changed language button design, extracted image meta data into new config file
This commit is contained in:
@@ -0,0 +1,39 @@
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{
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"images": [
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{
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"id": "pixelcnn_1",
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"image": "images/mnist_conditioned_gen_results_cropped.png",
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"image_pos": "center"
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},
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{
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"id": "pixelcnn_2",
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"image": "images/seminararbeit.png",
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"image_pos": "left"
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},
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{
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"id": "boardgame_1",
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"image": "images/boardgame_demo.png",
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"image_pos": "center"
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},
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{
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"id": "boardgame_2",
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"image": "images/boardgame_connection.png",
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"image_pos": "center"
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},
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{
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"id": "boardgame_3",
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"image": "images/boardgame_ai.png",
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"image_pos": "left"
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},
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{
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"id": "towerdefense_1",
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"image": "images/towerdefense_demo.png",
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"image_pos": "center"
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},
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{
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"id": "personal_website_1",
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"image": "images/personal_website.png",
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"image_pos": "left"
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}
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]
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}
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+21
-8
@@ -10,10 +10,17 @@
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<body>
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<aside class="sidebar">
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<div id="sidebar-top">
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<h3 id="sidebar-top-head">Marvin Kraußer</h3>
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<div id="sidebar-top-content"></div>
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<div class="lang-dropdown">
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</div>
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<nav id="navbar">
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</nav>
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<div class="sidebar-bottom-margin">
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<div class="lang-dropdown" id="lang-dropdown">
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<button id="lang-button">Sprache</button>
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<div id="lang-menu" class="lang-menu hidden">
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@@ -21,14 +28,13 @@
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<div class="lang-item hidden" data-lang="en">en</div>
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</div>
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</div>
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</div>
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<nav id="navbar">
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</nav>
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<div id="sidebar-bottom">
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<a target="_blank" link.rel="noopener noreferrer"
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href="https://github.com/marvinkrausser">github.com/marvinkrausser ↗</a>
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<a href="mailto:marvin.krausser277@gmail.com">marvin.krausser277@gmail.com</a>
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</div>
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</div>
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</aside>
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<div class="main-content">
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@@ -94,6 +100,8 @@
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async function loadData() {
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const response = await fetch(`./lang/${lang}.json`);
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const image_response = await fetch(`./config/img_config.json`)
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const image_config = await image_response.json()
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const data = await response.json();
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const website_title = document.getElementById("website_title");
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@@ -218,7 +226,10 @@
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const block_image = document.createElement("div");
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const image = document.createElement("img");
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image.src = content.image;
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const image_id = content.image;
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const image_object = image_config.images.find(img => img.id === image_id);
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image.className = image_object.image_pos;
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image.src = image_object.image;
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image.loading = "lazy";
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block_image.appendChild(image);
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@@ -285,16 +296,16 @@
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const button = document.getElementById("lang-button");
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const menu = document.getElementById("lang-menu");
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const items = document.querySelectorAll(".lang-item");
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const dropdown = document.getElementById("lang-dropdown");
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button.textContent = lang;
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button.addEventListener("click", () => {
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items.forEach(item => {
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if (item.dataset.lang != lang) {
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item.classList.toggle("hidden");
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}
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item.classList.toggle("hidden", item.dataset.lang == lang);
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});
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menu.classList.toggle("hidden");
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dropdown.classList.toggle("show-border");
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});
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items.forEach(item => {
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@@ -303,6 +314,7 @@
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button.textContent = item.textContent;
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menu.classList.add("hidden");
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dropdown.classList.remove("show-border");
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items.forEach(element => {
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element.classList.add("hidden");
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});
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@@ -315,6 +327,7 @@
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document.addEventListener("click", (e) => {
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if (!e.target.closest(".lang-dropdown")) {
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menu.classList.add("hidden");
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dropdown.classList.remove("show-border");
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items.forEach(element => {
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element.classList.add("hidden");
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});
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+7
-7
@@ -23,12 +23,12 @@
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{
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"heading": "Bildgenerierung mit Deep Learning",
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"text": "Das Modell verwendet Convolutional Neural Networks und Deep Learning zur Generierung von Bildern. Als Trainingsdatensatz wurden die MNIST-Digits verwendet und mittels CUDA auf einer GPU trainiert. Zusätzlich kann das Modell gezielt mit Klassen als Eingabe gesteuert werden, wie im Beispiel mit den Ziffern von 0 bis 9 gezeigt. Aufgrund begrenzter Ressourcen ist mein Modell auf Datensätze mit niedriger Komplexität beschränkt.",
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"image": "images/mnist_conditioned_gen_results_cropped.png"
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"image": "pixelcnn_1"
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},
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{
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"heading": "Seminararbeit",
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"text": "Zusätzlich zum Projekt wurde eine --link-- und ein --link-- erstellt.",
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"image": "images/seminararbeit.png",
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"image": "pixelcnn_2",
