Miracle-dz/UniFAR-FTUs huggingface dataset:
Öğrenmeye Yönelik Epistemolojik İnançlar Ölçeğinin Uygulamalı Uyarlama ve Güvenirlik Çalışması

Article Info The basic of the current research was to conduct the Turkish langauge adaptation, reliability and validity analyses of the Epistemological Belief Scale Towards Learning (EBSTL) that had been developed by Sing-Chai, Teo, and Beng-Lee (2009). In addition, the participatory prospective teachers’ (PTs) epistemological beliefs about learning were also explored in terms of gender, academic attainment, age, grade level and academic program type variables. The current research was conducted by the participation of 395 prospective teachers who were enrolled in İstanbul Aydın University’s Faculty of Education. Exploratory factor analysis demonstrated that EBSTL, incorporating 23 items, were composed by four sub-factors labelled as attaining the knowledge, nurture vs. nature, absolute and single reality and epistemic confliction. The established model was found out as acknowledgeable in terms of goodness-of-fit indices that were extracted by virtue of the confirmatory factor analysis. Mann Whitney-U and Kruskal Wallis-H tests for variance analyses confirmed the fact that the PTs epistemological beliefs about learning were significantly differed for the gender variable; however, no significant differences were revealed for the grade level and academic program types. Multiple regression analysis’ results also showed that there was a positive and lower relation among the variables as epistemological beliefs about learning, ages and academic attainments of the PTs.
Understanding Rapid Spanning Tree Protocol ( 802 . 1 w )

Introduction Support of RSTP in Catalyst Switches New Port States and Port Roles Port States Port Roles New BPDU Format New BPDU Handling BPDU are Sent Every Hello-Time Faster Aging of Information Accepting Inferior BPDUs Rapid Transition to Forwarding State Edge Ports Link Type Convergence with 802.1D Convergence with 802.1w Proposal/Agreement Sequence UplinkFast New Topology Change Mechanisms Topology Change Detection Topology Change Propagation Compatibility with 802.1D Conclusion NetPro Discussion Forums Featured Conversations Related Information Cisco Understanding Rapid Spanning Tree Protocol (802.1w)
Racial-Cultural Events in Group Therapy as Perceived by Group Therapists

ABSTRACT This qualitative study explored the nature of the retrospective experiences of helpful and difficult racial-cultural events in group therapy as perceived by eight White group therapists and six group therapists of color who had a minimum of 5 years of experience working in a variety of group therapy settings. Racial-cultural events are incidents, interactions, or processes in a therapy group that are interpreted as related to or influenced by visible racial dimensions, and any stereotypes and assumptions pertaining to those dimensions. Participants completed demographic questionnaires and in-depth, semistructured telephone interviews. Interviews were audiotaped and transcribed, and then the transcriptions were analyzed using grounded theory, resulting in three main emergent themes: (a) helpful events, (b) mixed events, and (c) hindering events. Study findings provide insight into effective group therapy with multicultural populations and offer directions for future research.
Weighted Acma

The analytical constant modulus algorithm (ACMA) is a deterministic array processing algorithm to separate sources based on their constant modulus. It has been derived without detailed regard to noise processing. In particular, the estimates of the beamformer are known to be asymptotically biased. In the present paper, we investigate this bias, and obtain a straightforward weighting scheme that will whiten the noise and remove the bias. This leads to improved performance for larger data sets.
Age , Gender and Race Estimation from Unconstrained Face Images

Automatic estimation of demographic attributes (e.g., age, gender, and race) from a face image is a topic of growing interest with many potential applications. Most prior work on this topic has used face images acquired under constrained and cooperative scenarios. This paper addresses the more challenging problem of automatic age, gender, and race estimation from real-life face images (face images in the wild) acquired in unconstrained conditions. Given an input face image, we first normalize it by performing pose and photometric corrections. Biologically inspired features (BIF) are then extracted from the normalized face image, including both the central face region and the surrounding context region. Given this representation, three different Support Vector Machines (SVM) are used to predict the age group (or exact age), gender, and race of a subject. Experimental results on two large public-domain unconstrained face databases (Images of Groups and LFW) show that the proposed approach significantly outperforms the stateof-the-art methods. Our results also highlight that extraction of demographic attributes from face images in the wild is a difficult problem.
Recent Advances in Digital Halftoning and Inverse Halftoning Methods

