Computational language have been used in physics research
for many years and there is a plethora of programs and packages on the Web which can be used to solve dierent problems. In this report I trying to use as many of these available solutions as possible and not reinvent the wheel. Some of these packages have been written in C program. As I stated above, physics relies heavily on graphical representations. Usually,the scientist would save the results
from some calculations into a file, which then can be read and used for display by a graphics package like Gnuplot.
Computational language have been used in physics research
for many years and there is a plethora of programs and packages on the Web which can be used to solve dierent problems. In this report I trying to use as many of these available solutions as possible and not reinvent the wheel. Some of these packages have been written in C program. As I stated above, physics relies heavily on graphical representations. Usually,the scientist would save the results
from some calculations into a file, which then can be read and used for display by a graphics package like Gnuplot.
A New Double Numerical Integration Formula Based On The First Order DerivativeIRJESJOURNAL
ABSTRACT: A new double numerical integration formula based on the value of integrated function and first order derivative of the integrable function was proposed. Different from the traditional mechanical quadrature formula, contibuted integral function and first order derivative of the integral function. Four nodes are selected appropriately in the integral interval. Used the value of function and first order derivative, constructed a new numerical integration formula that achieve seven order algebraic precision. Then analysed the algebraic precision、 remainder、stypticity and stability of the formula. Then generalized the formula into double integral. In the end, according to the two typical examples vertified the formula’s validity and fesibility. This formula enrich the content of numerical calculation. Provided a new method for solving double numerical integrations.
Numerical Method Analysis: Algebraic and Transcendental Equations (Non-Linear)Minhas Kamal
Numerical Method Analysis- Solution of Algebraic and Transcendental Equations (Non-Linear Equation). Algorithms- Bisection Method, False Position Method, Newton-Raphson Method, Secant Method, Successive Approximation Method.
Visit here for getting code implementation- https://github.com/MinhasKamal/AlgorithmImplementations/blob/master/numericalMethods/equationSolving/NonLinearEquationSolvingProcess.c
Created in 2nd year of Bachelor of Science in Software Engineering (BSSE) course at Institute of Information Technology, University of Dhaka (IIT, DU).
This study presents an improvement to the Brent¡¯s Method by reconstruction. The Brent¡¯s Method determines the next iteration interval from two subsections, whereas the new method determines the next iteration interval from three subsections constructed by four given points and thus can greatly reduce the iteration interval length. The new method not only gets more readable but also converges faster. An experiment is made to investigate its performance. Results show that, after simplification, the computational efficiency can greatly be improved.
A New Double Numerical Integration Formula Based On The First Order DerivativeIRJESJOURNAL
ABSTRACT: A new double numerical integration formula based on the value of integrated function and first order derivative of the integrable function was proposed. Different from the traditional mechanical quadrature formula, contibuted integral function and first order derivative of the integral function. Four nodes are selected appropriately in the integral interval. Used the value of function and first order derivative, constructed a new numerical integration formula that achieve seven order algebraic precision. Then analysed the algebraic precision、 remainder、stypticity and stability of the formula. Then generalized the formula into double integral. In the end, according to the two typical examples vertified the formula’s validity and fesibility. This formula enrich the content of numerical calculation. Provided a new method for solving double numerical integrations.
Numerical Method Analysis: Algebraic and Transcendental Equations (Non-Linear)Minhas Kamal
Numerical Method Analysis- Solution of Algebraic and Transcendental Equations (Non-Linear Equation). Algorithms- Bisection Method, False Position Method, Newton-Raphson Method, Secant Method, Successive Approximation Method.
Visit here for getting code implementation- https://github.com/MinhasKamal/AlgorithmImplementations/blob/master/numericalMethods/equationSolving/NonLinearEquationSolvingProcess.c
Created in 2nd year of Bachelor of Science in Software Engineering (BSSE) course at Institute of Information Technology, University of Dhaka (IIT, DU).
This study presents an improvement to the Brent¡¯s Method by reconstruction. The Brent¡¯s Method determines the next iteration interval from two subsections, whereas the new method determines the next iteration interval from three subsections constructed by four given points and thus can greatly reduce the iteration interval length. The new method not only gets more readable but also converges faster. An experiment is made to investigate its performance. Results show that, after simplification, the computational efficiency can greatly be improved.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
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.
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.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Show drafts
volume_up
Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
3. Theory
Root-finding problem: Bisection Method is also called the interval
halving method, the binary search method, or the dichotomy method. is
based on the Bolzano’s theorem for continuous functions.
Intermediate value theorem states that if f is a continuous
function whose domain contains the interval [a, b], then it takes on any
given value between f(a) and f(b) at some point within the interval.
This has two corollaries:
1.If a continuous function has values of opposite sign inside an interval,
then it has a root in that interval (Bolzano's theorem).
2.The image of a continuous function over an interval is itself an interval
3
4. Algorithm
Graphical Interpretation
1.Two values a and b are chosen for which f(a) > 0 and f(b)
< 0 (or the other way around)
2.Bisection: a midpoint c is calculated as the arithmetic
mean between a and b, c = (a + b) / 2
3.The function f is evaluated for the value of c
4.If f(c) = 0 means that we found the root of the function,
which is c
5.If f(c) ≠ 0 we check the sign of f(c):
1.if f(c) has the same sign as f(a) we replace a with c and
we keep the same value for b
2.if f(c) has the same sign as f(b), we replace b with c and
we keep the same value for a
6.We go back to step 2. and recalculate c with the new value
of a or b
We continue in this manner and the process is repeated until
the root is obtained. How close the value of c gets to the real
root depends on the value of the tolerance we set for the
algorithm
4
5. Script File
%define the function
f=@(x)2*x.^3+8*x.^2-20; a=1; b=2; error=10^(-4);
i=1
c=(a+b)/2 %bisection using mean value theorem
d=f(c)
while abs(f(c))>error %defining tolerance
if f(c)<0 && f(a)<0
a=c;
else
b=c;
end
i=i+1
c=(a+b)/2;
d=f(c)
%plot the iterated values using bisection method
x = 1:0.0001:2
plot(c,d,'o');
hold on
end
%plot the final iterated value
plot(c,d,"*")
y=0;
%plot the given function
plot(x, f(x))
z=@(x)0*x;
%plot the x-axis
plot(x,z(x))
hold off
5
7. Plot of the value calculated after ith iterations in Bisection
method
7
8. Plot of the value calculated after 18th iteration (Final step in the given
tolerance) from Bisection method
8
9. Conclusion
• The final value calculated after iterations is shown in the
second plot
• to calculate an approximate root of a function within tolerance
ε, the number n of iterations we need to perform is at least:
n ≥ log((b−a)/ε)/log(2)
here, n≥ 4/log(2) = 13.28 (in accordance with the number of
iterations n=18)
• Iteration terminates when bound for relative error is less than
tolerance, |p-pn|/min{|an|,|bn|}< 10-4
and sequence pn convergence to p with rate of convergence
O(1/2n)
9
10. Caveats
• Bisection Method is a simple root finding method,
easy to implement and very robust.
• However, the disadvantages of this method is that
it’s relatively slow.
• Because of this, most of the time, the bisection
method is used as a starting point to obtain a rough
value of the solution which is used later as a
starting point for more rapidly converging methods.
10