Dhaka University Journal of Applied Science & Engineering https://journal.library.du.ac.bd/index.php/DUJAPSE Official Journal of faculty of Engineering and Technolog, University of Dhaka, Dhaka-1000, Bangladesh. en-US deanengg@du.ac.bd (Prof. Dr. Md. Habibur Rahman) deanengg@du.ac.bd (Prof. Dr. Md. Habibur Rahman) Tue, 22 Feb 2000 23:48:48 +0600 OJS 3.2.1.5 http://blogs.law.harvard.edu/tech/rss 60 Editor's Note https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1984 ---- Md. Habibur Rahman Copyright (c) 2000 Dhaka University Journal of Applied Science & Engineering https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1984 Mass Spectrophotometric Observation of the Probable Compounds from Taxux baccata Linn. (European Yew) https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1985 Highly colored natural products from the powdered leaves and twigs of the plant were successively extracted using hexane and a mixture of chloroform-methanol (1:1). Chromatographic fractions of these extracts were analyzed further. Taxagifine, a 7,9,10-deacetylated taxagifine(1R,2R,3S,4R,5S,6S,8S,10R,11R,12R,15S)-2,3,4,6,11-pentahydroxy-5,15-dimethyl-9-methylidene-14-oxo-16-oxatetracyclo[10.5.0.02,15.05,10]heptadecan-8-yl (2E)-3-phenylprop-2-enoate), a hydroxyl ester (Triecosanyl-16-hydroxy-hexadecanoate), triacontanol-1 and a naphthalene glycoside (1,2,3-tri-O-methyl naphthalene-4-ol- (4→1α)-glucoside were isolated. Structures of the probable reported compounds were proposed using UV-Vis, FTIR and Mass spectrometric method. Nasima Akter, Shanta Biswas Copyright (c) 2000 Dhaka University Journal of Applied Science & Engineering https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1985 Simulation of the Electrical Characteristics of Double Gate FinFET with the Variation of Channel Length https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1986 In this research work, electrical characteristics of double gate FinFET have been simulated by varying the length of the channel region. 40 nm, 50nm and 60nm channel length has been considered to simulate the drain current VS front gate voltage characteristics for FinFET. For these three different values of channel length, electric field profile along the FinFET channel has also been studied in this research. Finally the electrostatic potential along the channel has been simulated for varying the channel length of the FinFET. After analyzing the simulations, it has been proposed that higher drain current, wide variation of electric field along the channel region as well as increased carrier mobility and lower electrostatic potential along the channel can be achieved for smaller value of the channel length of FinFET. The whole simulation works have been performed by Nano HUB online simulation tool named “DG-MOSFET” where the data of the simulation were processed and the plots were generated. Md. Mostak Ahmed, Arin Dutta, Zahid Hasan Mahmood Copyright (c) 2000 Dhaka University Journal of Applied Science & Engineering https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1986 Implementation and Analysis of Physiologically Based Pharmacokinetic (PBPK) Model for Docetaxel in Cancer Chemotherapy https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1987 Physiologically based pharmacokinetic (PBPK) models represent an important class of dosimetry models that are useful for predicting internal dose at target organs in human body. In this paper, a whole body Docetaxel based PBPK model has been implemented and analyzed. This model shows the variations and distributions of drug concentrations over time at different organs of human body. Higher drug concentration can affect human body with different toxic side effect. This model can help clinicians to measure the concentration of drugs at different organs using computer based simulation and to decide the correct dose for a patient. Md. Zahidul Islam, M. S. Alam Copyright (c) 2000 Dhaka University Journal of Applied Science & Engineering https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1987 Comparative Study of GaN and GaAs Based Heterojunction Bipolar Transistors https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1988 In this study, the base-width modulation of GaN and GaAs based heterojunction bipolar transistor is analyzed using an enhanced drift-diffusion model. This work has been done to understand the concept of base width modulation clearly for designing GaN and GaAs based power transistors. The considered structure of this study is: n-type AlGaN/AlGaAs layer as an emitter, p-type GaN/GaAs as a base and n-type GaN/GaAs as a collector. In order to illustrate the difference between GaAs and GaN we have changed the material of the structure without changing the doping concentrations. The emitter and collector widths are remain fixed, while the base width is varied in order to find the optimized base for providing high collector current density. For these structures the emitter-base junction turn on voltage must be greater than 2.7 V. The effect of C-B voltage on the base width is significant. The neutral base-width Xb is a function of C-B voltage which is varied by varying the C-B voltage changes from 2 to 70 volt. The change in neutral base width leads to a significant change in the collector current density. Finally an optimized GaN and GaAs based structure is proposed and also which structure gives better performance between these two has been investigated later. S. Islam, S. I. Swati, M. J. Rashid Copyright (c) 2000 Dhaka University Journal of Applied Science & Engineering https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1988 A Comparative Analysis on Feature Extraction and Classification of EEG Signal for Brain-Computer Interface Applications https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1989 Classification of EEG signal for Brain-Computer Interface (BCI) applications consists of three stages: Pre-processing; Feature extraction and Classification. There are different methods implemented in these stages found in existing literature. However, the performance of the methods has been measured on different datasets which made the results incomparable to each other. To address this problem, in this paper, different combination of feature extraction and classification methods has been implemented to classify a well known dataset (dataset 2A, BCI Competition IV) so that a comparative analysis can be made based on identical platform to find out the best combination of methods. In the pre-processing step, the EEG data was band-pass filtered to remove the artifacts and Common Spatial Pattern (CSP) was applied to increase the discriminativity of the data. Two types of features: Time Domain Parameters (TDP) and Adaptive Auto-Regressive (AAR) parameters were extracted from the pre-processed EEG signal. The features were classified using two