Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive log-spectral regression for in-car speech recognition using multiple distributed microphones

This letter addresses issues in improving hands-free speech recognition performance in different car environments. We propose a new speech-enhancement approach based on optimizing regression of the log-spectra, which is used to estimate the log-spectra of speech at a close-talking microphone by using multiple spatially distributed microphones. The regression weights can be adapted automatically for different noise environments. Compared to the nearest distant microphone and adaptive beamformer generalized sidelobe canceller (GSC), the proposed approach shows an advantage in the average relative word error rate (WER) reduction of 58.5 and 10.3%, respectively, for isolated word recognition under 15 real-car environments.
The Effect Of A Self-affirmation Manipulation On Threat Processing, Drinking Behaviour, And Implicit Responses To Alcohol Cues In Hazardous Drinkers

This thesis aims to add to the literature on self-affirmation as a means of reducing derogation of health risk messages, and engendering behaviour change. By exclusively sampling university students who drink hazardously, this study is also intended to add to the evidence base regarding interventions for alcohol misuse in this high-risk group. Part 1 of the thesis reviews another type of intervention for student drinking, namely, parent-based interventions. Numerous experimental studies have been published in recent years which examine the efficacy of this type of intervention. Findings suggest that parental influence on young people can extend into late adolescence and the early twenties, and, consequently, delivering an intervention solely to parents can produce effects on youth alcohol misuse. Part 1 therefore aims to summarise what is known about these interventions thus far, and make recommendations for future research. Part 2 of the thesis reports an experimental study of the efficacy of a self-affirmation manipulation on derogation of a health risk message, as well as changes in drinking behaviour one week after the intervention. Furthermore, it describes the results of a test of the effects of self-affirmation on automatic approach-avoidance biases to alcohol-related stimuli, which were assessed using a Relevant-feature Stimulus-Response Compatibility task. The third part of the thesis critically appraises aspects of Part 2. It elaborates on the decision-making processes involved in choosing a measure of implicit cognition, and formulating a risk message. It also describes difficulties with recruitment and how these were addressed, and concludes with reflections on the work from a clinical perspective.
A comparison of methods for identification of early aspects

Aspects are tangled and scattered behaviours across a system. The identification of early aspects helps to separate these behaviours from the requirements and improve modularity in the design and implementation stages. In recent years, many methods for identification of crosscutting concerns have been proposed at the requirements level. This paper analyzes how these well-known Aspect-Oriented Requirements Engineering approaches address crosscutting concern and makes a comparison between these techniques.
A Syntactic Approach to Modularity in Denotational Semantics

This paper proposes a syntactic reformulation of the modular approach to Denotational Semantics in [Mog89a, Mog91a]. This reformulation is based on a duality between model constructions and translations of theories (often called relative interpretations), analogous to Gabriel-Ulmer duality. To demonstrate the simplicity and usability of the syntactic reformulation, we give a sample of theories and translations, which can be used to give semantics to concurrent languages (via translation into suitable metalanguages).
ShapeLearner: Towards Shape-Based Visual Knowledge Harvesting

Abstract. The explosion of images on the Web has led to a number of efforts to organize images semantically and compile collections of visual knowledge. While there has been enormous progress on categorizing entire images or bounding boxes, only few studies have targeted fine-grained image understanding at the level of specific shape contours. For example, given an image of a cat, we would like a system to not merely recognize the existence of a cat, but also to distinguish between the cat’s legs, head, tail, and so on. In this paper, we present ShapeLearner, a system that acquires such visual knowledge about object shapes and their parts. ShapeLearner jointly learns this knowledge from sets of segmented images. The space of label and segmentation hypotheses is pruned and then evaluated using Integer Linear Programming. ShapeLearner places the resulting knowledge in a semantic taxonomy based on WordNet and is able to exploit this hierarchy in order to analyze new kinds of objects that it has not observed before. We conduct experiments using a variety of shape classes from several representative categories and demonstrate the accuracy and robustness of our method.
Proximal psychiatric risk factors for suicidality in youth: the Great Smoky Mountains Study.

