Miracle-dz/UniFAR-FTUs huggingface dataset:
Extracting Conceptual Knowledge from Text Corpora

Poesio, in preparation. StruDEL: A distributional semantic model based on properties and types Outline Introduction Distributional semantics The TOEFL synonym match task From distributional semantics to conceptual knowledge StruDEL Testing StruDEL Property generation Categorization Other tasks The Human Experience Text corpora Corpora are large electronic collections of texts produced in natural communicative settings Popular in language engineering, lexicography, language teaching/learning since (at least) the nineties Typology and some famous exemplars: Corpora and the human experience Computational modelers in cognitive science (e.g., Rogers and McClelland 2004) typically work with hand-crafted input Corpora are " real " , natural input, akin to what humans hear/read, with same problems of noise and skewed input distribution (Zipf's law) humans must face Computer seen as statistics-driven agent that " learns " from its environment: can it teach us something about human learning? Zipf's law The contextual view meaning Acquisition/representation of meaning/conceptual knowledge is core issue in cognitive science Corpus-based simulations can help! The contextual view meaning Acquisition/representation of meaning/conceptual knowledge is core issue in cognitive science Corpus-based simulations can help! " You should tell a word by the company it keeps " (Firth, 1957) " [T]he semantic properties of a lexical item are fully reflected in appropriate aspects of the relations it contracts with actual and potential contexts [. ] [T]here are are good reasons for a principled limitation to linguistic contexts " (Cruse, 1986) Outline Introduction Distributional semantics The TOEFL synonym match task From distributional semantics to conceptual knowledge StruDEL Testing StruDEL Property generation Categorization Other tasks The Human Experience Distributional semantics Word space models (WSMs) Meaning of word/concept defined by set of contexts in which word occurs in corpus Similarity of words represented as geometric distance among context vectors Distributional semantics Co-occurrence extraction for target word dog The dog barked in the park. The owner of the dog put him on the leash since he barked. bark park owner leash Distributional semantics Co-occurrence extraction for target word dog The dog barked in the park. The owner of the dog put him on the leash since he barked. bark + park owner leash Distributional semantics Co-occurrence extraction for target word dog The dog barked in the park. The owner of the dog put him on the leash since he barked. bark + park + owner leash Distributional semantics Co-occurrence extraction for target word dog The dog barked in the park. The owner of the dog …
Multi-channel analysis of the EEG signals and statistic particularities for epileptic seizure forecast

In France, 5 to 8 people in 1000 suffer from epilepsy. An epileptic seizure is sudden, impressive, and is often followed by a loss of consciousness by the patient. The clinical studies have demonstrated that neuronal activity is responsible for these seizures. The electroencephalograms recorded by the doctors allow the visualization of the very beginning of the crises. The aim of our previous studies was to determine characteristics of the EEG signals that will allow us to forecast the seizures (Peyrodie et al., 2001). We reached the conclusion that using that using principal components analysis, we were able to find out some grapho-elements in the 2 first principal components that where leading us to highlight a state were patients are likely to make a seizure. A new challenge consists in trying to provide an interpretation of these grapho-elements. The first part is concerned in the explanation of the principal components analysis and the results it gave us. The second part is concerned with a statistical study of the principal components using a log-likelihood method. The third part is concerned with the use of independent component analysis to filter the EEG signals.
Förderung ethischer Bewertungskompetenz: der Einfluss ausgewählter Lerngelegenheiten auf dieinhaltliche Ausdifferenzierung und die Kohärenzder Komponenten des fachdidaktischen Wissens vonBiologielehrkräften

