Decision Rule for Investment in Frameworks of Reuse

2009 ◽  
pp. 140-147
Author(s):  
Roy Gelbard
Keyword(s):  
Decision Making ◽  
Software Development ◽  
Development Time ◽  
Real Life ◽  
Cost Effective ◽  
Improve Quality ◽  
Restricted Model ◽  
Code Unit ◽  
New Models ◽  
Unlimited Time

Reuse helps to decrease development time, code errors, and code units. Therefore, it serves to improve quality and productivity frameworks in software development. The question is not HOW to make the code reusable, but WHICH amount of software components would be most beneficial, that is, cost-effective in terms of reuse, and WHAT method should be used to decide whether to make a component reusable or not. If we had unlimited time and resources, we could write any code unit in a reusable way. In other words, its reusability would be 100%. However, in real life, resources are limited and there are clear deadlines to be met. Given these constraints, decisions regarding reusability are not always straightforward. The current research focuses on decision-making rules for investing in reuse frameworks. It attempts to determine the parameters, which should be taken into account in decisions relating to degrees of reusability. Two new models are presented for decision-making relating to reusability: (i) a restricted model and (ii) a non-restricted model. Decisions made by using these models are then analyzed and discussed.

Decision Rule for Investment in Frameworks of Reuse

2009 ◽  
pp. 1013-1021
Author(s):  
Roy Gelbard
Keyword(s):  
Decision Making ◽  
Software Development ◽  
Development Time ◽  
Real Life ◽  
Cost Effective ◽  
Improve Quality ◽  
Restricted Model ◽  
Code Unit ◽  
New Models ◽  
Unlimited Time

Reuse helps to decrease development time, code errors, and code units. Therefore, it serves to improve quality and productivity frameworks in software development. The question is not HOW to make the code reusable, but WHICH amount of software components would be most beneficial, that is, cost-effective in terms of reuse, and WHAT method should be used to decide whether to make a component reusable or not. If we had unlimited time and resources, we could write any code unit in a reusable way. In other words, its reusability would be 100%. However, in real life, resources are limited and there are clear deadlines to be met. Given these constraints, decisions regarding reusability are not always straightforward. The current research focuses on decision-making rules for investing in reuse frameworks. It attempts to determine the parameters, which should be taken into account in decisions relating to degrees of reusability. Two new models are presented for decision-making relating to reusability: (i) a restricted model and (ii) a non-restricted model. Decisions made by using these models are then analyzed and discussed.

Decision Rule for Investment in Reusable Code

2010 ◽  
pp. 154-160
Author(s):  
Roy Gelbard
Keyword(s):  
Decision Making ◽  
Software Development ◽  
Decision Rule ◽  
Development Time ◽  
Real Life ◽  
Improve Quality ◽  
Restricted Model ◽  
Code Unit ◽  
New Models ◽  
Unlimited Time

Reusable code helps to decrease code errors, code units and therefore development time. It serves to improve quality and productivity frameworks in software development. The question is not HOW to make the code reusable, but WHICH amount of software components would be most beneficial (i.e. costeffective in terms of reuse), and WHAT method should be used to decide whether to make a component reusable or not. If we had unlimited time and resources, we could write any code unit in a reusable way. In other words, its reusability would be 100%. However, in real life, resources and time are limited. Given these constraints, decisions regarding reusability are not always straightforward. The current chapter focuses on decision-making rules for investing in reusable code. It attempts to determine the parameters, which should be taken into account in decisions relating to degrees of reusability. Two new models are presented for decisions-making relating to reusability: (i) a restricted model, and (ii) a non-restricted model. Decisions made by using these models are then analyzed and discussed.

scholarly journals Rough Set Theory-Based Multi-Class Decision Making Framework for Cost Effective Treatment of COVID-19 Suspected Patients

2021 ◽  
Author(s):  
Sandip Majumder ◽  
Samarjit Kar
Keyword(s):  
Decision Making ◽  
Effective Treatment ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Real Life ◽  
Cost Effective ◽  
Bayesian Decision ◽  
Cost Effective Treatment ◽  
The Cost

Abstract Rough set theory approximates a concept by the three regions, namely positive, negative and boundary regions. The three regions enable us to derive three types of decisions, namely acceptance, rejection and deferment. The deferment decision gives us the flexibility to further examine suspicious objects and reduce misclassification. The main objective of this paper is to provide a cost effective treatment of a patient suspect to COVID-19 positive by using multiclass three-way decision making with the help of Rough set theory. The cost-based analysis of three-way decisions brings the theory closer to real-world applications where costs play an indispensable role. In our approach, we extend the three-way decision to three-way multiclass decision, offering a new framework of multiple classes. Different types of misclassification errors are treated separately based on the notation of loss function from Bayesian decision theory. In our cost sensitive classification approach, the cost caused by a different kind of error are not assumed to be equal. Finally, a numerical example for a cost effective treatment of a patient with COVID-19 disease is considered to demonstrate the practicability and efficacy of the developed idea in real-life applications.

scholarly journals Bayesian maintenance decision optimisation based on computing the information value from condition inspections

