Miracle-dz/UniFAR-FTUs huggingface dataset:
View-invariant human action recognition via robust locally adaptive multi-view learning

Human action recognition is currently one of the most active research areas in computer vision. It has been widely used in many applications, such as intelligent surveillance, perceptual interface, and content-based video retrieval. However, some extrinsic factors are barriers for the development of action recognition; e.g., human actions may be observed from arbitrary camera viewpoints in realistic scene. Thus, view-invariant analysis becomes important for action recognition algorithms, and a number of researchers have paid much attention to this issue. In this paper, we present a multi-view learning approach to recognize human actions from different views. As most existing multi-view learning algorithms often suffer from the problem of lacking data adaptiveness in the nearest neighborhood graph construction procedure, a robust locally adaptive multi-view learning algorithm based on learning multiple local L1-graphs is proposed. Moreover, an efficient iterative optimization method is proposed to solve the proposed objective function. Experiments on three public view-invariant action recognition datasets, i.e., ViHASi, IXMAS, and WVU, demonstrate data adaptiveness, effectiveness, and efficiency of our algorithm. More importantly, when the feature dimension is correctly selected (i.e., >60), the proposed algorithm stably outperforms state-of-the-art counterparts and obtains about 6% improvement in recognition accuracy on the three datasets.
Learning to Block Undesired Comments in the Blogosphere

A significant amount of the available information on web sites come from the interaction with users, such as news sites and blogs, where readers can post comments and sometimes develop habits of frequenting them. Some blogs specialize in certain subjects, receive the users credibility and become references in the field. However, the ease of inserting content through text comments makes room for unwanted messages, which affect the user experience, reduce the quality of the information provided by the websites and indirectly causing personal and economic losses. Given this scenario, this paper presents a comprehensive analysis of machine learning techniques applied to automatically detect undesired comments posted on blogs. Experiments carried out with a real and public database indicate that support vector machines and logistic regression, trained with both attributes extracted from the text messages and metadata from the posts, are promising in the task of filtering unwanted comments.
Simulation of coherent multiple imaging by means of pupil-plane filtering in optical microlithography

A resolution enhancement technique for optical microlithography based on coherent multiple imaging was investigated with use of Prolith/2 (a commercial lithographic simulation tool). It was shown that a Fabry–Perot etalon placed between the mask and the projection lens of an optical stepper could be interpreted as an appropriate transmission-phase pupil-plane filter. While previous calculations were able to evaluate simple patterns (such as an on-axis contact hole), this new approach also allows the simulation of complex mask patterns. Evaluation of the point-spread function of the optical systems by means of coherent multiple imaging showed that an optimized filter is capable of increasing the resolution by 28% and the depth of focus by 150%.
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National (or regional) seismic hazard maps, determined from probabilistic seismic hazard analysis, quantify the expected intensity of shaking in a region(s) over the course of one or more desired time interval(s). Building codes use these maps to define the lateral force levels for the design of new and the retrofit of existing structures. In the past, the maps depicted the shaking intensity measure of peak ground acceleration (PGA). In recent times, they have switched to depicting short period (0.2 s) and long period (1.0 s) spectral accelerations as these values may be directly used to fully define the code design response spectrum. Two hazard levels are typically of interest to the engineering community, the shaking intensity with a 10% probability of being exceeded in 50 years and the shaking intensity with a 2% probability of being exceeded in 50 years. These two levels of shaking define the Design Basis Earthquake (DBE, an earthquake with a recurrence interval of 475 years) and the Maximum Considered Earthquake (MCE, an earthquake with a recurrence interval of 2475 years) spectra. Typically, the codes’ design intent is to avoid loss of life under the DBE and collapse under the MCE.
A study on nomophobia and its correlation with sleeping difficulty and anxiety among medical students in a medical college, Telangana

Background: Social media and digital communication have become a part of life. Many things were made easy through online connectivity. The mobile phones not only connects people at anytime, anywhere and with anybody, but also movable and portable. Mobile phones when used extensively may cause a number of physical and psychological problems. Nomophobia (NO-MObile phone-PHOBIA) is one of the psychological problems related to exclusive use of mobile phone. It is the fear/anxiety of being away from mobile phone contact. The objectives are to study grading of nomophobia and to find out any correlation exits between nomophobia and sleeping difficulty and anxiety among medical students.Methods: A cross sectional study is conducted for duration of 6 months among medical students using semi-structured questionnaire. Nomophobia questionnaire (NMP-Q) is used to assess nomophobia, Athens insomnia scale is used to assess sleeping difficulty and general anxiety disorder- 7 Item scale is used to assess general anxiety.Results: The study showed that out of 364 students, 62 (17%) have mild, 234 (64.3%) have moderate and 68 (18.7%) have severe nomophobia. There is a weak positive correlation between nomophobia and sleeping difficult and anxiety.Conclusions: There problem of nomophobia is alarming; there is a need to reduce nomophobia, and to evolve effective strategies to enhance human interaction.
DRAFT Bayesian Nonparametric Modeling for Causal Inference