Diese Studie beruht auf der Annahme, dass die unterschiedliche Kompetenz von Lehrern im Beruf das Ergebnis von Lerngelegenheiten ist. Fur diese Studie ist sowohl das Strukturmodell zur Lehrerkompetenz von Baumert und Kunter (2011) als auch das Pentagon-Modell von Park und Chen (2012) theorieleitend. Hauptforschungsaufgabe ist es, die Gesamtheit des themenspezifischen fachdidaktischen Inhaltswissens fur den Kompetenzbereich "Bewertung" zu erheben sowie empirisch begrundete Hinweise zu erhalten, wie Lerngelegenheiten die Entwicklung des fachdidaktischen Wissens beeinflussen und wie effektive Fortbildungen im Rahmen der sogenannten "dritten Phase" der Biologielehrerbildung zu gestalten sind. Es wurden inhaltliche Leitlinien fur Lehrerfortbildungen zum Kompetenzbereich Bewertung entwickelt. Der Einsatz von problemspezifizierten Textvignetten mit anschliesender PCK-Kartierung kann zu einer deutlich verbesserten Effizienz von Fortbildungsmasnahmen beitragen.
Première démonstration expérimentale d’un interrupteur HEMT normally-off en GaN avec une région P-GaN enterrée

Un nouveau concept d'interrupteur de puissance HEMT en GaN presentant la fonctionnalite « normally-off » est experimentalement valide. L'introduction d'une couche P-GaN suffisamment dopee (autour de 2 x 10 18 cm-3) au sein de la couche buffer GaN NID, en-dessous de l'electrode de grille et sous l'interface AlGaN / GaN, permet d'obtenir une tension de seuil positive de 0,8 V, soit un decalage significatif superieur a 6 V par rapport a celle d'un HEMT conventionnel « normally-on ».
Teaching for Quality Learning at Changing Universities. A tour de force of modern education history – an interview with Professor John Biggs

Professor John Biggs is a world-famous psychologist and educationist who in 2017, was invested as a Member of the Order of Australia (AM) for “significant service to tertiary education, particularly in the fields of curriculum development and assessment”. John Biggs has been actively involved in education for six decades and has been a Professor of both Education and Psychology. Professor Biggs’ most ground-breaking and innovative contributions – such as SOLO taxonomy, constructively aligned OBTL (Outcome-based Teaching & Learning), criterion-referenced assessment and students’ surface and deep approaches to learning – are all discussed in this wide-ranging interview. Moreover, Biggs discusses his illustrious academic career, his concerns about the corporatisation of universities and his alternative vision of higher education, and also what he refers to, tongue-firmly-in-cheek, as his “constructive but misaligned retirement”.
Visitor and resident perceptions of the slow city movement: the case of Japan

ABSTRACT The concept of Slow Tourism has evolved in recent years, and while the literature discussion about the Cittàslow (Slow City) movement has been increasing, little is known about its application in destinations outside of Europe where it originated. Through a survey of visitors and residents, this study examined the awareness level of the movement in the pioneer case of Japan. The discussion of this paper sought to investigate the movement, as a way to understand the interest in, and appropriateness of increased visibility for Kesennuma Cittàslow, located in the northeast corner of Miyagi prefecture, Japan. The study provides new insights into the Cittàslow phenomenon that has been gaining attention within the academic discourse.
Contribution of Quality of Experience to optimize multimedia services : the case study of video streaming and VoIP

The emerging and fast growth of multimedia services have created new challenges for network service providers in order to guarantee the best user's Quality of Experience (QoE) in diverse networks with distinctive access technologies. Usually, various methods and techniques are used to predict the user satisfaction level by studying the combined impact of numerous factors. In this thesis, we consider two important multimedia services to evaluate the user perception, which are: video streaming service, and VoIP. This study investigates user's QoE that follows three directions: (1) methodologies for subjective QoE assessment of video services, (2) regulating user's QoE using video a rate adaptive algorithm, and (3) QoE-based power efficient resource allocation methods for Long Term Evaluation-Advanced (LTE-A) for VoIP. Initially, we describe two subjective methods to collect the dataset for assessing the user's QoE. The subjectively collected dataset is used to investigate the influence of different parameters (e.g. QoS, video types, user profile, etc.) on user satisfaction while using the video services. Later, we propose a client-based HTTP rate adaptive video streaming algorithm over TCP protocol to regulate the user's QoE. The proposed method considers three Quality of Service (QoS) parameters that govern the user perception, which are: Bandwidth, Buffer, and dropped Frame rate (BBF). The BBF method dynamically selects the suitable video quality according to network conditions and user's device properties. Lastly, we propose a QoE driven downlink scheduling method, i.e. QoE Power Escient Method (QEPEM) for LTE-A. It esciently allocates the radio resources, and optimizes the use of User Equipment (UE) power utilizing the Discontinuous Reception (DRX) method in LTE-A
Asian Long-Range Transport in Relation to Atmospheric Rivers in Northern California