Halftoning is the rendition of continuous-tone pictures on displays, paper or other media that are capable of producing only two levels. In digital halftoning, we perform the gray scale to bilevel conversion digitally using software or hardware. In the last three decades, several algorithms have evolved for halftoning. Examples of algorithms include ordered dither, error diffusion, blue noise masks, green noise halftoning, direct binary search (DBS), and dot diffusion. In this paper, we first review some of the algorithms which have a direct bearing on our paper and then describe some of the more recent advances in the field. The dot-diffusion method for digital halftoning has the advantage of pixel-level parallelism unlike the error-diffusion method, which is a popular halftoning method. However, the image quality offered by error diffusion is still regarded as superior to most of the other known methods. We first review error diffusion and dot diffusion, and describe a recent method to improve the image quality of the dot-diffusion algorithm which takes advantage of the Human Visual System (HVS) function. Then, we discuss the inverse halftoning problem.
Peer-Mediated Literacy-Based Behavioral Interventions: A Job Coaching Strategy for Secondary Students With ASD

Many secondary students with autism spectrum disorder (ASD) are not taught employability skills and routines needed for competitive or supported employment in regular community environments. Literacy-based behavioral interventions (LBBIs) that combine print, pictures, and behavioral rehearsal are effective for promoting acquisition and maintenance of numerous skills, but have not been investigated as a job coaching intervention for individuals with ASD. In this study, a peer coworker was taught to deliver an LBBI guide to students with ASD as a job coaching intervention for three skills in an employment preparation routine: preparing and selling coffee in a work-site food truck. Results showed students’ accuracy with the skills in the work routine increased, and maintained after the intervention.
Iron limits the cell division rate of Prochlorococcus in the eastern equatorial Pacific

Prochlorococcus, a small unicellular cyanobacterium, is an important member of the phytoplankton community in the eastern equatorial Pacific. When these waters were enriched with iron during IronEx II, the chlorophyll per cell and cell size of Prochlorococcus increased, implying that they were iron limited. The extent of this limitation was unclear, however, and the number of Prochlorococcus remained constant. To examine whether cell division rates were stimulated significantly by iron, we used a cell cycle analysis approach to measure them in and out of the Fe‐enriched patch and in Fe‐enriched bottles. The cell division rate increased from 0.6 to 1.1 d−1 over 6 d of exposure to the elevated iron concentrations in the patch. Cells incubated in bottles with additional iron had rates of 1.4 d−1 or two doublings per day. Prochlorococcus mortality rates, measured independently, nearly doubled after the addition of iron. This matched the increase in the cell division rate and maintained a relatively constant population size. Thus the cell division rates of even the smallest phytoplankton in the equatorial Pacific are significantly iron limited, but biomass is constrained by both iron limitation and microzooplankton grazing. The differential response of individual phytoplankton groups to the addition of iron during IronEx II was at least partially a result of differential mortality rates over the time course of the experiment. How the community would respond to sustained fertilization, however, is not obvious.
Solitary pulmonary nodule: characterization with combined wash-in and washout features at dynamic multi-detector row CT.

