Relevant bibliographies by topics / Artificial dendrite

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Artificial dendrite'

Author: Grafiati
Published: 7 July 2024
Last updated: 31 July 2025

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Journal articles on the topic "Artificial dendrite"

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Jia, Dongbao, Weixiang Xu, Dengzhi Liu, Zhongxun Xu, Zhaoman Zhong, and Xinxin Ban. "Verification of Classification Model and Dendritic Neuron Model Based on Machine Learning." Discrete Dynamics in Nature and Society 2022 (July 4, 2022): 1–14. http://dx.doi.org/10.1155/2022/3259222.

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Artificial neural networks have achieved a great success in simulating the information processing mechanism and process of neuron supervised learning, such as classification. However, traditional artificial neurons still have many problems such as slow and difficult training. This paper proposes a new dendrite neuron model (DNM), which combines metaheuristic algorithm and dendrite neuron model effectively. Eight learning algorithms including traditional backpropagation, classic evolutionary algorithms such as biogeography-based optimization, particle swarm optimization, genetic algorithm, popu
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Liu, Yang. "Overview of the Recent Progress of Suppressing the Dendritic Growth on Lithium Metal Anode for Rechargeable Batteries." Journal of Physics: Conference Series 2152, no. 1 (2022): 012060. http://dx.doi.org/10.1088/1742-6596/2152/1/012060.

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Abstract The lithium metal has been considered as a competitive material for anode on the high-energy storage battery because of its various advantages, such as high capacity, low density, and the lowest electrochemical potential. However, the uncontrolled dendritic growth on the anode surface could cause the short circuit, even explosion of the battery. Therefore, strategies about how to effectively inhibit the formation of dendrites is of great importance. This paper will first give a brief introduction on the growth of dendrites. The attention is then focused on the recent advancements to s
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Cheng, Shaoyong. "Mitigating Lithium Dendrite Growth through Anode Material Selection and Optimization in Lithium Metal Batteries." MATEC Web of Conferences 410 (2025): 01028. https://doi.org/10.1051/matecconf/202541001028.

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Lithium dendrite growth in lithium metal batteries (LMBs) causes capacity loss, short circuits, and thermal runaway. This study explores anode material optimization and structural design to mitigate dendrite formation. Freestanding Li membranes fabricated with lignin- containing cellulose nanofibers (LCNF) and MXene form a robust, low- porosity structure that suppresses dendrites. Three-dimensional (3D) current collectors homogenize electric fields and regulate Li-ion flux, stabilizing Li deposition. An artificial solid electrolyte interphase (SEI) layer based on sp²- hybridized covalent organ
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Tanaka, Makito, Tetsuro Sasada, Tetsuya Nakamoto, et al. "Immunogenicity of Artificial Dendritic Cells Is Upregulated by ROCK Inhibition-Mediated Dendrite Formation." Blood 114, no. 22 (2009): 3022. http://dx.doi.org/10.1182/blood.v114.22.3022.3022.

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Abstract Abstract 3022 Poster Board II-998 Dendritic cells (DC) are “professional” antigen-presenting cells (APC) that can prime T cells. Their characteristic morphology and phenotype segregate them from other APC. Many studies suggest that mature DC are able to induce potent antitumor T cell immunity that can reject tumors. Based on this, numerous cancer vaccine trials using ex vivo generated DC have been conducted in humans. However, the observed objective response rates in these studies have been disappointing. This could partially be attributed to difficulties in generating large numbers o
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Mu, Yanlu, Tianyi Zhou, Zhaoyi Zhai, et al. "Metal organic complexes as an artificial solid-electrolyte interface with Zn-ion transfer promotion for long-life zinc metal batteries." Nanoscale 13, no. 48 (2021): 20412–16. http://dx.doi.org/10.1039/d1nr05753g.

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The schematic diagram for the plating/stripping process of Zn. (a) Corrosion, by-products, and Zn dendrites are observed on a bare Zn electrode. (b) The Zn–THBA protective layer endows a dense and dendrite-free plating/stripping morphology.
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Jing, Zhaokun, Yuchao Yang, and Ru Huang. "Dual-mode dendritic devices enhanced neural network based on electrolyte gated transistors." Semiconductor Science and Technology 37, no. 2 (2021): 024002. http://dx.doi.org/10.1088/1361-6641/ac3f21.

