Gotowe bibliografie tematyczne / Dynamic Cell Clustering (DCC)

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  2. Rozprawy doktorskie
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  4. Streszczenia konferencji

Gotowa bibliografia na temat „Dynamic Cell Clustering (DCC)”

Autor: Grafiati
Data publikacji: 2 listopada 2024
Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Dynamic Cell Clustering (DCC)"

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Wang, Zheng, Lara M. Linden, Kaleb M. Naegeli, et al. "UNC-6 (netrin) stabilizes oscillatory clustering of the UNC-40 (DCC) receptor to orient polarity." Journal of Cell Biology 206, no. 5 (2014): 619–33. http://dx.doi.org/10.1083/jcb.201405026.

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The receptor deleted in colorectal cancer (DCC) directs dynamic polarizing activities in animals toward its extracellular ligand netrin. How DCC polarizes toward netrin is poorly understood. By performing live-cell imaging of the DCC orthologue UNC-40 during anchor cell invasion in Caenorhabditis elegans, we have found that UNC-40 clusters, recruits F-actin effectors, and generates F-actin in the absence of UNC-6 (netrin). Time-lapse analyses revealed that UNC-40 clusters assemble, disassemble, and reform at periodic intervals in different regions of the cell membrane. This oscillatory behavio
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Alammari, Amr A., Mohd Sharique, Athar Ali Moinuddin, and Mohammad Samar Ansari. "Local-Partial Signal Combining Schemes for Cell-Free Large-Scale MU-MIMO Systems with Limited Fronthaul Capacity and Spatial Correlation Channels." Electronics 11, no. 17 (2022): 2757. http://dx.doi.org/10.3390/electronics11172757.

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Cell-free large-scale multi-user MIMO is a promising technology for the 5G-and-beyond mobile communication networks. Scalable signal processing is the key challenge in achieving the benefits of cell-free systems. This study examines a distributed approach for cell-free deployment with user-centric configuration and finite fronthaul capacity. Moreover, the impact of scaling the pilot length, the number of access points (APs), and the number of antennas per AP on the achievable average spectral efficiency are investigated. Using the dynamic cooperative clustering (DCC) technique and large-scale
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Peters, Georg, and Richard Weber. "DCC: a framework for dynamic granular clustering." Granular Computing 1, no. 1 (2016): 1–11. http://dx.doi.org/10.1007/s41066-015-0012-z.

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Umar, Saminu, and Gafar M. Oyeyemi. "A Hybrid LSTM-DCC Model for Multivariate Cryptocurrency Volatility Prediction." Asian Journal of Probability and Statistics 27, no. 7 (2025): 179–91. https://doi.org/10.9734/ajpas/2025/v27i7784.

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Accurate volatility forecasting remains a central challenge in the analysis of cryptocurrency markets, where extreme price fluctuations, nonlinear dependencies and evolving cross-asset correlations complicate traditional modeling approaches. This study proposes a hybrid framework that integrates the Dynamic Conditional Correlation (DCC) Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MGARCH) model with Long Short-Term Memory (LSTM) networks to enhance forecasting accuracy. The LSTM–DCC model improves the representation of volatility clustering, structural breaks and int
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Haoxuan, Fu. "Study on the Dynamic Correlation between Chinese and American Financial Markets." INTERNATIONAL JOURNAL OF SOCIAL SCIENCE, INNOVATION AND EDUCATIONAL TECHNOLOGIES (ONLINE) - ISSN: 2717-7130 1, no. 3 (2020): 337–41. https://doi.org/10.5281/zenodo.3972443.