PURPOSE To prospectively assess the accuracy of combined wash-in and washout characteristics at dynamic contrast material-enhanced multi-detector row computed tomography (CT) in distinguishing benign from malignant solitary pulmonary nodules. MATERIALS AND METHODS Institutional review board approval and informed consent were obtained. The study included 107 patients (62 men, 45 women; mean age, 55 years; range, 22-81 years) with a solitary pulmonary nodule. After unenhanced CT (2.5-mm collimation) scans were obtained, dynamic CT was performed by using a helical technique (series of images obtained throughout the nodule, with 2.5-mm collimation, at 30, 60, 90, and 120 seconds and 4, 5, 9, 12, and 15 minutes) after intravenous injection of contrast medium (120 mL). Tissue diagnosis was made in 70 nodules, and follow-up images showed benignancy in the remaining 37 (no change in size, n = 32; decrease in size, n = 5). CT findings were analyzed in terms of wash-in and washout of contrast medium. Sensitivity, specificity, and accuracy for malignant nodules were calculated by considering both the wash-in and washout characteristics at dynamic CT. RESULTS There were 49 malignant and 58 benign nodules. When diagnostic criteria for malignancy of both wash-in of 25 HU or greater and washout of 5-31 HU were applied, sensitivity, specificity, and accuracy for malignancy were 94% (46 of 49 nodules), 90% (52 of 58 nodules), and 92% (98 of 107 nodules), respectively. Of 58 benign nodules, 27 showed less than 25 HU wash-in, 14 showed persistent contrast enhancement without washout and with wash-in of 25 HU or greater, and 11 showed washout greater than 31 HU and wash-in of 25 HU or greater. CONCLUSION Evaluation of solitary pulmonary nodules by analyzing combined wash-in and washout characteristics at dynamic contrast-enhanced multi-detector row CT showed 92% accuracy for distinguishing benign nodules from malignant nodules.
I/O Throttling and Coordination for MapReduce

As a leading framework for data intensive computing, MapReduce has gained enormous popularity in large-scale data analysis. With the increasing adoption of multi/many core platform, more and more MapReduce tasks are now running on the same node and sharing the same storage resources. The concurrency of tasks raises the issue of I/O stream congestion. We have observed significant throughput drops and task delays caused by I/O stream congestion in the MapReduce framework. In this paper, we propose two techniques to address the I/O stream congestion in MapReduce tasks. First, I/O stream throttling is presented to limit the number of concurrent I/O streams, and avoid throughput drops. Furthermore, to alleviate the I/O contention among multiple MapReduce jobs, I/O coordination orders the I/O streams in accordance to job priority. By exclusively granting I/O resources to streams with higher priorities, the coordination effectively shortens the average job completion time. Experimental results from Hadoop confirm that the proposed techniques improve the average job completion time by up to 33.74%. In addition, the proposed techniques greatly accelerate the execution of high priority jobs; thereby, showing it is capable of fostering QoS in the MapReduce framework. KeywordsI/O stream; MapReduce; I/O scheduling; throttling; coordination
Poisson noise removal via learned dictionary

In this paper, we address the restoration of images corrupted by Poisson noise. The proposed new model contains two terms: one is from the sparse representation of the transformed image via variance stabilizing transformation (VST); the other is a data-fidelity term caused by the statistical properties of Poisson noise. The main algorithm is efficient. We first learn a dictionary to sparsely represent the transformed image using a state-of-the-art dictionary learning method, and then solve the minimization of the variational form by Newton method. Comparative experiments are carried out to show the leading performance of our new model.
Capturing Human Motion based on Modified Hidden Markov Model in Multi-View Image Sequences

Human motion capturing is of great importance in video information retrieval, hence, in this paper, we propose a novel approach to effectively capturing human motions based on modified hidden markov model from multi-view image sequences. Firstly, the structure of the human skeleton model is illustrated, which is extended from skeleton root and spine root, and this skeleton consists of right leg, left leg and spine. Secondly, our proposed human motion capturing system is made up of data training module and human motion capturing module. In the data training module, multi-views motion information is extracted from a human motion database, and feature database of human motion capturing is constructed through combining multi-views motions. In the human motion capturing module, results of motion capturing can be achieved through motion classification based on a modified hidden markov model. Thirdly, the modified hidden markov model is designed by utilizing the fuzzy measure, fuzzy integer, and fuzzy intersection operator through a scaling process. Finally, a standard motion capture dataset- MPI08_Database is utilized to make performance evaluation. Compared with the existing methods, the proposed approach can effectively capture human motions with high precision
Predicting dementia in Parkinson disease by combining neurophysiologic and cognitive markers

