Miracle-dz/UniFAR-FTUs huggingface dataset:
Standards for Evaluating the Fairness of Photograph Lineups

In theory a lineup is fair, from the perspective of the suspect, to the extent that the suspect is not distinctive in appearance from the other lineup members (foils) and all of the foils are reasonably similar in general appearance to the suspect. Lineup fairness can be divided into two dimensions-size and bias. Several proposed methods for empirically evaluating lineup fairness were assessed in terms of their sensitivity to absolute standards of lineup fairness and their discriminability, the extent that they differentiated between lineups designed to be fair and those constructed via less rigorous selection procedures. One of three lineup size measures and both measures of lineup bias showed significant discriminability. The sensitivity of the measures depended on the criteria arbitrarily chosen or, when using statistical significance, on sample size. Race of mock witness had some impact on evaluations of Black lineups but not on evaluations of White lineups. Results indicated that a sample size of 18 .
Visualization of Isosurfaces with Parametric Cubes

To render images from volume datasets, an interpolation method also called reconstruction is needed. The level of details of the resultant image closely depends on the filter used for reconstruction. We propose here a new filter producing C1 continue surfaces. The provided image quality is better than current high‐quality algorithms, like splatting or trilinear raycasting, where tiny details are often eliminated. In contrast with other studied high quality filters that are practically unusable, our algorithm has been implemented interactively on a modest platform thanks to an efficient implementation using parametric cubes. We also demonstrate the interest of a min‐max octree in the visualization of isosurfaces interactively thresholded.
Robust Pitch Estimation Using l1-regularized Maximum Likelihood Estimation

This paper presents a new method of robust pitch estimation using sparsity-based estimation techniques. The method is developed based on sparse representation of a temporal-spectral pitch feature. The robust pitch feature is obtained by accumulating spectral peaks over consecutive frames. It is expressed as a sparse linear combination of an over-complete set of peak spectrum exemplars. The probability distribution of the noise is assumed to be Gaussian with non-zero mean. The weights of the linear combination are estimated by maximizing the likelihood of the feature under sparsity constraint. The sparsity constraint is incorporated as an l 1 regularization term. From the estimated weights, the major constituent exemplars are identiﬁed and the fundamental frequency is determined. Experimental results show that, with this method, pitch estimation accuracy is signiﬁcantly improved, particularly at low signal-to-noise ratios.
The effect of leadership attributes and motivation to lead on preferred job characteristics (job attributes): case study of undergraduates in Malaysian universities

The objective of this study was to examine the relationship between the leadership attributes and motivation to lead (MTL) of undergraduates in Malaysia with their inclination to choose specific types of job characteristics or job attributes. Many researches has proven that personality is positively related to preferred job characteristics, but no research to the researchers’ knowledge has been done on leadership attributes and motivation to lead with selected job characteristics. Data were collected from 711 undergraduates from Malaysian public universities. The results showed that leader attributes contributes a stronger predictive effect than the motivation or keenness to lead in determining the selection of specific job characteristics. This finding supports the research hypothesis that undergraduates who have been exposed to leadership training and development have gained greater emotional and cognitive maturity that enable them to be more open to a broader range of job characteristic types. No significant difference was observed between males and females, nor between Science and Humanity programs of study in the students’ selection of specific job characteristics. Findings, implications and directionsfor research are discussed.
A Collaborative Framework for In-network Video Caching in Mobile Networks

Due to explosive growth of online video content in mobile wireless networks, in-network caching is becoming increasingly important to improve the end-user experience and reduce the Internet access cost for mobile network operators. However, caching is a difficult problem due to the very large number of online videos and video requests, limited capacity of caching nodes, and limited bandwidth of in-network links. Existing solutions that rely on static configurations and average request arrival rates are insufficient to handle dynamic request patterns effectively. In this paper, we propose a dynamic collaborative video caching framework to be deployed in mobile networks. We decompose the caching problem into a content placement subproblem and a source-selection subproblem. We then develop SRS (System capacity Reservation Strategy) to solve the content placement subproblem, and LinkShare, an adaptive traffic-aware algorithm to solve the source selection subproblem. Our framework supports congestion avoidance and allows merging multiple requests for the same video into one request. We carry extensive simulations to validate the proposed schemes. Simulation results show that our SRS algorithm achieves performance within 1 − 3% of the optimal values and LinkShare significantly outperforms existing solutions.
Betraying the Intellectual Tradition: Public Intellectuals and the Crisis of Youth

