On Monday, 15/1/2024, the Control and Systems Engineering Department held a workshop entitled (The Main Paragraphs Included in Scientific Research) in the (PC2) Laboratory. The workshop was delivered by (Asst. Lect. Nibras Zayer Saleh) and (Asst. Lect. Attarid Khudair Ahmed) in the presence of a number of the academic staff of the department. The workshop dealt with the steps of writing scientific research, which included choosing the appropriate topic, recording the sources of basic information, as well as collecting and organizing ideas and the main paragraphs that comprise them. 

    On Monday, 15/1/2024, a workshop entitled (Using Mendeley in Referring to Sources) was held in the Control and Systems Engineering Department at the (PC1) Laboratory. The workshop was delivered by (Asst. Prof. Farah Flaih Hassan) and (Asst. Lect. Russell Adel Kadhum) in the presence of a number of the academic staff of the department. The workshop covered an introduction to the program, its importance, how to install it and connect it to the MS Word program, and how to use it to indicate references and change the signal style according to the available styles. 

    On 18/1/2024, the master’s thesis submitted by the graduate student (Dhoha Firas Jassim) majoring in (Computer Engineering) was discussed in the Discussion Hall (Hall No. 9) at the Control and Systems Engineering Department. The thesis is entitled “Hand-free Human-Computer Interface Based on Mouth Microgestures”.

The discussion committee consisted of:

1- Asst. Prof. Dr. Mona Muhammad Jawad / Chairwoman

2- Asst. Prof. Dr. Mahmoud Zaki Abdullah / Member

3- Lect. Dr. Haider Da’ami Rissan / Member

4- Lect. Dr. Walid Fawaz Sharif / Member and Supervisor

Tongue-based human interaction systems have emerged as an alternative to other input devices, as human interaction systems technology has improved the user experience in various applications, such as medical and security applications, self-driving vehicles, and smart wearable devices. This application is especially useful for individuals with severe disabilities. However, human tongue interaction systems often rely on invasive surgical methods, including dental retainers, tongue piercings, and multiple oral electrodes, which are impractical for daily use due to hygiene concerns and discomfort. This study proposes the use of deep learning methods to analyze and detect subtle tongue-based gestures for non-intrusive systems. By addressing the aforementioned limitations, the system detects gestures non-intrusively by measuring tongue vibrations using an accelerometer placed on the genioglossus muscle, eliminating the need for intraoral fixtures. To evaluate the classification results, the deep learning results were compared with those of four widely used machine learning algorithms, including Decision Tree, Random Forest, SVM, and KNN. The raw data was pre-processed in the time and frequency domains to extract classification patterns, which uses CNN machine learning layers and pooling. The raw data was used in a deep learning model to process temporal data and automatically capture complex patterns. The discussion was attended by the Assistant Head of the Department for Scientific Affairs and Postgraduate Studies (Prof. Dr. Abbas Hussein Issa). On this occasion, we congratulate the student (Dhoha Firas Jassim) and wish her continued success.