Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Image Stitching Method for Heterogeneous Car Videos Based on Bounding Boxes of Features

Heterogeneous car video recorders can capture scene information with different modalities including viewing angles, resolutions, and lens sensors. Traditional methods cannot accurately perform image stitching on the images captured by heterogeneous cameras. This paper presents an efficient method to stitch heterogeneous images by allowing a driver to view an ultra-wide angle without blind spots. It extracts bounding boxes of brake lights and license plate numbers as feature points to be matched. A homography matrix is computed to stitch the heterogeneous video images. Experimental results show that our proposed method can stitch images accurately and efficiently, which is superior to the existing methods.
An Improved Three-Stage Classifier for Activity Recognition

Recently, Human Activity Recognition (HAR) has become an important research area because of its wide range of applications in several domains such as health care, elder care, sports monitoring systems, etc. The use of wearable sensors — specifically the use of inertial sensors such as accelerometers and gyroscopes — has become the most common approach to recognize physical activities because of their unobtrusiveness and ubiquity. Overall, the process of building a HAR system starts with a feature extraction phase and then a classification model is trained. In the work of Siirtola et al. is proposed an intermediate clustering step to find the homogeneous groups of activities. For the recognition step, an instance is assigned to one of the groups and the final classification is performed inside that group. In this work we evaluate the clustering-based approach for activity classification proposed by Siirtola with two additional improvements: automatic selection of the number of groups and an instance reassi.
Motion and Structure from Motion in a piecewise Planar Environment

We show in this article that when the environment is piecewise linear, it provides a powerful constraint on the kind of matches that exist between two images of the scene when the camera motion is unknown. For points and lines located in the same plane, the correspondence between the two cameras is a collineation. We show that the unknowns (the camera motion and the plane equation) can be recovered, in general, from an estimate of the matrix of this collineation. The two-fold ambiguity that remains can be removed by looking at a second plane, by taking a third view of the same plane, or by using a priori knowledge about the geometry of the plane being looked at. We then show how to combine the estimation of the matrix of collineation and the obtaining of point and line matches between the two images, by a strategy of Hypothesis Prediction and Testing guided by a Kalman filter. We finally show how our approach can be used to calibrate a system of cameras.
Impact of a mentoring program on psychosocial wellbeing of youth in Rwanda: Results of a quasi-experimental study

Addressing the psychosocial needs of vulnerable children and youth is viewed increasingly as a priority of humanitarian programs, particularly in Africa, where the scale of the problem necessitates community-based solutions. This quasi-experimental study tested a model of adult mentorship and support to improve psychosocial outcomes among youth-headed households in a rural area of Rwanda. Two rounds of data were collected from youth who served as heads of their households. Following the baseline survey in 2004 (n = 692), an adult mentorship program was implemented among half the sample. A follow-up survey was conducted after 18 months of intervention exposure (n = 593). Through regular home visits, mentors developed a stable, caring relationship with youth in their community living without an adult caregiver. Each mentor was assigned 2–3 youth-headed households located within their own community to visit at least once a month for 2–3 hours in the home. Over an 18-month period, 156 trained adult mentors (60% male, 40% female) visited and supported 441 households. Multivariable analyses explored linkages between exposure to the intervention and four key psychosocial outcomes: perceptions of adult support, marginalization, grief and symptoms of depression. Over time, youth with a mentor reported a significant increase in perceptions of available adult support and decreases in marginalization. While grief in the comparison group grew significantly over time, grief levels in the intervention group remained stable, suggesting that the mentorship program may have mitigated grief among youth in the intervention areas. Intervention respondents also reported a slight, but significant, decrease in depressive symptoms. Findings suggest that the mentoring program enhanced available support and community connectedness among youth in this study. However, program impact on emotional wellbeing was more modest. More intensive interventions may be needed to reduce grief symptoms and for those with high levels of depressive symptoms.
Images, Objects, and Surfaces in Zn

An exact analytical approach to n-dimensional discrete images, objects, and surfaces is given. Objects are defined as finite grid point sets of Zn. Using the 2n-neighborhood of Zn, components are maximal connected sets of object points. Formulas are given for count measures of object (points, edges, faces, cells, marginal elements, etc.), and the Euler number ψ(n). Such measures are defined in Z3 with respect to volume, surface content, and the mean curvature integral in E3. The generalization for Zn allows the definition of similarities between n-dimensional objects. The Euler number and other object characteristics can be expressed only by numbers of marginal elements of single object surfaces. Finally, a general formula for ψ(3) is given.
An Efficient Algorithm for Foley-Sammon Optimal Set of Discriminant Vectors by Algebraic Method

