Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantics and constraint parsing of word graphs

A constraint-based parser capable of processing a word graph containing multiple sentence hypotheses has been developed. When syntactic constraints are applied to a word graph, this parse is able to prune the graph of many ungrammatical sentence hypotheses and limit the possible parses of the remaining sentences. However, in many cases syntactic information alone is insufficient for selecting a single sentence hypothesis from a word graph. Hence, semantic constraints have been added to the parser to limit ambiguity further. The authors review the constraint parsing algorithm and then provide a simple example illustrating how syntactic and semantic features can be used to prune word candidates from a word graph and eliminate incorrect parses for the remaining sentences. They also report on the effectiveness of syntactic and semantic constraints for reducing the ambiguity of word networks constructed for N-best sentence hypotheses provided by the ATIS (Air Travel Information System) database. <<ETX>>
Placement method targeting predictability robustness and performance

We study the relationship between robustness, predictability and performance of VLSI circuits. It is shown that predictability and performance are conflicting objectives. Performance and robustness are statically conflicting objectives but they are statistically non-conflicting. We propose and develop means for changing a standard timing-driven partitioning-based placement algorithm in order to design more predictable and robust circuits without sacrificing much of performance.
SFTrust: A double trust metric based trust model in unstructured P2P system

The P2P system is an anonymous and dynamic system, which offers enormous opportunities, and also presents potential threats and risks. In order to restrain malicious behaviors in P2P system, previous studies try to establish efficient trust models on P2P system. However, most of the trust models use a single trust metric, which can not reflect the practical trust values of the peers effectively. In this paper, we propose a trust model called SFTrust based on a double trust metric. SFTrust separates trust between the service providing and feedbacking. The system is based on the topology adaptation protocol, which was proposed in the unstructured P2P system. Simulation results show that SFTrust can efficiently resist general attacks. Compared with the single trust metric model, our mechanism can take full advantages of all the peers' service abilities for high performance.
The ocean is not deep enough: pressure tolerances during early ontogeny of the blue mussel Mytilus edulis

Early ontogenetic adaptations reflect the evolutionary history of a species. To understand the evolution of the deep-sea fauna and its adaptation to high pressure, it is important to know the effects of pressure on their shallow-water relatives. In this study we analyse the temperature and pressure tolerances of early life-history stages of the shallow-water species Mytilus edulis. This species expresses a close phylogenetic relationship with hydrothermal-vent mussels of the subfamily Bathymodiolinae. Tolerances to pressure and temperature are defined in terms of fertilization success and embryo developmental rates in laboratory-based experiments. In M. edulis, successful fertilization under pressure is possible up to 500 atm (50.66 MPa), at 10, 15 and 20°C. A slower embryonic development is observed with decreasing temperature and with increasing pressure; principally, pressure narrows the physiological tolerance window in different ontogenetic stages of M. edulis, and slows down metabolism. This study provides important clues on possible evolutionary pathways of hydrothermal vent and cold-seep bivalve species and their shallow-water relatives. Evolution and speciation patterns of species derive mostly from their ability to adapt to variable environmental conditions, within environmental constraints, which promote morphological and genetic variability, often differently for each life-history stage. The present results support the view that a direct colonization of deep-water hydrothermal vent environments by a cold eurythermal shallow-water ancestor is indeed a possible scenario for the Mytilinae, challenging previous hypothesis of a wood/bone to seep/vent colonization pathway.
Image composition methods for sort-last polygon rendering on 2-D mesh architectures

In this paper, a new sort-last parallel polygon rendering implementation is given for 2-D mesh message-passing architectures such as the Ineel Delta and Paragon. Our implementation provides a very fast rendering rate for extremely large sets of polygons, a requirement of scientific visualization, C A D / C A M , and many other applications. We implement and evaluate our scheme on the Intel Delta parallel computer at Caltech. Using 512 processors to render Eric Haines's SPD s tandard scenes, our scheme achieves a rendering rate of 2.8 4.0 million triangles/second. K e y w o r d s : Polygon Rendering, SPD, Delta, Load Balancing
A Toolkit for Live Annotation of Opera Performance: Experiences Capturing Wagner's Ring Cycle

Performance of a musical work potentially provides a rich source of multimedia material for future investigation, both for musicologists’ study of reception and perception, and in improvement of computational methods applied to its analysis. This is particularly true of music theatre, where a traditional recording cannot sufﬁciently capture the ephemeral phenomena unique to each staging. In this paper we introduce a toolkit developed with, and used by, a musi-cologist throughout a complete multi-day production of Richard Wagner’s Der Ring des Nibelungen . The toolkit is centred on a tablet-based score interface through which the scholar makes notes on the scenic setting of the performance as it unfolds, supplemented by a variety of digital data gathered to structure and index the annotations. We report on our experience developing a system suitable for real-time use by the musicologist, structuring the data for reuse and further investigation using semantic web technologies, and of the practical challenges and compromises of ﬁeldwork within a working theatre. Finally we consider the utility of our tooling from both a user perspective and through an initial quantitative investigation of the data gathered.
Speaker Identification by GMM based i Vector

