Miracle-dz/UniFAR-FTUs huggingface dataset:
Part decomposition and description of 3D shapes

Addresses the problem of obtaining natural descriptions of 3D shapes. The authors present one of the first attempts to address the description of 3D compound objects, where the parts are connected smoothly. The input the authors consider is either complete 3D data or range data from a single view. The authors suggest a volumetric graph representation of the object, where the nodes represent individual parts and the edges represent connectivity information. The authors suggest the use of properties of the parabolic curves for performing the part decomposition. The authors consider parts with tubular structure with a straight or curved axis. They are also interested in the internal description of the parts. The authors study two classes of shapes, namely straight homogeneous GCs, and planar right constant GCs. The authors suggest the use of properties of the parabolic curves for recovering natural descriptions of these classes in terms of their cross sections and axes.
Running involvement and life satisfaction: The role of personality

ABSTRACT Accumulating evidence suggests that physically active leisure represents an important correlate of life satisfaction; however, the role that personality has on leisure involvement and life satisfaction remains ambiguous. This study explored whether the big-five personality traits explain running involvement and life satisfaction. Participants (N = 742) were recruited from a distance-running event held in the United States. The results revealed that conscientiousness had positive indirect effects on life satisfaction through attraction, centrality, and self-expression. Openness to experience also had positive indirect effects on life satisfaction through attraction and self-expression. These findings indicate that greater life satisfaction occurs for individuals with high conscientiousness and openness to experience through the enjoyment derived from running and the expression of identity through running.
A Summary Sentence Decomposition Algorithm for Summarizing Strategies Identification

Expert summarizers employ a number of strategies to produce summaries. Teachers need to identify which strategies are used by students to help them improve their summary writing. However, the task is time consuming. This paper reports on our effort to develop an algorithm to identify the summarizing strategies employed by students using summary sentence decomposition. The summarizing strategies used by experts are identified and translated into a set of heuristic rules. A summary sentence decomposition algorithm is then developed based on the heuristic rules. A preliminary test was carried out and the results are discussed.
The Campaign Value of Incumbency: A New Solution to the Puzzle of Less Effective Incumbent Spending

A puzzle in research on campaign spending is that while expenditure is positively related to votes won, this effect is far more strongly, or even exclusively, enjoyed by challengers rather than by incumbents. We unearth a new explanation for the puzzle, focusing on the hidden, yet variable, campaign value of office perquisites which incumbents deploy in their campaigns to win votes. When these variable office benefits are unobserved, then the effect is to make observed incumbent spending less effective than spending by challengers. Using data from the 2002 Irish general election, where incumbency was assigned a variable campaign value and included in declared campaign spending, we are able to demonstrate this hidden incumbency effect and estimate its relationship to electoral success, in terms of overall votes, share of votes, and probability of winning a seat. Contrary to previous research showing ineffective incumbent spending, we find that when the campaign value of office is also measured, public office value “spending” is not only very effective in winning votes, but also seems to be more effective than regular incumbent spending.
Genome-wide analysis of p53 transcriptional programs in B cells upon exposure to genotoxic stress in vivo

The tumor suppressor p53 is a transcription factor that coordinates the cellular response to DNA damage. Here we provide an integrated analysis of p53 genomic occupancy and p53-dependent gene regulation in the splenic B and non-B cell compartments of mice exposed to whole-body ionizing radiation, providing insight into general principles of p53 activity in vivo. In unstressed conditions, p53 bound few genomic targets; induction of p53 by ionizing radiation increased the number of p53 bound sites, leading to highly overlapping profiles in the different cell types. Comparison of these profiles with chromatin features in unstressed B cells revealed that, upon activation, p53 localized at active promoters, distal enhancers, and a smaller set of unmarked distal regions. At promoters, recognition of the canonical p53 motif as well as binding strength were associated with p53-dependent transcriptional activation, but not repression, indicating that the latter was most likely indirect. p53-activated targets constituted the core of a cell type-independent response, superimposed onto a cell type-specific program. Core response genes included most of the known p53-regulated genes, as well as many new ones. Our data represent a unique characterization of the p53-regulated response to ionizing radiation in vivo.
Spotting Fake Retweeting Activity in Twitter

Given the retweeting activity around the posts of several Twitter users, how can we spot organic users’ reactions from fake retweets that aim to boost a post’s appearance of popularity? Our main intuition is that organic behavior has more variability, while fraudulent behavior is more synchronized. We refer to the detection of such fraudulent activities as the Retweet Fraud problem and propose: (A) a set of carefully designed features for characterizing retweet threads, i.e. a given post’s retweets, (B) an efficient method for spotting fraudsters. We present experiments on a real dataset of almost 12 million retweets crawled from Twitter, where our method achieves a 97% accuracy.
An Investigation into the Experiences of Homeschooled Individuals with Autism that Led to Success in the On-Campus College Environment: A Case Study