Building upon the late Pierre Bourdieu's belief that intellectuals had a major responsibility in bridging intellectual work and the operation of politics, this paper argues that intellectuals, especially those in higher education, need to recognise that youth is an important moral referent and political starting point for addressing a number of issues related to a wide ranging number of political problems, including environmental and class concerns to matters of race, gender, and disability. Youth invokes compassion and understanding, which are crucial to shaping the civic imagination. The emphasis on young people's experience is important because it foregrounds the relationship between power and the lived realities shaped by material relations of power. More specifically, young people provide a more crucial lens through which hegemony can be analysed, compassion mobilised, and politics engaged beyond local interests and national boundaries. Educators need a new language in which young people are not detached from politics but become central to any transformative notion of pedagogy conceived in terms of social and public responsibility.
Embedded EEG localization error using separately lobe for electrodes configuration

The study of the EEG inverse problem consists in active brain's source reconstruction. In this paper we review the localization error from this reconstruction using a new configuration of electrodes on the scalp. The suggested new configuration consists on studying each lobe separately. The objective is to minimize the localization error with a minimum number of electrodes. To validate this study, we use the Shrinking sLORETA-FOCUSS method as a solution of the inverse problem. The obtained results show very interesting values using a minimum number of electrodes placed on the scalp surface. In this paper we will embed the proposed approach on an FPGA platform using adaptation techniques. Due to different electrodes we used the dynamic partial reconfiguration technic. The different electrodes data are treated by IPs based on VHDL accelerators. The proposed architecture will be embedded on Xilinx Virtex 5 ML 507 platform.
Cross-Document Narrative Frame Alignment

Automated cross-document comparison of narrative facilitates co-reference and event similarity identification in the retellings of stories from different perspectives. With attention to these outcomes, we introduce a method for the unsupervised generation and comparison of graph representations of narrative texts. Composed of the entity-entity relations that appear in the events of a narrative, these graphs are represented by adjacency matrices populated with text extracted using various natural language processing tools. Graph similarity analysis techniques are then used to measure the similarity of events and the similarity of character function between stories. Designed as an automated process, our first application of this method is against a test corpus of 10 variations of the Aarne-Thompson type 333 story, "Little Red Riding Hood. " Preliminary experiments correctly co-referenced differently named entities from story variations and indicated the relative similarity of events in different iterations of the tale despite their order differences. Though promising, this work in progress also indicated some incorrect correlations between dissimilar entities.
A systematic review of evidence for the psychometric properties of the Strengths and Difficulties Questionnaire

This article synthesized evidence for the validity and reliability of the Strengths and Difficulties Questionnaire in children aged 3–5 years. A systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement guidelines was carried out. Study quality was rated using the Consensus-based Standards for the Selection of Health Measurement Instruments. In total, 41 studies were included (56 manuscripts). Two studies examined content and cultural validity, revealing issues with some questions. Six studies discussed language validations with changes to some wording recommended. There was good evidence for discriminative validity (Area Under the Curve ≥ 0.80), convergent validity (weighted average correlation coefficients ≥ 0.50, except for the Prosocial scale), and the 5-factor structural validity. There was limited support for discriminant validity. Sensitivity was below 70% and specificity above 70% in most studies that examined this. Internal consistency of the total difficulty scale was good (weighted average Chronbach’s alpha parents’ and teachers’ version 0.79 and 0.82) but weaker for other subscales (weighted average parents’ and teachers’ range 0.49–0.69 and 0.69–0.83). Inter-rater reliability between parents was moderate (correlation coefficients range 0.42–0.64) and between teachers strong (range 0.59–0.81). Cross-informant consistency was weak to moderate (weighted average correlation coefficients range 0.25–0.45). Test-retest reliability was mostly inadequate. In conclusion, the lack of evidence for cultural validity, criterion validity and test-retest reliability should be addressed given wide-spread implementation of the tool in routine clinical practice. The moderate level of consistency between different informants indicate that an assessment of a pre-schooler should not rely on a single informant.
Deadlock avoidance in model predictive direct torque control

For medium voltage AC drives, model predictive direct torque control (MPDTC) shows excellent performance characteristics regarding the switching frequency and the harmonic distortion of the torque and the stator currents, outperforming classic control schemes, such as direct torque control and field oriented control. Besides these advantages, the MPDTC algorithm runs occasionally into so called deadlocks, in which no suitable voltage vector exists. Even though an exit strategy is available to resolve these situations, deadlocks tend to cause spikes in the instantaneous switching frequency and impact the overall performance of MPDTC. This paper focuses on new methods to avoid such deadlocks, using terminal constraints and terminal weights. The proposed methods greatly reduce-and in many cases completely avoid-deadlocks. Moreover, a significant reduction of the switching frequency and the harmonic distortion is observable in the case of a five-level topology.
Graph-based semi-supervised learning with manifold preprocessing for image classification