The study investigates the effect of aerosol long-range transport on precipitation over Northern California during atmospheric river (AR) events in the 2017 cold season (January–April). ARs in 2017 were one of the strongest to date, and the intense precipitation associated with the ARs resulted in flooding, destruction of property, and contamination of water supplies. The Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) data shows Asian dust traveling across the Northern Pacific Ocean along with AR events. Aerosol measurements in California, provided by the Interagency Monitoring of Protected Visual Environments (IMPROVE), show that more Asian dust tends to be observed over the coast, while non-Asian/localized dust is observed inland. A mixture of Asian and localized dust is observed over the mountains, although higher amounts of both are observed in the spring (March–April). Back trajectory analysis confirms that Asian aerosols are transported along the air parcels, and each AR event has its own transport pattern in terms of horizontal advection and vertical lifting. Correlation between precipitation and aerosols is low. This suggests that aerosols contribute little to the decrease of local precipitation during the 2017 AR events.
Design and Analysis of Resource Management Software for In-Vehicle IPv6 Networks

SUMMARY Various demands for next generation networks can be condensed into always-best-connected, ubiquitous, mobile, all-IP, applicationaware, and converged networks. Vehicles have also come to be ubiquitous computing platforms associated with mobile communication functions. IPv6 has been introduced for all-IP ubiquitous communications. This paper proposes application-aware resource management for in-vehicle IPv6 networks, which are adaptive to different hardware configurations. We focus on power and bandwidth, since their management is critical for mobile communications. To manage these two critical resources, we identify the mobility characteristics and hardware configurations of in-vehicle networks. Based on these characteristics, we propose vehicle-aware power saving schemes. Our main idea for power saving is to dynamically adjust the mobile router (MR) advertisement interval and binding update lifetime. In addition, depending on the hardware configuration of the wireless environment, we propose two adaptive bandwidth management schemes using multihoming, which we refer to as best-connected MR selection based on location and high-data-rate MR selection based on priority. We evaluate the performance of our bandwidth management schemes by performing simulations, and that of our power saving schemes by mathematical analysis. Based on the results, it was found that the performance of each software scheme depends on the hardware configuration, so that an application
Fully distributed time-varying formation-containment control for large-scale nonholonomic vehicles with an unknown real leader

This paper addresses the time-varying formation-containment (FC) problem for general linear multi-agent systems based on an observer viewpoint under the directed communication graph which contains a spanning tree. A new format of time-varying formation shapes with the properties of translation, scalability and rotation is proposed. Then the time-varying formation tracking problem where the real leader's input is unknown to all other agents is solved independently. After that, the time-varying FC problem where the challenge is how to deal with the formation-achieving agents' unknown nonzero inputs for containment-achieving agents, is firstly addressed. All the designed controllers, which need no eigenvalue information of the whole graph, are fully distributed and so can be applied to large-scale systems. The influence of communication graph structure to the control convergence rate is further analysed. The above theoretical results are verified by multiple nonholonomic vehicles in simulations.
Financial Accounting Measurement Concept, Asset Specificity, and the Application of Fair Value to Ecotourism Enterprises

