Miracle-dz/UniFAR-FTUs huggingface dataset:
Acoustic Simulations of Cochlear Implants in Human and Machine Hearing Research

Cochlear implant is an instrument which can be implanted in the inner ear and can restore partial hearing to profoundly deaf people (Loizou, 1999a) (see Fig. 1). Acoustic simulations of cochlear implants are widely used in cochlear implant research. Basically, they are acoustic signals which simulate what the profoundly deaf people could hear when they wear cochlear implants. Useful conclusions can be deduced from the results of experiments performed with acoustic simulations of cochlear implants. There are two typical applications in cochlear implant research which use acoustic simulations of cochlear implants. In the first one, acoustic simulations of cochlear implants are used to define how many independent channels are needed in order to achieve high levels of speech understanding (Loizou et al., 1999). The second application of acoustic simulations in cochlear implants research is for determining the effect of electrode insertion depth on speech understanding (Baskent & Shannon, 2003; Dorman et al., 1997b). In this chapter, we review briefly these conventional applications of acoustic simulations in cochlear implants research and, on the other hand, introduce novel applications of acoustic simulations of cochlear implants, both in cochlear implants research and in other domains, such as automatic speech recognition (ASR) research. To this end, we present quantitative analyses on the fundamental frequency (F0) of the cochlear implant-like spectrally reduced speech (SRS) which are, essentially, acoustic simulations of cochlear implants (Loizou, 1999a). These analyses support the report of (Zeng et al., 2005), which was based on subjective tests, about the difficulty of cochlear implant users in identifying speakers. Following the results of our analyses, the F0 distortion in state-of-the-art cochlear implants is large when the SRS, which is acoustic simulation of cochlear implant, is synthesized only from subband temporal envelopes (Do, Pastor & Goalic, 2010a). The analyses revealed also a significant reduction of F0 distortion when the frequency modulation is integrated in cochlear implant, as proposed by (Nie et al., 2005). Consequently, the results of such quantitative analyses, performed on relevant acoustic traits, could be exploited to conduct subjective studies in cochlear implant research. On the other hand, we investigate the automatic recognition of the cochlear implant-like SRS. Actually, state-of-the-art ASR systems rely on relevant spectral information, extracted from original speech signals, to recognize input speech in a statistical pattern recognition framework. We show that from certain SRS spectral resolution, it is possible to achieve (automatic) recognition performance as good as that attained with the original clean speech even though the cochlear implant-like SRS is synthesized only from subband temporal envelopes of the original clean speech (Do, Pastor & Goalic, 2010b; Do, Pastor, Le Lan & Goalic, 2010). Basing on this result, a novel framework Acoustic Simulations of Cochlear Implants in Human and Machine Hearing Research
The phase study of PSF model in MR

Partially separable functions (PSF) has been admitted highly sparse sampling in k-t space and proved an effective way to achieve high spatiotemporal resolution. However, it is still unsure whether the PSF reconstructed algorithm effects a change of the phase of magnetic resonance (MR) image. In view of this, we simulated a series of images in which the phases of designed area were exponential changed. After sparse data sampling and reconstruction by PSF, the phase variations of these images were compared before and after PSF processing. Simulation results showed that the phases of these images were preserved after the PSF reconstruction.
Locomoting with Less Computation but More Morphology

Biped walking is one of the most graceful movements observed in humans. Today’s humanoid robots, despite their undeniably impressive performance, are still a long way from the elegance and grace found in Nature. To narrow the gap between natural and artificial systems, we propose to rely more on morphology, intrinsic dynamics, and less on raw computation. This paper documents a series of simulated and real “pseudo-passive” dynamic biped walkers in which computation is traded off for good morphology, that is, adequate mechanical design and appropriate material properties These two factors are parameterized, and the resulting solution space is explored in simulation. Interesting solutions are then realized in the real world. Our experiments show that successful pseudo-passive walkers with a good morphology locomote by converting oscillatory energy into forward movement.
School Attendance , Child Labor and Local Labor Markets in Urban Brazil

Prepared for presentation at the conference " Crises and Disasters: Measurement and Mitigation of their Human Costs " organized by the IDB and IFPRI. Abstract While the income (poverty) effect on child labor is long established as a main determinant of child labor, there is a growing body of literature considering the pull of the labor market. This paper demonstrates that ceteris paribus, employment rates for 14-16 year old boys and girls in urban Brazil increase as local labor market opportunities improve. Children are also more likely to leave school as local labor market conditions become more favorable. The effects of aggregate shocks on children's school and work behavior are examined with particular focus on whether the income effect or substitution effect dominates as macroeconomic conditions change over time. The study uses data from the Pesquisa Nacional Amostra de Domicilios, a large household survey that is conducted almost annually by the IBGE. We use variation in the urban areas of 25 states over 12 years to identify the aggregate effects.
A Network of Ontologies for the Integration of Planning and Scheduling Activities in Batch Process Industries

