Miracle-dz/UniFAR-FTUs huggingface dataset:
RECOVERING INTRINSIC SCENE CHARACTERISTICS FROM IMAGES

We suggest that an appropriate role of early visual processing is to describe a scene in terms of intrinsic (vertical) characteristics -- such as range, orientation, reflectance, and incident illumination -- of the surface element visible at each point in the image. Support for this idea comes from three sources: the obvious utility of intrinsic characteristics for higher-level scene analysis; the apparent ability of humans to determine these characteristics, regardless of viewing conditions or familiarity with the scene; and a theoretical argument that such a description is obtainable, by a noncognitive and nonpurposive process, at least, for simple scene domains. The central problem in recovering intrinsic scene characteristics is that the information is confounded in the original light-intensity image: a single intensity value encodes all the characteristics of the corresponding scene point. Recovery depends on exploiting constraints, derived from assumptions about the nature of the scene and the physics of the imaging process.
Identifying a group of subject experts using formal concept analysis

Expertise retrieval has already gained significant interest in the area of information retrieval due to multitude of concrete application contexts where search for specific experts is required. In this paper, we introduce a formal concept analysis approach for clustering of a group of experts with respect to given subject areas. Initially, the domain of interest is presented at some level of abstraction by partitioning the domain to a number of subject areas. Next each expert is represented by a vector of contributions of the expert to the different areas. This defines an overlapping partition, which is further analyzed and refined into a disjoint one by applying Formal Concept Analysis. In this way a hierarchical conceptual structure is automatically derived. It consists of concepts where each one represents a subset of experts belonging to a number of subject areas. The set of all derived concepts partitions the experts into a set of disjoint expert areas.
Dual-Microphone Speech Dereverberation in a Noisy Environment

Speech signals recorded with a distant microphone usually contain reverberation and noise, which degrade the fidelity and intelligibility of speech, and the recognition performance of automatic speech recognition systems. In E. Habets (2005) presented a multi-microphone speech dereverberation algorithm to suppress late reverberation in a noise-free environment. In this paper we show how an estimate of the late reverberant energy can be obtained from noisy observations. A more sophisticated speech enhancement technique based on the optimally-modified log spectral amplitude (OM-LSA) estimator is used to suppress the undesired late reverberant signal and noise. The speech presence probability used in the OM-LSA is extended to improve the decision between speech, late reverberation and noise. Experiments using simulated and real acoustic impulse responses are presented and show significant reverberation reduction with little speech distortion
Black Women Students at Predominantly White Universities: Narratives of Identity Politics, Well-Being and Leadership Mobility

This narrative inquiry study uses personal experiences as a method of ethnographic research among Black women student leaders. The collegiate life stories of six African American women undergraduates experiencing gendernoir racial battle fatigue are described and analyzed. Combined are participant journaling, lived experiential interviews, and organizational observations within various organizational situations. Participants’ narratives are presented to understand the process of enacting leadership within varied organizational contexts while experiencing racial and gender-racialized aggressions. A three-dimensional narrative inquiry is utilized to restory field texts. In this instance, narrative inquiry is applied to demonstrate how participants respond to the effects of cumulative racial stressors in ways that positively influence their practice of leadership. Emergent themes were as follows: (a) buffered leadership and (b) holistic leadership. Participants spoke of avoiding gender-racialized aggression by using buffered leadership to create proximal distance between themselves and adverse racial interactions with White males. Participants used holistic leadership to describe nuanced Black womanhood to White women peers to dismantle stereotypes and increase rapport.
SemVersion: A Versioning System for RDF and Ontologies

Knowledge domains and their semantic representations via ontologies are typically subject to change in practical applications. Additionally, engineering of ontologies often takes place in distributed settings where multiple independent users interact. Therefore, change management for ontologies becomes a crucial aspect for any kind of ontology management environment. This paper introduces a new RDF-centric versioning approach and an implementation called SemVersion. SemVersion provides structural and semantic versioning for RDF models and RDFbased ontology languages like RDFS. The requirements for our system are derived from a practical scenario in the librarian domain, i.e. the
Synchrony and Sympathy: Social Entrainment With Music Compared to a Metronome

