Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Region-matching Approach Based on Disparity Gradient

According to disparity gradient theory, the paper presents a fast region-matching approach. Differing with some region matching algorithms, its matching search range is variable . The approach’s strategy : First, according to different identity, matching pixels' search range will be educed. Second, region-matching will be processed and disparity map will be done. The experiment result indicates that the proposed algorithm is the higher matching speed and the less calculation than the ones based on invariable search range.
Estimating the Impacts of Area Regeneration Programmes in Scotland on Health and Unemployment: a quasi-experimental approach

The last three decades have seen significant investment in area-based initiatives in the UK to regenerate areas experiencing multiple disadvantage. However, there is a dearth of robust evidence on the impacts that area regeneration has on residents’ lives. This is particularly so in the case of the Scottish Area Regeneration Partnership (SARP) Programmes initiated in the mid-1990s, the original evaluation of which was beset by a lack of baseline data and poor data collection through the life of the programmes. This study investigated if residents who lived in SARP areas had improved health and employment outcomes compared to individuals living in similarly disadvantaged areas that had not been subject to regeneration over a ten-year period (1991-2001). A quasi experiment was undertaken using data from the Scottish Longitudinal Study. Propensity score matching was used to identify comparator areas and a Difference in Differences analysis was conducted to investigate the impacts of the SARP programmes for three outcomes: limiting long-term illness, hospital admissions and unemployment. No positive (or negative) programme impact was found on any of the outcomes assessed. Thus, residents in SARP areas over the study period did not see their health and employment prospects improve compared with residents in similarly disadvantaged non-regeneration comparator areas.
Controlling Voice Source Parameters to Transform Characteristics of Synthetic Voices

The success of the speech communication process depends not only on the intelligibility of the speech transmitted to the listener but also on how the message is spoken. An important aspect that carries underlying information in speech besides the linguistic content is the type of voice. Humans change instinctively or intentionally their voice depending on their mood, the environment, the listener, the feelings they want to transmit, etc. In order to take advantage of this valuable aspect of speech in applications of synthetic voices for spoken communication is necessary that the computer can produce a high variability of voices and that it can predict an appropriate voice based on environmental cues, including feedback information about the listener. This work fits into the subject of modelling and transforming acoustic aspects of speech for controlling the type of synthetic voice. The goal is to accurately model an important acoustic component of speech related to voice characteristics which is aspiration noise. This noise signal results from the turbulence of air passing through the glottis during human speech production. It can be represented by an amplitude modulated Gaussian noise, which depends on the glottal volume velocity and glottal area. For example, this modulation effect is more important in breathy voice than modal because the vocal folds usually do not completely close for breathy unlike modal.
Adaptive Robust Header Compression Algorithm in LTE System

Adopting full IP,LTE system has higher data rate and system capacity than the wireless system ever before. In order to make better use of wireless bandwidth resources,LTE has applied agile and reliable ROHC to deal with overlarge wireless packet header. Due to the dynamic changes of the wireless environment,channel quality changes at any time. As a result,ROHC compression algorithm will be not suitable. In this paper,a kind of adaptive robust header compression algorithm is put forward which can dynamically make adjustment of ROHC compression parameters according to the changing conditions of wireless channel. The simulation results show that,compared with the ROHC compression algorithm,the algorithm proposed in the paper has higher compression efficiency and better applicability as well.
On Job Mobility and Earnings Growth

This study examines the relationship between job mobility (mobility between employers), and wage growth. This relationship is examined in the short term (year–to-year) as well as in the medium-long term (after five years). Findings are presented for three sub-periods of equal length within the overall period, referring to a decade and a half between 1990 and 2005, with the aim of learning about the persistence and stability of this relationship throughout demographically, economically and socially distinct periods. The data used in this study come from the administrative data of the Tax Authorities, combined with additional demographic and economic data from other sources. According to the data, job stability noticeably diminished between the first and second half of the 1990s, and remained at a similar level afterwards. In the short term, the results show that job mobility—even when voluntary—has a negative effect on wage growth in each of the three studied periods, regardless of market and social conditions in these periods. Nevertheless, from a cumulative perspective over a period of five years, involuntary job mobility appears to have a negative effect on wage levels in the long term as well, while the findings regarding voluntary mobility are inconclusive but may be positive. The long-term moderate increase in wages related to job mobility may be explained by the hypothesis that in the current labor market, employees regard transitions between employers as a form of investment that carries certain risks but may be fruitful in the long term, despite its short-term costs—similar to what the human capital theory suggests regarding the acquisition of education or any other professional training. The findings also show that the effect of job mobility on wage growth in the long term is not resistant to periodical conditions and changes between the different periods. Considering the transition costs of job mobility, which are not taken into account in this study, job stability seems to be related, for the most part, to better wage growth.
stargazer : LaTeX code for well-formatted regression and summary statistics tables (R package)

stargazer produces LaTeX code for well-formatted tables that hold regression analysis results from several models side-by-side, as well as summary statistics. It supports model objects from lm, glm, svyglm, gee, gam, polr, survreg, coxph, as well as from the implementation of these in zelig. It also supports the following zelig models for social network analysis: ”cloglog.net”, ”gamma.net”, and ”logit.net”.
A conceptual model in fish disease diagnosis expert system