In real worlds applications, some former research papers have shown that manifold learning tries to discover the non-linear low-dimensional data manifold from a high-dimensional space. Many natural images and the face images are believed to be sampled from a manifold. In this paper, we try to investigate whether discovering such manifold can aid the semi-supervised learning algorithms. We propose a novel graph-based learning algorithm locality preserving graph-based semi-supervised method (LLGSM), which firstly use both labeled and unlabeled examples as unlabeled to discover the manifolds of the data samples and then use the projected labeled examples together with projected unlabeled ones to do classification. Experiments performed on some public image data sets have demonstrated the effectiveness of our algorithm.
Age differences in ethanol discrimination: acquisition and ethanol dose generalization curves following multiple training conditions in adolescent and adult rats.

BACKGROUND Adolescents and adults vary in sensitivity to many effects of ethanol (EtOH), although it is unknown whether they also differ in their perception of EtOH's subjective cues. This study characterized EtOH discrimination in adolescent and adult male rats using a rapidly acquired Pavlovian conditioned approach procedure. METHODS EtOH at 1 of the 3 training doses (0.75, 1.0, or 1.25 g/kg) served as either a positive (POS) or negative (NOS) occasion setter. Each 20-minute training session consisted of eight 15-second presentations of 2 cue lights located on either side of a dipper delivering chocolate Boost(®) . For POS-trained rats, the cue lights reliably predicted 5-second presentations of chocolate Boost during EtOH but not saline sessions, with the opposite contingencies used for NOS-trained rats. Anticipatory approach behavior (head entries into the reward delivery area) in the presence and absence of the cue lights was used to calculate discrimination scores on EtOH and saline sessions. Following acquisition, various doses of EtOH (0 to 1.5 g/kg) were administered to establish generalization curves. RESULTS Although animals of both ages responded differentially on EtOH and saline sessions by the end of acquisition, adults met criterion more quickly and had higher discrimination scores during reinforced sessions than adolescents. Whereas adolescents failed to demonstrate any dose-dependent responding during testing when trained with the 0.75 or 1.25 g/kg EtOH doses, adults demonstrated broader EtOH generalization during testing sessions following training with all 3 EtOH doses. Among adolescents trained with 1.0 g/kg EtOH, less generalization occurred relative to adults. CONCLUSIONS Adolescents were less sensitive to EtOH's interoceptive effects, indicating that EtOH is likely a more salient cue for adults than for adolescents. These findings contribute to evidence that suggests adolescent-typical insensitivity to internal cues that typically limit EtOH consumption may contribute to the elevated intake commonly reported during this developmental period.
Regional Brain Activation With Advertising Images

Preferences for purchasing goods and services may be shaped by many factors, including advertisements presenting logical, persuasive information or those using images or text that may modify behavior without requiring conscious recognition of a message. We tested the hypothesis that these two types of messages (logical persuasion [LP] vs. nonrational influence [NI]) might affect brain function differently in a pilot project, using stimuli drawn from real-world print advertisements and quantitative electroencephalography as a noninvasive measure of regional brain activity. Twentyfour healthy subjects, 11 women and 13 men, viewed images while brain electrical activity was recorded. We used the low-resolution brain electromagnetic tomography method to quantify current intensity in brain regions implicated in decision-making and emotional processing. Data were analyzed using a block design to compare brain activity during LP and NI stimuli periods. LP images were associated with consistently and significantly higher activity levels in orbitofrontal, anterior cingulate, amygdala, and hippocampus regions than were NI images. These findings suggest that advertising images can evoke different levels of regional brain activity related to the use of LP and NI elements.
A novel approach on Cuckoo search algorithm using Gamma distribution

Cuckoo search algorithm (CS) is one of the most efficient optimization techniques developed so far. Several attempts have been made in past in order to improve the efficiency of CSO algorithm. In this paper we have tried to exploit the fundamental step length distribution function of the CS algorithm in order to increase its efficiency. Cuckoo search is a metaheuristic optimization technique. In place of conventional Levy distribution, Gamma distribution has been used. We will represent the increased efficiency of the Gamma distribution aided CSO algorithm in the following paper.
Single-Channel Maximum-Likelihood T60 Estimation Exploiting Subband Information

