Superconducting motors are an enabling technology for future large scale electric transport, such as freight, aviation, and shipping. As cryogenics are essential for superconductivity, the power electronics used to dr...
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Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Solid-state quantum memories can provide broadband storage, but they primarily suffer from low stor...
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We investigated the effect of copper ion concentration in zinc-copper dual-ion electrolytes to suppress dendrites and extend the cycle life of zinc ion capacitors. The devices were characterized in terms of changes in...
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ISBN:
(数字)9798331529468
ISBN:
(纸本)9798331529475
We investigated the effect of copper ion concentration in zinc-copper dual-ion electrolytes to suppress dendrites and extend the cycle life of zinc ion capacitors. The devices were characterized in terms of changes in microstructure and cycling stability. The nuclei size was decreased in the optimal copper ion concentration to promote lateral deposition and avoid vertical dendrites. The device exhibited stable cycling performance with a capacitance retention of 95% after 10,000 redox cycles, compared to the device with single zinc ion electrolyte which short circuited at around 1,250 redox cycles.
Safety is paramount in all swimming pools. The current systems expected to address the problem of ensuring safety at swimming pools have significant problems due to their technical aspects, such as underwater cameras ...
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The Column Subset Selection (CSS) problem has been widely studied in dimensionality reduction and feature selection. The goal of the CSS problem is to output a submatrix S, consisting of k columns from an n × d i...
ISBN:
(纸本)9798331314385
The Column Subset Selection (CSS) problem has been widely studied in dimensionality reduction and feature selection. The goal of the CSS problem is to output a submatrix S, consisting of k columns from an n × d input matrix A that minimizes the residual error ||A – SS† A||2F where S† is the Moore-Penrose inverse matrix of S. Many previous approximation algorithms have non-linear running times in both n and d, while the existing linear-time algorithms have a relatively larger approximation ratios. Additionally, the local search algorithms in existing results for solving the CSS problem are heuristic. To achieve linear running time while maintaining better approximation using a local search strategy, we propose a local search-based approximation algorithm for the CSS problem with exactly k columns selected. A key challenge in achieving linear running time with the local search strategy is how to avoid exhaustive enumerations of candidate columns for constructing swap pairs in each local search step. To address this issue, we propose a two-step mixed sampling method that reduces the number of enumerations for swap pair construction from O(dk) to k in linear time. Although the two-step mixed sampling method reduces the search space of local search strategy, bounding the residual error after swaps is a non-trivial task. To estimate the changes in residual error after swaps, we propose a matched swap pair construction method to bound the approximation loss, ensuring a constant probability of loss reduction in each local search step. In expectation, these techniques enable us to obtain the local search algorithm for the CSS problem with theoretical guarantees, where a 53(k + 1)-approximate solution can be obtained in linear running time O(ndk4 log k). Empirical experiments show that our proposed algorithm achieves better quality and time compared to previous algorithms on both small and large datasets. Moreover, it is at least 10 times faster than state-of-the-art algorith
Facial micro-expressions indicate brief and subtle facial movements that appear during emotional communication. In comparison to macro-expressions, micro-expressions are more challenging to be analyzed due to the shor...
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Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Here, we report a storage efficiency greater than 28% in a Tm3+: YAG crystal in elevated temperatur...
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Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output ...
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Choosing the right major at an early age can be overwhelming. In addition, career advising is limited in many schools. Studies show that among the factors that affects career selection are personal attributes, passion...
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ISBN:
(数字)9798331523657
ISBN:
(纸本)9798331523664
Choosing the right major at an early age can be overwhelming. In addition, career advising is limited in many schools. Studies show that among the factors that affects career selection are personal attributes, passion, and career exploration activities. In this study, we present an AI powered application utilizing Flutter and Virtual Reality (VR) technology to assist high school and university students in making informed career choices. The application provides personalized career recommendations based on personality tests. The study analyzed a publicly available dataset combining the results of Big Five personality test with personal information including the study majors. Synthetic Minority Oversampling Technique (SMOTE) was employed to handle class imbalance. Multiple classification models (Random Forest, Gradient Boosting, Decision Tree, Naive Bayes, and KNN) were tested. Our findings demonstrate that the Random Forest classifier, achieved better performance with an accuracy of 87.3% and an AUC-ROC of 0.99.
An intrusion Detection System (IDS) is a system that resides inside the network and monitors all incoming and outgoing traffic. It prevents unethical activities from happening over the network. With the use of IoT dev...
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