Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantic similarity methods in wordNet and their application to information retrieval on the web

Semantic Similarity relates to computing the similarity between concepts which are not lexicographically similar. We investigate approaches to computing semantic similarity by mapping terms (concepts) to an ontology and by examining their relationships in that ontology. Some of the most popular semantic similarity methods are implemented and evaluated using WordNet as the underlying reference ontology. Building upon the idea of semantic similarity, a novel information retrieval method is also proposed. This method is capable of detecting similarities between documents containing semantically similar but not necessarily lexicographically similar terms. The proposed method has been evaluated in retrieval of images and documents on the Web. The experimental results demonstrated very promising performance improvements over state-of-the-art information retrieval methods.
On The Phase Crossing Statistics and Random FM Noise in Generalized Rice Fading Channels

On The Phase Crossing Statistics and Random FM Noise in Generalized Rice Fading Channels In this paper we consider phase process second order statistics of generalized Rice (Beckmann) multipath fading channel. Closed-form expression for JPDF of phase and random FM noise is derived. Furthermore expressions for the PDF and CDF of random FM noise are obtained. The level-crossing rate of the phase process is then obtained for any phase crossing level. Obtained expressions reduces to known ones for Hoyt, Rice and Rayleigh fading channels, since these are the special cases of generalized Rice fading channel. Moreover, derived analytical expressions are compared with results obtained by computer simulation where excellent agreement is achieved. Presented results can be applied for analyzing the statistics of FM spikes in the case of data transmission over generalized Rice fading channels.
Adaptive Motor Behavior of Cerebellar to Unfamiliar External Forces Patients During Exposure

The authors investigated adaptation of goal-directed forearm movements to an unknown external viscous force assisting forearm flexion in 6 patients with cerebellar dysfunction and in 6 control participants. Motor performance was generally degraded in cerebellar patients and was markedly reduced under the force con- dition in both groups. However, patients and controls were able to adapt to the novel force within 8 trials. Only the healthy controls were able to improve motor performance when readapting to a null-force condition. The results indicate that cerebellar patients' motor control system has imprecise estimations of actual limb dynamics at its disposal. Force adaptation may have been pre- served because single-joint movements were performed, whereas the negative viscous force alone and no interaction forces had to be
The development of vocabulary and morphological awareness: A longitudinal study with college EFL students

Abstract While the relationship between vocabulary, morphological awareness, and reading comprehension has been examined extensively, research on this relationship among adult second language learners has only been explored recently. The present study addresses this gap by examining how adult English as a foreign language learners developed different types of English vocabulary and morphological awareness over the course of one academic year. Participants included 523 college freshmen in Taiwan with varying reading proficiency levels. Results from a series of mixed-measure analyses of variance revealed that (a) even the more proficient college English as a foreign language learners failed to fully grasp morphological principles; (b) the gap in vocabulary between the less skilled readers, the average, and the skilled readers widened significantly over the course of one academic year; (c) the effect of phonological and orthographic changes involved in morphologically complex words differed for the assessment of base meaning, but did not vary across proficiency levels; (d) progress in different aspects of morphological awareness, such as interpreting the meaning of the suffix or identifying the base of a morphologically complex word, varied significantly among readers of different proficiency levels; and (e) suffixes of different parts of speech posed different challenges to learners. Theoretical and pedagogical implications of the findings are discussed.
The Effect of Brief-Tone Stimulus Duration on the Brain Stem Auditory Steady-State Response