This paper presents a new method for computing the discriminant vectors of the Foley–Sammon optimal set. First, an equivalent criterion is presented to replace the Fisher criterion; then, the problem of computing the discriminant vectors in Rn is transformed into the maximum problem in a subspace. Several theorems relating to the method are also presented. Experimental results show that the present method is superior to the positive pseudoinverse method, and the perturbation method in terms of correct classification rate.
Use of Reporting Guidelines in Scientific Writing: PRISMA, CONSORT, STROBE, STARD and Other Resources

Abstract In this special article we describe a number of reporting guidelines endorsed by the CONSORT (Consolidated Standards of Reporting Trials) group for a range of research designs that commonly appear in scientific journals: systematic reviews, clinical trials with and without randomisation, observational studies, n-of-1 (or single-case experimental design) trials, and diagnostic studies. We also consider reporting guidelines for studies using qualitative methodology. In addition to reporting guidelines, we present method quality rating scales, which aim to measure risk of bias that threatens the internal validity of a study. Advantages of reporting guidelines and method quality rating scales for authors include the provision of a structure by which to improve the clarity and transparency of report writing; for reviewers and readers advantages include a method by which to critically appraise an article. Brain Impairment endorses these reporting guidelines and applies them within the review process for submissions to the journal.
Recent Results in Hierarchical Clustering. I - The Reducible Neighborhoods Clustering Algorithm

The clustering of large data sets is of great interest in fields such as pattern recognition, numerical taxonomy, image or speech processing. The traditional Ascendant Hierarchical Algorithm (AHC) cannot be run for sets of more than a few thousand elements. The reducible neighborhoods clustering algorithm, which is presented in this paper, has overtaken the limits of the traditional hierarchical clustering algorithm by generating an exact hierarchy on a large data set. The theoretical justification of this algorithm is the so-called Bruynooghe reducibility principle, that lays down the condition under which the exact hierarchy may be constructed locally, by carrying out aggregations in restricted regions of the representation space. As for the Day and Edelsbrunner algorithm, the maximum theoretical time complexity of the reducible neighborhoods clustering algorithm is O(n2log n), regardless of the chosen clustering strategy. But the reducible neighborhoods clustering algorithm uses the original data table and its practical performances are by far better than Day and Edelsbrunner’s algorithm, thus allowing the hierarchical clustering of large data sets, i.e. composed of more than 10 000 objects.
A Connectionist Approach to Speech Recognition

The task discussed in this paper is that of learning to map input sequences to output sequences. In particular, problems of phoneme recognition in continuous speech are considered, but most of the discussed techniques could be applied to other tasks, such as the recognition of sequences of handwritten characters. The systems considered in this paper are based on connectionist models, or artificial neural networks, sometimes combined with statistical techniques for recognition of sequences of patterns, stressing the integration of prior knowledge and learning. Different architectures for sequence and speech recognition are reviewed, including recurrent networks as well as hybrid systems involving hidden Markov models.
A critical juncture for synthetic biology

EMBO Reports (2018) e46153 The development of new technologies and their applications often have to navigate regulatory limitations and public attitudes, expectations or resistance—the trajectories of genetically modified crops in the Europe or the success of in vitro fertilization after initial resistance demonstrate how public attitudes and regulation can determine if a technology succeeds or fails. Academic scientists and companies working on new technologies increasingly must consider these factors and mitigate real and perceived risks of the technology so as to avoid overreaching regulation and public resistance that could threaten innovation. In this context, social science takes an important role by gauging public attitudes about if and how the emergence of new technologies stokes fears and raises hopes. This article illustrates how the natural sciences and social sciences interacted in the emerging fields of synthetic biology and nanotechnology, specifically the timing and rise of social science research and commentary on the potential impact and risks of these emerging technologies. > Generally, it is expected that physical sciences research would grow earlier and faster than the social sciences owing to the responsive and reflexive nature of social science inquiry. In the case of nanotechnology, the private sector was afforded two decades of growth without commensurate academic discourse from social scientists, while in the case of synthetic biology, both physical and social science have been intertwined from the very beginning. Ignorance of social science discourse could hinder research on synthetic biology and commercial opportunities [1]. Given the broad benefits this technology may offer, it is important for industry to proactively engage with the general public and regulatory community to foster transparent and responsible dialogue regarding the field's best …
Robust Medical Test Evaluation Using Flexible Bayesian Semiparametric Regression Models

