Application of Neural Networks in Animal Science

2010 ◽  
pp. 440-456
Author(s):  
Emilio Soria ◽  
Carlos Fernández ◽  
Antonio J. Serrano ◽  
Marcelino Martínez ◽  
José R. Magdalena ◽  
...  
Keyword(s):  
Data Analysis ◽  
Linear Models ◽  
Production Systems ◽  
Human Society ◽  
Human History ◽  
Animal Science ◽  
Practical Applications ◽  
Yield Production ◽  
Non Linear ◽  
And Performance

Stock breeding has been one of the most important sources of food and labour throughout human history. Every advance in this field has always led to important and beneficial impacts on human society. These innovations have mainly taken place in machines or genetics, but data analysis has been somewhat ignored. Most of the published works in data analysis use linear models, and there are few works in the literature that use non-linear methods for data processing in stock breeding where these methods have proven to obtain better results and performance than linear, classical methods. This chapter demonstrates the use of non-linear methods by presenting two practical applications: milk yield production in goats, and analysis of farming production systems.

scholarly journals Non-linear population discrete models with two time scales: re-scaling of part of the slow process

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Luis Sanz ◽  
Rafael Bravo de la Parra ◽  
Marcos Marvá ◽  
Eva Sánchez
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Linear Models ◽  
Discrete Models ◽  
Fast Time ◽  
Compact Sets ◽  
Practical Applications ◽  
Fast Time Scale ◽  
Non Linear ◽  
Time Systems

Abstract In this work we present a reduction result for discrete-time systems with two time scales. In order to be valid, previous results in the field require some strong hypotheses that are difficult to check in practical applications. Roughly speaking, the iterates of a map as well as their differentials must converge uniformly on compact sets. Here, we eliminate the hypothesis of uniform convergence of the differentials at no significant cost in the conclusions of the result. This new result is then used to extend to non-linear cases the reduction of some population discrete models involving processes acting at different time scales. In practical cases, some processes that occur at a fast time scale are often only measured at slow time intervals, notably mortality. For a general class of linear models that include such a kind of processes, it has been shown that a more realistic approach requires the re-scaling of those processes to be considered at the fast time scale. We develop the same type of re-scaling in some non-linear models and prove the corresponding reduction results. We also provide an application to a particular model of a structured population in a two-patch environment.

scholarly journals Catalytic Functionalized Structured Monolithic Micro-/Mesoreactors: Engineering, Properties, and Performance in Flow Synthesis: An Overview and Guidelines

2021 ◽  
Vol 3 ◽  
Author(s):  
Katarzyna Szymańska ◽  
Agnieszka Ciemięga ◽  
Katarzyna Maresz ◽  
Wojciech Pudło ◽  
Janusz Malinowski ◽  
...  
Keyword(s):  
Continuous Flow ◽  
Production Systems ◽  
Engineering Properties ◽  
Darcy Law ◽  
High Yield ◽  
Yield Production ◽  
Working Volume ◽  
Catalytic Sites ◽  
And Performance ◽  
A Minor

In this review article, we first discussed the development of silica monoliths with hierarchical macro-/mesopore structure and their potential figures of merit as continuous-flow micro-/mesoreactors of up to 30 ml working volume. Making use of the flow hindrance of different pore structures seen from the Darcy law perspective, we discriminated four structures of the monoliths (M1–M4). We then summarized the most important results, mainly from our studies of continuous-flow structured monolithic reactors and rotating bed reactors (RBRs) filled with structured pellets, activated with various catalytic entities and enzymes. The results show that an increase in the flow rate and thus velocity in reactors activated with more conventional catalytic sites has no or a minor positive effect on the apparent reaction rate. On the contrary, in those with the most open structure (M1) and functionalized with enzymes, it could increase by more than two orders of magnitude even at low overpressures. The production systems worked stably for at least 200 h. To conclude, the synthetic system made of the hierarchically structured monoliths, or RBRs filled with structured catalytic pellets, lay the foundation for a new platform for the high-yield production of a wide variety of specialty chemicals, even on a multikilogram scale, in a safe and sustained manner.

