Titlebook: Quantum Computing: Applications and Challenges; Habiba Drias,Farouk Yalaoui Conference proceedings 2024 The Editor(s) (if applicable) and

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itende mit entsprechenden digitalen Kompetenzen zur Verfügung stehen. Gleichzeitig bietet die Digitalisierung dem HR-Management selbst die Chance, die eigenen Prozesse und Instrumente weiterzuentwickeln und noch mehr zu optimieren. Ma?gebliche Ver?nderungen gibt es vor allem in drei organisatorische

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Variational Circuit Based Hybrid Quantum-Classical Algorithm VC-HQCA, classifiers implemented in Qiskit, a widely-used quantum computing framework..The findings of this research provide compelling evidence for the significance of variational circuit design in QML models. By demonstrating the impact of circuit design on model performance.

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,Quantum Inspired Grey Wolf Optimizer for?Convolutional Neural Network Hyperparameter Optimization,experiments on the CIFAR-10 dataset using the AlexNet architecture. Comparison with other GWO-based approaches shows the excellent performance of the proposed algorithm in terms of classification accuracy. Furthermore, the numerical results indicate the potential of qGWO-CNN to be a promising approa

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Frequent Itemsets Mining Using New Quantum Inspired Elephant Swarm Algorithm,y of QDEHO with well-known state of the art algorithms such as Particle Swarm Optimization (PSO) and Bat algorithm (BAT) was undertook, where the results showed that QDEHO is superior to the competing algorithms in almost all datasets.

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Gaussian Quantum-Behaved PSO Strategy for Lithium Battery Model Optimization,PSO strategy’s exceptional performance showcases the advantages of combining quantum mechanics’ principles and Gaussian distributions with swarm intelligence for accurate and efficient lithium battery modeling, paving the way for improved energy storage system applications.

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,Q-CODA: Co-designing Quantum Codes and?Architectures for?Hardware-Aware Quantum Error Correction, can potentially further suppress logical faults by avoiding oversimplified assumptions. We introduce a modeling framework to quantify overhead reductions from our coordinated techniques. While considerable research remains to realize practical solutions, this work delineates promising directions by