Miracle-dz/UniFAR-FTUs huggingface dataset:
USING THE THEORY OF PLANNED BEHAVIOR TO PREDICT CRIME REPORTING INTENT

There is a disparity between the number of crimes committed and number of reports victims file with police, often called the “reporting gap” (Baumer & Lauritsen, 2010). The reporting gap makes it important to understand what influences victims’ decisions to report crimes. Previous research has indicated that a variety of factors influence reporting intentions but most research does not rely on a behavioral theory. This research uses the Theory of Planned Behavior (TPB; Ajzen & Fishbein, 1980) to predict crime victims’ intentions to report their victimizations to police. Using a mock crime scenario and survey questions, this research explored whether the TPB model factors (i.e., victims’ attitudes, perceived social norms, and perceived behavioral control (PBC)) predict crime reporting intentions. A second “expanded model” included traditional predictors of reporting (e.g., perceived severity, victim characteristics) in addition to the TPB factors. The TPB model predicted crime reporting intent. The enhanced model did not increase predictive power over the TPB model. The most influential TPB factor was social norms. The strong predictive power of social norms was greater than attitudes, PBC, and even traditional predictors of reporting. This expands the behavior and decision-making contexts in which this model can be used. Knowing what factors (e.g., social norms) predict victim reporting could assist in implementing programs to increase crime reporting and improve policing.
Graph-based joint clustering of fixations and visual entities

We present a method that extracts groups of fixations and image regions for the purpose of gaze analysis and image understanding. Since the attentional relationship between visual entities conveys rich information, automatically determining the relationship provides us a semantic representation of images. We show that, by jointly clustering human gaze and visual entities, it is possible to build meaningful and comprehensive metadata that offer an interpretation about how people see images. To achieve this, we developed a clustering method that uses a joint graph structure between fixation points and over-segmented image regions to ensure a cross-domain smoothness constraint. We show that the proposed clustering method achieves better performance in relating attention to visual entities in comparison with standard clustering techniques.
The SAMBA Approach to Community-Based Interactive Digital Television

SAMBA is a European Project funded under the 1ST 6th framework program for International collaboration on iDTV between Europe and Latin America. The main objective of the project is to create a framework for allowing local communities and citizens (including low income population) to access community-oriented content and services by means of iDTV channels. SAMBA approach consists in developing user- friendly Web-based tools for iDTV community-oriented content creation. Besides, SAMBA will explore the potentials of utilization of iDTV for the creation of future services and business models for the fixed and mobile TV market.
Clustering data with Particle Swarm Optimization using a new fitness

Data clustering has been studied for a long time and every day trends are proposed for better outcomes in this field. One of the latest trends in this area is the application of Particle Swarm Optimization (PSO) in clustering which has good potential for improvements. In this paper, we consider a new fitness function for our PSO-based clustering method and compared it with the previous ones. Experimental results show that our method has better outcomes than the other ones.
Adaptive control for a cable driven robot arm

The cable-driven mechanism is usually used in robotic systems for the efficient transmission of forces or torques from actuators to the end-effector. However, the control design is challenging for these systems due to the cable compliance and transmission elasticity. In this paper, adaptive control in a cascaded structure is designed for the trajectory tracking of a cable driven robot arm. The desired control input is obtained by developing an adaptation scheme, which does not require the computation of the regressor matrix. Proportional-derivative (PD) control is designed to specify the actual control input such that the trajectory tracking is achieved. Simulation results are provided to show the effectiveness of the proposed method.
Labour Supply and Income Tax Changes: A Simulation Study for Finland

