Miracle-dz/UniFAR-FTUs huggingface dataset:
Using EM to Derive a Convergent Alternative to Loopy Belief Propagation University of Toronto Technical Report CSRG-579

EMBP is a variant of Belief Propagation (BP) that always converges, even on graphical models with loops. Its initial ad hoc development was driven by the search for likely variable assignments in Constraint Satisfaction problems, but in general it can estimate marginal probabilities over any model that BP can. Thus we derive a canonical version of EMBP from first principles by applying the Expectation Maximization (EM) framework. In so doing we re-characterize the inference task as parameter estimation over a redundant problem representation combining the primal and dual versions of a graphical model, yielding a new technique whose formula is remarkably similar to BP’s despite guaranteeing convergence.
Unsupervised Modeling of Patient-Level Disease Dynamics

To provide insight into patient-level disease dynamics from data collected at irregular time intervals, this work extends applications of semi-parametric clustering for temporal mining. In the semi-parametric clustering framework, Markovian models provide useful parametric assumptions for modeling temporal dynamics, and a non-parametric method is used to cluster the temporal abstractions instead of operating on the original data. Our contribution extends abstraction to continuous-time Markov models and the clustering component to the non-parametric Bayesian setting, which does not require the number of clusters to be indicated a priori.
Controlled streaming of video over the Internet

Multimedia content transfer over the internet is becoming increasingly important with a large penetration of smart phones PDAs, Laptops and IPTV. The interfaces supporting real-time applications such as Tele-education, entertainment, tele-medicine, remote monitoring and control are consuming a lot of bandwidth. All these applications require reliable streaming of the data over the internet, adhering to the assured Quality of Service (QoS). In this paper, smart streaming techniques exploiting the redundancies in the data are discussed.
Interactive sketching of urban procedural models

3D modeling remains a notoriously difficult task for novices despite significant research effort to provide intuitive and automated systems. We tackle this problem by combining the strengths of two popular domains: sketch-based modeling and procedural modeling. On the one hand, sketch-based modeling exploits our ability to draw but requires detailed, unambiguous drawings to achieve complex models. On the other hand, procedural modeling automates the creation of precise and detailed geometry but requires the tedious definition and parameterization of procedural models. Our system uses a collection of simple procedural grammars, called snippets, as building blocks to turn sketches into realistic 3D models. We use a machine learning approach to solve the inverse problem of finding the procedural model that best explains a user sketch. We use non-photorealistic rendering to generate artificial data for training convolutional neural networks capable of quickly recognizing the procedural rule intended by a sketch and estimating its parameters. We integrate our algorithm in a coarse-to-fine urban modeling system that allows users to create rich buildings by successively sketching the building mass, roof, facades, windows, and ornaments. A user study shows that by using our approach non-expert users can generate complex buildings in just a few minutes.
The Influence of X-Factor (Trunk Rotation) and Experience on the Quality of the Badminton Forehand Smash

Abstract No existing studies of badminton technique have used full-body biomechanical modeling based on three-dimensional (3D) motion capture to quantify the kinematics of the sport. The purposes of the current study were to: 1) quantitatively describe kinematic characteristics of the forehand smash using a 15-segment, full-body biomechanical model, 2) examine and compare kinematic differences between novice and skilled players with a focus on trunk rotation (the X-factor), and 3) through this comparison, identify principal parameters that contributed to the quality of the skill. Together, these findings have the potential to assist coaches and players in the teaching and learning of the forehand smash. Twenty-four participants were divided into two groups (novice, n = 10 and skilled, n = 14). A 10-camera VICON MX40 motion capture system (200 frames/s) was used to quantify full-body kinematics, racket movement and the flight of the shuttlecock. Results confirmed that skilled players utilized more trunk rotation than novices. In two ways, trunk rotation (the X-factor) was shown to be vital for maximizing the release speed of the shuttlecock – an important measure of the quality of the forehand smash. First, more trunk rotation invoked greater lengthening in the pectoralis major (PM) during the preparation phase of the stroke which helped generate an explosive muscle contraction. Second, larger range of motion (ROM) induced by trunk rotation facilitated a whip-like (proximal to distal) control sequence among the body segments responsible for increasing racket speed. These results suggest that training intended to increase the efficacy of this skill needs to focus on how the X-factor is incorporated into the kinematic chain of the arm and the racket.
Structural analysis of dialects, sub-dialects and sub-sub-dialects of Chinese

