013). Second, we have witnessed the emergence of a growing number of innovation-oriented forms of public–private interaction under catchy titles such as ‘public–private partnerships’ (PPPs) (Hodge and Greve 2005), ‘public procurement of innovation’ (Lember, Kattel and Kalvet 2014), ‘innovative contracting out’ (Lindholst and Bogetoft 2011) and ‘public–private innovation partnerships’ (Brogaard and Petersen 2014). Today, perhaps more than ever before, there is a search for new forms of public–private collaboration that have the potential for delivering efficient public services, enhancing innovation and safeguarding public value in its widest sense (Moore 1995).This chapter examines how governments can enhance public sector innovation by utilizing new as well as old forms of public–private interaction that mobilizes the knowledge, competencies and resources of the private sector. We focus on three major yet distinct forms of public and private interplay: contracting out, public procurement and public–private partnerships (PPPs). The aim is to examine how these widely used interaction forms fit into the emerging NPG paradigm and how they can contribute to enhanced innovation, learning and collaboration under the evolving NPG framework.As outlined by the editors in Chapter 1 of the book, innovation and learning are embedded into collective action and institutions governing the public–private collaboration.

Detection and Evaluation of Driver Distraction Using Machine Learning and Fuzzy Logic

Abstract: In addition to vehicle control, drivers often perform secondary tasks that impede driving. Reduction of driver distraction is an important challenge for the safety of intelligent transportation systems. In this paper, a methodology for the detection and evaluation of driver distraction while performing secondary tasks is described and an appropriate hardware and a software environment is offered and studied. The system includes a model of normal driving, a subsystem for measuring the errors from the secondary tasks, and a module for total distraction evaluation. A new machine learning algorithm defines driver performance in lane keeping and speed maintenance on a specific road segment. To recognize the errors, a method is proposed, which compares normal driving parameters with ones obtained while conducting a secondary task. To evaluate distraction, an effective fuzzy logic algorithm is used. To verify the proposed approach, a case study with driver-in-the-loop experiments was carried out, in which participants performed the secondary task, namely chatting on a cell phone. The results presented in this research confirm its capability to detect and to precisely measure a level of abnormal driver performance.

Random Forest for Gene Expression Based Cancer Classification: Overlooked Issues

Abstract: Random forest is a collection (ensemble) of decision trees. It is a popular ensemble technique in pattern recognition. In this article, we apply random forest for cancer classification based on gene expression and address two issues that have been so far overlooked in other works. First, we demonstrate on two different real-world datasets that the performance of random forest is strongly influenced by dataset complexity. When estimated before running random forest, this complexity can serve as a useful performance indicator and it can explain a difference in performance on different datasets. Second, we show that one should rely with caution on feature importance used to rank genes: two forests, generated with the different number of features per node split, may have very similar classification errors on the same dataset, but the respective lists of genes ranked according to feature importance can be weakly correlated.

Dark diversity in dry calcareous grasslands is determined by dispersal ability and stress-tolerance

Abstract: Temperate calcareous grasslands are characterized by high levels of species richness at small spatial scales. Nevertheless, many species from a habitat-specific regional species pool may be absent from local communities and represent the dark diversity' of these sites. Here we investigate dry calcareous grasslands in northern Europe to determine what proportion of the habitat-specific species pool is realized at small scales (i.e. how the community completeness varies) and which mechanisms may be contributing to the relative sizes of the observed and dark diversity. We test whether the absence of particular species in potentially suitable grassland sites is a consequence of dispersal limitation and/or a low ability to tolerate stress (e.g. drought and grazing). We analysed a total of 1223 vegetation plots (1 x 1 m) from dry calcareous grasslands in Sweden, Estonia and western Russia. The species co-occurrence approach was used to estimate the dark diversity for each plot. We calculated the maximum dispersal distance for each of the 291 species in our dataset by using simple plant traits (dispersal syndrome, growth form and seed characteristics). Large seed size was used as proxy for small seed number; tall plant height and low S-strategy type scores were used to characterise low stress-tolerance. Levels of small-scale community completeness were relatively low (more species were absent than present) and varied between the grasslands in different geographic areas. Species in the dark diversity were generally characterized by shorter dispersal distances and greater seed weight (fewer seeds) than species in the observed diversity. Species within the dark diversity were generally taller and had a lower tolerance of stressful conditions. We conclude that, even if temperate grasslands have high levels of small-scale plant diversity, the majority of potentially suitable species in the regional species pool may be absent as a result of dispersal limitation and low stress-tolerance. (Less)