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Impact of social media brand blunders on brand trust and brand liking
(Sage, 2023-07)
More companies are engaging with consumers in real-time on digital platforms, which may lead to accidental or unintentional sharing of messages. Accordingly, how to manage online brand crises has become an increasingly ...
Adaptive shared control with human intention estimation for human agent collaboration
(IEEE, 2022)
In this paper an adaptive shared control frame-work for human agent collaboration is introduced. In this framework the agent predicts the human intention with a confidence factor that also serves as the control blending ...
Classifying LPI radar waveforms with time-frequency transformations using multi-stage CNN system
(IEEE, 2022)
As the number of radar waveforms in the cognitive electronic warfare applications increases, individual detection and classification performances of each waveform vary furthermore due to their different characteristics. ...
On the use of machine learning for predicting defect fix time violations
(Science and Technology Publications, 2022)
Accurate prediction of defect fix time is important for estimating and coordinating software maintenance efforts. Likewise, it is useful to predict whether or not the initially estimated defect fix time will be exceeded ...
A prudential paradox: The signal in (not) restricting bank dividends
(Wiley, 2022)
By restricting dividends in the weakest banks, prudential regulators counterintuitively induce more capital payouts in marginal banks. The potential for bank runs exacerbates the incentive to signal strength through dividend ...
Automatic detection of attachment style in married couples through conversation analysis
(Springer, 2023-05-31)
Analysis of couple interactions using speech processing techniques is an increasingly active multi-disciplinary field that poses challenges such as automatic relationship quality assessment and behavioral coding. Here, we ...
Deep reinforcement learning approach for trading automation in the stock market
(IEEE, 2022)
Deep Reinforcement Learning (DRL) algorithms can scale to previously intractable problems. The automation of profit generation in the stock market is possible using DRL, by combining the financial assets price 'prediction' ...
Actor-critic reinforcement learning for bidding in bilateral negotiation
(TÜBİTAK, 2022)
Designing an effective and intelligent bidding strategy is one of the most compelling research challenges in automated negotiation, where software agents negotiate with each other to find a mutual agreement when there is ...
Genetic algorithms and heuristics hybridized for software architecture recovery
(Springer, 2023-06-26)
Large scale software systems must be decomposed into modular units to reduce maintenance efforts. Software Architecture Recovery (SAR) approaches have been introduced to analyze dependencies among software modules and ...
A comparative study on the high-temperature forming and constitutive modeling of Ti-6Al-4V
(Springer, 2022-09-28)
Ti-6Al-4V alloy is often preferred for high-performance components such as aerospace components due to its superior material properties and thermal resistance. In order to produce these components in the desired geometry, ...
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