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"links": [
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{
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"id": "seminararbeit",
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@@ -60,7 +60,7 @@
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{
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"heading": "Client",
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"text": "Der Game Client wurde mit Unity und C# entwickelt und basiert auf einem rundenbasierten Bewegungs- und Kartensystem. Sämtliche Designs wurden eigenständig erstellt. Auch ein --link-- und --link-- wurden erstellt.",
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"image": "images/boardgame_demo.png",
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"image": "boardgame_1",
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"links": [
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{
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"id": "entwicklerhandbuch",
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@@ -77,12 +77,12 @@
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{
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"heading": "Server",
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"text": "Der Server wurde in C# mit einer mehrschichtigen Architektur umgesetzt, die eine klare Trennung zwischen WebSocket-Verbindungsmanagement und spielbezogener Logik (z. B. Spielerzuweisung und Sitzungsverwaltung) ermöglicht. Die Kommunikation zwischen Server und Client wurde durch ein definiertes JSON-Schema standardisiert, um die Kompatibilität und Austauschbarkeit der von verschiedenen Entwicklerteams entwickelten Komponenten sicherzustellen.",
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"image": "images/boardgame_connection.png"
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"image": "boardgame_2"
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},
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{
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"heading": "KI-Spieler",
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"text": "Zusätzlich wurden mehrere regelbasierte KI-Spieler implementiert, die in das System integriert werden können. Die Codequalität wurde durch automatisierte Tests sichergestellt. Die Zusammenarbeit im Team erfolgte nach agilen Methoden (Scrum), und Server sowie KI wurden containerbasiert mit Docker bereitgestellt.",
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"image": "images/boardgame_ai.png"
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"image": "boardgame_3"
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}
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]
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},
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@@ -107,7 +107,7 @@
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{
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"heading": "Singleplayer Tower Defense Game",
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"text": "Einfaches Tower-Defense-Spiel das von Grund auf mit eigenen Designs erstellt wurde. Nutzt den A*-Algorithmus zur Berechnung des Laufweges. Ein Demo-Build ist im Github Repository vorhanden.",
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"image": "images/towerdefense_demo.png"
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"image": "towerdefense_1"
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}
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]
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},
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@@ -126,7 +126,7 @@
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{
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"heading": "Technisches",
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"text": "Die Website wurde mit HTML, CSS und JavaScript ohne die Verwendung externer Libraries entwickelt. Der Inhalt ist in sprachspezifischen JSON-Dateien gespeichert. Die Website wird dynamisch mithilfe von JavaScript aus der jeweiligen JSON-Datei generiert. Das Git-Repository verwendet einen Feature-Branch-Workflow, um die Korrektheit der Website auch während der Entwicklung sicherzustellen.",
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"image": "images/personal_website.png"
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"image": "personal_website_1"
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}
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]
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}
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+7
-7
@@ -23,12 +23,12 @@
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{
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"heading": "Image generation with Deep Learning",
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"text": "The model uses Convolutional Neural Networks and deep learning to generate images. The MNIST digits dataset was used for training, and the model was trained on a GPU using CUDA. Additionally, the model can be specifically controlled with class inputs, as shown in the example with digits from 0 to 9. Due to limited resources, my model is restricted to low-complexity datasets.",
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"image": "images/mnist_conditioned_gen_results_cropped.png"
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"image": "pixelcnn_1"
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},
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{
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"heading": "Seminar paper",
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"text": "A --link-- and --link-- were created alongside the Project.",
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"image": "images/seminararbeit.png",
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"image": "pixelcnn_2",
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"links": [
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{
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"id": "seminararbeit",
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@@ -60,7 +60,7 @@
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{
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"heading": "Client",
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"text": "The game client was developed using Unity and C# and is based on a turn-based movement and card system. All designs were created independently. A --link-- and --link-- were also created.",
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"image": "images/boardgame_demo.png",
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"image": "boardgame_1",
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"links": [
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{
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"id": "entwicklerhandbuch",
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@@ -77,12 +77,12 @@
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{
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"heading": "Server",
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"text": "The server was implemented in C# using a layered architecture that ensures a clear separation between WebSocket connection management and game-related logic (e.g. player assignment and session management). Communication between server and client was standardized using a defined JSON schema to ensure compatibility and interchangeability of components developed by different teams.",
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"image": "images/boardgame_connection.png"
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"image": "boardgame_2"
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},
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{
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"heading": "AI Players",
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"text": "In addition, several rule-based AI players were implemented that can be integrated into the system. Code quality was ensured through automated tests. Team collaboration followed agile methods (Scrum), and both server and AI were deployed using Docker containers.",
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"image": "images/boardgame_ai.png"
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"image": "boardgame_3"
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}
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]
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},
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@@ -107,7 +107,7 @@
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{
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"heading": "Singleplayer Tower Defense Game",
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"text": "Simple tower defense game created entirely from scratch with custom designs. Uses the A* algorithm to calculate the pathfinding route. A demo build is available in the GitHub repository.",
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"image": "images/towerdefense_demo.png"
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"image": "towerdefense_1"
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}
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]
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},
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@@ -126,7 +126,7 @@
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{
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"heading": "Technical details",
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"text": "The website was developed using HTML, CSS, and JavaScript without the use of external libraries. The content is stored in language-specific JSON files. The website is dynamically generated using JavaScript based on the respective JSON file. The Git repository follows a feature-branch workflow to ensure correctness of the website even during development.",
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"image": "images/personal_website.png"
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"image": "personal_website_1"
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}
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]
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}
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+60
-30
@@ -9,6 +9,7 @@
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--sans: 'DM Sans', system-ui, sans-serif;
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--nav-w: 230px;
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--font-size: 17px;
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--margin-main-content: 100px;
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}
