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Chakchai So-In, Raj Jain and Abdel-Karim Al Tamimi
Deficit Round Robin (DRR) is a fair packet-based scheduling discipline commonly used in wired networks where link capacities do not change with time. However, in wireless networks, especially wireless broadband networks, i.e., IEEE 802.16e Mobile WiMAX, ...
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Jie Yang, Jiajia Zhu and Ziyu Pan
Aiming at the resource allocation problem of a non-orthogonal multiple access (NOMA) system, a fairness index based on sample variance of users? transmission rates is proposed, which has a fixed range and high sensitivity. Based on the proposed fairness ...
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Ting Zeng and Tianjian Yang
Behavioral factors (i.e., risk aversion and fairness concern) are considered for profit allocation in a closed-loop supply chain. This paper studies a two-echelon closed-loop supply chain (CLSC) consisting of a risk-neutral manufacturer, a risk-averse fa...
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Gabriela Andre Agung,SeTin SeTin
Pág. 171 - 183
Organizational politics and budgeting are the phenomena that exist in every organization. This study aims to examine the effect of organizational politics on budgetary participation through procedural fairness. Organizational politics refers to three dim...
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Stefania Collodi, Maria Fiorenza, Andrea Guazzini and Mirko Duradoni
Reputational systems promote pro-social behaviors, also in virtual environments, therefore their study contributes to the knowledge of social interactions. Literature findings emphasize the power of reputation in fostering fairness in many circumstances,...
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L. P. Vermeulen,M. Coetzee
AbstractThe purpose of this study was to identify the dimensions of affirmative action (AA) fairness in order to develop a valid and reliable questionnaire to assess employees? perceptions of the fairness of AA decisions and practices, and to explore the...
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L. P. Vermeulen,M. Coetzee
AbstractThe purpose of this study was to identify the dimensions of affirmative action (AA) fairness in order to develop a valid and reliable questionnaire to assess employees? perceptions of the fairness of AA decisions and practices, and to explore the...
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Tiago P. Pagano, Rafael B. Loureiro, Fernanda V. N. Lisboa, Gustavo O. R. Cruz, Rodrigo M. Peixoto, Guilherme A. de Sousa Guimarães, Ewerton L. S. Oliveira, Ingrid Winkler and Erick G. Sperandio Nascimento
The majority of current approaches for bias and fairness identification or mitigation in machine learning models are applications for a particular issue that fails to account for the connection between the application context and its associated sensitive...
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Ajeng Rachma Pertiwi, Syaiful Iqbal, Zaki Baridwan
Pág. 143 - 150
This study aims to empirically examine the effect of tax fairness and tax knowledge on tax compliance for Micro, Small and Medium Enterprises (MSMEs). Azmi and Perumal (2008) identified five of tax fairness dimensions: general fairness, exchanges with th...
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Andreas Könsgen, Md. Shahabuddin, Amanpreet Singh and Anna Förster
Multipath transport protocols are aimed at increasing the throughput of data flows as well as maintaining fairness between users, which are both crucial factors to maximize user satisfaction. In this paper, a mixed (non)linear programming (MINLP) solutio...
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Lu Han, Xiaohong Huang, Dandan Li and Yong Zhang
In the ring-architecture-based federated learning framework, security and fairness are severely compromised when dishonest clients abort the training process after obtaining useful information. To solve the problem, we propose a Ring- architecture-based ...
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Ishaani Priyadarshini
Autism spectrum disorder (ASD) has been associated with conditions like depression, anxiety, epilepsy, etc., due to its impact on an individual?s educational, social, and employment. Since diagnosis is challenging and there is no cure, the goal is to max...
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Qiaoxing Li and Qinrui Tian
The academic research on the spatial distribution of pension institutions is mostly from the perspective of constructing or improving spatial analysis methods. It is not considered that with the development of social science and technology, the facilitie...
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Wen Tian, Xuefang Zhou, Ying Zhang, Qin Fang and Mingjian Yang
This work can enhance the airline?s participation in the implementation process of the CTOP and the fairness in the resource collaborative allocation of en-route network.
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Assyifa Nur Amanda Putri,Innocentius Bernarto
Pág. 77 - 90
This research aims to analyze the positive influence of price fairness, promotion, and perceived ease of use on repurchase intention. The survey method was used to analyze the results. Data collection technique was carried out through a questionnaire ins...
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Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes and Laurent Risser
Automatic recommendation systems based on deep neural networks have become extremely popular during the last decade. Some of these systems can, however, be used in applications that are ranked as High Risk by the European Commission in the AI act?for ins...
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Nikzad Chizari, Keywan Tajfar and María N. Moreno-García
In today?s technology-driven society, many decisions are made based on the results provided by machine learning algorithms. It is widely known that the models generated by such algorithms may present biases that lead to unfair decisions for some segments...
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Yazhi Liu, Dongyu Wei, Chunyang Zhang and Wei Li
In QoE fairness optimization of multiple video streams, a distributed video stream fairness scheduling strategy based on federated deep reinforcement learning is designed to address the problem of low bandwidth utilization due to unfair bandwidth allocat...
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Zheyi Chen, Weixian Liao, Pu Tian, Qianlong Wang and Wei Yu
Distributed machine learning paradigms have benefited from the concurrent advancement of deep learning and the Internet of Things (IoT), among which federated learning is one of the most promising frameworks, where a central server collaborates with loca...
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Pranita Patil and Kevin Purcell
Although deep learning has proven to be tremendously successful, the main issue is the dependency of its performance on the quality and quantity of training datasets. Since the quality of data can be affected by biases, a novel deep learning method based...
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