Miracle-dz/UniFAR-FTUs huggingface dataset:
Are we promoting critical autonomous thinking ? Observation of conversational genres can help us answer that question – but it is not enough

This work is based on the assumption that if the classroom is a space which triggers the appearance of manifestations of critical autonomous thinking, then it will promote that kind of thinking by the students, in other contexts. But what counts as a manifestation of critical autonomous thinking and how can we observe them? As Robert Young’s work on indoctrination and conversational genres seemed a promising conceptual framework for understanding what goes on in the classroom in this respect, we took it as a starting point for exploring answers to this question. Our exploration both through fieldwork and theoretical reflection, led us to some conclusions, among which are 1) the postulation of new genres which refine the conceptual categories originally formulated by Young; 2) the finding that analysis of function is not enough, requiring also a contents dimension with which one can analyse what critical autonomous thinking is promoted about, in particular classroom situations; and 3) the finding that classroom situations are frequently more contradictory and fragmented than presupposed by the very idea of genre.
Analysis of some batch arrival queueing systems with balking, reneging, random breakdowns, fluctuating modes of service and Bernoulli schedulled server vacations

The purpose of this research is to investigate and analyse some batch arrival queueing systems with Bernoulli scheduled vacation process and single server providing service. The study aims to explore and extend the work done on vacation and unreliable queues with a combination of assumptions like balking and re-service, reneging during vacations, time homogeneous random breakdowns and fluctuating modes of service. We study the steady state properties, and also transient behaviour of such queueing systems. Due to vacations the arriving units already in the system may abandon the system without receiving any service (reneging). Customers may decide not to join the queue when the server is in either working or vacation state (balking). We study this phenomenon in the framework of two models; a single server with two types of parallel services and two stages of service. The model is further extended with re-service offered instantaneously. Units which join the queue but leave without service upon the absence of the server; especially due to vacation is quite a natural phenomenon. We study this reneging behaviour in a queueing process with a single server in the context of Markovian and non-Markovian service time distribution. Arrivals are in batches while each customer can take the decision to renege independently. The non-Markovian model is further extended considering service time to follow a Gamma distribution and arrivals are due to Geometric distribution. The closed-form solutions are derived in all the cases. Among other causes of service interruptions, one prime cause is breakdowns. We consider breakdowns to occur both in idle and working state of the server. In this queueing system the transient and steady state analysis are both investigated. Applying the supplementary variable technique, we obtain the probability generating function of queue size at random epoch for the different states of the system and also derive some performance measures like probability of server‟s idle time, utilization factor, mean queue length and mean waiting time. The effect of the parameters on some of the main performance measures is illustrated by numerical examples to validate the analytical results obtained in the study. The Mathematica 10 software has been used to provide the numerical results and presentation of the effects of some performance measures through plots and graphs.
Upper tropospheric ozoneproduction from lightning NO x-impacted convection : Smoke ingestion case study from the DC 3 campaign

As part of the Deep Convective Cloud and Chemistry (DC3) experiment, the National Science Foundation/National Center for Atmospheric Research (NCAR) Gulfstream-V (GV) and NASA DC-8 research aircraft probed the chemical composition of the inflow and outflow of two convective storms (north storm, NS, south storm, SS) originating in the Colorado region on 22 June 2012, a time when the High Park wildfire was active in the area. A wide range of trace species were measured on board both aircraft including biomass burning (BB) tracers hydrogen cyanide (HCN) and acetonitrile (ACN). Acrolein, a much shorter lived tracer for BB, was also quantified on the GV. The data demonstrated that the NS had ingested fresh smoke from the High Park fire and as a consequence had a higher VOC OH reactivity than the SS. The SS lofted aged fire tracers along with other boundary layer ozone precursors and was more impacted by lightning NOx (LNOx) than the NS. The NCARmaster mechanism boxmodel was initialized withmeasurements made in the outflow of the two storms. The NS and SS were predicted to produce 11 and 14 ppbv of O3, respectively, downwind of the storm over 2 days. Sensitivity tests revealed that the ozone production potential of the SS was highly dependent on LNOx. Normalized excess mixing ratios, ΔX/ΔCO, for HCN and ACN were determined in both the fire plume and the storm outflow and found to be 7.0 ± 0.5 and 2.3 ± 0.5 pptv ppbv , respectively, and 1.4 ± 0.3 pptv ppbv 1 for acrolein in the outflow only.
Augmenting a German Morphological Database by Data-Intense Methods