3 Copyright Page.4 Dedication . 5 Acknowledgments.6 List of Tables . 13 List of Figures . 14 List of Abbreviations . 15 CHAPTER ONE: INTRODUCTION . 16 Overview . 16 Background . 16 Situation to Self.17 Problem Statement . 19 Purpose Statement . 21 Significance of the Study . 22 Research Questions . 24 Central Research Question . 24 Sub-Questions . 25 Research Plan . 27 Delimitations and Limitations . 28 Definitions.30 Summary . 31 CHAPTER TWO: LITERATURE REVIEW . 33
What Are the Outcomes and Views of People With Mobility Limitations After Participating in a Community Circuit Group

Increasing services are addressing the needs of people living with long term conditions. The purpose of this observational study was to determine the impact of community circuit classes on balance and mobility of individuals with neurological conditions. Participants were recruited from people interested in or already taking part in circuit classes provided at a private rehabilitation clinic. Outcomes (4-Stage Balance test, 30 Second Chair Stand test and Timed Up and Go (TUG) were assessed before and after a block of circuit classes (at least six weekly sessions). Risk and fear of falling were measured using the Falls Risk Assessment Tool and the Falls Efficacy Scale respectively. Participants completed a self-report questionnaire to provide their views about the class. All 13 participants completed at least six classes. A difference was found in the TUG (p=0.05) but not in other outcome measures. All participants highly rated the organisation, level of staff skill and amount of assistance provided at the classes, but there was less satisfaction on the challenge and frequency of classes. Participating in circuit classes for a short-term period appears to have a positive impact on mobility and is an enjoyable form of exercise for people with neurological conditions. Stavric, V. , Mudge, S. , Robinson, L. , Mewa, M. What are the outcomes and views of people with mobility limitations after participating in a community circuit group? New Zealand Journal of Physiotherapy 45(3): 119-125. doi: 10.15619/ NZJP/45.3. 03
Acimn protocol: A protocol for anonymous communication in multi hop wireless networks

Summary form only given. Anonymity is the state of not being identifiable within a set of subjects. Different strategies exist for assuring anonymity in computer networks, such as the dining cryptographers network and mix networks. But these strategies were designed for wired networks requiring direct communication links or fixed infrastructure. Therefore they are not applicable to multi hop wireless networks without modification. The Acimn protocol bases on the combination of these two main strategies enabling nodes to communicate anonymously among each other. Every node of the network acts as a mix so that the Mix approach can be used to hide the multi hop communication. By using this technique only one message overhead per communication path is generated because of the key establishment among the nodes on the path. During following communications only little computational power is needed by every node on the path to decrypt the messages before forwarding them to the next node. Additionally every one hop communication is kept anonymously by using the DC-net protocol. Therefor the nodes are arranged in groups of at most three members that are in communication range of each other. Sending of messages takes place in rounds where in every round only one group member is able to transmit information but every member has to send data. Because of the maximal group size of three there can be maximally three times more messages compared to the sending without the DC-net approach. By utilizing the combination of both techniques neither non participating eavesdropper nor nodes on the communication path are able to track the communication partners while the overhead is kept small.
Constraints on the asymptotic baryon fractions of galaxy clusters at large radii

While X-ray measurements have so far revealed an increase in the volume-averaged baryon fractions fb(r) of galaxy clusters with cluster radii r, fb(r) should asymptotically reach a universal value fb(∞)=fb, provided that clusters are representative of the Universe. In the framework of hydrostatic equilibrium for intracluster gas, we have derived the necessary conditions for fb(∞)=fb. The X-ray surface brightness profile described by the β model and the temperature profile approximated by the polytropic model should satisfy γ≈2(1−1/3β) and γ≈1+1/3β for β 1, respectively, which sets a stringent limit to the polytropic index: γ 2/3 breaks down at rather large radii (≳30rc) where hydrostatic equilibrium has probably become inapplicable. We further explore how to obtain the asymptotic value fb(∞) of the baryon fraction from the X-ray measurement made primarily over the finite central region of a cluster. We demonstrate our method using a sample of 19 strong lensing clusters, which enables us to place a useful constraint on fb(∞): 0.094±0.035≤fb(∞)≤0.41±0.18, corresponding to a cosmological density parameter 0.122±0.069≤ΩM≤0.53±0.28 for H0=50 km s−1 Mpc−1. An optimal estimate of fb(∞) based on three cooling flow clusters with β<1/2 in our lensing cluster sample yields 〈fb(∞)〉=0.142±0.007 or ΩM=0.35±0.09.
A machine-learning approach to discovering company home pages

