Modeling a Task-Based Matrix-Matrix Multiplication Application for Resilience Decision Making

2017 ◽  
Keyword(s):  
Decision Making ◽  
Matrix Multiplication

ADOMC-NPR Automatic Decision-Making Offloading Framework for Mobile Computation Using Nonlinear Polynomial Regression Model

2019 ◽  
Vol 16 (4) ◽  
pp. 53-73
Author(s):  
Abdulrahman Elhosuieny ◽  
Mofreh Salem ◽  
Amr Thabet ◽  
Abdelhameed Ibrahim
Keyword(s):  
Decision Making ◽  
Adaptive Learning ◽  
Execution Time ◽  
Polynomial Regression ◽  
Mean Squared Error ◽  
Matrix Multiplication ◽  
Computation Offloading ◽  
Phase Curve ◽  
Predicting Model ◽  
Major Interest

Nowadays, mobile computation applications attract major interest of researchers. Limited processing power and short battery lifetime is an obstacle in executing computationally-intensive applications. This article presents a mobile computation automatic decision-making offloading framework. The proposed framework consists of two phases: adaptive learning, and modeling and runtime computation offloading. In the adaptive phase, curve-fitting (CF) technique based on non-linear polynomial regression (NPR) methodology is used to build an approximate time-predicting model that can estimate the execution time for spending the processing of the detected-intensive applications. The runtime computation phase uses the time predicting model for computing the predicted execution time to decide whether to run the application remotely and perform the offloading process or to run the application locally. Eventually, the RESTful web service is applied to carry out the offloading task in the case of a positive offloading decision. The proposed framework experimentally outperforms a competitive state-of-the-art technique by 73% concerning the time factor. The proposed time-predicting model records minimal deviation of the originally obtained values as it is applied 0.4997, 8.9636, 0.0020, and 0.6797 on the mean squared error metric for matrix-determinant, image-sharpening, matrix-multiplication, and n-queens problems, respectively.

scholarly journals Blockchain drivers to achieve sustainable food security in the Indian context

2021 ◽  
Author(s):  
Vinay Surendra Yadav ◽  
A. R. Singh ◽  
Rakesh D. Raut ◽  
Naoufel Cheikhrouhou
Keyword(s):  
Decision Making ◽  
Food Security ◽  
Matrix Multiplication ◽  
Multiple Criteria Decision Making ◽  
Fuzzy Decision Making ◽  
Sustainable Food ◽  
Governmental Organizations ◽  
Blockchain Technology ◽  
Indian Context ◽  
Agricultural Applications

AbstractBlockchain has the potential to improve sustainable food security due to its unique features like traceability, decentralized and immutable database, and smart contract mechanisms. However, blockchain technology is still in the early stages of adoption in particular in agricultural applications. In this context, this article aims to identify blockchain drivers to achieve sustainable food security in the Indian context and model them using an integrated MCDM (Multiple Criteria Decision Making) approach. The blockchain adoption drivers are identified through an exhaustive literature review and opinions from domain experts from industry, academia, and Agriculture Supply Chain (ASC) stakeholders. Subsequently, the integrated MCDM approach is developed by combining Total Interpretive Structural Modelling (TISM) and Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), which does not only investigate the interrelation between the identified constructs and builds hierarchy but also determines the intensity of the causal interrelationships. At a later stage, Fuzzy Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) is used to cluster the identified drivers to evaluate the importance of each driver. The results reveal that Traceability, Real-time information availability to agro-stakeholder, and Decentralized and immutable database are the most significant drivers. Policymakers, governmental organizations and other relevant stakeholders may utilize the information about the interrelationship between these drivers and their influential power, to frame suitable strategies for enhancing the adoption rate of blockchain in the Indian ASC.

scholarly journals Discussion on fuzzy decision making based on fuzzy number and compositional rule of inference

2015 ◽  
Vol 25 (2) ◽  
pp. 271-282 ◽  
Author(s):  
Ping-Teng Chang ◽  
Lung-Ting Hung
Keyword(s):  
Decision Making ◽  
Medical Diagnosis ◽  
Fuzzy Numbers ◽  
Fuzzy Theory ◽  
Matrix Multiplication ◽  
Original Method ◽  
Fuzzy Decision Making ◽  
Stochastic Matrices ◽  
Fuzzy Decision ◽  
Multiplication Operation

