Miracle-dz/UniFAR-FTUs huggingface dataset:
THE PROBLEM OF STUDYING NEOLOGISMS AND THEIR INFLUENCE ON THE ECOLOGY OF LANGUAGE

Abstract. The article raises the issues of neology and ecolinguistics. The authors specifythe criteria of ecolinguistic approach to studying neologisms based on ecolinguistic monitoringwhich helps to elicit factors that influence the formation of new words, spheres in which theyfunction in language as well as to define the type of new words and number of loanwordsamong them. The data under analysis is compiled by about 3000 new words that appeared inEnglish and Dutch in the last three decades. The authors elicit the main changes in the ecologyof the Dutch language on different levels in the stated time frame together with the factorsthat motivate the formation of neologisms. Among extralinguistic factors the authors list suchdeterminants as the emergence of new realia; scientific and technical advancement;globalization and development of the Internet. To intralinguistic factors the following arereferred: linguistic economy; expressiveness of linguistic means; systematization of thevocabulary; unification of linguistic signs; conversion and the shift in stylistic usage of thewords can also generate neologisms. Future development of the ecolinguistic approach inneology will help to track the evolution of modern national language and preserve its ecolinguisticbalance. The research results can be used in language education, lexicographic practice orstate language policy.Key words: neologism, ecolinguistic approach, ecolinguistic monitoring, loanword,language ecology.Language is known for its constantdevelopment with lexis being its most mobile level.Every generation gives life to new words derivedfrom the current reality. The electronic revolutionin the second half of the twentieth century causedthe scientific and technical progress to speed up,and these processes were immediately reflectedin language. Every year lexicographers registerhundreds of new words. According to the surveycarried out by Global Language Monitor, theEnglish language obtains a new word every98minutes [8, p. 34]. The analysis of different linguists’ viewpointsconcerning the phenomenon of neologism showed
A four-choice hybrid P300/SSVEP BCI for improved accuracy

Brain-computer interfaces (BCIs) usually rely on one of three types of signals: P300, SSVEP, or ERD. Recent work has shown that ‘hybrid’ BCIs that combine different types of signals may be superior to their simpler counterparts. This paper introduces a new type of hybrid P300/SSVEP BCI with a four-choice system. We compared this new approach to conditions that used only a P300 or SSVEP BCI. In addition to collecting EEG and performance data based on offline and then online runs, we also used questionnaires to explore the subject’s experiences with the different conditions. Results showed that subjects could use the hybrid BCI, and did not consider it more annoying, difficult or fatiguing than the P300 or SSVEP BCI. The hybrid condition improved performance relative to the SSVEP condition, but not the P300 condition. The hybrid condition did not elicit significant differences in the EEG measures compared here. These results validate this new BCI approach and provide support for future hybrid efforts.
The neural mechanisms underlying visual target search

The task of finding specific objects and switching between targets is ubiquitous in everyday life. Searching for a particular object requires our brains to activate and maintain a representation of the target (working memory), identify each encountered object (object recognition), and determine whether the currently viewed object matches the sought target (decision making). The comparison of working memory and visual information is thought to happen via feedback of target information from higher-order brain areas to the ventral visual pathway. However, what is exactly represented by these areas and how do they implement this comparison still remains unknown. To investigate these questions, we employed a combined approach involving electrophysiology experiments and computational modeling. In particular, we recorded neural responses in inferotemporal (IT) and perirhinal (PRH) cortex as monkeys performed a visual target search task, and we adopted population-based read-outs to measure the amount and format of information contained in these neural populations. In Chapter 2 we report that the total amount of target match information was matched in IT and PRH, but this information was contained in a more "explicit" (i.e. linearly separable) format in PRH. These results suggest that PRH implements an "untangling" computation to reformat its inputs from IT. Consistent with this hypothesis, a simple linear-nonlinear model was sufficient to capture the transformation between the two areas. In Chapter 3, we report that the untangling computation in PRH takes time to evolve. While this type of dynamic reformatting is normally attributed to complex recurrent circuits, here we demonstrated that this phenomenon could be accounted by the same instantaneous linear-nonlinear model presented in Chapter 2. This counterintuitive finding was due to the existence of non-stationarities in the IT neural representation. Finally, in Chapter 4 we completely describe a novel set of methods that we developed and applied in Chapters 2 and 3 to quantify the task-specific signals contained in the heterogeneous neural responses in IT and PRH, and to relate these signals to measures of task performance. Together, this body of work revealed a previously unknown untangling computation in PRH during visual search, and demonstrated that a feed-forward linear-nonlinear model is sufficient to describe this computation. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Neuroscience First Advisor Nicole C. Rust
The Effectiveness of Using Contextual Clues, Dictionary Strategy and Computer Assisted Language Learning (Call) In Learning Vocabulary