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With the deepening of the economic globalization and finance liberalization, the financial links between open economies are becoming closer and closer, and the interconnectivity between international financial markets is gradually increasing. With the support of DCC-GARCH model, the paper conducts an empirical study towards the dynamic correlation between American and Chinese stock markets. The result indicates that the logarithmic return series of Shanghai Composite index and S&P 500 index both show apparent volatility clustering and constancy. The correlation between them shows significa
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Haoxuan, Fu. "Study on the Dynamic Correlation between Chinese and American Financial Markets." INTERNATIONAL JOURNAL OF SOCIAL SCIENCE, INNOVATION AND EDUCATIONAL TECHNOLOGIES (ONLINE) - ISSN: 2717-7130 1, no. 3 (2020): 337–41. https://doi.org/10.5281/zenodo.3977135.

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With the deepening of the economic globalization and finance liberalization, the financial links between open economies are becoming closer and closer, and the interconnectivity between international financial markets is gradually increasing. With the support of DCC-GARCH model, the paper conducts an empirical study towards the dynamic correlation between American and Chinese stock markets. The result indicates that the logarithmic return series of Shanghai Composite index and S&P 500 index both show apparent volatility clustering and constancy. The correlation between them shows significa
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FOWLER, ANNA, VILAS MENON, and NICHOLAS A. HEARD. "DYNAMIC BAYESIAN CLUSTERING." Journal of Bioinformatics and Computational Biology 11, no. 05 (2013): 1342001. http://dx.doi.org/10.1142/s0219720013420018.

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Clusters of time series data may change location and memberships over time; in gene expression data, this occurs as groups of genes or samples respond differently to stimuli or experimental conditions at different times. In order to uncover this underlying temporal structure, we consider dynamic clusters with time-dependent parameters which split and merge over time, enabling cluster memberships to change. These interesting time-dependent structures are useful in understanding the development of organisms or complex organs, and could not be identified using traditional clustering methods. In c
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Şeker, Kudbeddin, and Ahmet Gökçe Akpolat. "Dynamic Stochastic Volatility Spillover Between Bitcoin and Precious Metals." Uluslararası Ekonomi İşletme ve Politika Dergisi 9, no. 1 (2025): 53–72. https://doi.org/10.29216/ueip.1596577.

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Since its creation in 2008, Bitcoin has often been compared to precious metals due to their shared characteristics as safe havens, hedges, and risk diversification tools. This study uses the DCC-GARCH model to analyze dynamic conditional correlations and volatility spillovers between Bitcoin and the returns of gold, copper, silver, and platinum. The findings reveal persistent volatility and clustering in the returns of both Bitcoin and these metals. There is a one-way volatility spillover from gold to Bitcoin, and from Bitcoin to copper, silver, and platinum. Significant dynamic conditional co
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Dai, Yun, and Hao Liu. "Application of the R-Tree Clustering Model in Medical Information Retrieval." Mobile Information Systems 2022 (August 11, 2022): 1–9. http://dx.doi.org/10.1155/2022/2887395.

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Hospitals produce a large amount of medical information every day. In the face of medical big data, the existing data processing methods cannot meet expectations and need to be continuously optimized. In the database system, when the stored objects are very large, and then the efficiency of data retrieval is a major bottleneck, therefore restricting the application of medical information. For that reason and to improve the efficiency of information retrieval, it is necessary to add an index to the information object and filter the dataset participating in the connection retrieval through the i
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Stavoe, Andrea K. H., and Daniel A. Colón-Ramos. "Netrin instructs synaptic vesicle clustering through Rac GTPase, MIG-10, and the actin cytoskeleton." Journal of Cell Biology 197, no. 1 (2012): 75–88. http://dx.doi.org/10.1083/jcb.201110127.

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Netrin is a chemotrophic factor known to regulate a number of neurodevelopmental processes, including cell migration, axon guidance, and synaptogenesis. Although the role of Netrin in synaptogenesis is conserved throughout evolution, the mechanisms by which it instructs synapse assembly are not understood. Here we identify a mechanism by which the Netrin receptor UNC-40/DCC instructs synaptic vesicle clustering in vivo. UNC-40 localized to presynaptic regions in response to Netrin. We show that UNC-40 interacted with CED-5/DOCK180 and instructed CED-5 presynaptic localization. CED-5 in turn si
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Rozprawy doktorskie na temat "Dynamic Cell Clustering (DCC)"

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Stock, Antoine. "Simulatiοn exaflοpique de la cοmbustiοn de sprays". Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMIR18.