Researchers have long struggled to identify causal effects in non-experimental settings. Many recently-proposed strategies assume ignorability of the treatment assignment mechanism and require fitting two models – one for the assignment mechanism and one for the response surface. We propose a strategy that instead focuses on very flexibly modeling just the response surface using a Bayesian nonparametric modeling procedure, Bayesian Additive Regression Trees (BART). BART has several advantages: it is far simpler to use than many recent competitors, requires less guess-work in model fitting, handles a large number of predictors, yields coherent uncertainty intervals, fluidly handles continuous treatment variables and missing data for the outcome variable. BART produces more efficient estimates in the non-linear situations tested in our simulations compared to propensity score matching, propensity-weighted estimators, and regression adjustment. Further, it is highly competitive in linear settings with the “correct” model, linear regression. Correspondence should be addressed to the first author at Columbia University, School of International and Public Affairs, 420 West 118th St., 1425 IAB, New York NY 10027
Possible Near-II? Channels for Remote Sensing Precipitable Water Vapor from Geostationat-y Satellite Platforms

Remote wssing of tropospheric water vapor profiles from current geostaticmary writher satellites are made using a few broadband infrared (IR) channels in the 6-13-pn~ region. Uncerminties greater than 21N0 exist in derived water vapor values just above the surface from the IR emission measurements. [n this paper, we propose three near-[R channels. one within the O.94-jMr1 water vapor band absorption region. and the other two in nearby atmospheric windows. for remote sensing of precipitable Water Vapor over land areas. excluding lakes and rivers, during daytime from future geoslationary satellite platforms. The physical principles are as follows. The reflectance of most surface targets vanes approximately linearly with wavelength near I pm. The solar radiation on the sun-surface-smsor ray path is attenuated by atmospheric water vapor. The ratio of the radiance from the absorption channel with the radiances from the two window channels removes the surface reflectance etTec[s and yields approximately the mean atmospheric water vapor w~nsmiltance or the absorption channel. The integrated waler vapa amount from ground to space can be obtained with a precision of kttter than 5% from the mean transmittance. Because surface retlec[ances vary slowly with time. Lempcml variation ofprecipitable wa[er vapor c~n be determined reliably. tiigh SPJLK II resoluti cm. prcc! pl table water “,opor images are derived t’rom spectral dtita collected by [he A(rhorne Visible-lnl’rared lrnag! ng Sp+xlrometcr. wh)ch memures solar radiation retlected by the surface In the 1)4-2 . 5-pn] rcgmn In 10-nn] channels and h~s a ground lns[~ntaneous tield ol’view of N m from Its platform on ~n ER-2 aircraft at 20 km. 1 he proposed neitr-l R rctlecmnce technique would complement the [R emission tcchrslques for remote sensing of wa[er vofmr prolilcs from geosta[io nary wtclll[e platforms, especmlly In the boundary layer where mosl of the water vapor IS Ioca[ed.
Pseudo-Codewords in LDPC Convolutional Codes

Iterative message-passing decoders for low-density parity-check (LDPC) block codes are known to be subject to decoding failures due to so-called pseudo-codewords. These failures can cause the large signal-to-noise ratio performance of message-passing decoding to be worse than that predicted by the maximum-likelihood decoding union bound. In this paper we study the pseudo-codeword problem for the class of LDPC convolutional codes decoded continuously using an iterative, sliding window, message-passing decoder. In particular, for an LDPC convolutional code derived by unwrapping a quasi-cyclic LDPC block code, we show that the free pseudo-weight of the convolutional code is at least as large as the minimum pseudo-weight of the underlying quasi-cyclic code. This result parallels the well-known relationship between the free Hamming distance of convolutional codes and the minimum Hamming distance of their quasi-cyclic counterparts. Finally, simulation results are included that show improved performance for unwrapped LDPC convolutional codes compared to their underlying quasi-cyclic codes
An FPGA Implementation of a Competitive Hopfield Neural Network for Use in Histogram Equalization

This paper presents a field programmable gate array (FPGA) implementation for a competitive Hopfield neural network (CHNN) to be used in image histogram equalization (HE). This algorithm is so computationally expensive that a viable hardware implementation is appealing provided that an efficient algorithm-to-architecture mapping can be achieved. The Xilinx Virtex-E was used for the hardware realization. An efficient use of the chip is outlined in the results.
Micro- and Nanoengineering Approaches to Control Stem Cell-Biomaterial Interactions