It is well known that estimation of the labour supply function is complicated by the non-linearity of the individual s budget constraint.Non-linearity may be caused by a number of factors such as the structure of the tax/benefit scheme or overtime rates. Non-linearities also cause problems in interpreting the policy implications of the estimates.In this study we use a well-structured econometric labour supply model that mimics actual budget constraints as closely as possible to analyse the labour-supply effects of different income tax regimes and systems. In addition to the empirically-specified labour supply model, we construct, for the first time in Finland, a behavioural microsimulation model.Our intent is to contribute to the tax debate in Finland by simulating several suggested changes in the tax system.Our simulation results show that none of the proposed reforms are self-financing.Revenue-neutral move to a proportional tax system does not have major effects on labour supply.The most pronounced behavioural effects are achieved when marginal tax rates are reduced at the lower end of the income tax schedule. Keywords: microsimulation, labour supply, taxation
Style-sheets Extraction from Existing Digital Contents by Image Processing for Web-Based BML Contents Management System

This paper proposes a web-based BML contentsmanagement system. BML is the short form of BroadcastMarkup Language which is a script language for databroadcasting contents included in digital TV broadcastingservices of Japan. The scripting style of BML is very similar tothat of HTML and it also supports style-sheets and JavaScript.However, in BML, there are many restrictions about thedisplay area size, font sizes, color types and so on because theBML-browser of TV is not flexible as compared with the Webbrowser.Although there are a couple of dedicated softwarepackages for BML contents creation, they are very expensiveand difficult to use. So, BML contents creation is not easy forthe end-user. To make it easier to create BML contents, theauthors have been developing a webbased BML contentsmanagement system. This paper explains fundamentalfunctionalities provided by the proposed BML contentsmanagement system.Already many digital contents were created and stored andwe can easily obtain their images by capturing the screensnapshot. So, this paper also proposes style-sheets extractionmethod for BML contents from such already existing digitalcontents by image processing techniques.
On the effect of synthetic morphological feature vectors on hyperspectral image classification performance

This paper studies the effect of synthetic feature vectors on the classification performance of hyperspectral remote sensing images. As feature vectors, it has been chosen to employ morphological attribute profiles, that have proven themselves in this field. At this early stage of our work, the relatively simple Bootstrapping algorithm has been used for synthetic feature vector generation. Based on experiments conducted on multiple hyperspectral datasets, it has been observed that synthetic feature vectors contribute considerably to classification performance in the case of limited training dataset sizes.
Reduced Lean Mass in Early Alzheimer Disease and Its Association With Brain Atrophy

Objective To examine body composition in individuals with early AD and without dementia and its relation to cognition and brain volume. Design Cross-sectional case-control study. Participants Individuals without dementia (Clinical Dementia Rating, 0; n = 70) and with early-stage AD (Clinical Dementia Rating, 0.5 or 1; n = 70) in the Alzheimer and Memory Program at the University of Kansas School of Medicine. Main Outcome Measures Participants were evaluated with brain magnetic resonance imaging (MRI), neuropsychological testing, and dual-energy x-ray absorptiometry to determine whole-body fat and lean masses. Body mass index was calculated as weight in kilograms divided by height in meters squared. Results Lean mass was reduced in persons with early AD compared with controls without dementia (F = 7.73; P = .006) after controlling for sex. Whole-brain volume (β = .20; P < .001), white matter volume (β = .19; P < .001), and global cognitive performance (β = .12; P = .007) were associated with lean mass (dependent variable) when controlling for age and sex. The total body fat and percentage of body fat values were not different across groups or related to cognition and brain volume. Conclusion Loss of lean mass is accelerated in AD and is associated with brain atrophy and cognitive performance, perhaps as a direct or indirect consequence of AD pathophysiology or through shared mechanisms common to both AD and sarcopenia.
A new method for intrusion detection on hierarchical wireless sensor networks

