Given the dire need of Computer Engineering students to have unlimited access to computer network equipment and supercomputers featuring high performance computing, Advanced Computer Networks and Cloud Computing Laboratory was launched in 2016 at Khatam University.
The main incentive for launching the Advanced Computer Networks and Cloud Computing Laboratory was offering the opportunity of simulating computer networks and running cloud-based systems. Thanks to the scientific potential and enthusiasm of the professors and students at Khatam University, this laboratory is currently functioning as a descent research site in the field of cloud computing and computer networks.
- Training courses in web-based programming;
- Training courses in Linux operating system;
- Training courses in system virtualization using VMWare Horizon.
Advanced Computer Networks and Cloud Computing Laboratory is currently equipped with seven up-to-date computer systems, an Hp-DL380 server, and a number of Cisco switches, all available to students for carrying out thesis projects. This laboratory offers the following possibilities, among others:
- Presenting a model for decentralized management of cloud computing platforms;
- Predicting the crystal structure of materials in multiple compounds through machine learning;
- Modeling and verification of cyber-physical systems for smart environments;
- Efficient engineering of deep learning models for real-time applications;
- Deep multitask learning for comprehensive visual analysis;
- Big data analysis with the help of machine learning to handle unexpected occurrences;
- Designing a suggestion system for movies in Persian;
- Developing Persian texts using deep learning;
- Finding overlapping sublattices in A3 and A7 lattices;
- Fast cryptographic algorithm for sending images of virtual classes using A5 lattice vector quantization;
- Detecting similar sublattices overlapping the A5 and A5 lattices;
- Secure transmission of medical images by concealing patients’ personal information in the image with the help of discrete wavelet transform and A6 lattice vector quantization;
- Automatic summarization of Instagram social network posts by combining semantic and statistical approaches;
- Classification of encrypted network traffic using deep learning methods;
- Face recognition in security camera images with the help of generative artificial neural networks;
- Authentication of Internet of Things sensors via watermarking;
- Embedding watermarks in deep neural networks;
- Diagnosis of Covid-19 based on patients’ CT scans using machine learning and deep learning;
- Implementation of integer to integer lifted wavelet libraries in Python language;
- Virtual inspection of clothes based on images;
- Enhancing the brightness of dark images for improved performance of self-driving vehicles at night;
- Behavioral modeling and influencing human choices.
Since the establishment of this laboratory, professors and students have managed to publish three articles in top international journals (Q1 rank) and present 15 papers in international conferences.