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.

Traveling wave with beta derivative spatial-temporal evolution for describing the nonlinear directional couplers with metamaterials via two distinct methods

Abstract: This work is reported the analytical solutions for describing the nonlinear directional couplers with metamaterials by including spatial–temporal fractional beta derivative evolution. The auxiliary ordinary differential equation method and the generalized Riccati method with the properties of beta derivative are implemented to secure such solutions. The solutions are obtained in the new forms by involving of some useful mathematical functions. The constraint conditions among the traveling wave parameters are evaluated. Some of the obtained solutions are presented graphically to illustrate the effectiveness of beta derivative parameter and mathematical techniques. It is investigated that the amplitudes of soliton are increased with the increase of fractional beta derivative parameter. The obtained results would be very useful to examine and understand the physical issues in nonlinear optics, especially in twin-core couplers with optical metamaterials.

Bengali text document categorization based on very deep convolution neural network

Abstract: In recent years, the amount of digital text contents or documents in the Bengali language has increased enormously on online platforms due to the effortless access of the Internet via electronic gadgets. As a result, an enormous amount of unstructured data is created that demands much time and effort to organize, search or manipulate. To manage such a massive number of documents effectively, an intelligent text document classification system is proposed in this paper. Intelligent classification of text document in a resource-constrained language (like Bengali) is challenging due to unavailability of linguistic resources, intelligent NLP tools, and larger text corpora. Moreover, Bengali texts are available in two morphological variants (i.e., Sadhu-bhasha and Cholito-bhasha) making the classification task more complicated. The proposed intelligent text classification model comprises GloVe embedding and Very Deep Convolution Neural Network (VDCNN) classifier. Due to the unavailability of standard corpus, this work develops a large Embedding Corpus (EC) containing 969 , 000 unlabelled texts and Bengali Text Classification Corpus (BDTC) containing 156 , 207 labelled documents arranged into 13 categories. Moreover, this work proposes the Embedding Parameters Identification (EPI) Algorithm, which selects the best embedding parameters for low-resource languages (including Bengali). Evaluation of 165 embedding models with intrinsic evaluators (semantic & syntactic similarity measures) shows that the GloVe model is more suitable (regarding Spearman & Pearson correlation) than other embeddings (Word2Vec, FastText, m-BERT) in Bengali text. Experimental results on the test dataset confirm that the proposed GloVe + VDCNN model outperformed (achieving the highest 96.96 % accuracy) the other classification models and existing methods to perform the Bengali text classification task.

Germanium telluride as a BSF material for high efficiency ultra-thin CdTe solar cell

Abstract: The polycrystalline cadmium telluride (CdTe) is regarded as one of the leading photovoltaic (PV) materials for its high efficiency and low-cost. The absorber material CdTe has the ideal and direct bandgap of 1.45 eV and it has a high absorption co-efficient over 5×10 5 /cm. In this work, the possibility of ultra-thin absorber layer of CdS/CdTe solar cell was investigated by numerical analysis utilizing AMPS (Analysis of Microelectronic and Photonic Structures) simulator. In the proposed cell, the CdTe layer was reduced and found that 1 �m CdTe layer is enough for acceptable range of cell conversion efficiency. The viability of this ultra-thin CdTe absorber layer was examined, together with 0.1 �m GeTe back surface field (BSF) layer to reduce the barrier height in the valence band and to minimize the recombination losses at the back contact of the CdS/CdTe cell. It was found that the proposed ultra-thin cells have conversion efficiency of 18.68% (Jsc = 21.47 mA/cm 2 , FF = 0.85, Voc = 1.02 V) without BSF and with 100 nm GeTe BSF conversion efficiency increased to 22.53% (Jsc = 24.28 mA/cm 2 , FF = 0.875, Voc = 1.06 V) with only 0.8 �m of CdTe layer. Moreover, it was found that the normalized efficiency of the proposed cells linearly decreased with the increasing operating temperature at the gradient of -0.16%/°C, which indicated better stability of the proposed CdTe solar cell.

A surveillance system based on motion detection and motion estimation using optical flow

Abstract: In today's world Surveillance system is playing an important role in the field of security. Moving object detection has been widely used in video surveillance system. As well as motion estimation is an important part of surveillance video processing such as video filtering and compression from video frames. This paper proposes a simple and efficient surveillance system based on motion detection with motion vector estimation from surveillance video frames. Motion is detected with a new approach-edge region determination which makes detection faster. The surveillance video is then processed for motion estimation using optical flow with Horn-Schunck algorithm for estimating motion vector for its reasonable performance and simplicity. This method is computationally faster without requiring any special hardware for image processing. So it can be more applicable to embedded systems.