Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulation and Experimentation of Walking of the Bioloid Humanoid Robot

An experimental study of walking of the Bioloid humanoid is presented in this paper. The studied walking pattern is based on cycloidal motions of the hip and the free foot. The parameters for these motions are found by testing in simulation, under a criterion of stability of walking. The trajectory planning process is carried out by applying the software developed for kinematic analysis and programming of the robot’s motions. The results show that the proposed cycloidal motions give an efficient and stable walking of the robot. The supplementary software used in our study is also described, which was developed in Matlab©. By applying it, the user specifies the walking parameters and computes the joint trajectories of the robot. Furthermore, this software controls the real time walking of the robot.
Characteristics of the Temporal Behavior of Entanglement between Photonic Binomial Distributions and a Two-Level Atom in a Damping Cavity

In the present study, temporal behavior of entanglement between photonic binomial distributions and a two-level atom in a leaky cavity, in equilibrium with the environment at a temperature T, is studied. In this regard, the master equation is solved in the secular approximation for the density matrix, when the initial photonic distribution is binomial, while the atomic states obey the Boltzmann distribution. The atom-photon density matrix so calculated is then used to compute the negativity, as a measure of entanglement. The behavior of atom-photon entanglement is, consequently, determined as a function of time and temperature. To justify the behavior of atom-photon entanglement, moreover, we employ the total density matrix to compute and analyze the time evolution of the initial photonic binomial probability distribution. Our results, along with representative figures reveal that the atomphoton degree of entanglement exhibits oscillations while decaying with time and asymptotically vanishes. It is further demonstrated that an increase in the temperature gives rise to a decrease in the entanglement. The finer characteristics of the temporal behavior of the corresponding probability distribution and, consequently, the atom-photon entanglement is also given and discussed.
Hybrid RANS/LES of Turbulent forced convectionflow over tandem square cylinders

Heat transfer in a turbulent forced convection flow over a tandem square cylinder has been numerically studied at moderate Reynolds numbers. The effects of complex wake interactions behind the cylinder on heat transfer is studied. Turbulence is modelled by Detached Eddy Simulation (DES) with kOmegaSSTDES and SpalartAllmarasDES model available in OpenFOAM solver. The forced convection flow is formulated by two dimensional unsteady incompressible flow by neglecting buoyancy terms. The flow domain dimensions have been chosen such that the blockage ratio is less than 5%. The governing equations are solved numerically by Finite Volume method. Results are reported for different Reynolds numbers by varying spacings between the 2 cylinders from 2D to 5D, varying configuration and varying sizes of cylinders. The velocity and vorticity profiles and average Nusselt number values for both the cylinders are presented. The wake region behind the cylinders varies significantly with spacing between the cylinders affecting the heat transfer characteristics of downstream cylinder. The effect of Reynolds number in heat transfer characteristics is less pronounced in the second cylinder as compared to the first cylinder. The present results are matching well with the available experimental correlations and results available in the literature.
An Efficient Replicated System for the Metadata of HDFS

Hadoop HDFS is an open source project from Apache Software Foundation for scalable, distributed computing and data storage. HDFS has become a critical component in today's cloud computing environment and a wide range of applications built on top of it. However, the initial design of HDFS has introduced a single-point-of-failure, since HDFS contains only one active namenode, if this namenode experiences software or hardware failures, the whole HDFS cluster is unusable, this is a reason why people are reluctant to deploy HDFS for an application whose requirement is high availability. In this paper, we present a solution to enable the high availability for HDFS's namenode through efficient metadata replication. Our solution has 3 major advantages than existing ones: We utilize multiple active namenodes, instead of one, to build a cluster to serve requests of metadata simultaneously; We implement a pub/sub system to handle the metadata replication process across these active namonodes efficiently; We also propose a novel replication algorithm to deal with the network delay when the namonodes are deployed in different areas. Based on the solution we build a prototype called NCluster and integrate it with HDFS. We evaluate NCluster to exhibit its feasibility and effectiveness. The experimental results show that our solution performs well with low replication cost, good throughput and scalability.
LISA Pathfinder micronewton cold gas thrusters: In-flight characterization

