Miracle-dz/UniFAR-FTUs huggingface dataset:
Image decomposition: separation of texture from piecewise smooth content

This paper presents a novel method for separating images into texture and piecewise smooth parts. The proposed approach is based on a combination of the Basis Pursuit Denoising (BPDN) algorithm and the Total-Variation (TV) regularization scheme. The basic idea promoted in this paper is the use of two appropriate dictionaries, one for the representation of textures, and the other for the natural scene parts. Each dictionary is designed for sparse representation of a particular type of image-content (either texture or piecewise smooth). The use of BPDN with the two augmented dictionaries leads to the desired separation, along with noise removal as a by-product. As the need to choose a proper dictionary for natural scene is very hard, a TV regularization is employed to better direct the separation process. Experimental results validate the algorithm's performance.
An Analytical MAC Model for IEEE 802.15.4 Enabled Wireless Networks With Periodic Traffic

The IEEE 802.15. 4 standard, which supports low-cost communications, has been applied in a variety of wireless networks. Developing accurate analytical models for the IEEE 802.15. 4 medium access control (MAC) protocol is critical for the design and performance evaluation of such networks. Periodic traffic is a common traffic pattern generated in many practical application scenarios, for which most existing analytical models assuming either saturated or random network traffic patterns become inapplicable. In this paper, we develop an accurate and scalable analytical model to analyze the IEEE 802.15. 4 MAC protocol with the periodic traffic. Our model can accurately capture the protocol stochastic behavior in each period in scenarios such as with or without retransmissions and with single clear channel assessment (CCA) or double CCAs. Extensive simulations are conducted to validate the proposed model by both transient and aggregate performance evaluations, and the results show that the model captures MAC behavior with periodic traffic accurately. We also discuss about extending the proposed model to account for heterogeneous scenarios and the hidden node problem.
GIANT PLANETS AND BROWN DWARFS

I. INTRODUCTION The study of extrasolar giant planets (EGPs*) and brown dwarfs via reflex stellar motion, broad–band photometry, and spectroscopy has finally come into its own. Doppler spectroscopy alone has revealed about 15 objects in the giant planet/brown dwarf regime, including was a milestone since Gl229 B displays methane spectral features and low surface fluxes that are unique to objects with effective temperatures (in this case, T eff ∼950 K) below those at the solar–metallicity main sequence edge (∼1750 K, Burrows et al. 1993). In addition, the almost complete absence of spectral signatures of metal oxides and hydrides (such as TiO, VO, FeH, and CaH) is in keeping with theoretical predictions that these species are depleted in the atmospheres of all but the youngest (hence, hottest) substellar objects and are sequestered in condensed form below the photosphere (Lunine et al. 1989; Marley et al. 1996). The wide range in mass and period, as well as the proximity of many of the
Spatio-temporal cuboid pyramid for action recognition using depth motion sequences

In this paper, we present an effective method to recognize human actions from sequences of depth maps, which are captured by a consume depth sensor. In our approach, we first project each frame of a depth sequence onto three orthogonal planes and generate the depth motion sequence (DMS) between two consecutive frames from the three projected views. Then we propose a spatio-temporal cuboid pyramid (STCP) to subdivide the DMS volumes into a set of spatial cuboids on scaled temporal levels. And a cuboid fusion scheme is presented to concatenate the histograms of oriented gradients (HOG) features extracted from the spatial cuboid. The proposed approach is evaluated on three public benchmark datasets, i.e., MSRAction3D, MSRGesture3D and MSRActionPairs dataset. The experimental results demonstrate that the proposed method achieves state-of-the-art performance.
A FLEXIBLE REAL-TIME MOTOR CONTROL SYSTEM FOR ROBOT JOINTS

-A flexible, real-time motor control system consisting of a DC motor and an incremental optical encoder is proposed. The system allows complex real-time control algorithms to be implemented with hardware control excepting PC-based software simulation. A motion control processor is used to bridge the Target PC and the robot joint through I/O devices. Simulink/Real Time Workshop (RTW) are the software interface loaded in the Workstation PC which generates the control codes and stand-alone program for various control algorithms. Figure1. The interactive design-prototype-test development process for the robot joint control. Design, prototype the model graphically in Matlab/Simulink
An Open Source HMM-based Text-to-Speech System for Brazilian Portuguese

Text-to-speech (TTS) is currently a mature tech- nology that is used in many applications. Some modules of a TTS depend on the language and, while there are many public resources for English, the resources for some under- represented languages are still limited. This work describes the development of a complete TTS system for Brazilian Portuguese which expands the already available resources. The system uses the MARY framework and is based on the hidden Markov model (HMM) speech synthesis approach. Some of the contributions of this work consist in implementing syllab- ification, determination of stressed syllable and grapheme-to- phoneme (G2P) conversion. This work also describes the steps for organizing the developed resources and implementing a Brazilian Portuguese voice within the MARY. These resources are made available and facilitate the research in text analysis and HMM-based synthesis for Brazilian Portuguese. Keywords— Text-to-speech systems, HMM-based speech syn- thesis, text analysis.
Hamiltonian analyses of new set of dual actions of bosonic p-branes

