Eco-Sakhteman: A Web Application for Pre-Feasibility of Construction Projects
As a backend developer, I was part of a cross-functional team that developed Eco-Sakhteman, a web application that helps users to prepare pre-feasibility reports for construction projects. Eco-Sakhteman allows users to input various parameters such as project location, size, budget, and duration, and then calculates five key indicators such as net present value (NPV), internal rate of return (IRR), payback period, benefit-cost ratio, and profitability index. These indicators help users to evaluate the economic viability and sustainability of their projects. Eco-Sakhteman also provides users with a graphical representation of the cash flow and the sensitivity analysis of the project. The web application was developed using ASP.NET framework and SQL Server database. I was responsible for designing and implementing the backend logic and the database schema, as well as integrating the frontend components with the backend services. I also wrote unit tests and documentation for the backend code. Eco-Sakhteman is a user-friendly and reliable web application that can assist users in making informed decisions about their construction projects.
Neuro 22 (EMG Signals Analysis Software)
Neuro 22 is a software that I have developed for analyzing electromyography (EMG) signals. Neuro 22 is a comprehensive and user-friendly software that offers seven types of tests and a capability to generate reports in Word and PDF formats based on the performed tests. Some of the features of Neuro 22 include:
- Real-time visualization of EMG signals and their frequency spectrum
- Automatic detection and removal of artifacts and noise
- Exporting and importing of EMG tests data in specific format.
- Customizable settings and preferences for each test and user
By developing Neuro 22, I have demonstrated my skills and expertise in software engineering, signal processing and user interface design. I have also contributed to the advancement of EMG research and applications by providing a powerful and versatile tool that can handle complex and diverse EMG data. My work on Neuro 22 has increased the final product’s value by about 15% and has received positive feedback from the clients and users.
Price Prediction Approach For Tehran Stock Exchange:
I have developed and presented an innovative approach for price prediction in Tehran Stock Exchange (TSE), one of the largest stock exchanges in the Middle East. My approach focused on predicting the prices of special indexes. I used ML.Net, a cross-platform and open-source machine learning framework for .Net developers, to implement my approach. I applied various machine learning techniques, such as data preprocessing, feature engineering, model selection, training, testing, and evaluation, to create a robust and accurate price prediction system. My system achieved an average relative error percentage of 8%, which means that it was able to predict the prices of the indexes with a high degree of accuracy and reliability. My approach and system were recognized as the best (1st place) among the participants of the AmirKabir Artificial Intelligence Competitions (AAIC), a prestigious and competitive event that showcases the latest research and applications of artificial intelligence in Iran. I received the first place award and a certificate of excellence for my outstanding work. This honor reflects my passion and skill for artificial intelligence and machine learning, as well as my ability to apply them to real-world problems and scenarios.