Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Distance Metric Learning in the Presence of Label Noise

Many distance learning algorithms have been developed in recent years. However, few of them consider the problem when the class labels of training data are noisy, and this may lead to serious performance deterioration. In this paper, we present a robust distance learning method in the presence of label noise, by extending a previous non-parametric discriminative distance learning algorithm, i.e., Neighbourhood Components Analysis (NCA). Particularly, we analyze the effect of label noise on the derivative of likelihood with respect to the transformation matrix, and propose to model the conditional probability of the true label of each point so as to reduce that effect. The model is then optimized within the EM framework, with additional regularization used to avoid overfitting. Our experiments on several UCI datasets and a real dataset with unknown noise patterns show that the proposed RNCA is more tolerant to class label noise compared to the original NCA method.
Technical opinion: getting the best of both real and virtual worlds

In contrast to virtual reality systems, generally designed to immerse the user as fully as possible within a synthetic environment, computer-augmented reality supplements real-world stimuli with computer-generated elements. Visually, this is achieved by electronic or optical superimposition of computer graphics with a user’s view of the real world. The potential applications are wide ranging, but there are a number of hurdles to overcome if such systems are to reach fruition. The greatest challenges relate to maintenance of accurate spatial and temporal registration of real and virtual entities when objects are moved or the point of view changes. However, even if these problems are resolved, inherent limitations associated with current “see-through” displays remain when it comes to producing convincing integration of real and virtual elements. Most problematic, they produce a graphic overlay that is transparent and easily washed-out in regions where the background is bright and, hence, are incapable of simulating the occlusion effects essential for appropriate depth perception. Proposed here is a simple but effective way of facilitating visual occlusion and improving the degree of color control in see-through augmented reality displays. While most people are familiar with the concept of combining computer-generated graphics with real-world imagery (exemplified, for example, by films such as “Jurassic Park”), achieving similar effects in a head-mounted display over a real-time view of our actual environment is a more difficult proposition. The principle of such computer augmentation of reality has its roots in the early headmounted display devised by Sutherland [8] and the subsequent head-up displays designed for military pilots. It is only recently that more wide-spread interest and potential has developed. Visual augmentation offers many of the advantages of a synthetic world while retaining the obvious value of interaction with reality. Getting the best of both worlds in this way offers many new and exciting possibilities, including assistance in manufacturing and maintenance [4, 5], medical imaging [3], robotic teleoperation [7], and design visualization [1]. However, significant difficulties are inherent, particularly with respect to applications for which the real and virtual elements need to be convincingly integrated. For example, accurate spatial and temporal registration of computer graphics with a real scene remains crucial to the success of most applications, especially those providing manufacturing or surgical guidance. Whereas small tracking inaccuracies might not be noticeable in an immersive VR system, even very small angular errors in detecting the orientation of an augmented reality headset can result in a large displacement in the registration of the graphics. Ultimately, more accurate methods of position and orientation tracking are required, as well as effective methods of tracking over larger distances. Further registration problems can occur due to Getting the Best of Both Real and Virtual Worlds Eric W. Tatham
The effects of ambiguity on project task structure in new product development

New product development (NPD) projects are characterised by task ambiguity, whereby the set of tasks necessary for project completion and the relationships between tasks are initially unknown and only emerge as the development process unfolds. This paper uses interview data from NPD project managers in a large telecom firm to examine the influence of product requirements ambiguity on NPD task structures. The findings are used to propose a taxonomy outlining four generic patterns by which NPD task structures change during the product development process as a result of requirements ambiguity—task expansion, contraction, substitution and combination. The results also highlight in general terms the role of communication, coordination, knowledge and problem solving as distributed NPD project teams struggle to resolve ambiguity. Knowledge of how NPD project task structures evolve can lead to improved strategies for managing projects with ambiguous requirements. Two general types of strategies are suggested, decomposition of project tasks to minimize interdependence between tasks and the flexible adaptation of NPD task structures as new forms of task interdependence are recognised during the development process. Copyright # 2006 John Wiley & Sons, Ltd.
Motivation in online communities

