Miracle-dz/UniFAR-FTUs huggingface dataset:
Human gait capture by tracking joint motion based on Kalman Filter

Human gait capture by vision plays an important role in the guidance for the rehabilitation of the lower limbs dysfunction patients. Unfortunately, it is not included in most of the present rehabilitation devices. This paper presents a novel real-time system for human gait capture by detecting the joints trajectory to obtain 3-D information of the joints motion by Kinect. Firstly, we put markers on the joints of each leg and detect them in a way combined background subtraction and multi-object template matching. Secondly, we estimate the potential regions in next frame by using Kalman Filter with current knowledge of the detected markers captured in the Kinect frame. Thirdly, we determine the position of markers within the potential region within the depth information. Finally, we accomplish gait capture by iteratively applying the estimation and detection method in a consecutive sequence of frames. This system achieves good tracking result and gait information at a frame rate of 30fps with a resolution of 640x480.
Omni-Directional Scanning Localization Method of a Mobile Robot Based on Ultrasonic Sensors

Improved ranging accuracy is obtained by the development of a novel ultrasonic sensor ranging algorithm, unlike the conventional ranging algorithm, which considers the divergence angle and the incidence angle of the ultrasonic sensor synchronously. An ultrasonic sensor scanning method is developed based on this algorithm for the recognition of an inclined plate and to obtain the localization of the ultrasonic sensor relative to the inclined plate reference frame. The ultrasonic sensor scanning method is then leveraged for the omni-directional localization of a mobile robot, where the ultrasonic sensors are installed on a mobile robot and follow the spin of the robot, the inclined plate is recognized and the position and posture of the robot are acquired with respect to the coordinate system of the inclined plate, realizing the localization of the robot. Finally, the localization method is implemented into an omni-directional scanning localization experiment with the independently researched and developed mobile robot. Localization accuracies of up to ±3.33 mm for the front, up to ±6.21 for the lateral and up to ±0.20° for the posture are obtained, verifying the correctness and effectiveness of the proposed localization method.
CN Tower Lightning Return-Stroke Current Simulation

Different functions have been used to model the lightning return-stroke current with the aid of direct current measurements at tall structures. In this paper, a comparison between the Pulse function and Heilder function is carried out to find out the suitability of each of these functions for simulating the lightning return-stroke current, measured at the CN Tower. An automated system for determining the CN Tower lightning return-stroke current waveform parameters is introduced. The curve fitting technique of this system and the estimation of the initial values of the simulation function parameters are presented. An artificial lightning signal, free of noise and reflections, is used as a reference signal for evaluating the parameter extraction system. Finally, cumulative statistics of the CN Tower lightning return-stroke current waveform parameters (peak, maximum rate of rise, risetime, pulse width, decay time and charge) are derived using the Pulse function parameters.
A high-resolution scheme of TVD type for the Aw-Rascle-Greenberg model of traffic flow

An approximate Riemann solver for the Aw-Rascle traffic flow model and the extension of Greenberg is constructed on the algebraic level. A discrete diffusion operator is added to the (oscillatory) high-order finite difference/element discretization to enforce a vectorial LED criterion. This yields a nonoscillatory but diffusive low-order scheme. To increase the accuracy an antidiffusion operator is added. The amount of antidiffusion is controlled using TVD flux limiters. Practical algorithms are presented for the derivation of the low-order scheme, construction of the antidiffusion operator, and the solution of the arising nonlinear algebraic system. Another option considered in this paper is based on a segregated treatment of the equations at hand. It is shown that scalar upwinding/limiting techniques are inappropriate, since even the low-order scheme produces oscillatory solutions to the coupled AR model, although it is monotone for each single equation. Hence, the strongly coupled algorithm developed in this paper yields superior results, as demonstrated by numerical examples.
Detection of coral distribution change in recent decades with satellite remote sensing

Coral reef is a very important ecosystem in Sanya Bay and it has been studied for years only with in situ observations. However, these in situ observations generally have point information and lack the spatial resolution. Recently in order to make clear coral reef spatial distribution and variation in Sanya Bay, Hainan, satellite data of Landsat, QuickBird, CBERS (China-Brazil Earth Resources Satellite program) and historical in situ observation data are used to retrieve and validate the information of coral reef. Based on the retrieved information, coral reef coverage and variation were studied in the paper. Satellite remote sensing results showed that area of coral reef distribution along coast of Dongmao (east) Islands and Ximao (west) islands in Sanya Bay reduced greatly in recent years, which coincides with variation trends of in situ observation data in the whole Sanya Bay. While analyzing the reason for coral reduction it was found that coral distribution in Sanya Bay conversely correlated with anthropic activities, such as digging coral reef for making lime and land use change. These activities change the water quality and sediment type which lead to the change in coral distribution.
Ucl Ssees Centre for Comparative Economics Which Institutions Encourage Entrepreneurial Growth Aspirations? Which Institutions Encourage Entrepreneurial Growth Aspirations?