This study investigates the effectiveness of three vocabulary learning methods that are Contextual Clues, Dictionary Strategy, and Computer Assisted Language Learning (CALL) in learning vocabulary among ESL learners. First, it aims at finding which of the vocabulary learning methods namely Dictionary Strategy, Contextual Clues, and CALL that may result in the highest number of words learnt in the immediate and delayed recall tests. Second, it compares the results of the Pre-test and the Delayed Recall Post-test to determine the differences of learning vocabulary using the methods. A quasi-experiment that tested the effectiveness of learning vocabulary using Dictionary Strategy, Contextual clues, and CALL involved 123 first year university students. Qualitative procedures included the collection of data from interviews which were conducted to triangulate the data obtain from the quantitative inquiries. Findings from the study using ANOVA revealed that there were significant differences when students were exposed to Dictionary Strategy, Contextual Clues and CALL in the immediate recall tests but not in the Delayed Recall Post-test. Also, there were significant differences when t test was used to compare the scores between the Pre-test and the Delayed Recall Post-test in using the three methods of vocabulary learning. Although many researchers have advocated the relative effectiveness of Dictionary Strategy, Contextual Clues, and CALL in learning vocabulary, the study however, is still paramount since there is no study has ever empirically investigated the relative efficacy of these three methods in a single study.
What Kinds of Hybrid Models are Used in Multiple Criteria Decision Analysis and Why

Currently, a growing number of papers presenting the hybrid models in the field of MCDA is observed. In this paper we try to explain the reasons for the growing popularity of hybrid models. The most important question considers the reasons for the use of these, rather complicated, structures. We also try to find out the differences between various models which are called hybrid.
Model-based multi-sensor fusion

A new class of ATR algorithms known in general as model-based have demonstrated some promising results. One major advantage of these new methods is that they are not only data-driven but they ore also model-driven. The fact that they are model-driven removes the dependence of the recognition process on a low level segmentation process. These new model-based approaches accomplish segmentation and recognition simultaneously. In other words, the process entertains multiple segmentation possibilities until a sufficient amount of high level and low level information is gathered so that an intelligent interpretation of what the image contains can be formed. A second major advantage of these new methodologies is the fact that the fusion of information from multiple sensors is a continual process not a one shot deal which is typical of first generation algorithms. This paper concentrates on the model-based ATR algorithm called relational template matching. <<ETX>>
Design of semi-algebraic low-density parity-check (SA-LDPC) codes for multilevel coded modulation

Semialgebraic low-density parity-check (SA-LDPC) codes are proposed for the multilevel coded modulation system. We optimize code parameters of LDPC codes according to the rate of each level by Gaussian approximation. Iterative multistage decoding (IMSD) scheme is adopted to get the significant improvement. System performance with Ungerboeck partitioning (UP) and mixed partitioning (MP) for 8PSK is evaluated respectively over additive white Gaussian noise (AWGN) channels. Many results are presented, they indicate that in terms of the tradeoff between hardware complexity and system performance, constructed multilevel coded modulation system based on optimized LDPC codes, capacity rule and MP is a good choice for the bandwidth efficient transmission over AWGN channels.
Circuit implementation of a trainable neural network using the generalized Hebbian algorithm with supervised techniques

An efficient hardware implementation of a training algorithm is presented, combining both supervised and unsupervised techniques. In VLSI circuits effects including random offsets and mismatch, system distortion, frequency response, and temperature deviations perturb the system outputs. Analysis of the generalized Hebbian algorithm (GHA) shows that these small deviations result in small perturbations of the output statistics and the weight matrix. Also, the conjugate-gradient optimization algorithm is formulated in continuous-time. Both the GHA and the optimization system can be efficiently implemented on a mesh of synapses. The low distortion and high bandwidth (>100 MHz) for the matrix operations and a high-performance analog memory indicate high performance for the GHA. From the mathematical theory, the error of the output statistics is less than 1%. <<ETX>>
ShaderSchool: a tutorial for shader programming

We present a tool for in-class and self-study learning that provides a convenient introduction into GLSL shader programming. The tool presents shaders in an interactive manner, and can be present in-class in a group interactive manner or used as an individual tutorial. In ShaderSchool the materials are presented in sections with interactive assignments integrated into the tool, which help reinforce the students learning. It was created and applied successfully in an university computer graphics class. Additionally, the ShaderSchool tool is extensible to easily incorporate further lessons.
Identification and tracking of maritime objects in near-infrared image sequences for collision avoidance