2021 ◽  
pp. 1748006X2097812
Author(s):  
Guang Zou ◽  
Kian Banisoleiman ◽  
Arturo González
Keyword(s):  
Decision Making ◽  
Structural Integrity ◽  
Fatigue Cracking ◽  
Cost Effective ◽  
Offshore Structures ◽  
Information Value ◽  
Bayesian Decision ◽  
Maintenance Strategies ◽  
Optimal Maintenance ◽  
Maintenance Decision

A challenge in marine and offshore engineering is structural integrity management (SIM) of assets such as ships, offshore structures, mooring systems, etc. Due to harsh marine environments, fatigue cracking and corrosion present persistent threats to structural integrity. SIM for such assets is complicated because of a very large number of rewelded plates and joints, for which condition inspections and maintenance are difficult and expensive tasks. Marine SIM needs to take into account uncertainty in material properties, loading characteristics, fatigue models, detection capacities of inspection methods, etc. Optimising inspection and maintenance strategies under uncertainty is therefore vital for effective SIM and cost reductions. This paper proposes a value of information (VoI) computation and Bayesian decision optimisation (BDO) approach to optimal maintenance planning of typical fatigue-prone structural systems under uncertainty. It is shown that the approach can yield optimal maintenance strategies reliably in various maintenance decision making problems or contexts, which are characterized by different cost ratios. It is also shown that there are decision making contexts where inspection information doesn’t add value, and condition based maintenance (CBM) is not cost-effective. The CBM strategy is optimal only in the decision making contexts where VoI > 0. The proposed approach overcomes the limitation of CBM strategy and highlights the importance of VoI computation (to confirm VoI > 0) before adopting inspections and CBM.

scholarly journals Public Officials’ Knowledge of Advances and Gaps for Implementing the Ecosystem Approach to Fisheries in Chile

2021 ◽  
Vol 13 (5) ◽  
pp. 2703
Author(s):  
Rodrigo A. Estévez ◽  
Stefan Gelcich
Keyword(s):  
Decision Making ◽  
Fisheries Management ◽  
Cost Effective ◽  
Ecosystem Approach ◽  
Social Dimensions ◽  
Public Officials ◽  
Government Officials ◽  
Effective Implementation ◽  
Mandatory Requirement ◽  
Support Decision Making

The United Nations calls on the international community to implement an ecosystem approach to fisheries (EAF) that considers the complex interrelationships between fisheries and marine and coastal ecosystems, including social and economic dimensions. However, countries experience significant national challenges for the application of the EAF. In this article, we used public officials’ knowledge to understand advances, gaps, and priorities for the implementation of the EAF in Chile. For this, we relied on the valuable information held by fisheries managers and government officials to support decision-making. In Chile, the EAF was established as a mandatory requirement for fisheries management in 2013. Key positive aspects include the promotion of fishers’ participation in inter-sectorial Management Committees to administrate fisheries and the regulation of bycatch and trawling on seamounts. Likewise, Scientific Committees formal roles in management allow the participation of scientists by setting catch limits for each fishery. However, important gaps were also identified. Officials highlighted serious difficulties to integrate social dimensions in fisheries management, and low effective coordination among the institutions to implement the EAF. We concluded that establishing clear protocols to systematize and generate formal instances to build upon government officials’ knowledge seems a clear and cost effective way to advance in the effective implementation of the EAF.

scholarly journals ACO with Intuitionistic Fuzzy Pheromone Updating Applied on Multiple-Constraint Knapsack Problem

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1456
Author(s):  
Stefka Fidanova ◽  
Krassimir Todorov Atanassov
Keyword(s):  
Decision Making ◽  
Knapsack Problem ◽  
Propositional Logic ◽  
Optimization Problems ◽  
Real Life ◽  
Combinatorial Optimization Problems ◽  
Intuitionistic Fuzzy ◽  
Life Problems ◽  
Multiple Constraint

Some of industrial and real life problems are difficult to be solved by traditional methods, because they need exponential number of calculations. As an example, we can mention decision-making problems. They can be defined as optimization problems. Ant Colony Optimization (ACO) is between the best methods, that solves combinatorial optimization problems. The method mimics behavior of the ants in the nature, when they look for a food. One of the algorithm parameters is called pheromone, and it is updated every iteration according quality of the achieved solutions. The intuitionistic fuzzy (propositional) logic was introduced as an extension of Zadeh’s fuzzy logic. In it, each proposition is estimated by two values: degree of validity and degree of non-validity. In this paper, we propose two variants of intuitionistic fuzzy pheromone updating. We apply our ideas on Multiple-Constraint Knapsack Problem (MKP) and compare achieved results with traditional ACO.

scholarly journals Practical Cross-Layer Radio Frequency-Based Authentication Scheme for Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4034
Author(s):  
Arie Haenel ◽  
Yoram Haddad ◽  
Maryline Laurent ◽  
Zonghua Zhang
Keyword(s):  
Internet Of Things ◽  
Radio Frequency ◽  
Real Life ◽  
Computation Time ◽  
Cost Effective ◽  
Battery Life ◽  
Cross Layer ◽  
Security Level ◽  
Cost Of Energy ◽  
Iot Devices

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.

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