This paper deals with the automatic enhancement of a new German morphological database. While there are some databases for flat word segmentation, this is the first available resource which can be directly used for deep parsing of German words. We combine the entries of this morphological database with the morphological tools SMOR and Moremorph and a context-based evaluation method which builds on a large Wikipedia corpus. We describe the state of the art and the essential characteristics of the database and the context method. The approach is tested on an inflight magazine of Lufthansa. We derive over 5,000 new instances of complex words. The coverage for the lemma types reaches up to over 99 percent. The precision of new found complex splits and monomorphemes is between 0.93 and 0.99.
Graphical Tool to integrate the Prometheus AEOlus methodology and Jason Platform

Software Engineering (SE) is an area that intends to build highquality software in a systematic way. However, traditional software engineering techniques and methods do not support the demand for developing Multiagent Systems. Therefore a new subarea has been studied, called Agent Oriented Software Engineering (AOSE). The AOSE area proposes solutions to issues related to the development of agent oriented systems. There is still no standardization in this subarea, resulting in several methodologies. Another predominant factor for the instability of this subarea is the limited supporting tools available. The main purpose of this paper is to present an Eclipse plug-in to support Prometheus AEOlus methodology. Additionally, we have created a mechanism that is able to automatically generate code to AgentSpeak language, which is the base language of the Jason platform.
Visualization for seeking and comparing clinical trials

The sheer quantity of information available on the Internet poses a challenge to users who need an efficient way of finding the information most relevant to their needs. One of the most frequent information-seeking activities of Internet users is the search for health and medical information. In this research, I focus on the user process of seeking information on clinical trials which are the only evidence-based source of information in the medical domain. Through my work, I show that improvements for seeking clinical-trial information could be made to enhance the effectiveness of seeking and gathering results from clinical trials. Unfortunately, little work has been reported on alternative methods and on visualization systems in particular for these enhancements. I suggest that this omission may be due to a lack of understanding of the particular information needs of users of clinical-trial data. Understanding the users’ needs is the first step towards providing more effective interfaces to support them in the information seeking process.
The effects of varying levels of Nigella sativa seed meal supplementation on nutrient digestibility and rumen fermentation characteristics in goats ( Kesan nilai berbeza-beza suplemen diet hampas biji Nigella sativa

The supplementations of various herbal feed additives with many nutritional properties have been widely investigated. The present study aims to investigate the effects of Nigella sativa seed meal (NSM) supplementation on nutrient digestibility and rumen fermentation characteristics of goats. In doing so, five mixed breed adult male goats were fed ad libitum with guinea grass hay (as basal diet), supplemented with NSM (DMI based on 1.5% of body weight) at 0% (NSM0), 0.8% (NSM8), 1.6% (NSM16) and 2.4% (NSM24). A mixture of Feral with Boer and Katjang breed of goats were used in this study. This study was carried out as a cross-over design of a 3-week cycle (2-weeks of adaptation and 1-week of experimental) and resumed after 1-week of washout period. It was revealed that there were no significant differences in nutrient digestibility of DM, OM, CF, DE, ADF, ADL and NDF, rumen pH, total VFA, individual VFA proportions and acetate: propionate ratio between control and NSM supplemented groups. Therefore, the results has proven that the addition of 0.8%, 1.6% and 2.4% NSM supplementation did not cause any adverse impact on feed digestibility and rumen fermentation characteristics of the goats. However, a larger number of replicates on the tolerance levels of NSM concentration in the dietary treatment of goats should be studied further.
POSITIVE CHARACTERISTIC METHODS IN COMMUTATIVE ALGEBRA

