Auswahl der wissenschaftlichen Literatur zum Thema „Co-Occurence network“
Geben Sie eine Quelle nach APA, MLA, Chicago, Harvard und anderen Zitierweisen an
Inhaltsverzeichnis
Machen Sie sich mit den Listen der aktuellen Artikel, Bücher, Dissertationen, Berichten und anderer wissenschaftlichen Quellen zum Thema "Co-Occurence network" bekannt.
Neben jedem Werk im Literaturverzeichnis ist die Option "Zur Bibliographie hinzufügen" verfügbar. Nutzen Sie sie, wird Ihre bibliographische Angabe des gewählten Werkes nach der nötigen Zitierweise (APA, MLA, Harvard, Chicago, Vancouver usw.) automatisch gestaltet.
Sie können auch den vollen Text der wissenschaftlichen Publikation im PDF-Format herunterladen und eine Online-Annotation der Arbeit lesen, wenn die relevanten Parameter in den Metadaten verfügbar sind.
Zeitschriftenartikel zum Thema "Co-Occurence network"
Ilhwan Kim und 정유진. „Co-occurence Word Network and Trends of the Concerns Surrounding Social Class“. Journal of Korealex ll, Nr. 18 (Oktober 2011): 7–40. http://dx.doi.org/10.33641/kolex.2011..18.7.
Der volle Inhalt der QuelleLi, Wei, Haozhou Zhou, Zhenyuan Lu und Sagar Kamarthi. „Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis“. Sensors 24, Nr. 4 (12.02.2024): 1202. http://dx.doi.org/10.3390/s24041202.
Der volle Inhalt der QuelleIlmi, Nurul, und Alva Nurvina Sularso. „SYSTEM LITERATURE REVIEW: IDENTIFIKASI PENYAKIT BERDASARKAN IRIDOLOGI“. Journal of Informatics and Communication Technology (JICT) 5, Nr. 1 (09.12.2023): 139–48. http://dx.doi.org/10.52661/j_ict.v5i1.192.
Der volle Inhalt der QuelleNugroho, Kuntoro Adi, und Yudi Eko Windarto. „Analyzing Depthwise Convolution Based Neural Network: Study Case in Ship Detection and Land Cover Classification“. Jurnal Ilmu Komputer dan Informasi 12, Nr. 2 (08.07.2019): 103. http://dx.doi.org/10.21609/jiki.v12i2.752.
Der volle Inhalt der QuelleMalacrinò, Antonino, Saveria Mosca, Maria Giulia Li Destri Nicosia, Giovanni E. Agosteo und Leonardo Schena. „Plant Genotype Shapes the Bacterial Microbiome of Fruits, Leaves, and Soil in Olive Plants“. Plants 11, Nr. 5 (24.02.2022): 613. http://dx.doi.org/10.3390/plants11050613.
Der volle Inhalt der QuelleOuvrard, X., J. M. Le Goff und S. Marchand-Maillet. „Hypergraph Modeling and Visualisation of Complex Co-occurence Networks“. Electronic Notes in Discrete Mathematics 70 (Dezember 2018): 65–70. http://dx.doi.org/10.1016/j.endm.2018.11.011.
Der volle Inhalt der QuelleHaake, Scott, Jared Brewer, Alex Nesta, Joseph Vento, Kathryn Beckermann und Anupama Reddy. „Spatial proteomics enables identification of prognostic biomarkers in papillary renal cell carcinoma“. Oncologist 28, Supplement_1 (23.08.2023): S2—S3. http://dx.doi.org/10.1093/oncolo/oyad216.005.
Der volle Inhalt der QuelleWidyaswari, Meidyta Sinantryana, Iis Noventi und Herdiantri Supriyana. „Anti-eczema Mechanism of Action of Nigella sativa for Atopic Dermatitis: Computer-aided Prediction and Pathway Analysis Based on Protein-chemical Interaction Networks“. Biomolecular and Health Science Journal 2, Nr. 2 (31.10.2019): 68. http://dx.doi.org/10.20473/bhsj.v2i2.15007.
Der volle Inhalt der QuelleDonges, J. F., R. V. Donner, N. Marwan, S. F. M. Breitenbach, K. Rehfeld und J. Kurths. „Nonlinear regime shifts in Holocene Asian monsoon variability: potential impacts on cultural change and migratory patterns“. Climate of the Past Discussions 10, Nr. 2 (06.03.2014): 895–975. http://dx.doi.org/10.5194/cpd-10-895-2014.