The LISA Pathfinder (LPF) mission has demonstrated the ability to limit and measure the fluctuations in acceleration between two free falling test masses down to sub-femto-g levels. One of the key elements to achieve such a level of residual acceleration is the drag free control. In this scheme the spacecraft is used as a shield against any external disturbances by adjusting its relative position to a reference test mass. The actuators used to move the spacecraft are cold gas micropropulsion thrusters. In this paper, we report in-flight characterization of these thrusters in term of noise and artefacts during science operations using all the metrology capabilities of LISA Pathfinder. Using the LISA Pathfinder test masses as an inertial reference frame, an average thruster noise of ∼0.17 μN/Hz is observed and decomposed into a common (coherent) and an uncorrelated component. The very low noise and stability of the onboard metrology system associated with the quietness of the space environment allowed the measurement of the thruster noise down to ∼20 μHz, more than an order of magnitude below any ground measurement. Spectral lines were observed around ∼1.5 mHz and its harmonics and around 55 and 70 mHz. They are associated with the cold gas system itself and possibly to a clock synchronization issue. The thruster noise-floor exhibits an excess of ∼70% compared to characterization that have been made on ground on a single unit and without the feeding system. However this small excess has no impact on the LPF mission performance and is compatible with the noise budget for the upcoming LISA gravitational wave observatory. Over the whole mission, nominal, and extension, the thrusters showed remarkable stability for both the science operations and the different maneuvers necessary to maintain LPF on its orbit around L1. It is therefore concluded that a similar cold gas system would be a viable propulsion system for the future LISA mission.
Robust backstepping‐based trajectory tracking control for quadrotors with time delays

In this brief, the robust trajectory tracking control problem is addressed for uncertain quadrotor systems with time delays. The quadrotor dynamical model is an under-actuated system subject to non-linearity, unmodelled uncertainties, parametric perturbations, external disturbances, and state and input time delays. A robust cascade trajectory tracking controller is developed by the backstepping method and the robust compensation theory. Theoretical analysis is given to prove that the tracking errors can converge into the given neighbourhood of the origin ultimately. An on-line unidirectional tuning method is given to determine the controller parameters. Experimental results are provided to verify the effectiveness of the proposed control approach and the parameter tuning method.
SEA_AP: a segmentation and labelling tool for prosodic analysis

This paper introduces a tool that performs segmentation and labelling of sound chains in phono units, syllables and/or words departing from a sound signal and its corresponding orthographic transcription. In addition, it also integrates acoustic analysis scripts applied to the Praat programme with the aim of reducing the time spent on tasks related to analysis, correction, smoothing and generation of graphics of the melodic curve. The tool is implemented for Galician, Spanish and Brazilian Portuguese. Our goal is to contribute, by means of this application, to automatize some of the tasks of segmentation, labelling and prosodic analysis, since these tasks require a large investment of time and human resources.
Networked Heterogeneous Systems in a ROS-Enabled Cloud Environment

It is important in the development of cloud robotics that the challenges presented by transferring computational loads to networked resources are properly addressed. The challenges include network latency, data integrity, security, and privacy. The objective of the present work is to investigate the issues of latency and data integrity in a representative cloud robotics environment. The present work involves setting up a cloud robotics network in an open-source Robot Operating System (ROS) framework and carrying out investigations on the levels of latency and reduction in data integrity as utilization of the network increases. In this study, a virtual datacenter has been set up to provide the foundation on which to build software systems to provide cloud services. Robot Operating System (ROS) framework has been used to facilitate communication among heterogeneous systems in the network. Three types of robots, including the Parrot AR.Drone2. 0, the Kobuki Turtlebot 2, and the LEGO EV3 have been implemented in the system. The system has been tested for baseline connectivity and under lowand high-bandwidth conditions to determine the latency and data integrity of the network connections. Additionally, a heterogeneous system consisting of sensor feedback from the AR.Drone2. 0 and motor control of the Turtlebot 2 has been built to examine the connection between the devices themselves. Through this study, it has been demonstrated that under low-bandwidth conditions, the network performs reasonably well in the areas of latency and data integrity. However, for high-bandwidth conditions involving image transmission, the network performance deteriorates considerably, both in terms of latency and data integrity. One possible reason is the wireless router used in the current setup. It is also recommended that, especially under high-bandwidth loads, it is necessary for networked systems to perform some portion of their computations on-board and high-bandwidth wireless connectivity to the cloud is facilitated. Ongoing research and future directions are also outlined. INDEX WORDS: Cloud robotics, Network, Heterogeneous, Robot Operating System NETWORKED HETEROGENEOUS SYSTEMS IN A ROS-ENABLED CLOUD ENVIRONMENT by CHRISTOPHER REID B.Sc., Georgia Southern University, 2013 A Thesis Submitted to the Graduate Faculty of Georgia Southern University in Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE STATESBORO, GEORGIA
An Algorithm for Generating Association Rules Based on the Information of Sub Ru les

One of the most important data mining problems is mining association rules. Traditional method for generating association rules from frequent itemse ts is expensive because it have to consider each real sub set of the frequent it emset which is not null. The paper considers how to use the obtained useful rule information of frequent sub K-itemsets to generate strong association rules for the frequent parent (K+1)-itemsets, the performance will be better when the fre quent itemset is very long or the confidence is very high, because it uses the o btained useful information.
A Lack-Of-Fit Test with Screening in Sufficient Dimension Reduction

