The uniqueness of the Salt Warehouse in Mantua: Analysis of the structure complexity from the Roman Wall to present

2016 ◽  
pp. 771-780
Author(s):  
A. Saisi ◽  
S. Terenzoni ◽  
L. Valsasnini
Keyword(s):  
Structure Complexity

scholarly journals Distinguishing Planting Structures of Different Complexity from UAV Multispectral Images

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1994
Author(s):  
Qian Ma ◽  
Wenting Han ◽  
Shenjin Huang ◽  
Shide Dong ◽  
Guang Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Confusion Matrix ◽  
Object Oriented ◽  
Low Complexity ◽  
Classification Model ◽  
Recursive Feature Elimination ◽  
Support Vector ◽  
Multispectral Images ◽  
High Complexity ◽  
Structure Complexity

This study explores the classification potential of a multispectral classification model for farmland with planting structures of different complexity. Unmanned aerial vehicle (UAV) remote sensing technology is used to obtain multispectral images of three study areas with low-, medium-, and high-complexity planting structures, containing three, five, and eight types of crops, respectively. The feature subsets of three study areas are selected by recursive feature elimination (RFE). Object-oriented random forest (OB-RF) and object-oriented support vector machine (OB-SVM) classification models are established for the three study areas. After training the models with the feature subsets, the classification results are evaluated using a confusion matrix. The OB-RF and OB-SVM models’ classification accuracies are 97.09% and 99.13%, respectively, for the low-complexity planting structure. The equivalent values are 92.61% and 99.08% for the medium-complexity planting structure and 88.99% and 97.21% for the high-complexity planting structure. For farmland with fragmentary plots and a high-complexity planting structure, as the planting structure complexity changed from low to high, both models’ overall accuracy levels decreased. The overall accuracy of the OB-RF model decreased by 8.1%, and that of the OB-SVM model only decreased by 1.92%. OB-SVM achieves an overall classification accuracy of 97.21%, and a single-crop extraction accuracy of at least 85.65%. Therefore, UAV multispectral remote sensing can be used for classification applications in highly complex planting structures.

Research on RS-WNN Integrated Modeling

2011 ◽  
Vol 105-107 ◽  
pp. 2169-2173
Author(s):  
Zong Chang Xu ◽  
Xue Qin Tang ◽  
Shu Feng Huang
Keyword(s):  
Neural Network ◽  
Rough Set ◽  
Attribute Reduction ◽  
Wavelet Neural Network ◽  
Integrated Modeling ◽  
Generalization Ability ◽  
Decision Attributes ◽  
Optimum Decision ◽  
Structure Complexity ◽  
Modeling Algorithm

Wavelet Neural Network (WNN) integration modeling based on Rough Set (RS) is studied. An integration modeling algorithm named RS-WNN, which first introduces a heuristic attribute reduction recursion algorithm to determine the optimum decision attributes and then conducts WNN modeling, is proposed. This method is adopted to more effectively eliminate the redundant attributes, lower the structure complexity of WNN, which reduce the time of training and improve the generalization ability of WNN. The result of the experiment shows this method is superior and efficient.

scholarly journals ABOUT FORENSIC EXPERT PARTICIPATION IN CASES OF ADMINISTRATIVE OFFENSES

2018 ◽  
Vol 18 ◽  
pp. 194-202
Author(s):  
O. P. Uhrovetskyi ◽  
O. O. Sviderskyi
Keyword(s):  
Legal Status ◽  
Actual Data ◽  
Forensic Research ◽  
Forensic Examination ◽  
Special Knowledge ◽  
Forensic Expert ◽  
Research Decision ◽  
Structure Complexity ◽  
Administrative Proceedings ◽  
Procedural Rights

