Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning real-time object detectors : probabilistic generative approaches

This dissertation is a computational investigation of the task of locating and recognizing objects in unconstrained images in real-time, and learning to do so with minimal supervision. We take a probabilistic generative modeling approach, which involves formulating analytical models of several real-world vision problems, studying how optimal inference would proceed under such models, developing techniques for learning parameters under these models, and evaluating the performance of the optimal inference algorithms in realistic data. We begin by developing a novel generative model of images under which an image is a collection of sets of pixels which are generated by different object categories. This provides a novel definition of "object" as a set of pixels that are co-dependent, but conditionally independent of the other sets of pixels in the image. We then develop an algorithm for optimal inference (i.e., detection of objects) and maximum likelihood learning when the segmentation of training images is known. We point out a computational tradeoff between robustness of object detection and precision of localization, and propose context dependent detectors as a way to solve the problem. These techniques are used to develop a state-of-the-art, real-time head, eye, and blink detector. We predict that similar context-dependent detectors may be found in the brain. We develop an algorithm for optimal inference and maximum likelihood learning when the segmentation of training images is unknown. We test this on image datasets labeled with the identity but not the location of objects, and achieve state-of-the-art performance in discovery of object categories. We then test the algorithm in a fully unsupervised context, in which a real-time person detector is learned from just a few minutes of visual information self-labeled through multi-modal contingency detection. This suggests that early face (and other) preferences in humans infants may be evidence for rapid statistical learning rather than innate biases. We develop software for learning robust, real-time object detectors from both labeled and unlabeled examples, including a real-time head, eye, and blink detector available to the public.
Transversals in Latin Squares

A latin square of order $n$ is an $n\times n$ array of $n$ symbols in which each symbol occurs exactly once in each row and column. A transversal of such a square is a set of $n$ entries such that no two entries share the same row, column or symbol. Transversals are closely related to the notions of complete mappings and orthomorphisms in (quasi)groups, and are fundamental to the concept of mutually orthogonal latin squares. Here we provide a brief survey of the literature on transversals. We cover (1) existence and enumeration results, (2) generalisations of transversals including partial transversals and plexes, (3) the special case when the latin square is a group table, (4) a connection with covering radii of sets of permutations. The survey includes a number of conjectures and open problems.
Gross Motor Performance by Children with Autism Spectrum Disorderand Typically Developing Children on TGMD-2

Objective: To examine the gross motor skill performance using the Test of Gross Motor Development-2 (TGMD- 2) on children with autism spectrum disorder (ASD) and their age matched peers (5-10 years). Methods: A total of 21 children with ASD (M=7.57 years) and 21 age matched typically developing children (M=7.38 years) participated in this study. TGMD-2 is a standardized test to assess 12 gross motor skills for children. All study participants completed the TGMD-2 assessments. A MANOVA was conducted on TGMD-2 scores to compare motor performance of children with ASD and typically developing children. Results: For the locomotor subtest, 67% children with ASD received poor standard scores and 40% of scores were very poor. About 60% children with ASD had poor standard scores and 33% of scores were very poor on object control skills as described in the TGMD-2 manual. For overall gross motor quotient scores, 81% children with ASD were below 79 and classified as poor and about 76% children scored below 70 and received very poor rating. A MANOVA analysis revealed significant performance difference between children with ASD and typically developing children (p<.01). The effect sizes (ES) describing motor delays of the study participants between the two groups were large (>.80). Conclusion and implication: For educators, therapists, and practitioners, it is important to note that children across the autism spectrum showed significant delays in gross motor skill performance when compared to their age matched peers. Locomotion and object control skills are fundamental motor skills in which children interact with their environment and other children. Developing a therapeutic intervention includes those gross motor skills may positively impact children with ASD’s movement competence.
Recurrent Online Clustering as a Spatio-Temporal Feature Extractor in DeSTIN

This paper presents a basic enhancement to the DeSTIN deep learning architecture by replacing the explicitly calculated transition tables that are used to capture temporal features with a simpler, more scalable mechanism. This mechanism uses feedback of state information to cluster over a space comprised of both the spatial input and the current state. The resulting architecture achieves state-of-the-art results on the MNIST classification benchmark.
Technology versus humanism: how patients perceive the use of electronic health records in physicians’ offices—a qualitative study