Researchers often need to infer how the conditional mean of a response varies with the predictors. Sufficient dimension-reduction techniques reduce the dimension by identifying a minimal set of linear combinations of the original predictors, without loss of information. This study tests whether a given small number of linear combinations of the original ultrahigh-dimensional covariates is sufficient to characterize the conditional mean of the response. We first introduce a novel consistent lack-of-fit test statistic for the case when the dimensionality of the covariates is moderate. The proposed test is shown to be n-consistent under the null hypothesis, and root-n-consistent under the alternative hypothesis. A bootstrap procedure is developed to approximate the p-values, and the consistency of the test is studied theoretically. To deal with the ultrahigh dimensionality, we introduce a two-stage lack-of-fit test with screening (LOFTS) procedure, based on a data-splitting strategy. The data are randomly partitioned into two equal halves. In the first stage, we apply the martingale difference correlationbased screening to one half of the data, and select a moderate set of covariates. Statistica Sinica: Preprint doi:10.5705/ss.202018. 0176
Privacy Preserving Three-Layer Naïve Bayes Classifier for Vertically Partitioned Databases

Data mining is the extraction of the hidden information from large databases. It is a powerful technology to explore important information in the data warehouse. Privacy preservation is a significant problem in the field of data mining. It is more challenging when data is distributed among different parties. In this paper, we address the problem of privacy preserving three-layer Naive Bayes classification over vertically partitioned data. Our approach is based on Secure Multiparty Computation (SMC). We use secure multiplication protocol to classify the new tuples. In our protocol, secure multiplication protocol allows to meet privacy constraints and achieve acceptable performance and our classification system is very efficient in term of computation and communication cost.
A New Wireless Sensor Network Scheme to Provide Quality of Service (QoS) for Smart Grid Applications

Wireless Sensor Networks (WSNs) has been utilized in a wide range of smart grids applications due to their capabilities to monitor environmental phenomena or connect the physical world to the virtual word. WSNs include large number of sensor nodes which obtain data about physical phenomena that is difficult to obtain in more conventional ways. For smart grid applications, supporting the Quality of Service (QoS) is the main requirement from WSNs, such as transmitting delay-critical data from smart grid assets as fast as possible or identifying priority packets which need to be transmitted before any other periodic packets and hence reducing the collision rate. At the same time, WSNs need to provide the required QoS for a long time (e.g. months or years) using the limited resources of the network (e.g. limited energy resources or channel bandwidth). Meeting such a goal requires a remarkable design for WSNs protocols in order to satisfy the requirements of delay/priority critical smart grid applications. In this paper, we propose a suit of novel WSNs Medium Access Control (MAC) protocol which aims to provide QoS in terms of low transmitting delay for packets and supporting the priority packets over the network for smart grid applications. Our proposed MAC protocol is called Delay and Priority MAC protocol (or DPMAC) for smart grid applications based on WSNs. DPMAC protocol is based on the delay estimation and priority packets that are defined by the application layer of the smart grid application and the network conditions. Our comprehensive performance analysis shows how the proposed DPMAC protocol can achieve low end-to-end delay and lower collision rate in comparison with the well-known IEEE 802.15. 4 MAC protocol which is used extensively in literature to provide the QoS for smart grid applications.
Aiding Dictionary Learning Through Multi-Parametric Sparse Representation

The ℓ 1 relaxations of the sparse and cosparse representation problems which appear in the dictionary learning procedure are usually solved repeatedly (varying only the parameter vector), thus making them well-suited to a multi-parametric interpretation. The associated constrained optimization problems differ only through an affine term from one iteration to the next (i.e., the problem’s structure remains the same while only the current vector, which is to be (co)sparsely represented, changes). We exploit this fact by providing an explicit, piecewise affine with a polyhedral support, representation of the solution. Consequently, at runtime, the optimal solution (the (co)sparse representation) is obtained through a simple enumeration throughout the non-overlapping regions of the polyhedral partition and the application of an affine law. We show that, for a suitably large number of parameter instances, the explicit approach outperforms the classical implementation.
Semiparametric Analysis of Short-Term and Long-Term Hazard Ratio Model with Length-Biased and Right-Censored Data

