Miracle-dz/UniFAR-FTUs huggingface dataset:
Broken Bodies, Broken Spirits: How Poor Health Contributes to A Cynical Worldview

Cynical hostility (or cynicism) is often considered as a major factor leading to bad health outcomes. The present research proposes that poor health might represent both a consequence and a source of cynicism. Using cross–lagged path analyses, we documented bidirectional associations between health and cynicism in a nationally representative sample of Germans (Study 1) and a large sample of the American elderly (Study 2): cynical individuals were more likely to develop health problems, and poor health promoted the development of a cynical worldview over time. These results were obtained using different indicators of health status, including both self–reported and interviewer–administered physical measures. Longitudinal mediation analyses showed perceived constraints to mediate the effect of poor health on cynicism. This effect remained robust even when adding an alternative mediator—depressive symptoms. Additional analyses showed that any particular health limitation was prospectively related to cynicism to the degree to which this limitation was associated with an increased sense of constraints in individuals’ life. © 2018 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology
Luminance-contrast-aware foveated rendering

Current rendering techniques struggle to fulfill quality and power efficiency requirements imposed by new display devices such as virtual reality headsets. A promising solution to overcome these problems is foveated rendering, which exploits gaze information to reduce rendering quality for the peripheral vision where the requirements of the human visual system are significantly lower. Most of the current solutions model the sensitivity as a function of eccentricity, neglecting the fact that it also is strongly influenced by the displayed content. In this work, we propose a new luminance-contrast-aware foveated rendering technique which demonstrates that the computational savings of foveated rendering can be significantly improved if local luminance contrast of the image is analyzed. To this end, we first study the resolution requirements at different eccentricities as a function of luminance patterns. We later use this information to derive a low-cost predictor of the foveated rendering parameters. Its main feature is the ability to predict the parameters using only a low-resolution version of the current frame, even though the prediction holds for high-resolution rendering. This property is essential for the estimation of required quality before the full-resolution image is rendered. We demonstrate that our predictor can efficiently drive the foveated rendering technique and analyze its benefits in a series of user experiments.
Real-time multi-resolution digital elevation map creation using the sensor model of a stereovision sensor

This paper presents an approach for constructing high quality Digital Elevation Maps (DEMs) from dense stereo data. As opposed to classical DEM creation algorithms, the proposed solution uses the sensor models of the stereovision sensor to correct the raw data. The direct and inverse sensor models are found from experiments. The algorithm decomposes the 2D cells containing vertical objects or object boundaries in order to model the objects more precisely. The approach distinguishes between 2 types of cells: cells containing horizontal and vertical objects. For the vertical object cells, connected components in the histogram of heights are found while in the horizontal object cells, the most representative height is determined using a mode-seeking approach similar to mean shift. The 3D reconstructed points are assigned to the cells around it by considering the probability of correspondence based on the 2D Gaussian component of the direct sensor model. In order to eliminate the noise, a similarity measure is computed between each 3D point and cell based on the calculated DEM cell descriptor and is discarded if the similarity score is smaller than a predefined threshold. The algorithm is implemented on the GPU in order to achieve a real-time execution speed and it is evaluated extensively in comparison with other DEM creation algorithms using the latest KITTI stereo benchmark data. The obtained DEM is denser, more accurate and the object boundaries are modeled more precisely.
Grid-Aware Network Resources Allocation using a Policy-Based Approach

Computing grids require the underlying network infrastructure to be properly configured for provisioning of appropriate communications among their nodes. The management of networks and grids are currently executed by different tools, operated by different administrative personnel. Eventually, the grid communication requirements need corresponding support from the network management tools, but such requirements are fulfilled only when grid administrators manually asks the network administrators for the corresponding configurations. In this paper, we propose a policy translation mechanism that creates network policies given grid requirements expressed in grid policies. We also present a system prototype that allows (a) grid administrators to define grid policies, and (b) network administrators to define translating rules. These translating rules are used by the translation mechanism proposed by this work for the generation of the necessary underlying network configuration policies. Resumo.Grids computacionais requerem que a infra-estrutura de rede subjacente seja adequadamente configurada para o fornecimento apropriado dos serviços de comunicaç ̃ o entre os nodos do grid. O gerenciamento da rede e do grid atualmente s ão executados atrav és de diferentes ferramentas, operadas por diferente pessoal administrativo. Eventualmente, os requisitos de comunicaç̃ao do grid precisam de um suporte de comunicaç ão orrespondente das ferramentas de gerenciamento de redes, mas esses requisitos somente s ão atendidos quando os administradores do grid manualmente requisitam aos administradores da rede as configuraç ões correspondentes. Este artigo prop õe um mecanismo de traduç ão de poĺ ıticas que cria poĺ ıticas de rede a partir dos requisitos do grid expressos nas pol ı́ticas de grid. É apresentado tamb ém um protótipo que permite (a) administradores de grid definirem pol ı́ticas de grid e (b) administradores da rede definirem regras de traduç ão. Essas regras de traduç̃ao s̃ao usadas pelo mecanismo de traduç ão proposto neste trabalho para geraç̃ao das poĺ ıticas necesś arias para configuraç̃ ao da rede subjacente.
A Dichotomic Search Algorithm for Mining and Learning in Domain-Specific Logics

