scholarly journals The epigenome and top-down causation

2011 ◽  
Vol 2 (1) ◽  
pp. 42-48 ◽  
Author(s):  
P. C. W. Davies
Keyword(s):  
Systems Theory ◽  
Physical Object ◽  
Biological Information ◽  
Top Down ◽  
Molecular Sequences ◽  
Information Theoretic ◽  
Time Operation ◽  
Real Time Operation ◽  
Physical And Chemical ◽  
Self Organizing

Genes store heritable information, but actual gene expression often depends on many so-called epigenetic factors, both physical and chemical, external to DNA. Epigenetic changes can be both reversible and heritable. The genome is associated with a physical object (DNA) with a specific location, whereas the epigenome is a global, systemic, entity. Furthermore, genomic information is tied to specific coded molecular sequences stored in DNA. Although epigenomic information can be associated with certain non-DNA molecular sequences, it is mostly not. Therefore, there does not seem to be a stored ‘epigenetic programme’ in the information-theoretic sense. Instead, epigenomic control is—to a large extent—an emergent self-organizing phenomenon, and the real-time operation of the epigenetic ‘project’ lies in the realm of nonlinear bifurcations, interlocking feedback loops, distributed networks, top-down causation and other concepts familiar from the complex systems theory. Lying at the heart of vital eukaryotic processes are chromatin structure, organization and dynamics. Epigenetics provides striking examples of how bottom-up genetic and top-down epigenetic causation intermingle. The fundamental question then arises of how causal efficacy should be attributed to biological information. A proposal is made to implement explicit downward causation by coupling information directly to the dynamics of chromatin, thus permitting the coevolution of dynamical laws and states, and opening up a new sector of dynamical systems theory that promises to display rich self-organizing and self-complexifying behaviour.

scholarly journals Exploring 3D Human Action Recognition Using STACOG on Multi-View Depth Motion Maps Sequences

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3642
Author(s):  
Mohammad Farhad Bulbul ◽  
Sadiya Tabussum ◽  
Hazrat Ali ◽  
Wenli Zheng ◽  
Mi Young Lee ◽  
...  
Keyword(s):  
Action Recognition ◽  
Depth Map ◽  
Human Action Recognition ◽  
Human Action ◽  
Collaborative Representation ◽  
Auto Correlation ◽  
Time Operation ◽  
Real Time Operation ◽  
Benchmark Datasets ◽  
Depth Motion Maps

This paper proposes an action recognition framework for depth map sequences using the 3D Space-Time Auto-Correlation of Gradients (STACOG) algorithm. First, each depth map sequence is split into two sets of sub-sequences of two different frame lengths individually. Second, a number of Depth Motion Maps (DMMs) sequences from every set are generated and are fed into STACOG to find an auto-correlation feature vector. For two distinct sets of sub-sequences, two auto-correlation feature vectors are obtained and applied gradually to L2-regularized Collaborative Representation Classifier (L2-CRC) for computing a pair of sets of residual values. Next, the Logarithmic Opinion Pool (LOGP) rule is used to combine the two different outcomes of L2-CRC and to allocate an action label of the depth map sequence. Finally, our proposed framework is evaluated on three benchmark datasets named MSR-action 3D dataset, DHA dataset, and UTD-MHAD dataset. We compare the experimental results of our proposed framework with state-of-the-art approaches to prove the effectiveness of the proposed framework. The computational efficiency of the framework is also analyzed for all the datasets to check whether it is suitable for real-time operation or not.

Representations need self-organizing top-down expectations to fit a changing world

1998 ◽  
Vol 21 (4) ◽  
pp. 473-474 ◽  
Author(s):  
Stephen Grossberg
Keyword(s):  
Top Down ◽  
Bottom Up ◽  
Computational Properties ◽  
Self Organizing ◽  
Changing World

“Chorus embodies an attempt to find out how far a mostly bottom-up approach to representation can be taken.” Models that embody both bottom-up and top-down learning have stronger computational properties and explain more data about representation than feedforward models do.

Real-Time Operation and Characterization of a High-Performance Time-Based Accelerometer

2015 ◽  
Vol 24 (6) ◽  
pp. 1703-1711 ◽  
Author(s):  
Rosana Alves Dias ◽  
Filipe Serra Alves ◽  
Margaret Costa ◽  
Helder Fonseca ◽  
Jorge Cabral ◽  
...  
Keyword(s):  
Real Time ◽  
High Performance ◽  
Performance Time ◽  
Time Operation ◽  
Real Time Operation

Cultural Change in ALS Real Time Operation and Optimization in Vaca Muerta Through CWE

2018 ◽  
Author(s):  
J. I. Alvarez Claramunt ◽  
P. E. Bizzotto ◽  
F. Sapag ◽  
E. Ferrigno ◽  
J. L. Barros ◽  
...  
Keyword(s):  
Real Time ◽  
Cultural Change ◽  
Time Operation ◽  
Vaca Muerta ◽  
Real Time Operation

scholarly journals A Novel Computational Approach for Harmonic Mitigation in PV Systems with Single-Phase Five-Level CHBMI

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2100 ◽  
Author(s):  
Rosario Miceli ◽  
Giuseppe Schettino ◽  
Fabio Viola
Keyword(s):  
Single Phase ◽  
Switching Frequency ◽  
Polynomial Equations ◽  
Voltage Waveform ◽  
Pv Systems ◽  
Time Operation ◽  
Novel Approach ◽  
Field Programmable ◽  
Real Time Operation ◽  
Harmonic Mitigation

