scholarly journals Granulation of Hypernetwork Models under the q-Rung Picture Fuzzy Environment

Mathematics ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 496 ◽  
Author(s):  
Anam Luqman ◽  
Muhammad Akram ◽  
Ali N. A. Koam
Keyword(s):  
Hierarchical Structure ◽  
Equivalence Relation ◽  
Quotient Space ◽  
Space Structures ◽  
Comparison Analysis ◽  
Fuzzy Environment ◽  
Proposed Model ◽  
Fuzzy Hypergraphs ◽  
Different Levels

In this paper, we define q-rung picture fuzzy hypergraphs and illustrate the formation of granular structures using q-rung picture fuzzy hypergraphs and level hypergraphs. Further, we define the q-rung picture fuzzy equivalence relation and q-rung picture fuzzy hierarchical quotient space structures. In particular, a q-rung picture fuzzy hypergraph and hypergraph combine a set of granules, and a hierarchical structure is formed corresponding to the series of hypergraphs. The mappings between the q-rung picture fuzzy hypergraphs depict the relationships among granules occurring at different levels. The consequences reveal that the representation of the partition of the universal set is more efficient through q-rung picture fuzzy hypergraphs and the q-rung picture fuzzy equivalence relation. We also present an arithmetic example and comparison analysis to signify the superiority and validity of our proposed model.

scholarly journals Dynamically Route Hierarchical Structure Representation to Attentive Capsule for Text Classification

2019 ◽  
Author(s):  
Wanshan Zheng ◽  
Zibin Zheng ◽  
Hai Wan ◽  
Chuan Chen
Keyword(s):  
Hierarchical Structure ◽  
Language Processing ◽  
Text Classification ◽  
Representation Learning ◽  
Structure Representation ◽  
Proposed Model ◽  
Adaptive Structure ◽  
Benchmark Datasets ◽  
Linguistic Units ◽  
Different Levels

Representation learning and feature aggregation are usually the two key intermediate steps in natural language processing. Despite deep neural networks have shown strong performance in the text classification task, they are unable to learn adaptive structure features automatically and lack of a method for fully utilizing the extracted features. In this paper, we propose a novel architecture that dynamically routes hierarchical structure feature to attentive capsule, named HAC. Specifically, we first adopt intermediate information of a well-designed deep dilated CNN to form hierarchical structure features. Different levels of structure representations are corresponding to various linguistic units such as word, phrase and clause, respectively. Furthermore, we design a capsule module using dynamic routing and equip it with an attention mechanism. The attentive capsule implements an effective aggregation strategy for feature clustering and selection. Extensive results on eleven benchmark datasets demonstrate that the proposed model obtains competitive performance against several state-of-the-art baselines. Our code is available at https://github.com/zhengwsh/HAC.

In-depth gaze at the astonishing mechanical behavior of bone: A review for designing bio-inspired hierarchical metamaterials

2020 ◽  
pp. 108128652097851
Author(s):  
Ivan Giorgio ◽  
Mario Spagnuolo ◽  
Ugo Andreaus ◽  
Daria Scerrato ◽  
Alberto Maria Bersani
Keyword(s):  
Structural Optimization ◽  
Mechanical Behavior ◽  
Bone Tissue ◽  
Hierarchical Structure ◽  
Reconstructive Surgery ◽  
Review Paper ◽  
Tissue Mechanics ◽  
The Hierarchical Structure ◽  
Mechanical Models ◽  
Different Levels

In this review paper, some relevant models, algorithms, and approaches conceived to describe the bone tissue mechanics and the remodeling process are showcased. Specifically, we briefly describe the hierarchical structure of the bone at different levels and underline the geometrical substructure characterizing the bone itself. The mechanical models adopted to describe the bone tissue at different levels of observation are introduced in their essential aspects. Furthermore, the modeling of the evolution, including the growth and resorption of bone, is treated by analyzing the main approaches employed, namely the mechanical feedback concept and the structural optimization perspective. In this regard, the most prominent ways to model the biomechanical stimulus are summarized. The modeling of the interaction with prostheses or grafts commonly used in reconstructive surgery is also recalled. The main aim of this survey consists thereby in providing the appropriate knowledge to mimic the deeply structured hierarchy of the bone tissue for synthesizing innovative and highly performing bio-inspired metamaterials.

scholarly journals Multimedia Quality Integration Using Piecewise Function

2011 ◽  
Vol 1 ◽  
pp. 375-380
Author(s):  
Shu Ai Wan ◽  
Kai Fang Yang ◽  
Hai Yong Zhou
Keyword(s):  
Visual Quality ◽  
Experimental Results ◽  
Integration Model ◽  
Quality Performance ◽  
Piecewise Function ◽  
Proposed Model ◽  
Constant Coefficients ◽  
Theoretical Analyses ◽  
Different Levels