At present, the measurement attribute of financial accounting is undergoing a transformation from historical cost to fair value, the standard-setting body is trying to expand the application of fair value measurement to projects beyond financial instruments, and eventually establish a new accounting model centered on fair value measurement. The establishment of a new accounting model centered on fair value measurement would mainly depend on whether fair value is applicable to all types of assets. The paper explores the applicability of fair value from a unique perspective – the specificity of assets, and concludes that fair value is not a proper measurement attribute for specific assets, and therefore the future accounting model will not necessarily be dominated by fair value, rather, it is very likely to be a mixed measurement model incorporating historical cost, fair value, and value-in-use.
A lexico-syntactic exploration of Ondo and Ikale dialects of the Yoruba Language

The study was a comparative study of Ondo and Ikale dialects of the Yoruba Language with a view to finding the areas of convergence and divergence between the two dialects. The study was based on 50 sentences from each of the dialects, but only 25 of the sentences were presented. They were anaylsed from the perspective of Halliday Systemic Function Grammar (SFG) in order to identify the prominent lexemes and syntactic structures of the sentences. Simple statistics based on percentages was used to calculate the number of lexemes and structures that are similar and different. It was discovered that the two dialects have basically the same lexemes at both subject and predicator levels. This shows that the speakers of the two dialects often make use of the same nominal and verbal items in their speeches. Besides, the two dialects share basically the same syntactic components - Subjects, Predicator, Complement and Adjunct in all the sentences examined, but the Adjunct is rarely used in the dialects. The dialects are however, found to be mainly different in the area of auxiliary verbs usage. Most of the words or lexemes in the dialects are found in the standard Yoruba, hence the mutual intelligibility of the dialects to an average Yoruba Language native speaker. It is thus envisaged that other dialects of Yoruba Language that are geographically close may equally share similar linguistic features and cultural norms. Key words: Yoruba Language, Ondo, Ikale, dialects.
Yield optimization in large RAM's with hierarchical redundancy

The authors present and analyze large RAM architectures with hierarchical redundancy and determine the optimal redundancy organization for yield enhancement. A two-level redundancy scheme is used for defect tolerance, and the defect distribution is modeled using the compounded Poisson model. The tree random access memory (TRAM), which has been proposed as a design methodology for future multimegabit memories (N. Jarwala et al., 1988) is considered as an example for modeling and optimization. The results show that the two-level hierarchical redundancy approach, with spare bit and word lines within memory quadrants, and additional spare modules for global sparing, along with redundant interconnections can efficiently provide defect tolerance and viable yields for future generations of high-density dynamic random access memories. >
Proceedings of the 1993 Winter Simulation Conference G.W. Evans, M. Mollaghasemi, E.C. Russell, W.E. Biles (eds.) USING UNIVARIATE BEZIER DISTRIBUTIONS TO MODEL SIMULATION INPUT PROCESSIES

In this paper we describe a graphical, interactive technique for modeling univariate simulation input processes with a distribution family based on Bdzier curves. This family has an open-ended parameterization and is capable of accurately representing an unlimited variety of distributional shapes. Our input-modeling technique is implemented in a self-contained, Windows-based software system called PRIME-Pbbabihstic Input Modeling Environment. Several examples illustrate the application of this technique.
Climate change impacts on local people livelihood and its adaptation through agroforestry in coastal district Patuakhali of Bangladesh

The study was carried out in Tiakhali and Lalua unions under Kalapara Upazila at Patuakhali district of Bangladesh to explore the climate change impacts and its adaptation through agroforestry. 85 household questionnaire survey, semi-structured interviews (SSI) and participatory rural appraisal (PRA) techniques were used to collect data. The findings revealed that 86% out of 85 respondents were victim to the impacts of climate change and ‘salinity intrusion’, ‘higher temperature’, and ‘sea level rise’ were identified as three most severe impacts with the opinion of 92%, 89%, and 85% respondents, respectively. From SSI and PRA exercise found the more or less similar results. Moreover, results indicated that the respondents (89.40%) were adopted various agroforestry practices and ‘homestead agroforestry’ and ‘fishery based tree plantation’ was the prioritized agroforestry practices to combat climate change impacts. Correlation (r) analysis revealed that most of the independent variables had a positive relationship with dependent variables. Keywords: Climate change, livelihood, PRA (Participatory rural appraisal), adaptation, agroforestry.
Improved Dynamical Particle Swarm Optimization Method for Structural Dynamics

