‘… That is the question': complementizer omission in extraposed that-clauses

2006 ◽  
Vol 10 (2) ◽  
pp. 371-396 ◽  
Author(s):  
GUNTHER KALTENBÖCK
Keyword(s):  
Information Value ◽  
Conditioning Factors ◽  
Complement Clause ◽  
Actual Use ◽  
Category Type ◽  
Corpus Data ◽  
Abstract Feature

This article investigates the omission of the that-complementizer in extraposed subject clauses (e.g. It is obvious (that) she did it), which has so far received very little attention in the literature. Using corpus data from the British component of the International Corpus of English (ICE-GB) various potential conditioning factors are analysed. Of these the following are found to have a major impact on the choice of zero that: informality of the text category, type of matrix predicate, and information value of the complement clause. On the basis of these corpus results the article then proposes a unified explanation for the use of that or zero by positing an underlying abstract feature of ‘distance’; for the that-complementizer, a semantic residue of its original demonstrative use, which gives rise to different pragmatic interpretations, depending on the actual use of that in context.

Research on Non-Landslide Selection Method for Landslide Hazard Mapping

2021 ◽  
Author(s):  
Xia Li ◽  
Jiulong Cheng ◽  
Dehao Yu ◽  
Yangchun Han
Keyword(s):  
Prediction Accuracy ◽  
Prediction Models ◽  
Selection Method ◽  
Landslide Hazard ◽  
River Channel ◽  
Information Value ◽  
Hazard Mapping ◽  
Landslide Prediction ◽  
Conditioning Factors ◽  
Landslide Hazard Mapping

Abstract Most landslide prediction models need to select non-landslides. At present, non-landslides mainly use subjective inference or random selection method, which makes it easy to select non-landslides in high-risk areas. To solve this problem and improve the accuracy of landslide prediction, the method of selecting non-landslide by Information value (IV) is proposed in this study. Firstly, 230 historical landslides and 10 landslide conditioning factors are extracted and interpreted by using Remote Sensing (RS) image, Geographic Information System (GIS) and field survey. Secondly, random, buffer, river channel or slope, and IV methods are used to obtain non-landslides, and the obtained non-landslides are applied to the popular SVM model for landslide hazard mapping (LHM) in western area of Tumen City. The landslide hazard map based on the river channel or slope method is seriously inconsistent with the actual situation of study area, Therefore, the three methods of random, buffer, and IV are verified and compared by accuracy, receiver operating characteristic (ROC) curve and the area under curves (AUC). The results show that the landslide prediction accuracy of the three methods is more than 80%, and the prediction accuracy is high, but the IV is higher. In addition, IV can identify the very high hazard regions with smaller area. Therefore, it is more reasonable to use IV to select non-landslides, and IV method is more practical in landslide prevention and engineering construction. The research results may be useful to provide basic information of landslide hazard for decision makers and planners.

scholarly journals Landslide Susceptibility Mapping using Bivariate Statistical Models and GIS in Chattagram District, Bangladesh

2021 ◽  
Author(s):  
Md. Sharafat Chowdhury ◽  
Bibi Hafsa
Keyword(s):  
Statistical Models ◽  
Landslide Susceptibility ◽  
Slope Angle ◽  
Information Value ◽  
Weight Of Evidence ◽  
Landslide Susceptibility Mapping ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Topographic Wetness Index ◽  
Conditioning Factors

Abstract This study attempts to produce Landslide Susceptibility Map for Chattagram District of Bangladesh by using five GIS based bivariate statistical models, namely the Frequency Ratio (FR), Shanon’s Entropy (SE), Weight of Evidence (WofE), Information Value (IV) and Certainty Factor (CF). A secondary landslide inventory database was used to correlate the previous landslides with the landslide conditioning factors. Sixteen landslide conditioning factors of Slope Aspect, Slope Angle, Geology, Elevation, Plan Curvature, Profile Curvature, General Curvature, Topographic Wetness Index, Stream Power Index, Sediment Transport Index, Topographic Roughness Index, Distance to Stream, Distance to Anticline, Distance to Fault, Distance to Road and NDVI were used. The Area Under Curve (AUC) was used for validation of the LSMs. The predictive rate of AUC for FR, SE, WofE, IV and CF were 76.11%, 70.11%, 78.93%, 76.57% and 80.43% respectively. CF model indicates 15.04% of areas are highly susceptible to landslide. All the models showed that the high elevated areas are more susceptible to landslide where the low-lying river basin areas have a low probability of landslide occurrence. The findings of this research will contribute to land use planning, management and hazard mitigation of the CHT region.