The application of Bayesian methods is increasing in modern epidemiology. Although parametric Bayesian analysis has penetrated the population health sciences, flexible nonparametric Bayesian methods have received less attention. A goal in nonparametric Bayesian analysis is to estimate unknown functions (e.g., density or distribution functions) rather than scalar parameters (e.g., means or proportions). For instance, ROC curves are obtained from the distribution functions corresponding to continuous biomarker data taken from healthy and diseased populations. Standard parametric approaches to Bayesian analysis involve distributions with a small number of parameters, where the prior specification is relatively straight forward. In the nonparametric Bayesian case, the prior is placed on an infinite dimensional space of all distributions, which requires special methods. A popular approach to nonparametric Bayesian analysis that involves Polya tree prior distributions is described. We provide example code to illustrate how models that contain Polya tree priors can be fit using SAS software. The methods are used to evaluate the covariate-specific accuracy of the biomarker, soluble epidermal growth factor receptor, for discerning lung cancer cases from controls using a flexible ROC regression modeling framework. The application highlights the usefulness of flexible models over a standard parametric method for estimating ROC curves.
Space-Time Block Coding Iterative Multiuser Receiver

We present a multiuser receiver for CDMA systems with the combination of turbo channel coding and space–time block coding. A turbo scheme based on multiuser detection, soft interference cancellation and decoding is provided, and the algorithms for space–time decoding and separately interference suppressing are derived in this paper. The multiuser detection consists of multiuser interference suppression and single-user space–time decoding. Then we develop the iterative multiuser receiver based on the soft estimates of the interfering users' symbols. Moreover, simulation is given to verify the effectiveness of the multiuser receiver.
Asymmetric TDP-43 distribution in primary progressive aphasia with progranulin mutation

Objective: Primary progressive aphasia (PPA) results from an asymmetric degeneration of the language dominant (usually left) hemisphere and can be associated with the pathology of Alzheimer disease (AD) or frontotemporal lobar degeneration (FTLD). This study aimed to investigate whether the anatomic distribution of TDP-43 inclusions displayed a corresponding leftward asymmetry in a patient with PPA with a mutation in the progranulin gene and FTLD pathology. Methods: Brain tissue from a 65-year-old patient with PPA and progranulin mutation was analyzed using immunohistochemical methods for TDP-43. Analysis was performed in the superior temporal gyrus, inferior temporal gyrus, inferior parietal lobule, orbitofrontal cortex, entorhinal cortex, and dentate gyrus. Neuronal intranuclear inclusions, neuronal cytoplasmic inclusions, and dystrophic neurites were quantified using modified stereologic analysis. Analysis of variance was used to determine significant effects. Results: All 3 types of inclusions predominated on the left side of analyzed cortical regions. They were also more frequent in language areas than in memory-related areas. Conclusion: These results demonstrate a phenotypically concordant distribution of abnormal TDP-43 inclusions in primary progressive aphasia (PPA). This contrasts with PPA cases with Alzheimer pathology where no consistent leftward asymmetry of neurofibrillary degeneration or amyloid deposition has been demonstrated despite the leftward asymmetry of the atrophy, and where neurofibrillary tangles show a greater density in memory than language areas despite the predominantly aphasic phenotype. This case suggests that the TDP-43 inclusions in PPA–frontotemporal lobar degeneration are more tightly linked to neuronal death and dysfunction than neurofibrillary and amyloid deposits in PPA–Alzheimer disease.
Online Survey Tools: Ethical and Methodological Concerns of Human Research Ethics Committees

A survey of 750 university human Research Ethics Boards (HRECs) in the United States revealed that Internet research protocols involving online or Web surveys are the type most often reviewed (94% of respondents), indicating the growing prevalence of this methodology for academic research. Respondents indicated that the electronic and online nature of these survey data challenges traditional research ethics principles such as consent, risk, privacy, anonymity, confidentiality, and autonomy, and adds new methodological complexities surrounding data storage, security, sampling, and survey design. Interesting discrepancies surfaced among respondents regarding strengths and weaknesses within extant guidelines, which are highlighted throughout the paper. The paper concludes with considerations and suggestions towards consistent protocol review of online surveys to ensure appropriate human subjects protections in the face of emergent electronic tools and methodologies.
Healthcare expenditures and patient satisfaction: cost and quality from the consumer's perspective in the US*