Abstract Electronic Health Records (EHRs) have the potential to improve the quality of care. In view of the accelerated adoption of EHRs, there is a need to understand conditions necessary for their effective use. Patients are the focus of healthcare and their perceptions and expectations need to be included in developing and implementing EHRs. The purpose of this study was to gather exploratory qualitative information from patients about their experiences and perceptions regarding the effects of EHRs on healthcare quality in physicians’ offices. We conducted five focus groups with patients representing a random mix of diverse socio-demographic backgrounds in Oklahoma. Related to EHRs, patients reported improvements on the technical side of care but no change on the human side. They expressed concerns about the potential for breach of confidentiality and security of medical records. They were also concerned about the possibility of governmental agencies or insurance companies having unauthorized access to patient records. Patients differentiated between the human and technical sides of care and reported no change or improvement in the doctor-patient interaction. Patients have an important perspective on the use of EHRs and their perceptions and experiences should be considered in the development, adoption and implementation of EHRs. Otherwise, the use of EHRs may not be fully effective. There is also a need to educate patients about the potential benefits and risks of EHRs and the steps being taken to mitigate such risks.
The Dynamics of Preference Elicitation after an Environmental Disaster: Stability and Emotional Load

Nonmarket valuation is commonly applied to infer the preferences of individuals for restoration policies after an environmental disaster. A crucial issue in this task is to determine the appropriate lapse of time after which the valuation techniques should be applied. This study investigates the role of the emotional load in explaining the dynamic patterns of elicited preferences. The results show that preferences tend to stabilize when the emotional load is also stable. The main implication is that attitudinal investigation of emotions could provide satisfactory information for determining the time frame for implementing more costly nonmarket valuation studies. (JEL Q51, Q54)
Privacy-Preserving Universal Authentication Protocol for Wireless Communications

Seamless roaming over wireless networks is highly desirable to mobile users, and security such as authentication of mobile users is challenging. In this paper, we propose a privacy-preserving universal authentication protocol, called Priauth, which provides strong user anonymity against both eavesdroppers and foreign servers, session key establishment, and achieves efficiency. Most importantly, Priauth provides an efficient approach to tackle the problem of user revocation while supporting strong user untraceability.
Cognitive screening in a population‐based sample of community‐living elderly: Effects of age and education on the construct of cognitive status

This study examined the measurement properties of a cognitive screening test, the Halifax Mental Status Scale (HMSS), in a population‐based sample of community‐living elderly subjects (N = 361) and a clinic sample (N = 20) of patients with Alzheimer's disease. Receiver operating characteristic analyses yielded estimates of sensitivity and specificity of approximately 90% for this test. Factor analysis confirmed a three‐factor solution for the HMSS. Although both age and education were correlated with the HMSS total score, their relationship to the factor scores differed. Our study shows that comprehensive cognitive status tests do not measure a unitary construct and that adjustment of summary scores for education is unlikely to optimize sensitivity and specificity. In population‐based studies, only those components of a test that reflect education should be adjusted.
Fat Cell–Specific Ablation of Rictor in Mice Impairs Insulin-Regulated Fat Cell and Whole-Body Glucose and Lipid Metabolism

OBJECTIVE Rictor is an essential component of mammalian target of rapamycin (mTOR) complex (mTORC) 2, a kinase that phosphorylates and activates Akt, an insulin signaling intermediary that regulates glucose and lipid metabolism in adipose tissue, skeletal muscle, and liver. To determine the physiological role of rictor/mTORC2 in insulin signaling and action in fat cells, we developed fat cell–specific rictor knockout (FRic−/−) mice. RESEARCH DESIGN AND METHODS Insulin signaling and glucose and lipid metabolism were studied in FRic−/− fat cells. In vivo glucose metabolism was evaluated by hyperinsulinemic-euglycemic clamp. RESULTS Loss of rictor in fat cells prevents insulin-stimulated phosphorylation of Akt at S473, which, in turn, impairs the phosphorylation of downstream targets such as FoxO3a at T32 and AS160 at T642. However, glycogen synthase kinase-3β phosphorylation at S9 is not affected. The signaling defects in FRic−/− fat cells lead to impaired insulin-stimulated GLUT4 translocation to the plasma membrane and decreased glucose transport. Furthermore, rictor-null fat cells are unable to suppress lipolysis in response to insulin, leading to elevated circulating free fatty acids and glycerol. These metabolic perturbations are likely to account for defects observed at the whole-body level of FRic−/− mice, including glucose intolerance, marked hyperinsulinemia, insulin resistance in skeletal muscle and liver, and hepatic steatosis. CONCLUSIONS Rictor/mTORC2 in fat cells plays an important role in whole-body energy homeostasis by mediating signaling necessary for the regulation of glucose and lipid metabolism in fat cells.
A Cost Sensitive Part-of-Speech Tagging: Differentiating Serious Errors from Minor Errors