CONTEXT Psychiatric disorder is a major risk factor for suicidality but has poor positive predictive value. OBJECTIVES To characterize proximal risks for suicidality associated with anxiety, depressive, disruptive behavior, and substance use disorders, and to test whether there are critical combinations of disorders that discriminate at-risk youth independent of severity of psychopathology. DESIGN The Great Smoky Mountains Study, a representative sample of children and adolescents aged 9 to 16 years from the southeastern United States. Subjects and their parents were interviewed on multiple occasions from 1993 to 2000 about the subjects' recent psychiatric and suicidal history. SETTING An epidemiological sample of youth. PARTICIPANTS The sample included 1420 individual subjects with 6676 records across 8 waves of data collection. MAIN OUTCOME MEASURES Wanting to die, suicidal ideation, suicide plans, or suicide attempt during the past 3 months. RESULTS Eleven broad psychiatric profiles discriminated suicidal youth. Risk was greatest in association with current depression plus anxiety (specifically GAD [generalized anxiety disorder]) (odds ratio, 468.53) or depression plus a disruptive disorder (primarily ODD [oppositional-defiant disorder]) (odds ratio, 222.94). Unless comorbid, anxiety and substance use disorders were not proximally associated with suicidality. The severity of symptom-related impairment and, in some cases, total symptom load explained risk associated with all psychiatric profiles except depression plus anxiety, specifically GAD (adjusted odds ratio, 50.16). Severity of impairment and poverty defined by federal guidelines for families were both independent risk factors, irrespective of psychiatric profile. Suicidal youth without diagnosable disorders had subthreshold (mostly disruptive) disorders, disabling relationship difficulties, or psychiatric symptoms without associated impairment. CONCLUSIONS Severity of symptom-related impairment and total symptom load explained most of the risk for suicidality associated with current psychiatric disorders. Only depression plus GAD discriminated at-risk youth independent of severity of psychopathology.
Resource Sharing Usage Aware Resource Selection Policies for Backfilling Strategies

Job scheduling policies for HPC centers have been extensively studied in the last few years, specially backfilling based policies. Almost all of these studies have been done using simulation tools. All the existent simulators use the runtime (either estimated or real) provided in the workload as a basis of their simulations. In our previous work we analyzed the impact on system performance of considering the resource sharing of running jobs including a new resource model in the Alvio simulator. In this paper we present two new Resource Selection Policies that have been designed using the conclusions reached in our preliminary work. First, the Find Less Consume Distribution that attempts to minimize the job runtime penalty that an allocated job will experience. Based on the utilization status of the shared resources in current scheduling outcome and job resource requirements, the LessConsume policy allocates each job process to the free allocations in which the job is expected to experience the lowest penalties. Second, we have also described the Find Less Consume Threshold Distribution selection policy which finds an allocation for the job that satisfies the condition that the estimated job runtime penalty factor is lower than a given value Threshold.
Reassortment Networks for Investigating the Evolution of Segmented Viruses

Many viruses of interest, such as influenza A, have distinct segments in their genome. The evolution of these viruses involves mutation and reassortment, where segments are interchanged between viruses that coinfect a host. Phylogenetic trees can be constructed to investigate the mutation-driven evolution of individual viral segments. However, reassortment events among viral genomes are not well depicted in such bifurcating trees. We propose the concept of reassortment networks to analyze the evolution of segmented viruses. These are layered graphs in which the layers represent evolutionary stages such as a temporal series of seasons in which influenza viruses are isolated. Nodes represent viral isolates and reassortment events between pairs of isolates. Edges represent evolutionary steps, while weights on edges represent edit costs of reassortment and mutation events. Paths represent possible transformation series among viruses. The length of each path is the sum edit cost of the events required to transform one virus into another. In order to analyze ¿ stages of evolution of n viruses with segments of maximum length m, we first compute the pairwise distances between all corresponding segments of all viruses in O(m2n2) time using dynamic programming. The reassortment network, with O(¿n2) nodes, is then constructed using these distances. The ancestors and descendents of a specific virus can be traced via shortest paths in this network, which can be found in O(¿n3) time.
A new IFFT/FFT hardware implementation structure for OFDM applications

In OFDM applications, IFFT/FFT hardware in the transceiver is usually designed jointly to carry out IFFT and FFT functions for transmission and receiving processes, respectively. We present a new IFFT/FFT hardware implementation structure with less complexity for OFDM applications. The proposed method can be applied to existing various FFT algorithms while implementing the OFDM. The 64-point IFFT/FFT chips for the radix-4/2 and radix-2/4/8 algorithms based on the proposed scheme are implemented by using TSMC 0.35 /spl mu/m, TSMC 0.25 /spl mu/m and UMC 0.18 /spl mu/m CMOS technologies. The implementation results show that our method can achieve a less complexity and area-efficiency IFFT/FFT processor.
Energy priority scheduling for variable voltage processors

Clock (and voltage) scheduling is an important technique to reduce energy consumption of variable-voltage processors. It is difficult, however, to achieve good results at the OS and hardware level when applications show bursty behavior. We take the approach that such applications must be made power aware and specify their future demands to a central scheduler controlling the clock speed and processor voltage. This paper describes our energy priority scheduling (EPS) heuristic that orders tasks according to how tight their deadlines are and how often tasks overlap. We schedule low-priority tasks first, since they can be easily preempted to accommodate for high-priority tasks later. The EPS heuristic does not always yield the optimal schedule, but has low complexity and can be used as an incremental on-line algorithm. We implemented EPS on a StrongARM-based variable-voltage platform. Measurements show that EPS reduces energy consumption with 50% for a bursty video decoding application without missing any frame deadlines.
Velocity-based shock propagation for multibody dynamics animation

