Miracle-dz/UniFAR-FTUs huggingface dataset:
An accurate estimation of the Levenshtein distance using metric trees and Manhattan distance

This paper presents an original clone detection technique which is an accurate approximation of the Levenshtein distance. It uses groups of tokens extracted from source code called windowed-tokens. From these, frequency vectors are then constructed and compared with the Manhattan distance in a metric tree. The goal of this new technique is to provide a very high precision clone detection technique while keeping a high recall. Precision and recall measurement is done with respect to the Levenshtein distance. The testbench is a large scale open source software. The collected results proved the technique to be fast, simple, and accurate. Finally, this article presents further research opportunities.
Recognizing human actions in still images: a study of bag-of-features and part-based representations

Recognition of human actions is usually addressed in the scope of video interpretation. Meanwhile, common human actions such as ''reading a book'', ''playing a guitar'' or ''writing notes'' also provide a natural description for many still images. In addition, some actions in video such as ''taking a photograph'' are static by their nature and may require recognition methods based on static cues only. Motivated by the potential impact of recognizing actions in still images and the little attention this problem has received in computer vision so far, we address recognition of human actions in consumer photographs. We construct a new dataset available at http://www.di. ens.fr/willow/research/stillactions/ with seven classes of actions in 911 Flickr images representing natural variations of human actions in terms of camera view-point, human pose, clothing, occlusions and scene background. We study action recognition in still images using the state-of-the-art bag-of-features methods as well as their combination with the part-based Latent SVM approach of Felzenszwalb et al. In particular, we investigate the role of background scene context and demonstrate that improved action recognition performance can be achieved by (i) combining the statistical and part-based representations, and (ii) integrating person-centric description with the background scene context. We show results on our newly collected dataset of seven common actions as well as demonstrate improved performance over existing methods on the datasets of Gupta et al. and Yao and Fei-Fei.
Coherent Software Cities

Coherent Software Cities are a software visualization approach which adopts the city metaphor to support the comprehension of various aspects of evolving software systems. For this purpose, the approach implements a three-staged modeling chain yielding coherent sets of application specific visualizations. In this context, a new layout approach for software cities is presented, which explicitly takes development history into account. Its effects are twofold: First, evolution becomes visible in the layouts, which allows for supporting new application scenarios. Second, layouts evolve smoothly and stable during system evolution, which allows software cities to be used online, i.e. during ongoing system development and maintenance.
Individual Differences in Asymmetric Resting-State Frontal Cortical Activity Modulate ERPs and Performance in a Global-Local Attention Task

Recent research has demonstrated that individual differences in approach motivation modulate attentional scope. In turn, approach and inhibition have been related to different neural systems that are associated with asymmetries in relative frontal activity (RFA). Here, we investigated whether such individual differences in asymmetric hemispheric activity during rest, and self-report measures of approach motivation (as measured by the behavioral inhibition system, BIS/behavioral activation system, BAS scales) would be predictive of the efficiency of attentional processing of global and local visual information, as indexed by event-related potentials (ERPs) and performance measures. In the reported experiment, participants performed a visual attention task in which they were required to either attend to the global shape or the local components of presented stimuli. Electroencephalogram was recorded during task performance and during an initial "resting state" measurement. The results showed that only the BAS-Reward Responsiveness subscale was associated with left RFA during rest, while BIS, BAS-Drive, and BAS-Fun Seeking were associated with more right-lateralized RFA. Importantly, left RFA during the "resting state" measurement was associated with increased P3 (right-lateralized) amplitudes and decreased P3 latencies on trials requiring a global focus. In turn, these ERPs were associated with enhanced performance on trials requiring a global focus. These results provide the first evidence for a positive association between left RFA during rest and increased efficiency of right-lateralized brain mechanisms that are involved in processing global information.
Speeding Up the Convergence of Value Iteration in Partially Observable Markov Decision Processes

Partially observable Markov decision processes (POMDPs) have recently become popular among many AI researchers because they serve as a natural model for planning under uncertainty. Value iteration is a well-known algorithm for finding optimal policies for POMDPs. It typically takes a large number of iterations to converge. This paper proposes a method for accelerating the convergence of value iteration. The method has been evaluated on an array of benchmark problems and was found to be very effective: It enabled value iteration to converge after only a few iterations on all the test problems.
Applying the Episodic Natural Actor-Critic Architecture to Motor Primitive Learning

