Miracle-dz/UniFAR-FTUs huggingface dataset:
Tele-Operation between Human and Robot Arm Using Wearable Electronic Device

Abstract In this paper, a wearable-type motion capturing system is designed and implemented. The device consists of flex sensors, photo detector and luminous element, AVR microcontroller and Bluetooth modules. It can transmit the motion capture data to host computer and then the computer calculates desired degrees for operating the slave robot. As a counterpart of the wearable system, it could be easily wearable, portable and is built to send the human motion data wirelessly. And it has no limitation to detect the human motion because the device capture human's motion directly unlikely motion capture camera using markers which isn't able to detect to their the locations frequently. The proposed system through the wearable device to control the robot arms can show feasible application of wireless man-machine interface and can be applicable various types.
Enhancing interaction with supplementary supportive user interfaces (UIs): meta-UIs, mega-UIs, extra-UIs, supra-UIs . . .

In order to improve the interaction control and intelligibility, end-user applications are supplemented with Supportive User Interfaces (SUI), like meta-UIs, mega-UIs, helping or configuration wizards. These additional UIs support the users by providing them with information about the available functionalities, the context of use, or the performed adaptations. Such UIs allow the user to supervise and modify an application interactive behavior according to her/his needs. Given the rising complexity of interactive systems, supportive UIs are highly desirable features. However, there is currently no common understanding of types and roles of supportive UIs. Enabling concepts and definitions underlying the engineering of such UIs are also missing. In order to fill this gap, the workshop seeks a discussion with a broad audience of researchers, who have experience with the design and development of supportive UIs.
Webhouse to support web intelligence in e-learning environments

The amazing usage of internet as a communication channel has changed the very structure of companies activities, being education a clear example of this situation. Though data mining has been successfully used to improve the 1-to-1 relationship in e-commerce sites, when applied to elearning environments the results are often limited to provide the educator with access summary information or primitive patterns. In any case, information being obtained is not being used proactively. For enviroments to profit from the information obtained it has to be integrated in a global infrastructure. This paper presents the design of a data e-learning web-house as supporting structure for future e-learning personalized systems.
Simulations of superhumps and superoutbursts

ABSTRA C T We numerically study the tidal instability of accretion discs in close binary systems using a two-dimensional SPH code. We find that the precession rate of tidally unstable, eccentric discs does not only depend upon the binary mass ratio q. Although the (prograde) disc precession rate increases with the strength of the tidal potential, we find that increasing the shear viscosity n also has a significant prograde effect. Increasing the disc temperature has a retrograde impact upon the precession rate. We find that motion relative to the binary potential results in superhump-like, periodic luminosity variations in the outer reaches of an eccentric disc. The nature and location of the luminosity modulation are functions of n. Light curves most similar to observations are obtained for n values appropriate for a dwarf nova in outburst. We investigate the thermal‐tidal instability model for superoutburst. A dwarf nova outburst is simulated by instantaneously increasing n, which causes a rapid radial expansion of the disc. Should the disc encounter the 3: 1 eccentric inner Lindblad resonance and become tidally unstable, then tidal torques become much more efficient at removing angular momentum from the disc. The disc then shrinks and ˙ Md increases. The resulting increase in disc luminosity is found to be consistent with the excess luminosity of a superoutburst.
Two New Rapid SNP-Typing Methods for Classifying Mycobacterium tuberculosis Complex into the Main Phylogenetic Lineages

There is increasing evidence that strain variation in Mycobacterium tuberculosis complex (MTBC) might influence the outcome of tuberculosis infection and disease. To assess genotype-phenotype associations, phylogenetically robust molecular markers and appropriate genotyping tools are required. Most current genotyping methods for MTBC are based on mobile or repetitive DNA elements. Because these elements are prone to convergent evolution, the corresponding genotyping techniques are suboptimal for phylogenetic studies and strain classification. By contrast, single nucleotide polymorphisms (SNP) are ideal markers for classifying MTBC into phylogenetic lineages, as they exhibit very low degrees of homoplasy. In this study, we developed two complementary SNP-based genotyping methods to classify strains into the six main human-associated lineages of MTBC, the “Beijing” sublineage, and the clade comprising Mycobacterium bovis and Mycobacterium caprae. Phylogenetically informative SNPs were obtained from 22 MTBC whole-genome sequences. The first assay, referred to as MOL-PCR, is a ligation-dependent PCR with signal detection by fluorescent microspheres and a Luminex flow cytometer, which simultaneously interrogates eight SNPs. The second assay is based on six individual TaqMan real-time PCR assays for singleplex SNP-typing. We compared MOL-PCR and TaqMan results in two panels of clinical MTBC isolates. Both methods agreed fully when assigning 36 well-characterized strains into the main phylogenetic lineages. The sensitivity in allele-calling was 98.6% and 98.8% for MOL-PCR and TaqMan, respectively. Typing of an additional panel of 78 unknown clinical isolates revealed 99.2% and 100% sensitivity in allele-calling, respectively, and 100% agreement in lineage assignment between both methods. While MOL-PCR and TaqMan are both highly sensitive and specific, MOL-PCR is ideal for classification of isolates with no previous information, whereas TaqMan is faster for confirmation. Furthermore, both methods are rapid, flexible and comparably inexpensive.
Approximation Schemes for Geometric Coverage Problems

