The document presents a neural tree model for estimating the uniaxial compressive strength (UCS) of rock materials from index test parameters. It develops and compares models using fuzzy inference systems, adaptive neuro-fuzzy inference systems, multi-layer perceptrons, and heterogeneous flexible neural trees. The best performing and lightest weight model was a multiobjective heterogeneous flexible neural tree, which estimated UCS with the lowest error and highest correlation. Among the different index test parameters, the point load strength test was found to be the most significant in estimating UCS.
Rock Mass Classification and also a brief description of Rock Mass Rating (RMR), Rock Structure Rating (RSR), Q valves and New Austrian Tunneling method (NATM)
Geological site investigation for Civil Engineering FoundationsDr.Anil Deshpande
Aim to introduce Preliminary geological Investigations for fulfilling knowledge about geological need to determine engineering properties of foundation rocks and check the suitability & feasibility of site wherein selection of site plays a crucial role to avoid future implications in civil engineering projects.
Introduction
Petrophysic of the rocks
It is the study of the physical and chemical properties of the rocks related to the pores and fluid distribution
Porosity, is ratio between volume of void to the total voids of the rock.
Permeability, is ability of a porous material to allow fluids to pass through it.
Electric, most of the sedimentary rocks don’t have conductivity.
Radiation, clay rocks have 40K, radiate alpha ray.
Hardness, it depends on the cementing material and thickness of the sediments.
WELL LOGGING
The systematic recording of rock properties and it’s fluid contents in wells being drilled or produced to obtain various petrophysical parameters and characteristics of down hole sequences (G.E Archie 1950).
The measurement versus depth or time, or both, of one or more physical properties in a well.
These methods are particularly good when surface outcrops are not available, but a direct sample of the rock is needed to be sure of the lithology.
A wide range of physical parameters can be measured.
In some cases, the measurements are not direct, it require interpretation by analogy or by correlating values between two or more logs run in the same hole.
Provide information on lithology, boundaries of formations and stratigraphic correlation.
Determine Porosity, Permeability, water, oil and gas saturation.
Reservoir modeling and Structural studies… etc.
Types of Well Logging
Logs can be classified into several types under different category
Permeability and lithology Logs
Gamma Ray log
Self Potential [SP] log
Caliber log
Porosity Logs
Density log
Sonic log
Neutron log
Electrical Logs
Resistivity Log
For contact : omerupto3@gmail.com
Rock Mass Classification and also a brief description of Rock Mass Rating (RMR), Rock Structure Rating (RSR), Q valves and New Austrian Tunneling method (NATM)
Geological site investigation for Civil Engineering FoundationsDr.Anil Deshpande
Aim to introduce Preliminary geological Investigations for fulfilling knowledge about geological need to determine engineering properties of foundation rocks and check the suitability & feasibility of site wherein selection of site plays a crucial role to avoid future implications in civil engineering projects.
Introduction
Petrophysic of the rocks
It is the study of the physical and chemical properties of the rocks related to the pores and fluid distribution
Porosity, is ratio between volume of void to the total voids of the rock.
Permeability, is ability of a porous material to allow fluids to pass through it.
Electric, most of the sedimentary rocks don’t have conductivity.
Radiation, clay rocks have 40K, radiate alpha ray.
Hardness, it depends on the cementing material and thickness of the sediments.
WELL LOGGING
The systematic recording of rock properties and it’s fluid contents in wells being drilled or produced to obtain various petrophysical parameters and characteristics of down hole sequences (G.E Archie 1950).
The measurement versus depth or time, or both, of one or more physical properties in a well.
These methods are particularly good when surface outcrops are not available, but a direct sample of the rock is needed to be sure of the lithology.
A wide range of physical parameters can be measured.
In some cases, the measurements are not direct, it require interpretation by analogy or by correlating values between two or more logs run in the same hole.
Provide information on lithology, boundaries of formations and stratigraphic correlation.
Determine Porosity, Permeability, water, oil and gas saturation.
Reservoir modeling and Structural studies… etc.
Types of Well Logging
Logs can be classified into several types under different category
Permeability and lithology Logs
Gamma Ray log
Self Potential [SP] log
Caliber log
Porosity Logs
Density log
Sonic log
Neutron log
Electrical Logs
Resistivity Log
For contact : omerupto3@gmail.com
Boring for exploration; various types of exploratory drills and their applicability Auger, Cable-tool, Odex, Core Drills; Core recovery: single and double tube core barrels, wire line core barrel; Storage of cores; Interpretation of borehole data
It covers seismic method, gravity method, electromagnetic method, magnetic method and radiometric method. all these methods help in mineral exploration
It,s all about Index properties of Rocks.
