Miracle-dz/UniFAR-FTUs huggingface dataset:
Uncertainty Models of the Gradient Constraint for Optical Flow Computation

The uncertainty involved in the gradient constraint for optical ow detection is often modeled as constant Gaussian noise added to the time-derivative of the image intensity. In this paper, we examine this modeling closely and investigate the error behavior by doing simulation. Our result indicates that the error depends on both the spatial derivatives and the image motion. We propose alternative uncertainty models based on our experiment. It is shown that the optical ow computation algorithms based on them can detect more accurate optical ow than the conventional least-squares method. key words: optical ow, gradient constraint, noise model, probability model, least squares, maximum likelihood criterion.
An LP based Fair Subcarrier Allocation Algorithm for Cooperative OFDMA Systems with Grouped Users

Cooperative communication and orthogonal frequency division multiplexing (OFDM) technology are both promising candidates for next generation wireless communication systems. In this paper a Linear Programming (LP) based subcarrier allocation algorithm for cooperative multiuser OFDM system with grouped user is proposed. The proposed algorithm maximizes the data rate of all users over downlink under given constraints over non-sharing of carriers and fairness of data rate among all users. In this proposed algorithm the non sharing constraint of subcarriers have been relaxed initially into sharing constraint so that the non–convex optimization problem becomes a convex optimization problem, and thus, can solved efficiently using standard convex optimization tools. After maximizing total capacity of all active users in the system, the subcarrier allocation constraint is, then converted back to non-sharing constraint. The performance of proposed algorithm is studied and simulation results show that higher total capacity can be achieved using the proposed algorithm.
Illumination Processing in Face Recognition 187 Illumination Processing in Face Recognition

Driven by the demanding of public security, face recognition has emerged as a viable solution and achieved comparable accuracies to fingerprint system under controlled lightning environment. In recent years, with wide installing of camera in open area, the automatic face recognition in watch-list application is facing a serious problem. Under the open environment, lightning changes is unpredictable, and the performance of face recognition degrades seriously. Illumination processing is a necessary step for face recognition to be useful in the uncontrolled environment. NIST has started a test called FRGC to boost the research in improving the performance under changing illumination. In this chapter, we will focus on the research effort made in this direction and the influence on face recognition caused by illumination. First of all, we will discuss the quest on the image formation mechanism under various illumination situations, and the corresponding mathematical modelling. The Lambertian lighting model, bilinear illuminating model and some recent model are reviewed. Secondly, under different state of face, like various head pose and different facial expression, how illumination influences the recognition result, where the different pose and illuminating will be examined carefully. Thirdly, the current methods researcher employ to counter the change of illumination to maintain good performance on face recognition are assessed briefly. The processing technique in video and how it will improve face recognition on video, where Wang’s (Wang & Li, 2009) work will be discussed to give an example on the related advancement in the fourth part. And finally, the current state-of-art of illumination processing and its future trends will be discussed.
Analysis of a Multidimensional Model of Body Image Disturbance Using Structural Modeling.

Although there has been a wealth of recent research on the construct of body image disturbance, it is still a highly controversial and poorly understood phenomenon. Much of previous research has treated body image disturbance as if it were a unidimensional construct. Recently, a multidimensional model was proposed which incorporated the concepts of body size distortion, preference for thinness, body dissatisfaction, and fear of fatness. The purpose of the present investigation was to examine this multidimensional model in an attempt to establish its validity and resolve many of the current controversies regarding body image disturbance. The LISREL 7 program was used to perform a structural modeling analysis of the theoretical model. The multidimensional model was tested against alternate one, two, and three dimensional models. Several specific hypothesized effects regarding the relationships between the underlying dimensions were also tested. A total of 175 women participated in the study, 54 eating disorder patients and 121 undergraduate students. The results supported the hypothesized four dimensional model, relative to alternative models. Body dissatisfaction appeared to be directly affected by both body size distortion and preference for thinness, in addition to actual body size. Fear of fatness was found
Slam with Sc-phd Filters Slam with Sc-phd Filters

By Chee Sing Lee, Sharad Nagappa, Narcis Palomeras, Daniel E. Clark, and Joaquim Salvi An Underwater Vehicle Application T he random finite-set formulation for multiobject estimation provides a means of estimating the number of objects in cluttered environments with missed detections within a unified probabilistic framework. This methodology is now becoming the dominant mathematical framework within the sensor fusion community for developing multiple-target tracking algorithms. These techniques are also gaining traction in the field of feature-based simultaneous localization and mapping (SLAM) for mobile robotics. Here, we present one such instance of this approach with an underwater vehicle using a hierarchical multiobject estimation method for estimating both landmarks and vehicle position.
The Influence of Discussions in Virtual Communities on Consumers' Purchasing Behaviors in E-commerce: Implications for Trust Sources, Trust Building, and Consumer Purchase Intention

