Results 101 to 110 of about 15,127 (194)

Enhancing ESG Insights Using Machine Learning: A Case Study of Top Performing Banks in Indonesia

Journal of Applied Informatics and Computing
This research related to the discover ESG practices by Top Performing Banks in Indonesia based on their Return on Asset (ROA) and Net Interest Margin (NIM). Due to the shifting the interest of the investor and the world condtion. Recently, investors have
Dean Tirkaamiana, Satrio Samudro Aji Basuki   +1 more
doaj   +1 more source

DBSCAN-MS: Distributed Density-Based Clustering in Metric Spaces

, 2019
DBSCAN is one of important density-based clustering methods, which has a wide range of applications in machine learning and data mining, to name but a few.
Rui Ma, Keyu Yang, Lu Chen, Gao, Yunjun, Chen, Gang, Chen, Lu, Wu, Sai, Sai Wu, Gang Chen, Yang, Keyu, Yunjun Gao, Ma, Rui   +11 more
core   +1 more source

A guide to host genetic determinants of female microbiome composition across distinct anatomical niches

The FEBS Journal, EarlyView.
Host genetic variation in immune regulation and cell signalling genes was associated with microbiome composition across vaginal, gut, oral and skin sites, while associations involving metabolic function, epithelial barrier integrity and hormonal processes were more site‐specific. Overall, our findings indicate that host genetic variation contributes to
Isabella Margaret Davidson, Elham Nikbakht, Hayley O'Neill, Larisa Margaret Haupt, Paul Joseph Dunn   +4 more
wiley   +1 more source

A global perspective on the annual cycles of whimbrels

Ibis, EarlyView.
Comparative analyses are central to understanding broad‐scale patterns in avian ecology, yet their application is often constrained by fragmented and uneven data availability. Recent advances in tracking technology have generated unprecedented insights into shorebird movements, resulting in numerous studies on single populations or flyways.
Camilo Carneiro, Tómas G. Gunnarsson, Gary Allport, Philip W. Atkinson, Anne N. M. A. Ausems, Pierrick Bocher, Roeland Bom, Malo Braquier, Stephen C. Brown, Sayam U. Chowdhury, Paula Cimprich, Delip K. Das, Charlotte Francesiaz, Robert E. Gill, Diana J. Hamilton, Maina C. Handmaker, Shariful Islam, Audrey Jaeger, Frédéric Jiguet, Chrystyn Jones, Emmanuel Joyeux, Jeffrey F. Kelly, Alan H. Kneidel, Fenliang Kuang, Chris Latty, Mathieu Le Corre, David Li, Rebeca C. Linhart, Ádám Lovas‐Kiss, Zhijun Ma, Scott McWilliams, Verónica Méndez, Jason Mobley, Samuel NG, Joshua Nightingale, Erica Nol, Julie Paquet, Theunis Piersma, Marie Pitts, Rivo Rabarisoa, Florinah Razafimandimby, Daniel R. Ruthrauff, Felicia Sanders, Shiloh Schulte, Philipp Schwemmer, Nathan R. Senner, Böðvar Þórisson, Lee Tibbitts, Nils Warnock, Bryan Watts, Brad Winn, Samantha J. Wolfe, Shufen Yang, José A. Alves   +53 more
wiley   +1 more source

CDBSCAN:Cloud Based DBSCAN Clustering Algorithm

, 2013
DBSCAN是一個頗負盛名的密度分群演算法，它的特色是可以在充滿雜訊的環境中找到具有任意形狀的群體。然而當資料的規模愈來愈大時，因為單一的電腦很難在效能上有所提升，DBSCAN無法有效率地處理這大量的資料。雲端運算在近期逐漸發長成熟，他可以幫助我們處理傳統演算法在面對大量資料時效率不佳的問題。 在這篇論文裡，我們提出了CDBSCAN演算法，CDBSCAN代表以雲端(Cloud)為基礎的DBSCAN演算法，它是一個分散式版本的DBSCAN演算法，並且被實施在一個雲端的平台上─Hadoop。我們利用Map ...
Chen, Tze-Yu, 陳則諭
core  

Unsupervised Global CBC/RUO/CPD Phenotyping Identifies Haematological Clusters Enriched for Thrombocytopenia Severity and Mechanisms

International Journal of Laboratory Hematology, EarlyView.
ABSTRACT Introduction Thrombocytopenia has heterogeneous mechanisms, including peripheral destruction, consumption, and reduced marrow production. This study developed an unsupervised global complete blood count/research‐use‐only/cell population data (CBC/RUO/CPD) phenotyping model and evaluated post hoc whether thrombocytopenia severity and clinically
Mohammad A. Altememi, Emmanuel J. Favaloro, Md Zahidul Islam, Sara Ng, Danny Hsu, Abishek B. Santhakumar   +5 more
wiley   +1 more source

MR-DBSCAN: a scalable MapReduce-based DBSCAN algorithm for heavily skewed data

, 2014
DBSCAN (density-based spatial clustering of applications with noise) is an important spatial clustering technique that is widely adopted in numerous applications.
Wuman Luo, Jianping Fan, Luo, Wuman, Fan, Jianping, Tan, Haoyu, Yaobin He, Shengzhong Feng, Haoyu Tan, He, Yaobin, Feng, Shengzhong   +9 more
core   +1 more source

Toward a deeper understanding of recovery trajectories in forest ecosystem restoration: a machine learning approach

Restoration Ecology, EarlyView.
Abstract Introduction The lack of integrated monitoring approaches and indicators hampers the understanding of forest restoration trajectories, as the recovery process involves multiple aspects of the ecosystem, which can respond differently to environmental changes due to their interactions and synergies.
Jenny Vivian, Robin L. Chazdon, Alison Shapcott, David J. Lee   +3 more
wiley   +1 more source

Implementation of K-Nearest Neighbor Algorithm on Density-Based Spatial Clustering Application with Noise Method on Stunting Clustering

Jurnal Diferensial
This paper studies the implementation of the K-Nearest Neighbor (KNN) algorithm on Density-Based Spatial Clustering Application with Noise (DBSCAN) method on stunting Clustering in the eastern region of Indonesia in 2022.
Friansyah Gani, Hasan S. Panigoro, Sri Lestari Mahmud, Emli Rahmi, Salmun K. Nasib, La Ode Nashar   +5 more
doaj   +1 more source

Noise‐induced reduction and early recovery of superior paraolivary nucleus sound‐offset responses

The Journal of Physiology, EarlyView.
Abstract figure legend Acoustic over‐exposure transiently disrupts auditory temporal processing in mouse superior paraolivary nucleus neurons. In control conditions, neurons exhibit robust sound‐offset (OFF) responses, which are abolished immediately following noise trauma, indicating impaired temporal encoding.
Mihai Stancu, Ezhilarasan Rajaram, Joseph A. Kroeger, Benedikt Grothe, Conny Kopp‐Scheinpflug   +4 more
wiley   +1 more source