Miracle-dz/UniFAR-FTUs huggingface dataset:
Function Alternations of the Mandarin Particle Dou: Distributor, Free Choice Licensor, and 'Even'

Many languages have particles that possess multiple logical functions. Take the Mandarin particle dou for example. Varying by the item it is associated with and the prosodic pattern of the environment it appears in, dou can trigger a distributivity effect, license a preverbal free choice item, or evoke an even-like inference. Considering universal grammar a simple system, we need to figure out, for a multi-functional particle, which of its functions is primary, what parametric variations are responsible for the alternations in function, and how these variations are conditioned. In this paper, I argue that the seemingly unrelated functions of dou share the same source: dou is a pre-exhaustification exhaustifier operating on sub-alternatives. Uniformly, dou affirms the truth of its propositional prejacent, negates the exhaustification of each sub-alternative, and presupposes a non-vacuity inference that there is at least one sub-alternative. Alternations in function result from minimal weakening operations on the semantics of sub-alternatives. In particular, sub-alternatives are primarily weaker alternatives, and the non-vacuity presupposition of dou yields a distributivity effect. When the semantics of sub-alternatives is weakened under particular syntactic or prosodic conditions, dou gains its other logical functions.
Cross-Lingual Lemmatization and Morphology Tagging with Two-Stage Multilingual BERT Fine-Tuning

We present our CHARLES-SAARLAND system for the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology, in task 2, Morphological Analysis and Lemmatization in Context. We leverage the multilingual BERT model and apply several fine-tuning strategies introduced by UDify demonstrating exceptional evaluation performance on morpho-syntactic tasks. Our results show that fine-tuning multilingual BERT on the concatenation of all available treebanks allows the model to learn cross-lingual information that is able to boost lemmatization and morphology tagging accuracy over fine-tuning it purely monolingually. Unlike UDify, however, we show that when paired with additional character-level and word-level LSTM layers, a second stage of fine-tuning on each treebank individually can improve evaluation even further. Out of all submissions for this shared task, our system achieves the highest average accuracy and f1 score in morphology tagging and places second in average lemmatization accuracy.
Modelling Requirements for EURACE Responsible

This document presents the initial modelling requirements for the development of the EURACE simulator. It is a survey of market mechanisms, trading protocols and learning algorithms. Its main purpose is to provide a catalogue of modelling choices and to serve as a background survey for the EURACE project as a whole. Acknowledgements This work was supported by the European Union through its 6th Framework Programme, FET-IST ’Complex Systems’. Funding for the STREP research project ‘EURACE’ under contract no. 035086, is gratefully acknowledged. The following persons have contributed to this paper. Andrea Teglio contributed to Section 7 on learning mechanisms. Discussions with Eric Guerci on the electricity markets in Section on 6.2 are gratefully acknowledged. General discussions on the topics in this paper have been held at various stages of development during the EURACE meetings. The first was held in Ancona, 27 October 2006 and the second was held in Nice, 26-28 January 2007. The usual disclaimer applies.
Evaluating Automotive Antennas for Cellular Radio Communications

Cellular connectivity plays an important role for the future development of automated and connected driving and intelligent traffic. An internet connection based on a 5G network can offer new services as entertainment (media streaming) or traffic information for improved navigation and cruising. Development and testing automotive antenna designs is time consuming and expensive. An open question is the evaluation of different antennas within a realistic environment. To fill this gap and facilitate optimal antenna design we introduce three scoring indicators to compare automotive antennas for cellular mobile communications and estimate their performance. This approach can be applied both to measured data and simulation results. The indicators help to make decisions on the type of integrated antenna by considering throughput as well as network coverage.
Crystal structure of (3aS,4R,5S,6R,6aS)-4,5,6-triacetoxy- 1-benzyl-3,3a,4,5,6,6a-hexahydro-1H-cyclopent[c]-isoxazole, C19H23NO7

C19H23NO7, orthorhombic, P2i2i2i (No. 19), a = 8.297(4) Â, b = 9.266(4) À, c = 25.17(1) À, V = 1935.3 À, Z = 4, Rgl(F) = 0.057, R*(F) = 0.160, T= 293 K. Source of material The title compound has been obtained by intramolecular nitrone cycloaddition [1-3]. Starting from methyl 6-iodo-2,3,4-tri-Oacetyl-a-D-manno-pyranoside [4,5], reaction with zinc and vitamin Β12 as catalyst afforded the corresponding 5-hexenose [5,6], which was transformed into the title compound without further purification by addition of Af-benzyl-hydroxy lamine and pyridine as a base (d. r. > 95/5). Purification by flash chromatography on silica and crystallization from ethyl acetate gave the isoxazolidine, (mp 382 K 383 Κ, [a]TM=-120, c = 0.87, CHCI3). Discussion The packing diagramme shows antiparallel strangs along the ¿»-axis. Table 1. Data collection and handling. Crystal: colourless block, size 0.5 χ 0.75 χ 1.25 mm Wavelength: Mo Ka radiation (0.71073 Â) μ: 0.99 cm" 1 Diffractometer, scan mode: Nicolet P3, Wyckoff
A Phonetic Rule-based Approach for Generating Casual English Sentences