Interpersonal synchronization of movements, such as walking at the same pace or dancing to the same beat, can strengthen pro-social behavior and affiliation. People all over the world come together every now and then to become entrained with a shared musical rhythm. Thus, the social and emotional power of music might further tighten interpersonal bonds. In the current study, we investigated whether social entrainment affects affiliation and helpfulness more strongly when tapping to music compared with a metronome. The between-subjects design consisted of four groups: tapping to the beat of music or to an isochronous metronome with an experimenter who tapped synchronously or asynchronously. The results of an implicit test showed that when listening to music, participants were more helpful toward a person who tapped synchronously compared with asynchronously. No such effect was found when listening and tapping to a metronome. The results of explicit ratings of the experimenter’s likability, however, did not confirm this effect. Music is a product of social interactions and might even be the result of evolutionary adaptation. Thus, we conclude that interpersonal synchrony or asynchrony during listening to music can fulfill or violate hard-wired social expectations. Compared with the experience of just moving in synchrony with a simple isochronous timekeeper, such as a metronome, social entrainment with music might increase social bonding by adding an extra layer of affective and neurophysiological mechanisms. The current experiment additionally shows that implicit or indirect measures can help elucidate how music, entrainment, affiliation, and pro-social behavior are connected.
Testing for Random Walk Coefficients in a Simple State Space Model

Three diierent tests for random walk coeecients in linear regression models have become popular: The LaMotte & McWhorter 1978] F-tests, the LBI test by Nyblom & MM akell ainen 1983], and the POI test by King 1980], especially in the version of Shively 1988]. This paper extends these traditional tests for random walk coeecients in linear regression models to more general models. More precisely, the assumption that under the null hypothesis all regression coeecients are constant over time is given up. These adapted tests are designed for situations where we already know that some coeecients follow a random walk. Hereby one will be enabled to test for random walk coeecients successively. As in other similar contexts, the problem arises of how to handle nuisance parameters. Three diierent methods are proposed and it is shown in a simulation study that these methods hardly aaect the good power properties of the tests proposed. These tests will be compared to the Marginal Likelihood based Lagrange Multiplier (MLLM) test by Rahman & King 1993a]. All methods proposed here may easily be extended to more general situations. I like to thank Helmut L utkepohl, Pentti Saikkonen, Timo Terr asvirta and Rolf Tschernig for very helpful comments on a previous version of this paper. The research was carried out within the Sonderforschungsbereich 373 at the Humboldt University Berlin and was printed using funds made available by the Deutsche Forschungsgemeinschaft.
Regression Testing Techniques for Agent Oriented Software

- In recent years, agent-based systems have received considerable attention in both academics and industry. The agent-oriented paradigm can be considered as a natural extension of the object-oriented (OO) paradigm. In this paper, a procedure using message flow graph (MFG) for regression testing of agent oriented software systems is proposed. This method however can be used when the interaction pattern of an agent changes. Furthermore a procedure for selection of modification-traversing regression test cases using execution trace is proposed. For illustration purpose, a multi agent air ticket booking system is implemented using JADE 3.5 and tested using our proposed methods.
Adaptation of a Key Phrase Extractor for Japanese Text

This paper presents some statistical observation relevant to Japanese keyphrase extraction, as well as the details of the implementation of a keyphrase extraction algorithm (called Extractor) for Japanese documents. Parts of the algorithm include an efficient method of extracting the keyphrase candidates, a way to pinpoint the most probable keyphrases using contextual information.
Computational Statistics and Data Analysis Reference Analysis for Birnbaum–saunders Distribution

In this paper we consider the Bayesian estimators for the unknown parameters of the Birnbaum–Saunders distribution under the reference prior. The Bayesian estimators cannot be obtained in closed forms. An approximate Bayesian approach is proposed using the idea of Lindley and Gibbs sampling procedure is also used to obtain the Bayesian estimators. These results are compared using Monte Carlo simulations with the maximum likelihood method and another approximate Bayesian approach Laplace's approximation. Two real data sets are analyzed for illustrative purposes.
Stress Appraisal, Coping Behaviors, and Level of Distress in an Ethnically Diverse Sample of Mothers with a Child in the Pediatric Intensive Care Unit

of a dissertation at the University of Miami. Dissertation supervised by Professor Jessica Roberts Williams. No. of pages in text. (124) Having a child in the Pediatric Intensive Care Unit (PICU) places parents at risk for Acute Stress Disorder (ASD) symptoms. ASD symptoms, or primary negative responses to a traumatic event, may increase parents’ risk for developing long-term Posttraumatic Stress Disorder (PTSD) one or more months later. The purpose of this study is to examine the stress appraisal, coping behaviors, and level of distress due to ASD in an ethnically diverse sample of mothers with a child in the PICU, while controlling for socioeconomic factors. A quantitative cross-sectional design, which surveyed mothers with a child age one day to 17 years in the intensive care unit, was used for this study. The instruments included in the survey were a Parent Demographic Sheet, the Pediatric Stressor Scale: Pediatric Intensive Care Unit, the Brief COPE, and the Acute Stress Disorder Scale. Results of this study add to the literature on parental stress and coping behaviors of minority mothers with a child in the PICU and can be used to guide culturally tailored nursing interventions to improve coping and decrease ASD symptoms in this population of mothers.
Leveraging Zipf's law for traffic offloading

