Miracle-dz/UniFAR-FTUs huggingface dataset:
Research in progress: where are all the people? the curious case of one-person IT departments

In this paper, we present a research-in-progress study that examines the characteristics of IT-departments that consist of a single employee. Spurred by the findings of a master's student project, we examined the data from another study we had conducted that revealed that fully 44% of municipalities in a Scandinavian country have such one-person-departments. Our survey also revealed that these "departments" provide full service to the municipalities which are quite heavy users of IT services. The obvious question is "how is it possible for the apparently skeletal IT department to provide full service? " Have we stumbled upon a new form of organizing the IT function? In this paper, we aim to map such departments to the models and frameworks that appear in the IS literature. We plan to conduct a series of interpretive case studies to understand how and why this structure emerged and what implications this has for IT personnel employed in these departments and the IT service delivery for organizations.
2010 2nd International Conference on Industrial and Information Systems a History Statistical Estimation Method for Hand-off Probability in Wireless Cellular System

In wireless cellular system, providing Quality-of­ Service (QoS) control during hand-offs is highly desirable. In this paper, a method to estimate hand-off probability using statistically recorded history data of mobile phone's mobility (connection or hand-off) is proposed. By designing a special statistical database structure and casting a three­ layer neural network on the history data, the cellular system reserves bandwidth for the hand-off mobile phones according to statistical background data, and then reduces the hand-off dropping probability.
Price Setting in a Variable Macroeconomic Environment: Evidence from Brazilian CPI∗

We study price setting in a variable macroeconomic environment using a unique data set from the Brazilian CPI index of Fundação Getulio Vargas. Our primary data consist of a panel of individual prices for goods and services covering 100% of the CPI for the 1996-2008 period. During this period a number of important events produced substantial macroeconomic variability in Brazil: two emerging market crises, a change of exchange rate and monetary regimes, blackouts and energy rationing, an election crisis, and a regular disinflation. As a consequence, inflation, macroeconomic uncertainty, exchange rates, and output exhibit important variation in our sample. We construct time series of price-setting statistics and relate them to macroeconomic variables using regression analyses. As an illustration of our results, we find that price increases are less frequent after a period of exchange rate appreciation, and more frequent: i) when inflation is higher; after a period of exchange rate depreciation (with an asymmetry relative to appreciations); in periods of high economic activity; and when macroeconomic uncertainty is higher. ∗*We thank IBRE-FGV (Brazilian Economy Institute of Getulio Vargas Foundation) for providing the data set, and participants at LACEA 2008, 2009 Workshop in International Economics and Finance in Montevideo, 2009 NBER SI 2009 Monetary Economics, seminars at EESP-FGV, Di Tella, and IPEA for comments on an even more preliminary version of this project. The views expressed in this paper are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System.
Model-free subspace-based LQG-designW

When only input/output data of a system are available the classical way to design a linear quadratic Gaussian controller consists of mainly three separate parts. First a system identiication step is performed to nd the system parameters. With these parameters a Kalman lter is designed to nd an estimate of the state of the system. Finally, this state is then used in an LQ-controller. In literature these three steps are hardly ever considered as one joint problem. Based on techniques from the eld of subspace system identiication the present paper gives a new, much more direct method to implement nite horizon LQG-controller. The three steps of the LQG-controller design, i.e. the system identiication, the Kalman lter and the LQ-controller are replaced by one single QR-decomposition. The equivalence between the new subspace based approach and the classical approach is proven.
The Behaviour of Small Investors in the Hong Kong Derivatives Markets: A factor analysis

This paper investigates the behaviour of small investors in Hong Kong’s derivatives markets. The study period covers the global economic crisis of 2011- 2012, and we focus on small investors’ behaviour during and after the crisis. We attempt to identify and analyse the key factors that capture their behaviour in derivatives markets in Hong Kong. The data were collected from 524 respondents via a questionnaire survey. Exploratory factor analysis was employed to analyse the data, and some interesting findings were obtained. Our study enhances our understanding of behavioural finance in the setting of an Asian financial centre, namely Hong Kong.
ROBUST OPTIMAL TESTS FOR CAUSALITY IN MULTIVARIATE TIME SERIES

Here, we derive optimal rank-based tests for noncausality in the sense of Granger between two multivariate time series. Assuming that the global process admits a joint stationary vector autoregressive (VAR) representation with an elliptically symmetric innovation density, both no feedback and one direction causality hypotheses are tested. Using the characterization of noncausality in the VAR context, the local asymptotic normality (LAN) theory described in Le Cam (1986, Asymptotic Methods in Statistical Decision Theory) allows for constructing locally and asymptotically optimal tests for the null hypothesis of noncausality in one or both directions. These tests are based on multivariate residual ranks and signs (Hallin and Paindaveine, 2004a, Annals of Statistics 32, 2642–2678) and are shown to be asymptotically distribution free under elliptically symmetric innovation densities and invariant with respect to some affine transformations. Local powers and asymptotic relative efficiencies are also derived. The level, power, and robustness (to outliers) of the resulting tests are studied by simulation and are compared to those of the Wald test. Finally, the new tests are applied to Canadian money and income data.
Sensor deployment for air pollution monitoring using public transportation system