Speaker Identification process is to identify a particular vocal cord from a set of existing speakers. In the speaker identification processes, unknown speaker voice sample targets each of the existing speakers present in the system and gives a predication. The predication may be more than one existing known speaker voice and is very close to the unknown speaker voice. The model is a Gaussian mixture model built by the extracted acoustic feature vectors from voice. The i-vector based dimension compression mapping function of the channel depended speaker, and super vector give better predicted scores according to cosine distance scoring associated with the order pair of speakers. In the order pair, the first coordinate is the unknown speaker i.e. test speaker, and the second coordinates is the existing known speaker i.e. target speaker. This paper presents the enhancement of the prediction based on i- vector in compare to the normalized set of predicted score. In the simulation, known speaker voices are collected through different channels and in different languages. In the testing, the GMM voice models, and GMM based i-Vector speaker voice models of the known speakers are used among the numbers of clusters in the test data set.
Communications of the Association for Information Systems the Domain Name System—past, Present, and Future Recommended Citation the Domain Name System—past, Present, and Future the Domain Name System—past, Present, and Future the Domain Name System—past, Present, and Future

This material is brought to you by the Journals at AIS Electronic Library (AISeL). It has been accepted for inclusion in Communications of the Association for Information Systems by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact elibrary@aisnet.org. The Domain Name System (DNS) is a critical component of the global Internet infrastructure. Throughout its history, its design and administration has experienced significant dynamic changes as the Internet itself has evolved. The history of the DNS is divided into six eras, based on underlying technological and administrative themes within each era. Developments in its governance, its application, and in other factors are discussed. Future directions for DNS use and abuse are explored, along with challenges in its future governance. Finally, a proposed research model is included to guide future study of the DNS evolution and its influences from political, legal, psychological, sociological, and technological perspectives.
A Quasi-Doherty SOI CMOS Power Amplifier With Folded Combining Transformer

A fully integrated transformer-based quasi-Doherty power amplifier (DPA) with an adaptive power divider (APD) is presented in this paper. A novel folded combining transformer is designed for power combining, which has smaller insertion loss than a conventional one. An APD adaptively controls the power delivered to carrier and peaking amplifiers by altering the input impedance of the peaking amplifier, which has a variable resonance frequency that changes according to the input power. Most of the power is delivered to the carrier amplifier at low incoming power, and it is divided between the carrier and the peaking amplifiers at high incoming power. With continuous wave signal at 1850 MHz, the quasi-DPA implemented with an SOI CMOS process achieves 39.8% and 44.4% power-added efficiencies (PAEs) at the first and the second peak, respectively. With wideband code division multiple access signal, it has 29.2-dBm average linear output power and a 40.47% PAE with a -33-dBc adjacent channel leakage ratio 1. With long-term evolution (LTE) signal, it delivers 27.2-dBm average linear output power and a 37.7% PAE, satisfying linearity requirements for the LTE.
Gut Bacterial Metabolism of the Soy Isoflavone Daidzein: Exploring the Relevance to Human Health

The indigenous intestinal microflora are involved in a variety of processes within the human body, and are important for maintaining host health. As such, interindividual differences in the ability to harbor certain intestinal bacteria might be associated with interindividual differences in health and/or disease susceptibility. In the last decade there has been considerable interest in phytoestrogen intakes in relation to human health. Daidzein, an isoflavone phytoestrogen found in soy, is metabolized to equol and O-desmethylangolensin (O-DMA) by intestinal bacteria. The specific bacterium/bacteria responsible for equol and O-DMA production in humans have yet to be identified definitively, but in vitro and animal studies have suggested that equol and O-DMA are more biologically active than their precursor daidzein. Interestingly, substantial interindividual differences in daidzein metabolism exist; following soy or daidzein consumption, approximately 30%–0% of the human population produce equol, and approximately 80%–90% produce O-DMA. Observational and intervention studies in humans have suggested that the ability to produce equol and O-DMA may be associated with reduced risk of certain diseases including breast and prostate cancers. However, relatively few studies have been conducted to date. In this review, we discuss the available evidence for a relationship between daidzein-metabolizing phenotypes and human health, and suggest potential mechanisms for some of the reported relationships.
Detection Performance with Many Antennas Available for Bandwidth-Efficient Uplink Transmission in MU-MIMO Systems