We present a system for generating casual English short sentences from regular English input using a phonetic rule-based approach. This is addressed as an AI task, with the potential application of generating Twitter-style sentences for marketing or other communication purposes. Our aim was to automatically produce sentences that would appear to a human reader to be indistinguishable to sentences which are the result of human creativity. To evaluate the performance of the system, we conducted Turing-type tests with human readers, to consider firstly “human-likeness”, and also “legibility” of the sentences. In this paper, we discuss the overall design of the system, the custom-made phoneme database, and the process and results of our evaluation experiment.
Two-step fault diagnosis framework for rolling element bearings with imbalanced data based on GSA-WELM and GSA-ELM

Rolling element bearings constitute the key parts on rotating machinery, and their fault diagnosis is of great importance. In many real bearing fault diagnosis applications, the number of fault data is much less than the number of normal data, i.e. the data are imbalanced. Many traditional diagnosis methods will get low accuracy because they have a natural tendency to favor the majority class by assuming balanced class distribution or equal misclassification cost. To deal with imbalanced data, in this article, a novel two-step fault diagnosis framework is proposed to diagnose the status of rolling element bearings. Our proposed framework consists of two steps for fault diagnosis, where Step 1 makes use of weighted extreme learning machine in an effort to classify the normal or abnormal categories, and Step 2 further diagnoses the underlying anomaly in detail by using preliminary extreme learning machine. In addition, gravitational search algorithm is applied to further extract the significant features and determine the optimal parameters of the weighted extreme learning machine and extreme learning machine classifiers. The effectiveness of our proposed approach is testified on the raw data collected from the rolling element bearing experiments conducted in our Institute, and the empirical results show that our approach is really fast and can achieve the diagnosis accuracies more than 96%.
Graceful Degradation of Adaptive Multiprocessor Systems on a Chip

This thesis explores the potential for using existing flexibility in order to allow Multiprocessor Systems on a Chip to function in the presence of permanent faults and to prolong their lifetime. Technology scaling in accordance with Moore’s law brings up reliability challenges and forces the use of potentially unreliable hardware components. However, hardware reconfigurability and workload flexibility can provide the means for permanent fault tolerance and graceful degradation via runtime system management. This work first elaborates on the concept of degradable hardware components and presents a methodology for characterizing each of their possible configurations. This is necessary if we intend to use this reconfigurability in an efficient manner to work around permanent faults. The characterization methodology is used to perform design space exploration aiming to find the optimal reconfiguration granularity for any given fault density. Subsequently, Graceful Degradation of Multiprocessor Systems on a Chip is defined as an optimization problem. Three algorithms are proposed for solving this problem within reasonable time, in order to be applicable at runtime: A novel fast heuristic based on incremental and partially precomputed solutions, and our versions of two well established search algorithms (simulated annealing and genetic algorithm), tailored to the particular problem. The fast heuristic is proven able to find a solution on average 81.9% as good as the exhaustively sought optimal one, in less than 2μsec on average. Our versions of simulated annealing and genetic algorithm find on average better solutions (86.6% and 89.6% as good as the optimal respectively), at the cost of one and two orders of magnitude slower execution time.
About vocabulary adaptation for automatic speech recognition of video data

This paper discusses the adaptation of vocabularies for automatic speech recognition. The context is the transcriptions of videos in French, English and Arabic. Baseline automatic speech recognition systems have been developed using available data. However, the available text data, including the GigaWord corpora from LDC, are getting quite old with respect to recent videos that are to be transcribed. The paper presents the collection of recent textual data from internet for updating the speech recognition vocabularies and training the language models, as well as the elaboration of development data sets necessary for the vocabulary selection process. The paper also compares the coverage of the training data collected from internet, and of the GigaWord data, with finite size vocabularies made of the most frequent words. Finally, the paper presents and discusses the amount of out-of-vocabulary word occurrences, before and after update of the vocabularies, for the three languages.
Innovation Research Programme DISCUSSION PAPER SERIES No . 012 Intellectual Property , Technology and Productivity Information Technology , Organization and Productivity in the Public Sector : Evidence from Police Departments