In China, there are hundred kinds of dialects. By traditional dialectology, they are classified into seven big dialect regions and most of them also have many sub-dialects and sub-subdialects. As they are different in various linguistic aspects, people from different dialect regions often cannot communicate orally. But for the sub-dialects of one dialect region, although they are sometimes still mutually unintelligible, more common features are shared. In this paper, a dialect pronunciation structure, which has been used successfully in dialectbased speaker classification in our previous work [1], is examined for the task of speaker classification and distance measurement among cities based on sub-dialects of Mandarin. Using the finals of the dialectal utterances of a specific list of written characters, a dialect pronunciation structure is built for every speaker in a data set and these speakers are classified based on the distances among their structures. Then, the results of classifying 16 Mandarin speakers based on their sub-dialects show that they are linguistically classified with little influence of their age and gender. Finally, distances among sub-sub-dialects are similarly calculated and evaluated. All the results show high validity and accordance to linguistic studies. Index Terms: Sub-dialects of Mandarin, pronunciation structure, speaker classification
Face Recognition Based on PCA and SVM Optimized by MEB

Face recognition has been widely researched in the classification issues. This paper proposed a new framework of face recognition based on PCA and SVM. In order to reduce the computation of SVM algorithm in the framework, MEB was introduced into the framework. Experimental results have shown that the proposed algorithm can get better results than basic PCA and PCA-SVM algorith.
Algorithms for packet classification

The process of categorizing packets into "flows" in an Internet router is called packet classification. All packets belonging to the same flow obey a predefined rule and are processed in a similar manner by the router. For example, all packets with the same source and destination IP addresses may be defined to form a flow. Packet classification is needed for non-best-effort services, such as firewalls and quality of service; services that require the capability to distinguish and isolate traffic in different flows for suitable processing. In general, packet classification on multiple fields is a difficult problem. Hence, researchers have proposed a variety of algorithms which, broadly speaking, can be categorized as basic search algorithms, geometric algorithms, heuristic algorithms, or hardware-specific search algorithms. In this tutorial we describe algorithms that are representative of each category, and discuss which type of algorithm might be suitable for different applications.
Minesweeper for Sensor Networks--Making Event Detection in Sensor Networks Dependable

Event detection using Wireless Sensor Networks (WSNs) has become a new field of research in the past years, increasing the need for dependability and fault tolerance. Our work exploits the massive redundancy of large WSNs in combination with neighbours' relations to identify faulty nodes. We present a new approach to categorize nodes in being faulty or fault free based on the event detection results of the nodes' neighbours and the nodes adjacent to the neighbours. For error probabilities
OR : An Open Source Coreference Resolution System

RELAXCOR is a constraint-based graph partitioning approach to coreference resolution solved by relaxation labeling. It is an open source software, available for download, that can be used for research proposes in issues related to coreference resolution as well as a black box processing tool. This paper describes the architecture of the system and its advantages.
Developing and implementing strategy for benefits realisation

Background. The failure of initiatives to adequately plan and deliver benefits is a perceived problem in the healthcare sector. Problems of strategy formation and successful innovation are widely discussed in the literature. The concept of benefits realisation offers a possible key to better planning, but before this can be achieved strategic innovation is necessary to integrate the benefits realisation process itself into the corporate planning process. Research question. How can successful strategic innovation be introduced into NHS trusts? Methodology. A prescriptive model of strategy has been developed, employing a phenomenological analysis which draws on: [1] one of the authors' twelve years experience of working in strategy formation and implementation; [2] the results of three years action research, developing the BeReal benefits realisation model. The strategy model is evaluated in the light of existing literature on organizational strategy and planning. It is intended that the model will be subsequently tested in an action research case study. Findings. Much of the literature stresses the emergent nature of strategy and the consequent difficulties that this presents for the development of formal planning models. The model seeks to integrate planning and implementation into an orderly learning process in which broad policy objectives are increasingly refined in the light of stakeholder and corporate needs. Three integrated planning 'levels' are identified: strategic; portfolio and project. Essential inputs are identified in each level, including: regulatory direction, community consultation and corporate planning; organizational capability, knowledge realisation and resource capacity; programme alignment, stakeholder alignment and structured project benefits. Conclusion. The model identifies essential inputs to the planning process which, if not properly managed, can result in organizational disruption or stakeholder dissatisfaction. It offers a structured procedure for integrating these. Finally, it demonstrates how the notion of benefits realisation and the BeReal process itself, fit into a coherent strategy development and implementation process.
Semantic Web for Knowledge Integration between Traditional Chinese Medicine and Biomedicine