This paper is concerned with SC/FDE for bandwidth-efficient uplink block transmission, with QAM schemes, in a MU MIMO system. The number of BS receiver antennas is assumed to be large, but not necessarily much larger than the overall number of transmitter antennas jointly using the same time/frequency resource at MT. In this context, we consider several detection techniques and evaluate, in detail, the corresponding detection performances (discussed with the help of selected performance bounds), for a range of values regarding the number of available BS receiver antennas. From our performance results, we conclude that simple linear detection techniques, designed to avoid the need of complex matrix inversions, can lead to unacceptably high error floor levels. However, by combining the use of such simple linear detectors with an appropriate interference cancellation procedure - within an iterative DF technique -, a close approximation to the SIMO MFB performance can be achieved after a few iterations, even for 64-QAM schemes, when the number of BS antennas is, at least, five times higher than the number of antennas which are jointly used at the user terminals.
Daydreams and the True Self

The feeling of knowing and expressing one’s true self (i.e., authenticity) is a critical component of well-being. This research examined how patterns of inner mental experience, or daydreaming styles, relate to differences in authenticity. In two online studies, participants completed a series of personality measures, including measures of daydreaming styles and authenticity. Study 1 (N = 201) and Study 2 (N = 203) generally supported our hypotheses. Positive constructive daydreaming predicted greater feelings of authentic living and lower feelings of true self-alienation, and guilty/fear-of-failure daydreaming predicted lower levels of authentic living and greater feelings of both true self-alienation and acceptance of external influence. Moreover, we found that poor attentional control was a consistent positive predictor of true self-alienation and a weak predictor of acceptance of external influence. These findings offer novel insight into how daydreaming relates to people’s subjective sense of knowing and being who they truly are.
Interactive Encoding and Decoding for One Way Learning: Near Lossless Recovery With Side Information at the Decoder

A source coding paradigm called interactive encoding and decoding (IED) is considered for a source network where a finite alphabet source <i>X</i> is to be encoded, and another finite alphabet source <i>Y</i> correlated with <i>X</i> is available only to the decoder as a helper. The optimal performance achievable asymptotically (OPAA) by IED is investigated, where the performance is measured as the average number of bits per symbol exchanged by the encoder and decoder until the decoder learns <i>X</i> with high probability. First, it is shown that for any stationary <i>(X</i>, <i>Y</i>), the OPAA by IED is given by the conditional entropy rate <i>H</i>(<i>X</i>|<i>Y</i>) of <i>X</i> given <i>Y</i>. This is in contrast with noninteractive Slepian-Wolf (SW) coding, where the OPAA is shown in general to be strictly greater than <i>H</i>(<i>X</i>|<i>Y</i>) when <i>(X</i>, <i>Y</i>) is not ergodic. Second, for a memoryless source pair (<i>X, Y</i>), it is shown that IED approaches <i>H</i>(<i>X</i>|<i>Y</i>) faster than SW coding does. Finally, it is demonstrated that one can convert any classical universal data compression algorithm with side information to a universal IED algorithm for the class <i>¿</i> of all stationary ergodic source pairs. In contrast, universal SW coding algorithms for the class <i>¿</i> do not exist.
On Nonparametric Bayesian Inference for theDistribution of a Random

The nonparametric Bayesian approach for inference regarding the unknown distribution of a random sample customarily assumes that this distribution is random and arises through Dirichlet process mixing. Previous work within this setting has focused on the mean of the posterior distribution of this random distribution which is the predictive distribution of a future observation given the sample. Our interest here is in learning about other features of this posterior distribution as well as about posteriors associated with functionals of the distribution of the data. We indicate how to do this in the case of linear functionals. An illustration, with a sample from a Gamma distribution, utilizes Dirichlet process mixtures of normals to recover this distribution and its features.
Multilevel bandwidth measurements and capacity exploitation in gigabit passive optical networks

The authors report an experimental investigation on the measurement of the available bandwidth for the users in gigabit passive optical networks (GPON) and the limitations caused by the Internet protocols, and transfer control protocol (TCP) in particular. We point out that the huge capacity offered by the GPON highlights the enormous differences that can be showed among the available and actually exploitable bandwidth. In fact, while the physical layer capacity can reach value of 100 Mb/s and more, the bandwidth at disposal of the user (i.e. either throughput at transport layer or goodput at application layer) can be much lower when applications and services based on TCP protocol are considered. In the context of service level agreements (SLA) verification, we show how to simultaneously measure throughput and line capacity by offering a method to verify multilayer SLA. We also show how it is possible to better exploit the physical layer capacity by adopting multiple TCP connections avoiding the bottleneck of a single connection.
The Harmless Drudge:Defining Ethnomusicology

