Polar plots represent data using polar coordinates rather than Cartesian coordinates. They graph data points using radial distance (r) from the center and angle (θ). Polar plots are useful for visualizing cyclical or directional data like waves, oscillations, or radar signals. They contain a radial axis for distance r, an angular axis marked in degrees or radians, and gridlines to aid interpretation. Data points are specified by their r and θ values and can be plotted as lines, scatter points, or filled areas. Polar plots see wide application in fields like engineering, physics, navigation, and more.
Prelude
PART (A) TYPES OF GRAPHS
Line graphs
Pie charts
Bar graph
Scatter plot
Stem and plot
Histogram
Frequency polygon
Frequency curve
Cumulative frequency or ogives
PART (B) FLOW CHART
PART (C) LOG AND SEMILOG GRAPH
In this video Data Graphics has been discussed. How the data can be presented with the help of different line graph, poly graph, bar diagram, histogram and Scatter plot and semi logarithmic plot/graph.
Portion completed:
1.DATA GRAPHICS
2. REPRESENTATION OF DATA
3. line graph,
4. poly graph,
5. bar diagram,
6. histogram
7. Pie diagram
8. Wind rose and star diagram
9. Flow Charts
10. Simple Bar Diagram
11. Line and Bar Graph
12. Multiple Bar Diagram
13. Compound Bar Diagram
14. Pie Diagram
15. Scatter plot
16. Semi-log plot
One of most important topics in ArcGIS and GIS, is coordinate system, the slides will cover this topic in order to understand the difference between various coordinate systems.
Prelude
PART (A) TYPES OF GRAPHS
Line graphs
Pie charts
Bar graph
Scatter plot
Stem and plot
Histogram
Frequency polygon
Frequency curve
Cumulative frequency or ogives
PART (B) FLOW CHART
PART (C) LOG AND SEMILOG GRAPH
In this video Data Graphics has been discussed. How the data can be presented with the help of different line graph, poly graph, bar diagram, histogram and Scatter plot and semi logarithmic plot/graph.
Portion completed:
1.DATA GRAPHICS
2. REPRESENTATION OF DATA
3. line graph,
4. poly graph,
5. bar diagram,
6. histogram
7. Pie diagram
8. Wind rose and star diagram
9. Flow Charts
10. Simple Bar Diagram
11. Line and Bar Graph
12. Multiple Bar Diagram
13. Compound Bar Diagram
14. Pie Diagram
15. Scatter plot
16. Semi-log plot
One of most important topics in ArcGIS and GIS, is coordinate system, the slides will cover this topic in order to understand the difference between various coordinate systems.
Data models are a set of rules and/or constructs used to describe and represent aspects of the real world in a computer. GIS can handle four data models for various applications. This module explains those four.
Cylindrical and spherical coordinates shalinishalini singh
In this Presentation, I have explained the co-ordinate system in three plain. ie Cylindrical, Spherical, Cartesian(Rectangular) along with its Differential formulas for length, area &volume.
Data models are a set of rules and/or constructs used to describe and represent aspects of the real world in a computer. GIS can handle four data models for various applications. This module explains those four.
Cylindrical and spherical coordinates shalinishalini singh
In this Presentation, I have explained the co-ordinate system in three plain. ie Cylindrical, Spherical, Cartesian(Rectangular) along with its Differential formulas for length, area &volume.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
An Approach to Detecting Writing Styles Based on Clustering Techniquesambekarshweta25
An Approach to Detecting Writing Styles Based on Clustering Techniques
Authors:
-Devkinandan Jagtap
-Shweta Ambekar
-Harshit Singh
-Nakul Sharma (Assistant Professor)
Institution:
VIIT Pune, India
Abstract:
This paper proposes a system to differentiate between human-generated and AI-generated texts using stylometric analysis. The system analyzes text files and classifies writing styles by employing various clustering algorithms, such as k-means, k-means++, hierarchical, and DBSCAN. The effectiveness of these algorithms is measured using silhouette scores. The system successfully identifies distinct writing styles within documents, demonstrating its potential for plagiarism detection.
Introduction:
Stylometry, the study of linguistic and structural features in texts, is used for tasks like plagiarism detection, genre separation, and author verification. This paper leverages stylometric analysis to identify different writing styles and improve plagiarism detection methods.
Methodology:
The system includes data collection, preprocessing, feature extraction, dimensional reduction, machine learning models for clustering, and performance comparison using silhouette scores. Feature extraction focuses on lexical features, vocabulary richness, and readability scores. The study uses a small dataset of texts from various authors and employs algorithms like k-means, k-means++, hierarchical clustering, and DBSCAN for clustering.
Results:
Experiments show that the system effectively identifies writing styles, with silhouette scores indicating reasonable to strong clustering when k=2. As the number of clusters increases, the silhouette scores decrease, indicating a drop in accuracy. K-means and k-means++ perform similarly, while hierarchical clustering is less optimized.