G Optimal Design in Non linear Models to Increase Silicon Oxide Purity Levels and Electrical Conductivity

2018 ◽  
pp. 150-155
Author(s):  
Muklas Rivai
Keyword(s):  
Electrical Conductivity ◽  
Optimal Design ◽  
Linear Models ◽  
Silicon Oxide ◽  
Information Matrix ◽  
Relevant Information ◽  
Non Linear

Optimal design is a design which required in determining the points of variable factors that would be attempted to optimize the relevant information so that fulfilled the desired criteria. The optimal fulfillment criteria based on the information matrix of the selected model.

Analysis of Non-Linear Activation Functions for Classification Tasks Using Convolutional Neural Networks

2019 ◽  
Vol 12 (3) ◽  
pp. 156-161 ◽  
Author(s):  
Aman Dureja ◽  
Payal Pahwa
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Activation Function ◽  
Primary Objective ◽  
Experimental Comparison ◽  
Activation Functions ◽  
Practical Applications ◽  
Network Activation ◽  
Non Linear ◽  
Hidden Layer

Background: In making the deep neural network, activation functions play an important role. But the choice of activation functions also affects the network in term of optimization and to retrieve the better results. Several activation functions have been introduced in machine learning for many practical applications. But which activation function should use at hidden layer of deep neural networks was not identified. Objective: The primary objective of this analysis was to describe which activation function must be used at hidden layers for deep neural networks to solve complex non-linear problems. Methods: The configuration for this comparative model was used by using the datasets of 2 classes (Cat/Dog). The number of Convolutional layer used in this network was 3 and the pooling layer was also introduced after each layer of CNN layer. The total of the dataset was divided into the two parts. The first 8000 images were mainly used for training the network and the next 2000 images were used for testing the network. Results: The experimental comparison was done by analyzing the network by taking different activation functions on each layer of CNN network. The validation error and accuracy on Cat/Dog dataset were analyzed using activation functions (ReLU, Tanh, Selu, PRelu, Elu) at number of hidden layers. Overall the Relu gave best performance with the validation loss at 25th Epoch 0.3912 and validation accuracy at 25th Epoch 0.8320. Conclusion: It is found that a CNN model with ReLU hidden layers (3 hidden layers here) gives best results and improve overall performance better in term of accuracy and speed. These advantages of ReLU in CNN at number of hidden layers are helpful to effectively and fast retrieval of images from the databases.

scholarly journals SWIPT in mMIMO system with non-linear energy-harvesting terminals: protocol design and performance optimization

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Kui Xu ◽  
Ming Zhang ◽  
Jie Liu ◽  
Nan Sha ◽  
Wei Xie ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Performance Optimization ◽  
Power Transmission ◽  
Base Station ◽  
Second Phase ◽  
Wireless Power ◽  
Half Duplex ◽  
Non Linear ◽  
Two Phases ◽  
And Performance

Abstract In this paper, we design the simultaneous wireless information and power transfer (SWIPT) protocol for massive multi-input multi-output (mMIMO) system with non-linear energy-harvesting (EH) terminals. In this system, the base station (BS) serves a set of uplink fixed half-duplex (HD) terminals with non-linear energy harvester. Considering the non-linearity of practical energy-harvesting circuits, we adopt the realistic non-linear EH model rather than the idealistic linear EH model. The proposed SWIPT protocol can be divided into two phases. The first phase is designed for terminals EH and downlink training. A beam domain energy beamforming method is employed for the wireless power transmission. In the second phase, the BS forms the two-layer receive beamformers for the reception of signals transmitted by terminals. In order to improve the spectral efficiency (SE) of the system, the BS transmit power- and time-switching ratios are optimized. Simulation results show the superiority of the proposed beam-domain SWIPT protocol on SE performance compared with the conventional mMIMO SWIPT protocols.