Conceptual model is an abstract description for real world.It is important to construct a strict and self-contained conceptual model in the process of information exchange between domain experts and developers.In this paper,fish disease diagnosis in the real world is distinguished and identified,diagnosis problem,diagnosis knowledge and diagnosis mode are abstracted.Fish-disease diagnosis problem is defined as a mathematics model including 8 factors,such as object,disease set,cause set,manifestation set,knowledge,display and conclusion.Diagnosis knowledge is described as a causal network model including cause, disease and manifestation.Resolve method is analyzed as a cycling process of obtaining-reasoning-adding information.In the last,a conceptual model for fish disease diagnosis is constructed.It can provide important theory basis for the construction of Fish Disease Diagnosis Expert System(FDDES).
Zur Rolle von Sprache im Emotionscoping

Die menschliche Sprache ist ein einzigartiges Konstrukt, dessen Wirkungskreis von sozialen Interaktionen bis hin zu kognitiven Prozessen innerhalb eines Individuums reicht. Die vorliegende Arbeit beschaftigt sich mit der Frage, welche Rolle Sprache bei der Bewaltigung von negativen Emotionen einnimmt. Die zugrundeliegenden Prozesse des Verhaltnisses von Sprache und Emotionsbewaltigung werden auf Basis vorhandener Theorien zu Sprachfunktionen, Emotionen und Coping in Beziehung gesetzt. Auf Grundlage der Literatur zu diesem Thema wird der Begriff des Emotionscopings eingefuhrt, der als die Bemuhungen zur Regulation und Anpassung emotionaler Reaktionen auf potenziell bedrohliche Situationen definiert wird. In einer explorativen Studie werden drei Experten zu der Rolle von Sprache im Emotionscoping befragt und eine qualitative Inhaltsanalyse anhand der Interview-Transkripte durchgefuhrt. Die Ergebnisse legen nahe, dass die Sprache vor allem durch die Steuerung kognitiver Ressourcen wie Bewusstsein und Aufmerksamkeit am Emotionscoping beteiligt ist. Dabei kommt der Sprache besonders bei der Verbalisierung der Emotion und bei der Modulation ihres Entstehungsprozesses eine zentrale Bedeutung zu. Auf Basis der Ergebnisse wird im Rahmen dieser Arbeit ein Modell zum sprachbasierten Emotionscoping entwickelt. Das Modell bildet neben den uber-geordneten Schritten des Coping-Prozesses auch die Wechselwirkungen und Zusammen-hange der einzelnen Prozessschritte untereinander ab.
PENALTY-BASED PAGERANK ALGORITHM

In this paper we give a brief overview of the original PageRank algorithm that is used in the Google search engine. This algorithm exploits the link structure of the web and greatly improves the results of Web search. We propose a new method for the computation of page rank on the basis of penalty scores assigned to web pages which are accessed through Advertisement links. We compare the page ranks obtained using the original page rank algorithm and our proposed penalty-based page rank method.
Feature selection algorithm based on Hellinger distance

To solve the feature selection problem,two kinds of definitions of Hellinger distance were studied in this paper,and the corresponding feature selection algorithms based on Hellinger distance were also proposed.The experiments on different data sets show the efficiency of the two algorithms.Compared with other feature selection algorithms,the feature selection algorithms based on Hellinger distance can get fewer features,which are useful for C4.5 and can improve the average accuracy of the classification in the learned data sets.
Fuzzy parallel parking control of autonomous ground vehicles in tight spaces

This paper develops and experimentally demonstrates an automatic parallel parking control algorithm for autonomous ground vehicles (AGVs). The automatic parallel parking problem is described and fuzzy logic controllers are designed for each step of the parking process. Detailed membership functions and fuzzy reasoning rules are given for each fuzzy logic controller. The parking algorithm is tested by simulation and experimental implementation based on the model of a skid steering autonomous ground vehicle. Both results demonstrate the ability of the developed algorithm to parallel park AGVs in tight spaces.
Does the 'Family Factor' Really Matter? Sentencing Offenders in Domestic and Non-Domestic Violence Cases in Russia