This contribution presents four algorithms developed by the authors for single-channel fullband and subband T60 estimation within the ACE challenge. The blind estimation of the fullband reverberation time (RT) by maximum-likelihood (ML) estimation based on [15] is considered as baseline approach. An improvement of this algorithm is devised where an energy-weighted averaging of the upper subband RT estimates is performed using either a DCT or 1/3-octave filter-bank. The evaluation results show that this approach leads to a lower variance for the estimation error in comparison to the baseline approach at the price of an increased computational complexity. Moreover, a new algorithm to estimate the subband RT is devised, where the RT estimates for the lower octave subbands are extrapolated from the RT estimates of the upper subbands by means of a simple model for the frequency-dependency of the subband RT. The evaluation results of the ACE challenge reveal that this approach allows to estimate the subband RT with an estimation error which is in a similar range as for the presented fullband RT estimators.
Audience Segmentation and Age Stratification Among Television Writers

In this research, we analyze quantitative longitudinal data on the careers of 8,990 television and film writers to assess whether barriers to career success for older writers have increased in recent years. We detect a substantial shift in age-earnings profiles in favor of younger television writers during an era when programming strategies increasingly targeted younger audiences. We argue that marketing strategies in television that emphasize audience demographics and distinctive features of the business context encourage "typecasting" that creates barriers to career success for older writers.
Less lethal technology: medical issues

Purpose – Less lethal weapons have become a critical tool for law enforcement when confronting dangerous, combative individuals in the field. The purpose of this paper is to review the medical aspects and implications of three different types of less lethal weapons.Design/methodology/approach – The paper conducted a comprehensive medical literature review on blunt projectiles, irritant sprays including oleoresin capsicum (OC), and conducted energy devices such as the Taser™. It reviews the history, mechanisms of action, intended and other physiologic effects, and medical safety risks and precautions of these devices. In particular, the paper focuses on the issue of sudden in‐custody death and less lethal weapons, reviewing case reports, animal research and human investigative studies on this topic.Findings – In general, these three different types of less lethal weapons have been effective for their intended use. Each type of less lethal weapon has a number of physiologic effects and specific medical issu.
Vegetation—soil water interaction within a dynamical ecosystem model of grassland in semi-arid areas

A dynamical ecosystem model with three variables, living biomass, wilted biomass and available soil wetness, isdeveloped to examine the vegetation—soil water interaction in semi-arid areas. The governing equations are based onthe mass conservation law. The physical and biophysical processes are formulated with the parameters estimated fromobservational data. Both numerical results and qualitative analysis of the model as well as observational data indicate thatthe maintenance of a grassland requires a minimum precipitation (or equivalently, a minimum moisture index), and thegrassland and desert ecosystem can coexist when precipitation is within a range above this threshold. Sensitivity studiesshow that these numerical results are robust with respect to model parameters and the transformation functions. It isalso found that the wilted vegetation plays a very important role in shaping the transition between grassland and desert.By using the theories of an attractor basin and multiple equilibrium states, the conditions for grassland maintenance andthe strategy of grazing are also analysed.
Iterative reconstruction for CT perfusion with a prior-image induced hybrid nonlocal means regularization: Phantom studies.

PURPOSE In computed tomography perfusion (CTP) imaging, an initial phase CT acquired with a high-dose protocol can be used to improve the image quality of later phase CT acquired with a low-dose protocol. For dynamic regions, signals in the later low-dose CT may not be completely recovered if the initial CT heavily regularizes the iterative reconstruction process. The authors propose a hybrid nonlocal means (hNLM) regularization model for iterative reconstruction of low-dose CTP to overcome the limitation of the conventional prior-image induced penalty. METHODS The hybrid penalty was constructed by combining the NLM of the initial phase high-dose CT in the stationary region and later phase low-dose CT in the dynamic region. The stationary and dynamic regions were determined by the similarity between the initial high-dose scan and later low-dose scan. The similarity was defined as a Gaussian kernel-based distance between the patch-window of the same pixel in the two scans, and its measurement was then used to weigh the influence of the initial high-dose CT. For regions with high similarity (e.g., stationary region), initial high-dose CT played a dominant role for regularizing the solution. For regions with low similarity (e.g., dynamic region), the regularization relied on a low-dose scan itself. This new hNLM penalty was incorporated into the penalized weighted least-squares (PWLS) for CTP reconstruction. Digital and physical phantom studies were performed to evaluate the PWLS-hNLM algorithm. RESULTS Both phantom studies showed that the PWLS-hNLM algorithm is superior to the conventional prior-image induced penalty term without considering the signal changes within the dynamic region. In the dynamic region of the Catphan phantom, the reconstruction error measured by root mean square error was reduced by 42.9% in PWLS-hNLM reconstructed image. CONCLUSIONS The PWLS-hNLM algorithm can effectively use the initial high-dose CT to reconstruct low-dose CTP in the stationary region while reducing its influence in the dynamic region.