We make hamiltonian analyses of the new set of dual bosonic p-brane (including string) actions which contain high non-linearity. The difficulties exist in two basic steps of the hamiltonian procedure, that is, in calculating canonical momenta and in solving velocities in terms of momenta. The former difficulty can be overcome by an ADM reparametrization of induced metrics, while the latter may be circumvented by some modification to the usual Hamiltonian procedure. We also compare our results with that of the other set composed of known dual p-brane actions.
Expert-based initialization of recursive mixture estimation

Initialization is an extremely important part of the mixture estimation process. There exists a series of initialization approaches in the literature concerning the mixture initialization. However, the majority of them is directed at initialization of the expectation-maximization algorithm widely used in this area. This paper focuses on the initialization of the mixture estimation with normal components based on the recursive statistics update of involved distributions, where the mentioned methods are not suitable. Its key part is the choice of the initial statistics. The paper describes several relatively simple initialization techniques primarily based on processing the prior data. The experimental part of the paper represents results of validation on real data.
Teachers` Attachment History and Child-Teacher Relationships in Early Childhood Education Settings: Examining Mediating Effect of Teachers` Psychological Well-Being

The purpose of this study is to examine the mediating effects of teachers' psychological well-being between teachers' attachment history and child-teacher relationships. The participants of this survey were 342 teachers from 41 day care centers and 11 kindergartens in four metropolitan cities and five provinces in Korea. The collected data were analysed through frequency and percentage calculation, Pearson's correlations, and the mediation methods suggested by Baron & Kenny(1986) were calculated by using SPSS 21.0. The findings are as follows. First, the percentage points of the attachment history of early childhood, the teachers' psychological well-being and the child-teacher relationship were higher than the average. Also, all the variables had correlations. Second, the teachers' psychological well-being partly mediated the relations between attachment history and child-teacher relationships. These results imply that teachers' psychological well-being is needed for positive child-teacher relationships, and can provide policy implications for teachers' psychological well-being in order to improve the quality of child-teacher relationships.
A hybrid nudging-ensemble Kalman filter approach to data assimilation. Part I: application in the Lorenz system

ABSTRACT A hybrid data assimilation approach combining nudging and the ensemble Kalman filter (EnKF) for dynamic analysis and numerical weather prediction is explored here using the non-linear Lorenz three-variable model system with the goal of a smooth, continuous and accurate data assimilation. The hybrid nudging-EnKF (HNEnKF) computes the hybrid nudging coefficients from the flow-dependent, time-varying error covariance matrix from the EnKF's ensemble forecasts. It extends the standard diagonal nudging terms to additional off-diagonal statistical correlation terms for greater inter-variable influence of the innovations in the model's predictive equations to assist in the data assimilation process. The HNEnKF promotes a better fit of an analysis to data compared to that achieved by either nudging or incremental analysis update (IAU). When model error is introduced, it produces similar or better root mean square errors compared to the EnKF while minimising the error spikes/discontinuities created by the intermittent EnKF. It provides a continuous data assimilation with better inter-variable consistency and improved temporal smoothness than that of the EnKF. Data assimilation experiments are also compared to the ensemble Kalman smoother (EnKS). The HNEnKF has similar or better temporal smoothness than that of the EnKS, and with much smaller central processing unit (CPU) time and data storage requirements.
Perceptions of Productivity and

This study focuses on the influence intellectual ca pital has on employees’ perceptions as related to b oth company investments and productivity levels. The data was o btained from 440 employees at 13 Portuguese compani es. Both ANOVA and Regression Analysis were conducted i n order to understand the impact three Intellectual Capital Scale components have on perceptions of inv estment and organizational productivity. Results sh ow that companies with higher scores of Structural Capital have a lower perception of investment in human reso urces and research, as well as a higher perception of inv estment in marketing and sales. Moreover, employees of companies with higher Structural Capital scores als o have higher perceptions of productivity. On the o ther hand, organizations with higher investment in Customer Ca pital tend to be associated with a lower perception of organizational productivity.
Geodesic Video Stabilization in Transformation Space