While research on criminal sentencing has been an active field of inquiry for decades, social disparities in sentencing of domestic and non-domestic violent offenders remain understudied. Using court data on defendants persecuted in Russia in 2010-2013 enriched with information from verdict texts, we examine the effects of diverse socio-demographic characteristics and victim-offender relationship on both incarceration and sentence length decisions in violent cases, controlling for a range of legal factors. Gender, marital, parental, and employment statuses, educational background, criminal record and some other social characteristics differ significantly among offenders convicted of intimate partner violence, child-parent abuse, or non-domestic violence. Offenders sentenced for child-parent violence have a higher probability to be incarcerated than other violent offenders, while the probability of incarceration does not differ significantly for perpetrators of intimate partner violence compared to non-domestic violent offenders. Moreover, partner abusers receive even shorter sentences than non-domestic violent offenders. This effect sustains only for female offenders but not male offenders when the interaction of gender and the victim-offender relationship is included. Marriage usually decreases sentence severity. However, victim-offender relationship significantly moderates the effect. Partner abusers receive no discount in sentence length for being officially married than offenders in non-domestic violence cases.
Currency Crisis, Monetary Policy, and Corporate Balance Sheet Vulnerabilities

This paper studies how the exposure of a country's corporate sector to interest rate and exchange rate changes affects the probability of a currency crisis.To analyze this question, we present a model that defines currency crisis as situations in which the costs of maintaining a fixed exchange rate exceed the costs of abandonment.The results show that a higher exposure to interest rate changes increaes the probability of crisis through an increased need for output loss compensation and an increased efficacy of monetary policy in stimulating output.A higher exposure to exchange rate changes also increases the need for output loss compensation.However, it lowers the efficacy of monetary policy in stimulating output through the adverse balance sheet effects of exchange rate depreciation.As a result, its effects on the probability of crisis is ambiguous.
Research on Anonymous User Preference Model of University Digital Library

Most user preference models of recommender system are built on the basis of registered user and long-term interests,however,users are always accustom to access to the Information Retrieval System anonymously.Based on the summary of characteristics on user preferences and information source of university digital library,this paper puts forward to build preference model for anonymous user and short-term interests,to recommend combined with professional users' long-term interests,and this study provides a new idea for building user preference model of university digital library recommender system using the VSM(Vector Space Model) to design user preference model.
Visualisation of Relational Database Structure by Graph Database

Most IT systems rely on dedicated databases, and most of these databases are relational. The advantages of such databases are well known and widely reported in literature. Unfortunately, attempts to identify the topology of links in the relational model produced by iterative development or administrative enhancements are often hampered by the large number of tables that make up the database and the lack of comprehensive technical documentation. Analysis of the model by someone other than its designer requires substantial effort. The aim of the presented work is therefore to develop an application for effective presentation of the database structure in the form of a directed graph. The main assumption was that a graph-oriented database environment would be used. This paper presents the RELATIONS-Graph application developed by the authors. This application automatically generates a directed graph which presents links between tables and attributes which constitute a relational database. The RELATIONS-Graph application can also scan the generated graph in order to discover links between selected tables and columns. This solution has been applied to SQL Server 2014 SP1 DBMS using the Microsoft . NET technology and the Neo4j graph database, also by . NET API. The RELATIONS-Graph application was developed in C#, an object-oriented programming language.
New Algorithm of GPS Positioning in Incomplete Condition of Temporal Insufficient Signal

A new algorithm is proposed to enable GPS positioning with acceptable accuracy based on less-than-three available satellites in insufficient condition caused by temporal signal blockage. Tests in real data demonstrate that the proposed algorithm offers significant improvement of GPS availability by providing location results suitable for navigation applications in temporal insufficient condition more than one minute. The algorithm does not need extra sensors or support of digital maps, meanwhile the increased gross system cost is neglectable.
High Performance Implementation for Aligning Compressed DNA Sequences

In molecular biology, sequence alignment is a way of arranging DNA, RNA or protein sequences to identify regions of similarity between the sequences. However, this is a challenging problem since these sequences such as DNA are huge in size and the databases are growing at an exponential rate. It requires tremendous amount of memory and large computational power. For example, the human genome in raw format ranges from 2 to 30Tera-bytes. The growth of the DNA affects the storage as well as bandwidth when these sequences need to be transferred. We need to utilize the repeats present in the DNA sequences to compress them. Applications such as DNA profiling, real time DNA crime investigation require access to the DNA sequences in real time. However, the applications mentioned not only require good compression ratio but also needs faster compression. As part of the first phase, we propose a new algorithm with a focus on the through put along with the compression ratio. The algorithm scales well and achieves a speed up of 11 on multi-cores and upto 23 on GPUs when run on M2070 Tesla card and up to 57on K20 Kepler GPUs. In the second phase, we present two types of alignment namely ungapped and gapped alignment. Multi-cores and GPUs can be used to align the sequences quickly. The focus mainly is on aligning the huge sequences accurately. The ungapped alignment achieves a speedup of up to 56 on K20 Kepler GPUs and the gapped alignment achieves a speedup of up to 15 on 16-core Intel Xeon E5-2680 processor.
Efficient secure computation enabled by blockchain technology

