Miracle-dz/UniFAR-FTUs huggingface dataset:
Age-related differences in adaptive decision making: Sensitivity to expected value in risky choice

While previous research has found that children make more risky decisions than their parents, little is known about the developmental trajectory for the ability to make advantageous decisions. In a sample of children, 5-11 years old, we administered a new risky decision making task in which the relative expected value (EV) of the risky and riskless choice options was varied over trials. Younger children (age 5-7) showed significantly less responsiveness to EV differences than their parents on both trials involving risky gains and trials involving risky losses. For older children (age 8-11) this deficit was smaller overall but was greater on loss trials than on gain trials. Children of both ages made more risky choices than adults when risky choices were disadvantageous. We further analyzed these results in terms of children's ability to utilize probability and outcome information, and discussed them in terms of developing brain structures vital for decision making under uncertainty.
Do Foreign Firms Crowd Out Domestic Firms? Evidence from the Czech Republic

I examine how foreign presence affects the growth and survival of domestic firms. Separating a negative crowding out and positive technology spillovers, I analyze whether the crowding out effect is dynamic, that is, domestic firms cut production over time as foreign firms grow, or a static effect realized on foreign entry into the industry. Using 19942001 firm-level Czech data, I find evidence of both technology spillovers and crowding out. However, crowding out is only short term; after initial entry shakeout, growing foreign sales increase domestic firm growth and survival, indicating domestic demand creation effect. However, I find no such benefits from domestic competition.
Reliability of 5-km Running Performance in a Competitive Environment

ABSTRACT The aim of this study was to examine the reliability of a 5-km time-trial during a competitive outdoor running event. Fifteen endurance runners (age = 29.5 ± 4.3 years, height = 1.75 ± 0.08 m, body mass = 71.0 ± 7.1 kg, 5-km lifetime personal best = 19:13 ± 1:13 minutes) completed two competitive 5-km time-trials over 2 weeks. No systematic differences in run time between Trial 1 and Trial 2 were reported (Trial 1: 1,217 ± 85 sec, 95% CI [1,170, 1,264]; and Trial 2: 1,216 ± 79 sec, [1,172 to 1,260], p = .855). Absolute reliability, expressed as the typical error (TE; 14.7 sec, 95% CI = 11.3–21.4 sec) and coefficient of variation (CV; 0.95 ± 0.65%, [0.59–1.31]) confirms the reliability of 5-km running performance in a competitive time trial.
Improved performance in TD-CDMA mobile radio system by optimizing energy partition in channel estimation

This letter addresses the optimum energy partition between the midamble and data fields, given the total energy per burst, in channel estimation for joint detected time-division code-division multiple-access systems. We show that, given the lengths of the data and midamble, in general, the optimal solution requires different amplitude levels. We also derive the burst structure leading to the optimum energy partition with equal amplitude symbols, and the performance degradation by using traditional choices. The analysis is validated by simulations.
The Compound Stimuli Visual Information (CSVI) Task Revisited: Presentation Time, Probability Distributions, and Attentional Capacity Limits

This study examined the validity of the Bose-Einstein (B-E) model of the Compound Stimuli Visual Information (CSVI) task, and its assumptions. Two experiments compared adults’ performance on the CSVI task in standard (5 sec) presentation condition and with shorter presentation times. Individual participants’ performance was analyzed with the B-E model, with different assumptions on the number of attending acts in each condition. Both experiments found that the capacity limit estimates found in both conditions were highly correlated with each other, and their means did not differ. The goodness of fit of B-E distributions to the data was also tested. It is concluded that the B-E model provides a valid estimate of attentional capacity limits in the CSVI.
When Technology Meets Human Desires