Air pollution monitoring is a very popular research topic and many monitoring systems have been developed. In this paper, we formulate the Bus Sensor Deployment Problem (BSDP) to select the bus routes on which sensors are deployed, and we use Chemical Reaction Optimization (CRO) to solve BSDP. CRO is a recently proposed metaheuristic designed to solve a wide range of optimization problems. Using the real world data, namely Hong Kong Island bus route data, we perform a series of simulations and the results show that CRO is capable of solving this optimization problem efficiently.
Optimal Online Risk-Tolerant Ordering Policy for the Newsvendor with Forecast

The classical newsvendor problem is to find a product's order quantity to maximize the expected profit under probabilistic demand. This paper restudies the problem under the perspective of competitive analysis, in which only the lower bound and upper bound rather than the distribution of the future demand are known. Some preliminary results of the problem with competitive analysis are given first in brief. And then it is considered in the risk-reward framework which provides the flexibility to develop some risky online strategies, as conventional competitive analysis seems too conservative and some decision-makers may incline to increase their risk for some reward in practice. In this framework, it is assumed that the vendor may have some forecast of the future demand and he can tolerate a certain level of risk for better reward. Based on his forecast and risk tolerance, an optimal online risk-tolerant ordering policy for the newsvendor is developed.
The Trading Agent Competition as a test problem for Constraint Solving under Change and Uncertainty

The annual Trading Agent Competition includes a Supply Chain Management game [1], in which agents must win contracts, obtain supplies, and produce goods, in competition with five other agents. In this position paper, we outline the problem domain, explaining why we believe it is a suitable testbed for reasoning about change and uncertainty in constraint optimisation, and we describe our initial attempts to design and implement a constraint-based agent to participate in the competition.
Deletion of the NSm Virulence Gene of Rift Valley Fever Virus Inhibits Virus Replication in and Dissemination from the Midgut of Aedes aegypti Mosquitoes

Background Previously, we investigated the role of the Rift Valley fever virus (RVFV) virulence genes NSs and NSm in mosquitoes and demonstrated that deletion of NSm significantly reduced the infection, dissemination, and transmission rates of RVFV in Aedes aegypti mosquitoes. The specific aim of this study was to further characterize midgut infection and escape barriers of RVFV in Ae. aegypti infected with reverse genetics-generated wild type RVFV (rRVF-wt) or RVFV lacking the NSm virulence gene (rRVF-ΔNSm) by examining sagittal sections of infected mosquitoes for viral antigen at various time points post-infection. Methodology and Principal Findings Ae. aegypti mosquitoes were fed an infectious blood meal containing either rRVF-wt or rRVF-ΔNSm. On days 0, 1, 2, 3, 4, 6, 8, 10, 12, and 14 post-infection, mosquitoes from each experimental group were fixed in 4% paraformaldehyde, paraffin-embedded, sectioned, and examined for RVFV antigen by immunofluorescence assay. Remaining mosquitoes at day 14 were assayed for infection, dissemination, and transmission. Disseminated infections were observed in mosquitoes as early as three days post infection for both virus strains. However, infection rates for rRVF-ΔNSm were statistically significantly less than for rRVF-wt. Posterior midgut infections in mosquitoes infected with rRVF-wt were extensive, whereas midgut infections of mosquitoes infected with rRVF-ΔNSm were confined to one or a few small foci. Conclusions/Significance Deletion of NSm resulted in the reduced ability of RVFV to enter, replicate, and disseminate from the midgut epithelial cells. NSm appears to have a functional role in the vector competence of mosquitoes for RVFV at the level of the midgut barrier.
A school-based motivational intervention to promote physical activity from a self-determination theory perspective

ABSTRACT The authors analyzed the effects of a multidimensional intervention to promote physical activity (PA) in school, based on self-determination theory. The study involved 88 students, between 14 and 17 years old, who were divided into a control group (n = 59) and an experimental group (n = 29). In the experimental group, a 6-month intervention was conducted, applying a teaching unit of fitness and health in physical education (PE) classes, an extracurricular program of healthy PA, and meetings with families. Questionnaires were administered to measure different motivational variables and PA levels at four time points. Significant differences were found in favor of the experimental group in parental and peer autonomy support; integrated regulation in PE; autonomy, intrinsic, and identified regulation in leisure-time PA; moderate, hard, and very hard PA; and physical self-worth. Motivational effects were maintained over time but the effects on PA levels disappeared at 6 months.
Darwin + Robots = Evolutionary Robotics: Challenges in Automatic Robot Synthesis