It can help those students who want to give presentation about this topic.
Also it can give you information about Pocks and very helpful in Geo mechanics.
Influence of geological condition on foundation and design of buildingDarshan Darji
these ppt is about Influence of geological condition on foundation and design of building. This Ppt clear your doubt about this influence of geological condition on foundation and design of building.
Assessment of wear rate is an inseparable section of the saw ability of dimension stone, and an essential task to optimization in the diamond wire saw performance. This research aims to provide an accurate, practical and applicable model for predicting the wear rate of diamond bead based on rock properties using applications and performances of intelligent systems. In order to reach this purpose, 38 cutting test results with 38 different rocks were used from andesites, limestones and real marbles quarries located in eleven areas in Turkey. Prediction of wear rate is determined by optimization techniques like Multilayer Perceptron (MLP) and hybrid Genetic algorithm –Artificial neural network (GA-ANN) models that were utilized to build two estimation models by MATLAB software. In this study, 80% of the total samples were used randomly for the training dataset, and the remaining 20% was considered as testing data for GA-ANN model. Further, accuracy and performance capacity of models established were investigated using root mean square error (RMSE), the coefficient of determination (R2) and standard deviation (STD). Finally, a comparison was made among performances of these soft computing techniques for predicting and the results obtained indicated hybrid GA-ANN model with a coefficient of determination (R2) of training = 0.95 and testing = 0.991 can get more accurate predicting results in comparison with MLP models.
Boring for exploration; various types of exploratory drills and their applicability Auger, Cable-tool, Odex, Core Drills; Core recovery: single and double tube core barrels, wire line core barrel; Storage of cores; Interpretation of borehole data
It covers seismic method, gravity method, electromagnetic method, magnetic method and radiometric method. all these methods help in mineral exploration
It,s all about Index properties of Rocks.
It can help those students who want to give presentation about this topic.
Also it can give you information about Pocks and very helpful in Geo mechanics.
Influence of geological condition on foundation and design of buildingDarshan Darji
these ppt is about Influence of geological condition on foundation and design of building. This Ppt clear your doubt about this influence of geological condition on foundation and design of building.
Assessment of wear rate is an inseparable section of the saw ability of dimension stone, and an essential task to optimization in the diamond wire saw performance. This research aims to provide an accurate, practical and applicable model for predicting the wear rate of diamond bead based on rock properties using applications and performances of intelligent systems. In order to reach this purpose, 38 cutting test results with 38 different rocks were used from andesites, limestones and real marbles quarries located in eleven areas in Turkey. Prediction of wear rate is determined by optimization techniques like Multilayer Perceptron (MLP) and hybrid Genetic algorithm –Artificial neural network (GA-ANN) models that were utilized to build two estimation models by MATLAB software. In this study, 80% of the total samples were used randomly for the training dataset, and the remaining 20% was considered as testing data for GA-ANN model. Further, accuracy and performance capacity of models established were investigated using root mean square error (RMSE), the coefficient of determination (R2) and standard deviation (STD). Finally, a comparison was made among performances of these soft computing techniques for predicting and the results obtained indicated hybrid GA-ANN model with a coefficient of determination (R2) of training = 0.95 and testing = 0.991 can get more accurate predicting results in comparison with MLP models.
Evaluation the Effect of Machining Parameters on MRR of Mild SteelIJSRD
Today’s life is totally based on Internet. Now a days people cannot imagine life without Internet. Information and communication technology plays vital role in today’s online networked society. In today’s life, we are very close to the online social networks. Online social networks are used for posting and sharing information across various social networking sites. But user’s privacy is not maintained by online social networks. For maintaining users sensitive information’s privacy online social networks provides little or no support. For filtering unwanted messages we propose a system using machine learning (ML). Using machine learning in soft classifier content based filtering performed. In proposed system filtering rules (FR’s) are provided for content independent filtering.. Blacklists are used for more flexibility by which filtering choices are increased. Proposed system provides security to the Online Social Networks.