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La simulation numérique des grandes échelles (LES, pour Large Eddy Simulation) s'est imposée comme un outil numérique puissant pour la conception et l'analyse des brûleurs de sprays, permettant de capturer avec une grande précision les interactions complexes entre l'écoulement turbulent, la combustion et la dynamique des sprays. Cependant, cette précision accrue de la LES s'accompagne d'un coût CPU élevé. Ces simulations nécessitent souvent l'utilisation de maillages de grande taille afin de résoudre les turbulences à petite échelle et les fronts de flamme nets, ainsi que la gestion de nombreu
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Putri, Givanna Haryono. "Revealing the Development of Immune Response through Temporal Dynamic Clustering." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/26874.

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The immune system is an integral part of our body and is responsible for keeping us healthy. For instance, under pathogenic invasion, an immune response is mounted to identify and clear the pathogens. The immune response is not always successful: whilst some individuals recover from a given infection, others do not. This has spurred efforts to better understand the process in the hope of finding effective health-promoting interventions. Cytometry is a key technology for quantifying the immune response, creating datasets that capture measurements of numerous characteristics of each individual c
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KC, Rabi. "Study of Some Biologically Relevant Dynamical System Models: (In)stability Regions of Cyclic Solutions in Cell Cycle Population Structure Model Under Negative Feedback and Random Connectivities in Multitype Neuronal Network Models." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou16049254273607.

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Części książek na temat "Dynamic Cell Clustering (DCC)"

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Dobrzyński, Maciej, Marc-Antoine Jacques, and Olivier Pertz. "Mining of Single-Cell Signaling Time-Series for Dynamic Phenotypes with Clustering." In Methods in Molecular Biology. Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2277-3_13.

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Guo, Mengli, Gang Chuai, Weidong Gao, and Yuhan Zhang. "Dynamic TDD Interference Mitigation Using Graph Theory Based Cell Clustering in 5G Ultra-Dense Network." In Lecture Notes in Electrical Engineering. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6571-2_85.

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Zhao, Zhanhong, Minzhu Xie, Qizhi Liu, and Ruijie Xie. "scGECA: A Graph Embedded Representation Learning Approach with Dynamic Attention Mechanism for Single-Cell Clustering." In Lecture Notes in Computer Science. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-95-0030-7_36.

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Parwez, Md Salik, Hasan Farooq, Ali Imran, and Hazem Refai. "Spectral Efficiency Self-Optimization through Dynamic User Clustering and Beam Steering." In Research Anthology on Developing and Optimizing 5G Networks and the Impact on Society. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7708-0.ch005.

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This paper presents a novel scheme for spectral efficiency (SE) optimization through clustering of users. By clustering users with respect to their geographical concentration we propose a solution for dynamic steering of antenna beam, i.e., antenna azimuth and tilt optimization with respect to the most focal point in a cell that would maximize overall SE in the system. The proposed framework thus introduces the notion of elastic cells that can be potential component of 5G networks. The proposed scheme decomposes large-scale system-wide optimization problem into small-scale local sub-problems a
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D'Hollander Erik H., Stroobandt Dirk, and Touhafi Abdellah. "ParaFPGA: Parallel Computing with Flexible Hardware." In Advances in Parallel Computing. IOS Press, 2010. https://doi.org/10.3233/978-1-60750-530-3-581.

