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Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

Daniel J Klionsky, Kotb Abdelmohsen, Akihisa Abe, Md Joynal Abedin, Hagai Abeliovich, Abraham Acevedo Arozena, Hiroaki Adachi, Christopher M Adams, Peter D Adams, Khosrow Adeli, Peter J Adhihetty, Sharon G Adler (+2455 others)
2016 Autophagy  
of Neuroscience, National Center of Neurology and Psychiatry, Department of Degenerative Neurological Diseases, Tokyo, Japan; 838 National Institute of Technology Rourkela, Department of Life Science  ...  Gastoenterology, Laboratory of Experimental Immunopathology, Castellana Grotte (BA), Italy; 836 National Institute of Infectious Diseases, Department of Bacteriology I, Tokyo, Japan; 837 National Institute  ...  Analysis of lysosomal association of fluorescent artificial CMA substrates.  ... 
doi:10.1080/15548627.2015.1100356 pmid:26799652 pmcid:PMC4835977 fatcat:bjaignwjiffyrjnz4r73rnkari

Ethical Issues in Public Health * *This case report is largely derived and modified from Tulchinsky T.H., Varavikova E.A., The new public health, 3rd edition. Academic Press/Elsevier: San Diego, 2014, chapter 15 pages 804–816 [chapter]

Theodore H. Tulchinsky
2018 Case Studies in Public Health  
à This case report is largely derived and modified from Tulchinsky T.H., Varavikova E.A., The new public health, 3rd edition. Academic Press/Elsevier: San Diego, 2014, chapter 15 pages 804À816.  ...  The dangers of ethical lapses are overwhelmingly apparent in the case of the Eugenics movement of the early 20 th century which metamorphosed from forced sterilizations in many liberal democratic countries  ...  The new public health, 3rd edition, San Diego, CA; Academic Press/Elsevier, 2014. Chapter 15, page 807.  ... 
doi:10.1016/b978-0-12-804571-8.00027-5 fatcat:6lokqn4pxbf4tirb7xzvdy54we

FRAMA 1.0: Framework for Moving Average Operators Calculation in Data Analysis

Bernabe Ortega-Tenezaca, Humbert Gonzalez-Diaz, Viviana Quevedo-Tumailli
2017 Proceedings of MOL2NET 2017, International Conference on Multidisciplinary Sciences, 3rd edition   unpublished
Speck-Planche and Cordeiro have also used this kind of models in multiple problems (8-11).  ...  From the obtained result a percentage sample of data is taken with a random contrast on which Machine Learning algorithms are applied  ...  We use both Linear Discriminant Analysis (LDA) and Artificial Neural Network (ANN) algorithms to seek alternative linear and non-linear models (50).  ... 
doi:10.3390/mol2net-03-05044 fatcat:rvne3eb37bdzpk75sttolss5cy

The Comparision of the Financial Failure with Artificial Neural Network and Logit Models

Ebru Caglayan Akay
2015 Pressacademia  
both artificial neural network and logit model results.  ...  The performances of artificial neural network and logit models have been compared by the analysis of the control set data and validity of these models.  ...  Graupe,Daniel (2007) "Prıncıples Of Artıfıcıal Neural Networks" 2nd Edition Advanced ). p = probability of an event happening 1-p= probability of an event not happening O O p + = 1 Logit  ... 
doi:10.17261/pressacademia.2015313060 fatcat:2gjigqeznzdrbmsg4xawvwlsdi

Comparative Analysis of Various Classification Algorithms in the Case of Fraud Detection

Ankur Rohilla
2017 International Journal of Engineering Research and  
In this paper we used three different classification algorithms (KNN, Neural network, C5.0) for fraud detection.  ...  In the case of credit card, fraudsters are the main intruder. These intruders can access some unauthorised transactions. It is very important to prevent your account transaction from these intruders.  ...  PROPOSED WORK Artificial neural network Artificial Neural Network functions similar as a human brain does. Human brain is a collection of neurons that are connected with each other.  ... 
doi:10.17577/ijertv6is090047 fatcat:u6luhleftvdxzeerayhi3bve6u

Sensor Network for the Monitoring of Ecosystem: Bird Species Recognition

Jinhai Cai, Dominic Ee, Binh Pham, Paul Roe, Jinglan Zhang
2007 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information  
Context neural network architecture was designed to embed the dynamic nature of bird songs into inputs.  ...  In this paper, we investigated the performance of bird species recognition using neural networks with different preprocessing methods and different sets of features.  ...  (t + p)}. (4) Neural Network: There are two kinds of time delay units in neural networks based on two principles.  ... 
doi:10.1109/issnip.2007.4496859 fatcat:amm3kiye4zaetcvvkorspgxjmq

Autonomous Design Of Modular Intelligent Systems

Pavel Nahodil, Jaroslav Vitku
2013 ECMS 2013 Proceedings edited by: Webjorn Rekdalsbakken, Robin T. Bye, Houxiang Zhang  
The principle of design is based on modified neuro-evolution and can be compared to modular neural networks.  ...  First, the design of simulator used is described, then the basic principle of hybrid networks is explained with it benefits and drawbacks. Finally, simple example is mentioned.  ...  ACKNOWLEDGEMENT This research has been funded by the Dept. of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague under SGS Project SGS12/146/OHK3/2T/13.  ... 
doi:10.7148/2013-0379 dblp:conf/ecms/NahodilV13 fatcat:gxrexsytlnattl6ryd65xwuxwa

