Chittagong University of Engineering & Technology

About: Chittagong University of Engineering & Technology is a education organization based out in Chittagong, Bangladesh. It is known for research contribution in the topics: Computer science & Renewable energy. The organization has 1200 authors who have published 1444 publications receiving 10418 citations. The organization is also known as: Engineering College, Chittagong & Bangladesh Institute of Technology, Chittagong.

BMGC: A Deep Learning Approach to Classify Bengali Music Genres

Abstract: Music genre classification (MGC) is the process of tagging music with their appropriate genres by analyzing music signals or the lyrics. With the accelerated surge in music data repositories, MGC can be extensively used in music recommendation systems, advertisement, and streaming services for systematic and efficient management. However, there have been many works on English music classification using different statistical and machine learning approaches, but there is no notable progress found in the arena of Bengali music. Besides, a few significant works have been found in utilizing Deep Learning (DL) methods to classify different music genres. Bengali music is significantly enriched with its contents and uniqueness. Moreover, the extent and scope of exploring the DL approach in Bengali music ground are still latent. Therefore, Bengali music genre classification is quite a new research area in the Deep learning field. In this work, we have constructed a Bengali Music Genre Classifier (BMGC) to categorize 6 Bengali music genres: ‘Adhunik’, ‘Band’, ‘Hiphop’, ‘Nazrulgeeti’, ‘Lalon’, and ‘Rabindra Sangeet’. We have created a Bengali music genre classification dataset (hereafter named BMGCD) containing 2944 Bengali music clips, and a Gated Recurrent Unit based deep learning model has been developed to predict the music genre from audio signals. Our developed model achieved an accuracy of 80.4% and 80.6% F1-score which surpasses the related existing works.

Depression Risk Prediction among Tech Employees in Bangladesh using Adaboosted Decision Tree

Abstract: Depression is a major depressive disorder. It is a psychological problem that hampers a person's daily life and decreases productivity. It is becoming a severe problem in our world. People of any age can be depressed. Despite having a flourishing tech industry in Bangladesh, cases of depression among tech employees are highly seen, which eventually leads to an unwanted situation in an employee's professional career and personal life. Depressed employees neither can concentrate on work nor are they able to be productive. This kind of incident is becoming common in the tech industry. For this reason, we are facing problem to achieve our desired goal in the tech industry. People can be depressed for various reasons. Many risk factors that contribute to depression include family problems, work pressure, lack of physical movement, drug abuse, etc. This research aims to predict the depression risk of a tech employee and determine the root cause of depression so that it becomes easier to treat depression at an early stage. To predict depression risk, the authors have used the Adaboosted decision tree. Using this Adaptive boosting technique on the standard decision tree approach, the authors have achieved better accuracy compared to the standard decision tree approach. In adaptive boosting, errors of previous models are corrected. The features of the dataset that were used to train and test the machine learning model was determined by a psychiatrist by rigorous analysis. The features were selected considering risk factors that contribute to depression. The data used for this research was collected under the direct supervision of a psychiatrist and technology expert. The Author's primary purpose of this research is to predict depression at a preventive stage so that necessary measures can be taken to treat depression among tech employees and to avoid unwanted situations.

Waste to energy: an overview by global perspective

Abstract: In this present era, amount of diverse types of waste is increasing day by day. For the insufficient and improper management of waste recycle system, global environment is being polluted tremendously. Every year, approximately 2.12 billion tonnes, a massive amount of waste is being dumped to the open environment worldwide. In this alarming scenario, as intensity of carbon emission is intensified, invention of bioenergy is hailed as a great accomplishment to transform waste to green energy that is environment-friendly and as well as sustainable. In this chapter, a worldwide scenario of both organic and inorganic wastes such as plastics, rubbers, e-waste, numerous biomass wastes, and others has been discussed comprehensively. Various conversion technologies: esterification, trans-esterification, anaerobic digestion, catalytic pyrolysis, and others are emphasized simultaneously in this study. This chapter also highlights perspective and economic potential of different forms of bioenergy such as biodiesel, bioethanol, bio-gas, and others. The review also concerns a detail discussion on greenhouse gas emission reduction upon consumption of bioenergy instead fossil fuels. Along with that, applications of bioenergy in electricity and transportation sector are also showcased. Moreover, projection of the sustainability of waste to energy for upcoming decades has been outlined.

A safe system with safe logistics support for Chittagong Port

Abstract: This paper presents a prototype implementation of an intelligent system called safe system that monitors container security in the port logistics. Logistics supports in the port require safe container status. The main focus of our contribution is to design a system that supports RFID (Radio Frequency Identification) Readers of all types (such as Reader Protocol complaint and vendor provided Readers), real time monitoring of sensing information and notify management about the status of the container in harbor logistics.

Disclosure of Financial Reporting of Islamic Financial Institutes of Bangladesh: A Concept of Relevant Reviews

Abstract: Islamic banking is a system of banking that avoids receipt and payment of interest in its transactions and conducts its operations in accordance with Shariah principles to achieve the objectives of Islamic economy. The main objective of this review paper is to compare the level of disclosure of information by the Islamic Banking sector in Bangladesh. Multiple linear regression techniques will be used to test the hypotheses under study. The findings of this review paper is the supervisory authorities should recognize the need to set up a regulatory framework that, while consistent with Islamic precepts, would be pragmatic and flexible enough to meet internationally-accepted prudential and supervisory requirements. Effective prudential supervision of Islamic Banks in their home countries is important to foster integration between Islamic and conventional banking systems.