Der volle Inhalt der QuelleDong, Ziqi, Furong Tian, Hua Yang, Tao Sun, Wenchuan Zhang und Dan Ruan. „A Framework with Elaborate Feature Engineering for Matching Face Trajectory and Mobile Phone Trajectory“. Electronics 12, Nr. 6 (13.03.2023): 1372. http://dx.doi.org/10.3390/electronics12061372.
Der volle Inhalt der QuelleDissertationen zum Thema "Co-Occurence network"
Maurice, Kenji. „Structuration des communautés et des réseaux microbiens des sols et des plantes dans un écosystème aride“. Electronic Thesis or Diss., Université de Montpellier (2022-....), 2024. http://www.theses.fr/2024UMONG006.
Der volle Inhalt der QuelleThe diversity, composition and assemblages of the soil and plant microbiome are partly determined by the environment and biotic interactions. The AlUla oasis, located in the Saudi Arabian desert, is characterized by strong abiotic constraints, linked to a hyper-alkaline pH and low availability of water and nutrients. The activity and growth of organisms is therefore subject to this punctual and spatially heterogeneous availability of resources. This leads to a spatially discontinuous distribution of plants, known as islands of fertility, which influence soil composition and microbial communities. Plants also form symbiotic relationships with microorganisms, which influence their health, resistance to drought and the acquisition of mineral and water resources, and are particularly critical in this ecosystem. Finally, these ecosystems, already weakened by climate change, are also subject to significant agricultural pressures, leading to soil degradation and associated biodiversity loss. Little is known at present about the biodiversity of hot, arid ecosystems, particularly in Saudi Arabia, a country whose borders have long remained closed.The goal of this thesis is to characterize the bacterial and fungal microbiome of soil and plants in relation to its environment, and its response to different land uses through amplicon sequencing. In order to extend the analytical framework of the study of community diversity and composition, I have sought to use co-occurrence network metrics and explore new methodologies for their study. In a first chapter, the mutual influence of plants, soil and microorganisms in a micro-environment, the fertility islands, is characterized. Then, a field sampling campaign over two seasons enabled me to carry out an extensive analysis of the plant microbiome using the co-occurrence network approach. Focusing on the intra- and inter-kingdom relationships of symbiotic taxa, this work demonstrated the redundant assortativity of mycorrhizal fungi, and the integration of nitrogen-fixing bacteria into the extended plant microbiome. The microbiome's response to a simulated precipitation event in the field was also used to characterize the microbiome's taxonomic response to water availability in the soil. In the third chapter, the microbiome's response to historical contingencies of an anthropogenic or natural nature, describes how cycles of desiccation and flooding affect contemporary microbial communities. By studying the stability of their interactions, it shows how past agricultural activities has had a lasting impact on the structure of the microbiome. Finally, the quantification of community assembly processes has made it possible to determine the effect of past disturbances on bacterial and fungal selection processes.Collectively, the results of this thesis improve our understanding of the assembly and structure of soil and plant microbiota in a little-known desert ecosystem. In addition, co-occurrence analyses have proven to be a valuable tool in the formulation of new fundamental hypotheses on the founding role of symbioses, and the response of the microbiota to disturbance. Continued study of the complex structure of networks, complemented by the exploration of microbial functions and reductionist approaches to be able to couple covariance relationships to ecological processes, promises major advances in microbial ecology in the future
Kale, Mehmet Cemil. „Multispectral co-occurence analysis for medical image processing“. The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1195500453.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Co-Occurence network"
Sri Kusuma Aditya, Christian, Mamluatul Hani'ah, Rizqa Raaiqa Bintana und Nanik Suciati. „Batik classification using neural network with gray level co-occurence matrix and statistical color feature extraction“. In 2015 International Conference on Information & Communication Technology and Systems (ICTS). IEEE, 2015. http://dx.doi.org/10.1109/icts.2015.7379892.
Der volle Inhalt der QuelleVirmani, Jitendra, Vinod Kumar, Naveen Kalra und Niranjan Khandelwal. „Prediction of Cirrhosis Based on Singular Value Decomposition of Gray Level Co-occurence Marix and aNneural Network Classifier“. In 2011 Developments in E-systems Engineering (DeSE). IEEE, 2011. http://dx.doi.org/10.1109/dese.2011.56.
Der volle Inhalt der Quelle