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Abstract As a fundamental component of biological neurons, dendrites have been proven to have crucial effects in neuronal activities. Single neurons with dendrite structures show high signal processing capability that is analogous to a multilayer perceptron (MLP), whereas oversimplified point neuron models are still prevalent in artificial intelligence algorithms and neuromorphic systems and fundamentally limit their efficiency and functionality of the systems constructed. In this study, we propose a dual-mode dendritic device based on electrolyte gated transistor, which can be operated to gen
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Berger, Thomas, Matthew E. Larkum, and Hans-R. Lüscher. "High I h Channel Density in the Distal Apical Dendrite of Layer V Pyramidal Cells Increases Bidirectional Attenuation of EPSPs." Journal of Neurophysiology 85, no. 2 (2001): 855–68. http://dx.doi.org/10.1152/jn.2001.85.2.855.

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Despite the wealth of recent research on active signal propagation along the dendrites of layer V neocortical pyramidal neurons, there is still little known regarding the traffic of subthreshold synaptic signals. We present a study using three simultaneous whole cell recordings on the apical dendrites of these cells in acute rat brain slices to examine the spread and attenuation of spontaneous excitatory postsynaptic potentials (sEPSPs). Equal current injections at each of a pair of sites separated by ∼500 μm on the apical dendrite resulted in equal voltage transients at the other site (“recip
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Peng, Hong, Tingting Bao, Xiaohui Luo, et al. "Dendrite P systems." Neural Networks 127 (July 2020): 110–20. http://dx.doi.org/10.1016/j.neunet.2020.04.014.

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Zhang, Xiliang, Sichen Tao, Zheng Tang, Shuxin Zheng, and Yoki Todo. "The Mechanism of Orientation Detection Based on Artificial Visual System for Greyscale Images." Mathematics 11, no. 12 (2023): 2715. http://dx.doi.org/10.3390/math11122715.

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Human visual system is a crucial component of the nervous system, enabling us to perceive and understand the surrounding world. Advancements in research on the visual system have profound implications for our understanding of both biological and computer vision. Orientation detection, a fundamental process in the visual cortex where neurons respond to linear stimuli in specific orientations, plays a pivotal role in both fields. In this study, we propose a novel orientation detection mechanism for local neurons based on dendrite computation, specifically designed for grayscale images. Our model
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Chakilam, Shashikanth, Dan Ting Li, Zhang Chuan Xi, Rimvydas Gaidys, and Audrone Lupeikiene. "Morphological Study of Insect Mechanoreceptors to Develop Artificial Bio-Inspired Mechanosensors." Engineering Proceedings 2, no. 1 (2020): 70. http://dx.doi.org/10.3390/ecsa-7-08199.

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Mechanoreceptors of the insect play a vital role for the insect to sense and monitor the environmental parameters, like flow, tactile pressure, etc. This paper presents the studies made on the morphology of the mechanoreceptor of the insect Blattella asahinai (scientific name of cockroach) that is a hair-like structure known as trichoid sensilla, by scanning electron microscope and confocal laser microscope. The scanned images show the details of sensilla components in which the hair is embedded in the sockets, which are connected with the cuticle and joint membrane, where the dendrite touches
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Dissertations / Theses on the topic "Artificial dendrite"

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Cheng, Long. "Relaxor ferroelectrics for neuromorphic computing." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPAST073.

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Pour surmonter les défis posés par les architectures traditionnelles de von Neumann, l'informatique neuromorphique s'inspire des sciences du cerveau pour créer du matérielécoénergétique adaptable à des tâches complexes. Les memristors, bien que novateurs,rencontrent des problèmes tels que la chaleur de Joule entravant le calcul neuronal à trèsbasse puissance.Pour remédier à cela, nous proposons un mécanisme de memcapacitor -la transition de phase induite par champ électrique. Les memcapacitors, qui expriment les signaux en tension, offrent une consommation d'énergie inférieure aux memristors (
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Chan, Erwin Pai Hsiung. "Immune reactivity to metal implants." University of Western Australia. School of Anatomy and Human Biology, 2009. http://theses.library.uwa.edu.au/adt-WU2009.0194.

