Miracle-dz/UniFAR-FTUs huggingface dataset:
Using boosting to improve a hybrid HMM/neural network speech recognizer

"Boosting" is a general method for improving the performance of almost any learning algorithm. A previously proposed and very promising boosting algorithm is AdaBoost. In this paper we investigate if AdaBoost can be used to improve a hybrid HMM/neural network continuous speech recognizer. Boosting significantly improves the word error rate from 6.3% to 5.3% on a test set of the OGI Numbers 95 corpus, a medium size continuous numbers recognition task. These results compare favorably with other combining techniques using several different feature representations or additional information from longer time spans. In summary, we can say that the reasons for the impressive success of AdaBoost are still not completely understood. To the best of our knowledge, an application of AdaBoost to a real world problem has not yet been reported in the literature either. In this paper we investigate if AdaBoost can be applied to boost the performance of a continuous speech recognition system. In this domain we have to deal with large amounts of data (often more than 1 million training examples) and inherently noisy phoneme labels. The paper is organized as follows. We summarize the AdaBoost algorithm and our baseline speech recognizer. We show how AdaBoost can be applied to this task and we report results on the Numbers 95 corpus and compare them with other classifier combination techniques. The paper finishes with a conclusion and perspectives for future work.
Dopamine Dynamics and Signaling in Drosophila: An Overview of Genes, Drugs and Behavioral Paradigms

Changes in dopamine (DA) signaling have been implicated in a number of human neurologic and psychiatric disorders. Similarly, defects in DA signaling in the fruit fly, Drosophila melanogaster, have also been associated with several behavioral defects. As most genes involved in DA synthesis, transport, secretion, and signaling are conserved between species, Drosophila is a powerful genetic model organism to study the regulation of DA signaling in vivo. In this review, we will provide an overview of the genes and drugs that regulate DA biology in Drosophila. Furthermore, we will discuss the behavioral paradigms that are regulated by DA signaling in flies. By analyzing the genes and neuronal circuits that govern such behaviors using sophisticated genetic, pharmacologic, electrophysiologic, and imaging approaches in Drosophila, we will likely gain a better understanding about how this neuromodulator regulates motor tasks and cognition in humans.
Adaptive multipath routing for network functions virtualization

Network Functions Virtualization (NFV) is a recent trend of network transformation that helps service providers offer new and multiple services in a more agile and cost effective way. However, the softwarization and cloudization of network functions can result in high congestion and low network performance for virtual networks. We develop a multipath routing solution for minimizing the maximum link utilization, thus leading to the performance improvement of NFV-based systems, as well as the efficient utilization of network resources. Our proposed algorithm can adapt the link weight system to the dynamic change of service demands for optimizing the distribution of network traffic, with regard to the fundamental NFV characteristics and the Equal-cost Multipath (ECMP) routing feature. The evaluation results show that the proposed solution outperforms a multipath solution with fixed link weight on various performance metrics. Interestingly, we find that the network performance is not significantly improved by increasing the number of paths beyond a threshold.
An encyclopedic approach for realization of security activities with agile methodologies

Agility among the software is searching concern during the development phase, as it boost adaptive planning, incremental and evolutionary development with many other features that are lightweight in nature. Security is one of the considerable concern in today's highly agile software development industry. More assertion is on to produce a protected software, so as to lessen the amount of risk and damage caused by the software. Evolving protected software with high agile characteristics is always a tough task to do because of heavy weight quality of security activities. This paper submit a innovative approach by which security activities can be combined with agile activities by calculating the mean agility value of both activities i.e. agile likewise security keeping in mind the aspects such as cost, time, recurrence, benefits affecting the agility of the activity. By accepting fuzzy value compatibility table (FVCT), rapport of embodiment of both the activities is done with fuzzy values.
Information Decay in Building Predictive Models Using Temporal Data

Most predictive data mining methods are based on the assumption that the historical data involved in building and verifying a model are the best estimator of what will happen in the future. However, the relevance of past to the future depends on the application domain in a specific timeframe. In this paper, we present a method of predicting the future from temporal data using information decay technique that estimate the relevance of the past to the future with the help of the knowledge of the information lifetime of the temporal data. We show how to use a decision tree data mining technique to build an information-decay-based predictive model by introducing an information decay method in impurity measure functions. The relevance of the concepts is proven by comparing two decision tree-based classifiers: one built using information decay over a specific timeframe and the other built setting aside the time factor.
UPFC Supplementary Controller Design Using Real-Coded Genetic Algorithm for Damping Low Frequency Oscillations in Power Systems