This paper describes the continuing development of an image processing system for use on high-speed passenger ferries. The system automatically identifies objects in a maritime scene and uses the detected motion to alert a human observer to potential collision situations. Three integrated image-processing algorithms, namely an image preprocessor, a motion cue generator, and a target tracker, perform the identification and tracking of maritime objects. The pre-processing filters the image and applies a histogram technique to segment the sea from potential objects of interest. The segmented image is passed to the motion cue generator, which provides motion cues based on the differences between consecutive frames of segmented image data. The target tracker applies dynamic constraints on object motion to solve the correspondence problem, thus increasing the confidence that an identified object is a target. Identified and tracked objects are highlighted to a human observer using a white box viewing cue placed directly around the object of interest.
Eliminating Amortization: On Data Structures with Guaranteed Response Time

An efficient amortized data structure is one that ensures that the average time per operation spent on processing any sequence of operations is small. Amortized data structures typically have very non-uniform response times, i.e., individual operations can be occasionally and unpredictably slow, although the average time over the sequence is kept small by completing most of the other operations quickly. This makes amortized data structures unsuitable in many important contexts, such as real-time systems, parallel programs, persistent data structures and interactive software. On the other hand, an efficient (single-operation) worst-case data structure guarantees that every operation will be processed quickly. The construction of worst-case data structures from amortized ones is a fundamental problem which is also of pragmatic interest. Progress has been slow so far, both because the techniques used were of a limited nature and because the resulting data structures had much larger hidden constant factors. I try to address both these issues in this thesis. I consider several inter-related dynamic data structuring problems for which only efficient amortized solutions were known and obtain new worst-case algorithms for them using a unified framework, that of "pebble" games. These two-player combinatorial games are formulated so that winning strategies translate fairly readily into worst-case algorithms for data structures. I analyze these games and obtain tight bounds on the payoffs to the players. These results are then made to yield new worst-case algorithms for finger search trees, partially and fully persistent linked data structures, fully persistent union-find, dynamic fractional cascading, range trees and segment trees. With my new algorithms I often get worst-case running times that match the old amortized bounds, in a few cases settling for considerable improvements over the best existing worst-case algorithm. Several of the new algorithms are comparable in simplicity to the amortized algorithms they are based on. The data structures considered in this thesis have numerous uses. Persistent data structures support efficient access to old versions of the data structure. They have been used in geometric algorithms, implementations of object oriented languages, optimistic discrete event simulation and tree pattern matching. Fractional cascading, segment trees and range trees are used extensively in geometric algorithms and range trees in databases as well. In addition pebble games appear to have applications unrelated to data structuring and may also be of independent interest, as they are similar in form to "vector balancing" and "chip firing" games studied by combinatorial mathematicians.
Roget's International Thesaurus

This thesaurus is based on the system devised by Peter Roget for his original thesaurus of 1852. Words and phrases are arranged according to the ideas or concepts that they express within an overall system of categories and classes. Thus the user can start from an idea and explore different ways to express it. This fifth edition brings Roget's original category concept towards the 21st century. 325,000 words and phrases are grouped by concept into 1073 categories with all synonyms, antonyms and related words presented together for quick and easy reference. The text has been fully revised and expanded, including 31 entirely new categories, such as computers, fitness and exercise, and all kinds of sport. The whole range of language from archaisms to the latest slang (labelled) is included.
Comparative Analysis of Fuzzy Logic with Reduced Rule Base and PI Controller for A Direct Torque Controlled Induction Motor Drive

Induction motors are most commonly used in the industry. Therefore, many control methods have been developed to obtain accurate speed trajectory and adequate torque values for induction motors. In this study, Simulation studies are realized for speed control of direct torque controlled (DTC) induction motor via MATLAB/Simulink. Firstly, a fuzzy logic controller (FLC) with reduced rule base is developed using MATLAB/Simulink Fuzzy Logic Toolbox. Then, the conventional PI controller and FLC have been applied, to speed control unit of induction motor. Simulation studies are implemented for both of the controllers under same conditions. The results obtained from conventional PI controller and FLC are analyzed and compared. According to obtained simulation results, it is observed that FLC provides better speed and torque response than PI controller.
A monolithic 0.5 to 50 GHz MODFET distributed amplifier with 6 dB gain

A monolithic 0.5-50-GHz distributed amplifier has been developed using a MODFET IC process to demonstrate a gain of 6.5 dB+or-0.5 dB across the frequency range. Input and output return losses were better than 12 dB. The noise figure of this amplifier was 4.8 dB+or-0.4 dB measured up to 26.5 GHz. The output power at the 1-dB compression point was 12 dBm at 40 GHz. <<ETX>>
A parallel implementation of the Hough transform method to detect lines and curves in pictures