These are notes of ten lectures given at IIT Bombay in June 2017 on applications of tight closure theory. The theory was developed by Melvin Hochster and Craig Huneke in the paper [HH2]; excellent accounts may be found in Huneke’s CBMS lecture notes [Hu], and Hochster’s course notes [Ho5]. At this stage, it has become a formidable task to give anything close to a comprehensive treatment of tight closure theory; our intention here is only to talk about a few concrete applications, and emphasize the concise and elegant proofs that the theory offers. These notes focus on applications to the Anand-Dumir-Gupta Conjectures about magic squares, the Hochster-Roberts Theorem regarding the Cohen-Macaulay property of rings of invariants, the Briançon-Skoda Theorem in complex analytic geometry, and uniform bounds on symbolic powers of ideals due to Ein-Lazarsfeld-Smith and Hochster-Huneke.
A Novel Approach for Genuinity Analysis of Hotel Online Reviews

: Background: Since previous decades Internet as well as smart phones have become easily accessible to maximum people. This has made social networking an integral part of human life. People are sharing their comments and reviews on the forum or portal about their views and experiences. These reviews help others to judge the brand value of any product. Even in taking the final decisions about the brand selections for best hotels, colleges and products people are gradually depending on the previous online reviews. In such scenario, some companies may indulge themselves in generating the fake reviews with wrong intentions to create the positive or negative hype about the particular products. It may mislead the customers and decision makers. Objectives: Objective is to develop an algorithm to development of the optimal machine learning algorithm for hotel reviews Efforts are made to remove maximum limitations and constraints of existing algorithms to develop a robust algorithm. Methodology: After finding the gaps appropriate mathematical models are proposed to be implemented to detect genuinety of the reviews based on behavior metrics, quantify the past trust analysis of the reviewer, group membership activities and quantify the sentimental analysis for the hotels. Findings: Due to filtration of the spam reviews and fake reviewers, systematic predication about the hotel facilities and ambience may be done that will encourage the customer to use the hotel booking website that will utilize such algorithms. Applications/Improvements: Although this work is specifically proposed for helping customers in selection of the best hotels by analyzing the previous online reviews, and help in concluding the right decision based on Location, Security, Price, Quality, Ambiance etc. Yet the something similar model may be designed after minor modifications for taking right decision in selecting the best colleges,
Modal Analysis of aSmall H-Darrieus Wind Turbine Based on 3 D CAD , FEA

Rotary machines have many rotating structures necessity design-optimization. Their structure motions are controlled at low-frequency by rigidity, at high-frequency by inertia and at resonance level by damping. Using modal model, dynamic design of the structure developed can be predicted, analyzed and improved. Recently, H-Darrieus wind turbine (HDWT) has received considerable attention due to its inherent structural characteristics. This machine intends a promising design of renewable energy conversion system in urban and isolatedareas. Though, the system suffers fromseveral dynamic problems caused by geometry, centrifugal and aerodynamic cyclic loadings. Present paper investigated dynamic design-optimization of a three-bladed (HDWT) based on its natural structural parameters using 3D-CAD-FEA using SolidWorks modeling and simulationsoftware. From simulation results obtained, (i) the minimum static safety factor of the wind turbine materials is equal to 1.4. It is greater than that recommanded by the international standard IEC61400-1, assessing an acceptable value to1.35 when the mass of the system is not obtain by weighting; (ii) the first three natural frequencies of the system are (17.73, 17.99 and 21.07Hz), the resultant mass participates (10.55, 10.44 and 0.04%), the modal damping (9.19, 9.17 and 9.05%), also resonant amplification (5.44, 5.44 and 5.52), magnitude ratios (100, 97.13 and 70.82%)are calculated and mode shapes associated are predicted and analyzed; and (iii) critical operating conditions of wind turbine under forced excitations due to the wind speeds at various regimes are also treated and assessed. The static and dynamic stability and reliability of the system are shown since all quality indicators tested are consistent according to structure dynamics standards made in steel materials. KeywordsH-Darrieus wind turbine, Structuredynamics, Design-optimization, Static-analysis, Modal-analysis, 3D-CAD-FEA.
Improving Japanese semantic-role-labeling performance with transfer learning as case for limited resources of tagged corpora on aggregated language