scholarly journals Sensuator: A Hybrid Sensor–Actuator Approach to Soft Robotic Proprioception Using Recurrent Neural Networks

Actuators ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 30
Author(s):  
Pornthep Preechayasomboon ◽  
Eric Rombokas
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Linear Models ◽  
Open Loop ◽  
Proof Of Concept ◽  
State Estimator ◽  
Loop Control ◽  
Practical Applications ◽  
Soft Actuator ◽  
The Cost

Soft robotic actuators are now being used in practical applications; however, they are often limited to open-loop control that relies on the inherent compliance of the actuator. Achieving human-like manipulation and grasping with soft robotic actuators requires at least some form of sensing, which often comes at the cost of complex fabrication and purposefully built sensor structures. In this paper, we utilize the actuating fluid itself as a sensing medium to achieve high-fidelity proprioception in a soft actuator. As our sensors are somewhat unstructured, their readings are difficult to interpret using linear models. We therefore present a proof of concept of a method for deriving the pose of the soft actuator using recurrent neural networks. We present the experimental setup and our learned state estimator to show that our method is viable for achieving proprioception and is also robust to common sensor failures.

scholarly journals Towards a contemporary player learning in development framework for sports practitioners

2021 ◽  
pp. 174795412110023
Author(s):  
Mark O Sullivan ◽  
Carl T Woods ◽  
James Vaughan ◽  
Keith Davids
Keyword(s):  
Linear Process ◽  
Task Environment ◽  
Coach Education ◽  
Development Framework ◽  
Novel Approach ◽  
Non Linear ◽  
And Performance ◽  
Learning Development ◽  
High Level ◽  
User Friendly

As it is appreciated that learning is a non-linear process – implying that coaching methodologies in sport should be accommodative – it is reasonable to suggest that player development pathways should also account for this non-linearity. A constraints-led approach (CLA), predicated on the theory of ecological dynamics, has been suggested as a viable framework for capturing the non-linearity of learning, development and performance in sport. The CLA articulates how skills emerge through the interaction of different constraints (task-environment-performer). However, despite its well-established theoretical roots, there are challenges to implementing it in practice. Accordingly, to help practitioners navigate such challenges, this paper proposes a user-friendly framework that demonstrates the benefits of a CLA. Specifically, to conceptualize the non-linear and individualized nature of learning, and how it can inform player development, we apply Adolph’s notion of learning IN development to explain the fundamental ideas of a CLA. We then exemplify a learning IN development framework, based on a CLA, brought to life in a high-level youth football organization. We contend that this framework can provide a novel approach for presenting the key ideas of a CLA and its powerful pedagogic concepts to practitioners at all levels, informing coach education programs, player development frameworks and learning environment designs in sport.

scholarly journals Switched Capacitor DC-DC Converters: A Survey on the Main Topologies, Design Characteristics, and Applications

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2231
Author(s):  
Alencar Franco de Souza ◽  
Fernando Lessa Tofoli ◽  
Enio Roberto Ribeiro
Keyword(s):  
Voltage Regulation ◽  
Inherent Difficulty ◽  
Practical Applications ◽  
Dc Power ◽  
Higher Power ◽  
Voltage Doubler ◽  
Converter Design ◽  
Design Characteristics ◽  
And Performance ◽  
Full Charge

This work presents a review of the main topologies of switched capacitors (SCs) used in DC-DC power conversion. Initially, the basic configurations are analyzed, that is, voltage doubler, series-parallel, Dickson, Fibonacci, and ladder. Some aspects regarding the choice of semiconductors and capacitors used in the circuits are addressed, as well their impact on the converter behavior. The operation of the structures in terms of full charge, partial charge, and no charge conditions is investigated. It is worth mentioning that these aspects directly influence the converter design and performance in terms of efficiency. Since voltage regulation is an inherent difficulty with SC converters, some control methods are presented for this purpose. Finally, some practical applications and the possibility of designing DC-DC converters for higher power levels are analyzed.

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