misc changes

Author: Arthod

_projects/bzip2_in_java_project.md

@@ -15,11 +15,11 @@ This pipeline improves compressibility by first rearranging input data into runs
 
 My bachelor thesis focused on implementing the bzip2 compression and decompression pipeline in Java, and analyzing the performance and contribution of the individual components to the overall compression process. We further experiment with different configurations to the standard pipeline and suggest improvements to the algorithm while retaining backwards compatibility.
 
-The thesis was supervised by [Prof. Rolf Fagerberg](https://imada.sdu.dk/u/rolf/).
+The thesis was supervised by Prof. [Rolf Fagerberg](https://imada.sdu.dk/u/rolf/).
 
 ## Thesis and Source Code
 
-- Thesis available [here](assets/pdf/bzip2_bachelor_thesis.pdf) in pdf.
+- Thesis available [here](/assets/pdf/ahmadothman-bachelorproject.pdf) in pdf.
 - Implementation can be found in the GitHub repository [Bzip2-in-Java](https://github.com/Arthod/Bzip2-in-Java).
 
 ## References

_projects/ihtc2024_project.md

@@ -10,7 +10,7 @@ related_publications: false
 
 The [Integrated Healthcare Timetabling Competition 2024](https://ihtc2024.github.io/) (IHTC 2024) [[1]](#1) was an international competition that challenged participants to develop algorithms for solving a complex integrated healthcare timetabling problem. The competition introduced the problem Integrated Healthcare Timetabling Problem (IHTP), which integrates several NP-hard subproblems found in healthcare scheduling, including patient scheduling, nurse rostering and operating theatre scheduling.
 
-As part of a team of two, [Prof. Marco Chiarandini](https://imada.sdu.dk/u/marco) and I, we ranked 2nd in the competition and 1st in the open-source category out of a total of 32 teams across the world. Our solution was a multi-neighborhood, lexicographic local search algorithm that consisted of two phases: a simulated annealing phase followed by an iterated local search phase. The solver is available in our [GitHub repository](https://github.com/Arthod/ihtc2024-imada-submission).
+As part of a team of two, Prof. [Marco Chiarandini](https://imada.sdu.dk/u/marco) and I, we ranked 2nd in the competition and 1st in the open-source category out of a total of 32 teams across the world. Our solution was a multi-neighborhood, lexicographic local search algorithm that consisted of two phases: a simulated annealing phase followed by an iterated local search phase. The solver is available in our [GitHub repository](https://github.com/Arthod/ihtc2024-imada-submission).
 
 The algorithm was implemented in C++ and was largely structured around the [ROAR-NET API specification](https://github.com/roar-net/roar-net-api-spec), with various modifications focused on performance. Because of this, our result was featured in a [news article from the ROAR-NET](https://roar-net.eu/news/ihtc-2024-best-oss-prize/).