In this paper, a novel approach to low order harmonic mitigation in fundamental switching frequency modulation is proposed for high power photovoltaic (PV) applications, without trying to solve the cumbersome non-linear transcendental equations. The proposed method allows for mitigation of the first-five harmonics (third, fifth, seventh, ninth, and eleventh harmonics), to reduce the complexity of the required procedure and to allocate few computational resource in the Field Programmable Gate Array (FPGA) based control board. Therefore, the voltage waveform taken into account is different respect traditional voltage waveform. The same concept, known as “voltage cancelation”, used for single-phase cascaded H-bridge inverters, has been applied at a single-phase five-level cascaded H-bridge multilevel inverter (CHBMI). Through a very basic methodology, the polynomial equations that drive the control angles were detected for a single-phase five-level CHBMI. The acquired polynomial equations were implemented in a digital system to real-time operation. The paper presents the preliminary analysis in simulation environment and its experimental validation.

scholarly journals TDOA-based microwave imaging algorithm for real-time microwave ablation monitoring

2017 ◽  
Vol 10 (2) ◽  
pp. 169-178 ◽  
Author(s):  
Shouhei Kidera ◽  
Luz Maria Neira ◽  
Barry D. Van Veen ◽  
Susan C. Hagness
Keyword(s):  
Real Time ◽  
Microwave Ablation ◽  
Microwave Imaging ◽  
Ablation Zone ◽  
Real Time Monitoring ◽  
Imaging Algorithm ◽  
Array Measurements ◽  
Time Operation ◽  
Real Time Operation ◽  
Propagation Media

Microwave ablation is widely recognized as a promising minimally invasive tool for treating cancer. Real-time monitoring of the dimensions of the ablation zone is indispensable for ensuring an effective and safe treatment. In this paper, we propose a microwave imaging algorithm for monitoring the evolution of the ablation zone. Our proposed algorithm determines the boundary of the ablation zone by exploiting the time difference of arrival (TDOA) between signals received before and during the ablation at external antennas surrounding the tissue, using the interstitial ablation antenna as the transmitter. A significant advantage of this method is that it requires few assumptions about the dielectric properties of the propagation media. Also the simplicity of the signal processing, wherein the TDOA is determined from a cross-correlation calculation, allows real-time monitoring and provides robust performance in the presence of noise. We investigate the performance of this approach for the application of breast tumor ablation. We use simulated array measurements obtained from finite-difference time-domain simulations of magnetic resonance imaging-derived numerical breast phantoms. The results demonstrate that our proposed method offers the potential to achieve millimeter-order accuracy and real-time operation in estimating the boundary of the ablation zone in heterogeneous and dispersive breast tissue.

scholarly journals Development of a Low-Cost Data Acquisition System for Very Short-Term Photovoltaic Power Forecasting

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6075
Author(s):  
Guilherme Fonseca Bassous ◽  
Rodrigo Flora Calili ◽  
Carlos Hall Barbosa
Keyword(s):  
Low Cost ◽  
Renewable Energy Sources ◽  
Relevant Information ◽  
Acquisition System ◽  
Time Operation ◽  
Detection Point ◽  
Real Time Operation ◽  
Forecast Models ◽  
Input Variables ◽  
Power Forecasting

The rising adoption of renewable energy sources means we must turn our eyes to limitations in traditional energy systems. Intermittency, if left unaddressed, may lead to several power-quality and energy-efficiency issues. The objective of this work is to develop a working tool to support photovoltaic energy forecast models for real-time operation applications. The current paradigm of intra-hour solar-power forecasting is to use image-based approaches to predict the state of cloud composition for short time horizons. Since the objective of intra-minute forecasting is to address high-frequency intermittency, data must provide information on and surrounding these events. For that purpose, acquisition by exception was chosen as the guiding principle. The system performs power measurements at 1 Hz frequency, and whenever it detects variations over a certain threshold, it saves the data 10 s before and 4 s after the detection point. A multilayer perceptron neural network was used to determine its relevance to the forecasting problem. With a thorough selection of attributes and network structures, the results show very low error with R2 greater than 0.93 for both input variables tested with a time horizon of 60 s. In conclusion, the data provided by the acquisition system yielded relevant information for forecasts up to 60 s ahead.

scholarly journals CONTROLLING AND MONITORING OF AUTOMATION WATER SUPPLY SYSTEM BASED ON IOT WITH THEFT IDENTIFICATION

2017 ◽  
Vol 5 (5) ◽  
pp. 320-325
Author(s):  
Ahmad T. Jaiad ◽  
Hamzah Sabr Ghayyib
Keyword(s):  
Water Supply ◽  
Real Time ◽  
Water Conservation ◽  
Water Distribution ◽  
Network Connectivity ◽  
Raspberry Pi ◽  
Human Beings ◽  
Residential Areas ◽  
Time Operation ◽  
Real Time Operation

Water is the most precious and valuable because it’s a basic need of all the human beings but, now a day water supply department are facing problem in real time operation this is because less amount of water in resources due to less rain fall. With increase in Population, urban residential areas have increased because of this reasons water has become a crucial problem which affects the problem of water distribution, interrupted water supply, water conservation, water consumption and also the water quality so, to overcome water supply related problems and make system efficient there is need of proper monitoring and controlling system. In this project, we are focusing on continuous and real time monitoring of water supply in IOT platform. Water supply with continuous monitoring makes a proper distribution so that, we can have a record of available amount of water in tanks, flow rate, abnormality in distribution line. Internet of things is nothing but the network of physical objects embedded with electronics, sensors, software, and network connectivity. Monitoring can be done from anywhere as central office. Using Adafruit as free sever data continuously pushed on cloud so we can see data in real time operation. Using different sensors with controller and raspberry pi as Mini computer can monitor data and also control operation from cloud with efficient client server communication.

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