As our population ages, there is a greater need for a suitable supply of engineered tissues to address a range of debilitating ailments. Stem cell based therapies are envisioned to meet this emerging need. Despite significant progress in controlling stem cell differentiation, it is still difficult to engineer human tissue constructs for transplantation. Recent advances in micro- and nanofabrication techniques have enabled the design of more biomimetic biomaterials that may be used to direct the fate of stem cells. These biomaterials could have a significant impact on the next generation of stem cell based therapies. Here, we highlight the recent progress made by micro- and nanoengineering techniques in the biomaterials field in the context of directing stem cell differentiation. Particular attention is given to the effect of surface topography, chemistry, mechanics and micro- and nanopatterns on the differentiation of embryonic, mesenchymal and neural stem cells.
Meliper : Making News Personal

Getting fresh and relevant news about our interest topics is a fundamental matter in today’s fast-paced information era. But there is a lack of personal solutions that treat each user individually. While following technology news via popular websites, we are presented vast number of articles about any technology related area. But if we are interested in just certain aspects of technology, we still have to browse through all the articles and try to find the ones that we are actually interested among many that are irrelevant. Meliper [2] gives users control about what news they want to receive, and the users can filter the information based on their interest. So users dont have to deal with irrelevant news. The system also learns from user behavior and adjusts retrieval and ranking accordingly.
Stacked Deck: Go-Shops and Auction Theory

During the recent wave of private equity buyouts, boards of directors of selling companies have been increasingly turning toward go-shop provisions as a way of fulfilling their Revlon duty to maximize shareholder value. This paper uses auction theory to determine whether or not go-shop provisions generate additional bidders, and therefore a higher expected revenue, for the selling company. Section I summarizes the important aspects of auction theory as it relates to corporate takeovers. Section II provides a background of go-shop provisions, discussing what kind of transactions go-shops are being used in and summarizes how a typical go-shop provision works. Section III summarizes the impact on expected revenue, based on auction theory developed in Section I and the observations in Section II, of go-shop provisions and concludes that go-shops are not effective at inducing financial bidders to bid for a company during the go-shop period. Section IV offers a set of recommendations to make go-shops more effective at inducing additional bidders and recommends some actions that selling boards can take to improve go-shops.
Physically based image synthesis of materials : a methodology towards the visual comparison of physical vs. virtual samples

The assessment of images of complex materials on an absolute scale is difficult for a human observer. Comparing physical and virtual samples side-by-side simplifies the task by introducing a reference. The goal of this article is to study the influence of image exposure on the perception of realism on images of paint materials containing sparkling metallic flakes. We use a radiometrically calibrated DSLR camera to acquire high resolution raw photographs of our physical samples which provide us with radiometric information from the samples. This is combined with the data obtained from the calibration of a stereoscopic display and shutter glasses to transform the raw photographs into images that can be shown by the display, controlling the colorimetric output signal. This ensures that we can transform our data back and forth between a radiometric and a colorimetric representation, minimizing the loss of information throughout the chain of acquisition and visualization. In this article we propose a paired comparison scenario that improves the results from our previous work, focusing on three main aspects: stereoscopy, exposure time, and dynamic range. Our results show that observers consider stereoscopy as the most important factor of the three for judging the similarity of these images to the reference, followed by exposure time and dynamic range, which supports our claims from previous research.
Kinetic Monte Carlo simulations of 1 D and 2 D traffic flows : Comparison of two lookahead rules

We employ an efficient list-based kinetic Monte Carlo (KMC) method to study traffic flow models on one-dimensional (1D) and two-dimensional (2D) lattices based on the exclusion principle and Arrhenius microscopic dynamics. This model implements stochastic rules for cars’ movement based on the configuration of the traffic ahead of each car. In particular, we compare two different lookahead rules: one is based on the distance from the car under consideration to the car in front of it, the other one is based on the density of cars ahead. The 1D numerical results of these two rules suggest different coarse-grained macroscopic limits in the form of integro-differential Burgers equations. The 2D results of both rules exhibit a sharp phase transition from freely flowing to fully jammed, as a function of initial density of cars. However, the look-ahead rule based on the density of the traffic produces more realistic results. The KMC simulations reported in this paper are compared with those from other well-known traffic flow models and the corresponding empirical results from real traffic.
Where We Used to Live: Validating Retrospective Measures of Childhood Neighborhood Context for Life Course Epidemiologic Studies