Different approaches of design methodology that have been developed throughout the history of the design methods movement have produced many insights into the structure of the design process (Alexander, 1964; Simon, 1969; Schön. 1983; Hubka and Eder, 1987; Pahl and Beitz. 1984; Roozenburg and Eekels, 1995). It seems however, that little of this accumulated knowledge is used in the daily practice of designing. The relation between design methodology and design practice is still weak (Cross, 1993; Achten et al. 2005). One reason might be that design methods are not addressing the designer’s needs. And thus are not supporting the designer, with a specific task, to solve the problem at hand. (BadkeSchaub et al. 2005) The aim of this research project was to develop a solution for this problem: the concept of Community Based Design Support (CBDS). This concept, inspired by the online community platforms that are emerging on the internet, enables the integration of a personal, contextual, social and dynamic dimension in design methodology Based on the CBDS model a software platform was designed: Designflow. A prototype was built to test if the concept of CBDS can provide designers with efficient and effective design support.
Road sign detection based on visual saliency and shape analysis

Road sign detection plays an important role in driver assistance system. However, it faces problems of high computational cost and low contrast in video sequences. In this paper, we propose a two-level hierarchical algorithm which addresses these problems by making better use of the color and shape information of road signs. In order to solve the problem of low image contrast, we propose to improve the color contrast using our algorithm based on visual saliency. In order to reduce the high computational cost, an improved radial symmetry transform (IRST) is developed for grouping feature points on the basis of their underlying symmetry in an image. Experimental results show that our methods are robust to a broad range of lighting conditions and efficient enough for real-time applications.
Lack of myostatin results in excessive muscle growth but impaired force generation

The lack of myostatin promotes growth of skeletal muscle, and blockade of its activity has been proposed as a treatment for various muscle-wasting disorders. Here, we have examined two independent mouse lines that harbor mutations in the myostatin gene, constitutive null (Mstn−/−) and compact (Berlin High Line, BEHc/c). We report that, despite a larger muscle mass relative to age-matched wild types, there was no increase in maximum tetanic force generation, but that when expressed as a function of muscle size (specific force), muscles of myostatin-deficient mice were weaker than wild-type muscles. In addition, Mstn−/− muscle contracted and relaxed faster during a single twitch and had a marked increase in the number of type IIb fibers relative to wild-type controls. This change was also accompanied by a significant increase in type IIB fibers containing tubular aggregates. Moreover, the ratio of mitochondrial DNA to nuclear DNA and mitochondria number were decreased in myostatin-deficient muscle, suggesting a mitochondrial depletion. Overall, our results suggest that lack of myostatin compromises force production in association with loss of oxidative characteristics of skeletal muscle.
EXTENDING LAMBDA-CALCULUS WITH UNBIND AND REBIND

We extend the simply typed λ -calculus with unbind and rebind primitive constructs. That is, a value can be a fragment of open code, which in order to be used should be explicitly rebound. This mechanism nicely coexists with standard static binding. The motivation is to provide an unifying foundation for mechanisms of dynamic scoping , where the meaning of a name is determined at runtime, re-binding , such as dynamic updating of resources and exchange of mobile code, and delegation , where an alternative action is taken if a binding is missing. Depending on the application scenario, we consider two extensions which diﬀer in the way type safety is guaranteed. The former relies on a combination of static and dynamic type checking. That is, rebind raises a dynamic error if for some variable there is no replacing term or it has the wrong type. In the latter, this error is prevented by a purely static type system, at the price of more sophisticated types.
QOS-BASED RANKING MODEL FOR WEB SERVICE SELECTION CONSIDERING USER REQUIREMENTS

Web services are widely used in the business applic ation development to achieve interoperability among standalone systems. Efficient and effective techniq ues are required to find and select required servic s among similar services which is an important task i n the service-oriented computing. Ranking process which is part of Web service discovery system helps the users to find the desired services effectively . The existing research contribution for ranking process does not consider the user’s requirements which are an important factor to rank web services. In this work , vector-based ranking method is enhanced to consid er user’s requirements. The vector-based model is sele cted because of its simplicity and high efficiency. The web services are evaluated on the basis of their si milar ty degrees to the optimal or the best values of various quality attributes. Experiments are conduct ed with real dataset and the improved algorithm is compared with the other approaches and it is found that the enhanced vector-based ranking method is efficient in terms of execution time to return the result set.
The Effect of Industry Life Cycles and Strategic Alliances on Employment Contract Modeling

This paper analyses what kind of employment contract must be offered to the manager (agent) of a company by the owner (principal) in the case of strategic alliance formation by taking into consideration their industry life cycles. Agency problem may arise between managers and principals because managers’ actions may not be intrinsically unobservable in strategic alliances. A set of proposals and models is suggested mainly based on the various levels of uncertainty prevailing in the industry. Overall, the shows that in mature stages of the industry, principals are better off by offering the contract where agents receive a fixed payment (i.e. the first best solution), whereas in growth stages agents get fixed payments with additional performance pay (i.e. the second best solution). In both cases the principals get the residual outcome.
An efficient Newton-type method for the computation of ML estimators in a uniform linear array