Many application domains make use of specific data structures such as sequences and graphs to represent knowledge. These data structures are ill-fitted to the standard representations used in machine learning and data-mining algorithms: propositional representations are not expressive enough, and first order ones are not efficient enough. In order to efficiently represent and reason on these data structures, and the complex patterns that are related to them, we use domain-specific logics. We show these logics can be built by the composition of logical components that model elementary data structures. The standard strategies of top-down and bottom-up search are ill-suited to some of these logics, and lack flexibility. We therefore introduce a dichotomic search strategy, that is analogous to a dichotomic search in an ordered array. We prove this provides more flexibility in the search, while retaining completeness and non-redundancy. We present a novel algorithm for learning using domain specific logics and dichotomic search, and analyse its complexity. We also describe two applications which illustrates the search for motifs in sequences; where these motifs have arbitrary length and length-constrained gaps. In the first application sequences represent the trains of the East-West challenge; in the second application they represent the secondary structure of Yeast proteins for the discrimination of their biological functions.
An Improved Signcryption with Proxy Re-encryption and its Application

Signcryption with proxy re-encryption was proposed recent by Chandrasekar. However, his scheme did not provide public verifiability, which is a desirable property in applications such as certified e-mail protocol. In this paper we firstly improve a id-based signcryption with proxy re-encryption scheme, which provides public verifiable property in a way that any third party can verify the validity, then based on this scheme we propose a modified signcryption with proxy re-encryption so that it can be used as a cryptographic primitive of certified e-mail protocol, finally we present a certified e-mail protocol in id-based setting with semi-trusted third party which reduce the trust extent of third party, and improve the efficiency and practice.
ARtalet: Tangible User Interface Based Immersive Augmented Reality Authoring Tool for Digilog Book

A Digilog Book is an augmented reality (AR) based next generation publication supporting both sentimental analog emotions and immersive digital contents to improve a user’s experience. This paper enhances the Digilog Book authoring tool, ARtalet. This is a tangible user interface based immersive AR authoring tool providing an intuitive non-programming based authoring methods using a 3D user interface in an AR environment. As novel authoring functions, we propose 3D object trajectory manipulation, real-time deformation, and audio/vibration feedback authoring functions to enhance a user’s experience and interest. The ARtalet can be applicable to other Digilog application authoring, including posters, pictures, newspapers, and sign boards*.
Pedagogical Beliefs about Critical Thinking among Indonesian Mathematics Pre-service Teachers

This study aims to (1) measure pre-service teachers’ pedagogical belief in the value of teaching Critical Thinking (CT), their preparedness to teach CT, and their preference toward constructivist teaching approaches to develop students’ CT skills; and (2) explore the potential links between these pedagogical beliefs and aspects of teacher education experience. Participants were 223 mathematics pre-service teachers from 3 teacher education institutions in East Java, Indonesia. Beliefs about the value of teaching CT and perceived readiness to teach CT were measured using Likert-type scales, while preference towards constructivist instruction was assessed using vignettes depicting teaching dilemmas. Participants believed that some CT skills (thinking independently and logical communication) were important, but CT dispositions were not. About 60% believed they are prepared to teach CT and generally preferred constructivist over traditional instruction. Most aspects of the pre-service education were not associated with pedagogical beliefs about CT disposition, perceived preparedness, or preference for constructivist instruction, while some were only weakly associated with belief about teaching CT skills. These highlight the need for mathematics teacher educators to give more emphasis on the importance of CT, especially its dispositional dimensions, and the role of constructivist instruction in developing CT.
Energy Efficient Client-Centric Shaping of Multi-flow TCP Traffic

Energy consumption is a concern with mobile de-vices nowadays. Network interfaces are among the most power hungry components in these devices. In this paper, we describe the design and implementation of a client-centric protocol for energy efficiency. Inspired by earlier work, our protocol works by exploiting the TCP flow-control mechanism to shape incoming traffic into bursts in order to utilize the unused bandwidth between the server and the client. Our solution works with multiple simultaneous connections and it is extensible to different scheduling policies. Furthermore, the purely client-centric nature of the protocol enables easier deployment of the solution. The protocol is application independent and it is targeted for bulky TCP transfers. The solution can be used on Linux based systems and is kept portable as it can be deployed with different wireless devices without major modifications. We have tested our solution with real web-servers and our results show that the protocol can achieve sleep time up to 80 percent and 45percent of total duration of one and four active simultaneous connections, respectively.
Analysis of Optical Signals Evoked by Peripheral Nerve Stimulation in Rat Somatosensory Cortex: Dynamic Changes in Hemoglobin Concentration and Oxygenation

