Results 71 to 80 of about 64,340 (254)

Kernel Analysis Based on Dirichlet Processes Mixture Models

Entropy, 2019
Kernels play a crucial role in Gaussian process regression. Analyzing kernels from their spectral domain has attracted extensive attention in recent years. Gaussian mixture models (GMM) are used to model the spectrum of kernels.
Jinkai Tian, Peifeng Yan, Da Huang
doaj   +1 more source

Enhancing Low‐Temperature Performance of Sodium‐Ion Batteries via Anion‐Solvent Interactions

Advanced Functional Materials, EarlyView.
DOL is introduced into electrolytes as a co‐solvent, increasing slat solubility, ion conductivity, and the de‐solvent process, and forming an anion‐rich solvent shell due to its high interaction with anion. With the above virtues, the batteries using this electrolyte exhibit excellent cycling stability at low temperatures. Abstract Sodium‐ion batteries
Cheng Zheng, Qian Yao, Yanan Sun, Hongyu Lv, Zhongchao Bai, Guoliang Zhang, Nana Wang, Jian Yang   +7 more
wiley   +1 more source

Counterion Dependent Side‐Chain Relaxation Stiffens a Chemically Doped Thienothiophene Copolymer

Advanced Functional Materials, EarlyView.
Oxidation of a thienothiophene copolymer, p(g3TT‐T2), via different doping strategies and dopant molecules resulted in materials with similar oxidation levels and a high electrical conductivity of ≈100 S cm−1. However, mechanical properties varied significantly, with sub‐glass transition temperatures and elastic moduli spanning from –44°C to –3°C and ...
Mariavittoria Craighero, Meghna Jha, Elsa Veronica Flores‐Vela, Joost Kimpel, Andreas Schaefer, Jiali Guo, Jesika Asatryan, Alberto Peinador Veiga, Shuichi Haraguchi, Per‐Anders Carlsson, Jaime Martín, Mariano Campoy‐Quiles, Christian Müller   +12 more
wiley   +1 more source

Timely Classification and Verification of Network Traffic Using Gaussian Mixture Models

IEEE Access, 2020
We present a novel approach for timely classification and verification of network traffic using Gaussian Mixture Models (GMMs). We generate a separate GMM for each class of applications using component-wise expectation-maximization (CEM) to match the ...
Hassan Alizadeh, Harald Vranken, Andre Zuquete, Ali Miri   +3 more
doaj   +1 more source

Hard-Clustering with Gaussian Mixture Models

CoRR, 2016
Training the parameters of statistical models to describe a given data set is a central task in the field of data mining and machine learning. A very popular and powerful way of parameter estimation is the method of maximum likelihood estimation (MLE). Among the most widely used families of statistical models are mixture models, especially, mixtures of
Johannes Blömer, Sascha Brauer, Kathrin Bujna   +2 more
openaire   +2 more sources

Intermediate Resistive State in Wafer‐Scale Vertical MoS2 Memristors Through Lateral Silver Filament Growth for Artificial Synapse Applications

Advanced Functional Materials, EarlyView.
In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa, Milan Buttberg, Ke Ran, Rana Walied Ahmad, Dennis Braun, Lukas Völkel, Jimin Lee, Sofía Cruces, Bart Macco, Bárbara Canto, Holger Lerch, Thorsten Wahlbrink, Holger Kalisch, Michael Heuken, Andrei Vescan, Joachim Mayer, Zhenxing Wang, Ilia Valov, Stephan Menzel, Max C. Lemme   +19 more
wiley   +1 more source

Integration of Low‐Voltage Nanoscale MoS2 Memristors on CMOS Microchips

Advanced Functional Materials, EarlyView.
This article presents the first monolithic integration of nanoscale MoS2‐based memristors into the back‐end‐of‐line of foundry‐fabricated CMOS microchips in a one‐transistor‐one‐resistor (1T1R) architecture. The MoS2‐based 1T1R cells exhibit forming‐free, nonvolatile resistive switching with ultra‐low operating voltages, low cycle‐to‐cycle variability ...
Jimin Lee, Sofía Cruces, Xiaohua Liu, Yang Chen, Vasilis A. Maroufidis, Janghyun Jo, Lukas Völkel, Dennis Braun, Michael Möller, Leon Brackmann, Holger Kalisch, Michael Heuken, Andrei Vescan, Rafal E. Dunin‐Borkowski, Joachim Mayer, Stefan Wiefels, Max C. Lemme   +16 more
wiley   +1 more source

Robust Electrocaloric Performance Enabled by Highly‐Polar Frustrated Nanodomains in NaNbO3‐Based Ferrodistortive Relaxor

Advanced Functional Materials, EarlyView.
P4bm framework in NaNbO3‐Ba(Ti, Hf)O3 ferrodistortive relaxor entails short‐range and highly‐polar ferrodistortive orders. The abundant highly‐polar orders facilitate to increase entropy change, and robust octahedral oxygen tilt enables to impede thermal perturbations.
Feng Li, Changshun Dai, He Qi, Jiecheng Liu, Xiaoming Shi, Heng Zhou, Qiong Yang, Mingsheng Long, Lei Shan, Chunchang Wang, Jianli Wang, Zhenxiang Cheng   +11 more
wiley   +1 more source

Swelling‐Programmed Topographical Guidance for Dynamic Spheroid Self‐Assembly via a Mechanochemical Hydrogel Niche

Advanced Functional Materials, EarlyView.
A swelling‐programmed micropatterned hydrogel guides adherent cells through a controlled transition from cell–matrix anchoring to cadherin‐mediated cell–cell compaction, enabling rapid assembly of high‐viability spheroids with defined size and morphology.
Han Gyeol Nam, Seon Yeong Chae, Young Woo Kwon, Hye Jin Heo, Hye Rin Lee, Ji Hyeok Lee, Dong‐Wook Han, Yun Hak Kim, Suck Won Hong   +8 more
wiley   +1 more source

Positive Sequential Data Modeling Using Continuous Hidden Markov Models Based on Inverted Dirichlet Mixtures

IEEE Access, 2019
The hidden Markov model (HMM) has long been one of the most commonly used probability graph models for modeling sequential or time series data. It has been widely used in many fields ranging from speech recognition, face recognition, anomaly detection ...
Ru Wang, Wentao Fan
doaj   +1 more source