Project Work Breakdown Structure Similarity Estimation Using Semantic and Structural Similarity Measures

2020 ◽  
Author(s):  
Navid Torkanfar ◽  
Ehsan Rezazadeh Azar
Keyword(s):  
Similarity Measures ◽  
Structural Similarity ◽  
Project Work ◽  
Work Breakdown Structure ◽  
Similarity Estimation ◽  
Structure Similarity

scholarly journals Development of risk-based standardized WBS (Work Breakdown Structure) for quality planning of high rise building architectural works

2018 ◽  
Vol 159 ◽  
pp. 01019 ◽  
Author(s):  
Mirradewi Rianty ◽  
Yusuf Latief ◽  
Leni Sagita Riantini
Keyword(s):  
Iso 9001 ◽  
Project Work ◽  
Analysis Method ◽  
High Quality ◽  
Quality Performance ◽  
Quality Planning ◽  
Work Breakdown Structure ◽  
High Rise ◽  
Management Quality ◽  
Qualitative Risk Analysis

Work Breakdown Structure (WBS) is a breakdown of project work into smaller components so it can be better managed. Although each project is unique, most buildings can be standardized in their activities to enable the provision of a stronger forecast for project management. Quality performance is also important to be controlled and risk consideration approach is now required for overall quality management process in the updated ISO 9001. Therefore, the development of risk-based WBS for quality planning is proposed. The objective of the study was to develop risk-based WBS for high-quality building architectural works. The research consisted of several stages with qualitative risk analysis method. The result indicates that standardized WBS consists of 5 primary levels and 2 complementary levels, with 14 dominant risk variables on quality performance, and recommended risk responses as the development.

Risk Analysis on Investment of Hydropower Project Based on WBS and RBS

2012 ◽  
Vol 468-471 ◽  
pp. 2641-2646
Author(s):  
Lei Lin ◽  
Song Jiang Wang
Keyword(s):  
Monte Carlo Simulation ◽  
Large Scale ◽  
Risk Identification ◽  
Project Work ◽  
Investment Risk ◽  
Hydropower Project ◽  
Monte Carlo Simulation Technique ◽  
Work Breakdown Structure ◽  
Risk Characteristics ◽  
Risk Breakdown Structure

Based on the investment risk characteristics of large-scale hydropower project, the risk identification of investment for hydropower project is investigated according to the project Work Breakdown Structure(WBS) and Risk Breakdown Structure(RBS). The method for estimating the investment risk of hydropower project is applying Monte Carlo simulation technique. This method is applied to analyze the risk of the Hsin-an River hydropower project in the Zhejiang Province based on experts' experiences. Good result is attained.

scholarly journals Using Local Alignments for Relation Recognition

2010 ◽  
Vol 38 ◽  
pp. 1-48 ◽  
Author(s):  
S. Katrenko ◽  
P. W. Adriaans ◽  
M. Van Someren
Keyword(s):  
Sequence Similarity ◽  
General Relation ◽  
Similarity Measures ◽  
Semantic Relatedness ◽  
Structural Similarity ◽  
Learning Task ◽  
Semantic Knowledge ◽  
Local Alignment ◽  
Data Sets ◽  
Definition Of

This paper discusses the problem of marrying structural similarity with semantic relatedness for Information Extraction from text. Aiming at accurate recognition of relations, we introduce local alignment kernels and explore various possibilities of using them for this task. We give a definition of a local alignment (LA) kernel based on the Smith-Waterman score as a sequence similarity measure and proceed with a range of possibilities for computing similarity between elements of sequences. We show how distributional similarity measures obtained from unlabeled data can be incorporated into the learning task as semantic knowledge. Our experiments suggest that the LA kernel yields promising results on various biomedical corpora outperforming two baselines by a large margin. Additional series of experiments have been conducted on the data sets of seven general relation types, where the performance of the LA kernel is comparable to the current state-of-the-art results.

Social Network Inspired Approach to Intelligent Monitoring of Intelligence Data

2011 ◽  
pp. 79-100 ◽  
Author(s):  
Qiang Shen ◽  
Tossapon Boongoen
Keyword(s):  
Similarity Measure ◽  
Similarity Measures ◽  
Alternative Methods ◽  
Common Denominator ◽  
Communication Behaviors ◽  
Similarity Estimation ◽  
Order Of Magnitude ◽  
Qualitative Similarity ◽  
The Common ◽  
Link Information