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ParaFPGA 2009 is a Mini-Symposium on parallel computing with field programmable gate arrays (FPGAs), held in conjunction with the ParCo conference on parallel computing. FPGAs allow to map an algorithm directly onto the hardware, optimize the architecture for parallel execution, and dynamically reconfigure the system in between different phases of the computation. Compared to e.g. Cell processors, GPGPU's (general-purpose GPU's) and other high-performance devices, FPGAs are considered as flexible hardware in the sense that the building blocks of one or more single or multiple FPGAs can be inte
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Streszczenia konferencji na temat "Dynamic Cell Clustering (DCC)"

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Liu, Yi, and Bo Li. "User Mobility-Based Dynamic Clustering Algorithm for Cell-Free Massive MIMO Systems." In 2024 7th International Conference on Electronics Technology (ICET). IEEE, 2024. http://dx.doi.org/10.1109/icet61945.2024.10672692.

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Audivet Durán, Cinthia, and Marco E. Sanjuán. "On-Line Early Fault Detection of a Centrifugal Chiller Based on Data Driven Approach." In ASME 2016 10th International Conference on Energy Sustainability collocated with the ASME 2016 Power Conference and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/es2016-59291.

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A district cooling system (DCS) is a system that distributes thermal energy through chilled water from a central source to residential, commercial, or industrial consumers, designated to air conditioning purposes. It is one of the most important part of a heating, ventilation, air conditioning and refrigeration systems (HVAC), because a DCS is composed of: Cooling towers, central chiller plant, water distribution systems and clusters of consumer buildings. This research is focused on the central chiller plant, due to it accounts for a substantial portion of the total energy consume of DCS and
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Savazzi, Pietro, and Lorenzo Favalli. "Dynamic Cell Sectorization Using Clustering Algorithms." In 2007 IEEE 65th Vehicular Technology Conference. IEEE, 2007. http://dx.doi.org/10.1109/vetecs.2007.135.

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Zimmermann, Hans-martin, Alexander Seitz, and Ruediger Halfmann. "Dynamic Cell Clustering in Cellular Multi-Hop Networks." In 2006 10th IEEE Singapore International Conference on Communication Systems. IEEE, 2006. http://dx.doi.org/10.1109/iccs.2006.301458.

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Huan Sun, Xiaobo Zhang, and Wei Fang. "Dynamic cell clustering design for realistic coordinated multipoint downlink transmission." In 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC 2011). IEEE, 2011. http://dx.doi.org/10.1109/pimrc.2011.6139718.

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Samarakoon, Sumudu, Mehdi Bennis, Walid Saad, and Matti Latva-aho. "Dynamic clustering and sleep mode strategies for small cell networks." In 2014 11th International Symposium on Wireless Communications Systems (ISWCS). IEEE, 2014. http://dx.doi.org/10.1109/iswcs.2014.6933487.

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Wang, Xiaoyu, Shi Jin, Xiqi Gao, Wen Zhong, Guo Li, and Tianle Deng. "User Rate Evaluation of Dynamic Clustering in Homogeneous Small Cell Networks." In 2013 IEEE 78th Vehicular Technology Conference (VTC Fall). IEEE, 2013. http://dx.doi.org/10.1109/vtcfall.2013.6692452.

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Dai, Wei, Siyuan Yang, Mondher Bouazizi, and Tomoaki Ohtsuki. "K-Means Clustering-Aided Dynamic Multi-Cell Optimization Algorithm for HAPS." In GLOBECOM 2023 - 2023 IEEE Global Communications Conference. IEEE, 2023. http://dx.doi.org/10.1109/globecom54140.2023.10437302.

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Yan, Yan, Kai Niu, Ping Gong, and Zhiqiang He. "Base station energy saving based on dynamic programming combined with cell clustering." In 2013 IEEE 5th International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications (MAPE). IEEE, 2013. http://dx.doi.org/10.1109/mape.2013.6689966.

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Dghais, Wael, Malek Souilem, Hao Ran Chi, Ayman Radwan, and Abd-Elhamid M. Taha. "Dynamic Clustering for Power Effective Small Cell Deployment in HetNet 5G Networks." In ICC 2020 - 2020 IEEE International Conference on Communications (ICC). IEEE, 2020. http://dx.doi.org/10.1109/icc40277.2020.9149059.

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