Virtual Community and E-commerce are both new research area which is becoming popular in IS academia. In most of research papers, virtual community and e-commerce are talked separately in different stream. Since many e-commerce websites contain a virtual community, we combine these two together to consider whether discussions in virtual communities can influence people’s online shopping behaviors. This paper bases on literature of trust to propose that there are several types of trust sources – poster trust sources, consumer trust sources, and environment trust sources – engender consumer trust in posters in a virtual community. In addition, consumer trust in posters can affect consumer trust in sellers who referred in the posters’ discussion contents, and then affect consumers’ purchase intention further.
Road-Junction Traffic Signal Timing Optimization by an adaptive Particle Swarm Algorithm

The purpose of this paper is to investigate the application of particle swarm optimization (PSO) algorithm in solving the traffic signal timing optimization problem. A local fuzzy-logic controller (FLC) installed at each junction is used to provide some initial solutions for the particle swarm optimization algorithm. Coordination parameters from adjacent junctions are taken into consideration by local fuzzy-logic controller. The membership functions and the rules of the fuzzy logic controller (FLC) are optimized using the standard particle swarm optimization (SPSO) algorithm. A new particle swarm optimization algorithm is used to optimize the average delay and average number of stops for adjacent junctions and to handle the constraints. The simulation results show that the delay per vehicle can be substantially reduced under constant traffic demands and time-varying traffic demands, particularly when the traffic demands on the upstream is larger than the traffic demand on the downstream. The implementation of this method does not require complicated hardware, and such simplicity makes it a useful tool for offline studies or real-time control purposes
Large Neighborhood Search for the Single Vehicle Pickup and Delivery Problem with Multiple Loading Stacks

This paper studies a single vehicle pickup and delivery problem with loading constraints. In this problem, the vehicle contains a number of (horizontal) stacks of finite capacity for loading items from the rear of the vehicle. Each stack must satisfy a last-in- first-out constraint where any new item must be loaded on top of a stack and any unloaded item must be on top of its stack. A large neighborhood search is proposed for solving this problem. Computational results are reported on different types of randomly generated instances. Results are also reported on benchmark instances for two special cases of our problem and a comparison is provided with state-of-the-art methods.
A quantitative assessment of uncertainties affecting estimates of global mean OH derived from methyl chloroform observations

[1] We estimated the global abundance of OH for the years 1988–1994 by interpreting observations of methyl chloroform (MCF) from two networks using an inverse technique and a 3-D chemical transport model driven by assimilated meteorology. Our inversion approach optimized both the emissions of MCF and the abundance of OH. Because of an a priori overestimate of the latitudinal gradient of MCF concentration by the model in the standard setup, the inversion lowers global emissions and the global sink due to OH. Optimized emissions are about 10% lower than published inventories on average between 1988 and 1994, and the decrease in the sink suggested by the inversion implies an average lifetime for MCF (with respect to tropospheric OH) of about 6.9 years, 11–21% longer than the 5.7–6.2 years reported in previous optimization studies. Our results are driven by the need to match the observed latitudinal gradient of MCF while balancing the MCF budget. We find that these results depend on the a priori constraint placed on MCF emissions, the rate of interhemispheric mixing in the model, the interhemispheric distribution of OH assumed, and the model simulation of pollution events. Since these factors are highly uncertain, we believe that the level of understanding on global lifetimes of pollutants removed by OH is lower than might be implied by the narrow range of estimates for MCF lifetime in the literature.
Wavelet-based fractal analysis of the epileptic EEG signal

The wavelet transform is a natural tool for characterizing self-similar signals. In this work, the spectral exponent γ derived from the wavelet-based representation for 1/f processes is used to investigate the self-similarity of electrocorticography (intracranial EEG) signals from an epilepsy patient. An increase in γ leads to sample signals with smoother temporal patterns. Our computational results show that during an epileptic seizure γ is significantly higher than that associated with other states of the brain, implying that wavelet-based fractal analysis is potentially a useful computational tool for epileptic seizure detection.
Inflation-Gap Persistence in the U.S

We estimate vector autoregressions with drifting coefficients and stochastic volatility to investigate whether US inflation persistence has changed. We focus on the inflation gap, defined as the difference between inflation and trend inflation, and we measure persistence in terms of short- to medium-term predictability. We present evidence that inflation-gap persistence increased during the Great Inflation and that it fell after the Volcker disinflation. We interpret these changes using a dynamic new Keynesian model that highlights the importance of changes in the central bank's inflation target. (JEL E12, E31, E52, E58)
Persistence of a Methicillin- Resistant Staphylococcus aureus Clone in a Drug- Use Network