scholarly journals Sea cliff instability susceptibility at regional scale: a statistically based assessment in southern Algarve, Portugal

2013 ◽  
Vol 1 (3) ◽  
pp. 1965-2003 ◽  
Author(s):  
F. M. S. F. Marques ◽  
R. Matildes ◽  
P. Redweik
Keyword(s):  
Natural Hazard ◽  
Regional Scale ◽  
Roc Curves ◽  
Predisposing Factors ◽  
Information Value ◽  
Multivariate Logistic Regression ◽  
Land Use Regulations ◽  
Conditioning Factors ◽  
Different Types ◽  
Sea Cliff

Abstract. Mass movements of different types and sizes are the main processes of sea cliff evolution and also a considerable source of natural hazard, making its assessment a relevant issue in terms of human losses prevention and land use regulations. To address the assessment of the spatial component of sea cliff hazard, i.e. the susceptibility, a statistically based study was made to assess the capacity of a set of conditioning factors to express the occurrence of sea cliff failures affecting areas located along their top. The study was based on the application of the bivariate Information Value and multivariate Logistic regression statistical methods, using a set of predisposing factors for cliff failures, mainly related with geology (lithology, bedding dip, faults) and geomorphology (maximum and mean slope, height, aspect, plan curvature, toe protection) which were correlated with a photogrammetry based inventory of cliff failures occurred in a 60 yr period (1947–2007). The susceptibility models were validated against the inventory data using standard success rate and ROC curves, and provided encouraging results, indicating that the proposed approaches are effective for susceptibility assessment. The results obtained also stress the need for improvement of the predisposing factors to be used in this type of studies and the need of detailed and systematic cliff failures inventories.

scholarly journals "A TOT PEROVSKOJ NE DAL VSLAST' POSPAT'": PROSODY AND GRAMMAR OF ANAPHORIC TOT THROUGH THE LENS OF CORPUS DATA

2020 ◽  
Author(s):  
V. I. Podlesskaya ◽  
Keyword(s):  
Information Structure ◽  
Anaphora Resolution ◽  
Prosodic Features ◽  
Semantic Roles ◽  
Actual Distribution ◽  
Spoken Discourse ◽  
Verb Forms ◽  
Actual Use ◽  
Corpus Data ◽  
National Corpus

Based on data from the Russian National Corpus and the General InternetCorpus of Russian, the paper addresses syntactic, sematic and prosodic features of constructions with the demonstrative TOT used as an anaphor. These constructions have gained some attention in earlier studies [Paducheva 2016], [Berger, Weiss 1987], [Kibrik 2011], [Podlesskaya 2001], but their analysis (a) covered primarily their prototypical uses; and (b) was based on written data. The data from informal, esp. from spoken discourse show however that the actual use of these constructions may deviate considerably from the known prototype. The paper aims at bridging this gap. I claim (i) that the function of TOT is to temporary promote a referent from a less privileged discourse status to a more privileged one; and (ii) that TOT can be analyzed on a par with switch reference devices in the languages where the latter are grammatically marked (e.g. on verb forms). The following parameters of TOT-constructions are discussed: syntactic and semantic roles of TOT and of its antecedent in their respective clauses, linear and structural distances between TOT and its antecedent, animacy of the maintained referent. Special attention is payed to the information structure of the TOT construction: I give structural and prosodic evidence that TOT never has a rhematic status. The revealed actual distribution of TOT (a) adds to our understanding of cross-linguistic variation of anaphoric functions of demonstratives; and, hopefully, (b) may contribute to further developing computational approaches to coreference and anaphora resolution for Russian, e.g. by improving datasets necessary for this task.

