Probabilistic Graphical Models on Multi-Core CPUs using Java 8

In this paper, we discuss software design issues related to the development of parallel computational intelligence algorithms on multi-core CPUs, using the new Java 8 functional programming features. In particular, we focus on probabilistic graphical models (PGMs) and present the parallelisation of a collection of algorithms that deal with inference and learning of PGMs from data. Namely, maximum likelihood estimation, importance sampling, and greedy search for solving combinatorial optimisation problems. Through these concrete examples, we tackle the problem of defining efficient data structures for PGMs and parallel processing of same-size batches of data sets using Java 8 features. We also provide straightforward techniques to code parallel algorithms that seamlessly exploit multi-core processors. The experimental analysis, carried out using our open source AMIDST (Analysis of MassIve Data STreams) Java toolbox, shows the merits of the proposed solutions.Comment: Pre-print version of the paper presented in the special issue on Computational Intelligence Software at IEEE Computational Intelligence Magazine journa

Secure pseudo-random linear binary sequences generators based on arithmetic polynoms

We present a new approach to constructing of pseudo-random binary sequences (PRS) generators for the purpose of cryptographic data protection, secured from the perpetrator's attacks, caused by generation of masses of hardware errors and faults. The new method is based on use of linear polynomial arithmetic for the realization of systems of boolean characteristic functions of PRS' generators. "Arithmetizatio" of systems of logic formulas has allowed to apply mathematical apparatus of residue systems for multisequencing of the process of PRS generation and organizing control of computing errors, caused by hardware faults. This has guaranteed high security of PRS generator's functioning and, consequently, security of tools for cryptographic data protection based on those PRSs

An expectation-maximization algorithm for probabilistic reconstructions of full-length isoforms from splice graphs.

Reconstructing full-length transcript isoforms from sequence fragments (such as ESTs) is a major interest and challenge for bioinformatic analysis of pre-mRNA alternative splicing. This problem has been formulated as finding traversals across the splice graph, which is a directed acyclic graph (DAG) representation of gene structure and alternative splicing. In this manuscript we introduce a probabilistic formulation of the isoform reconstruction problem, and provide an expectation-maximization (EM) algorithm for its maximum likelihood solution. Using a series of simulated data and expressed sequences from real human genes, we demonstrate that our EM algorithm can correctly handle various situations of fragmentation and coupling in the input data. Our work establishes a general probabilistic framework for splice graph-based reconstructions of full-length isoforms

Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN

Parties, Committees, and Rules in the U.S. House of Representatives

This dissertation project aims to build upon the literature of positive theories of legislative politics, and provide three more nuanced stories about various stages in the U.S. House of Representatives: rules making, committee composition, and floor voting. The chapter, Conditional Nature of Rules Changes, examines why the U.S. House of Representatives has changed its standing rules regarding the principle of majority rule and minority rights. I begin by taking a critical look at previous studies on this subject, after which I propose an alternative theory on the conditional nature of rules changes. The empirical findings reveal that different combinations of factors are required for the two distinct types of rules changes. In particular, the size and homogeneity of the majority party are the main factors for promoting majority rule while the size of the majority party and the dimensionality of policy space are the main factors for creating minority rights. The chapter, Minority Party Members on Committees, questions why a generic legislature allows minority party members on committees. If the majority party considers the minority a burden, then it could choose to exclude minority party members entirely from the committee system. This has, however, rarely happened in history. This chapter provides one possible explanation to this puzzle via a simple signaling game. In equilibrium, I show that the majority party has an incentive to include the minority party delegation on the committee. By allowing the minority to make a public speech on the uncertainty, the majority leadership can constrain the majority committee delegation in a way to serve the party in general: the majority committee delegation, in equilibrium, moderates the bill proposal in order to respond to the minority\u27s public speech. The chapter, Special Rules and Dimensionality, is one of the first attempts to investigate the determinants for dimensionality of individual bills. I first develop a theory on partisan manipulation of dimensionality by focusing especially on the role of restrictive special rules in the House of Representatives: party leaders try to reduce the dimensionality of individual bills in order to have clear party image and to avoid ugly defeats. I collect every piece of major legislation identified by Clinton and Lapinski: 2006), and record the contents of their special rules. Ultimately, the data demonstrate that restrictive rules contribute to lower dimensionality