Early life exposures influence numerous social determinants of health, as distal causes or confounders of later health outcomes. Although a growing literature is documenting how early life socioeconomic position affects later life health, few epidemiologic studies have tested measures for operationalizing early life neighborhood context, or examined their effects on later life health. In the Life-course Influences on Fetal Environments (LIFE) Study, a retrospective cohort study among Black women in Southfield, Michigan (71% response rate), we tested the validity and reliability of retrospectively-reported survey-based subjective measures of early life neighborhood context(N=693). We compared 3 subjective childhood neighborhood measures (disorder, informal social control, victimization), with 3 objective childhood neighborhood measures derived from 4 decades of historical census tract data 1970-2000, linked through geocoded residential histories (tract % poverty, tract % black, tract deprivation score derived from principal components analysis), as well as with 2 subjective neighborhood measures in adulthood. Our results documented that internal consistency reliability was high for the subjective childhood neighborhood scales (Cronbach’s α =0.89, 0.93). Comparison of subjective with objective childhood neighborhood measures found moderate associations in hypothesized directions. Associations with objective variables were strongest for neighborhood disorder (rhos=.40), as opposed to with social control or victimization. Associations between subjective neighborhood context in childhood versus adulthood were moderate and stronger for residentially-stable populations. We lastly formally tested for, but found little evidence of, recall bias of the retrospective subjective reports of childhood context. These results provide evidence that retrospective reports of subjective neighborhood context may be a cost-effective, valid, and reliable method to operationalize early life context for health studies.
Methods for analysis of skewed data distributions in psychiatric clinical studies: working with many zero values.

OBJECTIVE Psychiatric clinical studies, including those in drug abuse research, often provide data that are challenging to analyze and use for hypothesis testing because they are heavily skewed and marked by an abundance of zero values. The authors consider methods of analyzing data with those characteristics. METHOD The possible meaning of zero values and the statistical methods that are appropriate for analyzing data with many zero values in both cross-sectional and longitudinal designs are reviewed. The authors illustrate the application of these alternative methods using sample data collected with the Addiction Severity Index. RESULTS Data that include many zeros, if the zero value is considered the lowest value on a scale that measures severity, may be analyzed with several methods other than standard parametric tests. If zero values are considered an indication of a case without a problem, for which a measure of severity is not meaningful, analyses should include separate statistical models for the zero values and for the nonzero values. Tests linking the separate models are available. CONCLUSIONS Standard methods, such as t tests and analyses of variance, may be poor choices for data that have unique features. The use of proper statistical methods leads to more meaningful study results and conclusions.
The context of unintended pregnancy among married women in the USA

Background and methodology Unintended pregnancy is a concern in the USA due to its association with adverse physical, mental, social and economic outcomes. Few studies have examined this issue among married women from a social and contextual perspective. This study targeted married women to examine factors associated with unintended pregnancy using the ecological model of health promotion that focuses attention on both individual and social environmental factors. Data from the National Survey of Family Growth (NSFG) were merged with NSFG contextual files to examine the major predictive factors. Results Multilevel logistic regression modelling revealed that married women of lower socioeconomic status, higher parity, who lived in communities with a high rate of marital dissolution had a higher probability of an unintended pregnancy. Women reported that their husbands were likely to concur with the unintended designation of the pregnancy. Discussion and conclusions This study utilised a unique perspective to examine contextual factors related to unintended pregnancy among married women. The results support the need to focus on the couple as a unit for prevention efforts. Social policies to enhance access to family planning services are necessary to improve outcomes and prevent unintended pregnancies.
The Politics of Public Policy Decisions in Local Government in Uganda

ix CHAPTER ONE: INTRODUCTION . 1 1.1. Research Background . 1 1.2. Structure of the Thesis . 8 CHAPTER TWO: CONCEPTUAL AND THEORETICAL FRAMEWORK . 12 2.1. Local Government, Decentralisation and the making of Public Policy Decisions 12 2.2. Decentralisation: The African Experience . 19 2.2.1. Local Government and Decentralisation in Uganda . 21 2.3. Actor-centered Institutionalism. 23 2.3.1. Institutions in Actor-centered Institutionalism . 24 2.3.2. ACI perspective of Actors. 26 2.3. 3. Actor Constellations and modes of interaction . 27 CHAPTER THREE: METHODOLOGY . 34 3.0. The Research Approach . 34 3.1. Research design . 35 3.2. Sampling . 37 3.2.1. Data collection techniques . 41 3.2.2. Data Analysis . 44 3.2.3. Ethical Considerations, Technical Aspects and Challenges . 44
Porous Interfaces for Small Screen Multitasking using Finger Identification

The lack of dedicated multitasking interface features in smartphones has resulted in users attempting a sequential form of multitasking via frequent app switching. In addition to the obvious temporal cost, it requires physical and cognitive effort which increases multifold as the back and forth switching becomes more frequent. We propose porous interfaces, a paradigm that combines the concept of translucent windows with finger identification to support efficient multitasking on small screens. Porous interfaces enable partially transparent app windows overlaid on top of each other, each of them being accessible simultaneously using a different finger as input. We design porous interfaces to include a broad range of multitasking interactions with and between windows, while ensuring fidelity with the existing smartphone interactions. We develop an end-to-end smartphone interface that demonstrates porous interfaces. In a qualitative study, participants found porous interfaces intuitive, easy, and useful for frequent multitasking scenarios.