Multibody dynamics are used in interactive and real-time applications, ranging from computer games to virtual prototyping, and engineering. All these areas strive towards faster and larger scale simulations. Particularly challenging are large-scale simulations with highly organized and structured stacking. We present a stable, robust, and versatile method for multibody dynamics simulation. Novel contributions include a new, explicit, fixed time-stepping scheme for velocity-based complementarity formulations using shock propagation with a simple reliable implementation strategy for an iterative complementarity problem solver specifically optimized for multibody dynamics.
Draft: Subdivision Schemes for Variational Splines

The original theory of splines grew out of the study of simple variational problems. A spline was a function that minimized some notion of energy subject to a set of interpolation constraints. A more recent method for creating splines is subdivision. A spline is the limit of a sequence of functions, each related by some simple averaging rule. This paper shows that the two ideas are intrinsically related. Speciically, the solution space to a wide range of variational problems can be captured as spline spaces deened through subdivision.
Progression of Decomposed Situation Calculus Theories

In many tasks related to reasoning about consequences of a logical theory, it is desirable to decompose the theory into a number of components with weakly-related or independent signatures. This facilitates reasoning when signature of a query formula belongs to only one of the components. However, an initial theory may be subject to change due to execution of actions affecting features mentioned in the theory. Having once computed a decomposition of a theory, one would like to know whether a decomposition has to be computed again for the theory obtained from taking into account the changes resulting from execution of an action. In the paper, we address this problem in the scope of the situation calculus, where change of an initial theory is related to the well-studied notion of progression. Progression provides a form of forward reasoning; it relies on forgetting values of those features which are subject to change and computing new values for them. We prove new results about properties of decomposition components under forgetting and show when a decomposition can be preserved in progression of an initial theory.
Book Review: Using Mplus for structural equation modeling: A researcher’s guide

may well be on the right side of history, citing a Gallup poll indicating that 38% of Americans identify as conservative, compared to 34% independent and 24% liberal (p. 191). While polling has been volatile, depending on time and place, these differences are sizable, indicating that Brooks has the wind to his back. Thus, his concluding strategy for asserting a conservative replacement to the liberal welfare state is not misplaced. Certainly, the devil will be in the details, but Brooks has made a signal contribution to the Right’s cause with regard to social welfare, and liberals would be advised to read this book.
Effects of L-carnitine and L-acetyl-carnitine on testicular sperm motility and chromatin quality

Background: Sperm cells extracted from testes (TESE) have poor chromatin quality and motility. Various substances are used in the laboratory to increase sperm motility and improve the ART outcomes; however, there are few research which considered improving both sperm motility and chromatin quality. Objective: The aim of this investigation was to evaluate the improvement of the testicular sperm motility and chromatin quality exposed to L-carnitine (LC) and L-acetyl-carnitine (LAC), which are normally concentrated in testis and epididymis, compared with Pentoxifylline (PF), which used for sperm motility enhancement in IVF procedures. Materials and Methods: TESE samples from 30 male mice divided into four parts. The sperm samples were added to Ham' F10 (control) or the media contained 1.76mM of LC, LAC or PF), then, the samples were kept in the room temperature for 30, 90 and 180 min. At each time step, sperm motility and chromatin quality were assessed. Chromatin quality was evaluated by chromomycin A3 and aniline blue. Statistical analysis was performed using one way analysis of variance (ANOVA). A p-value less than 0.05 were accepted as a statistically significant difference. Results: The results showed LC, LAC and PF significantly increased the sperm motility. However, sperm chromatin quality only improved significantly by administration of LC and LAC. Conclusion: Administration of LC and LAC to the testicular sperm samples can lead to improve both sperm motility and chromatin quality. It may be because they can mimic in vivo sperm condition during late spermatogenesis.
SEW-ing a Simple Endorsement Web to incentivize trustworthy participatory sensing

Two crucial issues to the success of participatory sensing are (a) how to incentivize the large crowd of mobile users to participate and (b) how to ensure the sensing data to be trustworthy. While they are traditionally being studied separately in the literature, this paper proposes a Simple Endorsement Web (SEW) to address both issues in a synergistic manner. The key idea is (a) introducing a social concept called nepotism into participatory sensing, by linking mobile users into a social “web of participants” with endorsement relations, and (b) overlaying this network with investment-like economic implications. The social and economic layers are interleaved to provision and enhance incentives and trustworthiness. We elaborate the social implications of SEW, and analyze the economic implications under a Stackelberg game framework. We derive the optimal design parameter that maximizes the utility of the sensing campaign organizer, while ensuring participants to strictly have incentive to participate. We also design algorithms for participants to optimally “sew” SEW, namely to manipulate the endorsement links of SEW such that their economic benefits are maximized and social constrains are satisfied. Finally, we provide two numerical examples for an intuitive understanding.
The Moderating Effect of Online Purchase Experience on the Evaluation of Online Store Attributes and the Subsequent Impact on Market Response Outcomes