We present a novel formulation of video stabilization in the space of geometric transformations. With the setting of the Riemannian metric, the optimized smooth path is cast as the geodesics on the Lie group embedded in transformation space. While solving the geodesics has a closed-form expression in a certain space, path smoothing can be easily implemented by using geometric interpolation, rather than optimizing any space-time energy function. Specially, by using the geodesic solution in the space of rigid transformations, our approach even gains speedup $10\times $ faster than state-of-the-art methods for path smoothing and motion compensation, and guarantees no extra distortion drawn into the stabilized frames. The experiments demonstrate the efficiency and effectiveness of our algorithm on stabilizing a variety of shaky videos.
p53-Dependent Transcriptional Responses to Interleukin-3 Signaling

p53 is critical in the normal response to a variety of cellular stresses including DNA damage and loss of p53 function is a common feature of many cancers. In hematological malignancies, p53 deletion is less common than in solid malignancies but is associated with poor prognosis and resistance to chemotherapy. Compared to their wild-type (WT) counterparts, hematopoietic progenitor cells lacking p53 have a greater propensity to survive cytokine loss, in part, due to the failure to transcribe Puma, a proapoptotic Bcl-2 family member. Using expression arrays, we have further characterized the differences that distinguish p53−/− cells from WT myeloid cells in the presence of Interleukin-3 (IL-3) to determine if such differences contribute to the increased clonogenicity and survival responses observed in p53−/− cells. We show that p53−/− cells have a deregulated intracellular signaling environment and display a more rapid and sustained response to IL-3. This was accompanied by an increase in active ERK1/2 and a dependence on an intact MAP kinase signaling pathway. Contrastingly, we find that p53−/− cells are independent on AKT for their survival. Thus, loss of p53 in myeloid cells results in an altered transcriptional and kinase signaling environment that favors enhanced cytokine signaling.
Avoidance of Multiple Dynamic Obstacles

this article is a continuation of the previous article called “Obstacle Avoidance in Dynamic Environment: a Hierarchical Solution”, which presented the concept for obstacle avoidance in dynamic environment suitable for mobile robot. The task of obstacle avoidance is divided in three principal groups: local, global and for emergencies. The global avoidance is here approached, in which the concept used is based on reinforcement learning and on an algorithm for planning the avoidance, in such a way that the situations are divided into four states and two kinds of actions are possible. The states define in what situation the movement relationship between the robot and the dynamic obstacles is present, and the actions decide in which direction the robot must follow, in order to avoid a possible collision. The algorithm plans in order to decide an action, which certainly is not the best for each obstacle, but normally is the best considering the group.
A comparative study of cooperative and non-cooperative game theory in network selection

Fifth generation wireless network is consisting of heterogeneous networks to provide end to end mobility and service to mobile users. So in heterogeneous wireless network, selection of the optimal network becomes an important task. In recent years, network selection has been mostly studied by using different mathematical methods. But in this paper, the network selection problem is modelled as the evolutionary and bankruptcy game in heterogeneous wireless networks. Analytical Hierarchy Process (AHP) is used to decide the weights of different attributes according to service requirement and evolutionary and bankruptcy game theory is used for ranking of the networks. Evolutionary game is used as the non-cooperative game for studying the behavior of selfish users and bankruptcy game is used as the cooperative game for achieving mutual advantage. The comparison between the cooperative game and non-cooperative game is studied in case of streaming, conversational and background traffic class. Simulation results show that different networks are selected for different traffic class according to user preference.
Improved Performance of RF Energy Powered Wireless Sensor Node with Cooperative Beam Selection

RF energy harvesting is a promising potential solution to provide convenient and perpetual energy supplies to low-power wireless sensor networks. In this paper, we investigate the energy harvesting performance of a wireless sensor node powered by harvesting RF energy from existing multiuser MIMO system. Specifically, we propose a random unitary beamforming (RUB) based cooperative beam selection scheme to enhance the energy harvesting performance at the sensor. Under a constant total transmission power constraint, the multiuser MIMO system tries to select a maximal number of active beams for data transmission, while satisfying the energy harvesting requirement at the sensor. We derive the exact closed-form expression for the distribution function of harvested energy in a coherence time over Rayleigh fading channels. We further investigate the performance tradeoff of the average harvested energy at the sensor versus the sumrate of the multiuser MIMO system.
Synestouch: Haptic + audio affective design for wearable devices

Little is known about the affective expressivity of multisensory stimuli in wearable devices. While the theory of emotion has referenced single stimulus and multisensory experiments, it does not go further to explain the potential effects of sensorial stimuli when utilized in combination. In this paper, we present an analysis of the combinations of two sensory modalities - haptic (more specifically, vibrotactile) stimuli and auditory stimuli. We present the design of a wrist-worn wearable prototype and empirical data from a controlled experiment (N=40) and analyze emotional responses from a dimensional (arousal + valence) perspective. Differences are exposed between “matching” the emotions expressed through each modality, versus "mixing" auditory and haptic stimuli each expressing different emotions. We compare the effects of each condition to determine, for example, if the matching of two negative stimuli emotions will render a higher negative effect than the mixing of two mismatching emotions. The main research question that we study is: When haptic and auditory stimuli are combined, is there an interaction effect between the emotional type and the modality of the stimuli? We present quantitative and qualitative data to support our hypotheses, and complement it with a usability study to investigate the potential uses of the different modes. We conclude by discussing the implications for the design of affective interactions for wearable devices.
Sampling Traffic Analysis of Anonymous Communications in Mobile Ad Hoc Networks

