Prime University or PU is a private university in Mirpur, Dhaka, Bangladesh. The university was established by the Private University Act 1992. PU is affiliated by the University Grants Commission Bangladesh. The University was established in 2002 at Mirpur, Dhaka. PU is the first venture of the Prime Foundation. Wikipedia.
Shahadat N.,Prime University |
Hossain I.,City University of Bangladesh |
Rohman A.,City University of Bangladesh |
Matin N.,City University of Bangladesh
ECCE 2017 - International Conference on Electrical, Computer and Communication Engineering | Year: 2017
As tremendous growth of information in the internet, the importance of Network security also dramatically increases. Network and Host based Intrusion Detection System (IDS) are two primary systems in Network Security infrastructure. When new intrusion types are appeared in Network or Host, some serious problems are also appeared to detect these new intrusions. Due to this reason, IDSs demanded better than Signature based detection. The action of intrusion is represented by some features and collects the corresponding featured data from these uncertain feature characteristics. In last two decades, several techniques are developed to detect intrusion by using these data as human labeling which is very time consuming and expensive process. In this paper, we proposed a data mining rule based algorithm called Decision Table (DT) to detect intrusion and a new feature selection process to remove irrelevant/correlated features simultaneously. An empirical analysis on KDD'99 cup dataset was performed by using our proposed and some other existence feature selection techniques with DT and some others classification algorithms. The experimental results showed that proposed approach provides better performance in accuracy and cost compared among Bayesian Network, Naïve Bayes Classifier and other developed algorithms with data mining KDD'99 cup challenge in all cases. © 2017 IEEE.
Shahadat N.,Prime University |
Rahman B.,City University of Bangladesh |
Ahmed F.,City University of Bangladesh |
Anwar F.,City University of Bangladesh
ECCE 2017 - International Conference on Electrical, Computer and Communication Engineering | Year: 2017
To ignore noisy, skewed, correlated, imbalanced and unnecessary features from real life problems, the feature subset selection with learning algorithm was faced some problems of selecting these relevant features. Several factors like-skewed, high kurtosis valued, dependence or correlation influenced features as well as the classifiers performance. A Dropout technique (feature subset selection method) was used to select relevant and important features and mixed with a classifier named as Probabilistic Neural Network (PNN) to find the performance. This study conducted Dropout technique with PNN to prevent above irrelevant features to get better performance. The main task of this method was to apply several techniques (by omitting some fixed features like-skewed, high kurtosis valued, dependent or correlated and Dropout) with PNN in several datasets and noticed that the overall performance for all datasets was significantly improved or unchanged for Dropout with PNN(DPNN) and DPNN always performed better than others. © 2017 IEEE.
Ahmed F.,Islamic University of Technology |
Hossain E.,Prime University |
Bari A.S.M.H.,Samsung |
Shihavuddin A.,University of Girona
12th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2011 - Proceedings | Year: 2011
The local binary pattern (LBP) operator has been proved to be a simple and effective approach for facial feature representation. However, the LBP operator thresholds P neighbors at the value of the center pixel in a local neighborhood and encodes only the signs of the differences between the gray values. Thus, the LBP operator discards some important texture information. This paper presents a new local texture operator, the compound local binary pattern (CLBP), and a feature representation method based on CLBP codes for facial expression recognition. The CLBP operator combines extra P bits with the original LBP code, which are used to express the magnitude information of the differences between the center and the neighbor gray values. We empirically evaluate the effectiveness of the proposed feature representation for person-independent expression analysis. Extensive experiments show the superiority of the CLBP method against some other appearance-based feature representation methods. © 2011 IEEE.
Habib M.T.,North South University |
Habib M.T.,Prime University |
Rokonuzzaman M.,Independent University, Bangladesh
Journal of Multimedia | Year: 2011
Over the years significant research has been performed for machine vision based fabric inspection systems in order to replace manual inspection, which is time consuming and not accurate enough. Automated fabric inspection systems mainly involve two challenging problems: One is defect detection and another is classification, which remains elusive despite considerable research effort in automated fabric inspection. The research reported to date to solve the defect classification problem appears to be insufficient, particularly in selecting appropriate set of features. Scene analysis and feature selection play a very important role in the classification process. Insufficient scene analysis results in an inappropriate set of features. Selection of an inappropriate feature set increases complexities of subsequent steps and makes the classification task harder. Considering this observation, we present a possibly appropriate feature set in order to address the problem of fabric defect classification using neural network (NN). We justify the features from the point of view of distinguishing quality and feature extraction difficulty. We performed some experiments in order to show the utility of proposed features and compare performances with recently reported relevant works. More than 98% classification accuracy has been found, which appears to be very promising. © 2011 ACADEMY PUBLISHER.