Adopting an alternative, yet complimentary view to the traditional, performance-based task/technology fit perspective, we examine the post-adoption of social network sites (SNS) by extending the concept of IT desirability as a central predictor of SNS continuous-use. We conceptualize SNS desirability as reflecting the affective relationship individuals experience with SNS, an approach that emphasizes both the IT and the individual as two social actors whose characteristics jointly determine the emotional outcome of their interactions. Based on the 16 basic desires of Sensitivity theory we explore individual differences to uncover intrinsic motives that can explain SNS continuous-use. We hypothesize that SNS desirability is influenced by the compatibility between individuals’ basic desires and the capability of an SNS to satisfy them. This individual-SNS fit is then hypothesized to influence SNS continuous-use through the construct of desirability. Subsequently, these hypotheses will be empirically assessed in the context of several popular SNSs.
A Convergent 3-Block SemiProximal Alternating Direction Method of Multipliers for Conic Programming with 4-Type Constraints

In this paper, we consider conic programming problems whose constraints consist of linear equalities, linear inequalities, a nonpolyhedral cone, and a polyhedral cone. A convenient way for solving this class of problems is to apply the directly extended alternating direction method of multipliers (ADMM) to its dual problem, which has been observed to perform well in numerical computations but may diverge in theory. Ideally, one should find a convergent variant which is at least as efficient as the directly extended ADMM in practice. We achieve this goal by designing a convergent semiproximal ADMM (called sPADMM3c for convenience) for convex programming problems having three separable blocks in the objective function with the third part being linear. At each iteration, the proposed sPADMM3c takes one special block coordinate descent (BCD) cycle with the order $1 \rightarrow 3 \rightarrow 2 \rightarrow 3$, instead of the usual $1 \rightarrow 2 \rightarrow 3$ Gauss--Seidel BCD cycle used in the nonconvergent directly extended 3-block ADMM, for updating the variable blocks. Our numerical experiments demonstrate that the convergent method is at least 20% faster than the directly extended ADMM with unit step-length for the vast majority of about 550 large-scale doubly nonnegative semidefinite programming problems with linear equality and/or inequality constraints. This confirms that at least for conic convex programming, one can design a convergent and efficient ADMM with a special BCD cycle of updating the variable blocks.
Asymptotic Ruin Probabilities and Optimal Investment for an Insurer

This thesis deals with the classical model of ruin theory given by a Poisson claim number process with identically and independently distributed single claims and a constant premium flow, but with the additional feature that the insurer has the possibility to invest in a risky asset. In Chapter 1 we first introduce the risk process (Section 1.1). Then we briefly discuss the distinction between light-tailed claim distributions and heavy-tailed claim distributions (Section 1.2) and classical results on (infinite time) ruin probabilities without investment possibility (Section 1.3). We finally introduce the investment possibility, modelled by geometric Brownian motion, in Section 1.4. Chapter 1 mainly serves the purpose of introducing notions and notations and gives a first idea of the problems to be considered thereafter. In Chapter 2, Section 2.1, we give an exponential upper bound on the minimal ruin probability of an insurer, who is incurring small claims (with exponential moments) and who invests in a risky asset modelled by geometric Brownian motion. (The minimal ruin probability is obtained by investing in an appropriate way.) The bound is smaller than the classical exponential Cramer–Lundberg bound without investment. The trading strategy yielding this exponential bound can be calculated explicitly. In Section 2.2 we give an exponential lower bound for the minimal ruin probability with the same exponent as in the case of the upper bound, under the assumption of a uniform exponential moment in the tail distribution. With the help of the latter result we can show that the constant investment strategy yielding the upper exponential bound is asymptotically optimal, as the initial reserve of the insurer tends to infinity (Section 2.3). In Section 2.4 we show that – without the assumption of a uniform exponential moment in the tail distribution – for arbitrary initial reserve, the insurer either gets ruined, or she becomes infinitely rich as time goes to infinity. In Section 2.5 we compare the constant investment strategy, which we obtain explicitly, with the constant investment strategy, which is optimal in the well-known diffusion approximation, for exponentially distributed claims. Then the generalization of the above results to a setting with more than one risky asset is discussed (Section 2.6). Finally, we present an example for a claim size distribution with exponential moments, but no uniform exponential moment in the tail distribution (Section 2.7). Chapter 3 deals with the generalization of the results of Chapter 2 to a setting, where the investment possibility is modelled by an exponential Levy process. Section 3.1 provides
Traffic Shaping of Spam Botnets