Wireless Sensor Network (WSN) is a novel technology in wireless field. The main function of this technology is to use sensor nodes to sense important information, just like battlefield data and personal health information, under the limited resources. It is important to avoid malicious damage while information transmits in wireless network. So Wireless Intrusion Detection System (WIDS) becomes one of important topics in wireless sensor networks. The attack behavior of wireless sensor nodes is different to wired attackers. In this paper, we will propose an isolation table to detect intrusion in hierarchical wireless sensor networks and to estimate the effect of intrusion detection effectively. The primary experiment proves the isolation table intrusion detection can prevent attacks effectively.
Violent Female Youth Offenders: An Exploration of the Correlates of Violence Motivation, Victim Type and Ethnicity

ii ACKNOWLEDGEMENTS . iv LIST OF TABLES . vi LIST OF FIGURES . x CHAPTER ONE: INTRODUCTION . 1 Background . 1 The Extent of the Problem – Trends in Youth Offending . 4 Risk Factors and Correlates of Antisocial Behaviour amongst Female Youth . 9 Individual Characteristics . 10 Family Characteristics . 14 Peer Characteristics . 16 School Characteristics . 18 Community and Neighborhood Characteristics . 19 The Psychological Wellbeing of Female Youth Offenders. 22 Externalising Disorders . 23 Internalising Disorders . 25 Racial/Ethnic Discrepancies in Mental Health Disorders amongst Female Youth Offenders . 26 Female Youth and Violence . 27 Offending Specialisation: Can Violent Offenders be distinguished from Nonviolent Offenders? 28 Female Use of Violence in NZ Studies . 29 Victimisation and Violence . 30 Substance Use, Alcohol and Violence . 31 Psychopathology and Antisocial Behaviour/Violence . 32 Violence Motivation: Instrumental and Reactive Violence . 33 Victim-Offender Relationship . 38 Prevention and Intervention . 43 The Present Study . 45
The orbital period of V458 Vulpeculae, a post-double common-envelope nova

We present time-resolved optical spectroscopy of V458 Vulpeculae (Nova Vul 2007 No. 1) spread over a period of 15 months starting 301 d after its discovery. Our data reveal radial-velocity variations in the He iiλ5412 and He iiλ4686 emission lines. A period analysis of the radial-velocity curves resulted in a period of 98.096 47 ± 0.000 25 min (0.068 122 55 ± 0.000 000 17 d) which we identify with the orbital period of the binary system. V458 Vul is therefore the planetary nebula central binary star with the shortest period known. We explore the possibility of the system being composed of a relatively massive white dwarf (M1≳ 1.0 M⊙) accreting matter from a post-asymptotic giant branch star which produced the planetary nebula observed. In this scenario, the central binary system therefore underwent two common-envelope episodes. A combination of previous photoionization modelling of the nebular spectra, post-asymptotic giant branch evolutionary tracks and the orbital period favour a mass of M2∼ 0.6 M⊙ for the donor star. Therefore, the total mass of the system may exceed the Chandrasekhar mass, which makes V458 Vul a Type Ia supernova progenitor candidate.
Hidden Depths and Everyday Secrets: How Audience Sense- Making Can Inform Arts Policy and Practice

ABSTRACT This article responds to the arts policy and research call for better understandings of arts audiences—actual and potential. The authors report on the application of Dervin's Sense-Making Methodology (SMM) to audience research. SMM is an approach developed specifically for providing data useful to informing policies and practices of institutions mandated to serve publics. We review the narrative themes that have emerged from our analyses of accounts of cultural experiences by several hundred informants, and we offer five sample applications that illustrate potentials and their implications for arts policy and practice.
Ionic Mechanism of Ouabain-Induced Concurrent Apoptosis and Necrosis in Individual Cultured Cortical Neurons