A methodology to the multiobjective structural design of buildings based on an improved particle swarm optimization algorithm is presented, which has proved to be very efficient and robust in nonlinear problems and when the optimization objectives are in conflict. In particular, the behaviour of the particle swarm optimization (PSO) classical algorithm is improved by dynamically adding autoadaptive mechanisms that enhance the exploration/exploitation trade-off and diversity of the proposed algorithm, avoiding getting trapped in local minima. A novel integrated optimization system was developed, called DI-PSO, to solve this problem which is able to control and even improve the structural behaviour under seismic excitations. In order to demonstrate the effectiveness of the proposed approach, the methodology is tested against some benchmark problems. Then a 3-story-building model is optimized under different objective cases, concluding that the improved multiobjective optimization methodology using DI-PSO is more efficient as compared with those designs obtained using single optimization.
Robust Hyperspectral Unmixing Using Total Variation Regularized Low-Rank Approximation

Hyperspectral unmixing is the process of finding the fractional abundances and corresponding spectral signatures of a mixed pixel in a hyperspectral image. However, several types of noise such as dead pixels, stripes, impulse noise and Gaussian noise called as mixed noise are introduced in the hyperspectral images due to imperfect imaging sensors and atmospheric conditions, which degrades the performance of the unmixing algorithms. We propose a robust semi-supervised unmixing method to obtain the fractional abundances of the spectral signatures based on low-rank representation (LRR)and total variation (TV)using a a priori available spectral library. LRR estimates the global lowest rank representation of the abundance matrix whose columns are the abundance vectors of each pixel and TV regularization promotes the spatial piecewise smoothness of the abundance map. The sparse noise components are suppressed using an $l_{1}$ norm regularization term. Extensive simulation results on synthetic and real hyperspectral data sets show that the proposed method is effective in obtaining the abundance maps under mixed noise.
Holographic technology applied to face location and identification

Holographic technology has been successfully applied on a number of applications in the fields of pattern recognition and prediction. A short review of the face recognition problem introduces one to the fundamental aspects of holographic technology, which are briefly discussed so that their similarities and differences from typical neural nets are shown. Some of the applications of this tool are mentioned in this paper. The image base used is of 31 images of 10 different faces with different facial expressions (happiness, anger and sadness). Data describing these human faces is explained including the sets of data for supervised training and generalization of the holographic cell. The results of applying this technology to face location, for this data set, show that performance is well above 99% accuracy which supports holographic cells as a sound tool for pattern recognition.
An Information Measure for Classification

1. The class to which each thing belongs. 2. The average properties of each class. 3. The deviations of each thing from the average properties of its parent class. If the things are found to be concentrated in a small area of the region of each class in the measurement space then the deviations will be small, and with reference to the average class properties most of the information about a thing is given by naming the class to which it belongs. In this case the information may be recorded much more briefly than if a classification had not been used. We suggest that the best classification is that which results in the briefest recording of all the attribute information. In this context, we will regard the measurements of each thing as being a message about that thing. Shannon (1948) showed that where messages may be regarded as each nominating the occurrence of a particular event among a universe of possible events, the information needed to record a series of such messages is minimised if the messages are encoded so that the length of each message is proportional to minus the logarithm of the relative frequency of occurrence of the event which it nominates. The information required is greatest when all frequencies are equal. The messages here nominate the positions in measurement space of the 5 1 points representing the attributes of the things. If the expected density of points in the measurement space is everywhere uniform, the positions of the points cannot be encoded more briefly than by a simple list of the measured values. However, if the expected density is markedly non-uniform, application