In this paper the important issue of multimedia quality evaluation is concerned, given the unimodal quality of audio and video. Firstly, the quality integration model recommended in G.1070 is evaluated using experimental results. Theoretical analyses aide empirical observations suggest that the constant coefficients used in the G.1070 model should actually be piecewise adjusted for different levels of audio and visual quality. Then a piecewise function is proposed to perform multimedia quality integration under different levels of the audio and visual quality. Performance gain observed from experimental results substantiates the effectiveness of the proposed model.

scholarly journals Blockchain-Enhanced Fair Task Scheduling for Cloud-Fog-Edge Coordination Environments: Model and Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Wenjuan Li ◽  
Shihua Cao ◽  
Keyong Hu ◽  
Jian Cao ◽  
Rajkumar Buyya
Keyword(s):  
Task Scheduling ◽  
User Satisfaction ◽  
Chain Structure ◽  
Computing Model ◽  
Blockchain Technology ◽  
Node Distribution ◽  
Proposed Model ◽  
Task Processing ◽  
Scheduling Models ◽  
Different Levels

The cloud-fog-edge hybrid system is the evolution of the traditional centralized cloud computing model. Through the combination of different levels of resources, it is able to handle service requests from terminal users with a lower latency. However, it is accompanied by greater uncertainty, unreliability, and instability due to the decentralization and regionalization of service processing, as well as the unreasonable and unfairness in resource allocation, task scheduling, and coordination, caused by the autonomy of node distribution. Therefore, this paper introduces blockchain technology to construct a trust-enabled interaction framework in a cloud-fog-edge environment, and through a double-chain structure, it improves the reliability and verifiability of task processing without a big management overhead. Furthermore, in order to fully consider the reasonability and load balance in service coordination and task scheduling, Berger’s model and the conception of service justice are introduced to perform reasonable matching of tasks and resources. We have developed a trust-based cloud-fog-edge service simulation system based on iFogsim, and through a large number of experiments, the performance of the proposed model is verified in terms of makespan, scheduling success rate, latency, and user satisfaction with some classical scheduling models.

scholarly journals A Hierarchical End-to-End Model for Jointly Improving Text Summarization and Sentiment Classification

2018 ◽  
Author(s):  
Shuming Ma ◽  
Xu Sun ◽  
Junyang Lin ◽  
Xuancheng Ren
Keyword(s):  
Hierarchical Structure ◽  
Online Reviews ◽  
Text Summarization ◽  
Sentiment Classification ◽  
Experimental Results ◽  
Joint Learning ◽  
End To End ◽  
Abstractive Summarization ◽  
Main Ideas ◽  
Different Levels

Text summarization and sentiment classification both aim to capture the main ideas of the text but at different levels. Text summarization is to describe the text within a few sentences, while sentiment classification can be regarded as a special type of summarization which ``summarizes'' the text into a even more abstract fashion, i.e., a sentiment class. Based on this idea, we propose a hierarchical end-to-end model for joint learning of text summarization and sentiment classification, where the sentiment classification label is treated as the further ``summarization'' of the text summarization output. Hence, the sentiment classification layer is put upon the text summarization layer, and a hierarchical structure is derived. Experimental results on Amazon online reviews datasets show that our model achieves better performance than the strong baseline systems on both abstractive summarization and sentiment classification.

scholarly journals An Integrated Fuzzy Model for Selecting Resilient Suppliers in Electronics Industry of Iran

Logistics ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 71
Author(s):  
Hamzeh Aghababayi ◽  
Mohsen Shafiei Shafiei Nikabadi
Keyword(s):  
Real Life ◽  
Fuzzy Model ◽  
Electronics Industry ◽  
Electronic Industry ◽  
Chain Management ◽  
Fuzzy Environment ◽  
Proposed Model ◽  
Delay Times ◽  
Effective Decision

Selecting appropriate and resilient suppliers is an important issue in supply chain management (SCM) literature. Making an effective decision on this issue can decrease external risks and disruptions, purchase costs, and delay times and also guarantees business continuity in the event of disruptions and, consequently, increases company competitiveness and customer satisfaction. This paper aims to provide a model based on identifying and investigating related criteria to evaluate suppliers’ resilience and select the most resilient suppliers in Iran’s electronic industry. To this purpose, the screening technique, the best–worst methodology (BWM), and goal programming (GP) have been applied in the fuzzy environment. The proposed model has been implemented and demonstrated by a case study of the electronic industry, as a real-life example. The results show that agility (0.227), compatibility (0.153), and vulnerability (0.102) are the most important factors for a resilient supplier.

scholarly journals Extensions of Dombi Aggregation Operators for Decision Making under m-Polar Fuzzy Information

2020 ◽  
Vol 2020 ◽  
pp. 1-20 ◽  
Author(s):  
Muhammad Akram ◽  
Naveed Yaqoob ◽  
Ghous Ali ◽  
Wathek Chammam
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Fuzzy Information ◽  
Ordered Weighted Averaging ◽  
Fuzzy Environment ◽  
Proposed Model ◽  
Electre I ◽  
Geometric Operator