In their seminal work, Mustafa and Ray (2009) showed that a wide class of geometric set cover (SC) problems admit a PTAS via local search -- this is one of the most general approaches known for such problems. Their result applies if a naturally defined "exchange graph" for two feasible solutions is planar and is based on subdividing this graph via a planar separator theorem due to Frederickson (1987). Obtaining similar results for the related maximum k-coverage problem (MC) seems non-trivial due to the hard cardinality constraint. In fact, while Badanidiyuru, Kleinberg, and Lee (2012) have shown (via a different analysis) that local search yields a PTAS for two-dimensional real halfspaces, they only conjectured that the same holds true for dimension three. Interestingly, at this point it was already known that local search provides a PTAS for the corresponding set cover case and this followed directly from the approach of Mustafa and Ray. In this work we provide a way to address the above-mentioned issue. First, we propose a color-balanced version of the planar separator theorem. The resulting subdivision approximates locally in each part the global distribution of the colors. Second, we show how this roughly balanced subdivision can be employed in a more careful analysis to strictly obey the hard cardinality constraint. More specifically, we obtain a PTAS for any "planarizable" instance of MC and thus essentially for all cases where the corresponding SC instance can be tackled via the approach of Mustafa and Ray. As a corollary, we confirm the conjecture of Badanidiyuru, Kleinberg, and Lee regarding real half spaces in dimension three. We feel that our ideas could also be helpful in other geometric settings involving a cardinality constraint.
Towards journalometrical analysis of a scientific periodical: a case study

In this paper we use several approaches to analyse a scientific journal as a complex system and to make a possibly more complete description of its current state and evolution. Methods of complex networks theory, statistics, and queueing theory are used in this study. As a subject of the analysis we have chosen the journal ``Condensed Matter Physics'' (this http URL). In particular, based on the statistical data regarding the papers published in this journal since its foundation in 1993 up to now we have composed the co-authorship network and extracted its main quantitative characteristics. Further, we analyse the priorities of scientific trends reflected in the journal and its impact on the publications in other editions (the citation ratings). Moreover, to characterize an efficiency of the paper processing, we study the time dynamics of editorial processing in terms of queueing theory and human activity analysis.
Review: An urgent need for research on factors impacting adherence to and retention in care among HIV-positive youth and adolescents from key populations

The 50% increase in HIV‐related deaths in youth and adolescents (aged 10–24) from 2005 to 2012 highlights the need to improve HIV treatment and care in this population, including treatment adherence and retention. Youth and adolescents from key populations or young key populations (YKP) in particular are highly stigmatized and may face additional barrier(s) in adhering to HIV treatment and services. We reviewed the current knowledge on treatment adherence and retention in HIV care among YKP to identify gaps in the literature and suggest future directions to improve HIV care for YKP.
Spatio-Temporal Mask Learning : Application to Speech

In this paper, we describe the spatio-temporall map which is an original algorithm to learn and recognize dynamic patterns represented by sequences. This work is slanted toward an internal and explicit representation of time which seems to be neuro-biologically relevant. The map involves units with diierent kinds of links: feed-forward connections, intra-map connections and inter-map connections. This architecture is able to learn sequences robust to noise from an input stream. The learning process is self-organized for the feed-forward links and pseudoo self-organized for the intra-map links. An application to French spoken digits recognition is presented.
Reflective Approach for Software Design Decision Making

Good software design practice is difficult to define and teach. Despite the many software design methods and processes that are available, the quality of software design relies on human factors. We notice from literature and our own experiments that some of these factors concern design reasoning and reflection. In this paper, we propose a reflective approach to software design decision making. The approach is built upon Two-Minds model and is enabled by a set of problem-generic reflective questions. We illustrate its usefulness in design sessions with an example taken from preliminary experimentation.
Dependable performance analysis for fuzzy clustering of web usage data