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The use of metals like titanium (Ti) and vanadium (V) are common in many medical implants for orthopaedic and orthodontic purposes. The most frequent cause of implant failure is aseptic loosening, resulting from an inflammatory reaction and increased osteolysis at the bone-metal interface. Currently, the pathophysiological mechanism of aseptic loosening remains poorly understood. One hypothesis suggests the reactivity of immune cells (metal hypersensitivity) towards metal ions released through the biocorrosion of metal implants. This thesis examines the effects of titanium and vanadium ions on
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Takeda, Shigeo. "Functionalization of Glucan Dendrimers and Bio-applications." Kyoto University, 2020. http://hdl.handle.net/2433/253505.

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Janzakova, Kamila. "Développement de dendrites polymères organiques en 3D comme dispositif neuromorphique." Electronic Thesis or Diss., Université de Lille (2022-....), 2023. http://www.theses.fr/2023ULILN017.

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Les technologies neuromorphiques constituent une voie prometteuse pour le développement d'une informatique plus avancée et plus économe en énergie. Elles visent à reproduire les caractéristiques attrayantes du cerveau, telles qu'une grande efficacité de calcul et une faible consommation d'énergie au niveau des logiciels et du matériel. À l'heure actuelle, les implémentations logicielles inspirées du cerveau (telles que ANN et SNN) ont déjà démontré leur efficacité dans différents types de tâches (reconnaissance d'images et de la parole). Toutefois, pour tirer un meilleur parti des algorithmes
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Almeida, Fernando Mendonça de. "Autoproteção para a internet das coisas." Universidade Federal de Sergipe, 2016. https://ri.ufs.br/handle/riufs/3361.

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Fundação de Apoio a Pesquisa e à Inovação Tecnológica do Estado de Sergipe - FAPITEC/SE<br>The Internet of Things is a new paradigm of communication based on the ubiquitous presence of objects that, having unique address, they can cooperate with their peers to achieve a common goal. Applications in several areas can benefit from this new paradigm, but the Internet of Things is very vulnerable to attack. The large number of connected devices make an autonomic approach necessary and the small amount of resources requires the use of efficient techniques. This paper proposes a self-protection
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Lin, Yu-Sheng, and 林侑陞. "Synthesis of Peptide Conjugated Poly(amidoamine) Dendrimer as Artifical Racemerase." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/97525607925182174395.

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碩士<br>高雄醫學大學<br>醫藥暨應用化學研究所<br>98<br>Pyridoxal 5′-Phosphate (PLP) is the active member of of vitamin B6. PLP are known to perform numbers of reactivities in a variety of enzymes in which the lysine is a conserved residue for harboring PLP via Schiff base moiety. This is also known as external aldimine. During the course of reaction, the inbound substrate will form new Schiff base with PLP, and known as external aldimine. The exchange between external and internal aldimine is important for the demonstration of reactions. Base on the previous experimental results, we design a tripeptide involving
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Book chapters on the topic "Artificial dendrite"

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Rouw, Eelco, Jaap Hoekstra, and Arthur H. M. van Roermund. "An artificial dendrite using active channels." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0100484.

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Bell, Tony. "Artificial dendritic learning." In Neural Networks. Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-52255-7_37.

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Jia, Huijue. "Memory in Dendritic Spines." In Neuroscience for Artificial Intelligence. Jenny Stanford Publishing, 2023. http://dx.doi.org/10.1201/9781003410980-5.

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Herreras, O., J. M. Ibarz, L. López-Aguado, and P. Varona. "Dendrites: The Last-Generation Computers." In Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45720-8_1.

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Chelly, Zeineb, Abir Smiti, and Zied Elouedi. "COID-FDCM: The Fuzzy Maintained Dendritic Cell Classification Method." In Artificial Intelligence and Soft Computing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29350-4_28.

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Ohme, M., and A. Schierwagen. "A reduced model for dendritic trees with active membrane." In Artificial Neural Networks — ICANN 96. Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61510-5_117.

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Möller, Ralf, and Horst-Michael Groß. "Possible Functional Roles of the Bipartite Dendrites of Pyramidal Cells." In Neural Networks: Artificial Intelligence and Industrial Applications. Springer London, 1995. http://dx.doi.org/10.1007/978-1-4471-3087-1_9.