, Stefan SchaalUniversity of Southern California, Los Angeles CA 90089, USAAbstract. Inthispaper, weinvestigatemotorprimitivelearning withtheNatural Actor-Critic approach. The Natural Actor-Critic consists out ofactor updates which are achieved using natural stochastic policy gradientswhile the critic obtains the natural policy gradient by linear regression.We show that this architecture can be used to learn the “building blocksof movement generation”, called motor primitives. Motor primitives areparameterizedcontrolpoliciessuchassplinesornonlineardiﬀerentialequa-tions with desired attractor properties. We show that our most modernalgorithm, the Episodic Natural Actor-Critic outperforms previous algo-rithms by at least an order of magnitude. We demonstrate the eﬃciencyof this reinforcement learning method in the application of learning to hita baseball with an anthropomorphic robot arm.
Temporal integration: reflections in the M100 of the auditory evoked field

Previous work investigating temporal integration in the formation of the auditory evoked field component, M100, indicates an accumulation of stimulus attribute information in the processes underlying the M100 response with a temporal window for this integration of ∼25–32 ms. We investigate the influence of stimulus duration on M100 amplitude using sinusoidal tone stimuli of increasing duration under two experimental conditions: constant intensity, and constant energy (with stimulus intensity decreasing as duration increased). We report that M100 amplitude increases with stimulus duration up to a point of saturation at ∼40 ms; importantly, this dependence holds in both experimental conditions, despite differing stimulus intensities. Thus we conclude that (within this ∼40 ms temporal window) stimulus duration itself, and not integrated energy, determines M100 amplitude.
Social work students’ experiences in a Christianity and sexual minority intergroup dialogue

Abstract A tension between the lesbian, gay, and bisexual (LGB) and (heterosexual) conservative Christian communities has been documented within social work. This qualitative study explores students’ experiences in a Christianity and LGB sexuality intergroup dialogue at an American graduate social work program. This dialogue was the first known case of intergroup dialogue being used to address these topics in a social work program. Students’ motivations for participating in the dialogue, challenges faced throughout the dialogue, and what they learned are discussed. Pedagogical implications for schools of social work and intergroup dialogue are outlined.
Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems

We describe an efficient technique for adapting control parameter settings associated with differential evolution (DE). The DE algorithm has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters, which are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE. We present an algorithm-a new version of the DE algorithm-for obtaining self-adaptive control parameter settings that show good performance on numerical benchmark problems. The results show that our algorithm with self-adaptive control parameter settings is better than, or at least comparable to, the standard DE algorithm and evolutionary algorithms from literature when considering the quality of the solutions obtained
Anatomical structure similarity estimation by random forest

The morphological similarity of anatomical structures is essential to the study of the species evolution. In this paper, we investigate the unsupervised shape similarity analysis by a random-forest-based metric. The dense continuous deformation fields are employed as the shape descriptors. The forest is built when given the unlabeled deformation fields, where the leaves can be seen as an optimal clustering of the data set. The salient region is defined based on the dominant feature channels determined by the forests. The pairwise shape distance is computed efficiently with just binary comparisons stored in tree branches. We have applied our method to several skeletal data sets, including the skulls, teeth, radii, and metatarsals. Our experiments demonstrate the proposed method can handle the taxonomic classification effectively.
Time abstraction in timed µCRL à la regions

We present the first step towards combining the best parts of the real-time verification methods based on timed automata (the use of regions and zones), and of the process-algebraic approach of languages like LOTOS and /spl mu/CRL. This could provide with additional verification possibilities for real-time systems, not available in existing timed-automata-based tools like UPPAAL. We aim to transfer the successful techniques of regions and zones as used for the analysis of timed automata to the realm of timed /spl mu/CRL. First, we aim at replacing all parameters of sort time occurring in the resulting process equation by parameters of discrete sorts. To achieve this goal we apply process-algebraic transformations and abstraction techniques to the given process equation. As a result we obtain a process equation that is closely related to the given one in the following sense. If we abstract from the fractional parts of the time stamps in the actions, both of the equations will be timed bisimilar.
Ravana: controller fault-tolerance in software-defined networking

Software-defined networking (SDN) offers greater flexibility than traditional distributed architectures, at the risk of the controller being a single point-of-failure. Unfortunately, existing fault-tolerance techniques, such as replicated state machine, are insufficient to ensure correct network behavior under controller failures. The challenge is that, in addition to the application state of the controllers, the switches maintain hard state that must be handled consistently. Thus, it is necessary to incorporate switch state into the system model to correctly offer a "logically centralized" controller. We introduce Ravana, a fault-tolerant SDN controller platform that processes the control messages transactionally and exactly once (at both the controllers and the switches). Ravana maintains these guarantees in the face of both controller and switch crashes. The key insight in Ravana is that replicated state machines can be extended with lightweight switch-side mechanisms to guarantee correctness, without involving the switches in an elaborate consensus protocol. Our prototype implementation of Ravana enables unmodified controller applications to execute in a fault-tolerant fashion. Experiments show that Ravana achieves high throughput with reasonable overhead, compared to a single controller, with a failover time under 100ms.
Novel channel estimation method for coherent IR-UWB