In the last decades, the integration of informatics applications sup- porting planning, scheduling and control has been a serious concern of the in- dustrial community. Many standards have been developed to tackle this issue by addressing the exchange of data between the scheduling function and its immediate lower and upper levels in the planning pyramid. However, a more comprehensive approach is required to tackle integration problems, since this matter entails much more than data exchange. So, this article presents an onto- logical framework that provides the foundations to reach an effective interoper- ability among the various applications linked to scheduling activities.
Optimal parameter selection of a Model Predictive Control algorithm for energy efficient driving of heavy duty vehicles

This paper presents an improved approach to the problem of energy efficient driving of heavy duty vehicles. The proposed model for a map-based Model Predictive Control (MPC) leads to an underlying Quadratic Programming (QP) optimization problem, allowing computationally efficient and robust solutions. A parameter estimation procedure is developed for a vehicle- and optimization-independent parametrization of the tradeoff between saving energy and keeping a desired vehicle velocity. Extensive simulations on a highway scenario for different optimization parameters give further insight to optimization properties, which can be utilized to enhance control performance. Compared to previous literature, we demonstrate a significant improvement of the computation time to under one-fifth of a millisecond, while maintaining (or even increasing) the fuel consumption reduction, which is 8.1 percent with the proposed approach compared to a standard cruise controller, without a decrease in the average cruising speed.
Maximum Likelihood Procedures for Estimating Genetic Parameters for Later Lactations of Dairy Cattle

An algorithm is presented for simultaneous estimation of variance and covariance components by restricted maximum likelihood in a two-way multivariate mixed model. In contrast to previous applications of restricted maximum likelihood the procedure accommodates environmental covariances between traits and also allows for different numbers of traits measured on different individuals. Results from an analysis of the first three lactation records of dairy cattle are given for a small set of data, and a computing strategy is described for this case.
A lightweight data integration architecture

Content syndication specifications such as Atom have become a popular mechanism to disseminate information across the Internet, with many sites providing Atom feeds for users to subscribe to and consume. Such a scenario typifies the originally intended use of Atom; however, our research has explored an alternative domain for this syndication technology. This research has evaluated Atom for its potential as a lightweight platform to support data integration from a set of data sources to a single target database. The implementation of the Atom-based architecture that we developed for this research combines freely available server-side scripting technology with the simplified asynchronous connection scheme that content syndication technology offers. We use several use cases each with different degrees of complexity, yet sharing common requirements, as a guide in the development of our prototype. In order to evaluate our Atom-based architecture, our experimental design required the construction of an evaluation framework that measured the prototype’s impact upon the network and computation resources it consumed. These measurements were compared with observations of response time requirements between operational and analytical processing systems. The experiments carried out to evaluate the Atom-based data integration architecture have shown that the architecture has potential in facilitating a lightweight data integration solution. Our research has shown that an Atom-based architecture is capable of operating within a range of conditions and environments, and with further development, would be capable of greater processing efficiency and wider compatibility with other types of data structures.
Approximation algorithms for partial covering problems ( Submission to ICALP 2001 , Track A )

We study the generalization of covering problems to partial covering. Here we wish to cover only a desired number of elements, rather than covering all elements as in standard covering problems. For example , in k-set cover, we wish to choose a minimum number of sets to cover at least k elements. For k-set cover, if each element occurs in at most f sets, then we derive a primal-dual f-approximation algorithm (thus implying a 2-approximation for k-vertex cover) in polynomial time. In addition to its simplicity, this algorithm has the advantage of being parallelizable. For instances where each set has cardinality at most three, we obtain an approximation of 4=3. We also present better-than-2-approximation algorithms for k-vertex cover on bounded degree graphs, and for vertex cover on expanders of bounded average degree. We obtain a polynomial-time approximation scheme for k-vertex cover on planar graphs, and for covering points in R d by disks.
MODIFIED HARMONY SEARCH ALGORITHM BASED UNIT COMMITMENT WITH PLUG-IN HYBRID ELECTRIC VEHICLES