All types of part-of-speech (POS) tagging errors have been equally treated by existing taggers. However, the errors are not equally important, since some errors affect the performance of subsequent natural language processing seriously while others do not. This paper aims to minimize these serious errors while retaining the overall performance of POS tagging. Two gradient loss functions are proposed to reflect the different types of errors. They are designed to assign a larger cost for serious errors and a smaller cost for minor errors. Through a series of experiments, it is shown that the classifier trained with the proposed loss functions not only reduces serious errors but also achieves slightly higher accuracy than ordinary classifiers.
ILP-based scheduling with time and resource constraints in high level synthesis

Presents a formal analysis of the constraints of the scheduling problem, and evaluates the structure of the scheduling polytope described by those constraints. Polyhedral theory and duality theory are used to demonstrate that efficient solutions of the scheduling problem can be expected from a carefully formulated integer linear program (ILP). Furthermore, the authors present an algorithm to lower bound the resource requirement of the time-constrained scheduling problem that enables them to solve the ILP more efficiently. <<ETX>>
Equalization of OFDM systems in time-varying channels using frequency domain redundancy

Time variations of doubly-selective channels lead to the loss of orthogonality among subcarriers, resulting in intercarrier interference (ICI) in orthogonal frequency division multiplexing (OFDM) systems. The one tap frequency equalizer is not applicable any more in this case. In this paper, we propose a frequency domain equalizer (FEQ) for OFDM systems in time varying channels using the existing redundancy in the frequency domain. We show that the equalizer matrix has a sparse structure, and thus a low computational complexity. Simulation results show that the proposed equalizer is capable of canceling ICI effectively with a low complexity.
THE INFLUENCE OF HYDROSTATIC PRESSURE ON THE GROWTH AND VIABILITY OF TERRESTRIAL AND MARINE BACTERIA

Although there is abundant evidence that a rich microflora exists at the bottom of the ocean, in deep oil well brines, and in other habitats characterized by high pressure (cf. ZoBell, 1946), no clear understanding has been reached concerning the influence of pressure on the growth, viability, and metabolism of the organisms in such environments. The results of older (Certes, 1884a,b,c; Regnard, 1884; Certes and Cochin, 1884; Roger, 1895; Krause, 1902; Chlopin and Tammann, 1903; Hite, Giddings, and Weakley, 1914; Larson, Hartzell, and Diehl, 1918), as well as more recent, studies (cf. reviews by Macheboeuf and Basset, 1934; Cattell, 1936; Bridgman, 1946) with respect to the effects of presure on microbial processes in general are not only inadequate but in some cases apparently inconsistent. Furthermore, before the advent of the theory of absolute reaction rates in 1935 (Eyring, 1935; Glasstone, Laidler, and Eyring, 1941) no rational basis was available for the interpretation of the action of pressure on chemical reaction rates, and it has been only within the past several years that this theory has been applied to biological reactions in living cells (cf. reviews by Johnson, 1947; Johnson and Eyring, 1948.) The latter studies have shown that, in all cases, the observed effects of pressure may be profoundly modified by temperature; a fundamental relationship that had previously remained almost unnoticed. In view of these circumstances, we have undertaken to reinvestigate the prob. lem, with special reference to the relation between temperature and the effects of hydrostatic pressure, as well as the relation of the natural habitat of the organism to the effects observed. The present report is in the nature of a survey of the influence of pressures up to 9,000 pounds per square inch (about 600 atmospheres), at different constant temperatures, on the growth and viability of representative species of both marine and terrestrial bacteria in pure culture, initially in the logarithmic growth phase. Extensive quantitative data are necessary for kinetic analyses of the pressure effects and will be made the subject of later investigations, as will, likewise, the significance of certain biological and other factors, such as the specific physiology of the organism, growth phase, composition of the medium, and so forth.
Using back-propagation neural networks for functional software testing

To create reliable, safe, and high quality software is the primary purpose of software testing. With the development of software engineering, functional software testing is one essential part of software testing. This paper explains that back-propagation neural networks can be used for functional software testing efficiently and significantly. In here we established a method which is sufficient to reveal the majority of software faults in functional testing. We explained how the method can be used to produce a set of test cases covering the most common functional existing in software automatically. Then we used the proposed methodology to test large-scale software systems. Based on the results, in the paper we paid more attention to more arithmetic and date mining methods for function software testing development.
Reconciling Human Smoking Behavior and Machine Smoking Patterns: Implications for Understanding Smoking Behavior and the Impact on Laboratory Studies

