Multi-Version PYZ Builder Script: A Universal Python Module Creation Tool حسب Pavel Izosimov (20096259)

"…By implementing advanced security measures such as <a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank"><b>end-to-end encryption</b></a>, <a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank"><b>asymmetric encryption</b></a>, and <a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank"><b>symmetric encryption</b></a>, the platform strives to keep code better protected during transmission and execution.Explore other tools offered by Alpha Beta Network:</p><ul><li><a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank"><b>Secure Python Code Manager</b></a>: A command-line tool for secure Python code sharing and protection using the Alpha Beta Network cloud platform.…"

Parallel plot showing hyperparameter exploration. حسب Ramona Leenings (11167294)

Comparative analysis of WordNet replacement impact on data distribution. حسب Enock Niyonkuru (21246879)

(3a) Paradigms, computer languages and their syntax.pdf حسب Paul A. Gagniuc (1818325)

(3a) Paradigms, computer languages and their syntax.pptx حسب Paul A. Gagniuc (1818325)

(3b) Paradigms, computer languages and their syntax.pptx حسب Paul A. Gagniuc (1818325)

(3c) Paradigms, computer languages and their syntax.pptx حسب Paul A. Gagniuc (1818325)

(3b) Paradigms, computer languages and their syntax.pdf حسب Paul A. Gagniuc (1818325)

BOFdat Step 3: Identifying species-specific metabolic end goals. حسب Jean-Christophe Lachance (6619307)

(3c) Paradigms, computer languages and their syntax.pdf حسب Paul A. Gagniuc (1818325)

DataSheet1_MATLAB Implementation of Physics Informed Deep Neural Networks for Forward and Inverse Structural Vibration Problems.PDF حسب Tanmoy Chatterjee (9968759)

"…As a bonus, complete executable codes of all four representative (both forward and inverse) problems in structural vibrations have been provided along with their line-by-line lucid explanation and well-interpreted results for better understanding.…"

Search-based testing (Genetic Algorithm) - Chapter 11 of the book "Software Testing Automation" حسب Saeed Parsa (13893726)

"…</p> <p><br></p> <p>The following function instrumen_input_file, takes a function, func, as input and instruments the function by adding probes to compute the branch distance for each condition within a predicate. </p> <pre><code>def instrument_input_file(func):<br> <br> <br> <br>    </code></pre> <pre><code># converts the source code into a stream<br> <br> <br> <br>     </code></pre> <pre><code>     source = inspect.getsource(func)<br> <br> <br> <br>    </code></pre> <pre><code> # Build a parse tree for the input source<br> <br> <br> <br>    </code></pre> <pre><code>     tree = ast.parse(source)<br> <br> <br> <br>    </code></pre> <pre><code> # While traversing the parse tree instrument, the AST<br> <br> <br> <br>     </code></pre> <pre><code>      BranchTransformer().visit(tree)<br> <br> <br> <br>    </code></pre> <pre><code> # Removes extra blank lines and spaces<br> <br> <br> <br>     </code></pre> <pre><code>       tree = ast.fix_missing_locations(tree)<br> <br> <br> <br>    </code></pre> <pre><code> # Instrument the source code based on the AST instrumentation<br> <br> <br> <br>  </code></pre> <pre><code>       save_as_instrumented_python(astor.to_source(tree), </code></pre> <pre><code>        <strong>"nameeeeeeeeeeeeeeeeeeeeee"</strong>)<br> <br> <br> <br>     </code></pre> <pre><code># We are in the main<br> <br> <br> <br>     </code></pre> <pre><code>      current_module = sys.modules[__name__]<br> <br> <br> <br>     </code></pre> <pre><code>       code = compile(node, filename=<strong>""</strong>, </code></pre> <pre><code>                                  mode=<strong>"exec"</strong>)<br> <br> <br> <br>   </code></pre> <pre><code>         exec(code, current_module.…"

Data_Sheet_1_The Dmipy Toolbox: Diffusion MRI Multi-Compartment Modeling and Microstructure Recovery Made Easy.PDF حسب Rutger H. J. Fick (7497242)

"…In particular, Dmipy is geared toward facilitating reproducible, reliable MC-modeling pipelines, often allowing the whole process from model construction to parameter map recovery in fewer than 10 lines of code. To demonstrate Dmipy's ease of use and potential, we implement a wide range of well-known MC-models, including IVIM, AxCaliber, NODDI(x), Bingham-NODDI, the spherical mean-based SMT and MC-MDI, and spherical convolution-based single- and multi-tissue CSD. …"

Advancing Solar Magnetic Field Modeling حسب Carlos António (21257432)

"…<br><br>We developed a significantly faster Python code built upon a functional optimization framework previously proposed and implemented by our team. …"