Fuzzy clustering is a popular method for modeling web usage data, and a number of techniques have been proposed. Performance of such techniques has been demonstrated through experiments using datasets which are often limited in the size and/or variety. This is mainly due to the difficulty in acquiring large real data, and also to the huge amount of time and effort required in performing experiments. We investigate ways to ensure dependability of such results and their analyses. For this we consider three issues. First we need to ensure that the clustering quality indices used for comparing different techniques are not biased towards any parameter specific to any of them. Second, more ground truth is provided by measuring the quality through an application of the usage model than through the clustering quality index alone. Third, given the limited data sets and experiments, use of statistical significance testing can provide more confidence in that the results obtained are not by mere chance. We present our approach for dependable performance analysis using some well-known fuzzy clustering techniques along with prediction quality used as the application specific metric.
1 1 1 Fe b 20 02 Density Matrix Renormalisation Group Approach to the Massive Schwinger Model

The massive Schwinger model is studied, using a density matrix renormalisation group approach to the staggered lattice Hamiltonian version of the model. Lattice sizes up to 256 sites are calculated, and the estimates in the continuum limit are almost two orders of magnitude more accurate than previous calculations. Coleman’s picture of ‘half-asymptotic’ particles at background field θ = π is confirmed. The predicted phase transition at finite fermion mass (m/g) is accurately located, and demonstrated to belong in the 2D Ising universality class. PACS Indices: 12.20. -m, 11.15. Ha Typeset using REVTEX 1
Ore grade estimation of a limestone deposit in India using an Artificial Neural Network

This study describes a method used to improve ore grade estimation in a limestone deposit in India. Ore grade estimation for the limestone deposit was complicated by the complex lithological structure of the deposit. The erratic nature of the deposit and the unavailability of adequate samples for each of the lithogical units made standard geostatistical methods of capturing the spatial variation of the deposit inadequate. This paper describes an attempt to improve the ore grade estimation through the use of a feed forward neural network (NN) model. The NN model incorporated the spatial location as well as the lithological information for modeling of the ore body. The network was made up of three layers: an input, an output and a hidden layer. The input layer consisted of three spatial coordinates (x, y and z) and nine lithotypes. The output layer comprised all the grade attributes of limestone ore including silica (SiO2), alumina (Al2O3), calcium oxide (CaO) and ferrous oxide (Fe2O3). To justify the use of the NN in the deposit, a comparative evaluation between the NN method and the ordinary kriging was performed. This evaluation demonstrated that the NN model decisively outperformed the kriging model. After the superiority of the NN model had been established, it was used to predict the grades at an unknown grid location. Prior to constructing the grade maps, lithological maps of the deposit at the unknown grid were prepared. These lithological maps were generated using indicator kriging. The authors conclude by suggesting that the method described in this paper could be used for grade-control planning in ore deposits.
OPTIMAL RATE CONTROL FOR HIGH SPEEDTELECOMMUNICATION NETWORKSEitan

We present in this paper two approaches for designing controllers that dynamically regulate the rate of data ow into a network based on feedback state information. They result in controllers that are similar to ones that have been advocated for both end-to-end and hop-by-hop congestion control in high-speed networks. Many existing control protocols have been developed on growing available experience, using ad-hoc techniques that did not come as a result of a control-theoretical study. This is due to the high complexity of the controlled systems, that are typically decentralized , have non-linear dynamics, and may only use partial noisy delayed information. Some attempts have been made in recent years to use control theory to design ow controllers with, however, no explicit objective functions to be minimized; moreover, the class of control policies in existing theoretical work is quite restricted. In this paper we formulate explicitly some cost criteria to be minimized, related to performance measures such as delays, through-puts and loss probabilities. Using a linearized model, we then view the design problem as an optimal control problem. We follow two approaches to model interfering traac and other unknown data: the H 1 approach, and the LQG one; and determine for both cases the optimal controllers. Some simulation results complete the study.
Million-Atom Count Simulations of the Effects of Carbon Nanotube Length Distributions on Fiber Mechanical Properties