— This paper presents a systematic approach for designing Unified Power Flow Controller (UPFC) based supplementary damping controllers for damping low frequency oscillations in a single-machine infinite-bus power system. Detailed investigations have been carried out considering the four alternatives UPFC based damping controller namely modulating index of series inverter ( m B ), modulating index of shunt inverter ( m E ), phase angle of series inverter ( δ B ) and phase angle of the shunt inverter ( δ E ). The design problem of the proposed controllers is formulated as an optimization problem and Real- Coded Genetic Algorithm (RCGA) is employed to optimize damping controller parameters. Simulation results are presented and compared with a conventional method of tuning the damping controller parameters to show the effectiveness and robustness of the proposed design approach. MATLAB/SIMULINK,
Now you hear it, now you don't: empirical studies of audio browsing behavior behavior

We present several studies that investigate how people use audio documents and uncover new principles for designing audio navigation technology. In particular, we report on an ethnographic study of voicemail users, experimental studies of human voicemail processing and the design of a new structural browser that embodies principles learned from the forementioned empirical studies. Specifically, our studies show that the reinforcement of audio memory and appropriate definition of content-based playback units are important properties of interfaces suited to human audio processing behaviors.
Tego nie było, czyli o pamięciowym efekcie negacji przy stwierdzaniu nieobecności czegoś u dzieci w wieku przedszkolnym

Studies of the acquisition of negative meanings suggest that rejection (refusal) is the first semantic category of negation children are able to express. The second negative function that is typically attested in children’s gestures and speech refers to the expression of disappearance or nonexistence – this function of negation is the topic of our study. In this article an experiment is presented demonstrating that negation can have paradoxical effects, making children believe that a negated idea actually existed. In the experiment, the participants (five and six year old children) listened to a description of a house, in which some objects were mentioned, some were negated, and some were not mentioned at all. After one day, when questioned about the existence of all the objects, the children gave more false alarms in the case of the negated items that the ones not mentioned at all. The results are discussed in terms of the inhibition and retention hypothesis.
Information theoretic privacy for smart meters

Smart meters (SMs) measure and report energy consumption of individual users to the utility provider at short intervals on the order of minutes. While SM data is used to increase the efficiency in electricity distribution, it also conveys sensitive private data on the energy consumption behaviour of individual customers. In this work, privacy in a smart metering system is studied from an information theoretic perspective in the presence of alternative energy sources and storage units. An alternative energy source provides increased privacy by diversifying the energy source, and the storage device filters the real energy consumption to reduce the leaked data. Connections between this problem and rate-distortion theory is established, and both theoretical and numerical results are presented.
Genetic Characterization of the Klebsiella pneumoniae waa Gene Cluster, Involved in Core Lipopolysaccharide Biosynthesis

ABSTRACT A recombinant cosmid containing genes involved in Klebsiella pneumoniae C3 core lipopolysaccharide biosynthesis was identified by its ability to confer bacteriocin 28b resistance toEscherichia coli K-12. The recombinant cosmid contains 12 genes, the whole waa gene cluster, flanked bykbl and coaD genes, as was found in E. coli K-12. PCR amplification analysis showed that this cluster is conserved in representative K. pneumoniae strains. Partial nucleotide sequence determination showed that the same genes and gene order are found in K. pneumoniae subsp.ozaenae, for which the core chemical structure is known. Complementation analysis of known waa mutants from E. coli K-12 and/or Salmonella enterica led to the identification of genes involved in biosynthesis of the inner core backbone that are shared by these three members of theEnterobacteriaceae. K. pneumoniae orf10 mutants showed a two-log-fold reduction in a mice virulence assay and a strong decrease in capsule amount. Analysis of a constructed K. pneumoniae waaE deletion mutant suggests that the WaaE protein is involved in the transfer of the branch β-d-Glc to the O-4 position ofl-glycero-d-manno-heptose I, a feature shared by K. pneumoniae, Proteus mirabilis, and Yersinia enterocolitica.
A N G E W a N D T E M a T H E M a T I K Contract-based Component System Design Contract-based Component System Design