Compromised computers, known as bots, are the major source of spamming. Detecting them can help greatly improve control of unwanted traffic. In this paper, we develop a traffic control mechanism to detect and delay the traffic of suspicious senders and bots. By delaying spammer's traffic, it has been reported that 90% of spam emails can be eliminated. In our proposed mechanism, we group spammers based on their behavior and transmission patterns. These patterns of spammers show high correlation between group members irrespective of geographic location, network ID, content, and kind of receivers. After identification of these botnet groups we applied traffic shaping techniques a pre-filtering analysis to avoid use of automated machines(bots) to spam a particular domain. Thus the source for majority of spam is blocked before reaching email servers. We also identify how randomly the botnets behave and how easy it is to capture a botnet behavior, based on Information theory. To our knowledge, there is no work reported on detecting and mitigating botnets based on their behavior and in particular transmission patterns.
ANALISIS PENGARUH ILLUSION OF CONTROL, BETTER-THAN-AVERAGE, MISCALIBRATION, DESIRABILITY BIAS DAN PENDIDIKAN TERHADAP PERILAKU OVERCONFIDENCE(Studi Kasus pada Mahasiswa Ekonomi & Non-Ekonomi Universitas Diponegoro dalam Pengambilan Keputusan Keuangan)

Overconfidence is a behaviour where someone, feeling very confident about the things, ignoring unimportant factors, taking excessive risk because of their abilities. This is one of bias in behavioural finance, which is the modern financial theory that has a relation with the economics and psychological factors. Overconfidence itself affected by cognitive biases such as an illusion of control, better-than-average, miscalibration, desirability bias and education. This study will take a case study on the economic students and non-economic students through financial decision. Research population used was bachelor degree students at the Diponegoro University, and taken samples of the all-purpose 172 respondents which consisting of two categories. First, respondent against a background of economic education, and the second one is respondent with non-economics educational background. The separation of the group performed in order to know whether there are significant differences regarding the overconfidence behaviour in terms of financial decisions. The results showed that the illusion of control, better-than-average and desirability bias in respondents from the Faculty of Economics & Business has a positive and significant effect to the overconfidence related in financial decisions. Otherwise, miscalibration indicate negative and significant effect on overconfidence behaviour. Different side shown by respondents from NON-Faculty of Economics & Business. The results showed that the illusion of control and better-than-average has a positive and significant effect to the overconfidence. Furthermore, desirability bias has the positive and no significant effect on the overconfidence behaviour. While miscalibration has the negative and no significant effect on overconfidence. Mastery in economic and finance have a positive and significant influence to create overconfidence behavioural in terms of financial decision with the coefficient value of 0,591.
Investigating the Neural Correlates of Crossmodal Facilitation as a Result of Attentional Cueing: An Event-Related fMRI Study

Attentional cueing modulated neural processes differently depending on input modality. I used event-related fMRI to investigate how auditory and visual cues affected reaction times to auditory and visual targets. Behavioural results showed that responses were faster when: cues appeared first compared to targets and cues were auditory versus visual. The first result was supported by an increase in BOLD percent signal change in sensory cortices upon cue but not target presentation. Task-related activation patterns showed that the auditory cue activated auditory and visual cortices while the visual cue activated the visual cortices and the fronto-polar cortex. Next, I computed brain-behaviour correlations for both cue types which revealed that the auditory cue recruited medial visual areas and a fronto-parietal attentional network to mediate behaviour while the visual cue engaged a posterior network composed of lateral visual areas and subcortical structures. The results suggest that crossmodal facilitation occurs via independent neural pathways depending on cue modality. iii Acknowledgments
Random Effects Modeling Approaches for Estimating ROC Curves from Repeated Ordinal Tests without a Gold Standard