A novel channel estimation scheme is proposed for coherent impulse radio ultra wideband (IR-UWB) system based on IEEE 802.15. 4a specification. By extracting and utilizing the information on the frequency synchronization, the proposed channel estimation algorithm improves the receiver performance even under the restricted number of preamble symbols in IEEE 802.15. 4a signal format. Simulation results over the IEEE 802.15. 4a channel models show the performance gain with the proposed algorithm compared to ordinary channel estimation method.
Molecular epidemiology of hepatitis C virus subtype 3a in injecting drug users

Hepatitis C virus subtype 3a (HCV‐3a) originates from Asia and has spread widely among injecting drug users as well as other patient groups in industrialized countries. HCV subtype 3a infection remains highly prevalent and frequently transmitted in the population of intravenous drug users. The objective of this study was to understand better the mechanisms of the worldwide HCV‐3a epidemics in drug users. Ninety‐three sera from HCV‐3a‐infected IDUs from France, the United States, Brazil, Argentina, and Australia were studied. Phylogenetic analyses of the non‐structural 5B region showed no specific clustering according to the continent of the patient's origin. Non‐exclusive clusters of viral sequences from South America, Australia, and California were observed, but topologies were not supported by strong bootstrap values. The results suggest that HCV‐3a has been transmitted from a common origin through a unique worldwide epidemic that rapidly spread among drug users. Regional transmission occurred in the recent past, leading to an embryonic genetic diversification of HCV‐3a among local injecting drug user population. J. Med. Virol. 78:1296–1303, 2006. © 2006 Wiley‐Liss, Inc.
Errors in the Initial Conditions for Numerical Weather Prediction: A Study of Error Growth Patterns and Error Reduction with Ensemble Filtering

Title of dissertation: ERRORS IN THE INITIAL CONDITIONS FOR NUMERICAL WEATHER PREDICTION: A STUDY OF ERROR GROWTH PATTERNS AND ERROR REDUCTION WITH ENSEMBLE FILTERING John Harlim, Doctor of Philosophy, 2006 Dissertation directed by: Professor Brian R. Hunt Department of Mathematics In this dissertation, we study the errors of a numerical weather prediction due to the errors in initial conditions and we present efficient nonlinear ensemble filters for reducing these errors. First, we investigate the error growth, that is, the growth in time of the distance E between two solutions of a global weather model with similar initial conditions. Typically E grows until it reaches a saturation value Es. We find two distinct broad log-linear regimes, one for E below 2% of Es and the other for E above. In each, log(E/Es) grows as if satisfying a linear differential equation. When plotting d log(E)/dt vs log(E), the graph is convex. We argue this behavior is quite different from error growth in other simpler dynamical systems, which yield concave graphs. Secondly, we present an efficient variation of the Local Ensemble Kalman Filter [32, 33] and the results of perfect model tests with the Lorenz-96 model. This scheme is locally similar to performing the Ensemble Transform Kalman Filter [5]. We also include a “four-dimensional” extension of the scheme to allow for asynchronous observations. Finally, we present a modified ensemble Kalman filter that allows a nonGaussian background error distribution. Using a distribution that decays more slowly than a Gaussian is an alternative to using a high amount of variance inflation. We demonstrate the effectiveness of this approach for the three-dimensional Lorenz-63 model and the 40-dimensional Lorenz-96 model in cases when the observations are infrequent, for which the non-Gaussian filter reduces the average analysis error by about 10% compared to the analogous Gaussian filter. The mathematical formulation of this non-Gaussian filter is designed to preserve the computational efficiency of the local filter described in the previous paragraph for high-dimensional systems. ERRORS IN THE INITIAL CONDITIONS FOR NUMERICAL WEATHER PREDICTION: A STUDY OF ERROR GROWTH PATTERNS AND ERROR REDUCTION WITH ENSEMBLE FILTERING
STUDY ON PHENOTYPIC AND GENOTYPIC CHARACTERIZATION OF BACTERIAL SPECIES ISOLATED FROM DECAYED FRUITS

