Results 121 to 130 of about 108,016 (310)

Tissue‐Stimulator Platform for Electrically Stimulating Pancreatic β‐Cells for Long‐Term Functional Regulation

Advanced Functional Materials, EarlyView.
We present a tissue‐stimulator platform for seamless electrode integration with pancreatic tissue, applying uniform electrical stimulation through optimized design with biohybrid 3D printing. Advantageous effects of electrical stimulation on β‐cell function were observed, including enhanced calcium signaling, islet morphology, and maturation.
Jihwan Kim, Uijung Yong, Myungji Kim, Jaewook Kim, Yeonggwon Jo, In Kyong Shim, Song Cheol Kim, Jinah Jang   +7 more
wiley   +1 more source

Using support vector machines with multiple indices of diffusion for automated classification of mild cognitive impairment

, 2012
Few studies have looked at the potential of using diffusion tensor imaging (DTI) in conjunction with machine learning algorithms in order to automate the classification of healthy older subjects and subjects with mild cognitive impairment (MCI).
Lamberton, Franck, David Prvulovic, O’Neill, Desmond, Desmond O'Neill, Harald Hampel, Prvulovic David, Bartley, M., Prvulovic, D., Coughlan, T., Mazoyer, B., Lamberton, F., Collins, D.R., Bokde, Arun L W, Laurence O'Dwyer, Coughlan Tara, O'Neill, Desmond, Ewers, Michael, Bokde, A.L., O'Neill, D., Ewers, M., Mazoyer Bernard, Franck Lamberton, Collins, D. Rónán, O'Neill Desmond, Arun L W Bokde, Tara Coughlan, Bartley, Máiréad, Bokde Arun L. W., Faluyi, Y.O., Hampel Harald, D Rónán Collins, O'Dwyer Laurence, O'Dwyer, Laurence, Collins, D Rónán, Máiréad Bartley, Tanner, C., Faluyi, Yetunde O., Tanner Colby, Bartley Máiréad, O’Dwyer, Laurence, Bokde, Arun L. W., Lamberton Franck, Faluyi Yetunde O., Mazoyer, Bernard M., Mazoyer, Bernard, Hampel, Harald, Prvulovic, David, Michael Ewers, O'Dwyer, L.G., Faluyi, Yetunde O, Colby Tanner, Collins D. Rónán, Tanner, Colby, Hampel, H., Coughlan, Tara, Ewers Michael, Yetunde O Faluyi, Bernard Mazoyer   +57 more
core   +1 more source

A Non‐Reciprocal Architected Porous Medium

Advanced Functional Materials, EarlyView.
ABSTRACT In several fluid flow, energy‐dumping, and energy‐harvesting applications, a dominant flow direction or dominant resistance direction is desirable. In this study, we propose a simple modular geometry that doubles flow resistance in one direction relative to the opposite direction, while maintaining laminar viscous flow.
Clément Vezies, Pablo Zavattieri, Nicolás Silin   +2 more
wiley   +1 more source

Interior Point Methods for Massive Support Vector Machines

, 2000
We investigate the use of interior point methods for solving quadratic programming problems with a small number of linear constraints where the quadratic term consists of a low-rank update to a positive semi-de nite matrix. Several formulations of the
Ferris, Michael, Munson, Todd
core  

Active Learning‐Accelerated Discovery of Fibrous Hydrogels with Tissue‐Mimetic Viscoelasticity

Advanced Functional Materials, EarlyView.
Active learning accelerates the design of fibrous hydrogels that mimic the viscoelasticity of native tissues. By integrating multi‐objective optimization and closed‐loop experimentation, this approach efficiently identifies optimal formulations from thousands of possibilities and decouples elasticity and viscosity. The resulting hydrogels offer tunable
Zhengkun Chen, Zheyuan Miao, Gary Tom, Austin H. Cheng, Elizaveta Gusarova, Benjamen Zondag, Tianyi Wu, Dianoosh Kalhori, Boris Hinz, Milad Abolhasani, Alán Aspuru‐Guzik, Eugenia Kumacheva   +11 more
wiley   +1 more source

Memory-efficient large-scale linear support vector machine

, 2014
Stochastic gradient descent has been advanced as a computationally efficient method for large-scale problems. In classification problems, many proposed linear support vector machines as very effective classifiers.
Takeda, Akiko, Niranjan, Mahesan, Alrajeh, Abdullah   +2 more
core  

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source

Exploring Kernel Machines and Support Vector Machines: Principles, Techniques, and Future Directions

Mathematics
The kernel method is a tool that converts data to a kernel space where operation can be performed. When converted to a high-dimensional feature space by using kernel functions, the data samples are more likely to be linearly separable.
Ke-Lin Du, Bingchun Jiang, Jiabin Lu, Jingyu Hua, M. N. S. Swamy   +4 more
doaj   +1 more source

Multitraining support vector machine for image retrieval

, 2006
Relevance feedback (RF) schemes based on support vector machines (SVMs) have been widely used in content-based image retrieval (CBIR). However, the performance of SVM-based RF approaches is often poor when the number of labeled feedback samples is small.
Tao, D., Li, J, Li, X, Li, J., Li, Xuelong, Allinson, N., Allinson, N, Tao, D   +7 more
core   +1 more source

Integrated Field‐Free SOT Domain‐Wall Synapses and MTJ Stochastic Neurons for Hardware Boltzmann Machines

Advanced Functional Materials, EarlyView.
Field‐free spin‐orbit torque domain‐wall synapses integrated with stochastic MTJ neurons enable compact hardware Boltzmann machines. Leveraging intrinsic stochasticity and multi‐level conductance, the system achieves efficient probabilistic learning with high accuracy, demonstrating a scalable spintronic platform for energy‐efficient edge AI.
Aijaz H. Lone, Meng Tang, Camelia Florica, Bin He, Jingkai Xu, Selma Amara, Georgian Melinte, Xixiang Zhang, Gianluca Setti   +8 more
wiley   +1 more source