ABSTRACT Background: Both cost and quality of healthcare are major concerns in the United States. Using patient satisfaction as a quality indicator, we seek to identify the relationship between healthcare cost and quality from the perspective of the community-dwelling population in the United States. Methods: We examined a nationally representative sample of 13 980 adults (age ≥ 18 years) in the 2003 Medical Expenditure Panel Survey (MEPS). Given the idiosyncrasies of the cost data distribution, a recently developed extended estimating equation (EEE) model was employed to identify the relationship between patient satisfaction and healthcare expenditure, after controlling for individual demographic covariates, co-morbidity profile, and functional and activity limitations. A series of sensitivity analyses were conducted, in addition, to verify the identified relationship. All statistics were adjusted using the proper sampling weight from the MEPS data. Results: Average annual healthcare expenditures for 2003 ranged between $3923 and $6073 when grouped by patient satisfaction ratings with a mean value $4779 for all individuals who rated perceived satisfaction of their healthcare. We found that there is no statistically significant relationship between patient satisfaction and total healthcare expenditure ( p = 0.60) and a non-monotonic relationship is not identified either. All sensitivity analyses results revealed a lack of relationship between patient satisfaction and healthcare expenditures. Limitations: Patient satisfaction might not reflect the quality of healthcare from an objective clinical standpoint. The identified cost–satisfaction relationship may not be extrapolated to other quality indicators. Due to the cross-sectional study design, no causal relationship could be inferred between patient satisfaction and healthcare expenditure. Conclusions: Our study adds to the literature on healthcare cost and quality by suggesting that the improvement of patient satisfaction may not require additional healthcare spending.
The Role of Numeracy in Informed Consent for Surveys

If empirical estimates of disclosure risk are included in informed consent statements for surveys or other forms of research, participants must be able to understand the information provided. Using data from an online vignette-based experiment, this article explores the role that numeracy or quantitative literacy may play in comprehension of disclosure risk. Results suggest that less numerate persons are less sensitive to extreme differences in the disclosure risk described in the hypothetical vignettes.
Ethnographic Research with Adolescent Students: Situated Fieldwork Ethics and Ethical Principles Governing Human Research

This paper explores ethical dilemmas in situated fieldwork ethics concerning ethnographic studies of adolescent students. While consequentialist and deontological ethics form the basis of the ethical stances shared by ethnographers and research ethics committees, the interpretation of those principles may diverge in school-based ethnography with adolescent students because of the particular role of the adult ethnographer vis-à-vis developmentally immature adolescents not held legally responsible for many of their actions. School ethnographers attempt to build trust with adolescent participants in order to learn about their hidden cultural worlds, which may involve activities that are very harmful to the youths involved. They face many difficult and sometimes unexpected choices, including whether to intervene and how to represent events and adolescents in published findings. Scenarios with examples drawn from research conducted in public high schools are used to illustrate and explicate dilemmas in formal research and latent insider/outsider roles and relations involving harmful adolescent behaviors, advocacy, and psychological trauma. Also examined are analytical procedures used to construct interpretations leading to representations of research participants in the resulting publication.
Measuring How People View Biomedical Research: Reliability and Validity Analysis of the Research Attitudes Questionnaire

With increasing numbers of studies on research ethics and a need to improve the recruitment of research subjects, the ability to measure attitudes toward biomedical research has become important. The Research Attitudes Questionnaire is a significant predictor of the public's attitudes toward and willingness to participate in research, yet limited data are available on its psychometric properties. This study establishes the scale's internal consistency and dimensionality using a large Internet-based sample from the United States. One item was removed due to a poor item-total correlation, and three additional items were removed which formed a reverse-wording measurement artifact factor. With improved internal consistency and dimensionality, the seven-item version has the advantages of shorter administration time and improved psychometric properties.
A Split L2 Data Cache for Scalable Cc-numa Multiprocessors

In scalable CC-NUMA multiprocessors, it is crucial to reduce the average memory access time. For applications where the second-level (L2) cache is large enough, we propose a split L2 cache to utilize the surplus space. The split L2 cache is composed of a traditional LRU cache and an RVC (Remote Victim Cache) which only stores the data of remote memory address range. Thus, it reduces the average L2 cache miss time by keeping remote blocks that would be discarded otherwise. Though the split cache does not reduce the miss rates, it is observed to reduce the total execution time effectively by up to 27%. It even outperform an LRU cache of double size.
A BICMOS 120 MW 11 GHZ transimpedance amplifier Dedicated for High-Speed Photoreceivers

We present a new low-noise, low-power SiGe transimpedance amplifier (TIA) by combining an automatic DC photo-current cancellation, an on-chip DC offset compensation circuit and a single-ended to differential conversion scheme. The conversion method is based of the replica biasing technique in order to provide balanced output signals to the subsequent stages. The chip was fabricated in a 0.18 μm SiGe BiCMOS technology. Experimental results show excellent performances such as 11 GHz bandwidth, 75-dBΩ transimpedance, -19.2 dBm sensitivity measured at 10 Gb/s at a Bit Error Rate (BER) of 10-12, input referred noise, and 9.5 ps peak-to-peak jitter which are the best overall performances reported in its category. The photoreceiver chip is expected to dissipate only 120 mW from a single 3.3 V power supply.