We develop entrepreneurship and institutional theory to explain entrepreneurial growth aspirations across individuals and institutional contexts. Our framework generates hypotheses at the national level about the negative impact of higher levels of corruption, weaker property rights and greater government activity on entrepreneurs " aspirations to increase employment. Also we explore whether, at the micro level, knowing other entrepreneurs compensates for weaknesses in institutions. We test these hypotheses using the Global Entrepreneurship Monitor surveys in 42 countries for 2001-2006, applying a multilevel estimation framework. We find support for our main hypotheses but intellectual property rights are found to have no explanatory power.
THE ACS SURVEY OF GALACTIC GLOBULAR CLUSTERS. XI. THE THREE-DIMENSIONAL ORIENTATION OF THE SAGITTARIUS DWARF SPHEROIDAL GALAXY AND ITS GLOBULAR CLUSTERS

We use observations from the Hubble Space Telescope Advanced Camera for Surveys (HST/ACS) study of Galactic globular clusters to investigate the spatial distribution of the inner regions of the disrupting Sagittarius dwarf spheroidal galaxy (Sgr). We combine previously published analyses of four Sgr member clusters located near or in the Sgr core (M54, Arp 2, Terzan 7, and Terzan 8) with a new analysis of diffuse Sgr material identified in the background of five low-latitude Galactic bulge clusters (NGC 6624, 6637, 6652, 6681, and 6809) observed as part of the ACS survey. By comparing the bulge cluster color–magnitude diagrams to our previous analysis of the M54/Sgr core, we estimate distances to these background features. The combined data from four Sgr member clusters and five Sgr background features provide nine independent measures of the Sgr distance and, as a group, provide uniformly measured and calibrated probes of different parts of the inner regions of Sgr spanning 20° over the face of the disrupting dwarf. This allows us, for the first time, to constrain the three-dimensional orientation of Sgr's disrupting core and globular cluster system and compare that orientation to the predictions of an N-body model of tidal disruption. The density and distance of Sgr debris are consistent with models that favor a relatively high Sgr core mass and a slightly greater distance (28–30 kpc, with a mean of 29.4 kpc). Our analysis also suggests that M54 is in the foreground of Sgr by ∼2 kpc, projected on the center of the Sgr dSph. While this would imply a remarkable alignment of the cluster and the Sgr nucleus along the line of sight, we cannot identify any systematic effect in our analysis that would falsely create the measured 2 kpc separation. Finally, we find that the cluster Terzan 7 has the most discrepant distance (25 kpc) among the four Sgr core clusters, which may suggest a different dynamical history than the other Sgr core clusters.
A Meta-heuristically Approach of the Spatial Assignment Problem of Human Resources in Multi-sites Enterprise

The aim of this work is to present a meta-heuristically approach of the spatial assignment problem of human resources in multi-sites enterprise. Usually, this problem consists to move employees from one site to another based on one or more criteria. Our goal in this new approach is to improve the quality of service and performance of all sites with maximizing an objective function under some managers imposed constraints. The formulation presented here of this problem coincides perfectly with a Combinatorial Optimization Problem (COP) which is in the most cases NP-hard to solve optimally. To avoid this difficulty, we have opted to use a meta-heuristic popular method, which is the genetic algorithm, to solve this problem in concrete cases. The results obtained have shown the effectiveness of our approach, which remains until now very costly in time. But the reduction of the time can be obtained by different ways that we plan to do in the next work.
Emphysema as a Risk Factor for the Outcome of Surgical Resection of Lung Cancer

It is unclear whether emphysema, regardless of airflow limitation, is a predictive factor associated with survival after lung cancer resection. Therefore, we investigated whether emphysema was a risk factor associated with the outcome after resection for lung cancer. This study enrolled 237 patients with non small cell lung cancer with stage I or II who had surgical removal. Patient outcome was analyzed based on emphysema. Emphysema was found in 43.4% of all patients. Patients with emphysema were predominantly men and smokers, and had a lower body mass index than the patients without emphysema. The patients without emphysema (n=133) survived longer (mean 51.2±3.0 vs. 40.6±3.1 months, P=0.042) than those with emphysema (n=104). The univariate analysis showed a younger age, higher FEV1/FVC, higher body mass index, cancer stage I, and a lower emphysema score were significant predictors of better survival. The multivariate analysis revealed a younger age, higher body mass index, and cancer stage I were independent parameters associated with better survival, however, emphysema was not. This study suggests that unfavorable outcomes after surgical resection of lung cancer should not be attributed to emphysema itself.
Maps, sheaves, and K3 surfaces