Objective: To assess the ability of neurophysiologic markers in conjunction with cognitive assessment to improve prediction of progression to dementia in Parkinson disease (PD). Methods: Baseline cognitive assessments and magnetoencephalographic recordings from 63 prospectively included PD patients without dementia were analyzed in relation to PD-related dementia (PDD) conversion over a 7-year period. We computed Cox proportional hazard models to assess the risk of converting to dementia conveyed by cognitive and neurophysiologic markers in individual as well as combined risk factor analyses. Results: Nineteen patients (30.2%) developed dementia. Baseline cognitive performance and neurophysiologic markers each individually predicted conversion to PDD. Of the cognitive test battery, performance on a posterior (pattern recognition memory score < median; hazard ratio (HR) 6.80; p = 0.001) and a fronto-executive (spatial span score < median; HR 4.41; p = 0.006) task most strongly predicted dementia conversion. Of the neurophysiologic markers, beta power < median was the strongest PDD predictor (HR 5.21; p = 0.004), followed by peak frequency < median (HR 3.97; p = 0.016) and theta power > median (HR 2.82; p = 0.037). In combination, baseline cognitive performance and neurophysiologic measures had even stronger predictive value, with the combination of impaired fronto-executive task performance and low beta power being associated with the highest dementia risk (both risk factors vs none: HR 27.3; p < 0.001). Conclusions: Combining neurophysiologic markers with cognitive assessment can substantially improve dementia risk profiling in PD, providing potential benefits for clinical care as well as for the future development of therapeutic strategies.
Honeybee flight metabolic rate: does it depend upon air temperature?

SUMMARY Differing conclusions have been reached as to how or whether varying heat production has a thermoregulatory function in flying honeybees Apis mellifera. We investigated the effects of air temperature on flight metabolic rate, water loss, wingbeat frequency, body segment temperatures and behavior of honeybees flying in transparent containment outdoors. For periods of voluntary, uninterrupted, self-sustaining flight, metabolic rate was independent of air temperature between 19 and 37°C. Thorax temperatures (Tth) were very stable, with a slope of thorax temperature on air temperature of 0.18. Evaporative heat loss increased from 51 mW g-1 at 25°C to 158 mW g-1 at 37°C and appeared to account for head and abdomen temperature excess falling sharply over the same air temperature range. As air temperature increased from 19 to 37°C, wingbeat frequency showed a slight but significant increase, and metabolic expenditure per wingbeat showed a corresponding slight but significant decrease. Bees spent an average of 52% of the measurement period in flight, with 19 of 78 bees sustaining uninterrupted voluntary flight for periods of> 1 min. The fraction of time spent flying declined as air temperature increased. As the fraction of time spent flying decreased, the slope of metabolic rate on air temperature became more steeply negative, and was significant for bees flying less than 80% of the time. In a separate experiment, there was a significant inverse relationship of metabolic rate and air temperature for bees requiring frequent or constant agitation to remain airborne, but no dependence for bees that flew with little or no agitation; bees were less likely to require agitation during outdoor than indoor measurements. A recent hypothesis explaining differences between studies in the slope of flight metabolic rate on air temperature in terms of differences in metabolic capacity and thorax temperature is supported for honeybees in voluntary flight, but not under agitation.
Prepared for Difference? Exploring Child Protection Practice with Aboriginal and Torres Strait Islander Families in Rural Australia

In Australia, over-representation of Aboriginal and Torres Strait Islander children in child protection systems is increasing. The legacy of the stolen generation has led to grief, sadness and loss of identity for many people, and major disparities in health, education, employment and housing means that Aboriginal and Torres Strait Islander families are more susceptible to child welfare interventions in the present and future. This makes it imperative that responses for these families are more effective, in order to achieve socially just outcomes. As well, Australia’s growing multicultural society has increased demand for services provided to people from diverse cultural backgrounds to recognise the impact and importance of culture and to respond effectively. Cultural competency, which focuses on developing knowledge, skills and values for cross cultural practice, has gained momentum. It aims to enhance the ability of workers to provide culturally relevant and effective responses to people from different cultural backgrounds. However, ensuring that practices in the human services are culturally appropriate, culturally safe, salient, and effective, has proved elusive.
How to design space efficient revocable IBE from non-monotonic ABE