Due to hardware developments, strong application needs and the overwhelming innuence of the net in almost all areas, distributed systems, especially software systems, have become one of the most important topics for nowadays software industry. Unfortunately, distribution adds its share to the problems of developing complex software systems. Heterogeneity in both, hardware and software, concurrency, distribution of components and the need for in-teroperability between diierent systems complicate matters. Although subject to permanent changes, distributed systems have high requirements w.r. t. dependability and performance. Moreover, new technical aspects like resource management, load balancing and deadlock handling put an additional burden onto the developer. Nowadays design methods and programming languages fail to describe the speciic properties of distributed systems in an adequate manner. One of the essential drawbacks of the design methods which are around for some time now, is the lack of support for the dynamic aspects of distributed software systems. Based on object-oriented analysis and design, our approach adds the aspects of architectural modeling to the usual structural modeling of distributed software systems. Moreover, behavioral modeling w.r. t. concurrency, competition for resources and coordination is made more intuitive by means of an adequate modeling language. We use a speciic kind of high-level petri-nets, so-called Object Coordination Nets (OCoNs). The result is an integrated design language which seamlessly combines the well-known approaches of object-oriented analysis and development with methods which work well for the speciic aspects of distributed software systems. The TYCS approach (Typed Component Systems) proposes a component notion with black-box abstraction based on the behavioral contracts of the OCoN approach. The contract notion and its beneets are further improved to enforce a greater degree of separation concerning synchronization eeects between the contract providing and using components. To support composition the OCoN contract subtype notion that allows trader-based contract matching is used. A syntactical notion of component types on top of the contract notion and a set of related behavior assumptions for components has been developed. They can ensure deadlock free composition while preserve a great degree of exibility during the design of component-based systems. Abstract Component technology tries to solve many problems of todays software industry practice: the productivity and produced quality should be increased and a better infrastructure for maintenance of the products is promised. The integration of oo-the-shelf components to build customized products allows to source out the development of general purpose components. A crucial prerequisite for the intended …
Visual, aural, read/write, and kinesthetic: An assessment of learning styles among undergraduate medical students of M R Medical College, Kalaburagi

Background: Globally, research on education states that there will be unique learning style for an individual and it differs from person to person. There is a need for the students and even the teachers a starting place for thinking about and understand how students learn to achieve the maximum benefits from existing various modern teaching methodologies. Objectives: The present study was undertaken to assess the learning styles among undergraduate (UG) medical students of Mahadevappa Rampure Medical College, Kalaburagi, Karnataka. Materials and Methods: A descriptive cross-sectional study was conducted among UG medical students belonging to two consecutive batches in the 1st and 2nd year of medical training were invited to participate in the exercise. Of the total 250 students who invited, 213 (85.2%) participated, and the data were collected by administering a printed form of Version 7.8 visual, aural, read/write, and kinesthetic questionnaire. The sample size was drawn using convenient sampling technique. Learning style preference was assessed depending on the score for each question. Statistical analysis was done in terms of percentages and proportions and using chi-square tests. Results: The majority of students in our study was unimodal learners (54%). The predominant sensory modality of learning was kinesthetic (65.2%), followed by aural (20%). Unimodality was the preferred learning style more among males (58.3%), but females were more kinesthetic learners (75%). Conclusion: We use a combination of teaching methods in our daily routine as teachers, but there has not been an active effort to determine whether these methods adequately meet the requirements of different types of learners. We hope that the data from the present study will help us to adopt better approaches in teaching and training the students and make learning a more fruitful experience.
Evaluation of AMD's advanced synchronization facility within a complete transactional memory stack

AMD's Advanced Synchronization Facility (ASF) is an x86 instruction set extension proposal intended to simplify and speed up the synchronization of concurrent programs. In this paper, we report our experiences using ASF for implementing transactional memory. We have extended a C/C++ compiler to support language-level transactions and generate code that takes advantage of ASF. We use a software fallback mechanism for transactions that cannot be committed within ASF (e.g., because of hardware capacity limitations). Our evaluation uses a cycle-accurate x86 simulator that we have extended with ASF support. Building a complete ASF-based software stack allows us to evaluate the performance gains that a user-level program can obtain from ASF. Our measurements on a wide range of benchmarks indicate that the overheads traditionally associated with software transactional memories can be significantly reduced with the help of ASF.
Feature Extraction Method for Epileptic Seizure Detection Based on Cluster Coefficient Distribution of Complex Network