types of classifiers: Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM). A comparative analysis has been conducted to identify the best combination of feature and classifier. The analysis reveals that, TDP features classified using LDA classifier provides best performance and hence demands application in real time BCI system. Mohammed Nowaz Rabbani Chowdhury, Subrata Kumar Aditya Copyright (c) 2000 Dhaka University Journal of Applied Science & Engineering https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1989 Reeal Time Featur Based Vehicle Detection and Classification from On-Road Videos https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1990 Vision Based vehicle detection and classification has become an active area of research for intelligent transportation system. But this task is very difficult and challenging due to the dynamic condition of roads. In the proposed method, a feature based cost effective detection and classification method is proposed that is suitable for real time applications, provide satisfactory accuracy and computationally cheap. The proposed method uses haar-like image features and AdaBoost classifier for detection. To reduce false positive rate, we propose to use two virtual detection lines (VDL). In order to predict the class of a vehicle, we propose a two level classifier where first classifier separates bigger (bus, truck) vehicles from the smaller one (car, CNG, rickshaw) based on some shape information of vehicles. For the second classifier, we propose to use bag of features (BOF) model which uses the feature efficiently and generates bag of visual words (BOVW). Shape based features are used for first classifier and texture based feature (SURF) is used for second classifier. Error correcting output code (ECOC) framework is used to achieve multi class prediction with SVM to predict the class. Extensive experiments have been carried out on different local traffic data of varying environments to evaluate the detection and classification performance of the proposed method. Experimental results demonstrate that the proposed two level classifier achieves a significant improvement in classification of heterogeneous vehicles in terms of accuracy with a considerable execution time as compared to other methods. Md. Shamim Reza Sajib, Saifuddin Md. Tareeq Copyright (c) 2000 Dhaka University Journal of Applied Science & Engineering https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1990 A Probabilistic Analysis of Levelized Cost of Energy (LCOE) for Bangladesh https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1991 Energy crisis is one of the major problem for Bangladesh to eradicate extreme poverty and achieve middle-income status. Electricity production in Bangladesh is mostly from conventional energy sources like fossil fuels and natural gas. Experiencing huge shortage of electricity and realizing the future energy demand of the country, the government of Bangladesh is going to install a nuclear power plant for the large scale (2.4 GW) electricity production. A comparative study is conducted in this paper to observe the levelized cost of energy scenario for several electricity generating technologies. The present calculation is done using the LCOE simulator. From the simulation results, it is found that the distribution of levelized bus bar costs for the nuclear power plant is in the range of 11.69-17.84 cents/kWh, with a most probable value of about 14.75 cents/kWh; for coal-fired plants the corresponding values are 15.56–19.90 cents/kWh and 17.73 cents/kWh and for the combined cycle gas power plant the corresponding values are in the range of 15.90-17.30 cents/kWh and a most probable value of about 16.60 cents/kWh. Comparing the results from different technologies, it is worth saying that nuclear power plant is the best option for large scale (2.4 GW) power production for a developing country like Bangladesh. Md. Al Amin Hossain, Md. Mahidul Haque Prodhan, Md. Iqbal Hosan, Md. Jafor Dewan, Md. Faisal Rahman Copyright (c) 2000 Dhaka University Journal of Applied Science & Engineering https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1991 Complexity Analysis of the Multivariate Wind Measurements: Renewable Energy Applications https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1992 Complexity analysis of real world multivariate wind data is addressed using the recently proposed multivariate multiscale entropy (MMSE) analysis. Both the original (univariate) MSE and the multivariate MSE methods are shown to perform better than traditional complexity analysis techniques, since they operate on multiple temporal scales of the signals and are, thus, able to extract information regarding inherent long range correlations in the data, signatures of structural complexity. The MMSE method, in addition, can also quantify inter-channel correlations in multivariate data and is perfectly suited for the analysis of multichannel data, where the channels exhibit different dynamical properties, such as three-dimensional wind speed. To cater for the non-stationarity of wind recordings, a novel scheme is presented for obtaining data-driven scales from input data using multivariate extension of empirical mode decomposition (MEMD), in order to obtain robust estimates. Our method can thus characterise different wind dynamics regimes and cloud-cover conditions in complexity domain. Finally, we illuminate how the different dynamic complexities associated with different wind regimes, and their connection with atmospheric parameters, such as temperature, or cloud cover, can be used as baseline knowledge in several important settings in renewable energy. Mosabber Uddin Ahmed Copyright (c) 2000 Dhaka University Journal of Applied Science & Engineering https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1992 Multiscale Complexity Analysis: A Novel Approach for Anomaly Detection in Multivariate Data https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1993 In this paper, a novel method is presented for anomaly detection in multivariate data. The proposed method is based on computing multivariate entropy of input data at multiple scales, via the MMSE method, a technique recently proposed for the dynamical complexity analysis of multivariate data. In the proposed methodology, the anomalous behaviour is assumed to be generated by a constrained system and thus is easily differentiated from the established normal behaviour, in accordance with the “complexity loss” hypothesis, traditionally used for physiological systems. Simulations are provided to demonstrate the effectiveness of the approach on real world data sets in terms of anomaly detection. Mosabber Uddin Ahmed Copyright (c) 2000 Dhaka University Journal of Applied Science & Engineering https://journal.library.du.ac.bd/index.php/DUJAPSE/article/view/1993