Background: Recent Food and Drug Administration legislation enables the mandating of product performance standards for cigarette smoke and the evaluation of manufacturers' health claims for modified tobacco products. Laboratory studies used for these evaluations and also for understanding tobacco smoke toxicology use machines to generate smoke. The goal of this review is to critically evaluate methods to assess human smoking behavior and replicate this in the laboratory. Methods: Smoking behavior and smoking machine studies were identified using PubMed and publicly available databases for internal tobacco company documents. Results: The smoking machine was developed to generate smoke to allow for comparing cigarette tar and nicotine yields. The intent was to infer relative human disease risk, but this concept was flawed because humans tailor their smoking to the product, and chemical yields and toxicologic effects change with different smoking profiles. Although smoking machines also allow for mechanistic assessments of smoking-related diseases, the interpretations also are limited. However, available methods to assess how humans puff could be used to provide better laboratory assessments, but these need to be validated. Separately, the contribution of smoke mouth-holding and inhalation to dose need to be assessed, because these parts of smoking are not captured by the smoking machine. Better comparisons of cigarettes might be done by tailoring human puff profiles to the product based on human studies and comparing results across regimens. Conclusions: There are major research gaps that limit the use of smoking machine studies for informing tobacco control regulation and mechanistic studies. (Cancer Epidemiol Biomarkers Prev 2009;18(12):3305–20)
PRACTICAL VALUE OF UNDERSTANDING THE MINDSET OF SECONDARY SCHOOL TEACHERS AND STUDENTS IN ENGLISH LANGUAGE CLASSROOM

Understanding the mind set of students and teachers seeks much more importance in the present scenario. The present study is intended to find the type of mindset of secondary school students in learning English language on the select areas and also made an attempt to find out the effect of fixed mindset of students on the attitude of students towards English language. Understanding the mind set of secondary school English teachers regarding the performance and attitude of students in learning English language on select areas revealed the result that most of the teachers are having fixed mind set and there is an urgent necessity to change the situation. A sample of 100 secondary school students and 20 secondary school English teachers were selected randomly from the state of Kerala. Majority of students are having fixed mindset in select areas and they believe that it is talent which is worthwhile and their effort won’t do anything in learning English language. A shift in this situation is the need of the hour. For that the teachers should change their mindset and motivate the learners to assure themselves that their intelligence is not static.
The influence of social connectedness and monitoring on adolescent sexual activity in Ghana

This paper examines the connectedness of unmarried adolescents to parents, friends and key social institutions. The focus is on the role these groups play with respect to information, communication and monitoring about sexual and reproductive health as well as the association of parental monitoring and communication with sexual activity and condom use. We draw on 2004 nationally-representative survey data from 12-19 year olds and qualitative evidence from focus group discussions and in-depth interviews with adolescents in 2003. The qualitative data show clear gender differences in communication: daughters get messages about avoiding pregnancy while sons are told only to “be careful. ” While fathers tend to be autocratic, mothers are considered to be sympathetic but not very helpful with information about sexual issues. Other adults, such as grandparents, are viewed as being very helpful about sex-related matters. Multivariate analyses of the survey data show a negative relationship between parental monitoring and recent sexual activity for both males and females and that the higher the level of monitoring, the lower the likelihood of recent sexual activity. Parental communication with adolescents about sex-related matters was not associated with sexual activity for males but had a positive association for female adolescents. Once adolescents are already sexually-active, parental monitoring and communication have little bearing on the use of condoms (one of the most common methods used by adolescents).
Homophily of Network Ties and Bonding and Bridging Social Capital in Computer-Mediated Distributed Teams

This research studied homophily of network ties in distributed teams in both task-related instrumental networks and non-task related expressive networks. Homophily of network ties was examined in terms of demographic and social characteristics, including gender, race, geographic location, and group assignment. Social network data were collected from 32 students enrolled in a distance learning class from two universities. MQAP regression analysis showed that homophily in gender and in race had no significant impact on the development of either instrumental or expressive ties. In instrumental networks, both homophily in group assignment and in location had significant impact on the development of network ties. In expressive networks, homophily in location had significant impact on the development of network ties, but the impact of homophily in group membership was only marginally significant. Further analysis of bonding ties with people of the same group and bridging ties with people from different groups showed that bonding social capital can exert significant influence on performance.
Peer-to-Peer contents delivery system considering network distance

Network traffic on the Internet has been increasing in recent years. Some reports by government institutions indicate that Peer-to-Peer (P2P) traffic consumes 30% of network bandwidth on the Internet. In most current P2P file-sharing software, computers, which are called "peer" get files not only from computers that are nearby on the network but also from those that are far away. This is because the computers do not consider the relative location of other computers on the Internet. We regard Round Trip Time (RTT) or Time To Live (TTL) as the network distance and design a new P2P content delivery system. In this system, to decrease waste, peers on the P2P file-sharing network prioritize nearby peers when obtaining files. Peers search for other peers that have desired files using clusters, based on network distance and trend of contents which a peer has. Peers search for popular files from other peers in distance-based clusters and search for less popular files from peers in trend-based clusters. Simulation results indicate our system facilitates a reduction in traffic in the whole network.