Conclusion and Future Work:
The system works well for distinguishing writing styles with two clusters but becomes less accurate as the number of clusters increases. Future research could focus on adding more parameters and optimizing the methodology to improve accuracy with higher cluster values. This system can enhance existing plagiarism detection tools, especially in academic settings.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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Online aptitude test management system project report.pdfKamal Acharya
The purpose of on-line aptitude test system is to take online test in an efficient manner and no time wasting for checking the paper. The main objective of on-line aptitude test system is to efficiently evaluate the candidate thoroughly through a fully automated system that not only saves lot of time but also gives fast results. For students they give papers according to their convenience and time and there is no need of using extra thing like paper, pen etc. This can be used in educational institutions as well as in corporate world. Can be used anywhere any time as it is a web based application (user Location doesn’t matter). No restriction that examiner has to be present when the candidate takes the test.
Every time when lecturers/professors need to conduct examinations they have to sit down think about the questions and then create a whole new set of questions for each and every exam. In some cases the professor may want to give an open book online exam that is the student can take the exam any time anywhere, but the student might have to answer the questions in a limited time period. The professor may want to change the sequence of questions for every student. The problem that a student has is whenever a date for the exam is declared the student has to take it and there is no way he can take it at some other time. This project will create an interface for the examiner to create and store questions in a repository. It will also create an interface for the student to take examinations at his convenience and the questions and/or exams may be timed. Thereby creating an application which can be used by examiners and examinee’s simultaneously.
Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
2. Polar Plot:
A polar plot, also known as a polar graph or polar chart, is a graphical representation of data in a circular
format. It is particularly useful for visualizing data that has a directional or angular component, such as
data involving angles or periodic phenomena. Polar plots are commonly used in various fields, including
engineering, physics, and mathematics, to represent complex data patterns and relationships.
Coordinate System: In a polar plot, data is represented in a polar coordinate system, which is different
from the more common Cartesian coordinate system (x, y). In a polar coordinate system, you have:
•Radial Axis: This is the distance from the center (origin) of the plot to a data point. It corresponds to the
"r" value in polar coordinates.
•Angular Axis: This is the angle measured from a reference direction (usually the positive x-axis in
Cartesian coordinates) to the line connecting the origin to the data point. It corresponds to the "θ" value in
polar coordinates.
•Data Points: Each data point in a polar plot is represented by its distance from the origin (r) and the
angle at which it lies (θ). You can use this information to plot data as a series of points, lines, or other
markers in the polar coordinate system.
3. Axes: Polar plots typically have radial gridlines that extend outward from the origin,
with evenly spaced angles marked around the circle. These gridlines help in reading and
interpreting data values.
Scales: The radial and angular axes may have different scales. The radial scale usually
starts from the center and extends outward, while the angular scale often ranges from 0
to 360 degrees or is divided into smaller angular increments.
Data Visualization: Depending on your data and goals, you can use various types of
markers, lines, or curves to represent data points on the polar plot. For example, you
might use lines to connect data points, scatter points to show individual measurements,
or area shading to highlight specific regions.
4. Interpretation: Polar plots are particularly useful for visualizing cyclical or periodic patterns in data. For
example, they are commonly used in radar applications to display the direction and strength of signals.
Scientists and engineers also use polar plots to analyze data related to waves, oscillations, and circular
phenomena.
5. Cartesian Coordinates:
•Explain what Cartesian coordinates are:
• Emphasize that they use two perpendicular axes (x and y) to represent a point's position.
• Describe the x-axis as horizontal and the y-axis as vertical.
• Note that the intersection of these axes is the origin (0, 0).
• Mention that you specify a point's location by providing an x-value and a y-value (e.g., (x, y)).
Polar Coordinates:
•Explain what polar coordinates are:
• Emphasize that they use a different system based on distance (r) and angle (θ).
• Describe the radial axis (r) as representing the distance from the origin to a point.
• Describe the angular axis (θ) as representing the angle between the reference direction (usually the
positive x-axis) and the line connecting the origin to the point.
• Note that polar coordinates provide a different way to specify a point's location compared to
Cartesian coordinates.
6. Components:
•Radial Axis (r):
• Describe the radial axis as the line extending from the center (origin) of the polar plot outward.
• Explain that the radial axis represents the distance (r) from the origin to data points.
• Mention that the radial axis typically contains labeled tick marks and scales to indicate the values
of r.
•Angular Axis (θ):
• Describe the angular axis as the circle around the center of the polar plot.
• Explain that the angular axis represents the angle (θ) measured from a reference direction (often
the positive x-axis) to the line connecting the origin to data points.
• Mention that the angular axis typically contains labeled angles (e.g., 0°, 45°, 90°) or radians.