Internet traffic has Zipf-like properties at multiple aggregation levels. These properties suggest the possibility of offloading most of the traffic from a complex controller (e.g., a software router) to a simple forwarder (e.g., a commodity switch), by letting the forwarder handle a very limited set of flows; the heavy hitters. As the volume of traffic from a set of flows is highly dynamic, maintaining a reliable set of heavy hitters over time is challenging. This is especially true when we face a volume limit in the non-offloaded traffic in combination with a constraint in the size of the heavy hitter set or its rate of change. We propose a set selection strategy that takes advantage of the properties of heavy hitters at different time scales. Based on real Internet traffic traces, we show that our strategy is able to offload most of the traffic while limiting the rate of change of the heavy hitter set, suggesting the feasibility of alternative router designs.
Mining Energy-Aware Commits

Over the last years, energy consumption has become a first-class citizen in software development practice. While energy-efficient solutions on lower-level layers of the software stack are well-established, there is convincing evidence that even better results can be achieved by encouraging practitioners to participate in the process. For instance, previous work has shown that using a newer version of a concurrent data structure can yield a 2.19x energy savings when compared to the old associative implementation [75]. Nonetheless, little is known about how much software engineers are employing energy-efficient solutions in their applications and what solutions they employ for improving energy-efficiency. In this paper we present a qualitative study of "energy-aware commits". Using Github as our primary data source, we perform a thorough analysis on an initial sample of 2,189 commits and carefully curate a set of 371 energy-aware commits spread over 317 real-world non-trivial applications. Our study reveals that software developers heavily rely on low-level energy management approaches, such as frequency scaling and multiple levels of idleness. Also, our findings suggest that ill-chosen energy saving techniques can impact the correctness of an application. Yet, we found what we call "energy-aware interfaces", which are means for clients (e.g., Developers or end-users) to save energy in their applications just by using a function, abstracting away the low-level implementation details.
Total Bregman divergence and its applications to shape retrieval

Shape database search is ubiquitous in the world of bio-metric systems, CAD systems etc. Shape data in these domains is experiencing an explosive growth and usually requires search of whole shape databases to retrieve the best matches with accuracy and efficiency for a variety of tasks. In this paper, we present a novel divergence measure between any two given points in Rn or two distribution functions. This divergence measures the orthogonal distance between the tangent to the convex function (used in the definition of the divergence) at one of its input arguments and its second argument. This is in contrast to the ordinate distance taken in the usual definition of the Bregman class of divergences [4]. We use this orthogonal distance to redefine the Bregman class of divergences and develop a new theory for estimating the center of a set of vectors as well as probability distribution functions. The new class of divergences are dubbed the total Bregman divergence (TBD). We present the l\-norm based TBD center that is dubbed the t-center which is then used as a cluster center of a class of shapes The t-center is weighted mean and this weight is small for noise and outliers. We present a shape retrieval scheme using TBD and the t-center for representing the classes of shapes from the MPEG-7 database and compare the results with other state-of-the-art methods in literature.
Optimization of the Fast Retrial Algorithm in OFDMA Wireless Networks

Random access strategies have been applied to various wireless systems for a long time. Recently, the fast retrial algorithm has been proposed to improve the performance of random access in orthogonal frequency-division multiple access (OFDMA) system. This paper studies the performance of the OFDMA system with the fast retrial algorithm when the number of subchannels can be adjustable depending on traffics, and also the relationship between the number of subchannels and throughput of each subchannel.
The effect of representative training dataset selection on the classification performance of the promoter sequences

Promoter prediction is an important task for genome annotation. The aim of this study is to build a classification method for promoter prediction. Base-stacking energy values of dinucleotides are used for feature extraction and Support Vector Machines (SVMs) are used for classification. Human genome promoter sequences are used as the positive training data and three types of datasets are prepared as the negative data including intergenic and transcribed sequences. Best results are achieved by selecting equal number of random sequences from intergenic and transcribed sequences while preparing the negative datasets.
No change in the regional distribution of tidal volume during lateral posture in mechanically ventilated patients assessed by electrical impedance tomography

