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Decision making under acute stress modeled by an adaptive temporal–causal network model

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Veri¯cation of the Network Model by Mathematical Analysis. Updated connection weights for the Scenario 4.. A state Y in an adaptive temporal – causal network model has a stationary point at t if d Y ðtÞ= d t ¼ 0 . Similarly, a connection weight ! in an adaptive temporal – causal network model has a stationary point at t if d !ðtÞ= d t ¼ 0 . An adaptive temporal – causal network model is in an equilibrium state at t if all states and connections have a stationary point at t .

Prediction of host-pathogen protein interactions by extended network model

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Then, the description of the extended network model (ENM) is presented.. Location-based encoding (LBE) (Kưsesoy et al., 2019), amino acid pairs (AAP) (Chen et al., 2007), and amino acid composition (AAC) (Bhasin and Raghava, 2004) are used for feature encoding. The details of encoding and prediction methods are given as appendices in the supplementary material section (Appendices A and B)..

Predicting breast cancer drug response using a multiple-layer cell line drug response network model

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Comprehensive anticancer drug response prediction based on a simple cell line-drug complex network model. A novel approach for drug response prediction in cancer cell lines via network representation learning.. Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization

A network generator for covert network structures

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In the case of the Caviar network, we know which nodes had some management roles from the publicly released court proceedings. 1) was identified as the leader of the hashish group, and node N12 as the leader of the cocaine group. 1 shows more nodes in management roles in the Caviar groups. Illustration of our model integration of the stochastic block model (SBM) with the hierarchical multi-layer network model in the Caviar network..

CompTIA Network+ Certification Study Guide part 6

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TCP/IP is the default protocol used by the Internet and many current OSes, such as Microsoft Windows and Novell NetWare.. that are centrally located, while a decentralized network model has resources and administration that are distributed throughout the network.. as equals, and acting as both clients and servers of the network.. The topology of a network is the physical layout of computers,.

A study on the construction of multicultural trade network by using Chang Po-Go‘s trade network

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The paper suggests a way to utilize Chang Po-Go's trade network model which is being re-evaluated as a competitive model of Asia in the 21st century in line with this trend.. Chang Po-Go's trade model is the subject of benchmarking that we should follow in the era of globalization, and it raises the necessity of continuous and systematic research value as a compass of the future trade.. Existing research on Chang Po-Go network.

Handbook of Neural Network Signal Processing P1

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The figure on the left-hand side depicts the data samples and the initial position of the separating hyperplane, whose normal vector contains the weights to the perceptron. 1.2.2.1.1 Applications of the Perceptron Neuron Model. A multilayer perceptron (MLP) neural network model consists of a feed-forward, layered network of McCulloch and Pitts’ neurons. Some of the most frequently used activation functions for MLP include the sigmoid function and the hyperbolic tangent function..

Motion learning using spatio temporal neural network

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The network model had been trained to perform the fish motion sequence learning with a target response, R A or R B . This is to show that the network could successfully associate all pairs to their target responses.. The network was then trained with a set of fish motion with repeating points.. With such conditions, the network performance was observed if the network could successfully learn not just the association between S i and S j but also the sequence of S i …S j.

Lecture Advanced Computer Networks - Chapter 4: Network Transport

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Provide a model for the network. Estimate the parameters for the model based on probing. Decide sending rate using the network model. Congestion-based congestion control. More packets accumulate in the buffer of the network devices. congestion control). Adjust sending rate based on measured RTT — trying to operate at the optimal point. Not competitive to flows with loss-based congestion control algorithms, why?. Control sending rate based on the model:. congestion control algorithms.

A modified semi-parametric regression model for flood forecasting

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The results have shown that a semi- parametric regression model, along with artificial neural network models, is capable of modeling and forecasting the flood water levels, especially for low warning times. The precision of the estimates will depend on the quality of the information used to train the model. parametric regression model, together with artificial neural network, can be very useful tools for modeling and forecasting spatio-temporal flood water levels.

Model-Based Design for Embedded Systems- Part 19

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The TrueTime network model assumes the presence of a network interface card or a bus controller implemented either in the hardware or the software (i.e., as drivers). The Contiki interface to the I 2 C bus is software-based and corresponds well to the TrueTime model. In the ATMEL AVRs, however, it is normally the responsibility of the application programmer to manage all bus access and synchronization directly in the application code.

A neural network method for spamassasin rules generation

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The neural network model. An input e-mail message is fed into the feature selector layer in the form of a binary vector x which was described in a previous section.

CompTIA Network+ Certification Study Guide part 68

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Answer D is incorrect because servers are used, making this a client/server model.. of the amount of data being stored, there are three file servers, a web server for the intranet, an e-mail server for internal e-mail, and a SQL Server that is used for several databases that have been developed in house. Client/server B. Peer-to-peer C. Client/server. A decentralized network model has network resources and administration distributed throughout the network.

Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty

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Such a Gaussian linear model is an appropriate model for single-cell gene-expression data [19, 20].. The prior probability of the model θ for the class c is repre- sented by π(θ | c), where M. (6) where π(θ | c ) denotes the prior probability of the corresponding network model θ for class c. (7) Now, using the above definition in (4)-(6) leads to the following exact OBC solution:. θ , c is used in (9) due to the independency of the training trajectories..

StressGenePred: A twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in arabidopsis

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To deal with the high-dimension and low-sample-size data problem, our model is designed to share a core neural network model between twin sub-neural network models: 1) biomarker gene discovery model 2) stress type prediction model.. Multiple heterogeneous time-series gene expression data Multiple stress time-series gene expression data is a set of time-series gene expression data.

Hydrostatic pressure distribution of oil lubrication film for internal gear motors and pumps: Solution of resistance network

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Opitz in [9] used the hydraulic resistance model to calculate the hydrostatic pressure for journal bearing.. In this paper, the resistance network model for the calculation of the pressure distribution of the oil lubrication film between the ring gear and its housing is introduced. The results point out that the shape, values, and trends of the pressure distribution for both cases are almost identical.

Neural Network Applications in Intelligent

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A second neural network was developed to estimate the frequency response of the cutting operation. The neural network used was a Gaussian machine. A multilayer feedforward neural network was trained using the BP algorithm to model the manufacturing process..

Neural network based tonal feature for Vietnamese speech recognition using multi space distribution model

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To maintain these advantages, we are going to apply MLP for extracting tonal feature, and adapt it to the MSD model.. Tonal bottle neck feature. In order to achieve a better tonal feature we present a progress to extract a tonal bottle neck feature (TBNF), so- called, based on a bottle neck MLP network.. TBNF then is adapted to the/an MSD model. A trained bottle neck MLP network of five layers is used to extract TBNF.

Model-Based Design for Embedded Systems- Part 18

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A TrueTime model may contain several network blocks, and each kernel block may be connected to more than one network. The network blocks may be used in two different ways. The first way is to have one kernel block for each node in the network. The tasks inside the ker- nels can then send and receive arbitrary MATLAB structure arrays over the network using certain kernel primitives.

Consensus of large-scale group decision making in social network: The minimum cost model based on robust optimization

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Consensus of large-scale group decision making in social network: the minimum cost model based on robust optimization. Social network Robust optimization. In the practical consensus of LSGDM, the unit adjustment cost of experts is difficult to obtain and may be uncertain. Then, a minimum cost model based on robust optimization is proposed to solve the robust optimization consensus problem..