For several decades, secure multiparty computation has been the topic of extensive research, as it enables computing any functionality in a privacy-preserving manner, while ensuring correctness of the outputs. In recent years, the field has seen tremendous progress in terms of efficiency, although most results remained impractical for real applications concerning complex functionalities or significant data. When privacy is not a concern and we are only interested in achieving consensus in a distributed computing environment, the rise of cryptocurrencies, specifically Bitcoin, has presented an efficient and robust solution that exceeds the limits imposed by prior theoretical results. Primarily, Bitcoin’s relative efficiency and superiority in achieving consensus is due to its inclusion of incentives. By doing so, it extends the standard cryptographic model to one that reasons about security through rationality of the different players. Inspired by this idea, this thesis focuses on the development of an efficient, generalpurpose secure computation platform that relies on blockchain and cryptocurrencies (e.g., Bitcoin) for efficiency and scalability. Similar to how Bitcoin transformed the idea of distributed consensus, the goal in this work is to take secure multi-party computation from the realm of theory to practice. To that end, a formal model of secure computation in an environment of rational players is developed and is used to show how in this framework, efficiency is improved compared to the standard cryptographic model. The second part of this thesis deals with improving secure computation protocols over the integers and fixed-point numbers. The protocols and tools developed are a significant improvement over the current state-of-the-art, with an optimally efficient secure comparison protocol (for up to 64-bit integers) and better asymptotic bounds for fixed-point division. Thesis Supervisor: Alex ’Sandy’ Pentland Title: Toshiba Professor of Media Arts and Sciences
Machine Learning, 17, 5-46 (1994) © 1994 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands,

Although a landmark work, version spaces have proven fundamentally limited by being constrained to only consider candidate classifiers that are strictly consistent with data. This work generalizes version spaces to partially overcome this limitation. The main insight underlying this work is to base learning on version- space intersection, rather than the traditional candidate-elimination algorithm. The resulting learning algorithm, incremental version-space merging (IVSM), allows version spaces to contain arbitrary sets of classifiers, however generated, as long as they can be represented by boundary sets. This extends version spaces by increasing the range of information that can be used in learning; in particular, this paper describes how three examples of very different types of information—ambiguous data, inconsistent data, and background domain theories as traditionally used by explanation-based learning—can each be used by the new version-space approach.
How science, technology and innovation can be placed in broader visions — Public opinions from inclusive public engagement activities

This study investigates how different segments of the public, with varying degrees of interest in S&T, could formulate opinions on a broader vision and the role they think STI should play in Japanese society through 2020 (Tokyo's Olympic and Paralympic year) and toward 2030. We conducted nine inclusive public engagement activities. Results indicated that the broad public opinions did not completely overlap with officials' opinions, a value of “open and appropriate” was mainly found from the unengaged public, and the visions and values based on their opinions could well be incorporated into the official document. Engaging the disinterested in S&T remains an issue.
Characteristics of three phase active power filter using extension pq theory

In this paper, the authors propose a calculation method for the compensating current reference of an active power filter, where a nonlinear load exists in a three-phase three-wire unsymmetrical voltage system. This new method has been named the extension pq method. The authors have experimented with the extension pq method and the pq method, using the same current controlled IPM inverter for both methods. The results of the experiments proved that, in the unsymmetrical voltage system, the source current was distorted in case of the pq method, but undistorted in case of the extension pq method.
ZigBee test framework

This project aims to build up a common ZigBee test framework. The common test framework can be used by teams developing devices using ZigBee. The objective is to reuse of the test infrastructure, test fixtures as well as to simplify the exchange of test engineers between teams. In this project, we have developed a test framework using the C# plugin architecture. We have developed a Hue Bridge plugin and an EWAC plugin, deployed them into the Bridge regression test and EWAC test. The existing test fixtures using the Bridge/EWAC plugins test interfaces have been used to validate the correct functioning of the plugins. We also have a design demonstration of a support function, e.g., the test configuration to be extendable to different test environments. The project results are an evolutionary step towards an unifying test framework among development teams.