Energy deficiency and dysfunction of the Na+, K+-ATPase are common consequences of many pathological insults. The nature and mechanism of cell injury induced by impaired Na+, K+-ATPase, however, are not well defined. We used cultured cortical neurons to examine the hypothesis that blocking the Na+, K+-ATPase induces apoptosis by depleting cellular K+ and, concurrently, induces necrotic injury in the same cells by increasing intracellular Ca2+ and Na+. The Na+, K+-ATPase inhibitor ouabain induced concentration-dependent neuronal death. Ouabain triggered transient neuronal cell swelling followed by cell shrinkage, accompanied by intracellular Ca2+and Na+ increase, K+ decrease, cytochrome c release, caspase-3 activation, and DNA laddering. Electron microscopy revealed the coexistence of ultrastructural features of both apoptosis and necrosis in individual cells. The caspase inhibitor Z-Val-Ala-Asp(OMe)-fluoromethyl ketone (Z-VAD-FMK) blocked >50% of ouabain-induced neuronal death. Potassium channel blockers or high K+ medium, but not Ca2+ channel blockade, prevented cytochromec release, caspase activation, and DNA damage. Blocking of K+, Ca2+, or Na+ channels or high K+ medium each attenuated the ouabain-induced cell death; combined inhibition of K+ channels and Ca2+ or Na+ channels resulted in additional protection. Moreover, coapplication of Z-VAD-FMK and nifedipine produced virtually complete neuroprotection. These results suggest that the neuronal death associated with Na+, K+-pump failure consists of concurrent apoptotic and necrotic components, mediated by intracellular depletion of K+ and accumulation of Ca2+ and Na+, respectively. The ouabain-induced hybrid death may represent a distinct form of cell death related to the brain injury of inadequate energy supply and disrupted ion homeostasis.
Articulated hand tracking using key poses driven particle filtering

Tracking an articulated hand is very difficult problem due to the high dimensionality of the hand joint movements. We propose a system to track the articulated hand using our key pose driven particle filtering. The articulated hand is modeled as a cardboard model which has 24 DOF. Using motion constraints between the finger joints, the dimension of the articulated hand model is reduced to 13 DOF. The proposal distribution is based on the Gibbs sampler-based motion model and the matching probabilities of key poses onto the observation image. The motion model is based on the motion constraints between the hand joints. Each movement of joints is predicted by Gibbs sampler which is modeled as our motion model. We show the experimental results of tracking the articulated hand by Key poses driven particle filtering.
An automatic scheme for stereoscopic video object-based watermarking using qualified significant wavelet trees

A fully automatic system for embedding visually recognizable watermark patterns to video objects is proposed. The architecture consists of 3 main modules. In the first module, unsupervised video object extraction is performed, by analyzing stereoscopic pairs of frames. Then each video object is decomposed into three levels with ten subbands, using the discrete wavelet transform (DWT) and three pairs of subbands are formed (HL/sub 3/, HL/sub 2/), (LH/sub 3/, LH/sub 2/) and (HH/sub 3/, HH/sub 2/). Next qualified significant wavelet trees (QSWTs) are estimated for the specific pair of subbands that contains the highest energy content compared to the other two pairs. QSWTs are derived from the embedded zerotree wavelet (EZW) algorithm and they are high-energy coefficient paths within the selected pair of subbands. Finally, in the third module, visually recognizable watermark patterns are redundantly embedded to the coefficients of the highest energy QSWTs and the inverse DWT is applied to provide the watermarked video object. The performance of the proposed video object watermarking system is tested under various signal distortions such as JPEG lossy compression, sharpening, blurring and adding different types of noise. Experimental results on real life stereoscopic images are presented to indicate the efficiency and robustness of the proposed scheme.
Modelling networks of biochemical reactions