In the wake of recent terrorist atrocities, intelligence experts have commented that failures in detecting terrorist and criminal activities are not so much due to a lack of data, as they are due to difficulties in relating and interpreting the available intelligence. An intelligent tool for monitoring and interpreting intelligence data will provide a helpful means for intelligence analysts to consider emerging scenarios of plausible threats, thereby offering useful assistance in devising and deploying preventive measures against such possibilities. One of the major problems in need of such attention is detecting false identity that has become the common denominator of all serious crime, especially terrorism. Typical approaches to this problem rely on the similarity measure of textual and other content-based characteristics, which are usually not applicable in the case of deceptive and erroneous description. This barrier may be overcome through link information presented in communication behaviors, financial interactions and social networks. Quantitative link-based similarity measures have proven effective for identifying similar problems in the Internet and publication domains. However, these numerical methods only concentrate on link structures, and fail to achieve accurate and coherent interpretation of the information. Inspired by this observation, the chapter presents a novel qualitative similarity measure that makes use of multiple link properties to refine the underlying similarity estimation process and consequently derive semantic-rich similarity descriptors. The approach is based on order-of-magnitude reasoning. Its performance is empirically evaluated over a terrorism-related dataset, and compared against several state-of-the-art link-based algorithms and other alternative methods.

A LEXICAL DECISION TREE SCHEME FOR SUPPORTING SCHEMA MATCHING

2011 ◽  
Vol 10 (03) ◽  
pp. 519-537 ◽  
Author(s):  
BEEN-CHIAN CHIEN ◽  
SHIANG-YI HE
Keyword(s):  
Decision Tree ◽  
Lexical Decision ◽  
Structural Similarity ◽  
Schema Matching ◽  
Similarity Matching ◽  
Matching Method ◽  
Matching Algorithm ◽  
Essential Step ◽  
Structure Similarity ◽  
Two Phases

To manipulate semantic web and integrate different data sources efficiently, automatic schema matching plays a key role. A generic schema matching method generally includes two phases: the linguistic similarity matching phase and the structural similarity matching phase. Since linguistic matching is an essential step for effective schema matching, developing a high accurate linguistic similarity matching scheme is required. In this paper, a schema matching approach called Similarity Yield Matcher (SYM) is proposed. In SYM, a lexical decision tree is presented to determine the linguistic similarity matching of the first phase. A structural matching algorithm is then proposed to find the structure similarity between two tree schemas. The proposed schema matching approach was evaluated by testing on several benchmarks of real schemas and comparing with other methods. The experimental results show that the proposed lexical decision tree substantially improves the linguistic similarity matching effectively and efficiently. The proposed SYM algorithm also performs high effectiveness on 1–1 schema matching.

scholarly journals Exploiting structure similarity in refinement: automated NCS and target-structure restraints in BUSTER

2012 ◽  
Vol 68 (4) ◽  
pp. 368-380 ◽  
Author(s):  
Oliver S. Smart ◽  
Thomas O. Womack ◽  
Claus Flensburg ◽  
Peter Keller ◽  
Włodek Paciorek ◽  
...  
Keyword(s):  
Functional Form ◽  
Cyclic Peptide ◽  
Structure Refinement ◽  
Structural Similarity ◽  
Peptide Ligand ◽  
Macromolecular Structure ◽  
Target Structure ◽  
X Ray ◽  
Structure Similarity ◽  
The Difference

Maximum-likelihood X-ray macromolecular structure refinement in BUSTER has been extended with restraints facilitating the exploitation of structural similarity. The similarity can be between two or more chains within the structure being refined, thus favouring NCS, or to a distinct `target' structure that remains fixed during refinement. The local structural similarity restraints (LSSR) approach considers all distances less than 5.5 Å between pairs of atoms in the chain to be restrained. For each, the difference from the distance between the corresponding atoms in the related chain is found. LSSR applies a restraint penalty on each difference. A functional form that reaches a plateau for large differences is used to avoid the restraints distorting parts of the structure that are not similar. Because LSSR are local, there is no need to separate out domains. Some restraint pruning is still necessary, but this has been automated. LSSR have been available to academic users of BUSTER since 2009 with the easy-to-use -autoncs and -target target.pdb options. The use of LSSR is illustrated in the re-refinement of PDB entries 5rnt, where -target enables the correct ligand-binding structure to be found, and 1osg, where -autoncs contributes to the location of an additional copy of the cyclic peptide ligand.

scholarly journals Current Trends and Advances in Image Quality Assessment

2019 ◽  
Vol 25 (3) ◽  
pp. 77-84 ◽  
Author(s):  
Krzysztof Okarma
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Video Quality ◽  
Structural Similarity ◽  
3D Images ◽  
Similarity Estimation ◽  
Current Trends ◽  
3D Printed ◽  
Image Quality Index

Image quality assessment (IQA) is one of the constantly active areas of research in computer vision. Starting from the idea of Universal Image Quality Index (UIQI), followed by well-known Structural Similarity (SSIM) and its numerous extensions and modifications, through Feature Similarity (FSIM) towards combined metrics using the multi-metric fusion approach, the development of image quality assessment is still in progress. Nevertheless, regardless of new databases and the potential use of deep learning methods, some challenges remain still up to date. Some of the IQA metrics can also be used efficiently for alternative purposes, such as texture similarity estimation, quality evaluation of 3D images and 3D printed surfaces as well as video quality assessment.

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