Summary Estimating diagnostic accuracy without a gold standard is an important problem in medical testing. Although there is a fairly large literature on this problem for the case of repeated binary tests, there is substantially less work for the case of ordinal tests. A noted exception is the work by Zhou, Castelluccio, and Zhou (2005, Biometrics61, 600–609), which proposed a methodology for estimating receiver operating characteristic (ROC) curves without a gold standard from multiple ordinal tests. A key assumption in their work was that the test results are independent conditional on the true test result. I propose random effects modeling approaches that incorporate dependence between the ordinal tests, and I show through asymptotic results and simulations the importance of correctly accounting for the dependence between tests. These modeling approaches, along with the importance of accounting for the dependence between tests, are illustrated by analyzing the uterine cancer pathology data analyzed by Zhou et al. (2005) .
Contrast masking e ects may disappear with practiceAlain

Contrast detection thresholds are known to increase with background contrast, a phenomenon called contrast masking. We found that, under some conditions, observers improved their masked detection performance by repetitive practice of a masking experiment. This learning eeect resulted in a cancelation of suprathresh-old contrast masking within the contrast range measured. A 2AFC discrimination paradigm was used, with stimuli consisting of Gabor signals as maskers and target, presented at the same location and time. Untrained observers showed increased detection thresholds with increasing mask contrast for suprathreshold mask contrasts , but perceptual learning caused an elimination of this classical eeect, with masked thresholds reaching the no-mask level and below. Learning did not decrease , but rather somewhat increased, discrimination thresholds when target and mask shared the same Gabor signal parameters. Performance improvement was found to be speciic for orientation and mask conngurations, though it did transfer between mirror symmetric mask conngurations and between eyes. These results argue against a static transducer function based account for contrast masking and are consistent with a theory assuming multiple feature based interactive network capable of long term gain modiications.
Context adaptive variable length decoder of H.264

This paper presents a software implementation of context adaptive variable length decoder (CAVLD) and context adaptive variable length coder (CAVLC). Efficient algorithms for coding and decoding of Coeff_Token, levels, total zeros, and run_before have been developed, which are the five vital syntax elements of CAVLC and CAVLD. The necessary blocks namely Integer Transform, quantization and their inverses are also coded. This implementation can process video sequences of any size. Experiments have been conducted to process video sequences up to High Definition 720p (1280×720 pixels) resolution and up to 30fps frame rate and also for high resolution pictures. The reconstructed pictures are of acceptable video quality with PSNR values greater than 34dB. The design can be conFig.d to different Qp values. The proposed work is coded using matlab and serves as a basis for FPGA implementation of H.264 Base line video decoder.
Hyperspectral Signal Processing Applications in Environmental Monitoring Identification and Mapping of the Invasive Plant Species Purple Loosestrife

The invasive plant Purple Loosestrife (Lythrum salicaria) is considered a threat to numerous ecosystems across the United States. It was introduced from Europe to North America in the 1800s. Now known as the "purple plague", it has spread across 48 of 50 states in the US and all provinces in Canada. The U.S. Fish and Wildlife Service declared Purple Loosestrife "Public Enemy #1 on Federal Lands", and The Nature Conservancy listed it as the 2nd most troublesome weed in wetlands. Monitoring and mapping of Purple Loosestrife is a challenge due to the difficulty of access to the vast, remote and most often privately owned marsh lands of New York State. This paper presents the results of a recent study of hyperspectral signal processing for the identification, classifying and mapping of Purple Loosestrife. A set of combined methods of signal processing were used including: geographic calibration, atmospheric correction, minimum noise fraction, pixel purity index, regions of interesting locating, hyperspectral library creation and spectral angle mapper classification. The classification accuracy is significantly increased (91.7%) due to the application of the self-built hyperspectral library STIHL
Transformational leadership on the athletic field: An international review