Since there always exists a possibility that some users' private keys are stolen or expired in practice, it is important for identity based encryption (IBE) system to provide a solution to revocation. The current most efficient revocable IBE system has a private key of size O(log ns) and update information of size O(r log(n/r)) where r is the number of revoked users. In this paper, we present a new revocable IBE system in which the private key only contains two group elements and the update information size is O(r). We show that the proposed constructions for the revocation mechanism are more efficient in terms of space cost and provide a generic methodology to transform a non-monotonic attribute based encryption into a revocable IBE. We also demonstrate how the proposed method can be employed to develop an efficient hierarchical revocable IBE system.
Validating An Online Adaptive System Using Support Vector Machines

In this paper, we propose a novelty detection method based on Support Vector Machines as a candidate approach for validating online adaptive systems. As a oneclass classifier, the support vector data description is able to form a decision boundary around the learned data domain with very little or no knowledge of data points outside the boundary (outliers). Preliminary studies on an actual online adaptive system show that the support vector data description can be adopted as an effective tool for finding indications of the safe region for the learned domain, whereby we are able to separate faulty behavior from normal events.
On Rayleigh-Ritz Method in Three-Parameter Eigenvalue Problems

paper deals with the computation of the eigenvalues of a three-parameter Sturm-Liouville problem in the form of ordinary differential equation using Rayleigh-Ritz Method, a method which is based on the principle of variational methods. This method has been effective in computing the eigenvalues of self-adjoint problems. The resulting equations obtained in applying Rayleigh-Ritz method on the problem are solved to find the rough estimates of the eigenvalues of the problem. Rough estimates are used as starting approximations in the corresponding shooting method to obtain their actual values. Keywordseigenfunction, multiparameter, variational method, Rayleigh-Ritz method. In this paper a brief account of the method used is given. The starting values of the eigenvalues are obtained by solving the algebraic equations obtained on application of Rayleigh-Ritz method. Using these starting values in the corresponding shooting method of the problem, actual values are obtained. The shooting method requires good starting values because the convergence and its rapidity both depend on starting values. Shooting method of (10) is extended to treat the problem (1.1)-(1.2) numerically in the present case.
Buy4Me: A Delivery System via Mobility Prediction Based on Mobile Crowd Sensing

With the prevalent development of rich sensor-equipped smart phones, mobile crowd sensing becomes a new sensing paradigm beyond traditional sensor networks. In this paper we propose and develop Buy4Me, a delivery system based on mobile crowd sensing. It can be used in different scales, such as a university campus or a city, to make shopping and delivering more convenient. When you need something not near, Buy4Me can recommend a friend to bring it for you without extra work. Users' mobility histories are analyzed to predict where a user will visit, and whether she will encounter with the others. Then Buy4Me ranks friends by the probability of whether they completing the delivering task, and returns top-k friends. We evaluate the method with the dataset contributed by Microsoft Research Asia, and find that it can achieve acceptable recommendation accuracy.
ROLE OF COMPLEMENT IN INDUCTION OF ANTIBODY PRODUCTION IN VIVO

In an in vivo study in mice, suppression by the C3-cleaving protein of cobra venom (CoF), and other C3-reactive agents (zymosan, aggregated IgG, anti-C3 antibodies, and type III pneumococcal polysaccharide) of the thymus-dependent antibody responses to sheep erythrocytes, ovalbumin, and human IgG was demonstrated. The thymus-independent antibody response to polyvinyl-pyrrolidone was however unaffected by CoF. These and other published observations suggest that there may be a requirement for functional C3 in induction of thymus-dependent but not thymus-independent antibody production. A model for the role of C3 in lymphocyte cooperation is proposed based on these data analyzed in the light of existing knowledge of this process. It is postulated that fixed C3 interacting with macrophage See PDF for Structure and B-cell C3 receptors might enhance or facilitate T-dependent presentation of antigen to B cells.