Most of the methods adopted for processing of decayed fruits and degradation of wastes are not economical. In order to achieve 100% resource recovery from wastes, a novel type of waste treatment is to be followed, so that, the recovered byproducts could be used as biofertilizers. The objective of this study is identification of bacteria for studying their phenotypic and genotypic characters using molecular tools and conversion of wastes into biosolids as useful byproducts. Decayed fruit samples were procured and pure culture of bacterial strains were isolated. The isolated strains were subjected for phenotypic analysis of biochemical tests and genotypic gene expressions of 16S rRNA amplification, after which, the bacterial species identified were two strains of Bacillus subtilis, Serratia marcescens, Arthrobacter nicotianae and Corynebacterium singulare. The antibiogram activity was performed in all the cultures. From this analysis, strains were found to be resistant to most of the antibiotics.
Associations between Pain-Related Anxiety, Gender, and Prescription Opioid Misuse among Tobacco Smokers Living with HIV/AIDS

ABSTRACT Background: People living with HIV/AIDS (PLWHA) who smoke cigarettes are vulnerable to greater pain and aberrant use of prescription pain medications. Prescription opioid misuse is highly prevalent among PLWHA and can lead to a variety of adverse outcomes. Pain-related anxiety, which has been implicated in the maintenance of both pain and tobacco dependence, may also play a role in prescription pain medication misuse. Objectives: This study aimed to test associations between pain-related anxiety and prescription opioid misuse. We hypothesized that, among those prescribed opioid medication, pain-related anxiety would be positively associated with current opioid misuse, and stated intentions to misuse prescription opioids in the future. We further hypothesized that these relations would be more pronounced among males (vs. females). Methods: Participants included 61 PLWHA daily tobacco smokers with pain. Hierarchical regressions were used to test interactions between gender and pain-related anxiety on current and intended opioid misuse among those prescribed opioid medications. Results: There was a significant interactive effect of pain-related anxiety and gender on opioid misuse, such that pain-related anxiety was positively associated with current opioid misuse among male (but not female) participants who were prescribed opioid medications. Among both males and females, pain-related anxiety was positively associated with intention to misuse prescription pain medications in the future. Conclusions/Importance: Additional research into the role of pain-related anxiety in prescription opioid misuse is warranted. This type of work may inform the development of tailored interventions for PLWHA smokers who are prescribed opioid pain medications.
Realistic and real-time simulation of water

A modified physics-based method is adopted to control the water waves, and the discretization of the governing 2D N-S equation is taken as the interaction between the variables in spaces, based on the idea of spreading though the neighboring regions. Meshing model of the water surface is based on a terrain LOD scheme called Tiled Quad-tree. With that the region of water surface can be extended unboundedly. A new controlling strategy is used, that the driving parameters of the water movement is taken separately, so it's easy to change parameters in real time while generating various water waves. Reflection and refraction of rays in water is simulated to improve the visual impression. It is shown that these methods can efficiently produce realistic movement of various water waves in real-time.
Adaptive management of QoS in Open Systems

In this paper, we present a software architecture to support soft real-time applications, such as multimedia streaming and telecommunication systems, in open embedded systems. Examples of such systems are consumer electronic devices (as cellular phones, PDAs, etc.), as well as multimedia servers (video servers, VoIP servers, etc.) and telecommunication infrastructure devices. For such applications, it is important to keep under control the resource utilization of every task, otherwise the Quality of Service experienced by the users may be degraded. Our proposal is to combine a resource reservation scheduler (that allows us to partition the CPU time in a reliable way) and a feedback based mechanism for dynamically adjusting the CPU fraction (bandwidth) allocated to a tasks. In particular, our controller enables specified Quality of Service (QoS) levels for the application while keeping the allocated bandwidth close to its actual needs. The adaptation mechanism consists of the combination of a prediction and of a feedback correction that operates locally on each task. The consistency of the system is preserved by a supervisor component that manages overload conditions and enacts security policies. We implemented the framework in AQuOSA, a software architecture that runs on top of the Linux kernel. We provide extensive experimental validation of our results and offer evaluation of the introduced overhead, which is remarkably lower than the one introduced by other different solutions.
Health, hygiene and biosecurity: Tribal knowledge claims in the UK poultry industry

Since 1997 the world has been facing the threat of a human influenza pandemic that may be caused by an avian virus and the poultry industry around the globe has been grappling with the highly pathogenic strain of avian influenza H5N1, or in more informal terms bird flu. The UK poultry industry has lived with and through this threat and its consequences since 2005. This study investigates knowledge claims about health, hygiene and biosecurity as tools to ward off the threat from this virus. It takes a semi-ethnographic and discourse analytic approach to analyse a small corpus of semi-structured interviews carried out in the wake of one of the most publicised outbreaks of H5N1 in Suffolk in 2007. It reveals that claims about what best to do to protect flocks against the risk of disease are divided along lines imposed on the one hand by the structure of the industry and on the other by more ‘tribal’ lines drawn by knowledge and belief systems about purity and dirt, health and hygiene.