Objective: To investigate the effect of brief-tone stimulus duration on the amplitude of the brain stem auditory steady-state response (ASSR), both in single- and multiple-stimulus conditions. Design: In Experiment 1, the primary stimuli were Blackman-windowed 500- and 2000-Hz brief tones presented using repetition rates of 79 and 83 Hz, respectively. Stimuli had durations ranging from 0.5 to 12 msec. In the single-stimulus condition, these two stimuli were presented dichotically, whereas in the four-stimulus multiple-stimulus condition, instead of being presented alone, each stimulus was combined with three interfering stimuli, which were also Blackman-windowed brief tones spaced one octave apart, and presented at rates of 77 to 96 Hz. In Experiment 2, the effect of brief-tone duration and the effect of interfering stimuli were further studied by systematically removing interfering stimuli from the multiple stimuli, with the goal of determining which specific stimuli in the multiple stimuli were responsible for the interference. In both experiments, stimuli were presented at 75 ppe dB SPL. The subjects were normal-hearing adults, who relaxed or slept during the recording sessions. Results: Experiment 1: ASSR amplitudes increased as stimulus duration decreased in the single-stimulus condition, for both 500 and 2000 Hz. However, amplitudes did not significantly increase until stimuli were quite brief (2 msec for 2000 Hz; 6 msec for 500 Hz). In the four-stimulus multiple-stimulus condition, the pattern of amplitude increase with decreasing stimulus duration at 2000 Hz was similar to that in the single-stimulus condition, although amplitudes at all durations were reduced. However, for 500-Hz stimuli in the four-stimulus multiple-stimulus condition, ASSR amplitudes showed no change as stimulus duration decreased. Experiment 2: for 2000-Hz stimuli, the 4000-Hz interfering stimuli resulted in the largest change in amplitude, the 1000-Hz interfering stimuli had a small effect, and the 500-Hz interfering stimuli had no effect. For 500-Hz stimuli, the 1000-Hz interfering stimuli had the greatest effect, the 2000-Hz interfering stimuli the next largest, and the 4000-Hz interfering stimuli a small effect. The interference effects for 500-Hz stimuli occurred only for brief (≤6 msec) stimuli, with no effects of the interfering stimuli when the 500-Hz stimuli were 8 or 12 msec in duration. Conclusion: Although brief tones may result in larger-amplitude ASSRs, their duration must be quite brief (not more than three to four cycles) to show a significant amplitude increase. Moreover, when presented together with other stimuli in the multiple-stimulus technique, response interference reduces the amplitudes of ASSRs, and for 500 Hz removes the amplitude gain normally seen with decreasing duration. Brief-tone stimuli, therefore, may not be optimal for ASSR threshold estimation, especially because of the compromise in frequency specificity accompanying the use of very brief tones.
Microwave and terahertz spectroscopy

Spectroscopy, or the study of the interaction of light with matter, has become one of the major tools of the natural and physical sciences during this century. As the wavelength of the radiation is varied across the electromagnetic spectrum, characteristic properties of atoms, molecules, liquid and solids are probed. In the optical and ultraviolet regions (λ ~ 1 µm up to 100 nm) it is the electronic structure of the material that is investigated, while at infrared wavelengths (~ 1-30 µm) the vibrational degrees of freedom dominate.
Large contributions of coupled protonation equilibria to the observed enthalpy and heat capacity changes for ssDNA binding to Escherichia coli SSB protein

Many macromolecular interactions, including protein‐nucleic acid interactions, are accompanied by a substantial negative heat capacity change, the molecular origins of which have generated substantial interest. We have shown previously that temperature‐dependent unstacking of the bases within oligo(dA) upon binding to the Escherichia coli SSB tetramer dominates the binding enthalpy, ΔHobs, and accounts for as much as a half of the observed heat capacity change, ΔCp. However, there is still a substantial ΔCp associated with SSB binding to ssDNA, such as oligo(dT), that does not undergo substantial base stacking. In an attempt to determine the origins of this heat capacity change, we have examined by isothermal titration calorimetry (ITC) the equilibrium binding of dT(pT)34 to SSB over a broad pH range (pH 5.0–10.0) at 0.02 M, 0.2 M NaCl and 1 M NaCl (25°C), and as a function of temperature at pH 8.1. A net protonation of the SSB protein occurs upon dT(pT)34 binding over this entire pH range, with contributions from at least three sets of protonation sites (pKa1 = 5.9–6.6, pKa2 = 8.2–8.4, and pKa3 = 10.2–10.3) and these protonation equilibria contribute substantially to the observed ΔH and ΔCp for the SSB‐dT(pT)34 interaction. The contribution of this coupled protonation (∼ −260 to −320 cal mol−1 K−1) accounts for as much as half of the total ΔCp. The values of the “intrinsic” ΔCp,0 range from −210 ± 33 cal mol−1 °K−1 to −237 ± 36 cal mol−1K−1, independent of [NaCl]. These results indicate that the coupling of a temperature‐dependent protonation equilibria to a macromolecular interaction can result in a large negative ΔCp, and this finding needs to be considered in interpretations of the molecular origins of heat capacity changes associated with ligand‐macromolecular interactions, as well as protein folding. Proteins 2000;Suppl 4:8–22. © 2000 Wiley‐Liss, Inc.
Facilitating the development of leadership qualities in the Foundation Phase