The conjectural equivalence of curve counting on Calabi-Yau 3-folds via stable maps and stable pairs is discussed. By considering Calabi-Yau 3-folds with K3 fibrations, the correspondence naturally connects curve and sheaf counting on K3 surfaces. New results and conjectures (with D. Maulik) about descendent integration on K3 surfaces are announced. The recent proof of the Yau-Zaslow conjecture is surveyed. The paper accompanies my lecture at the Clay research conference in Cambridge, MA in May 2008.
A Multi-Role Collaborative Method and Platform for Developing Software Requirements

In general, software development consists of requirements analysis, system analysis, system design, implementation, and testing. Among these phases, requirements analysis plays an important role during the software development. How to capture customer’s desired requirements precisely is a great challenge. Many efforts have been made in the area of requirements engineering. The most used approach is using goaloriented approach to capture, analyze, and elaborate requirements. However, few efforts have been invested to investigate software requirements development by a group of team members. In this paper, we present a collaborative method and process to develop software requirements on a network-based collaborative platform. There are multi-roles and each of the roles performs a number of tasks of requirements writing, reviewing, and commenting at the same time on the network-based environment. Different roles are in charge of different tasks. Based on the collaborative method, a number of role relationships are proposed. In order to achieve the purpose of collaborative working, the platform provides several collaborative services to satisfy the need of developing requirements of a software system. All users carry out their work through different collaborative patterns. After all stakeholders finish their authoring of requirements, the integrated software requirements document will be generated.
Iwssip 2010 -17th International Conference on Systems, Signals and Image Processing Time Delayed Independent Component Analysis for Data Quality Monitoring

— In the information era, databases in companies and research centers are getting larger, which makes the quality of data a key issue. In this paper, time delayed independent component analysis is used for data quality monitoring of electric load time series. The independent component analysis (ICA) was applied in the preprocessing phase, which increased the data quality system performance. The extraction of signal sources reduced the forecast error, revealed relevant information and narrowed the validation corridor width.
Information Visualization in Facility Location and Vehicle Routing Decisions

Facility location and vehicle routing are amongst the most important logistic decisions in today’s organizations. These aspects are intertwined and, in some cases, should be addressed in an integrated way (giving rise to the location-routing approach). A decision support tool that can make easier the visualization (and editing) of information regarding these problems is becoming increasingly important as: it enables to further understand the problem at hand; and, at the same time, it fosters better communication of the decisions in a way easier to understand by the general public. This paper presents some concepts for information visualization on the problems arisen by the aforementioned decisions, which have been incorporated in a decision support tool and tested using usability evaluation methods.
On the use of autocorrelation analysis for pitch detection

One of the most time honored methods of detecting pitch is to use some type of autocorrelation analysis on speech which has been appropriately preprocessed. The goal of the speech preprocessing in most systems is to whiten, or spectrally flatten, the signal so as to eliminate the effects of the vocal tract spectrum on the detailed shape of the resulting autocorrelation function. The purpose of this paper is to present some results on several types of (nonlinear) preprocessing which can be used to effectively spectrally flatten the speech signal The types of nonlinearities which are considered are classified by a non-linear input-output quantizer characteristic. By appropriate adjustment of the quantizer threshold levels, both the ordinary (linear) autocorrelation analysis, and the center clipping-peak clipping autocorrelation of Dubnowski et al. [1] can be obtained. Results are presented to demonstrate the degree of spectrum flattening obtained using these methods. Each of the proposed methods was tested on several of the utterances used in a recent pitch detector comparison study by Rabiner et al. [2] Results of this comparison are included in this paper. One final topic which is discussed in this paper is an algorithm for adaptively choosing a frame size for an autocorrelation pitch analysis.
Spam detection with a content-based random-walk algorithm

In this work we tackle the problem of the spam detection on the Web. Spam web pages have become a problem for Web search engines, due to the negative effects that this phenomenon can cause in their retrieval results. Our approach is based on a random-walk algorithm that obtains a ranking of pages according to their relevance and their spam likelihood. We introduce the novelty of taking into account the content of the web pages to characterize the web graph and to obtain an a-priori estimation of the spam likekihood of the web pages. Our graph-based algorithm computes two scores for each node in the graph. Intuitively, these values represent how bad or good (spam-like or not) is a web page, according to its textual content and the relations in the graph. Our experiments show that our proposed technique outperforms other link-based techniques for spam detection.
Violence in Japanese Television Commercials: Application of the NTVS Coding System to Commercial Analysis