The extraordinary mechanical properties of carbon nanotubes (CNTs) make them prime candidates as a basis for super infrastructure materials. Ab initio, tight binding, and molecular dynamics simulations and recent experiments have shown that CNTs have tensile strengths up to about 15.5 million psi (110 GPa), Young’s modulus of 150 million psi (1 TPa), and density of about 80 lbs/ft3 (1.3 g/cm3). These qualities provide tensile strength-toweight and stiffness-to-weight ratios about 900 times and 30 times, respectively, those of high-strength (100,000- psi) steel. Building macromaterials that maintain these properties is challenging. Molecular defects, voids, foreign inclusions, and, in particular, weak intermolecular bonds have, to date, prevented macromaterials formed from CNTs from having the remarkable strength and stiffness characteristics of CNTs. The van der Waals forces associated with CNTsrepresent a force per unit length between CNTs. Accordingly, one would expect the bond strength between aligned CNTs to increase with overlap length. Real filaments are likely composed of CNTs with some distribution of lengths. To understand the effects that CNT length distributions have on the tensile strength of neat filaments of aligned CNTs, we performed a series of quenched molecular dynamics simulations on high performance computers using Sandia Laboratory’s Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) code. The cross-section of each filament was composed of hexagonal closest-packed (HCP) array CNT strands that formed two HCP rings. The filaments were constructed by placing (5,5) chirality CNTs end to end. While the choice of a single-chirality CNT fiber is currently unrealizable, the use of a singlechirality fiber allowed us to focus only on the effects of CNT lengths on filament response. The lengths of the CNTs were randomly selected to have Gaussian distribution with the average length ranging from 100 to 1,600Å. A series of simulations were performed on filament with lengths ranging from 400 to 6,400Å. For each filament, the strain was increased in small increments and quenched between strain increments. The total tensile force on the filament was recorded and used to determine the uniaxial stress-strain response of the filaments. The results of the simulations quantified the improvements in Young’s modulus, tensile strength, and critical strain as a function of the increase in the average component CNT lengths. These are the first molecular dynamics simulations that the authors are aware of that treat statistical qualities of realistic CNT structures. The simulation results are being used to guide the molecular design of CNT filaments to achieve super (1 million psi) strength. The simulations would be impractical, and perhaps impossible, without massively parallel, highperformance computational platforms and molecular dynamics simulation tools optimized to run on such platforms.
Bronchial Artery Embolization for Hemoptysis: A Retrospective Observational Study of 344 Patients

Background: Hemoptysis is a significant clinical entity with high morbidity and potential mortality. Both medical management (in terms of resuscitation and bronchoscopic interventions) and surgery have severe limitations in these patients population. Bronchial artery embolization (BAE) represents the first-line treatment for hemoptysis. This article discusses clinical analysis, embolization approach, outcomes and complications of BAE for the treatment of hemoptysis. Methods: A retrospective analysis of 344 cases, who underwent bronchial arteriography at Tianjin Haihe Hospital between 2006 and 2013. Several aspects of outcome were analyzed: Demographics, clinical presentation, radiographic studies, results, complications and follow-up of BAE. Results: Three hundred and forty-four consecutive patients underwent bronchial arteriography, 336 of 344 patients (97.7%) performed BAE; there were 1530 coils for 920 arteries embolized; the main responsible sources for bleeding were right bronchial artery (29.7%), left bronchial artery (21.6%), combined right and left bronchial trunk (18.4%), right intercostal arteries (13.3%); 61 patients (17.7%) had recurrent hemoptysis within 1 month after undergoing BAE, 74 patients (21.5%) had recurrent hemoptysis over 1 month after undergoing BAE; The common complications of BAE included subintimal dissection, arterial perforation by a guide wire, fever, chest pain, dyspnea, etc. The follow-up was completed in 248 patients, 28 patients had been dead, 21 patients still bleed, 92 patients had lost to follow-up. Conclusions: The technique of BAE is a relatively safe and effective method for controlling hemoptysis. The complications of BAE are rare. Although the long-term outcome in some patients is not good, BAE may be the only life-saving treatment option in patients who are poor surgical candidates.
For Peer Review Analysis of Scalability in Population-based Evolutionary Algorithms for Linear-like Fitness Functions

An important feature of evolutionary algor ithms (EAs) is their scalability, i.e. the per formance of a populationbased EA may be improved through increasing the population size. However scalability may be lost if the population size grows over a threshold, called thecut-off point. A cr itical question about scalability is: where is the cut-off point? Although exper imental study could be carr ied out to answer this question, the answer is restr icted to small input sizes and population sizes. Theoretical analysis, albeit difficult to do, is necessary in answer ing this question. This paper takes linear-like functions as a case study. The main result is that tight lower and upper bounds on the first hitting time have been der ived for the (N+N) EA using bitwise mutation, elitist selection, with or without uniform crossover. Then the cut-off point is drawn from these bounds. This gives an exact descr iption of the relationship between the population size and the first hitting time. I t is also proven that the lower bound on the fist hitting time can be attained by the (N + N) EA with a problem-specific implementation.
Improving collocation extraction by using syntactic patterns

A study on using syntactic patterns to improve window-based collocation extraction systems is presented. The support collocation patterns and reject collocation patterns retrieved from a chunked corpus and are used in two different strategies. The first strategy uses only the support patterns in preprocessing stage whereas the second strategy incorporates both the support and the reject patterns into the existing systems. Experimental results show that the use of syntactic patterns can significantly improve the performance of collocation extraction especially for filtering out pseudo collocations and the extraction of low-occurrence collocations.