The authors allocate in administrative proceedings in cases of administrative offenses among other participants to a forensic expert who takes a special place in this process and give a description of legal status of forensic expert in cases on administrative offenses taking into account the peculiarities of expert involving stage in administrative proceedings. The authors emphasize that at various stages of administrative proceedings a forensic expert performs one function: performing examination. At the central stage of administrative proceedings, namely consideration of the case on an administrative offense and adoption of the resolution therein by authorized authority to consider an administrative offense. If there is a need to use of special knowledge, forensic examination is assigned and opportunity is provided to expert to exercise procedural rights and obligations and submit examination conclusion as a result of expert research. Decision on forensic examination assignment in cases of administrative offenses in the jurisdiction is usually performed in resolutions of the authorized authority (official) that is in charge of proceedings administrative offense. Expert conclusion is an independent means of proof in administrative proceedings. Structure complexity of expert conclusion as a procedural document lies in the fact that it derives from the structure of a special forensic research, since it reflects its features. Expert conclusion is subject to investigation and verification by the court and actual data contained therein are judged by general rules, since they are actual data about certain circumstances of objective reality. It is concluded that participation of expert in proceedings on administrative offenses at the present stage is as fully possible realized at the second central stage of proceedings in consideration of case on administrative offense.

The effect of using an online-based course on the learning of grammar inductively and deductively

ReCALL ◽  
2009 ◽  
Vol 21 (3) ◽  
pp. 319-336 ◽  
Author(s):  
Ali Farhan AbuSeileek
Keyword(s):  
Complex Sentence ◽  
Simple Sentence ◽  
Computer Based Learning ◽  
Language Structure ◽  
Computer Mediated ◽  
Two Factors ◽  
Post Test ◽  
Computer Based ◽  
Structure Complexity ◽  
Compound Sentence

AbstractThis study aims at exploring the effectiveness of using an online-based course on the learning of sentence types inductively and deductively. To achieve this purpose, a computer-mediated course was designed. The sample of the study consists of four groups taught under four treatments of grammar: (1) with computer-based learning inductively, (2) with computer-based learning deductively, (3) with non-computer-based learning inductively, and (4) with non-computer-based learning deductively. A pre-test/post-test design (between-subject) is used to investigate the effect of two factors: method (computer-based learning vs. non-computer-based learning) and technique (induction vs. deduction) on the students’ learning of sentence types. The results reveal a new manner of enhancing grammar learning based on the level of language structure complexity. The computer-based learning method is found to be functional for more complex and elaborate structures, like the complex sentence and compound complex sentence, and more complicated grammar structures need to be taught by means of the deductive technique. None of the inductive and deductive techniques is reported to be more practical with simple grammar structures such as the simple sentence and compound sentence.

The Match Between Structural Attributes and Content-Based Orientation of Managerial Cognition: An Exploratory fsQCA Study of ‘Hidden Champions’

2021 ◽  
pp. 1-29
Author(s):  
Linan Lei ◽  
Yanan Fu ◽  
Xiaobo Wu ◽  
Jian Du
Keyword(s):  
High Performance ◽  
Qualitative Comparative Analysis ◽  
Empirical Method ◽  
Decision Makers ◽  
Strategic Decision ◽  
Cognitive Content ◽  
Managerial Cognition ◽  
Organizational Action ◽  
Structure Complexity ◽  
Technology Orientation

ABSTRACT Strategic decision makers interpret information and translate it into organizational action through the lens of strategic schemas. How should firms realize high performance with various strategic schemas? Cognitive content and structure have been shown to underlie strategic schemas, but few studies have considered them together. This study employs aggregation analysis to clarify the interaction between cognitive content (technology orientation, market orientation) and structure (complexity, centrality) in affecting the firm performance (FP) of ‘hidden champion’ companies, identified by the Economy and Information Technology Department of Zhejiang Province, China. The empirical method applies fuzzy-set qualitative comparative analysis to generate strategic schema profiles for high FP. This exploratory study fills a gap in the literature on managerial cognition and provides key lessons from ‘hidden champion’ companies in China and their paths for small- and medium-sized enterprises to grow.

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