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@media (prefers-color-scheme: dark) {
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@@ -67,21 +68,36 @@ a {
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display: flex;
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gap: 3px;
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margin-top: 10px;
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width: 83px;
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width: 91px;
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height: 40px;
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display: flex;
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justify-content: center;
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align-items: center;
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border: none;
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background: none;
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margin-bottom: 10px;
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}
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.lang-dropdown.show-border {
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border: 1px solid var(--border);
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border-radius: 8px;
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background: var(--bg2);
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}
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.lang-menu {
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display: flex;
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align-items: center;
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gap: 3px;
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margin-top: 5px;
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}
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.lang-item {
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cursor: pointer;
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background-color: var(--surface);
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width: 40px;
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height: 20px;
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text-align: center;
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height: 24px;
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display: flex;
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align-items: center;
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justify-content: center;
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border: 1px solid var(--border);
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border-radius: 8px;
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color: var(--muted);
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@@ -187,10 +203,16 @@ option {
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font-size: 13px;
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}
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.sidebar-bottom-margin {
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margin-top: auto;
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display: flex;
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flex-direction: column;
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align-items: center;
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}
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#sidebar-bottom {
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padding: 36px 32px 28px;
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border-top: 1px solid var(--border);
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margin-top: auto;
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display: flex;
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flex-direction: column;
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gap: 14px;
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@@ -208,9 +230,9 @@ option {
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#introduction {
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padding-top: 100px;
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margin-left: 60px;
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margin-left: var(--margin-main-content);
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margin-bottom: 60px;
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margin-right: 100px;
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margin-right: var(--margin-main-content);
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}
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#introduction p {
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@@ -227,15 +249,15 @@ option {
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}
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.content-block {
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height: 400px;
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height: 600px;
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display: grid;
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grid-template-columns: 1fr 1fr;
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}
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.section-header {
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margin: 80px;
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margin-left: 60px;
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margin-right: 40%;
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margin-left: var(--margin-main-content);
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margin-right: var(--margin-main-content);
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}
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.tags {
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@@ -263,34 +285,48 @@ option {
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overflow: hidden;
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border-top: 1px solid var(--border);
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border-bottom: 1px solid var(--border);
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display: flex;
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}
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.block-image.right {
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margin-right: 60px;
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margin-right: var(--margin-main-content);
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border-left: 1px solid var(--border);
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justify-content: left;
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}
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.block-image.left {
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margin-left: 60px;
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margin-left: var(--margin-main-content);
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border-right: 1px solid var(--border);
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justify-content: right;
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}
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.block-image img {
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height: 100%;
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width: 100%;
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max-width: 700px;
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max-height: 700px;
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object-fit: cover;
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}
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.block-image img.left {
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object-position: left;
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}
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.block-image img.center {
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object-position: center;
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}
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.block-image img.right {
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object-position: right;
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}
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.block-text {
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display: flex;
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flex-direction: column;
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justify-content: center;
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border-top: 1px solid var(--border);
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overflow: hidden;
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}
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.block-text.right {
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margin-right: 60px;
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padding-left: 60px;
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}
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.block-text.left {
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padding-right: 60px;
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margin-left: 60px;
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margin-right: var(--margin-main-content);
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padding-left: var(--margin-main-content);
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}
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.text-content {
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@@ -302,12 +338,6 @@ option {
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font-weight: normal;
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}
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.block-image img {
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width: 100%;
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height: 100%;
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object-fit: cover;
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}
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.text-link:hover {
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border-color: var(--text);
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}
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@@ -325,7 +355,7 @@ option {
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}
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.link-row {
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margin: 60px;
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margin: var(--margin-main-content);
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margin-top: 30px;
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}
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