Adaptive Boltzmann Medical Dataset Machine Learning

The RBM is a stochastic energy-based model of an unsupervised neural network (RBM). RBM is a key pre-training for Deep Learning. Structure of RBM includes weights and coefficients for neurons. Better network structure allows us to examine data more thoroughly, which is good. We looked at the variance of parameters in learning on demand to fix the problem. To determine why RBM's energy function fluctuates, we'll look at its parameter variance. A neuron generation and annihilation algorithm is smeared with an adaptive RBM learning method to determine the optimal number of hidden neurons for attribute imputation during training. When the energy function isn't converged and parameter variance is high, a hidden neuron is generated. If the neuron doesn't disrupt learning, it'll destroy the hidden neuron. In this study, some yardstick PIMA data sets were tested

Fuzzy-based fault-tolerant and instant synchronization routing technique in wireless sensor network for rapid transit system

In the present era, rapid transits are one of the most affordable means of public transport with various useful integrated application systems. The majority of the integrated applications are deployed in concern over safety and precautionary measures against the worst side-effects of unfortunate emergencies. For such cases, high-end reliable and autonomous systems provide possible positive solutions. Wireless Sensor Network is one of the suitable choices for rapid transit applications to gain positive results with inexpensive implementation cost. However, managing few network consequences like fault tolerance, energy balancing and routing critical informative packets are considered to be the challenging task due to their limited resource usage restriction. In this paper, a novel fuzzy logic-based fault tolerance and instant synchronized routing technique have been proposed specifically for the rapid transit system. On utilizing the fuzzy logic concepts, most of the computational complexities and uncertainties of the system is reduced. The central thematic of the proposed design is concerned over the synchronized routing and permanent faults which abruptly depicts the non-functional nature of the sensor nodes during normal operations. Moreover, our proposed simulation outcomes proved to be improvised evidence on obtaining maximum packet delivery ratio which tends to handle an emergency situation in the compartments of rapid transits

A review of shear strength models for rock joints subjected to constant normal stiffness

The typical shear behaviour of rough joints has been studied under constant normal load/stress (CNL) boundary conditions, but recent studies have shown that this boundary condition may not replicate true practical situations. Constant normal stiffness (CNS) is more appropriate to describe the stress-strain response of field joints since the CNS boundary condition is more realistic than CNL. The practical implications of CNS are movements of unstable blocks in the roof or walls of an underground excavation, reinforced rock wedges sliding in a rock slope or foundation, and the vertical movement of rock-socketed concrete piles. In this paper, the highlights and limitations of the existing models used to predict the shear strength/behaviour of joints under CNS conditions are discussed in depth

Strain Pattern Analysis of Mylonites From Sitampundi-Kanjamalai Shear Zone, Thiruchengode, South India

This study aims to investigate the petrography and strain pattern of mylonites from parts of N-S trending Sitampundi-Kanjamalai Shear Zone (SKSZ) around Thiruchengode. The petrographic study indicates the presence of recrystallized quartz, K-feldspar, plagioclase, biotite and some hornblende. The kinematic analysis of Mylonites was done with the help of shear sense indicators such as recrystallized type quartz (quartz ribbon) around the cluster of feldspar, S-C fabric shows dextral shear sense and some sinisterly shear sense in some parts of SASZ which can be considered as a product of partitioning of both strain and vorticity between domains. These all indicates the simple shear extension along E-W direction and the mylonitic foliation shows the pure shear compression along N-S direction. Further the study of bulk strain analysis by Flinn plot method using L and T section of mylonite shows k<1 which lies in the field of flattening zone of finite strain. The kinematic vorticity number is calculated by Rxz/β method which gives the value of 0.36 indicating the general shear. The rigid grain graph shows that the pure shear component is more ­­­­dominant than the simple shear component. The analysis leads to the conclusion that the mylonite has experienced a high temperature shearing of above 700°cat deep crustal level

Numerical Model‐Software for Predicting Rock Formation Failure‐Time Using Fracture Mechanics

Real‐time integrated drilling is an important practice for the upstream petroleum industry. Traditional pre‐drill models, tend to offset the data gathered from the field since information obtained prior to spudding and drilling of new wells often become obsolete due to the changes in geology and geomechanics of reservoir‐rocks or formations. Estimating the complicated non‐linear failure‐time of a rock formation is a difficult but important task that helps to mitigate the effects of rock failure when drilling and producing wells from the subsurface. In this study, parameters that have the strongest impact on rock failure were used to develop a numerical and computational model for evaluating wellbore instability in terms of collapse, fracture, rock strength and failure‐time. This approach presents drilling and well engineers with a better understanding of the fracture mechanics and rock strength failureprediction procedure required to reduce stability problems by forecasting the rock/formation failuretime. The computational technique built into the software, uses the stress distribution around a rock formation as well as the rock’s responses to induced stress as a means of analyzing the failure time of the rock. The results from simulation show that the applied stress has the most significant influence on the failure‐time of the rock. The software also shows that the failure‐time varied over several orders of magnitude for varying stress‐loads. Thus, this will help drilling engineers avoid wellbore failure by adjusting the stress concentration properly through altering the mud pressure and well orientation with respect to in‐situ stresses. As observed from the simulation results for the failure time analysis, the trend shows that the time dependent strength failure is not just a function of the applied stress. Because, at applied stress of 6000–6050 psi there was time dependent failure whereas, at higher applied stress of 6350–6400 psi there was no time dependent strength failure

Modelling the shear behaviour of sedimentary rock joints under constant normal stiffness conditions

The typical shear behaviour of rock joints has been studied under a constant normal load (CNL) or zero normal stiffness condition, but recent studies have shown that this boundary condition may not replicate more practical situations, and that constant normal stiffness (CNS) is a more appropriate boundary condition to describe the stress-strain response of field joints. In addition to the effect of boundary conditions, the shear behaviour of a rough joint also depends on its surface properties and the initial stress acting on its interface. Despite this, exactly how these parameters affect the shear behaviour of joints is not fully understood because the stress-strain response of joints is governed by non-uniform asperity damage and the resulting gouge that accumulates on their interfaces. Therefore, an attempt has been made in this study to predict the complete shear behaviour of rough joints incorporating the asperity deformation under CNS conditions. In order to validate this analytical model, a series of CNS shear tests were conducted on rough tensile (natural) joints and their replicas at a range of initial normal stresses that varied from 0.4 to 1.6 MPa. Comparisons between the predicted shear behaviour and the experimental results show close agreement

Selection of an effective substrate to treat gray water in horizontal flow constructed wetlands

A study was carried out to compare the performances of different substrates used in a laboratory scale subsurface flow constructed wetland systems to treat gray water released from the university staff canteen. Three wooden boxes with the dimensions of 60cm x 25cm x 25cm were fabricated and 15mm rock aggregates, pebbles (15mm) and broken tiles (25mm) were used as substrates (which were selected considering the availability) in each of the boxes. Each horizontal subsurface flow bed was fed in a batch process with gray water with a flow rate of 20 litres per day. The retention time for each batch was maintained as 6 days. BOD, COO, pH, conductivity, N03-, P043-, turbidity and temperature in the influent and the effluent were monitored for every batch of waste water passed through the systems and their removal efficiencies were determined. The highest removal efficiencies of COD and, BOD,and P043- were 80%-90%and 60%- 80%, respectively were recorded from broken tiles, while highest removal efficiency of N03-, of 60%- 90%, was recorded from aggregates. Removal of turbidity in all three tanks was similar being between 60%- 90%. Hence, crushed aggregates and broken tiles are found to be the best substrates, considering the removal efficiencies to treat gray water