Point-Set Registrations for Ultrasound Probe Calibrations

-Undergraduate Thesis-Updated January 25, 2022 Author: Matteo Tanzi Year: 2022 Purpose: Undergraduate Thesis Currently, algorithms for point-based, line-based and dynamic registrations are being developped to be ported into 3D Slicer as modules Github Repository Structure This github repository contains Jupyter Notebooks and Python Programs The Python Programs are found within the programs folder – descriptions can be found below The Jupyter Notebooks – Found within Documentation – will outline the research and development techniques used for the point-set registration programs, […]

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Analyze Big Sequence Alignments with PySpark in AWS EMR

This repo hosts my code for the article “Analyze Big Sequence Alignments with PySpark in AWS EMR”. Spark AWS CLI AWS Account Follow the instruction in the article. Once you have uploaded the files into your S3 bucket, run aws emr create-cluster –name “Spark_step_pip” –release-label emr-6.5.0 –applications Name=Spark –log-uri s3://[your_S3_bucket]/logs/ –instance-type m5.xlarge –instance-count 3 –bootstrap-actions Path=s3://[your_S3_bucket]/emr_bootstrap.sh –use-default-roles –auto-terminate –steps “Type=Spark,Name=SparkProgram,ActionOnFailure=CONTINUE,Args=[–deploy-mode,cluster,–master,yarn,–py-files,s3://[your_S3_bucket]/helper_function.py,s3://[your_S3_bucket]/spark_3mer.py,s3://[your_S3_bucket]/test.sam,[your_S3_bucket],sankey.json]”    

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Versionsverwaltung & Open Source Hausaufgabe

Herzlich Willkommen zu dieser Hausaufgabe für unseren MOOC: Let’s Git! Wir hoffen, dass Du viel lernen wirst und dabei auch Spaß hast. In dieser Hausaufgabe wirst du eine Webseite zu deinem Lieblingscharakter aus Filmen oder Büchern erstellen. Hier kannst du zwei Beispiele betrachten: Beispiel 1 und Beispiel 2. Du wirst hier den Github Flow üben, aber das wirst du dann in den Aufgaben erkennen. Um die Aufgabe zu starten, folge einfach folgenden Schritten: Nutze dieses Repository als Vorlage für ein […]

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A Celery application to collect data, download media and extract information from social media APIs

A Celery application to collect data, download media and extract information from social media APIs. Requirements You must have a Redis DB instance running (which is currently used as the Celery broker). Also, another DB will probably be used as the Celery backend in the future(if we ever need backend, that is). You must also have a MongoDB instance running as the application’s write layer. Usage Run celery: celery -A app.core.celery.worker worker -l info Note, that Celery does not support […]

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Hammer DDos With Python

$ apt update$ apt upgrade$ apt install python$ apt install git$ apt install dnsutils$ git clone https://github.com … Hammer need the Name Server of a website which you want to attack…To get the Name Server…just type$ nslookup example.comNote the IP Address of that Website then $ cd Hammer$ python hammer.py -s [ip Address] -t 135example:$ python hammer.py -s 123.45.67.89 -t 135 GitHub View Github    

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Looping With Python enumerate()

In Python, a for loop is usually written as a loop over an iterable object. This means that you don’t need a counting variable to access items in the iterable. Sometimes, though, you do want to have a variable that changes on each loop iteration. Rather than creating and incrementing a variable yourself, you can use Python’s enumerate() to get a counter and the value from the iterable at the same time! In this course, you’ll see how to: Use […]

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Sequential prediction learning framework and algorithm

This is the implementation of our paper “Sequential Prediction of Social Media Popularity with Deep Temporal Context Networks“. Dataset To successfully test performance, we created TPIC Dataset, a temporal popularity image collection dataset. Overview Our DTCN contains three main components, from embedding, learning to predicting. With a joint embedding network, we obtain a unified deep representation of multi-modal user-post data in a common embedding space. Then, based on the embedded data sequence over time, temporal context learning attempts to recurrently […]

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Notebook researcher with python

To run the server, you must follow these instructions: At the very beginning, just clone the repo and create a “venv” for it and install the requirements via: pip install -r requirements.txt windows First, you have to install postgresql. The instructions are held in this link below:https://www.postgresqltutorial.com/install-postgresql/ Set “password” and “port” carefully, as you should know them further. Then, open pgadmin and create a database named “notebook_researcher”. After that, open file“quran_django/settings/production.py” and change these items: On line 88, set “Name” […]

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