In this paper we proposed the use of effective features and transfer leaning to improve the accuracies of neural-network-based models for accurate semantic role labeling (SRL) of Japanese, which is an aggregated language. We ﬁrst reveal that the ﬁnal morphemes in each argument, which have not been discussed in previous work on English SRL are effective features in determining semantic role labels in Japanese. We then discuss the possibility of using large-scale training corpora annotated with different semantic labels from the target semantic labels by transfer learning on CNN, 3-LNN, and GRU models. The experimental results of Japanese SRL on the proposed models indicate that all of the neural-network-based models performed better with transfer learning as well as using the feature vectors of ﬁnal moprhemes in each argument.
Application of Wavelet Neuro-Fuzzy System (WNFS) method for stock forecasting

Forecasting is a very important element in decision making, because the effectiveness of a decision, generally depends on several factors that we cannot see when the decision was taken. In this study, the Wavelet Neuro-Fuzzy System (WNFS) model that combines wavelet transformation and neuro-fuzzy techniques is applied to forecast daily closing stock price data of BMRI.JK. The observed daily stock price data are decomposed into some sub-series components by maximal overlap discrete wavelet transform (MODWT), then the appropriate sub-series that have higher correlation to the real data are used as inputs of the neuro-fuzzy model for daily forecasting stock price for three days in advance. The neuro-fuzzy model is begun with determining the membership value of each data using Fuzzy C-Means, followed by fuzzy inference procedure of the Sugeno model. The result shows that the presence of wavelet input in Neuro-Fuzzy System, can provide optimal prediction in daily stock price data, with small error value of predicted result. This would be helped investors or economists to produce meaningful information in either buy or sell a stock.
Identifikation asymmetrischer Preisanpassungsprozesse für integrierte Zeitreihen / The Identification of Asymmetrie Price Transmission Processes with Integrated Time Series

Zusammenfassung In vielen Studien werden die Erkenntnisse der Cointegrationstheorie bei der Bestimmung symmetrischer Preisanpassungen auf räumlich oder vertikal getrennten Märkten umgesetzt. Bei der Identifikation asymmetrischer Preisanpassungsprozesse hingegen wird immer noch der Ansatz von Wolffram aus dem Jahre 1971 benutzt. Im folgenden Beitrag werden die Unzulänglichkeiten dieses Ansatzes aufgezeigt. Darauf aufbauend werden unter Berücksichtigung der Eigenschaften integrierter Prozesse adäquate Modelle zur Messung asymmetrischer Preisanpassungsprozesse entwickelt. Diese Modelle werden auf Preisdaten für den Weltweizenmarkt angewendet, für den erst kürzlich - unter Verwendung des klassischen Ansatzes - asymmetrische Preisanpassungsreaktionen nachgewiesen wurden (Mohanty, Peterson & Kruse 1995). Summary Many studies of symmetric price transmission between vertically or spatially linked markets make use of cointegration methods. When estimating asymmetric price transmission, however, a method developed by Wolffram in 1971 is still used. This method fails to consider the time series properties of integrated processes. We explore the relationship between asymmetric price transmission and cointegration and demonstrate that Wolffram’s approach is incompatible with cointegration between two price series. We then develop an alternative method for the estimation of asymmetric transmission between integrated time series. This method is applied to wheat price data from the world’s major exporters, data for which Mohanty, Peterson & Kruse (1995), using Wolffram’s approach, have recently presented evidence of asymmetric transmission.
Low SWaP SWIR video engine for image intensifier replacement

