Search alternatives:
like » life (Expand Search)
selection » detection (Expand Search)
Showing 1 - 20 results of 889 for search 'distributed like selection', query time: 0.15s Refine Results
  1. 1

    Model Selection Approach for Distributed Fault Detection in Wireless Sensor Networks by Mrinal Nandi, Anup Dewanji, Bimal Roy, Santanu Sarkar

    Published 2014-01-01
    “…We develop schemes under the model selection procedure and multiple model selection procedure and use the concept of Bayesian model averaging to identify a set of likely fault sensors and obtain an average predictive error.…”
    Get full text
    Article
  2. 2

    An Intelligent Distributed Channel Selection Framework with Hybrid Mode Selection for Interference Mitigation in D2D based 5G Networks by Abdullilah A. Alotaibi, Salman A. AlQahtani

    Published 2024-10-01
    “…In this paper, an intelligent distributed channel selection framework (IDCSF) in D2D communication for 5G networks with hybrid selection modes of D2D is proposed to help DUs select the best channel for transmission to mitigate interference. …”
    Get full text
    Article
  3. 3
  4. 4
  5. 5

    Probabilistic inference and Bayesian‐like estimation in animals: Empirical evidence by Thomas J. Valone

    Published 2024-07-01
    “…I examine three aspects of empirical work that shed light on the idea that animals can make such decisions in a Bayesian‐like manner. First, many animals are sensitive to variance differences in behavioral options, one metric used to characterize frequency distributions. …”
    Get full text
    Article
  6. 6
  7. 7
  8. 8

    Experimental study on smoke temperature distribution and thermal-driven propagation in groove-like spaces under different fan arrangements by Sinian Gu, Houyang Liu, Yang Wang, Zhichao Yu, Yunji Gao

    Published 2025-05-01
    “…In order to explore the fire smoke temperature and propagation characteristics of the groove space under the overpass considering different fan spacing arrangements, a series of gas fire experiments were carried out in the reduced fire experiment platform of groove-like space. Three fire source powers and four fan arrangement conditions are selected. …”
    Get full text
    Article
  9. 9

    Patterns of genetic diversity in five species of Passeriformes co-distributed in an environmental gradient by Marcela Restrepo-Arias, Héctor F. Rivera-Gutiérrez, Iván Darío Soto-Calderón, Ernesto Pérez-Collazos, Catalina González-Quevedo

    Published 2025-09-01
    “…Both species' distribution ranges and environmental gradients can influence this diversity through mechanisms such as gene flow, selection, and genetic drift. …”
    Get full text
    Article
  10. 10

    Distributions of non‐native and native plants are not determined by the same environmental factors by Bart Steen, Antoine Adde, Martin A. Schlaepfer, Antoine Guisan, Luigi Maiorano

    Published 2024-10-01
    “…In the framework of correlative species distribution models, we used newly developed methods for efficient automated selection of a parsimonious number of predictor environmental variables to determine which ones, out of a large candidate set in eight classes, have the strongest explanatory power for both species groups. …”
    Get full text
    Article
  11. 11

    Efficient Distributed Denial of Service Attack Detection in Internet of Vehicles Using Gini Index Feature Selection and Federated Learning by Muhammad Dilshad, Madiha Haider Syed, Semeen Rehman

    Published 2025-01-01
    “…Considering that smart vehicles are becoming interconnected through the Internet of Vehicles, cybersecurity threats like Distributed Denial of Service (DDoS) attacks pose a great challenge. …”
    Get full text
    Article
  12. 12

    The TEDDY Framework: An Efficient Framework for Target Tracking Using Edge-Based Distributed Smart Cameras with Dynamic Camera Selection by Jaemin Yang, Jongwoo Lee, Ilju Lee, Yaesop Lee

    Published 2025-03-01
    “…The proposed framework employs context-aware dynamic camera selection, activating only the cameras most likely to detect the target based on its predicted trajectory. …”
    Get full text
    Article
  13. 13

    RecompGPT: Generative Pre-Trained Transformers-Assisted Interactive Human Gaze Pattern Learning and Distribution Modeling for Scene Recomposition by Wang Shang, Nassiriah Binti Shaari, Nur Sauri Bin Yahaya, Liu Hao

    Published 2025-01-01
    “…LOAL is an active-learning algorithm that selects multiple representative patches from each scene image. …”
    Get full text
    Article
  14. 14
  15. 15

    Tissue Distribution and Proliferation Characteristics of pVA1-like Plasmid After Infection with Vibrio parahaemolyticus in the Pacific White Shrimp Penaeus vannamei by Xingqi SU, Qiang FU, Xupeng LI, Jie KONG, Jiteng TIAN, Baoxiang CAO, Ning LIU, Sheng LUAN, Kun LUO, Xianhong MENG

    Published 2025-06-01
    “…Through quantitative oral infection using RT-qPCR and other techniques, P. vannamei were infected with VpAHPND in low inoculum groups (4.76×105 CFU/tail, 1.76×105 CFU/tail) (L group) and high inoculum groups (3.84×107 CFU/tail, 1.68×107 CFU/tail) (H group) at five different time points (3, 6, 9, 24, and 48 h) across nine different tissues (gill, stomach, intestine, eyestalk, muscle, hepatopancreas, fifth pleopod, abdominal nerve, and second antennae flagellum), studying the distribution and changes of PirAVp copy numbers. The amount of pVA1-like plasmid carried by V. parahaemolyticus was determined by the gene expression of the virulence protein PirAVp, which in turn represented the distribution and change characteristics of V. parahaemolyticus. …”
    Get full text
    Article
  16. 16

    Clinical, immunological and ethical aspects of selecting a recipient for cadaver kidney transplantation by V. A. Vatazin, A. B. Zulkarnaev, V. A. Stepanov

    Published 2020-04-01
    “…The quality of donor organ and unconditional priority on highly sensitized candidates are the conceptual fundamental principles of organ distribution in the US and Europe. Under donor kidney shortage, selecting a recipient is always competitive. …”
    Get full text
    Article
  17. 17
  18. 18
  19. 19
  20. 20