In the problem of estimating the angles of arrival to a uniform linear array, we present an efficient method to compute Maximum Likelihood (ML) estimations, based on the Modified Variable Projection (MVP) algorithm. In contrast to methods like Iterative Quadratical Maximum Likelihood (IQML) or the Iterative Method of Direction Estimation (IMODE), it is not based on a polynomial parameterization but on directly exploiting the Vandermonde structure through analytical tools like the Fast Fourier Transform (FFT), the geometric series summation formula, and Horner's synthetic division. The computational burden of the proposed method is significantly smaller than the burden of IMODE and of the Relaxation (RELAX) algorithm. Besides, it is shown that the computation of the ML estimation can be divided in a preliminary step in which a few FFTs are computed and an iterative step with a complexity that is independent of the array size.
Exploring the Heritage of American Higher Education: The Evolution of Philosophy and Policy. American Council on Education/Oryx Press Series on Higher Education.

1 Portraits in Diversity: The Scope of America's Investment in Higher Education 2 Purpose and Performance: The Evolution of Higher Education Mission and Goals 3 Guardians and Governance: The Culture of Decision and Authority in Academic Life 4 Competence and Conscience: The Challenges of Curriculum and Program Design 5 Performance Accountability: The Evidence of Quality 6 Forms of Finance: The Uses of Fiscal Policy 7 Student Life and Development: The Mosaic of Student Influence and Involvement 8 Faculty Role and Responsibility: The Perceptions of Professorial Performance 9 Academics and Athletics: The Arenas of Ideological and Physical Contest 10 Reform and Renewal: The Dance of Change and Tradition
"Prototypes in the mist: The early epochs of category learning": Correction to Smith and Minda (1998).

Recent ideas about category learning have favored exemplar processes over prototype processes. However, research has focused on small, poorly differentiated categories and on task-final performances—both may highlight exemplar strategies. Thus, we evaluated participants' categorization strategies and standard categorization models at successive stages in the learning of smaller, less differentiated categories and larger, more differentiated categories. In the former case, the exemplar model dominated even early in learning. In the latter case, the prototype model had a strong early advantage that gave way slowly. Alternative models, and even the behavior of individual parameters within models, suggest a psychological transition from prototype-based to exemplar-based processing during category learning and show that different category structures produce different trajectories of learning through the larger space of strategies.
A two-dimensional passive dynamic running biped with knees

This is the first study of a real physical kneed bipedal robot that exhibits passive dynamic running (PDR). Passive dynamic walking (PDW), which has its roots in the pioneering research of McGeer, intrinsically offers not only nonlinear phenomena such as the pull-in effect and period-doubling bifurcation, but also offers an extremely interesting phenomenon that facilitates the engineering of a highly efficient walking robot. In recent years, a wide variety of verification experiments in PDW were performed using actual devices. In contrast, however, very few studies addressed PDR. In the present study, we developed a two-dimensional real physical passive dynamic running biped with knees. The device stands 400 mm tall and weights 4.8 kg. By carefully designing the properties of the elastic elements implemented into the hip joints and the stance legs in the present device, we achieved stable passive dynamic running of 36 steps. The device runs at about 0.83 m/s down a 0.22 rad slope. To the best of our knowledge, this is a first report of such a performance. This result is expected to prove useful not only for designing human-like natural and efficient bipedal robots, but also for understanding the principles underlying bipedal locomotion.
Scattering of diffuse photon density waves by spherical inhomogeneities within turbid media: Analytic solution and applications

We present an analytic solution for the scattering of diffuse photon density waves by spherical inhomogeneities within turbid media. The analytic result is compared to experimental measurements. Close agreement between theory and experiment permits the use of the theory to determine the properties of unknown sphere-like objects embedded in turbid media. The analytic solution is extended to encompass several problems of practical interest in imaging, including the influence of multiple sources, multiple objects, and boundaries on the characterization of spherical inhomogeneities. We also extend the solution to encompass time-domain measurements. We present an analytic solution for the scattering of diffuse photon density waves (DPDWs) from spherical inhomogeneities
Space perception in virtual environments