In this paper, a content analysis of 7,599 Japanese TV commercials was conducted to examine the characteristics of commercials that showed violence and violent behaviour. By applying the National Television Violence Study (NTVS) method (Smith et al., 1998), we modified coding items for the content analysis. The results showed that 4.51 percent of the examined commercials contained violent behaviour. These were often aired in the late evening and morning, and found in animation programmes and movies. As for the types of products in the commercials, they are mostly advertisements for video games, music, movies and TV programmes. The commercials also contained elements such as the means and realism of violent behaviour that promote the learning of aggression from the perspective of social learning theory. We discuss the possibility of applying the NTVS coding system to commercial analysis.
Building a computer Mahjong player based on Monte Carlo simulation and opponent models

Predicting opponents' moves and hidden states is important in imperfect information games. This paper describes a method for building a Mahjong program that models opponent players and performs Monte Carlo simulation with the models. We decompose an opponent's play into three elements, namely, waiting, winning tiles, and winning scores, and train prediction models for those elements using game records of expert human players. Opponents' moves in the Monte Carlo simulations are determined based on the probability distributions of the opponent models. We have evaluated the playing strength of the resulting program on a popular online Mahjong site “Tenhou”. The program has achieved a rating of 1718, which is significantly higher than that of the average human player.
Instrumental systematics and weak gravitational lensing

We present a pedagogical review of the weak gravitational lensing measurement process and its connection to major scientific questions such as dark matter and dark energy. Then we describe common ways of parametrizing systematic errors and understanding how they affect weak lensing measurements. Finally, we discuss several instrumental systematics and how they fit into this context, and conclude with some future perspective on how progress can be made in understanding the impact of instrumental systematics on weak lensing measurements.
Phosphorylation by Rho Kinase Regulates CRMP-2 Activity in Growth Cones

ABSTRACT Collapsin response mediator protein 2 (CRMP-2) enhances the advance of growth cones by regulating microtubule assembly and Numb-mediated endocytosis. We previously showed that Rho kinase phosphorylates CRMP-2 during growth cone collapse; however, the roles of phosphorylated CRMP-2 in growth cone collapse remain to be clarified. Here, we report that CRMP-2 phosphorylation by Rho kinase cancels the binding activity to the tubulin dimer, microtubules, or Numb. CRMP-2 binds to actin, but its binding is not affected by phosphorylation. Electron microscopy revealed that CRMP-2 localizes on microtubules, clathrin-coated pits, and actin filaments in dorsal root ganglion neuron growth cones, while phosphorylated CRMP-2 localizes only on actin filaments. The phosphomimic mutant of CRMP-2 has a weakened ability to enhance neurite elongation. Furthermore, ephrin-A5 induces phosphorylation of CRMP-2 via Rho kinase during growth cone collapse. Taken together, these results suggest that Rho kinase phosphorylates CRMP-2, and inactivates the ability of CRMP-2 to promote microtubule assembly and Numb-mediated endocytosis, during growth cone collapse.
From software product lines to system of systems: Analysis of an evolution path

Software Product Line (SPL) refers to engineering methods and techniques able to deliver families of related products designed to meet domain-specific requirements and increase software reuse. System of Systems (SoS) is a composition of independent and interoperable systems intended to achieve unique goals collectively. In this paper, we discuss about conventional SPL approaches and the reasons why they commonly are not a natural choice for delivering SoS members. Then, we propose an evolution path for SPL Engineering (SPLE) to narrow the gap between SPL and SoS. Finally, we present a case study in which we designed a sample SoS by composing systems instantiated from SPL.
Vector field contours

We describe an approach to define contours of 3D vector fields and employ them as an interactive flow visualization tool. Although contours are well-defined and commonly used for surfaces and 3D scalar fields, they have no straightforward extension in vector fields. Our approach is to extract and visualize specific stream lines which show the most similar behavior to contours on surfaces. This way, the vector field contours are a particular set of isolated stream line segments that depend on the view direction and few additional parameters. We present an analysis of the usefulness of vector field contours by demonstrating their application to linear vector fields. In order to achieve interactive visualization, we develop an efficient GPU-based implementation for real-time extraction and rendering of vector field contours. We show the potential of our approach by applying it to a number of example data sets.