The origins of reflected light changes associated with neuronal activity (optical signals) were investigated in rat somatosensory cortex with optical imaging, microspectrophotometry, and laser-Doppler flowmetry, and dynamic changes in local hemoglobin concentration and oxygenation were focused on. Functional activation was carried out by 2-second, 5-Hz electrical stimulation of the hind limb under chloralose anesthesia. These measurements were performed at the contralateral parietal cortex through a thinned skull. Regional cortical blood flow (rCBF) started to rise 1.5 seconds after the stimulus onset, peaked at 3.5 seconds (26.7% ± 9.7% increase over baseline), and returned to near baseline by 10 seconds. Optical signal responses at 577, 586, and 805 nm showed a monophasic increase in absorbance coincident with the increase in rCBF; however, the signal responses at 605 and 760 nm were biphasic (an early increase and late decrease in absorbance) and microanatomically heterogeneous. The spectral changes of absorbance indicated that the concentrations of both total hemoglobin and oxyhemoglobin increased together with rCBF; deoxyhemoglobin, increased slightly but distinctly (P = 0.016 at 1.0 seconds, P = 0.00038 at 1.5 seconds) just before rCBF increases, then decreased. The authors conclude that activity-related optical signals are greatly associated with a moment-to-moment adjustment of rCBF and metabolism to neuronal activity.
Audio Watermarking Based on Reverberation

To get the best effect of art, the music should be added different artificial reverberation. A new watermarking method based on reverberation theory is proposed in this paper. The embed process same as the process that adds reverberation to recordings in music studio to make it sound quite natural like in a real concert hall. The watermark are embedded by convoluting the original audio signal and a room impulse response that obtained by image method[4]. The parameters for calculating the room impulse response are used as secret key that must be used in the decoding process to ensure security. When decoding, homomorphic deconvolution method is used to separate the kernel function from the cepstrum of the watermarked audio signal, and then take cross-correlation with the delay sequence of room impulse response to get watermark by searching the peak.
Efficient Data Gathering in Intermittent Connected Mobile Sensor Networks

Intermittent Connected Mobile Sensor Networks (ICMSN) have emerged in recent studies, e.g. underwater sensor networks, wildlife tracking and human-oriented flu virus monitoring. In these networks, conventional routing protocols in WSN are not suitable for data gathering application in ICMSN since packets will be dropped when no complete route to the sink is available. In this paper, we propose an efficient data gathering scheme for ICMSN, which is composed of forwarding protocol and buffer management. Message forwarding makes decision on which sensors are qualified for next hop based on nodal delivery probability, which signifies the likelihood that the sensor can deliver the message to the sink successfully based on the nodal mobility pattern and residual energy. Buffer management consists of two related components: queuing mechanism and purging mechanism. The former determines priority of messages to transmit based on the importance factor, which indicates importance of the messages and QoS requirement of transmission. The latter utilizes a death vector generated by the sink to purge useless messages that have been delivered from the network. Our experimental results show that the proposed data gathering scheme supports the different transmission requirement of messages and achieves the good performance tradeoff between delivery ratio, delay and resource consumption.
Parameter estimation of a lead-acid battery model using genetic algorithm

Lead-Acid batteries models classifications are shown. The battery model used and its charging and discharging equations are shown. These equations are expanded to find the value of the time constant of this model, which is fixed at a given value. A genetic algorithm is applied to these expanded equations to estimate the value of the time constant. Some battery charging and discharging cycles are used for estimation and validation of the proposed system. A time constant other than the previously set value is found. A simulation study is used to demonstrate the feasibility of the proposed parameter determination method.
The String Subsequence Kernel in Text Classification with SVMs

The support vector machine (SVM) is a method of predicting the classification of input data. Given a set of positive and negative training examples of a class, a binary SVM classifier represents the examples in a high-dimensional space and finds the separating hyperplane between the two classes with the highest margin. If the input data is not linearly separable, it can be transformed into a higher-dimensional feature space. For efficient computation, a kernel function may be used to directly compute the inner product between data points in the feature space without explicitly representing the data in the higherdimensional feature space, thus avoiding the high computational costs associated with feature extraction in the higher-dimensional space.
Risk factors for efflux pump overexpression in fluoroquinolone-resistant Escherichia coli.

