Testing a computational model of causative overgeneralizations: Child judgment and production data from English, Hebrew, Hindi, Japanese and K’iche’

How do language learners avoid the production of verb argument structure overgeneralization errors (*The clown laughed the man c.f. The clown made the man laugh), while retaining the ability to apply such generalizations productively when appropriate? This question has long been seen as one that is both particularly central to acquisition research and particularly challenging. Focussing on causative overgeneralization errors of this type, a previous study reported a computational model that learns, on the basis of corpus data and human-derived verb-semantic-feature ratings, to predict adults’ by-verb preferences for less- versus more-transparent causative forms (e.g., * The clown laughed the man vs The clown made the man laugh) across English, Hebrew, Hindi, Japanese and K’iche Mayan. Here, we tested the ability of this model (and an expanded version with multiple hidden layers) to explain binary grammaticality judgment data from children aged 4;0-5;0, and elicited-production data from children aged 4;0-5;0 and 5;6-6;6 (N=48 per language). In general, the model successfully simulated both children’s judgment and production data, with correlations of r=0.5-0.6 and r=0.75-0.85, respectively, and also generalized to unseen verbs. Importantly, learners of all five languages showed some evidence of making the types of overgeneralization errors – in both judgments and production – previously observed in naturalistic studies of English (e.g., *I’m dancing it). Together with previous findings, the present study demonstrates that a simple learning model can explain (a) adults’ continuous judgment data, (b) children’s binary judgment data and (c) children’s production data (with no training of these datasets), and therefore constitutes a plausible mechanistic account of the acquisition of verbs’ argument structure restrictions.

Track Fractured Well Inflow Performance Using Historic Production Logging and Surface Well Performance Data in Sultanate of Oman

PDO operates about 200 deep gas wells in the X field in the Sultanate of Oman, producing commingled from the Barik gas-condensate and Miqrat lean gas reservoir completed by multiple hydraulic fracturing. Their inflow performance relation (IPR) is tracked to diagnose condensate damage, hydraulic fracture cleanup and differential reservoir pressure depletion. The best IPR data is collected through multi-rate production logging but surface production data serves as an alternative. This paper describes the process of deriving IPR's from production logging and surface production data, and then evaluates 20 years of historic IPR data to quantify the impact of condensate damage and condensate cleanup with progressive reservoir pressure depletion, to demonstrate the massive damage and slow cleanup of hydraulic fractures placed in depleted reservoirs, to show how hydraulic fractures facilitate the vertical cross-flow between isolated reservoir intervals, and to highlight that stress-dependent permeability does not play a major role in this field.

Integrated fracture characterization of Asmari reservoir in Haftkel field

The Asmari reservoir in Haftkel field is one of the most prolific naturally fractured reservoirs in the Zagros folded zone in the southwest of Iran. The primary production was commenced in 1928 and continued until 1976 with a plateau rate of 200,000 bbl/day for several years. There was an initial gas cap on the oil column. Gas injection was commenced in June 1976 and so far, 28% of the initial oil in place have been recovered. As far as we concerned, fracture network is a key factor in sustaining oil production; therefore, it needs to be characterized and results be deployed in designing new wells to sustain future production. Multidisciplinary fracture evaluation from well to reservoir scale is a great privilege to improve model’s accuracy as well as enhancing reliability of future development plan in an efficient manner. Fracture identification and modeling usually establish at well scale and translate to reservoir using analytical or numerical algorithms with the limited tie-points between wells. Evaluating fracture network from production data can significantly improve conventional workflow where limited inter-well information is available. By incorporating those evidences, the fracture modeling workflow can be optimized further where lateral and vertical connectivity is a concern. This paper begins with the fracture characterization whereby all available data are evaluated to determine fracture patterns and extension of fracture network across the field. As results, a consistent correlation is obtained between the temperature gradient and productivity of wells, also convection phenomenon is confirmed. The findings of this section help us in better understanding fracture network, hydrodynamic communication and variation of temperature. Fracture modeling is the next step where characteristics of fractures are determined according to the structural geology and stress directions. Also, the fault’s related fractures and density of fractures are determined. Meanwhile, the results of data evaluation are deployed into the fracture model to control distribution and characteristics of fracture network, thereby a better representation is obtained that can be used for evaluating production data and optimizing development plan.

