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Artykuły w czasopismach na temat „Co-Occurence network”

Autor: Grafiati

Data publikacji: 28 września 2024

Data aktualizacji: 31 lipca 2025

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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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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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Dong, Ziqi, Furong Tian, Hua Yang, Tao Sun, Wenchuan Zhang, and Dan Ruan. "A Framework with Elaborate Feature Engineering for Matching Face Trajectory and Mobile Phone Trajectory." Electronics 12, no. 6 (2023): 1372. http://dx.doi.org/10.3390/electronics12061372.

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The advances in positioning techniques have generated massive trajectory data that represent the mobility of objects, e.g., pedestrians and mobile phones. It is important to integrate information from various modalities for subject tracking or trajectory prediction. Our work attempts to match a face with a corresponding mobile phone based on the heterogeneous trajectories. We propose a framework which associates face trajectories with their corresponding mobile phone trajectories using elaborate and explainable features. Our solution includes two stages: an initial selection of phone trajector

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Wang, Li, Tao Yu, Yaxin Zhu, et al. "Amplicon-based sequencing and co-occurence network analysis reveals notable differences of microbial community structure in healthy and dandruff scalps." BMC Genomics 23, no. 1 (2022). http://dx.doi.org/10.1186/s12864-022-08534-4.

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Abstract Background Dandruff is a chronic, recurring, and common scalp problem that is caused by several etiopathogeneses with complex mechanisms. Management of this condition is typically achieved via antifungal therapies. However, the precise roles played by microbiota in the development of the condition have not been elucidated. Despite their omnipresence on human scalp little is known about the co-occurrence/co-exclusion network of cutaneous microbiota. Results We characterized the scalp and hair surface bacterial and fungal communities of 95 dandruff-afflicted and healthy individuals resi

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MELEU, Ghislain Romaric, and Paulin MELATAGIA YONTA. "Growth model for collaboration networks." Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées Volume 24 - 2017 - Special... (February 16, 2017). http://dx.doi.org/10.46298/arima.1447.

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We propose a model of growing networks based on cliques formations. A clique is used to illustrate for example co-authorship in co-publication networks, co-occurence of words or collaboration between actors of the same movie. Our model is iterative and at each step, a clique of λη existing vertices and (1 − λ)η new vertices is created and added in the network; η is the mean number of vertices per clique and λ is the proportion of old vertices per clique. The old vertices are selected according to preferential attachment. We show that the degree distribution of the generated networks follows th

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Sferrazza, Paolo. "Archaeological and Experimental Lithic Microwear Classification Through 2D Textural Analysis and Machine Learning." Journal of Archaeological Method and Theory 32, no. 1 (2025). https://doi.org/10.1007/s10816-025-09701-z.

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Abstract The paper focuses on introducing 2D texture analysis as a quantitative method for functional analysis in archaeology. The paper aims to demonstrate the validity of this method for quantifying use-wear analysis and to evaluate different processing, extraction, and classification techniques. The method presented relies on five techniques of quantitative feature extraction from photographic images and nine classification techniques through machine learning algorithms. After creating a training dataset with experimental traces, machine learning models were validated through experimental a

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Peng, Jacqueline, Yunyun Zhou, and Kai Wang. "Multiplex gene and phenotype network to characterize shared genetic pathways of epilepsy and autism." Scientific Reports 11, no. 1 (2021). http://dx.doi.org/10.1038/s41598-020-78654-y.

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AbstractIt is well established that epilepsy and autism spectrum disorder (ASD) commonly co-occur; however, the underlying biological mechanisms of the co-occurence from their genetic susceptibility are not well understood. Our aim in this study is to characterize genetic modules of subgroups of epilepsy and autism genes that have similar phenotypic manifestations and biological functions. We first integrate a large number of expert-compiled and well-established epilepsy- and ASD-associated genes in a multiplex network, where one layer is connected through protein–protein interaction (PPI) and

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Zhang, Haolong, Yaxin Mo, Ling Wang, et al. "Potential shared pathogenic mechanisms between endometriosis and inflammatory bowel disease indicate a strong initial effect of immune factors." Frontiers in Immunology 15 (April 3, 2024). http://dx.doi.org/10.3389/fimmu.2024.1339647.

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IntroductionOver the past decades, immune dysregulation has been consistently demonstrated being common charactoristics of endometriosis (EM) and Inflammatory Bowel Disease (IBD) in numerous studies. However, the underlying pathological mechanisms remain unknown. In this study, bioinformatics techniques were used to screen large-scale gene expression data for plausible correlations at the molecular level in order to identify common pathogenic pathways between EM and IBD.MethodsBased on the EM transcriptomic datasets GSE7305 and GSE23339, as well as the IBD transcriptomic datasets GSE87466 and

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Pettersen, Jakob Peder, Madeleine S. Gundersen, and Eivind Almaas. "Robust bacterial co-occurence community structures are independent of r- and K-selection history." Scientific Reports 11, no. 1 (2021). http://dx.doi.org/10.1038/s41598-021-03018-z.

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AbstractSelection for bacteria which are K-strategists instead of r-strategists has been shown to improve fish health and survival in aquaculture. We considered an experiment where microcosms were inoculated with natural seawater and the selection regime was switched from K-selection (by continuous feeding) to r-selection (by pulse feeding) and vice versa. We found the networks of significant co-occurrences to contain clusters of taxonomically related bacteria having positive associations. Comparing this with the time dynamics, we found that the clusters most likely were results of similar nic

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