An m-polar fuzzy set is a powerful mathematical model to analyze multipolar, multiattribute, and multi-index data. The m-polar fuzzy sets have appeared as a useful tool to portray uncertainty in multiattribute decision making. The purpose of this article is to analyze the aggregation operators under the m-polar fuzzy environment with the help of Dombi norm operations. In this article, we develop some averaging and geometric aggregation operators using Dombi t-norm and t-conorm to handle uncertainty in m-polar fuzzy (mF, henceforth) information, which are mF Dombi weighted averaging (mFDWA) operator, mF Dombi ordered weighted averaging (mFDOWA) operator, mF Dombi hybrid averaging (mFDHA) operator, mF Dombi weighted geometric (mFDWG) operator, mF Dombi weighted ordered geometric operator, and mF Dombi hybrid geometric (mFDHG) operator. We investigate properties, namely, idempotency, monotonicity, and boundedness, for the proposed operators. Moreover, we give an algorithm to solve multicriteria decision-making issues which involve mF information with mFDWA and mFDWG operators. To prove the validity and feasibility of the proposed model, we solve two numerical examples with our proposed models and give comparison with mF-ELECTRE-I approach (Akram et al. 2019) and mF Hamacher aggregation operators (Waseem et al. 2019). Finally, we check the effectiveness of the developed operators by a validity test.

Deformation Capacity Limits for Reinforced Concrete Walls

2019 ◽  
Vol 35 (3) ◽  
pp. 1189-1212 ◽  
Author(s):  
Alex V. Shegay ◽  
Christopher J. Motter ◽  
Kenneth J. Elwood ◽  
Richard S. Henry
Keyword(s):  
Reinforced Concrete ◽  
Compressive Strain ◽  
Deformation Capacity ◽  
Concrete Walls ◽  
Capacity Limits ◽  
Reinforced Concrete Walls ◽  
Proposed Model ◽  
Bar Buckling ◽  
Bar Diameter ◽  
Different Levels

The use of deformation capacity limits is becoming increasingly common in seismic design and assessment of reinforced concrete (RC) walls. Deformation capacity limits for RC walls in existing design and assessment documents are reviewed using a comprehensive database. It is found that the existing models are inconsistent and do not account for variation in deformation capacity with changes in the ratio of neutral axis depth to wall length ( c/ L w) and ratio of transverse reinforcement spacing to longitudinal bar diameter ( s/ d b) at the wall end region. A new mechanics-based model considering strain limits on the concrete and reinforcement is recommended. Concrete compressive strain limits for different levels of wall end region detailing are selected based on curvature ductilities for the walls in the database. Reinforcement tensile strain is limited based on a model for bar buckling. The proposed model, which accounts for c/ L w and s/ d b, is shown to have less dispersion and more accuracy than existing models when compared against experimental data and provides consistency between assessment and design provisions.

scholarly journals The LR-Type Fuzzy Multi-Objective Vendor Selection Problem in Supply Chain Management

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1621
Author(s):  
Irfan Ali ◽  
Armin Fügenschuh ◽  
Srikant Gupta ◽  
Umar Muhammad Modibbo
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Real Life ◽  
Selection Problem ◽  
Programming Approach ◽  
Vendor Selection ◽  
Chain Management ◽  
Multi Objective ◽  
Fuzzy Environment ◽  
Proposed Model

Vendor selection is an established problem in supply chain management. It is regarded as a strategic resource by manufacturers, which must be managed efficiently. Any inappropriate selection of the vendors may lead to severe issues in the supply chain network. Hence, the desire to develop a model that minimizes the combination of transportation, deliveries, and ordering costs under uncertainty situation. In this paper, a multi-objective vendor selection problem under fuzzy environment is solved using a fuzzy goal programming approach. The vendor selection problem was modeled as a multi-objective problem, including three primary objectives of minimizing the transportation cost; the late deliveries; and the net ordering cost subject to constraints related to aggregate demand; vendor capacity; budget allocation; purchasing value; vendors’ quota; and quantity rejected. The proposed model input parameters are considered to be LR fuzzy numbers. The effectiveness of the model is illustrated with simulated data using R statistical package based on a real-life case study which was analyzed using LINGO 16.0 optimization software. The decision on the vendor’s quota allocation and selection under different degree of vagueness in the information was provided. The proposed model can address realistic vendor selection problem in the fuzzy environment and can serve as a useful tool for multi-criteria decision-making in supply chain management.

The structure and development of borderline personality disorder: A proposed model

1997 ◽  
Vol 170 (1) ◽  
pp. 82-87 ◽  
Author(s):  
Anthony Ryle
Keyword(s):  
Borderline Personality Disorder ◽  
Personality Disorder ◽  
Structural Model ◽  
Borderline Personality ◽  
Proposed Model ◽  
Analytic Therapy ◽  
Cognitive Analytic Therapy ◽  
Different Levels

BackgroundThe theory of cognitive analytic therapy is extended to offer an understanding of borderline personality disorder (BPD).MethodA structural model (the multiple self states model) and a classification of different levels of developmental damage are proposed.ResultsThe model offers an explanation of the phenomenology of BPD.ConclusionsThe multiple self states model provides insights that will be useful for clinicians involved in the psychotherapy and management of BPD patients.

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