Plug-in Hybrid Electric Vehicles (PHEV) technology shows great interest in the recent scientific literatures. Vehicle-to-grid (V2G) is a interconnection of energy storage of PHEVs and grid. By implementation of V2G dependencies of the power system on small expensive conventional units can be reduced, resulting in reduced operational cost. This paper represents an intelligent unit commitment (UC) with V2G optimization based on Modified Harmony Search Algorithm (MHSA). MHSA was conceptualized using the musical process of searching for a perfect state of harmony, just as the optimization process seeks to find a global solution that is determined by an objective function. Intelligent UC with V2G optimization in power system is presented in this paper. Since the number of PHEV in V2G is relatively high, UC with V2G optimization problem is more complex than the basic UC. A case study based on conventional 10-unit test system is conducted to facilitate the effectiveness of the proposed method. Results show a significant amount of cost reduction with integration of V2G in UC problem. Comparison of the results with those obtained by Particle Swarm Optimization shows the effectiveness of the proposed method.
Labor dynamics in a mobile micro-task market

The ubiquity of smartphones has led to the emergence of mobile crowdsourcing markets, where smartphone users participate to perform tasks in the physical world. Mobile crowdsourcing markets are uniquely different from their online counterparts in that they require spatial mobility, and are therefore impacted by geographic factors and constraints that are not present in the online case. Despite the emergence and importance of such mobile marketplaces, little to none is known about the labor dynamics and mobility patterns of agents. This paper provides an in-depth exploration of labor dynamics in mobile task markets based on a year-long dataset from a leading mobile crowdsourcing platform. We find that a small core group of workers (< 10%) account for a disproportionately large proportion of activity (> 80%) generated in the market. We find that these super agents are more efficient than other agents across several dimensions: a) they are willing to move longer distances to perform tasks, yet they amortize travel across more tasks, b) they work and search for tasks more efficiently, c) they have higher data quality in terms of accepted submissions, and d) they improve in almost all of these efficiency measures over time. We find that super agent efficiency stems from two simple optimizations --- they are 3x more likely than other agents to chain tasks and they pick fewer lower priced tasks than other agents. We compare mobile and online micro-task markets, and discuss differences in demographics, data quality, and time of use, as well as similarities in super agent behavior. We conclude with a discussion of how a mobile micro-task market might leverage some of our results to improve performance.
Identification of Novel IL-4/Stat6-Regulated Genes in T Lymphocytes1

IL-4, primarily produced by T cells, mast cells, and basophiles, is a cytokine which has pleiotropic effects on the immune system. IL-4 induces T cells to differentiate to Th2 cells and activated B lymphocytes to proliferate and to synthesize IgE and IgG1. IL-4 is particularly important for the development and perpetuation of asthma and allergy. Stat6 is the protein activated by signal transduction through the IL-4R, and studies with knockout mice demonstrate that Stat6 is critical for a number of IL-4-mediated functions including Th2 development and production of IgE. In the present study, novel IL-4- and Stat6-regulated genes were discovered by using Stat6−/− mice and Affymetrix oligonucleotide arrays. Genes regulated by IL-4 were identified by comparing the gene expression profile of the wild-type T cells induced to polarize to the Th2 direction (CD3/CD28 activation + IL-4) to gene expression profile of the cells induced to proliferate (CD3/CD28 activation alone). Stat6-regulated genes were identified by comparing the cells isolated from the wild-type and Stat6−/− mice; in this experiment the cells were induced to differentiate to the Th2 direction (CD3/CD28 activation + IL-4). Our study demonstrates that a number a novel genes are regulated by IL-4 through Stat6-dependent and -independent pathways. Moreover, elucidation of kinetics of gene expression at early stages of cell differentiation reveals several genes regulated rapidly during the process, suggesting their importance for the differentiation process.
A novel worst-case robust beamformer based on interference-plus-noise covariance reconstruction and uncertainty level estimation

A variant of adaptive worst-case (WC) beamformer is devised in this paper, which is robust against arbitrary unknown signal steering vector (SSV) mismatches. Compared with the conventional WC beamforming approach, the proposed method is further improved in terms of robustness by reconstructing the interference-plus-noise covariance matrix (IN-CM) and adaptively adjusting the uncertainty level of the SSV errors. In particular, the INCM is obtained by using the Capon spatial spectrum as the power distribution, and then the uncertainty level is estimated by maximizing the output power. Simulation results are included to illustrate the superiority of the proposed method.
Proceedings of Freenix Track: 2000 Usenix Annual Technical Conference

Swarm [3] is a storage system for Linux that provides scalable, reliable, and cost-e ective data storage. At its lowest level, Swarm implements a logstructured interface to a cluster of storage devices. Above the log, Swarm provides an infrastructure that allows high-level abstractions and functionality to be implemented easily and eÆciently. This paper describes the design and implementation of Swarm, paying particular attention to the Swarm infrastructure and how it has been used to construct two storage systems: Sting, a log-structured le system for Linux, and ext2fs/Swarm, a Swarm-based version of the Linux ext2 le system that runs unmodi ed above a block device compatibility layer. The paper concludes with a discussion of our experiences using Linux as a platform for research.
Modelling pitch accent types for Polish speech synthesis