Automatic epileptic seizure detection has important research significance in clinical medicine. Feature extraction method for epileptic EEG occupies core position in detection algorithm, since it seriously affects the performance of algorithm. In this paper, we propose a novel epileptic EEG feature extraction method based on the statistical property of complex networks theory. EEG signal is first converted to complex network and cluster coefficients of every node in the network are computed. Through analysis of the cluster coefficient distribution, the partial sum of cluster coefficient distribution is extracted as the classification feature. A public epileptic EEG dataset was utilized for evaluating the classification performance of extracted feature. Experimental results show that the extracted feature achieves classification accuracy up to 94.50%, which indicates that it can clearly distinguish between the ictal EEG and interictal EEG. The higher classification accuracy demonstrates the extracted classification feature's great potentiality of the real-time epileptic seizures detection.
Probabilistic Abductive Logic Programming using Possible Worlds

Reasoning in very complex contexts often requires purely deductive reasoning to be supported by a variety of techniques that can cope with incomplete data. Abductive inference allows to guess information that has not been explicitly observed. Since there are many explanations for such guesses, there is the need for assigning a probability to each one. This work exploits logical abduction to produce multiple explanations consistent with a given background knowledge and defines a strategy to prioritize them using their chance of being true. Another novelty is the introduction of probabilistic integrity constraints rather than hard ones. Then we propose a strategy that learns model and parameters from data and exploits our Probabilistic Abductive Proof Procedure to classify never-seen instances. This approach has been tested on some standard datasets showing that it improves accuracy in presence of corruptions and missing data.
POS Tagging Using Relaxation LabellingLlu

Relaxation labelling is an optimization technique used in many elds to solve constraint satisfaction problems. The algorithm nds a combination of values for a set of variables such that satis-es-to the maximum possible degree-a set of given constraints. This paper describes some experiments performed applying it to POS tagging, and the results obtained. It also ponders the possibility of applying it to Word Sense Disam-biguation.
The SCUBA Bright Quasar Survey (SBQS) - II. Unveiling the quasar epoch at submillimetre wavelengths

We present results of the first systematic search for submillimetre (submm) continuum emission from z ∼ 2, radio-quiet, optically-luminous (MB 4; Paper I). The target sensitivity of the survey, 3σ = 10 mJy at 850 µm, was chosen to enable efficient identification of bright submm sources, suitable for detailed follow-up. Nine targets are detected with 3σ significance or greater, with fluxes in the range 7‐17 mJy. Although the detection rate above 10 mJy is lower than that of the z > 4 survey, the weighted mean flux of the undetected sources, 1.9 ± 0.4 mJy, is similar to that at z > 4 (2.0 ± 0.6 mJy). The statistical significance of trends is analysed, and it is found that: (i) within the limited optical luminosity range studied, there is no strong evidence for a correlation between submm and optical luminosity; (ii) there is a suggestion of a variation of submm detectability with redshift, but that this is consistent with the K-correction of a characteristic far-infrared spectrum.
Rescue of Impaired Angiogenesis in Spontaneously Hypertensive Rats by Intramuscular Human Tissue Kallikrein Gene Transfer

Angiogenesis represents a compensatory response targeted to preserve the integrity of tissues subjected to ischemia. The aim of the present study was to examine whether reparative angiogenesis is impaired in spontaneously hypertensive rats (SHR), as a function of progression of hypertension. In addition, the potential of gene therapy with human tissue kallikrein (HK) in revascularization was challenged in SHR and normotensive Wistar-Kyoto rats (WKY) that underwent excision of the left femoral artery. Expression of vascular endothelial growth factor and HK was upregulated in ischemic hindlimb of WKY but not of SHR. Capillary density was increased in ischemic adductor muscle of WKY (from 266±20 to 633±73 capillaries/mm2 at 28 days, P <0.001), whereas it remained unchanged in SHR (from 276±20 to 354±48 capillaries/mm2, P =NS), thus compromising perfusion recovery as indicated by reduced plantar blood flow ratio (0.61±0.08 versus 0.92±0.07 in WKY at 28 days, P <0.05). In separate experiments, saline or 5×109 pfu adenovirus containing the HK gene (Ad.CMV-cHK) or the &bgr;-galactosidase gene (Ad.CMV-LacZ) was injected intramuscularly at 7 days after the induction of ischemia. Ad.CMV-cHK augmented capillary density and accelerated hemodynamic recovery in both strains, but these effects were more pronounced in SHR (P <0.01). Our results indicate that native angiogenic response to ischemia is impaired in SHR, possibly as a result of defective modulation of endothelial cell mitogens. Supplementation with kallikrein, one of the growth factors found to be deficient in SHR, restores physiological angiogenic response utilitarian for tissue healing. Our discoveries may have important implications in vascular medicine for therapeutic benefit.