Kazi Md. Al-Wakil

In this project we built a whole network for a given scenario. There were many constraints which we had to take into consideration. The main objective was to create a system where we can set up network by which we can communicate with the whole network given some constraints.

I have developed a full-stack web application where students, faculties, staff of BRAC University can Rent anything. It's not very uncommon for us to leave important things behind at home when we actually need it. For example, we might forget to take our calculator with us when we are having a math exam or we forget to take our charger but we need to charge our phone at university.In these cases, the website will be handy. Users can rent almost any necessary things from here.

A 4-bit ALU was designed in Verilog to perform four bit-wise operations (X-NOR, SUB, NAND, ADD) on two 4-bit inputs, A and B, based on a 3-bit opcode. The ALU produces a 4-bit output, C, and three flags- carry, zero, and sign, indicating the result of the operation. The project was implemented using Quartus.

This machine learning project aims to classify whether a person has diabetes based on a dataset sourced from Kaggle, originally provided by the National Institute of Diabetes and Digestive and Kidney Diseases. The dataset includes diagnostic measurements to predict the presence of diabetes. After pre-processing the data, it was split into 75% for training and 25% for testing. Three classification models were used to achieve the prediction- Decision Tree, Random Forest, and K-Neighbors Classifier. The project demonstrates the application of machine learning techniques in healthcare diagnostics.

This web application was developed for the Database Management System (CSE370) course at BRAC University to manage a football club's operations. The site offers two views- User View and Admin View. Users can purchase jerseys, merchandise, and other products from the club shop, with features like product search, price sorting, and access to their purchase history. Admins have the ability to add, update, and delete products, as well as manage players and board members in the database. Board members can log in as admins to inspect the website and view management details of the club shop. The project was built using HTML, CSS, PHP, and MySQL.

This project focuses on predicting the confidence of forest fires based on various attributes related to different cases and areas of forest fires. The goal is to better understand when wildfires are likely to occur and estimate their severity. As a regression problem, the project employs several machine learning models, including Linear Regression, Decision Tree, Random Forest, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), AdaBoost, Ridge Regression, and Lasso Regression. To assess the performance of these models, the Root Mean Square Error (RMSE) is used as the evaluation metric. The ultimate aim is to predict the likelihood and intensity of forest fires, which can assist in better forest management and preparedness.

This project aims to enhance security in parking lots by ensuring that vehicles cannot be removed without valid authentication. Upon arrival, drivers must enroll their fingerprints, which are stored in a database linked to their vehicle ID. A 16x2 LCD display shows available parking slots and the parking lot's temperature, while a temperature and humidity sensor controls the activation of a heater if needed. The IR proximity sensor detects vehicle presence, and the servo motor opens the gate when there are empty slots. When leaving, the driver must authenticate via the fingerprint sensor. If the fingerprint matches the database, the gate opens, indicated by a green LED; otherwise, the driver is flagged. The system uses an Arduino Uno and various sensors for implementation.

During the 2022 FIFA World Cup, a group of friends created a fun project to predict the score of every match before it began, adding excitement to the event. The system, implemented on Google Sheets, allowed participants to predict match outcomes based on certain criteria, earning points for accurate predictions. The person with the most points at the end of the tournament was crowned the winner. The project aimed to enhance the enjoyment of the World Cup while fostering friendly competition among participants.