We describe a Polish prosody modelling module for the Festival speech synthesis system. The module uses classification and regression trees for accent type prediction and a linear regression technique for F0 contour generation for these contours. The techniques used to attempt to overcome problems with the only available data are shown. We demonstrate how improvements were achieved by the use of a modified F0 stylisation, accent type clustering and language specific features. Results of a formal perception study show a significant preference for the new intonation model over the original one.
A hand posture recognition system utilizing frequency difference of infrared light

Hand gesture is one of the most effective methods to perform interactions between humans and also between humans and computers. However, currently existing depth cameras do not provide sufficient resolution and precision for effectively recognizing hand postures in distance (>2 meters). Existing researches tried to solve the limitation by using a combination of depth information and color information. However, they all could not have stable performance, because the color information is naturally affected by visible light condition. In this paper, we introduce a hardware system and an algorithm to recognize hand postures of a distant user while guaranteeing its performance even in the dark. Specifically, by utilizing infrared(IR) lights and their frequency difference, our system simultaneously gathers a depth map from Kinect and a high resolution IR image of a scene from an additional IR camera without any interference. The system analyzes the IR image of a hand using histogram of oriented gradients and support vector machine. In addition, the recognition system has a technique to compensate errors of hand position estimation unavoidable in any hand detection algorithms. As a result, from the experiment on real-time data, the proposed system classifies seven different hand postures with an average precision rate of 92.17% and the precision rate is maintained in the dark (<5 lux) with an average precision rate of 93.28%.
Interaction Of Presentations About The Personality Traits And Self-Assessment Of Success

The study objectives were: 1) the comparison of the actual and ideal self-image with the life satisfaction (LS) and with the self-assessment of success in professional activity and in life in general; 2) the analysis of the desirable changes in the personality traits of respondents and their co-twins. Survey sample – 136 members of female monozygotic twin pairs aged 18-46 years. The self-image as well as the desirable changes of personality traits were diagnosed by semantic differential method, LS – with the SWLS (E.Diener), a success self-assessment – using Dembo's scales on which the respondents marked their place among the other people. It was shown that there are some age-related changes of an ideal self-image, connected, first of all, with the increasing attractiveness of some negative personality characteristics. The research subjects estimate themselves as more disturbing and less attractive to people as well as less persistent and avoiding conflicts than their brothers and sisters. There were identified five generalized factors: Goodwill; Insecurity; Perseverance; Authoritativeness; Emotionality. Insecurity demonstrated the closest relationship with the life satisfaction. The greater life satisfaction corresponds as well the desire to have less Goodwill and less Perseverance. The direction of the own desirable changes and of the co-twin ones are identical, except for Authoritativeness. The respondents themselves want do not to be afraid of conflict situations, to be able to insist on their own. They would like to see their co-twin more gentle and compliant. The study confirms the hypothesis of the adaptive nature of negative personality characteristics.
Developing a Program to Strengthen Learning Leadership of School Principals under the Secondary Educational Service Areas

The purpose of this research was to develop the program on learning leadership strengthening for school principals under the secondary educational service areas. This study methodology was based on research and development (R&D) approach by the application of Participatory Action Research (PAR) with 4 phases. They were 1) finding the components and indicators of learning leadership, 2) study of the present and desirable condition of learning leadership, 3) developing learning leadership strengthening model, and 4) study of the implementation results program of learning leadership strengthening for school principals under the secondary educational service areas. The research findings reveal the program development comprises 70:20:10 ratio of learning leadership development—70 percent on the job experience and off the job experience, 20 percent professional learning community (PLC) process and personal feedback, and 10 percent training. The training involves 3 phases—phase 1 is training, phase 2 is integration with work practice, and phase 3 is follow up and evaluation.
¿Cómo evaluar la recuperación en salud mental?: Una revisión sistemática

There is an increasingly recognition of the concept of personal recovery in the treatment of mental illness. Recovery defined as living a fulfilling, rewarding life, even in the ongoing presence of a mental illness. Consequently, a number of different instruments have been designed to assess recovery-oriented outcomes. The objective of the study was to conduct a systematic revision of the domains and the instruments used to assess personal recovery and mental health services orientation to recovery. After the systematic review, it has been carried out a selection process of the most adequate instruments taking into account different criteria of adequacy, psychometric properties and the validation to the Spanish population. In the results have been obtained 35 instruments for measuring personal recovery and 18 for assessing the orientation of recovery in mental health services. However, many of them have been dismissed for not reaching the adequacy criteria. This review makes clear the lack of consensus on the concept of recovery, as a consequence of the high number of instruments that evaluate the same concept through different domains. In addition, few instruments offer data related to the psychometric properties and only one instrument to assess personal recovery is validated to the Spanish population.