Author's declaration: aware of legal responsibility I hereby declare that I have written this dis-sertation myself and all the contents of the dissertation have been obtained by legal means. Abstract The process in which a mathematical model of a molecular biological system is formulated and refined helps to articulate hypotheses and thereby supports the design of experiments to validate these hypotheses and the model itself. Once the model is validated it is used to speculate about mechanisms underlying a cell function of interest. In this disser-tation we describe and apply methods valid in a general framework of spatially homogeneous models of biochemical reactions networks. However , our focus is set specifically on practical applications to models of intracellular signalling pathways. We start with selecting the most plausible variant of a JAK-STAT pathway activation mechanism. Solution of this model selection task is based solely on a deterministic mathematical framework, represented by the ordinary differential equations. Moreover, here we exert a concept of ro-bustness based on the sensitivity analysis. Next, we extend the range of mathematical models of biochemical reactions network to a spatially homogeneous stochastic variant, represented by the continuous-time Markov process. To that end, we apply the probabilistic model checking technique to a simple enzymatic reaction model, exploring an idea of a property-specific sensitivity analysis. On this occasion, we have developed a supporting open source software named Tav4SB, used for scientific cloud computing. Finally, we exploit both deterministic and stochastic methods in a case study based on the heat-shock response model. We investigate the thermotolerance phenomenon and the effect of a combined hyperther-mia and a drug therapy of cancer. In principle, our results demonstrate feasibility and practical potential of techniques such as the sensitivity analysis and probabilistic model checking, as well as potential of a standardised, easily-accessible software, in the context of analysis of kinetic models of biological systems.
Factors Influencing Future Employees' Decision-Making to Participate in a BYOD Program: Does Risk Matter?

As people use mobile devices (smartphones, tablets, etc.) more and more in daily life, their desire grows to use the same devices at work. In response to this demand, many firms are considering to offer BYOD programs allowing their employees to bring their own devices to work and use them for business purposes. This study analyses how employees´ perceive the benefits and risk associated with BYOD. Additionally, it is investigated whether innovativeness traits can serve as predictors of BYOD program participation. For this account, a theoretical model building on net valence approaches from decision making and perceived risk theory is proposed and tested. German students with relevant work experience and close to finishing their studies (i.e. future employees) were surveyed (n = 71). \ The study demonstrates that benefits matter more than risks, at least for the suspected drivers of IT consumerization. The results show that the intention to enrol in a BYOD program is a function of perceived risk, perceived benefits and level of personal innovativeness. Among these factors, perceived benefit most strongly affects behavioural intention, whereas only safety risks proved to inhibit an individual´s intention to use privately-owned devices at work. Knowledge acquired from this study is particularly beneficial to IT executives to guide their decision to set up or adjust BYOD initiatives.
How Women's Political Representation affects Spending on Family Benefits

Abstract Recent research finds that women's political representation correlates with higher social expenditures. This paper makes two more specific predictions regarding family benefits. First, women voters and politicians are likely to prefer in-kind benefits to cash transfers. This is because the provision of childcare does more than money can do to ameliorate the double burden of work and family duties, thus strengthening women's autonomy. As a consequence female political representation should correlate with spending on in-kind family benefits, but not with expenditures on cash transfers. Second, the pressure on politicians to provide childcare services should be greater when there are higher levels of female participation in the labour force. Assuming that women politicians are more responsive to such demands, we should see a positive interaction effect between female labour force participation and women's political representation on in-kind spending. An analysis of public expenditures for family benefits in 27 OECD nations between 1980 and 2011 bears out both propositions.
Research Paper No . 2009 / 51 Innovation and Microenterprises Growth in Ethiopia

This paper addresses two prominent issues on the development of small enterprises in Africa. Which factors inhibit or foster innovation activities in small enterprises? Do innovators create more jobs? We use a large set of microenterprises survey data from Ethiopia that comprise 1000 observations with ten and fewer workers. The analysis shows that firms larger in size and in manufacturing are more likely to engage in innovative activities. Among the human capital variables vocational training is found to have a strong effect on the innovation activity. However, firms owned by female and old entrepreneurs are less likely to get involved in innovation. In an extended model of firm growth determinants that includes innovation indicators we found strong evidence that innovators grow faster than non-innovators. Firm growth is also affected by other factors such as the firm’s initial size, age, access to finance, sector, and owner character. Our estimation results provide supporting evidence to the stylized fact that the smaller, younger, and less capital constrained firms grow faster than their counterparts. Firms in manufacturing also grow faster than other sectors.