Bibliografie tematiche / Co-Occurence network

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Letteratura scientifica selezionata sul tema "Co-Occurence network"

Autore: Grafiati
Pubblicato: 28 settembre 2024
Ultima modifica: 19 luglio 2025

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Articoli di riviste sul tema "Co-Occurence network"

1

Ilhwan Kim and 정유진. "Co-occurence Word Network and Trends of the Concerns Surrounding Social Class." Journal of Korealex ll, no. 18 (2011): 7–40. http://dx.doi.org/10.33641/kolex.2011..18.7.

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Li, Wei, Haozhou Zhou, Zhenyuan Lu, and Sagar Kamarthi. "Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis." Sensors 24, no. 4 (2024): 1202. http://dx.doi.org/10.3390/s24041202.

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Abstract (sommario):
Digital twin technology has become increasingly popular and has revolutionized data integration and system modeling across various industries, such as manufacturing, energy, and healthcare. This study aims to explore the evolving research landscape of digital twins using Keyword Co-occurrence Network (KCN) analysis. We analyze metadata from 9639 peer-reviewed articles published between 2000 and 2023. The results unfold in two parts. The first part examines trends and keyword interconnection over time, and the second part maps sensing technology keywords to six application areas. This study rev
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Ilmi, Nurul, and Alva Nurvina Sularso. "SYSTEM LITERATURE REVIEW: IDENTIFIKASI PENYAKIT BERDASARKAN IRIDOLOGI." Journal of Informatics and Communication Technology (JICT) 5, no. 1 (2023): 139–48. http://dx.doi.org/10.52661/j_ict.v5i1.192.

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Identifikasi penyakit berdasarkan iridologi dengan metode terbaik sangat dinantikan para ahli sehingga dapat menjadi kemajuan dalam diagnosis medis. Untuk itu penting menghasilkan sistem yang akurat untuk identifikasi penyakit berdasarkan iridologi. Sistem yang akurat diperlukan metode terbaik yang menghasilkan akurasi yang tinggi. Maka dalam tulisan ini dilakukan tinjauan pustaka sistematis/ systematic literature review (slr) untuk menganalisis metode yang digunakan dalam setiap tahap identifikasi penyakit melalui citra iris mata. Hasilnya didapatkan metode Gray Level Co-Occurence Matrix (GLC
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Nugroho, Kuntoro Adi, and Yudi Eko Windarto. "Analyzing Depthwise Convolution Based Neural Network: Study Case in Ship Detection and Land Cover Classification." Jurnal Ilmu Komputer dan Informasi 12, no. 2 (2019): 103. http://dx.doi.org/10.21609/jiki.v12i2.752.

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Various methods are available to perform feature extraction on satellite images. Among the available alternatives, deep convolutional neural network (ConvNet) is the state of the art method. Although previous studies have reported successful attempts on developing and implementing ConvNet on remote sensing application, several issues are not well explored, such as the use of depthwise convolution, final pooling layer size, and comparison between grayscale and RGB settings. The objective of this study is to perform analysis to address these issues. Two feature learning algorithms were proposed,
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Malacrinò, Antonino, Saveria Mosca, Maria Giulia Li Destri Nicosia, Giovanni E. Agosteo, and Leonardo Schena. "Plant Genotype Shapes the Bacterial Microbiome of Fruits, Leaves, and Soil in Olive Plants." Plants 11, no. 5 (2022): 613. http://dx.doi.org/10.3390/plants11050613.

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The plant microbiome plays an important role in plant biology, ecology, and evolution. While recent technological developments enabled the characterization of plant-associated microbiota, we still know little about the impact of different biotic and abiotic factors on the diversity and structures of these microbial communities. Here, we characterized the structure of bacterial microbiomes of fruits, leaves, and soil collected from two olive genotypes (Sinopolese and Ottobratica), testing the hypothesis that plant genotype would impact each compartment with a different magnitude. Results show t
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Ouvrard, X., J. M. Le Goff, and S. Marchand-Maillet. "Hypergraph Modeling and Visualisation of Complex Co-occurence Networks." Electronic Notes in Discrete Mathematics 70 (December 2018): 65–70. http://dx.doi.org/10.1016/j.endm.2018.11.011.