For many marketing and business applications, it is necessary to know the home page of a company specified only by its company name. If we require the home page for a small number of big companies, this task is readily accomplished via use of Internet search engines or access to domain registration lists. However, if the entities of interest are small companies, these approaches can lead to mismatches, particularly if a specified company lacks a home page. We address this problem using a supervised machine-learning approach in which we train a binary classification model. We classify potential website matches for each company name based on a set of explanatory features extracted from the content on each candidate website. Our approach is related to web-based business intelligence in two ways: (1) we build the training set for our learning algorithms through crowdsourcing tools and illustrate their potential for business research, and (2) the success of our model allows one to easily use corporate home pages as data inputs into other research projects. Through the successful use of crowdsourcing, our approach is able to identify a correct home page or recognize that a valid home page does not exist with an accuracy that is 57% better than simply taking the highest ranked search engine result as the correct match.
Turbo-TCM and transmit antenna diversity in multipath fading channels with CSI PSAM

We consider turbo-trellis-coded transmission over fading MIMO channels with transmit diversity using space-time bloc codes. We consider the concatenation of turbo-TCM with a space-time block code and show that. in addition to the transmit diversity, substantial benefits can be obtained by turbo iteration. In addition an improved CSI PSAM (pilot Symbol-Assisted Modulation Technique) scheme is proposed to obtain an iterative channel state estimate procedure.
Integrating Simple yet Robust Protocol Layers for Wireless Ad Hoc Intervehicle Communications

We present an approach to simulating ad hoc network protocols integrated with their intended application. We implement the protocol layers and the application using the Specification and Description Language (SDL). Then, we simulate the ad hoc network directly from the SDL model. Using the interface of the SDL software tool, we incorporate the mobility model for hosts described in trace files. We suggest applying mobile ad hoc networks to communicating vehicles in road traffic. As an example, we look at vehicles exchanging messages to detect traffic jams on highways. Simulations of this application in a realistic traffic scenario demonstrate the powerful effect and robustness of rather simple, distributed protocols communicating through a mobile ad hoc network.
A statistical model of texture for medical image synthesis and analysis

We address the problem of building generative statistical models of the appearance of highly variable medical images, in particular mammograms. We treat appearance as a texture that can vary over the image plane. We present a model motivated by one of the most successful algorithms in the texture synthesis literature. Our approach has significant advantages over existing methods: it can learn from very large data sets, does not need to assume spatial ergodicity and can be used for synthesis and analysis. We present early results in the form of synthetic images.
African psychology and the emergence of the Madiban tradition

The recent welcome inclusion of the study of African psychology within the psychology degree curriculum of some forward-thinking African universities has been lauded as a great positive drive in the right direction. In the past, the practices that prevailed were those of mainstream Western psychology imported to Africa. This awkward situation originated during the period of colonialism and the emergence of missionary Christianity in Africa. This article proposes that if the current positive attitude toward African psychology is to last and bear fruit, there is a need to formally inaugurate a new order or tradition (referred to in this paper as the Madiban tradition) that would anchor and open up the study of psychology in African universities towards a new future: a future in which the progressive arm of both Western and African approaches to psychology would coexist and enjoy enduring mutual respect and equitable participatory presence in these programmes. This paper highlights the theoretical framework undergirding this vision and the challenges to be faced and new shifts to be made in implementing such a vision.
Image classification with recurrent attention models

In this work we apply a fully differentiable Recurrent Model of Visual Attention to unconstrained real-world images. We propose a deep recurrent attention model and show that it can successfully learn to jointly localize and classify objects. We evaluate our model on multiple digit images generated from MNIST data, Google Street View images, and a fine-grained recognition dataset of 200 bird species, and show that its performance is either comparable or superior to that of alternative models.
Query Learning with Large Margin Classi ersColin

The active selection of instances can sig-niicantly improve the generalisation performance of a learning machine. Large margin classiiers such as support vector machines classify data using the most informative instances (the support vectors). This makes them natural candidates for instance selection strategies. In this paper we propose an algorithm for the training of support vector machines using instance selection. We give a theoretical justiication for the strategy and experimental results on real and ar-tiicial data demonstrating its eeectiveness. The technique is most eecient when the data set can be learnt using few support vectors.
An arbitrary stressed NBTI compact model for analog/mixed-signal reliability simulations