This paper discusses regression analysis of length-biased and right-censored failure time data arising from the short-term and long-term hazard ratio model. Compared to some commonly used models such as the proportional hazards models, the shortterm and long-term hazard ratio model has the advantage of allowing crossing hazard functions and thus is more flexible. For the problem, we propose two methods, the conditional likelihood approach and the composite conditional likelihood approach, for estimation of regression parameters. Both asymptotic and finite sample properties of the proposed estimators are established and the numerical results suggest that the methods seem to work well in practical situations. In addition, the approaches are applied to a set of real data arising from a dementia study. 1 Statistica Sinica: Newly accepted Paper (accepted author-version subject to English editing)
Um arcabouço para compartilhamento eficiente de WLANs Wi-Fi por fatiamento de rede no contexto de redes ultra densas 5G

O advento de casos de uso inovadores no contexto das redes de quinta geracao (5G) tem desafiado as abordagens de redes de comunicacao estabelecidas. As demandas por baixa latencia, alta disponibilidade de largura de banda, escalabilidade, acesso ubiquo e suporte a conectividade para dispositivos IoT de capacidade limitada sao algumas das questoes que os provedores de redes precisam enfrentar atualmente. A tecnologia de WLANs WiFi, em decorrencia de sua alta densidade nos centros urbanos e capacidade de prover acesso compartilhado via solucoes como os hotspots, oferece enormes oportunidades de conectividade aos usuarios e dispositivos. Somando-se as redes Wi-Fi os recursos computacionais abundantes da infraestrutura do ISP — proximos portanto dos dispositivos finais —, tem-se uma infraestrutura na borda da rede com grande potencial de suprir as demandas acima mencionadas. Apesar disso, um levantamento do estado da arte identificou que nenhum dos trabalhos relacionados e capaz de articular esta infraestrutura da borda da rede de forma satisfatoria. Esta tese tem por objetivo geral propor uma solucao capaz de fazer uso do substrato que abrange as redes Wi-Fi de acesso compartilhado, os recursos da infraestrutura do ISP e as redes de acesso que interconectam ambos para oferecer no espaco urbano servicos escalaveis, de atraso reduzido, localizados e pervasivos. A solucao proposta, denominada WLAN slIcing SErvice (WISE), faz uso de tecnologias emergentes como as de virtualizacao de recursos computacionais e de virtualizacao de rede para fatiar a infraestrutura subjacente de forma a disponibiliza-la em particoes capazes de oferecer servicos diferenciados, com isolamento e independencia de operacao. O WISE expande ainda as capacidades computacionais dos Customer Premise Equipments (CPEs) que compoem as redes Wi-Fi de acesso compartilhado, transformando-os em nos de uma nevoa computacional aptos a abrigar parte de suas funcionalidades avancadas e a executar servicos locais virtualizados. O WISE foi avaliado por meio de uma bancada de testes real e demonstrou ser uma solucao superior as solucoes tradicionais de compartilhamento de redes Wi-Fi.
MULTI-POPULATION CENTRAL SOLUTION SEARCHINGALGORITHM BASED ON COMPUTATION RESOURCE DISTRIBUTING FOR ELECTRIC NETWORK PLANNING

An electric transmission planning algorithm of multi-population central solution searching is proposed according to a brand new conception of computation resource’s efficient allocation, each population acquires the computation resource by the criteria of searching efficiency. The algorithm uses the setting of memory cells of immune algorithm as reference, improves the memorizing efficiency by region memorizing in contrast to the usual point memorizing, and can recognize and memorize local optimum effectively. What’s more, it escapes from the local optimum by the information entropy describing of solution distances. The algorithm is of both excellent local and global searching capability and testified by the samples. The reason of low efficiency of modern heuristic algorithm is also analyzed.
Sources and Geographical Origins of PM10 in Metz (France) Using Oxalate as a Marker of Secondary Organic Aerosols by Positive Matrix Factorization Analysis

An original source apportionment study was conducted on atmospheric particles (PM10) collected in Metz, one of the largest cities of Eastern France. A Positive matrix factorization (PMF) analysis was applied to a sampling filter-based chemical dataset obtained for the April 2015 to January 2017 period. Nine factors were clearly identified, showing mainly contributions from anthropogenic sources of primary PM (19.2% and 16.1% for traffic and biomass burning, respectively) as well as secondary aerosols (12.3%, 14.5%, 21.8% for sulfate-, nitrate-, and oxalate-rich factors, respectively). Wood-burning aerosols exhibited strong temporal variations and contributed up to 30% of the PM mass fraction during winter, while primary traffic concentrations remained relatively constant throughout the year. These two sources are also the main contributors during observed PM10 pollution episodes. Furthermore, the dominance of the oxalate-rich factor among other secondary aerosol factors underlines the role of atmospheric processing to secondary organic aerosol loadings which are still poorly characterized in this region. Finally, Concentration-Weighted Trajectory (CWT) analysis were performed to investigate the geographical origins of the apportioned sources, notably illustrating a significant transport of both nitrate-rich and sulfate-rich factors from Northeastern Europe but also from the Balkan region.