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Haake, Scott, Jared Brewer, Alex Nesta, Joseph Vento, Kathryn Beckermann, and Anupama Reddy. "Spatial proteomics enables identification of prognostic biomarkers in papillary renal cell carcinoma." Oncologist 28, Supplement_1 (2023): S2—S3. http://dx.doi.org/10.1093/oncolo/oyad216.005.

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Abstract Background Papillary renal cell carcinoma (PRCC) is the second most common adult kidney cancer histology, constituting 15-20% of cases. While some patients may have indolent PRCC tumors that grow slowly, other tumors rapidly metastasize. Some PRCC tumors respond to immune checkpoint inhibitors. Thus, understanding the immune tumor microenvironment and how it correlates with patient outcomes in this relatively rare disease is a critical need. Spatial interrogation of patient samples has the potential to offer novel insights into the tumor-immune axis and provide avenues for enhanced di
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Baune, *Bernhard T. "NEW DEVELOPMENTS IN THE MULTI-OMICS PREDICTION OF TREATMENT RESPONSE PREDICTION IN PSYCHIATRY." International Journal of Neuropsychopharmacology 28, Supplement_1 (2025): i49—i50. https://doi.org/10.1093/ijnp/pyae059.087.

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Abstract The role of pharmacogenomics is to create an effective therapeutic strategy based on the genomic profile of a patient in order to improve response as well as remission and in particular to reduce relapse. To date, in the psychiatric field, although genomic studies on psychotropic medications have provided important insights into the molecular components involved in clinical outcomes, unfortunately findings have not identified biomarkers with a clear clinical utility (1). Studies using pharmacogenomics and pharmacotranscriptomic approaches, focusing on genetic variants and expression l
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Widyaswari, Meidyta Sinantryana, Iis Noventi, and 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, no. 2 (2019): 68. http://dx.doi.org/10.20473/bhsj.v2i2.15007.

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Introduction: Black cumin (Nigella sativa) is widely used to treat various diseases. It is also believed to relief skin conditions accompanied by itching symptom, such as atopic dermatitis (AD) or eczema. However, the anti-eczema mechanism of action is still unclear. The aims of this syudy was to identify anti-eczema mechanism of action of N. sativa for AD using computer aided prediction and pathway analysis based on protein-chemical networks. Methods: We utilized dataset consisting chemical compounds of N. sativa from KNApSAcK. It is a comprehensive species-metabolite relationship database. U
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Donges, J. F., R. V. Donner, N. Marwan, S. F. M. Breitenbach, K. Rehfeld, and J. Kurths. "Nonlinear regime shifts in Holocene Asian monsoon variability: potential impacts on cultural change and migratory patterns." Climate of the Past Discussions 10, no. 2 (2014): 895–975. http://dx.doi.org/10.5194/cpd-10-895-2014.

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Abstract. The Asian monsoon system has been recognised as an important tipping element in Earth's climate. In this work, we apply recurrence networks, a recently developed technique for nonlinear time series analysis of palaeoclimate data, for detecting episodes with pronounced changes in Asian monsoon dynamics during the last 10 ka in speleothem records from 10 caves covering the major branches of the Asian monsoon system. Our methodology includes multiple archives, explicit consideration of dating uncertainties with the COPRA approach and rigorous significance testing for the coexistence of
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Più fonti

Tesi sul tema "Co-Occurence network"

1

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.

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La diversité, la composition et les assemblages du microbiome du sol et des plantes sont conditionnés en partie par l’environnement et les interactions biotiques. L’oasis d’AlUla, située dans le désert d’Arabie Saoudite, est caractérisé par de fortes contraintes abiotiques, liées à un pH hyper alcalin et à la faible disponibilité en eau et en nutriments. L’activité et la croissance des organismes est donc soumise à cette disponibilité ponctuelle et spatialement hétérogène des ressources. En résulte une répartition spatiale discontinue des végétaux, les îlots de fertilité, qui influencent la co
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2

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.

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Atti di convegni sul tema "Co-Occurence network"

1

Sri Kusuma Aditya, Christian, Mamluatul Hani'ah, Rizqa Raaiqa Bintana, and 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.

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Virmani, Jitendra, Vinod Kumar, Naveen Kalra, and 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.

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