BACKGROUND We conducted a case-control study to identify risk factors for efflux overexpression, an important mechanism of fluoroquinolone resistance, among patients with fluoroquinolone-resistant Escherichia coli (FQREC) gastrointestinal tract colonization. METHODS Three annual fecal surveillance surveys were performed hospital-wide, and all patients colonized with FQREC (levofloxacin minimum inhibitory concentration, ≥8 μg/mL) were included in the study. Cases and controls were defined on the basis of overexpression of the AcrAB efflux pump, as measured by the organic solvent tolerance (OST) assay. A multivariable logistic regression model was developed to identify risk factors for OST positivity among patients with FQREC colonization. RESULTS Eighty-nine patients were colonized with FQREC: 44 (49.4%) and 45 (50.6%) patients had isolates that were OST-positive and OST-negative, respectively. On multivariable analyses, location on the surgical service was significantly associated with recovery of an OST-positive isolate (odds ratio, 7.36; 95% confidence interval, 1.82-29.7; P = .005). Furthermore, patients who had received a first-generation cephalosporin in the 30 days prior to sampling were less likely to have an OST-positive isolate (odds ratio, 0.20; 95% confidence interval, .04-.94; P = .04). CONCLUSIONS Among phenotypically identical FQREC isolates, different factors may drive the emergence of different resistance mechanisms. Further studies are needed to elucidate the relationship between antimicrobial use and specific resistance mechanisms.
ASSOCIATION FOR CONSUMER RESEARCH

In political campaigns candidates communicate with voters for a long period of time before the actual choice decision. What these candidates say and to whom as well as how they say it, is likely critical to their success. We draw from temporal construal theory to predict that the degree of abstraction (“why” laden appeals) versus concreteness (“how” laden appeals) of the message will be differentially persuasive depending on the temporal proximity of the choice. In three studies the effect is found to be strongest for uninvolved and uninformed subjects, who are more likely to be persuaded by peripheral cues.
Hybrid Machine Learning/Analytical Models for Performance Prediction: A Tutorial

Classical approaches to performance prediction of computer systems rely on two, typically antithetic, techniques: Machine Learning (ML) and Analytical Modeling (AM). ML undertakes a black-box approach, which typically achieves very good accuracy in regions of the features' space that have been sufficiently explored during the training process, but that has very weak extrapolation power (i.e., poor accuracy in regions for which none, or too few samples are known). Conversely, AM relies on a white-box approach, whose key advantage is that it requires no or minimal training, hence supporting prompt instantiation of the target system's performance model. However, to ensure their tractability, AM-based performance predictors typically rely on simplifying assumptions. Consequently, AM's accuracy is challenged in scenarios not matching such assumptions. This tutorial describes techniques that exploit AM and ML in synergy in order to get the best of the two worlds. It surveys several such hybrid techniques and presents use cases spanning a wide range of application domains.
Designing Student Affairs Organizational Structures: Perceptions of Senior Student Affairs Officers

Student affairs organizations have become complex entities and serve as a critical link to student success and the quality of the overall educational experience in collegiate institutions. Over time, new programs and services have been added to the array of existing programs and services with little attention focused on how these organizations might be designed to effectively meet the institution’s mission or address student needs. This research study was designed, in part, to investigate student affairs organizational structures within colleges and universities across the United States. The focus of this study was on the design and structure of student affairs organizations, but it also investigated where in the institution the senior student affairs officer reported. It explored questions related to what changes were made in student affairs organizations and why. The findings indicated that some change has occurred in student affairs organizations, but these changes have been modest. While student affairs organizations have retained their functional structures they also appeared to be generally organized by institutional type, and as a result somewhat reflective of institutional mission. The influences of revenue source and availability of resources appeared to remain the dominant influences in the current functional structures of student affairs organizations. While some of the desired reasons for organizational redesign appeared to be strategic and environmentally oriented, the actual changes and redesigns that were reported were not directly focused on these issues. These findings have implications for student affairs organizational effectiveness in the future.
Multi-Objective Genetic Programming with Redundancy-Regulations for Automatic Construction of Image Feature Extractors

We propose a new multi-objective genetic programming (MOGP) for automatic construction of image feature extraction programs (FEPs). The proposed method was originated from a well known multi-objective evolutionary algorithm (MOEA), i.e., NSGA-II. The key differences are that redundancy-regulation mechanisms are applied in three main processes of the MOGP, i.e., population truncation, sampling, and offspring generation, to improve population diversity as well as convergence rate. Experimental results indicate that the proposed MOGP-based FEP construction system outperforms the two conventional MOEAs (i.e., NSGA-II and SPEA2) for a test problem. Moreover, we compared the programs constructed by the proposed MOGP with four human-designed object recognition programs. The results show that the constructed programs are better than two human-designed methods and are comparable with the other two human-designed methods for the test problem.