Virtual reality systems commonly include both monocular and binocular depth cues, which have the potential to provide viewers with a realistic impression of spatial properties of the virtual environment. However, when multiple viewers share the same display, only one viewer typically receives the projectively correct images. All other viewers experience the same images despite displacement from the center of projection (CoP). Three experiments evaluated perceptual distortions caused by displacement from the CoP and compared those percepts to predictions of models based on monocular and binocular viewing geometry. Leftward and rightward displacement from the CoP caused virtual angles on the ground plane to be judged as larger and smaller, respectively, compared to judgments from the CoP. Backward and forward displacement caused rectangles on the ground plane to be judged as larger and smaller in depth, respectively, compared to judgments from the CoP. Judgment biases were in the same direction as cue-based model predictions but of smaller magnitude. Displacement from the CoP had asymmetric effects on perceptual judgments, unlike model predictions. Perceptual distortion occurred with monocular cues alone but was exaggerated when binocular cues were added. The results are grounded in terms of practical implications for multiuser virtual environments.
A Tabletop Projector-camera System for Remote and Nearby Pointing Operation

In this paper, we propose a pointing interface that can be easily installed and that enables remote and nearby operations with high recognition accuracy. We use a system put on a table consisting of multiple projectors and depth cameras. The system projects a shared screen and a personal screen per each user on a projection screen and on a table respectively and enables interaction according to the user's hand motion. A personal screen can be operated by touch operations and a shared screen can be operated by pointing with fingers. Touch and pointing direction are recognized from the depth image and the confidence map obtained by a depth camera. We developed an early prototype system for verification and implemented a presentation application that supports collaborative work to the system. This application allows a user to move a window between the shared screen and the personal screen and to perform various operations on the slides.
Learning Latent Factor Models of Human Travel

This paper describes probability models for human travel, using latent factors learned from data. The latent factors represent interpretable properties: travel distance cost, desirability of destinations, and affinity between locations. Individuals are clustered into distinct styles of travel. The latent factors combine in a multiplicative manner, and are learned using Maximum Likelihood. The resulting models exhibit significant improvements in predictive power over previous methods, while also using far fewer parameters than histogram-based methods. The method is demonstrated on travel data from two sources: geotags from a social image sharing site (Flickr), and GPS tracks from Shanghai taxis.
Finger cursor using gesture recognition

Since the computer is developed we are using mouse for cursor movement. In this era of touch screen devices human machine interaction is very important factor nowadays. Many devices are developed which can be operated without touching the system. So there should be any system in computer and laptop also to operate them without touching physically. So in this paper we have described new concept named `Finger Cursor'. It means operating computer's cursor using our finger's gestures. In this paper we have described methods and algorithms we have used for this system. We have described methods for color detection, image filtering, finding centroid and bounding a box to it, mouse movements and executing mouse events.
Individual Detection of Patients with Parkinson Disease using Support Vector Machine Analysis of Diffusion Tensor Imaging Data: Initial Results

BACKGROUND AND PURPOSE: Brain MR imaging is routinely performed in the work-up of suspected PD, yet its role is essentially limited to the exclusion of other pathologies. We performed a pattern-recognition analysis based on DTI data to detect subjects with PD at the individual level. MATERIALS AND METHODS: We included 40 consecutive patients with Parkinsonism suggestive of PD who had DTI at 3T, brain 123I ioflupane SPECT (DaTSCAN), and extensive neurologic testing including follow-up (17 PD: age range, 67.8 ± 6.7 years; 9 women; 23 Other: consisting of atypical forms of Parkinsonism; age range, 67.2 ± 9.7 years; 7 women). Data analysis included group-level TBSS and individual-level SVM classification. RESULTS: At the group level, patients with PD versus Other had spatially consistent increase in FA and decrease in RD and MD in a bilateral network, predominantly in the right frontal white matter. At the individual level, SVM correctly classified patients with PD at the individual level with accuracies up to 97%. CONCLUSIONS: Support vector machine–based pattern recognition of DTI data provides highly accurate detection of patients with PD among those with suspected PD at an individual level, which is potentially clinically applicable. Because most suspected subjects with PD undergo brain MR imaging, already existing MR imaging data may be reused; this practice is very cost-efficient.
Ontology-Based Expertise Locator

Large amount of experts are key asset that universities hold. In order to increase people's awareness of experts and foster collaborative opportunities, it is necessary to help users to locate experts with required expertise. This paper proposes a methodology for ontology-based expertise locator, a Semantic Web application that integrates pieces of relevant expertise information from heterogeneous data sources. We present the integration processes and ranking algorithm based on voting technique. Tests on the prototype system demonstrate that our system provides better performance on MAP and precision.