The purpose of this study was to propose and test an integrative theoretical model that allows one to determine the relative importance of online store attributes on market response outcomes (i.e., trust, satisfaction, and loyalty), and to examine the moderating effect of online purchase experience on the impact of online store attributes on trust and satisfaction. The empirical results showed that merchandising was the most important attribute to enhancing both trust and satisfaction, followed by security/privacy and order fulfillment. The findings also revealed that the source of consumer trust changes as consumer purchase experience increases, whereas the source of consumer satisfaction remains the same regardless of consumer purchase experience.
Neighbourhood Income Sorting and the Effects of Neighbourhood Income Mix on Income: A Holistic Empirical Exploration

An econometric model is specified in which an individual’s income and the income mix of the neighbourhood in which the individual resides are endogenous, thus providing a holistic model of phenomena that previously have been fragmented into neighbourhood effects and neighbourhood selection literatures. To overcome the biases from selection and endogeneity, the parameters of this model are estimated using instrumental variables in a fixed-effect panel analysis employing annual data on 90 438 working-age males in Stockholm over the 1995–2006 period. Evidence is found of both neighbourhood effects and neighbourhood selection, but more importantly, it is found that the magnitudes of these effects are substantially altered when taking selection and endogeneity biases into account, compared with when only controlling for selection. When taking endogeneity into account, the apparent impact of neighbourhood income mix on individual income is magnified and the effect of individual income on the percentage of high income in the neighbourhood is magnified.
The effects of bedroom air quality on sleep and next-day performance.

The effects of bedroom air quality on sleep and next-day performance were examined in two field-intervention experiments in single-occupancy student dormitory rooms. The occupants, half of them women, could adjust an electric heater to maintain thermal comfort but they experienced two bedroom ventilation conditions, each maintained for 1 week, in balanced order. In the initial pilot experiment (N = 14), bedroom ventilation was changed by opening a window (the resulting average CO2 level was 2585 or 660 ppm). In the second experiment (N = 16), an inaudible fan in the air intake vent was either disabled or operated whenever CO2 levels exceeded 900 ppm (the resulting average CO2 level was 2395 or 835 ppm). Bedroom air temperatures varied over a wide range but did not differ between ventilation conditions. Sleep was assessed from movement data recorded on wristwatch-type actigraphs and subjects reported their perceptions and their well-being each morning using online questionnaires. Two tests of next-day mental performance were applied. Objectively measured sleep quality and the perceived freshness of bedroom air improved significantly when the CO2 level was lower, as did next-day reported sleepiness and ability to concentrate and the subjects' performance of a test of logical thinking.
Hierarchical information fusion for human upper limb motion capture

Motion capture serves as a key technology in a wide spectrum of applications, including interactive game and learning, animation, film special effects, health-care and navigation. The existing human motion capture techniques, which use structured multiple high resolution cameras in the dedicated studio, are complicated and expensive. As rapid development of micro inertial sensors-on-chip, ubiquitous, real-time, and low cost human motion capture system using micro-inertial-sensors (MMocap) becomes possible. This paper presents a novel motion estimation algorithm by hierarchical fusion of sensor data and constraints of human dynamic model for human upper limb motion capture. Our method represents orientations of upper limb segments in quaternion, which is computationally effective and able to avoid singularity problem. To address the nonlinear human body segment motion, a particle filter is proposed to fuse 3D accelerometer and 3D micro-gyroscope sensor data to estimate upper limb motion recursively. Drift is the most challenging issue in motion estimation using inertial sensors. We present a novel solution by modeling the geometrical constraints in elbow joint and fuse these constraints to the particle filter process to compensate drift and improve the estimation accuracy. The experimental results have shown the feasibility and effectiveness of the proposed motion capture and analysis algorithm.
ALADIN: A scanner generator for incremental programming environments

A large number of scanner generators have been developed. Since they are restricted to the longest‐match rule, they are unsuitable for an incremental environment. We present the ALADIN system, which is able to deliver more than a single token if required. Thus, an ambiguity may be passed to the calling instance. Beyond this ‘incremental feature’, ALADIN is a well‐structured and easy‐to‐understand language. In contrast to existing systems, the desired behaviour of the generated scanners is completely specified explicitly. Thus, the specifications are more abstract than in other systems. A prototype implementation has shown that ALADIN‐generated scanners have about the same performance as those generated by Lex.