This paper provides an improved decision making approach based on fuzzy numbers and the compositional rule of inference by Yao and Yao (2001). They claimed to have created a new method that combines statistical methods and fuzzy theory for medical diagnosis. Currently, numerous papers have cited that work. In this study, we show that if we follow their matrix multiplication operation approach, we will obtain the same result as the original method proposed by Klir and Yuan (1995). Owing to a wellknown property of (row) stochastic matrices, if the multiplication is closed, the fuzzy and defuzzy procedure of Yao and Yao (2001) is redundant. Therefore, we advise researchers to think twice before applying this approach to medical diagnosis.

scholarly journals A process-based guide for international entrepreneurs while investing in the agrifood sector of an emerging economy: a multi-layer decision-making approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hannan Amoozad Mahdiraji ◽  
Moein Beheshti ◽  
Seyed Hossein Razavi Hajiagha ◽  
Niloofar Ahmadzadeh Kandi ◽  
Hasan Boudlaie
Keyword(s):  
Decision Making ◽  
Matrix Multiplication ◽  
Analytic Network Process ◽  
Emerging Economy ◽  
Barriers To Entry ◽  
Content Type ◽  
Fundamental Limitations ◽  
Network Process ◽  
Low Efficiency ◽  
Future Policy

PurposeDue to the political, economic and infrastructure barriers and risks that international entrepreneurs (IEs) face when researching an emerging economy's agrifood sector, this research aims to identify the major barriers, analyse their relationships, quantify their importance, classify and rank them. Thus, the IEs will gain a better understanding and vision of their decision-making processes in this era.Design/methodology/approachTo do this, the authors first created a list of barriers to entry for IEs into Iran's rising economy's agrifood industry. Following that, a multi-layer decision-making approach was developed and implemented to accomplish the research objectives. The first stage utilized a hybrid of interpretive structural modelling (ISM) and cross-impact matrix multiplication applied to classification (MICMAC) to depict the level-based conceptual model and classification of the IEs’ obstacles to entry into the agrifood sector. Following that, a hybrid decision-making trial and evaluation laboratory (DEMATEL), and analytic network process (ANP) called DANP was utilized to present a causal relationship between the barriers, identify their causes and effects, and also quantify the relevance of each barrier.FindingsAfter employing the multi-layer decision-making approach, the results demonstrated that fundamental limitations, including infrastructure and technology limitations, are the most critical barriers alongside policy factors encompassing governmental support and access to global or regional economy/market. According to the results, innovation and economic sustainability of the agrifood supply chain also matter. All of these critical barriers are intertwined and should be planned and solved simultaneously. Furthermore, based on DANP results, the sustainability pillars (economy, environment, society), besides the low efficiency of the agrifood sector in Iran, should be investigated further for future policy makings.Originality/valueA hybrid multi-layer decision-making approach has been used for analysing the barriers of investment in the agrifood sector of the emerging economy of Iran for the international entrepreneurs. Moreover, the authors provide implications and insights for IEs and officials for decision-making in the future.

Discarding optimality: Throwing out the baby with the bathwater?

2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Standard Observer ◽  
Rate Maximization ◽  
Reward Rate Maximization ◽  
Descriptive Standard ◽  
Observer Model

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

LPCD framework: Analytical tool or psychological model?

2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks
Keyword(s):  
Decision Making ◽  
Analytical Tool ◽  
Mathematical Framework ◽  
Bayesian Decision ◽  
Perceptual Decision Making ◽  
Psychological Model ◽  
Psychological Reality ◽  
Psychological Theories ◽  
Target Article ◽  
Bayesian Decision Making

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.

Elaborating the role of reflection and individual differences in the study of folk-economic beliefs

2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Cognitive Processes ◽  
Evolutionary History ◽  
Behavioral Responses ◽  
History Of ◽  
Economic Beliefs

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.

The primacy of conscious decision making – ERRATUM

2014 ◽  
Vol 38 (01) ◽  
pp. 46
Author(s):  
David R. Shanks ◽  
Ben R. Newell
Keyword(s):  
Decision Making ◽  
Conscious Decision

The primacy of conscious decision making – RETRACTION

2014 ◽  
Vol 38 (01) ◽  
pp. 48
Author(s):  
David R. Shanks ◽  
Ben R. Newell
Keyword(s):  
Decision Making ◽  
Conscious Decision
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