vii ABSTRACT IN TSHIVENḒA. ixIN TSHIVENḒA. ix DECLARATION OF EDITING.xi LIST OF ACRONYMS AND ABBREVIATIONS.xii TABLE OF CONTENTS.xiii LIST OF TABLES.xxi LIST OF FIGURES.xxiii ADDENDA.xxvi CHAPTER 1 .
Keen-Means: A Web Page Clustering Tool Based on an Self-Adjustable K-Means Algorithm

Search engines usually do their jobs well. However, due to the fact that most existing search algorithms are keyword-based, search engines may not work as expected in some scenarios when ambiguity problems are encountered. A possible approach to overcome it is to categorize Web resources in advance. In this research, a k-means variation, the keen-means algorithm, along with its implementation is proposed. The algorithm will dynamically and automatically adjust the k value to achieve better results.
Effect of high-level fish meal replacement by plant proteins in gilthead sea bream (Sparus aurata) on growth and body/fillet quality traits

DM) diets either based on fish meal (diet FM) or on a mixture of plant protein sources (diet PP), replacing 75% of fish meal protein. The growth trial was conducted in duplicate, two tanks for each dietary treatment. Growth performance and feed utilization were registered. Fillet quality parameters were evaluated and sensory analyses on cooked fillet were performed. Both groups had similar weight gain and specific growth rates. Feed intake was higher in sea bream fed diet FM (0.48 versus 0.44), while feed efficiency and protein efficiency ratio were significantly higher in sea bream fed PP (0.83 versus 0.77 and 2.0 versus 1.76, respectively). Sea bream fed diet FM had a lower hepatosomatic index (0.80 versus 0.87%), and a higher fillet yield (45.9 versus 44.9%). The fillet from sea bream fed diet FM had higher moisture (696 versus 682 g kg −1 ), lower lipid levels (91 versus 100 g kg −1 ) with higher levels of n-3 polyunsaturated fatty acids (PUFA) and monounsaturated fatty acids (MUFA), while the PP fed sea bream presented a higher level of PUFA n-6. There were minor differences in muscle free amino acid levels between the two diet groups. As regards sensory evaluation of cooked fillet, the judges were unable to discriminate the two dietary groups of fish. Summarizing, the results demonstrate the possibility to use diets containing high levels (750 g kg −1 ) of plant ingredients in gilthead sea bream without affecting growth performance and with minor effects on quality traits of commercial size sea bream.
Designing a Multilayer Feedforward Ensemble with the Weighted Conservative Boosting Algorithm

In previous researches we have analysed some methods to create committees of multilayer feedforward networks trained with the backpropagation algorithm. One of the most known methods that we have studied is Adaptive Boosting. In this paper we propose a variation of this method called weighted conservative boosting based on conservative boosting. In this case, a weight which depends on the database and on the ensemble is added to the equation used to update the sampling distribution. We have tested adaptive boosting, conservative boosting and weighted conservative boosting with seven databases from the UCI repository. We have used the mean Increase of Performance and the mean percentage of error reduction to compare both methods, the results show that weighted conservative boosting is the best performing method.
Research on Application of Improved Association Rules Algorithm in Intelligent QA System