•Gridlines:
• Highlight the presence of gridlines, which extend from the center to the outer edge of the polar
plot.
• Explain that these gridlines help in reading and interpreting data values.
• Note that gridlines are used to guide measurements and observations
7. Data Points in Polar Coordinates:
•Describe how data points are represented in polar coordinates:
• Emphasize that each data point is defined by two components: distance (r) and angle (θ).
• Explain that "r" represents the radial distance from the origin to the data point.
• Mention that "θ" represents the angle measured counterclockwise from a reference direction (often
the positive x-axis) to the line connecting the origin and the data point.
Data Clustering:
•Discuss how data clustering occurs in polar plots:
• Explain that data points with similar "r" values are located at the same radial distance from the
origin.
• Mention that variations in "θ" values result in data points being distributed angularly around the
origin.
• Use a diagram or visual aid to show clustered data points.
8. Line Plots:
•Describe line plots in polar coordinates:
• Explain that line plots connect data points with lines to visualize relationships or trends.
• Mention when to use them, such as for displaying continuous data patterns.
Scatter Plots:
•Discuss scatter plots in polar coordinates:
• Explain that scatter plots represent individual data points without connecting lines.
• Highlight their usefulness for displaying discrete data points, outliers, or irregular patterns.
Area Plots:
•Introduce area plots in polar coordinates:
• Describe how area plots fill the space between data points, creating shaded regions.
• Explain when to use them, such as for illustrating distributions or proportions.
Combination Plots:
•Mention that it's possible to combine different types of polar plots within a single graph:
• Explain that combination plots allow you to convey multiple aspects of the data simultaneously.
• Provide an example where a combination of line and scatter plots is used effectively.
9. Software Tools:
•Introduce the software tools or programming languages commonly used for creating
polar plots. Examples include:
• MATLAB: Mention that MATLAB has built-in functions for creating polar plots,
making it a popular choice among engineers and scientists.
• Python (with libraries like Matplotlib): Explain that Python offers versatility and
powerful plotting capabilities, including support for polar plots.
• Dedicated Polar Plot Software: Mention that some software packages are
specifically designed for creating polar plots, and they may offer additional
features or ease of use.
10. Steps for creating Polar plots:
•Provide a step-by-step overview of the process for creating polar plots using the chosen
software. This can include:
• Data Preparation: Mention how to format data for polar plots, including the r and
θ values.
• Plotting Functions: Explain which functions or commands to use within the
software to generate the polar plot.
• Customization: Discuss options for customizing the plot's appearance, such as
adjusting line styles, colors, labels, and titles.
• Saving and Exporting: Explain how to save or export the polar plot for use in
presentations or reports.
11. Applications:
Radar Systems:
Radar systems use polar plots to display the direction and strength of radar signals. This is crucial for
tracking aircraft, ships, weather patterns, and more in aviation, maritime, and meteorological
applications.
Antenna Design:
Engineers use polar plots to analyze and optimize the radiation patterns of antennas. It helps in
designing antennas for communication, radar, and satellite systems.
Wave Analysis:
Polar plots are used in physics and engineering to visualize waveforms, interference patterns, and the
behavior of waves in various mediums, including sound waves, electromagnetic waves, and water
waves.
Electrical Engineering:
In electrical engineering, polar plots are used to represent and analyze phasor diagrams, which show
the phase and magnitude relationships of sinusoidal signals. They are crucial for understanding AC
circuits and power systems.
12. Mechanical Engineering:
Engineers studying mechanical vibrations use polar plots to analyze patterns of oscillation and
vibrations in machinery and structures. This is essential for quality control and structural integrity
assessment.
Geophysics and Geology:
In geophysics, polar plots help analyze seismic data, including earthquake waves and subsurface
imaging. Geologists also use them to study the orientation of geological features.
Astronomy:
Astronomers use polar plots to map the positions and orbits of celestial objects such as planets, stars,
and galaxies. This aids in astronomical research, navigation, and celestial mechanics.
Mathematics:
Polar plots are used in mathematics to visualize and analyze polar equations and parametric curves.
They help illustrate mathematical concepts and patterns.
13. Biology:
In biology, polar plots are applied to analyze directional distributions in biological data. For example, they can
be used to study the orientation of animal migrations or the directional distribution of biological particles.
Navigation:
Polar plots are valuable in navigation systems, especially for marine and aviation applications. They assist in
determining positions, headings, and courses, aiding in navigation and collision avoidance.
Materials Science:
Researchers in materials science may use polar plots to study the properties of materials, such as the orientation
of crystalline structures.
Optics:
In optics, polar plots help visualize and analyze the polarization of light waves and their interactions with optical
elements.
Control Systems:
Polar plots are used in control system analysis to assess stability and performance characteristics of control
systems, particularly in the frequency domain.