Sir—The study by Quagliarello et al. [1] has shown links between geographic location, drug-sharing activities, and the transmission of staphylococci among users of injection drugs. Patterns of drug use, use of inhalation paraphernalia, and affiliation with 1 of 4 drug-use networks were identified as major contributors to the transfer of staphylococci in a nonoutbreak setting. The usefulness of a multifactorial approach in combining biological networks, social linkages, and molecular epidemiological techniques was thereby demonstrated. In a previous study, we identified dis
HYBRID ALGORITHM TO DETECT GLOBAL , ADAPTIVE , THRESHOLD AND SEGMENTATION OF COLOR IMAGE WITH ENTROPY AND ENERGY VALUE

ABSTARCT: Digital images occur very frequently in the world today. All images on the Internet are in digital form; most images seen in magazines and newspapers have been in digital form at some point before publication; and many films have been converted to a digital format for premastering. Digital Images are processed simply to improve the quality of the image, or they may be processed to extract useful information, such as the position, size or orientation of an object. Image analysis is an area of image processing that deals with techniques for extracting information from an image. In the simplest form, this task could be reading an address on a letter or finding defective parts on an assembly line. More complex image analysis systems measure quantitative information and use it to make a sophisticated decision such as trying to find images with a specified object in an image database. The various tasks involved in image analysis can be broken down into conventional (low level) techniques and knowledge-based (high level) techniques. KEY WORD: Digital Image, Image Segmentation, Edge detection, Canny Edge, Ostu Method
Discovery in grid and web services environments: A survey and evaluation

An important step in realizing the vision of both Web services and Grid is the provision of a robust, automatic and reliable solution for finding services or resources in such environments. Different solutions to this problem were already proposed, each with its specific model and realization. Although all solutions address the same problem, it is very difficult for a non-expert and even for an expert in the field to decide if and why one solution is better then another. This paper proposes a systematic set of criteria, a framework, that can help in the evaluation of different discovery approaches. Furthermore some of the most relevant discovery approaches in Web services and Grid environments are surveyed and evaluated according to the proposed evaluation framework.
Systems Biology of Tissue-Specific Response to Anaplasma phagocytophilum Reveals Differentiated Apoptosis in the Tick Vector Ixodes scapularis

Anaplasma phagocytophilum is an emerging pathogen that causes human granulocytic anaplasmosis. Infection with this zoonotic pathogen affects cell function in both vertebrate host and the tick vector, Ixodes scapularis. Global tissue-specific response and apoptosis signaling pathways were characterized in I. scapularis nymphs and adult female midguts and salivary glands infected with A. phagocytophilum using a systems biology approach combining transcriptomics and proteomics. Apoptosis was selected for pathway-focused analysis due to its role in bacterial infection of tick cells. The results showed tissue-specific differences in tick response to infection and revealed differentiated regulation of apoptosis pathways. The impact of bacterial infection was more pronounced in tick nymphs and midguts than in salivary glands, probably reflecting bacterial developmental cycle. All apoptosis pathways described in other organisms were identified in I. scapularis, except for the absence of the Perforin ortholog. Functional characterization using RNA interference showed that Porin knockdown significantly increases tick colonization by A. phagocytophilum. Infection with A. phagocytophilum produced complex tissue-specific alterations in transcript and protein levels. In tick nymphs, the results suggested a possible effect of bacterial infection on the inhibition of tick immune response. In tick midguts, the results suggested that A. phagocytophilum infection inhibited cell apoptosis to facilitate and establish infection through up-regulation of the JAK/STAT pathway. Bacterial infection inhibited the intrinsic apoptosis pathway in tick salivary glands by down-regulating Porin expression that resulted in the inhibition of Cytochrome c release as the anti-apoptotic mechanism to facilitate bacterial infection. However, tick salivary glands may promote apoptosis to limit bacterial infection through induction of the extrinsic apoptosis pathway. These dynamic changes in response to A. phagocytophilum in I. scapularis tissue-specific transcriptome and proteome demonstrated the complexity of the tick response to infection and will contribute to characterize gene regulation in ticks.
Hagedorn Behavior of Little String Theories