scholarly journals Comparison of Logistic Regression, Information Value, and Comprehensive Evaluating Model for Landslide Susceptibility Mapping

2021 ◽  
Vol 13 (7) ◽  
pp. 3803
Author(s):  
Rui-Xuan Tang ◽  
E-Chuan Yan ◽  
Tao Wen ◽  
Xiao-Meng Yin ◽  
Wei Tang
Keyword(s):  
Logistic Regression ◽  
Landslide Susceptibility ◽  
Slope Angle ◽  
Susceptibility Mapping ◽  
Information Value ◽  
Landslide Susceptibility Mapping ◽  
Slope Length ◽  
Landslide Occurrence ◽  
Conditioning Factors ◽  
Slope Structure

This study validated the robust performances of the recently proposed comprehensive landslide susceptibility index model (CLSI) for landslide susceptibility mapping (LSM) by comparing it to the logistic regression (LR) and the analytical hierarchy process information value (AHPIV) model. Zhushan County in China, with 373 landslides identified, was used as the study area. Eight conditioning factors (lithology, slope structure, slope angle, altitude, distance to river, stream power index, slope length, distance to road) were acquired from digital elevation models (DEMs), field survey, remote sensing imagery, and government documentary data. Results indicate that the CLSI model has the highest accuracy and the best classification ability, although all three models can produce reasonable landslide susceptibility (LS) maps. The robust performance of the CLSI model is due to its weight determination by a back-propagation neural network (BPNN), which successfully captures the nonlinear relationship between landslide occurrence and the conditioning factors.

scholarly journals Sea cliff instability susceptibility at regional scale: a statistically based assessment in the southern Algarve, Portugal

2013 ◽  
Vol 13 (12) ◽  
pp. 3185-3203 ◽  
Author(s):  
F. M. S. F. Marques ◽  
R. Matildes ◽  
P. Redweik
Keyword(s):  
Natural Hazard ◽  
Regional Scale ◽  
Roc Curves ◽  
Predisposing Factors ◽  
Information Value ◽  
Multivariate Logistic Regression ◽  
Land Use Regulations ◽  
Conditioning Factors ◽  
Different Types ◽  
Sea Cliff

Abstract. Sea cliff evolution is dominated by the occurrence of slope mass movements of different types and sizes, which are a considerable source of natural hazard, making their assessment a relevant issue in terms of human loss prevention and land use regulations. To address the assessment of the spatial component of sea cliff hazards, i.e. the susceptibility, a statistically based study was made to assess the capacity of a set of conditioning factors to express the occurrence of sea cliff failures affecting areas located along their top. The study was based on the application of the bivariate information value and multivariate logistic regression statistical methods, using a set of predisposing factors for cliff failures, mainly related to geology (lithology, bedding dip, faults) and geomorphology (maximum and mean slope, height, aspect, plan curvature, toe protection), which were correlated with a photogrammetry-based inventory of cliff failures that occurred in a 60 yr period (1947–2007). The susceptibility models were validated against the inventory data using standard success rate and ROC curves, and provided encouraging results, indicating that the proposed approaches are effective for susceptibility assessment. The results obtained also stress the need for improvement of the predisposing factors to be used in this type of study and the need for detailed and systematic cliff failure inventories.

Merging low vowels in metropolitan French

2015 ◽  
Vol 25 (3) ◽  
pp. 317-338 ◽  
Author(s):  
JANINE BERNS
Keyword(s):  
Conditioning Factors ◽  
Corpus Data ◽  
French Corpus

ABSTRACTPrescriptive pronunciation manuals of French generally present a vocalic inventory with two low vowels: front [a] and back [ɑ]. At the same time, descriptive overviews of modern French note the tendency of the posterior vowel to merge with the anterior token, especially in unstressed position. The actual spread and conditioning factors of this alleged merger are nevertheless unknown: we are ignorant about the degree of neutralization, and it is not clear whether it is a change affecting all regions and generations in France.This article studies the French low vowels from a sociolinguistic perspective, by analyzing metropolitan French corpus data.

Is Overgrazing Really Influencing Soil Erosion?

Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1077 ◽  
Author(s):  
Ionut Nicu
Keyword(s):  
Soil Erosion ◽  
Success Rate ◽  
Slope Angle ◽  
Area Under The Curve ◽  
Temporal Analysis ◽  
Drainage Density ◽  
Information Value ◽  
Topographic Wetness Index ◽  
Conditioning Factors ◽  
Multi Temporal

Soil erosion is a serious problem spread over a variety of climatic areas around the world. The main purpose of this paper is to produce gully erosion susceptibility maps using different statistical models, such as frequency ratio (FR) and information value (IV), in a catchment from the northeastern part of Romania, covering a surface of 550 km2. In order to do so, a total number of 677 gullies were identified and randomly divided into training (80%) and validation (20%) datasets. In total, 10 conditioning factors were used to assess the gully susceptibility index (GSI); namely, elevation, precipitations, slope angle, curvature, lithology, drainage density, topographic wetness index, landforms, aspect, and distance from rivers. As a novelty, overgrazing was added as a conditioning factor. The final GSI maps were classified into four susceptibility classes: low, medium, high, and very high. In order to evaluate the two models prediction rate, the AUC (area under the curve) method was used. It has been observed that adding overgrazing as a contributing factor in calculating GSI does not considerably change the final output. Better predictability (0.87) and success rate (0.89) curves were obtained with the IV method, which proved to be more robust, unlike FR method, with 0.79 value for both predictability and success rate curves. When using sheepfolds, the value decreases by 0.01 in the case of the FR method, and by 0.02 in the case of the success rate curve for the IV method. However, this does not prove the fact that overgrazing is not influencing or accelerating soil erosion. A multi-temporal analysis of soil erosion is needed; this represents a future working hypothesis.

Trust in Management Information Systems (MIS)

2020 ◽  
Vol 64 (1) ◽  
pp. 6-16 ◽  
Author(s):  
Sarah M. Meeßen ◽  
Meinald T. Thielsch ◽  
Guido Hertel
Keyword(s):  
Information Systems ◽  
Information Overload ◽  
Management Information Systems ◽  
Empirical Work ◽  
Future Research ◽  
Management Information ◽  
Trust In Management ◽  
Actual Use ◽  
Trust In Technology ◽  
The Internet Of Things

Abstract. Digitalization, enhanced storage capacities, and the Internet of Things increase the volume of data in modern organizations. To process and make use of these data and to avoid information overload, management information systems (MIS) are introduced that collect, process, and analyze relevant data. However, a precondition for the application of MIS is that users trust them. Extending accounts of trust in automation and trust in technology, we introduce a new model of trust in MIS that addresses the conceptual ambiguities of existing conceptualizations of trust and integrates initial empirical work in this field. In doing so, we differentiate between perceived trustworthiness of an MIS, experienced trust in an MIS, intentions to use an MIS, and actual use of an MIS. Moreover, we consider users’ perceived risks and contextual factors (e. g., autonomy at work) as moderators. The introduced model offers guidelines for future research and initial suggestions to foster trust-based MIS use.

Applicants’ Self-Presentational Behavior

2012 ◽  
Vol 11 (2) ◽  
pp. 77-85 ◽  
Author(s):  
Anne Jansen ◽  
Cornelius J. König ◽  
Eveline H. Stadelmann ◽  
Martin Kleinmann
Keyword(s):  
Personnel Selection ◽  
Randomized Response Technique ◽  
Randomized Response ◽  
Self Presentation ◽  
Actual Use

This study contributes to the literature on self-presentation by comparing recruiters’ expectations about applicants’ self-presentational behaviors in personnel selection settings to applicants’ actual use of these behaviors. Recruiters (N = 51) rated the perceived appropriateness of 24 self-presentational behaviors. In addition, the prevalence of these behaviors was separately assessed in two subsamples of applicants (N1 = 416 and N2 = 88) with the randomized response technique. In line with the script concept, the results revealed that recruiters similarly evaluated the appropriateness of specific self-presentational behaviors and that applicants’ general use of these behaviors corresponded to recruiters’ shared expectations. The findings indicate that applicants who use strategic self-presentational behaviors may just be trying to fulfill situational requirements.

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