With increasingly prevalent of E-learning, the intelligent Q/A system arise at the historic moment. In this paper we proposed an improved text cluster algorithm, with the improved association rules algorithm, it can classify the information in the database accurately according to the questions, locate the user's question fast and therefore speeds up the inquiry rate. The experimental result indicates that this plan has the merits of intelligence, self-renewing, and efficient Q/A and so on.
Predicting webpage credibility using linguistic features

The article focuses on predicting trustworthiness from textual content of webpages. The recent work Olteanu et al. proposes a number of features (linguistic and social) to apply machine learning methods to recognize trust levels. We demonstrate that this approach can be substantially improved in two ways: by applying machine learning methods to vectors computed, using psychosocial and psycholinguistic features and in a high-dimensional bag-of-words paradigm of word occurrences. Following Olteanu et al., we test the methods in two classification settings, as a 2-class and 3-class scenario, and in a regression setting. In the 3-class scenario, the features compiled by Olteanu et al. achieve weighted precision of 0.63, while the methods proposed in our paper raise it to 0.66 and 0.70. We also examine coefficients of the models in order to discover words associated with low and high trust.
Sequence of xynC and properties of XynC, a major component of the Clostridium thermocellum cellulosome

The nucleotide sequence of the Clostridium thermocellum F1 xynC gene, which encodes the xylanase XynC, consists of 1,857 bp and encodes a protein of 619 amino acids with a molecular weight of 69,517. XynC contains a typical N-terminal signal peptide of 32 amino acid residues, followed by a 165-amino-acid sequence which is homologous to the thermostabilizing domain. Downstream of this domain was a family 10 catalytic domain of glycosyl hydrolase. The C terminus separated from the catalytic domain by a short linker sequence contains a dockerin domain responsible for cellulosome assembly. The N-terminal amino acid sequence of XynC-II, the enzyme purified from a recombinant Escherichia coli strain, was in agreement with that deduced from the nucleotide sequence although XynC-II suffered from proteolytic truncation by a host protease(s) at the C-terminal region. Immunological and N-terminal amino acid sequence analyses disclosed that the full-length XynC is one of the major components of the C. thermocellum cellulosome. XynC-II was highly active toward xylan and slightly active toward p-nitrophenyl-beta-D-xylopyranoside, p-nitrophenyl-beta-D-cellobioside, p-nitrophenyl-beta-D-glucopyranoside, and carboxymethyl cellulose. The Km and Vmax values for xylan were 3.9 mg/ml and 611 micromol/min/mg of protein, respectively. This enzyme was optimally active at 80 degrees C and was stable up to 70 degrees C at neutral pHs and over the pH range of 4 to 11 at 25 degrees C.
Recovery of Blocky Images from Noisy and Blurred Data

The purpose of this investigation is to understand situations under which an enhancement method succeeds in recovering an image from data which are noisy and blurred. The method in question is due to Rudin and Osher. The method selects, from a class of feasible images, one that has the least total variation.Our investigation is limited to images which have small total variation. We call such images “blocky” as they are commonly piecewise constant (or nearly so) in grey-level values. The image enhancement is applied to three types of problems, each one leading to an optimization problem. The optimization problems are analyzed in order to understand the conditions under which they can be expected to succeed in reconstructing the desired blocky images. We illustrate the main findings of our work in numerical examples.
Real traffic logs creation for testing intrusion detection systems

Port scanning is one of the most popular reconnaissance techniques that many attackers use to profile running services on a potential target before launching an attack. Many port scanning detection mechanisms have been suggested in literature. To test the proposed detection approaches, researchers use data sets that are available online or simulate their own. However, the available data sets do not provide complete logs and are usually outdated. Furthermore, the simulated data sets provide logs that do not resemble reali¾? life scenarios. These deficiencies in the available data sets highly affect the performance of testing the intrusion detection systems IDSs and result in poor evaluations. Meanwhile, very little work has been done on generating port scanning benchmarks that researchers can use to test their detection methods. In this work, we suggest a simulation framework using OMNeT++ to generate benchmarks that resemble reali¾? life traffic. We approach the problem by dividing it into three modules: 1 topology creation; 2 good traffic generation; and 3 bad traffic generation, each of which are made realistic, similar to deployed and usable networks. The benchmark is then tested using Snort and MalwareAnalysis. The tested IDSs were not able to catch many of the generated port scanning attacks, specifically the slow and distributed ones. We also measured the attack detection efficiency of the IDSs under different loads of background activities. Hence, the proposed framework and the annotated benchmarks will provide researchers and industry with an effective way of testing the power of IDSs' port scanning detection modules. Copyright © 2014 John Wiley & Sons, Ltd.
Speech Enhancement Using Generative Dictionary Learning