The World Wide Web connects a wide variety of communities in medical domain, and provides a platform for knowledge exchange and integration between Traditional Chinese Medicine (TCM) and biomedicine. However, the cultural gaps between TCM and Western Medicine hinder cross-cultural communication. We utilize Semantic Web technologies to build a knowledge base that integrates distributed and heterogeneous knowledge elements from both biomedicine and TCM, and provides various information retrieval and knowledge discovery services. We explain how this integrated knowledge base helps to bridge the linguistic, semantic, and ontological gaps between different communities, and fosters cross-cultural scientific collaboration.
The Influence of Left Ventricular Late Diastolic Filling on the A Wave of the Left Ventricular Pressure Trace

To study the influence of left ventricular (LV) late diastolic filling on the A wave of the LV pressure, simultaneously recorded echocardiographic LV dimensions and high-fidelity LV pressure measurements were taken in 24 patients. Group I comprised eight patients without LV hypertrophy (LVH) and LV end-diastolic pressure (LVEDP) ≤ 13 mm Hg. Group 2 comprised 16 patients with LVH secondary to aortic stenosis, idiopathic hypertrophic subaortic stenosis, or hypertension and increased LVEDP. Patients in group 2 had significantly thicker left ventricles, decreased mitral E-to-F slopes, and larger A waves in the LV pressure curve. On the basis of end-diastolic chamber stiffness, we divided group 2 into two populations: 12 patients (group 2A) with end-diastolic chamber stiffness similar to that in group 1, and four patients (group 2B) with markedly elevated end-diastolic chamber stiffness. Patients in group 2A had a larger atrial contribution to LV filling than those with markedly abnormal stiffness (group 2B). Therefore, in LVH an increased A wave in the LV pressure may be related to either elevated end-diastolic chamber stiffness or augmented left atrial volume transport.
Mapping the Ensemble of Natural Image Patches by Explicit and Implicit Manifolds

Image patches are fundamental elements for object modeling and recognition. However, there has not been a panoramic study in the literature on the structures of the whole ensemble of natural image patches. In this article, we study the mathematical structures of the ensemble of natural image patches and map image patches into two types of subspaces which we call “explicit manifolds” and “implicit manifolds” respectively. On explicit manifolds, one finds those simple and regular image primitives, such as edges, bars, corners and junctions. On implicit manifolds, one finds those complex and stochastic image patches, such as textures and clutters. On these manifolds, different perceptual metrics are used. Then we show a unified framework for learning a probabilistic model on the space of patches by pursuing both types of manifolds under a common information theoretical principle. The connection between the two types of manifolds are realized through image scaling which changes the entropy of the image patches. The explicit manifolds live in low entropy regimes while the implicit manifolds live in high entropy regimes. In experiments, we cluster the natural image patches and compare the two types of manifolds with a common information theoretical criterion. We also study the transition of the manifolds over scales and show that the complexity peak in a middle entropy regime where most objects and parts reside.
DATA TRANSMISSION USING TCP , GZIP & TINY ALGORITHMS

The aim of the Paper is to provide the security during transmission of the data. Commonly used technologies are cryptography, Compression and decompression. This can be used for secure and fast sending for security purpose we are using the Cryptography technology and to increase the file transfer speed we are using the compression and decompression technologies. In this paper we described lot of processes for secure data transmission. First perform the compression and decompression techniques for decrease the file size. It will increase the transmission speed here maintains compression and decompression technique based on the GZIP Algorithm. Than perform the cryptography technique based on the TINY Encryption Algorithm. In sending process the TCP (Transaction control protocol) was involved.
Environmental Injustice, Political Agency and the Challenge of Creating Healthier Communities

I argue that our current understanding of the philosophical dimensions of environmental injustice neglects an important component of those injustices. Specifically, by focusing on distributive, participatory and recognitional injustice, we fail to respond to the ways that environmental exposures, even in the absence of physiological harms, can impact upon a person's experience of herself as a political agent. This has important implications for interventions in cases of environmental injustice, but also for how we understand what is required for full participation in a polity.
Exploiting 3D semantic scene priors for online traffic light interpretation