This essay talked about the multiplicity of the definitions of ethnomusicology,the different ways of defining a discipline,the history of the term "ethnomusicology",the principal activities of ethnomusicologists,and the kinds of people who eventually find themselves in this field. Beyond these,the author tried to give a two-pronged definition that is central to this book,and should like to tie it to four areas of belief: 1) Ethnomusicology is the study of music in culture;2) Ethnomusicology is the study of the world's musics from a comparative and relativistic perspective;3)Principally,ethnomusicology is study with the use of fieldwork;4) Ethnomusicology is the study of all of the musical manifestations of a society.
Content Bookmarking and Recommendation

Personalized services are increasingly becoming popular in the Internet. This work proposes a way of generating personalized content and simultaneously recommending users, web pages that, he/she might be interested in, based on his/her personalized content. In this work, we portray a system that not only helps the user in bookmarking the URL and snippets from the web page but also recommends web pages relevant to his/her interest. It applies a content-based filtering approach. We describe the details of the approach and implementation as well as address the challenges associated with it.
Differential privacy with δ-neighbourhood for spatial and dynamic datasets

Differential privacy provides a strong guarantee in protecting privacy of individuals who contributed to a published dataset. In this paper, we focus on spatial datasets and dynamic datasets, and attempt to exploit the intuition that farther-apart entities should have lesser influences to each other, and thus more privacy budget should be invested to protect close-by entities. To capture such intuition, we propose embedding the underlying spatial or temporal distance function into the notion of dataset neighbourhood. We called the proposed neighbourhood δ-neighbourhood, and discuss its implications in both spatial and dynamic datasets. For dynamic datasets, while there are known negative results on the standard differential privacy, it is possible to continuously and indefinitely publish under δ-neighbourhood by reusing the privacy budgets. Although known mechanisms, by definition, are also differentially private under δ-neighbourhood, they are not designed to exploit the relaxed notion for better utility. For spatial datasets, we propose an approach on 2D spatial points that re-allocates more budgets to nearby entities and thus obtains significantly higher utility. In addition, we give mechanisms that achieve "sustainable privacy" on dynamic datasets under both online and offline setting.
Lack of association between KIR genes and acute lymphoblastic leukemia in children.

To the editor: In a recent report, Almalte et al described novel associations between childhood acute lymphoblastic leukemia (ALL) and killer immunoglobulin-like receptor (KIR) genes in a case-control study including mostly French-Canadian patients. [1][1] The study was limited to the analysis of
Automated DSL construction based on software product lines

DSL (Domain-Specific Language) is one of the important approaches for software abstraction. In the past decades, DSLs have been provided by expert engineers familiar with domain knowledge and programming language processors. It is not easy for ordinary programmers to construct DSLs for their own purposes. To deal with this problem, we propose a language workbench called Argyle that can automatically generate a DSL by only specifying a set of functions needed to the DSL and an execution platform supported by the DSL. Argyle is based on software product lines and consists of the following two steps: 1) development of the core assets for constructing a family of DSLs and 2) DSL configuration using these core assets. To demonstrate the effectiveness of our approach, we developed a prototype DSL for supporting MSR (Mining Software Repositories), the most active research field in software engineering.
Genetic Programming Based Data Projections for Classification Tasks

In this paper we present a GP-based method for automatically evolve projections, so that data can be more easily classified in the projected spaces. At the same time, our approach can reduce dimensionality by constructing more relevant attributes. Fitness of each projection measures how easy is to classify the dataset after applying the projection. This is quickly computed by a Simple Linear Perceptron. We have tested our approach in three domains. The experiments show that it obtains good results, compared to other Machine Learning approaches, while reducing dimensionality in many cases. Keywords—Classification, Genetic Programming, projections.
Obtaining Accurate Neural Network Ensembles

The main contribution of this paper is to suggest a novel technique for automatic ensemble design, maximizing accuracy. The technique proposed first trains a large number of classifiers (here neural networks) and then uses genetic algorithms to select the members of the final ensemble. The proposed method, when evaluated on 22 publicly available data sets, results in ensembles obtaining very high accuracy, most often outperforming "typical standard ensembles". The study also shows that ensembles created using the straightforward approach of always selecting a fixed number (here five or ten) of top ranked networks results in very accurate ensembles. The conclusion is that the main reason for the increased accuracy is the possibility to select classifiers from a large pool. We argue that this is an important result, since it provides a data miner with an automatic tool for finding high-accuracy models, thus reducing the need for early decisions regarding techniques and model design
Trajectory following control of robotic manipulators using neural networks

A novel learning control architecture utilizing nonlinear computational properties of neural networks is presented. The nonlinear dynamics of the manipulator is assumed to be unknown, and the control scheme efficiently learns the required feedforward torques for a specified trajectory after a repeated number of trials. Simulation tests give promising results for real-time implementation of the algorithm. <<ETX>>