An Optimization-Based Method for the Explicit Production Data Analysis of Gas Wells

This work aims at the exploration of production data analysis (PDA) methods without iterations. It can overcome limitations of the advanced type curve analysis relying on the iterative calculation of material-balance pseudotime and current explicit methods reckoning on specific production schedule assumptions. The dynamic material balance equation (DMBE) is strictly proved by the integral variable substitution based on the gas flow equation under the boundary dominated flow (BDF) condition and the static material balance equation (SMBE) of a gas reservoir. We introduce the pseudopressure level function γ(p) and the recovery factor function R(p) to rewrite the DMBE in terms of observed variable Y and estimated variable Ye; then the PDA can be transformed into an optimization problem of minimizing the error between Y and Ye. An optimization-based method for the explicit production data analysis of gas wells (OBM-EPDA), therefore, is developed in the paper, capable of determining the BDF constant and gas reserves explicitly and accurately for variable rate and/or variable flowing pressure systems. Three stimulated cases demonstrate the applicability and validity of OBM-EPDA with small errors less than 1% for estimated values of both reserves and Y. Not second to previous studies, the field case analysis further proves its practicability. It is shown that the nonlinear relation of γ to R can be represented by a polynomial function merely dependent on the inherent properties of the gas production system even before sorting out the production data. The errors of observed variable Y provided by OBM-EPDA facilitate the data quality control, and the elimination of outliers not subject to the BDF condition improves the reliability of the analysis. For various gas systems producing whether at a constant rate, a constant bottomhole pressure (BHP), or under variable rate and variable BHP conditions, the proposed method gives insights into the well-controlled volume and production capacity of the gas well whether in a low-pressure or high-pressure gas reservoir, where the compressibilities of rock and bound water are considered.

RETRATO GEOGRÁFICO E DE GÊNERO DOS CURSOS DE JORNALISMO NO BRASIL: metodologia para análise da produção científica = GEOGRAPHIC AND GENDER PORTRAIT OF JOURNALISM COURSES IN BRAZIL: methodology for the analysis of scientific production

O objetivo deste estudo é apresentar uma proposta metodológica de avaliação dos fenômenos da colaboração científica e da sua coautoria, reconhecendo asmotivações que direcionam os pesquisadores a cooperar em suas atividades deprodução científica. A metodologia é de natureza quanti-qualitativa, exploratória e documental. Como suporte, utilizam-se ferramentas do aparato tecnológico dos softwares: scriptLattes e Excel, com a finalidade de contribuir na coleta e análise dos dados da produção científica. Como objeto de análise aplicada, foi realizado o levantamento do número de pesquisadores/professores efetivos, com o título acadêmico de doutor, em 42 cursos de Jornalismo de universidades federais do Brasil, com o uso do software scriptLattes. Como resultado, a equipe de pesquisa constatou 769 docentes (386 pesquisadoras e 383 pesquisadores), além de 84 pesquisadores (44 pesquisadores e 40 pesquisadoras) de produtividade em pesquisa do CNPq pertencentes a esse universo amostral nas cinco regiões brasileiras.AbstractThe purpose of this study is to present a methodological proposal for evaluating the phenomena of scientific collaboration and its co-authorship, recognizing themotivations that direct researchers to cooperate in their scientific productionactivities. The methodology is quantitative and qualitative, explotory and documentar. As a support, the tools of the technological apparatus of the following software´s are used: script Lattes and Excel, with the purpose of contributing to the collection and analysis of scientific production data. As an object of applied analysis, a survey of the number of effective researchers / professors, with the academic title of doctor, in 42 journalism courses at federal universities in Brazil, using the script Lattes software. As a result, the research team found 769 professors (386 researchers and 383 researchers); in addition to 84 researchers (44 researchers and 40 researchers) of CNPq research productivity belonging to this sample universe in the five Brazilian regions.

KOMPARASI METODE MOVING AVERAGE DAN TREND PROJECTION SEBAGAI ALAT UKUR PERENCANAAN PRODUKSI PADA UD. JAYA ABADI KABUPATEN PROBOLINGGO

The purpose of this research is to find out the comparison of forecasting calculations using the moving average and trend projection methods as a means measuring tool in production planning at UD. Jaya Abadi Probolinggo Regency. The type of research used is quantitative descriptive. Population and sample in this research is UD production data. Jaya Abadi Probolinggo Regerency from 2018 to March 2021. Data analysis using the moving average and trend projection methods which aim to predict future production or the next period. The results showed that the value of MAD (Mean Absolute Deviation) and the MSE (Mean Square Error) moving average values are higher than the MAD and the MSE trend projection, so the company you should use trend projection because when viewed from the results of the comparision of MAD and MSE, this method has a smaller error rate than the moving average method. So it can be concluded that the trend projection method can be used in planning bread production at UD. Jaya Abadi Probolinggo Regency

Development of cognitive strategies with digital games in non-formal education

This paper presents a case study analyzing which learning cognitive strategies are employed by students who play digital games in both in-school and out-of-school learning contexts. As a Case Study, it falls within the qualitative research category. The researcher integrated themselves to the subjects' learning facility for data-gathering, following all recommended ethical protocols for research involving underage subjects. The following data collection instruments were used: research diary, questionnaire, and interviews, conducted with teenagers who play digital games during formal learning activities. Analysis involved data-crossing and checking our data against existing studies and theories, as well as a cartographic production. Data indicates that digital games enhance student usage of cognitive strategies and favor competencies and abilities-based learning over formal learning contents.