This paper provides a comprehensive review of the international literature that used the paradigm of transformational leadership in the context of physical activity (PA) and sport. A bibliometric and content of all international publications (N = 28) analysis is performed by classifying research based on various parameters such as the contexts (high performance sports, educational/recreational sports, varsity sports, school/within-class of physical education), role of the leader studied (coaches, teachers/instructors, peers, parents), population (adolescents and adults), and variables that have been associated with transformational leadership style. This study supported the interest and applicability of transformational leadership paradigm in PA and sport context. Implications and future research are discussed.
Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices

A gamma process dynamic Poisson factor analysis model is proposed to factorize a dynamic count matrix, whose columns are sequentially observed count vectors. The model builds a novel Markov chain that sends the latent gamma random variables at time $(t-1)$ as the shape parameters of those at time $t$, which are linked to observed or latent counts under the Poisson likelihood. The significant challenge of inferring the gamma shape parameters is fully addressed, using unique data augmentation and marginalization techniques for the negative binomial distribution. The same nonparametric Bayesian model also applies to the factorization of a dynamic binary matrix, via a Bernoulli-Poisson link that connects a binary observation to a latent count, with closed-form conditional posteriors for the latent counts and efficient computation for sparse observations. We apply the model to text and music analysis, with state-of-the-art results.
Conditions for ignoring failures based on a requirements model

Ideally, all system failures should be compensated. In fact, most failure-prone systems try to compensate all their failures. However, sometimes a compensation is not essential. Hence, diagnosing and compensating each and every one of their failures may be ineffective. Thus, this work aims to increase the flexibility of failure handling in self-configuring systems, using tolerance policies based on requirements models. We allow the expression of conditions in which certain failures may be ignored – i.e., conditions in which a failure will not be compensated. Such policies may lead to reduced costs and performance improvement. The FAST 1 framework consists of the definition of a tolerance policy, the mechanisms to evaluate this policy and a tool to aid the creation and maintenance of policies. We use a Smart Office system to show the several types of policy rules in action.
RETURNS OF EDUCATION OF COLOMBIAN COUNTERS. HUMAN CAPITAL PERSPECTIVE RETORNO DA EDUCAÇÃO DE CONTADORES COLOMBIANOS. PERSPECTIVA DO CAPITAL HUMANO

RESUMEN El siguiente artículo es la continuación del proyecto investigativo “análisis de los retornos de la educación de los técnicos, tecnólogos egresados de las ciencias económicas desde la perspectiva del capital humano entre el periodo 2001-2012 como de la emulación de una tesis de grado de Maestría en la cual su objetivo general fue analizar la situación laboral de los docentes colombianos (Gómez & Barbosa, 2014). A diferencia con este pero siguiendo el mismo marco teórico, el siguiente artículo pretende identificar la retornos a la educación de los egresados de contaduría en Colombia desde los postulados de la teoría del capital humano en los periodos 2009-2012. Para ello se utilizaron ecuaciones Mincerianas del ingreso, se corrigió el sesgo de selección por el método propuesto por Heckman (1979), con datos de la G.E. I.H. (Gran Encuesta Integrada de Hogares) para las 12 profesiones escogidas. La principal conclusión es que los egresados de contaduría en el periodo estudiado evidencian retornos a la educación por debajo de la gran mayoría de las profesiones.
A LONGITUDINAL STUDY OF ENROLLMENT TRENDS AND GRADUATION GPAs FOR MEN AND WOMEN IN CIS PROGRAMS

Despite expanding opportunities, women are increasingly demonstrating a lack of interest in computer-related majors at the undergraduate level at virtually every American university. This research study focuses on enrollment characteristics of females entering computer studies (IT /IS) over a period of 12 years at a mid-sized university. The salient factors being tested by gender are the incoming SAT (Math, Verbal and Total) scores and the final outgoing GPA scores at the conclusion of the student academic experience. Thus aptitude is correlated with performance for a direct statistical comparison by gender. Pattern differences, also by gender, are examined at the enrollment stage. Additionally, salient factors such as demographic and professional characteristics, work-life balance, contextual influences, positive experiences, family and teacher influences, stereotypical connotations, prior usage, and negative life-style aspects are woven into the fabric of the research endeavor.