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: Renewable energy & Dielectric. 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.

Performance Analysis of a Microstrip Patch Antenna for Biomedical Applications

Abstract: A microstrip patch antenna's design and performance analysis for biomedical applications which operating at 2.45 GHz frequency range in ISM Band (2.4 GHz to 2.5 GHz) is represented in this paper. The antenna's good-looking feature is the proper thickness and suitable dimension. The special feature of this antenna is to make it perfect for On-body matched biomedical applications. FR4 material is used as the substrate to design the antenna. Individual properties of the Phantom model are perfectly maintained to get proper software simulated result. All the simulations, calculations and parameter results are fit for on-body matched conditions. To design the antenna CST Microwave Studio is used. Impressive S 11 of more than −50 dB for off-body and on-body as well as Specific absorption rate (SAR) of 0.0005 W/kg in on-body make the antenna compatible for biomedical application.

YANG modeling of network elements for the management and monitoring of Elastic Optical Networks

Abstract: To accommodate big data, new technologies and features have started to be used in core network. Consequently, optical transport network has evolved towards Elastic Optical Network (EON). Despite the effort made towards efficient and reliable network management, interoperability problem in multi-vendor setting of the EON remains unsolved and it hinders the network management and monitoring. Hence, Network operators need to rely on the proprietary management solutions. This phenomenon poses complexity in network configuration, control, monitoring and management and also in turn results in higher Capital Expenditure (CAPEX) and Operational Expenditure (OPEX) for the service providers. In this paper, standard data definition model of network elements of EON is presented for configuration, management and monitoring purpose. Standard YANG data models for the network elements, namely, Reconfigurable Optical Add/drop Multiplexer (ROADM), Bandwidth Variable Transponder (BVT) and Optical amplifier (OA) are presented. The implementation scenario for the developed data definition models are demonstrated for managing state of the art EON. It is contended that the adoption of these standard YANG data models within the NETCONF protocol not only facilitates the network configuration and management, but also improves the multi-vendor interoperability in the control and management plane of the EON.

Traditional Bengali Food Classification Using Convolutional Neural Network

Abstract: Image classification is turning into a significant and promising perspective in the fields of object recognition using computer vision. However, researchers have barely scratched the superficials of food image classification till now. To evaluate the dietary aptitudes of people from various ethnicities, the classification of their traditional foods makes a huge impact. That’s what steered us into the classification of seven traditional foods in Bangladesh. In this regard, our key contribution to this aspect is the development of a dataset of Traditional Bengali Food Image (TBFI) including images of seven different classes of traditional Bengali foods: Biriyani, Panta Ilish, Khichuri, Fuchka, Roshogolla, Dim Vuna & Kala Vuna. For this, a scratch model incorporating Convolutional Neural Network (CNN) has been developed, rectifying to another vital contribution. As conventional Neural Network doesn’t perform well in case of image datasets, the CNN approach has been followed in view of its high accuracy, computational power with efficiency and automatic recognition of important features without any human oversight. Moreover, transfer learning approach with fine tuned VGG16 has also been used for TBFI classification. The proposed model in this paper has generated a culminated outcome upon our TBFI dataset with an average accuracy of 98% in classifying the traditional Bengali food images.

Design and Optimization of an Efficient Molybdenum Disulfide (MoS 2 ) Solar cell with Tin Sulfide BSF

Abstract: Two-dimensional molybdenum disulfide (MOS 2 ) is a potential sunlight harvester due to low cost, layered type atomic structure, favorable electrical and optical properties. The performance of a molybdenum disulfide (MOS 2 ) photovoltaic cell is investigated by using the wxAMPS simulator. The hidden potentiality of Mos2is unfolded by using BSF strategy. The photoconversion efficiency is found 21.39% $(\pmb{J_{sc}}=\pmb{29.89}\ \mathbf{mA}/\mathbf{cm}^{\pmb{2}},\pmb{V_{oc}=0.841}\mathbf{V}$ and $\mathbf{FF}=\pmb{0.856}$ ) for $\mathbf{r}\ \ \pmb{1}\ \ \pmb{\mu} \mathbf{m\ MoS}_{\pmb{2}}$ absorber layer with 100 nm SnS BSF whereas in conventional structure, it is found 19.48% $(\pmb{V_{oc}=0.826}\mathbf{V}, \pmb{J_{sc}}=\pmb{27.848}\ \ \mathbf{mA}/\mathbf{cm}^{\pmb{2}}$ , and $\mathbf{FF}=\pmb{0.846)}$ without BSF for 1 $\pmb{\mu} \mathbf{m\ MoS}_{\pmb{2}}$ absorber layer. The measured temperature coefficient (TC) is $\pmb{-0.047\%/}^{\circ}\mathbf{C}$ for conventional photovoltaic cell structure and −0.046%/°C for a modified structure with SnS BSF. It indicates the better thermal stability of the modified structure compared to the conventional structure.

Conversion of energy equation for fiber suspensions in dusty fluid turbulent flow

Abstract: Turbulent energy plays a vital role in science and industries. Fiber suspension in turbulent flows has received significant attention since the electrical, thermal, and mechanical characteristics of the relating fiber composites are tactful to the spatial configuration and orientation of fibers. Turbulent energy can be affected by the fibers passes through the turbulent flow. It is further influenced by the occurrence of dust or other particles. The impact of the fibers along with such particles needs to be studied. To analyze the impact, it is very important to model dusty fluid turbulent fiber motion which can be substantially utilized in science and industries. Therefore, this study aims to construct a model for dusty fluid turbulent energy of fiber suspensions. The energy equation for turbulent flow was taken into account to develop the model. The turbulent fiber motion for dusty fluid was derived in correlation tensors, where the tensors are the function of distance, time, and space coordinates.