An implementation of the Hough transform method on the Connection Machine is described. Detection and description of lines and curves in a picture is extremely expensive on sequential machines. The Hough transformation lends itself to elegant implementation on machines with SIMD (single instruction stream, multiple data system) architectures. The crucial issue in SIMD implementations is the cost of interprocessor communication. In this work, appropriate optimizations were carried out to minimize such costs. <<ETX>>
Patterns of virtual collaboration

Virtual collaboration—the act of working together across boundaries of space, time, and organization, aided by technology—has become increasingly commonplace in recent years. Doing so, however, presents a number of challenges to those involved. One of these is that because of a lack of experience in collaborating through computer-based collaboration systems, there is little knowledge on how to carry out collaboration virtually. Another is that it is not easy for those not directly involved in the collaboration to know what is, and has been, “going on” during virtual collaboration. This thesis suggests that both of these challenges can be addressed with the same approach, namely by referring to observations of virtual collaboration. The problem then is how such observations of virtual collaboration can be obtained without requiring those involved in it to document their own actions. To address this problem is the objective of this thesis. The approach proposed here involves three elements: firstly, the collection of data about virtual collaboration; secondly, the modeling of this data; and thirdly, the derivation of increasingly abstract, larger-scale representations of virtual collaboration from this data. These representations are termed patterns of virtual collaboration, which are abstract descriptions of activities of virtual collaboration. A multi-layered conceptual model of information, the Information Pyramid of Virtual Collaboration, is proposed, providing different views of information related to virtual collaboration, at different levels of abstraction. The thesis then suggests how from a given body of data, patterns of virtual collaboration at a corresponding level of the Information Pyramid can be extracted, and how from collections of such patterns more abstract patterns of larger-scale activity can be derived, providing the observations of virtual collaboration sought. In considering how the extraction of patterns of virtual collaboration fits into the larger context of the conception, design, and use of collaboration systems, a Framework for Pattern Extraction and Feedback is proposed. This framework introduces the notion of collaboration memory, a type of organizational memory that contains records of collaborative activity. Moreover, the framework suggests how extracted patterns of virtual collaboration feed back into both ongoing development and use of collaboration systems.
Dynamic-range compression using digital frequency warping

In this paper, a multi-channel dynamic-range compressor system using digital frequency warping is described. A frequency-warped finite-impulse response (FIR) filter is realized by replacing the filter unit delays with a cascade of all-pass filters. The appropriate design of the frequency warping gives a non-uniform frequency representation very close to the auditory Bark scale. The resultant compressor offers good frequency resolution combined with low time delay, and has a group delay-versus-frequency response that is independent of the compressor gains. Listening tests indicate that the compressor group delay effects will be inaudible for most listeners and speech sounds.
Simulation‐based analysis of the resolution and SNR properties of partial k‐space EPI

In normal echo planar imaging (EPI) sequences, a long data acquisition time not only excessively attenuates the signal obtained from the sequence but also alters its resolution depending on the adjustment of the sequence. In conventional full echo mode, the image resolution is preserved because of the negative high frequency parts. However, signal to noise ratio (SNR) is poor because of attenuation of DC components. So, a new pulse sequence is designed for gradient echo-echo planar imaging (GE-EPI) to solve this problem. Instead of starting acquisition from the maximum point in k-Space, the acquisition point is selected according to the requirement. For example, if good SNR is required then the acquisition point selected is close to zero so as to preserve the DC components. If good resolution is required then the acquisition point selected is close to the maximum negative/positive point so as to preserve the negative/ positive high frequency. If both the SNR as well as good Resolution are required then a selection is made in between zero and maximum negative/positive point. In this way, the acquisition point is varied to get different choices for SNR and Resolution. © 2009 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 35B: 232–237, 2009
Traffic signal timing determination: the Cabal model

Cabal uses a genetic algorithm to optimise traffic signals. The aim in this early version of Cabal is to determine effective timing plans for an isolated intersection using realworld flow data matrices. Initial objectives are minimisation of delays, stops and queue lengths using fixed factor weights. Cabal optimises a cyclic signal control scheme made up of a set sequence of stages. Results of tests on a 5-leg intersection indicate that Cabal could operate effectively in realtime.
Tools for Composite Indicators Building

The views expressed in this report are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use which might be made of the following information A great deal of information on the European Union is available on the Internet. It can be accessed through the Europa server