In this paper we present a probabilistic framework for increasing online object detection performance when given a semantic 3D scene prior, which we apply to the task of traffic light detection for autonomous vehicles. Previous approaches to traffic light detection on autonomous vehicles have involved either precise knowledge of the relative 3D positions of the vehicle and the traffic light (requiring accurate and expensive mapping and localisation systems), or a classifier-based approach that searches for traffic lights in images (increasing the chance of false detections by searching all possible locations for traffic lights). We combine both approaches by explicitly incorporating both prior map and localisation uncertainty into a classifier-based object detection framework, generating a scale-space search region that only evaluates parts of the image likely to contain traffic lights, and weighting object detection scores by both the classifier score and the 3D occurrence prior distribution. We present results comparing a range of low- and high-cost localisation systems using over 30 km of data collected on an autonomous vehicle platform, demonstrating up to a 40% improvement in detection precision over no prior information and 15% improvement on unweighted detection scores. We demonstrate a 10x reduction in computation time compared to a naïve whole-image classification approach by considering only locations and scales in the image within a confidence bound of the predicted traffic light location. In addition to improvements in detection accuracy, our approach reduces computation time and enables the use of lower cost localisation sensors for reliable and cost-effective object detection.
Spectral Efficiency of the Cellular Two-Way Relaying with Large Antenna Arrays

This paper considers a multiuser cellular two-way relay network (cTWRN) where multiple users exchange information with a base station (BS) via a relay station (RS). Each user is equipped with a single antenna, while both the BS and the RS are equipped with a very large antenna array. We investigate the performance of the cTWRN with amplify-and-forward (AF) based physical-layer network coding, and derive closed-form expression for the asymptotic spectral efficiency when both the number of antennas at the BS and the RS grow large. It is shown that the noise propagation of the non-regenerative relaying protocol can be greatly suppressed, and the AF relaying scheme can approach the cut-set bound under certain conditions. We also investigate the performance of the AF relaying scheme under two power-scaling cases, and show that the transmit power of the BS and each user can be made inversely proportional to the number of relay antennas while maintaining a given quality-of-service. Numerical results are presented to verify the analytical results.
Perceived Parenting Styles and Parental Inconsistency Scale: Construct Validity in Young Adults

The study examines evidences of construct validity of the Perceived Parental Styles and Parental Inconsistency scale –EPIPP–, on a sample of 369 young adults. Individuals were asked about their father and their mother by means of 24 items. These conform six subscales that constitute a first-order-model–Affection, Dialogue, Indifference, Verbal Coercion, Physical Coercion and Prohibition– that additionally group into two major scales –a second-order model–:Responsiveness and Demandingness.A confirmatory factor analysis was carried out on the first-order and second-order factor structures, using maximum likelihood and a bootstrap procedure with 500 random samples. Resulting indexes showed an excellent fit in both models for the Father and Mother versions. Furthermore, adequate results were obtained in a cross-validation and a factorial invariance analysis. This way, solid evidences of construct validity were obtained for the EPIPP, suggesting it for the assessment of perceived parenting in young adults.
Secocrassumol, a seco-Cembranoid from the Dongsha Atoll Soft Coral Lobophytum crassum

Chemical investigations on the Dongsha Atoll soft coral Lobophytum crassum led to the purification of a new seco-cembranoid, secocrassumol. The structural elucidation was established by extensive NMR, HRESIMS and CD data. The absolute configuration at C-12 was determined as S using a modified Mosher’s acylation. Secocrassumol differs from previously known marine seco-cembranoid in that it possesses an unprecedented skeleton functionalized at C11-C12 bond cleavage. Secocrassumol showed antiviral activity against human cytomegalovirus (HCMV) with an IC50 value of 5.0 μg/mL.
Illumination Invariant Text Recognition System Based On Contrast Limit Adaptive Histogram Equalization in Videos/Images

The textual information present in the image/video plays a major role in understanding scene/video. In this paper, we propose a system for detecting the text in videos possessing varying illumination based on Contrast Limit Adaptive Histogram Equalization (CLAHE). Certain heuristic rules are applied to the preprocessed video frame to detect the text clusters. Further, the newly designed geometrical rules and morphological operations are employed on the obtained text detection results for text localization. Once the text gets localized, the text lines are segmented followed by character segmentation. The segmented characters are then recognized using OCR and then synthesized as voice output message which is audible so that one can hear and understand the text content present in videos. The experimental results obtained on publicly available standard datasets, TRECVID video dataset and our own video dataset illustrate that the proposed method can detect, localize and recognize the texts of various sizes, fonts and colors.
X-Ray Emission from the Guitar Nebula

We have detected weak soft X-ray emission from the pulsar wind nebula trailing the high-velocity star PSR 2224+65 (the “Guitar Nebula”). This X-ray flux gives evidence of γ ~ 107 eV particles in the pulsar wind and constrains the properties of the postshock flow. The X-ray emission is most easily understood if the shocked pulsar wind is partly confined in the nebula and if magnetic fields in this zone can grow to near-equipartition values.