Night Vision Imaging in the Short-Wave Infra-Red (SWIR) has some unique advantages over Visible, Near Infra-Red (NIR) or thermal imaging. It benefits from relatively high irradiance levels and intuitive reflective imaging. InGaAs/InP is the leading technology for two-dimensional (2D) SWIR detector arrays, utilizing low dark current, high efficiency and excellent uniformity. SCD's SWIR Imager is a low Size, Weight and Power (SWaP) video engine based on a low noise 640x512/15μm InGaAs Focal Plane Array (FPA) embedded in a low cost plastic package which includes a Thermo-Electric Cooler (TEC). The SWIR Imager dimensions are 31x31x32 mm3, it weighs 50 gram and has less than 1.4W Power consumption (excluding TEC). It supports conventional video formats, such as Camera Link and BT.656. The video engine image processing algorithms include Non-Uniformity Correction (NUC), Auto Exposure Control (AEC), Auto Gain Control (AGC), Dynamic Range Compression (DRC) and de-noising algorithms. The algorithms are specifically optimized for Low Light Level (LLL) conditions enabling imaging from sub mlux to 100 Klux light levels. In this work we will review the optimized video engine LLL architecture, electro-optical performance and the applicability to night vision systems.
Psychic closure: A prerequisite for the recognition of the sign-function?

When Peirce stated that 'a sign . is something which stands for something to somebody in some respect or capacity' (Peirce 1897, in Buchler 1955: 125), he clearly stressed its relational or triadic nature: if there are 'signs of meaning in the universe' (cf. Hoffmeyer 1996), they are always signs to someone, never signs as such. If signs stand for something, they inevitably stand for something to somebody. In other words, the sign-function has to be, implicitly or explicitly, recognized by someone; systems have in some sense to 'realize' the sign-function. The Peircean sign-conception is committed to a universe populated by dynamical, 'subjective', systems, i.e., beings that have developed some kind of autonomy out of which they are able to take something as standing for something else. So, if we want to understand signifying practices in Peircean terms, it is capital to understand (i) what makes systems into systems, (ii) how their being systems leads to the capacity of realizing and/or recognizing the sign-function, (iii) whether, and to what extent, our often intuitive, human-centered understanding of the sign determines our understanding of the workings of the sign-function in other types of systems. Biosemiotics, defined as 'the study of informational, communicative and semiotic aspects of living entities and processes' (as stated by Emmeche and Hoffmeyer in the call for papers in the present issue), argues that the above questions can, and have to be, pertinently and coherently addressed for living systems in general. It incites us to transgress the borders of human sign-practices and of human-centered ways of understanding, by considering them as part of signifying practices of living systems at large. However, it doesn't relieve us from the task of understanding in what way human systems, as living systems, express, specify, and particularize the kind of'sign-logic' that is supposed to be at work in living systems. Nor does it relieve us from addressing the question
Expertensystem zur Diagnoseunterstützung bei Hörprüfungen ( - Expert System for Aiding the Diagnosis in Hearing Screening (

Für Expertensysteme zur Diagnoseunterstützung wird eine Struktur mit fünf Ebenen vorgeschlagen. Diese Ebenen sind der Originalbereich, der Parameterund ein reduzierter Parameter-, bereich, die Klassifikationsund die abschließende Entscheidungsebene. Unter Nutzung dieser Struktur wurde ein Expertensystem speziell für das fruhkindliche Horscreening mit transito"> Tisch evozierten otoakustischen Emissionen (TEOAE) entwickelt. In einem nächsten Schritt l r wurde dieses System auf seine Eignung zur Bewertung von nicht altersspezifisch selektierten Emissionen untersucht. Für diesen Vergleich wurden Messungen an 252 überwiegend erwachsenen Patienten mit z. T. erworbenen Horstorungen herangezogen. Falsche Klassifikationsergebnisse aus einem ersten Durchlauf der neuen Daten durch das Expertensystem wurden zum Nachtraining genutzt, um die Pass-/Fail-Entscheidung an die erweiterten Bewertungskriterien anzupassen. Das danach mit breiterer Beispielbasis arbeitende System verbesserte sich bei der ' Klassifikation der neuen Daten in der Sensitivitat um 4,8 % auf 97,2 % und bezüglich der Spezi. fität um 2,0 % auf 95,5 %. Diese sowie die Ergebnisse von 97,3 % und 94,3 % bei der ausschließli. chen Klassifikation von Neugeborenen-TEOAE belegen die Vorteile der gewählten Struktur des Expertensystems und weisen die praktische Eignung des Verfahrens nach.