A compact NBTI model is presented by directly solving the reaction-diffusion (RD) equations in a simple way. The new model can handle arbitrary stress conditions without solving time-consuming equations and is hence very suitable for analog/mixed-signal NBTI simulations in SPICE-like environments. The model has been implemented in Cadence ADE with Verilog-A and also takes the stochastic effect of aging into account. The simulation speed has increased at least thousands times. The performance of the model is validated by both RD theoretical solutions as well as silicon results.
Urban Distribution Grid Topology Estimation via Group Lasso

The growing penetration of distributed energy resources (DERs) in urban areas raises multiple reliability issues. The topology reconstruction is a critical step to ensure the robustness of distribution grid operation. However, the bus connectivity and network topology reconstruction are hard in distribution grids. The reasons are that 1) the branches are challenging and expensive to monitor due to underground setup; 2) the inappropriate assumption of radial topology in many studies that urban grids are mesh. To address these drawbacks, we propose a new data-driven approach to reconstruct distribution grid topology by utilizing the newly available smart meter data. Specifically, a graphical model is built to model the probabilistic relationships among different voltage measurements. With proof, the bus connectivity and topology estimation problems are formulated as a linear regression problem with least absolute shrinkage on grouped variables (Group Lasso) to deal with meshed network structures. Simulation results show highly accurate estimation in IEEE standard distribution test systems with and without loops using real smart meter data.
Cache and bandwidth aware matrix multiplication on the GPU

Recent advances in the speed and programmability of consumer level graphics hardware has sparked a flurry of research that goes beyond the realm of image synthesis and computer graphics. We examine the use of the GPU (graphics processing unit) as a tool for scientific computing, by analyzing techniques for performing large matrix multiplies in GPU hardware. An earlier method for multiplying matrices on the GPU suffered from problems of memory bandwidth. This paper examines more efficient algorithms that make the implementation of large matrix multiplication on upcoming GPU architectures more competitive, using only 25% of the memory bandwidth and instructions of previous GPU algorithms.
Reduction of fast spin echo cusp artifact using a slice‐tilting gradient

A “featherlike” artifact, termed a cusp artifact, is sometimes seen along the phase‐encoding direction in sagittal or coronal fast spin echo images. This artifact arises from the spins, at a location distant from the magnet isocenter, that are excited and aliased to the field of view because their precession frequency is similar to those at the isocenter. Such a situation is created due to a combination of excessive gradient nonlinearity and rapid change of the main magnetic field near the edge of the magnet where the artifact‐producing spins are located. A novel technique is proposed to reduce this artifact, in which a fast spin echo pulse sequence is modified to slightly tilt the slice selected by the radiofrequency excitation pulse away from the slice selected by the radiofrequency refocusing pulses. At the edge of the field of view, the incomplete overlap between the slices selected by the excitation and refocusing pulses effectively reduces the signals from the artifact‐prone region. In contrast, the slices overlap substantially within the field of view so that the signals are largely retained. This slice‐tilting technique has been implemented on two commercial MRI scanners operating at 3.0 T and 1.5 T, respectively, and evaluated on phantoms and human spine and extremities using clinical protocols. Both phantom and human results showed that the technique decreased the strength of the cusp artifact by at least 65% and substantially limited the spatial extent of the artifact. This technique, which can be further enhanced by a simple postprocessing step, offers significant advantages over a number of other techniques for reducing the fast spin echo cusp artifact. It can be implemented on virtually any scanner without hardware modification, complicated calibration, sophisticated image reconstruction, or patient‐handling alteration. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.
A Parameterizable NoC Router for FPGAs

The Network-on-Chip (NoC) approach fordesigning (System-on-Chip) SoCs is currently used forovercoming the scalability and efficiency problems of traditional on-chipinterconnection schemes, such as shared buses and point-to-point links. NoCdesign draws on concepts from computer networks to interconnect IntellectualProperty (IP) cores in a structured and scalable way, promoting design re-use.This paper presents the design and evaluation of a parameterizable NoC routerfor FPGAs. The importance of low area overhead for NoC components is pivotal inFPGAs, which have limited logic and routing resources. We obtain a low arearouter design by applying optimizations in switching fabric and dual purposebuffer/connection signals. We utilize a store and forward flow control withinput and output buffering. We proffer a component library to increase re-useand allow tailoring of parameters for application specific NoCs of varioussizes. The proposed router supports the mesh architecture which is well knownfor its scalability and simple XY routing algorithm. We presentIP-core-to-router mapping strategies for multi-local port routers that enableample opportunity to optimize the NoC for application specific data traffic. Aset of experiments were conducted to explore the design space of the proposedNoC router using different values of key router parameters: channel width (flitsize), arbitration scheme and IP-core-to-router mapping strategy. Area andlatency results from the experiments are presented and analyzed. These resultswill be useful to designers who want to implement NoC on FPGAs.