This paper reviews the use of artificial evolution as a means for automatic generation of locomotion controllers for physical robots and autonomous agents from the perspectives of evolutionary objectives and control architecture. An overview beginning with the pioneering works in evolutionary robotics is given, leading up to the latest state-of-the-art research in these fields. Some key shortfalls in mainstream approaches are identified, concluding with some promising research directions.
Investigating rejection behavior in the ultimatum game as a measure of anthropomorphism

In this work I investigate the possibility of using rejection behavior in the Ultimatum Game as a measure of anthropomorphism. Other measures of anthropomorphism have been suggested, mostly in the form of surveys. These, however, capture only one aspect of anthropomorphism: users’ rational and conscious ideas about a piece of technology. More implicit measures are needed to assess users’ subconscious and behavioral responses to the technology. Literature indicates that in the Ultimatum Game players are willing to incur a cost to themselves to punish (by rejecting an offer) another player for unfair behavior. In order to examine if and how UG behavior could serve as a measure of anthropomorphism, I have investigated how human receivers respond to robotic players in the UG and how this relates to the way they respond to computer and human players. The results of this study show that responses to human, robotic and computer players do not differ significantly. This in contrast to earlier findings that computer offers are rejected less often than offers from a human opponent. This difference may have been caused by the methodologies used: in the other studies, subjects were deliberately put into a less anthropomorphic mindset when they played against computer opponents. In the current study, the instructions were the same for all types of opponents. UG rejection behavior, then, seems to vary with the level of anthropomorphism, which suggests that it can indeed be used as a measure of anthropomorphism. In addition, results show that although subjects claim that they see computers and robots as less intentional and responsible than humans, these attitudes are not reflected in their behavior toward robots and computers in the Ultimatum Game. This supports the idea that self-reported anthropomorphism is not the same as implicit anthropomorphism. Implications for HRI and HCI practice are discussed.
An Ethnography: How does Buddhist Doctrine, A Local Wisdom, Affect Older Thai Villagers' Well-being?

In line with global trends, Thailand has an increasingly aged society. Generally, Thai elderly from rural lowlands in the central area are committed to Buddhism. Accordingly, many use the wisdom of their understanding of Buddhist teachings about facing death to maintain their well-being. Thai local wisdom involves accumulated knowledge, skills, behavior, and beliefs integrated and absorbed from generation to generation. Thus, local wisdom is part of local culture. This article reports on an ethnographic study that aimed to gain understanding of the local wisdom of Buddhist doctrine with reference to facing death, and the relationship of that understanding to the elders’ maintenance of health among Central Thai villagers. Twenty elderly key informants and nineteen general informants were recruited by using snowball technique. Participant-observation began while the principal investigator (first author) was establishing rapport and trust with villagers and continued for two years of fieldwork. In-depth interviews were conducted after securing informed consent. Data were analyzed by thematic analysis. In the larger project of which this was a part, facing death as guided by Buddhist doctrine emerged as the central theme. The study reported here identifies two approaches to facing death peacefully were having deep awareness about death; and preparing for a peaceful death. Incorporating this local wisdom will help elderly face death peacefully. Health care providers can use this information to understand how wellbeing can be experienced by patients approaching death.
Design of biomimetic fibrillar interfaces: 1. Making contact

This paper explores the contact behaviour of simple fibrillar interfaces designed to mimic natural contact surfaces in lizards and insects. A simple model of bending and buckling of fibrils shows that such a structure can enhance compliance considerably. Contact experiments on poly(dimethylsiloxane) (PDMS) fibrils confirm the model predictions. Although buckling increases compliance, it also reduces adhesion by breaking contact between fibril ends and the substrate. Also, while slender fibrils are preferred from the viewpoint of enhanced compliance, their lateral collapse under the action of surface forces limits the aspect ratio achievable. We have developed a quantitative model to understand this phenomenon, which is shown to be in good agreement with experiments.
A Possible Magnetar Nature for IGR J16358–4726

We present detailed spectral and timing analysis of the hard X-ray transient IGR J16358-4726 using multisatellite archival observations. A study of the source flux time history over 6 yr suggests that lower luminosity transient outbursts can be occurring in intervals of at most 1 yr. Joint spectral fits of the higher luminosity outburst using simultaneous Chandra ACIS and INTEGRAL ISGRI data reveal a spectrum well described by an absorbed power-law model with a high-energy cutoff plus an Fe line. We detected the 1.6 hr pulsations initially reported using Chandra ACIS also in the INTEGRAL ISGRI light curve and in subsequent XMM-Newton observations. Using the INTEGRAL data, we identified a spin-up of 94 s (Ṗ = 1.6 × 10-4), which strongly points to a neutron star nature for IGR J16358-4726. Assuming that the spin-up is due to disk accretion, we estimate that the source magnetic field ranges between 1013 and 1015 G, depending on its distance, possibly supporting a magnetar nature for IGR J16358-4726.
Impact of severe signal degradation on ear recognition performance