Evaluation the Effect of Machining Parameters on MRR of Mild SteelIJSRD
Turning metal removal is the removal of metal outside diameter of a rotating cylindrical workpiece. As it is used to reduce the diameter. of the work piece generally to a specified dimension and to produce a smooth finish on the metal. Often, the work piece is turned so that the sections have different diameters. As is the machining operation that produces cylindrical. In its basic form, it can be defined as an outer surface machining: Based on the findings of the Pilot study, actual experimentation work will be designed and input machining parameters and their values finalized. The results are expected to show that the response variables (output parameters) strongly influenced by the control factors (input parameters). So, the results which are obtained after experimentation analyzed and modeled for their application in manufacturing industry It is concluded that for MRR be maximum factor Cutting speed has to be at high level 3, Feed has to be at high level & D.O.C has to be at high level.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Neural Tree for Estimating the Uniaxial Compressive Strength of Rock Materials
1. Neural Tree for Estimating the
Uniaxial Compressive Strength
of Rock Materials
Varun Kumar Ojha
ETH Zurich, Switzerland
Deepak Amban Mishra
Indian Institute of Petroleum & Energy, Visakhapatnam, India
Conference: Hybrid Computational Intelligence (HIS 2017)
Paper title:
Authors:
2. Uniaxial Compressive Strength (UCS)
• USC indicate strength of a rock
material
• UCS is used to test failing behavior of
rock material
• In laboratory a instrument
compresses a rock material and
checked when it crack (fail)
• UCS is important test to avoid
unintended event
Image source: Siratovich et al. Article, Physical property relationships of the Rotokawa Andesite,
a significant geothermal reservoir rock in the Taupo Volcanic Zone, New Zealand
July 2014 Geothermal Energy 1(2):10
3. UCS Index test parameters
• Block punch index (BPI),
• Point load strength (Is-50),
• Schmidt rebound hardness (SRH),
• Ultrasonic P-wave velocity (𝑉𝑝)
• Porosity (𝜂 𝑒)
• Density (𝜌)
Rock: before failing
Rock: after failing
Image source: Mohd Ashraf Mohamad Ismail, Laboratory and in-situ rock testing,
Advanced Geotechnical Engineering
4. Rock samples
Figure: Core sample photographs of (a) granite, (b) schistand (c) sandstone, and
corresponding photomicrographs (d, e, and f).
Collected from
Malanjkhand Copper
Project, Malanjkhand,
India; UCIL mine at
Jaduguda, India;
and SCCL,
Kothagudem, India
respectively.
5. Dataset
: : : : : : : :
: : : : : : : :
: : : : : : : :
Total samples: 60
Total input features: 5
Total output feature(s): 1
Training set: 40 randomly
selected samples)
Test set: 20 randomly
selected samples)
6. Computational Intelligence:
Fuzzy Inference System (FIS): Adaptive Neuro-Fuzzy Inference System (ANFIS):
Multi-layer Perceptron (MLP): Heterogeneous Flexible Neural Tree (HFNT):
7. Model Evaluation Criteria and Results
• Root mean squared error (𝑒)
• Correlation coefficient (𝑟)
• Squared of correlation coefficient (𝑟2)
• Number of parameters in the developed model (𝜒)
[1] Mishra DA, Srigyan M, Basu A, Rokade PJ (2015) Soft computing methods for estimating the uniaxial compressive strength of intact rock from index tests. Int J Rock Mech Min Sci 80:418{424
8. Model Evaluation Criteria and Results
• Root mean squared error (𝑒)
• Correlation coefficient (𝑟)
• Squared of correlation coefficient (𝑟2)
• Number of parameters in the developed model (𝜒)
[1] Mishra DA, Srigyan M, Basu A, Rokade PJ (2015) Soft computing methods for estimating the uniaxial compressive strength of intact rock from index tests. Int J Rock Mech Min Sci 80:418{424
The
Best
Model
9. Model Evaluation Criteria and Results
• Root mean squared error (𝑒)
• Correlation coefficient (𝑟)
• Squared of correlation coefficient (𝑟2)
• Number of parameters in the developed model (𝜒)
[1] Mishra DA, Srigyan M, Basu A, Rokade PJ (2015) Soft computing methods for estimating the uniaxial compressive strength of intact rock from index tests. Int J Rock Mech Min Sci 80:418{424
Best 𝑒, 𝑟,
𝑟2, and 𝜒
10. Light-weight efficient model (HFNTM)
HFNTM: Ojha et al. (2016) Ensemble of heterogeneous flexible neural trees using multiobjective genetic programming, Applied Soft Computing
13. Conclusion
• UCS from the index tests was best estimated by a light weight a
multiobjective heterogeneous flexible neural tree (HFNTM)
• Among the different types of index tests—destructive indices, non-
destructive indices, and physical properties—the destructive
mechanical rock indices BPI and Is-50 are found to be the best index
tests to estimate the UCS.