The enhancement of speech degraded by real-world interferers is a highly relevant and difficult task. Its importance arises from the multitude of practical applications, whereas the difficulty is due to the fact that interferers are often nonstationary and potentially similar to speech. The goal of monaural speech enhancement is to separate a single mixture into its underlying clean speech and interferer components. This under-determined problem is solved by incorporating prior knowledge in the form of learned speech and interferer dictionaries. The clean speech is recovered from the degraded speech by sparse coding of the mixture in a composite dictionary consisting of the concatenation of a speech and an interferer dictionary. Enhancement performance is measured using objective measures and is limited by two effects. A too sparse coding of the mixture causes the speech component to be explained with too few speech dictionary atoms, which induces an approximation error we denote source distortion. However, a too dense coding of the mixture results in source confusion, where parts of the speech component are explained by interferer dictionary atoms and vice-versa. Our method enables the control of the source distortion and source confusion trade-off, and therefore achieves superior performance compared to powerful approaches like geometric spectral subtraction and codebook-based filtering, for a number of challenging interferer classes such as speech babble and wind noise.
A System Description of P^4: Possible Punctuation Points Parser

We present a Natural Language Understanding (NLU) implementation that automatically inserts punctuation marks into a sequence of words to create a group of one or more syntactically correct sentences. The software, Possible Punctuation Points Parser (P^4) provides the ability for the user to input a string of words to process, performs the punctuation possibilities, and then provides several visualizations to illustrate how the software arrived at its final solution. P^4 uses a chart parsing algorithm combined with a search algorithm that creates data visualization structures. A potential application of this software is to serve as a formidable starting point for automatic punctuation mark insertion during voice-to-text conversion found on many mobile platforms.
Automated Extraction of Rich Software Models from Limited System Information

Reverse engineering a software system is challenged by the typically very limited information available about existing systems. Useful reverse engineering tasks include recovering a system's architectural, behavioral, and usage models, which can then be leveraged to answer important questions about a system. For example, using such models to analyze and predict a system's non-functional properties would help to efficiently assess the system's current state, planned adaptations, scalability issues, etc. Existing approaches typically only extract a system's static architecture, omitting the dynamic information that is needed for such analyses. The contribution of this paper is an automated technique that extracts a system's static architecture, behavior, and usage models from very limited, but readily available information: source code and test cases. These models can then be fed into known performance, reliability, and cost prediction techniques. We evaluated our approach for accuracy against systems with already established usage models, and observed that our approach finds the correct, but more detailed usage models. We also analyzed 14 open source software systems spanning over 2 million lines of code to evaluate the scalability of our approach.
Multiple-case outlier detection in least-squares regression model using quantum-inspired evolutionary algorithm

In ordinary statistical methods, multiple outliers in least-squares regression model are detected sequentially one after another, where smearing and masking effects give misleading results. If the potential multiple outliers can be detected simultaneously, smearing and masking effects can be avoided. Such multiple-case outlier detection is of combinatorial nature and 2N -1 sets of possible outliers need to be tested, where N is the number of data points. This exhaustive search is practically impossible. In this paper, we have used quantum-inspired evolutionary algorithm (QEA) for multiple-case outlier detection in least-squares regression model. An information criterion based fitness function incorporating extra penalty for number of potential outliers has been used for identifying the most appropriate set of potential outliers. Experimental results with four datasets from statistical literature show that the QEA effectively detects the most appropriate set of outliers.