We assessed the distribution of regional lung ventilation during moderate and steep lateral posture using electrical impedance tomography (EIT) in mechanically ventilated patients. Seven patients were placed on a kinetic treatment table. An elastic belt containing 16 electrodes was placed around the chest and was connected to the EIT device. Patients were moved to left and right lateral positions in a stepwise (10°) mode up to 60°. EIT images [arbitrary units (AU)] were generated and scanned for assessment of relative ventilation distribution changes [tidal volume (VT)]. A calibration procedure of arbitrary units (AUs) versus ventilator‐derived VT performed in all patients during three predefined positions (supine, 60°‐left dependent and 60°‐right‐dependent) showed a significant correlation between VT in supine, left and right lateral positions with the corresponding AUs (r2 = 0·356, P<0·05). Changes in VT were calculated and compared to supine position, and specific regions of interest (ROIs) were analysed. In our study, in contrast to recent findings, a change in lateral positions did not induce a significant change in regional tidal volume distribution. In right lateral positions, a broader variation of VT with a trend towards an increase in the dependently positioned lung was observed in comparison with supine. Lateral positioning promotes the redistribution of ventilation to the ventral regions of the lung. The use of EIT technology might become a helpful tool for understanding and guiding posture therapy in mechanically ventilated patients.
The instability of planetary systems in binaries: how the Kozai mechanism leads to strong planet-planet interactions

In this Letter we consider the evolution of a planetary system around a star inside a wide binary. We simulate numerically the evolution of the planetary orbits for both coplanar and highly inclined systems. We find that the Kozai mechanism operates in the latter case. This produces a highly eccentric outer planet the orbit of which crosses those of some of the inner planets. Strong planet-planet interactions then follow, resulting in the ejection of one or more planets. We note that planetary systems resembling our Solar system, formed around single stars in stellar clusters, may exchange into binaries and thus will be vulnerable to planet stripping. This process will reduce the number of Solar system-like planetary systems, and may produce at least some of the observed extrasolar planets. (Less)
Fast Algorithms for k-Word Proximity Search

When we search from a huge amount of documents, we often specify several keywords and use conjunctive queries to narrow the result of the search. Though the searched documents contain all keywords, positions of the keywords are usually not considered. As a result, the search result contains some meaningless documents. It is therefore effective to rank documents according to proximity of keywords in the documents. This ranking is regarded as a kind of text data mining. In this paper, we propose two algorithms for finding documents in which all given keywords appear in neighboring places. One is based on plane-sweep algorithm and the other is based on divide-and-conquer approach. Both algorithms run in O(n log n) time where n is the number of occurrences of given keywords. We run the algorithms on a large collection of html files and verify its effectiveness. key words: proximity search, text retrieval, plane-sweep, divideand-conquer
Using consensus measures for atlas construction

Atlas-based segmentation has been shown to provide promising results to delineate critical structures for radiotherapy planning. However, it requires to have a reference image with its reference segmentation available. Classical methods used to build an average segmentation can lead to over-segmentation in case of high variability among the manual segmentations. We propose in this paper a consensus-based approach to construct a reference segmentation from a database of manually delineated images. We first compute local consensus measures to estimate a variability map, and then deduct from it a consensus segmentation. Finally, the proposed method is evaluated using a dataset of 64 manually delineated images of the head and neck region.
Association of the c.385C>A (p.Pro129Thr) polymorphism of the fatty acid amide hydrolase gene with anorexia nervosa in the Japanese population

The functional c.385C>A single‐nucleotide polymorphism (SNP) in the fatty acid amide hydrolase (FAAH) gene, one of the major degrading enzymes of endocannabinoids, is reportedly associated with anorexia nervosa (AN). We genotyped the c.385C>A SNP (rs324420) in 762 lifetime AN and 605 control participants in Japan. There were significant differences in the genotype and allele frequencies of c.385C>A between the AN and control groups. The minor 385A allele was less frequent in the AN participants than in the controls (allele‐wise, odds ratio = 0.799, 95% confidence interval [CI] 0.653–0.976, P = 0.028). When the cases were subdivided into lifetime restricting subtype AN and AN with a history of binge eating or purging, only the restricting AN group exhibited a significant association (allele‐wise, odds ratio = 0.717, 95% CI 0.557–0.922, P = 0.0094). Our results suggest that having the minor 385A allele of the FAAH gene may be protective against AN, especially restricting AN. This finding supports the possible role of the endocannabinoid system in susceptibility to AN.
On the Pitfalls of Measuring Aid

Aid (ODA, Official Development Assistance) statistics are routinely produced by the Development Assistance Committee (DAC) of the OECD on the basis of data provided by bilateral donor agencies and using definitions and guidelines that represent a broad donor consensus. The use of new aid instruments, such as debt relief, has led to several changes and additions to DAC procedures over the years, but the underlying principles and methodology has remained unchanged since the early 1960s. Recent World Bank staff research proposes a more radical departure, introducing the concept of EDA, ‘Effective Development Assistance’. We use this recent contribution as a starting point to make a more thorough assessment of the methodology used to measure aid in general, and ODA in particular. The methodology is applied to some typical aid instruments, such as tied technical assistance, concessional loans and debt forgiveness. We illustrate that alternative aid measures can make a considerable difference on how we look on aid volumes and trends.