Knowledge Development in Artificial Intelligence Use in Paediatrics

Peter Kokol, Helena Blažun Vošner, Jernej Završnik
2022 Knowledge  
The use of artificial intelligence in paediatrics has vastly increased in the last few years.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ...  rough sets" or ("decision tree*" and (induction or heuristic)) or "artificial neural network*" or "support vector machines" or "rough sets" or "deep learning" or "intelligent systems" or "artificial intelligence  ... 
doi:10.3390/knowledge2020011 fatcat:xabhwnnlm5akzfwaqa4jxoqew4

Page 3345 of Mathematical Reviews Vol. , Issue 98E [page]

1998 Mathematical Reviews  
neural networks (173-213); David S.  ...  ) or neural networks (base an optimization procedure on brain models with neuron transmitters).  ... 

Application of Artificial Neural Network Sensitivity Analysis to Identify Key Determinants of Harvesting Date and Yield of Soybean (Glycine max [L.] Merrill) Cultivar Augusta

Gniewko Niedbała, Danuta Kurasiak-Popowska, Magdalena Piekutowska, Tomasz Wojciechowski, Michał Kwiatek, Jerzy Nawracała
2022 Agriculture  
The aim of this study was to identify the key meteorological factors affecting the harvest date (model M_HARV) and yield of the soybean variety Augusta (model M_YIELD) using a neural network sensitivity  ...  It was revealed that the variables assigned ranks 1 and 2 in the sensitivity analysis of the neural network forming the M_HARV model were total rainfall in the first decade of June and the first decade  ...  It should be noted that artificial neural networks operate on a "black box" principle; that is, they do not provide complete information regarding the method of obtaining specific answers or detailed relations  ... 
doi:10.3390/agriculture12060754 fatcat:dfm6smybkbc35d2dj7wn7iukl4

Dew Point Temperature Estimation: Application of Artificial Intelligence Model Integrated with Nature-Inspired Optimization Algorithms

Sujay Naganna, Paresh Deka, Mohammad Ghorbani, Seyed Biazar, Nadhir Al-Ansari, Zaher Yaseen
2019 Water  
The current research investigated the hybridization of a multilayer perceptron (MLP) neural network with nature-inspired optimization algorithms (i.e., gravitational search (GSA) and firefly (FFA)) to  ...  The efficiencies of the proposed hybrid MLP networks (MLP–FFA and MLP–GSA) were authenticated against standard MLP tuned by a Levenberg–Marquardt back-propagation algorithm, extreme learning machine (ELM  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/w11040742 fatcat:js4t4fvlqnfm7f736nqhabwt3u

Autonomous learning of disparity–vergence behavior through distributed coding and population reward: Basic mechanisms and real-world conditioning on a robot stereo head

Agostino Gibaldi, Andrea Canessa, Fabio Solari, Silvio P. Sabatini
2015 Robotics and Autonomous Systems  
Sabatini A neural model for binocular vergence control without explicit calculation of disparity. European Symposium on Artificial Neural Networks, Bruges, Belgium, 22-24 April, 2009. [CI. 27] M.  ...  In the international scenario such an approach imposed itself through the (1) definition of specific Research Programs aimed to overcome the formal framework of artificial neural networks and to relate  ... 
doi:10.1016/j.robot.2015.01.002 fatcat:zffxmka6tnc2jibsibxrf3zkmu

Page 1455 of Linguistics and Language Behavior Abstracts: LLBA Vol. 28, Issue 3 [page]

1994 Linguistics and Language Behavior Abstracts: LLBA  
subject index school administrators’ perceptions, stutterers; questionnaire; 9406641 Readability artificial neural networks’ performance, readability analysis; 9404676 Christmann, U., Modelle der Textverarbeitung  ...  Grice’s cooperative principle/ maxims utility, manipulation recognition; 9404728 English for Business & Economics testing, cloze tests use; tests; uni- versity economics students, Spain; 9404573 English  ... 

A classification technique of group objects by artificial neural networks using estimation of entropy on synthetic aperture radar images

Anton V. Kvasnov, Vyacheslav P. Shkodyrev
2021 Journal of Sensors and Sensor Systems  
The paper shows that classification of the target for three classes able to predict with fair accuracy P=0,964 based on an artificial neural network.  ...  The entropy of target spots on SAR images revaluates depending on the altitude and aspect angle of a UAV.  ...  This paper was edited by Rosario Morello and reviewed by two anonymous referees.  ... 
doi:10.5194/jsss-10-127-2021 fatcat:ko7shaf4sjbnlh2bt6agdcrfxm

Complex Hydrological System Inflow Prediction using Artificial Neural Network

2022 Tehnički Vjesnik  
Neural Networks: A Comprehensive the prediction of a karstic aquifer's response. Hydrological Foundation. Pearson Education Inc. Second Edition, 2004.  ...  This paper deals with the limitation of complex hydrological system inflow prediction using artificial neural network and inflow time series.  ... 
doi:10.17559/tv-20200721133924 fatcat:zfwvanwfmjgajj4lmrn7pdw22q
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