We investigate ear recognition systems for severe signal degradation of ear images in order to assess the impact on biometric performance of diverse well-established feature extraction algorithms. Various intensities of signal degradation, i.e. out-of-focus blur and thermal noise, are simulated in order to construct realistic acquisition scenarios. Experimental evaluations, which are carried out on a comprehensive database comprising more than 2,000 ear images, point out the effects of severe signal degradation on ear recognition performance using appearance features.
Trajectory Data Mining

The advances in location-acquisition and mobile computing techniques have generated massive spatial trajectory data, which represent the mobility of a diversity of moving objects, such as people, vehicles, and animals. Many techniques have been proposed for processing, managing, and mining trajectory data in the past decade, fostering a broad range of applications. In this article, we conduct a systematic survey on the major research into trajectory data mining, providing a panorama of the field as well as the scope of its research topics. Following a road map from the derivation of trajectory data, to trajectory data preprocessing, to trajectory data management, and to a variety of mining tasks (such as trajectory pattern mining, outlier detection, and trajectory classification), the survey explores the connections, correlations, and differences among these existing techniques. This survey also introduces the methods that transform trajectories into other data formats, such as graphs, matrices, and tensors, to which more data mining and machine learning techniques can be applied. Finally, some public trajectory datasets are presented. This survey can help shape the field of trajectory data mining, providing a quick understanding of this field to the community.
Generality or Specificity? Examining the Relation between Personality Traits and Mental Health Outcomes Using a Bivariate Bi–factor Latent Change Model

Most previous research has focused on the relationships between specific personality traits and specific facets of mental health. However, in reality most of the Big Five are associated at non–trivial levels with mental health. To account for this broad correlation, we proposed the ‘barometer hypothesis’, positing that behind both ratings of mental health and personality lies a barometer that indicates one's general feelings of positivity or negativity. To the extent that both the general factors of personality and mental health reflect this same barometer, we would expect them to be correlated. We tested alternative models using data from a large longitudinal panel study that includes two cohorts of participants who were assessed every two years, resulting in parallel 4–year longitudinal studies. Similar results were obtained across both studies. Supporting the ‘barometer hypothesis’, findings revealed that the optimal model included general latent factors for both personality traits and mental health. Compared to the broad raw pairwise correlations, the bi–factor latent change models revealed that the relation among levels and changes in the specific factors were substantially reduced when controlling for the general factors. Still, some relations remained relatively unaffected by the inclusion of the general factor. We discuss implications of these findings. Copyright © 2016 European Association of Personality Psychology
Learning to Use Learners' Advice

In this paper, we study a variant of the framework of online learning using expert advice with limited/bandit feedback. We consider each expert as a learning entity, seeking to more accurately reflecting certain real-world applications. In our setting, the feedback at any time $t$ is limited in a sense that it is only available to the expert $i^t$ that has been selected by the central algorithm (forecaster), \emph{i.e.}, only the expert $i^t$ receives feedback from the environment and gets to learn at time $t$. We consider a generic black-box approach whereby the forecaster does not control or know the learning dynamics of the experts apart from knowing the following no-regret learning property: the average regret of any expert $j$ vanishes at a rate of at least $O(t_j^{\regretRate-1})$ with $t_j$ learning steps where $\regretRate \in [0, 1]$ is a parameter. In the spirit of competing against the best action in hindsight in multi-armed bandits problem, our goal here is to be competitive w.r. t. the cumulative losses the algorithm could receive by following the policy of always selecting one expert. We prove the following hardness result: without any coordination between the forecaster and the experts, it is impossible to design a forecaster achieving no-regret guarantees. In order to circumvent this hardness result, we consider a practical assumption allowing the forecaster to "guide" the learning process of the experts by filtering/blocking some of the feedbacks observed by them from the environment, \emph{i.e.}, not allowing the selected expert $i^t$ to learn at time $t$ for some time steps. Then, we design a novel no-regret learning algorithm \algo for this problem setting by carefully guiding the feedbacks observed by experts. We prove that \algo achieves the worst-case expected cumulative regret of $O(\Time^\frac{1}{2 - \regretRate})$ after $\Time$ time steps.
A Metamodel of Unit Testing for Object-Oriented Programming Languages

A unit test is a method for verifying the accuracy and the proper functioning of a portion of a program. This work consists to study the relation and the approaches to test Object-Oriented Programming (OOP) programs and to propose a metamodel that enables the programmer to write the tests while writing the source code to be tested by exploiting the key features of OOP programming languages such as inheritance, polymorphism, etc.