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Panchev, Christo, Stefan Wermter, and Huixin Chen. "Spike-Timing Dependent Competitive Learning of Integrate-and-Fire Neurons with Active Dendrites." In Artificial Neural Networks — ICANN 2002. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-46084-5_145.

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Vandesompele, Alexander, Francis Wyffels, and Joni Dambre. "Dendritic Computation in a Point Neuron Model." In Artificial Neural Networks and Machine Learning – ICANN 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61616-8_48.

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Sommerkorn, G., U. Seiffert, D. Surmeli, A. Herzog, B. Michaelis, and K. Braun. "Classification of 3-D Dendritic Spines using Self-Organizing Maps." In Artificial Neural Nets and Genetic Algorithms. Springer Vienna, 1998. http://dx.doi.org/10.1007/978-3-7091-6492-1_28.

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Conference papers on the topic "Artificial dendrite"

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Nakagawa, K., T. Takaki, Y. Morita, and E. Nakamachi. "2D Phase-Field Analyses of Axonal Extension of Nerve Cell." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-64281.

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In this study, we aimed to develop a computer-aided simulation technique to predict the axonal extension in the neuronal network evolution processes for design new scaffolds to activate the nerve cell and promote the nerve regeneration. We developed a mathematical model of axonal extension by using phase-field method and evaluated the validity of the mathematical model by comparison with the experiments. In the previous experimental studies, the peripheral nerve scaffold has been introduced to guide the axonal extension. Damaged part of nerve was replaced by the artificial tube as the scaffold
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Hutchinson, Zachary. "Artificial Dendrites: an Algorithm." In 2020 IEEE Second International Conference on Cognitive Machine Intelligence (CogMI). IEEE, 2020. http://dx.doi.org/10.1109/cogmi50398.2020.00033.

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Jung, Jin-Young, and Michael M. Chen. "Numerical Simulation of Dendritic Solidification." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-1481.

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Abstract It is well known that the dendritic microstructure of alloys is a consequence of morphological instability of the solidification process, which is a result of the coupling of heat and mass transfer with the composition-dependent phase equilibrium condition mediated by the surface energy. There have been many numerical simulations of dendritic solidification. However, many successful simulations of dendritic growth have used non-discrete front tracking method such as artificial source method or phase field method, with demonstrably first order accuracy. Many also found it necessary to
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Kumar, Manoj, and Manan Suri. "Oxide-based Memory Devices as Artificial Dendrites for Neuromorphic Hardware." In 2023 IEEE 23rd International Conference on Nanotechnology (NANO). IEEE, 2023. http://dx.doi.org/10.1109/nano58406.2023.10231171.

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Li, Jiayi, Zhipeng Liu, Yaotong Song, and Shangce Gao. "Recurrent Dendritic Neural Network." In 2023 IEEE 11th Joint International Information Technology and Artificial Intelligence Conference (ITAIC). IEEE, 2023. http://dx.doi.org/10.1109/itaic58329.2023.10408923.

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Hutchinson, Zachary. "An Artificial Dendritic Neuron Model Using Radial Basis Functions." In 15th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications, 2023. http://dx.doi.org/10.5220/0011775400003393.

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Huang, R., H. Tawfik, and A. K. Nagar. "Artificial Dendritic Cells Algorithm for Online Break-In Fraud Detection." In 2009 Second International Conference on Developments in eSystems Engineering (DESE). IEEE, 2009. http://dx.doi.org/10.1109/dese.2009.59.

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van Ooyen, A. "Influence of dendritic morphology on axonal competition." In 9th International Conference on Artificial Neural Networks: ICANN '99. IEE, 1999. http://dx.doi.org/10.1049/cp:19991243.

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Zhou, Wen, Yiwen Liang, Hongbin Dong, Chengyu Tan, Zhenhua Xiao, and Weiwei Liu. "A Numerical Differentiation Based Dendritic Cell Model." In 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2017. http://dx.doi.org/10.1109/ictai.2017.00167.

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Huan Yang, Jun Fu, Shijie Yi, Chengyu Tan, and Yiwen Liang. "Dendritic cell algorithm for web server aging detection." In International Conference on Automatic Control and Artificial Intelligence (ACAI 2012). Institution of Engineering and Technology, 2012. http://dx.doi.org/10.1049/cp.2012.1088.

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