In this paper, we studied the security of anonymous communications in mobile ad hoc networks. We first proposed a statistical model for anonymous communications. By employing the principle of Bayesian inference, we were able to transform a traffic analysis problem into a sampling problem. Metropolis-Hastings algorithm was implemented to analyze the sampling problem. Experiments were conducted on Threshold Mix to evaluate the correctness and efficiency of this method. Compared with traditional traffic analysis methods, our method provides more legitimate probability results and has the potential to be used widely.
TA-LTL: Specifying Adaptation Timing Properties in Autonomic Systems

Increasingly, computer software must adapt dynamically to changing conditions. The correctness of adaptation cannot be properly addressed without precisely specifying the requirements for adaptation. In many situation, these requirements involve absolute time, in addition to a logical ordering of events. This paper introduces an approach to formally specifying such timing requirements for adaptive software. We introduce TA-LTL, a timed adaptation-based extension to linear temporal logic, and use this logic to specify three timing properties associated with the adaptation process: safety, liveness, and stability. A dynamic adaptation of interactive audio streaming software is used to illustrate timed temporal logic
Thermostable DNA Polymerase from a Viral Metagenome Is a Potent RT-PCR Enzyme

Viral metagenomic libraries are a promising but previously untapped source of new reagent enzymes. Deep sequencing and functional screening of viral metagenomic DNA from a near-boiling thermal pool identified clones expressing thermostable DNA polymerase (Pol) activity. Among these, 3173 Pol demonstrated both high thermostability and innate reverse transcriptase (RT) activity. We describe the biochemistry of 3173 Pol and report its use in single-enzyme reverse transcription PCR (RT-PCR). Wild-type 3173 Pol contains a proofreading 3′-5′ exonuclease domain that confers high fidelity in PCR. An easier-to-use exonuclease-deficient derivative was incorporated into a PyroScript RT-PCR master mix and compared to one-enzyme (Tth) and two-enzyme (MMLV RT/Taq) RT-PCR systems for quantitative detection of MS2 RNA, influenza A RNA, and mRNA targets. Specificity and sensitivity of 3173 Pol-based RT-PCR were higher than Tth Pol and comparable to three common two-enzyme systems. The performance and simplified set-up make this enzyme a potential alternative for research and molecular diagnostics.
Significant Impact of P-cycles on Survivable WDM Optical Network

It is known that Wavelength division multiplexing (WDM) technique enables single fiber to carry huge amount of data but optical WDM networks are prone to failures, therefore survivability is a very important requirement in the design of optical networks. In this paper, a comprehensive review about survivability of WDM networks has been discussed focusing on scalable and efficient p-cycles resilience techniques and a comparative analysis particularly among ring and mesh resilience techniques has been performed. In the context of network survivability, p-cycle based schemes attracted extensive research interests as they maintain balance between recovery speed and capacity efficiency. It is observed that pcycles are key to obtain mesh-like network efficiency from a ring-like protection.
A Target Depth Measurement Method Based on Light Field Imaging

4-D Light field information, of which we can extract the target depth information, can be obtained with only one photo using light field camera. The existing target depth information acquisition methods based on light field mostly need huge amounts of photographs and complicated mathematical calculations. To solve these problems, this paper puts forward a light-field-based depth measurement method, by which the image distance of corresponding target can be computed using Depth-From-Focus (DFF) method. The simulation experiment proved that only one image is needed to realize the different targets' depth resolving by this proposed method, and the results are of small error and little computational work.
Can Homicide Detectives Improve Homicide Clearance Rates?

The available scientific evidence on the value of detectives in clearing crimes generally suggests that most crimes are solved through the random circumstances of crime scenes rather than special follow-up investigation. Other research, however, suggests that the work of criminal investigators can increase the likelihood that crimes might be cleared through arrest. After years of homicide clearance rates that were lower than the national average, the Boston Police Department engaged a problem-oriented policing approach to improve their post-homicide criminal investigation processes and practices. Our quasi-experimental statistical analyses suggest that the intervention significantly increased key investigative activities and improved Boston homicide clearance rates relative to existing homicide clearance trends in other Massachusetts and U.S. jurisdictions.