We examine how information technology (IT) contributes to organizational change, labor demand, and improved productivity in the public sector using a new panel data set of police departments covering 1987-2003. While IT adoption is associated with increased administrative and organizational complexity and use of more highly educated officers, IT itself does not appear to enhance crime-fighting effectiveness. These results are robust to various methods for controlling for agency-level characteristics and the endogeneity of IT use. IT investments do, however, appear to improve police productivity when complemented with particular management practices–in this case, those associated with the Compstat program.
Qualitative, quantitative, and data mining methods for analyzing log data to characterize students' learning strategies and behaviors [discussant]

This symposium addresses how different classes of research methods, all based upon the use of log data from educational software, can facilitate the analysis of students’ learning strategies and behaviors. To this end, four multi-method programs of research are discussed, including the use of qualitative, quantitative-statistical, quantitative-modeling, and educational data mining methods. The symposium presents evidence regarding the applicability of each type of method to research questions of different grain sizes, and provides several examples of how these methods can be used in concert to facilitate our understanding of learning processes, learning strategies, and behaviors related to motivation, meta-cognition, and engagement.
DRBAC: Dynamic Row Buffer Access Control for Power and Performance of DRAM Systems

—Performance of dynamic random access memory (DRAM) has been steadily improved to overcome the concern that the DRAM access time may become the performance bottleneck of a system. Besides, DRAM power consumption has become a critical issue in mobile and server systems. The open page policy is widely used to minimize the memory access latency and the power consumption of the activate and the precharge commands. In this paper, we analyze DRAM power and performance according to memory request characteristics of applications. Especially, we observe that the row buffer access control influences the overall performance and power consumption. Further, the power-delay product (PDP) is sensitive to the row buffer hit ratio and the memory request frequency. Thus, we propose a method called dynamic row buffer access control (DRBAC) that changes the row buffer access limit dynamically based on the memory request characteristics. From simulation results, it is verified that DRBAC reduces the PDP value by up to 17.8% compared to the conventional method for various benchmarks. Therefore, we conclude that the proposed DRBAC is very effective for low power and high performance DRAM systems.
Perceptual Quality of Internet Telephony over {IEEE} 802.11e Supporting Enhanced {DCF} and Contention Free Bursting

As the IEEE 802.11 based internet access is becoming ubiquitos available it is excepted that WLAN will be applied for telephony. In this paper we follow the objective to access whether WLAN allows calls at toll quality. Toll quality is the minimal quality of PSTN-based telephons calls. With simulations we evaluate the MAC protocol modes distribution coordination function (DCF), enhanced DCF (EDCF) and contention free bursting (CFB). We have verifed our simulation model by cross-checking it with the results of other researchers. We present quantitative results of the perceptual quality and enhance the precision of performance evaluation on Voice over Wifi systems.
Low Power and Low Voltage Double Tail Dynamic Latch Comparator using 180nm Technology

The requirement for highly integrated and programmable analog-to-digital converters (ADCs), area efficiency, and ultra-low-power and high speed analog-to-digital converters is pushing toward the use of dynamic regenerative comparators to amplify speed and power efficiency. In this paper, analytical expressions are derived and an analysis on the delay of the dynamic comparators will be presented. From the analytical expressions, designers can obtain an instinct about the main contributors to the comparator delay and fully explore the tradeoffs in dynamic comparator design. Based on the analysis made, a new dynamic comparator is proposed, where the circuit of a conventional double tail comparator is modified for fast operation and low-power even in small supply voltages. By adding few transistors, the positive feedback during the regeneration is strengthened, which results in remarkably reduced delay time. Post-layout simulation results in an 180nm CMOS technology confirm the analysis results.
Tecnología educativa y su papel en el logro de los fines de la educación