We examine the Hagedorn behavior of little string theory using its conjectured duality with near-horizon NS5-branes. In particular, by studying the string-corrected NS5-brane supergravity solution, it is shown that tree-level corrections to the temperature vanish, while the leading one-loop string correction generates the correct temperature dependence of the entropy near the Hagedorn temperature. Finally, the Hagedorn behavior of ODp-brane theories, which are deformed versions of little string theory, is considered via their supergravity duals.
Location Update versus Paging Trade-Off in Cellular Networks: An Approach Based on Vector Quantization

In this paper, we propose two information-theoretic techniques for efficiently trading off the location update and paging costs associated with mobility management in wireless cellular networks. Previous approaches always attempt to accurately convey a mobile's movement sequence and hence cannot reduce the signaling cost below the entropy bound. Our proposed techniques, however, exploit the rate distortion theory to arbitrarily reduce the update cost at the expense of an increase in the corresponding paging overhead. To this end, we describe two location tracking algorithms based on spatial quantization and temporal quantization, which first quantize the movement sequence into a smaller set of codewords and then report a compressed representation of the codeword sequence. Although the spatial quantization algorithm clusters individual cells into registration areas, the more powerful temporal quantization algorithm groups sets of consecutive movement patterns. The quantizers themselves are adaptive and periodically reconfigure to accommodate changes in the mobile's movement pattern. Simulation study with synthetic and real movement traces for both single-system and multisystem cellular networks demonstrate that the proposed algorithms can reduce the mobile's update frequency to 3-4 updates/day with reasonable paging cost, low computational complexity, storage overhead, and codebook updates.
Coordination and control of globally distributed software development projects: the GOLDD case

Advanced information and communication technologies (ICT) enable cooperation of individuals and teams from globally distributed locations. Professionals from all over the world contribute with their expertise in projects which take on the character of globally distributed projects . While experiences with such projects in the manufacturing industry are well publicized and documented, during the last decade similar developments have become widespread in software engineering projects. Often, these developments take the form of outsourcing or consultant-client relationships, where part or all of the information systems (IS) development effort may be outsourced to an offsite vendor. As the offsite part of the work, mostly program development and testing, but increasingly design, migrates to distant software centers in Bangalore, India, Dublin, Ireland, and Singapore, these software projects are taking on the characteristics of globally distributed projects. In IS research and practice literature, coordination and control have been key issues in managing IS development projects. Preliminary research indicates that four factors affect the coordination and control of globally distributed projects: (1) geographical distributedness of sites, (2) differences of time zones, (3) cross-cultural differences
Measurement of intrinsic alignments in galaxy ellipticities

We measure the alignment of galaxy ellipticities in the local Universe over a range of scales using digitized photographic data from the {SuperCOSMOS} Sky Survey. We find for a magnitude cut of {bJ{\textless}20.5}, corresponding to a median galaxy redshift of z{\textasciitilde}0.1, and 2? 106 galaxies, that the galaxy ellipticities exhibit a non-zero correlation over a range of scales between 1 and 100arcmin. We detect this correlation in two colours, {bJ} and R and, most significantly, in the cross-correlation between the two bands, which is less likely to be contaminated by systematics. In particular, we measure the variance of mean galaxy ellipticities, ? 2(? ), in square angular cells on the sky as a function of cell size and find that it lies in the range, 2? 10- 4{\textgreater}=? 2(? ){\textgreater}{\textasciitilde}1? 10-5 for cell side lengths of between 15{\textless}=? {\textless}=100arcmin. Considering the low median redshift of the galaxies in the sample and hence the relatively low effective cross-section for lensing of these galaxies by the large-scale structure of the Universe, we propose that we have detected an intrinsic alignment of galaxy ellipticities. We compare our results with recent analytical and numerical predictions made for intrinsic galaxy alignment and find good agreement. We discuss the importance of these results for measuring cosmic shear from upcoming shallow surveys (e.g. the Sloan Digital Sky Survey) and we outline how these measurements could possibly be used to constrain models of galaxy formation and/or measure the mass distribution in the local Universe.
Multiple Source Procurement Competitions

Relationships between buying and selling organizations in business markets are varied and complex. One important relationship is procurement, or the type of alliance that buyers form with sellers to fulfill their purchasing needs. Multiple sourcing is often proposed to prevent a variety of procurement problems. We develop a bidding model to investigate the effect of multiple sourcing on competitive behavior prior to supplier selection. The model treats the number of bidders (and the decision to bid) endogenously. This distinctive feature allows us to show that the distribution of the number of bids is not independent of the competition type. Most previous models have not considered this question at all. Although multiple sourcing does increase participation in a bidding competition, we show that it can lead to strategic pre-award price increases that can mitigate the effects of the advantages stressed by most previous analyses of post-award supplier management.