Decision-Shaping From the Outside: Measuring and explaining the degree of preference attainment in the EEA EFTA Comments

The membership of Iceland, Liechtenstein and Norway in the European Economic Area (EEA) has often been suggested to entail a democratic deficit. These three European Free Trade Association (EFTA) members have to implement a significant share of EU legislation without having representation in the EU institutions. Nevertheless, even without formal voting rights, they may be able to influence EU policy-making. In particular, the EEA agreement ensure the EEA EFTA States the right to be consulted on relevant issues. Accordingly, the three states frequently submit joint comments on policy issues, what is known as the EEA EFTA Comments. However, the importance of these comments, and more generally the EEA EFTA States’ influence on EU policy, has been generally overlooked in the literature. To start filling this important gap, this thesis aims to measuring and explaining the level success in the EEA EFTA Comments. Building on third country and interest group influence theory, I suggest an exchange model for the influence of the EEA EFTA States, expecting area-specific resources, issue controversy and the preferences of the decision-makers to determine preference attainment. To answer the research questions, the thesis employs a multi-method approach. I measure the preference attainment for 273 individual positions found in 80 comments submitted between 1995 and 2019 on draft legislative proposals, analyse the factors of preference attainment using logistic regression and complement my quantitative analysis with interviews with officials from the EFTA Secretariat and EEA EFTA States. The results show that the preferences are fully attained in 39.6 percent and partly attained in 18 percent of the positions. The regression analyses provide support for the hypothesised effect of area-specific resources, indicating that attainment is more likely on energy- and maritime-related issues. The thesis helps to understand the previously under-researched joint efforts of EEA EFTA States to influence EU policy-making.MasteroppgaveSAMPOL350MASV-SAP

Who says what to whom? Alignments and arguments in EU policy-making

In the EU multilevel polity, domestic interest groups seek to shape EU legislation by accessing both national and EU institutions. Previous studies indicated that institutional and issue contexts, as well as organizational characteristics shape their strategies of interest representation. However, we know much less about how alignments and arguments impact on their participation in EU and national policy consultations. Addressing this gap, we investigate the lobbying strategies of almost 2,900 national interest organizations from five member states (Germany, the Netherlands, Slovenia, Sweden, and the United Kingdom) on 20 EU directive proposals bringing also a new empirical scope to the study of multilevel interest representation. The findings indicate that alignments and arguments shape the participation of domestic interest groups in consultations on EU policies. We infer from our study that some general predictions of interest group behaviour are overstretched and outline four variations of interest representation routines

Measuring the Effect of Social Background on Judicial Decision-Making in Tax Cases

Judicial decision-making is an important part of the law-making process. The positive research of judicial decision-making is expanding, and its normative significance is undeniable. Even so, judicial decision-making in tax cases has not yet received much empirical attention. This study contributes to the existing literature, empirically evaluating if, and to what extent, non-legal factors affect the outcomes of tax cases. It examines the potential effects of judges’ social backgrounds and adds to the rather small but growing empirical literature on tax litigation. I coded the dependent variable—the judge’s level of acceptance of the taxpayer’s claim, meaning whether the judge sides with the taxpayer and overrules the IRS’s decisions—as an ordinal variable rather than the more common binary coding of the prevailing party. Binary coding can often be arbitrary, resulting in loss of information and misestimation. By allowing for an intermediate category of the prevailing party, in addition to the traditional binary options, the variable transforms to an ordinal measure of the judge’s acceptance level of the taxpayer’s claim. This study finds that in the Israeli setting, judges’ gender, seniority, age at the time of appointment, and age at the time of the decision affect judges’ decisions and subsequently the law