espanolEste trabajo esta dirigido a develar el papel que tiene la tecnologia educativa en el logro de los fines de la educacion. Para alcanzar esta empresa se aplico la tecnica de analisis de contenidos a diversas obras y publicaciones referidas a la tematica del estudio, asi como a documentos emitidos por organismos internacionales y nacionales con inherencia en materia educativa. Se determino que la educacion puede lograr sus finalidades mas trascendentales mediante el uso sistematico de la tecnologia educativa, que emplea diversos medios y recursos para el aprendizaje escolar, ya sean los tradicionales (libros, pizarra, entre otros), o las herramientas que ofrecen las tecnologias de informacion y comunicacion (TIC); concepto que no puede considerarse equivalente al de tecnologia educativa. EnglishThis research seeks to unveil the role of Educational Technology in the achievement of educational purposes. In order to do so, the content analysis technique was used to conduct a thematic analysis of the several papers and publications related to this study, as well as documents submitted by national and international organizations related to the educational field. It was determined that education can achieve its most significant purposes though the systematic use of educational technology, which employs various means and resources in the process of school learning, it could refer to traditional resources (books, whiteboard, and others) or the Information and Communication Technology (ICT) tools; concept that cannot be considered equivalent to Educational technology.
A Hybrid Approach for Virtual Machine Migration in Cloud Computing Environment

A lot of research has been done in the field of cloud computing in computing domain. For its effective performance, variety of algorithms has been proposed. The role of virtualization is significant and its performance is dependent on VM Migration and allocation. More of the energy is absorbed in cloud; therefore, the utilization of numerous algorithms is required for saving energy and efficiency enhancement in the proposed work. In the proposed work, green algorithm has been considered with meta heuristic algorithms, ABC (Artificial Bee colony . Every server has to perform different or same functions. A cloud computing infrastructure can be modelled as Primary Machineas a set of physical Servers/host PM1, PM2, PM3… PMn. The resources of cloud infrastructure can be used by the virtualization technology, which allows one to create several VMs on a physical server or host and therefore, lessens the hardware amount and enhances the resource utilization. The computing resource/node in cloud is used through the virtual machine. To address this problem, data centre resources have to be managed in resource -effective manner for driving Green Cloud computing that has been proposed in this work using Virtual machine concept with ABC and Neural Network optimization algorithm. The simulations have been carried out in CLOUDSIM environment and the parameters like SLA violations, Energy consumption and VM migrations along with their comparison with existing techniques will be performed.
Evolution of neutral oxygen during the epoch of reionization and its use in estimating the neutral hydrogen fraction

We use synthetic sightlines drawn through snapshots of the Technicolour Dawn simulations to explore how the statistics of neutral oxygen (${\mathrm{O}\,{\small I}}$) absorbers respond to hydrogen reionization. The ionization state of the circumgalactic medium (CGM) initially roughly tracks that of the intergalactic medium, but beginning at z = 8 the CGM grows systematically more neutral owing to self-shielding. Weak absorbers trace diffuse gas that lies farther from haloes, hence they are ionized first, whereas stronger systems are less sensitive to reionization. The overall ${\mathrm{O}\,{\small I}}$ covering fraction decreases slowly with time owing to competition between ongoing enrichment and gradual encroachment of ionization fronts into increasingly overdense gas. While the declining covering fraction is partially offset by continued formation of new haloes, the ionization of the diffuse gas causes the predicted line-of-sight incidence rate of ${\mathrm{O}\,{\small I}}$ absorbers to decline abruptly at the overlap epoch, in qualitative agreement with observations. In comparison to the recently observed equivalent width (EW) distribution at z ≈ 6, the simulations underproduce systems with $\mathrm{EW} \ge 0.1 \mathring{\rm A}$, although they reproduce weaker systems with $\mathrm{EW} \ge 0.05 \mathring{\rm A}$. By z ≈ 5, the incidence of $\mathrm{EW} \lt 0.1 \mathring{\rm A}$ systems are overproduced, consistent with previous indications that the simulated ionizing background is too weak at z < 6. The summed column densities of $\mathrm{Si}\,{\small II}$ and $\mathrm{Si}\,{\small IV}$ trace the total oxygen column, and hence the ratio of the ${\mathrm{O}\,{\small I}}$ and $\mathrm{Si}\,{\small II}+ \mathrm{Si}\,{\small IV}$ comoving mass densities traces the progress of reionization. This probe may prove particularly useful in the regime where $x_{\mathrm{H}\,{\small I}} \gt 10{{\ \rm per\ cent}}$.
Single-electron tunneling PbS/InP neuromorphic computing building blocks

We study single-electron tunneling (SET) characteristics in crystalline PbS/InP junctions, that exhibit single-electron Coulomb-blockade staircases along with memory and memory-fading behaviors. This gives rise to both short-term and long-term plasticities as well as a convenient non-linear response, making this structure attractive for neuromorphic computing applications. For further insights into this prospect, we predict typical behaviors relevant to the field, obtained by an extrapolation of experimental data in the SET framework. The estimated minimum energy required for a synaptic operation is in the order of 1 fJ, while the maximum frequency of operation can reach the MHz range.