Khan K.,Bangladesh University |
Ali Akbar M.,University of Rajshahi |
Abdus Salam M.,Mawlana Bhashani Science and Technology University |
Hamidul Islam M.,Prime University |
Hamidul Islam M.,Griffith University
Ain Shams Engineering Journal | Year: 2014
In this talk we have applied an enhanced (G′/G)-expansion method to find the traveling wave solutions of the (2 + 1)-dimensional Zoomeron equation. The efficiency of this method for finding the exact solutions has been demonstrated. As a result, a set of exact solutions are derived, which can be expressed by the hyperbolic and trigonometric functions involving several parameters. When these parameters are taken as special values, the solitary wave solutions and the periodic wave solutions have been originated from the exact solutions. It has been shown that this method is effective and can be used for many other nonlinear evolution equations (NLEEs) in mathematical physics. © 2014 Production and hosting by Elsevier B.V. on behalf of Ain Shams University.
Ahmed S.F.,Prime University |
Sarker M.S.A.,University of Rajshahi
Journal of Computational and Applied Research in Mechanical Engineering | Year: 2015
The energy equation for turbulent flow of fiber suspensions was derived in terms of second order correlation tensors. Fiber motion of turbulent energy including the correlation between pressure fluctuations and velocity fluctuations was discussed at two points of flow field, at which the correlation tensors were the functions of space coordinates, distance between two points, and time. © 2015, Shahid Rajaee Teacher Tarining University (SRTTU). All rights reserved.
Huda K.,Prime University |
Huda K.,Khulna University of Engineering and Technology |
Hossain M.S.,Khulna University |
Hossain M.S.,Khulna University of Engineering and Technology |
Ahmad M.,Khulna University of Engineering and Technology
ICEEE 2015 - 1st International Conference on Electrical and Electronic Engineering | Year: 2015
In this paper, recognition of human activity, involving patterned eye movements, such as reading is introduced. Recognition of human activities is an important part in implementing ubiquitous, context-aware computer applications where computers can communicate with humans in a more interactive manner. Eye movement is a potential instrument in activity recognition as most of human activities involve movement of eyes. This paper describes a method to recognize reading activity from the eye movement patterns. Electrooculography (EOG) signal is used to quantify the eye movements in terms of electrostatic potential. The EOG signal is recorded using electrodes, placed at appropriate positions around the eyes. The extracted EOG signal is then analysed to detect eye movement patterns in connection to reading activity. © 2015 IEEE.
Golam Rashed M.,Prime University
Journal of Engineering Science and Technology Review | Year: 2011
Clustering in wireless sensor networks is one of the crucial methods for increasing of network lifetime. The network characteristics of existing classical clustering protocols for wireless sensor network are homogeneous. Clustering protocols fail to maintain the stability of the system, especially when nodes are heterogeneous. We have seen that the behavior of Heterogeneous-Hierarchical Energy Aware Routing Protocol (H-HEARP) becomes very unstable once the first node dies, especially in the presence of node heterogeneity. In this paper we assume a new clustering protocol whose network characteristics is heterogeneous for prolonging of network lifetime. The computer simulation results demonstrate that the proposed clustering algorithm outperforms than other clustering algorithms in terms of the time interval before the death of the first node (we refer to as stability period). The simulation results also show the high performance of the proposed clustering algorithm for higher values of extra energy brought by more powerful nodes. © 2011 Kavala Institute of Technology.
Agency: Department of Health and Human Services | Branch: | Program: STTR | Phase: Phase II | Award Amount: 996.94K | Year: 2013
DESCRIPTION (provided by applicant): The use of Surface Enhanced Raman Scattering (SERS) for biomolecule detection has been restricted due to the great difficulty of fabricating ultrasensitive and reproducible surface-plasmonic-resonance (SPR) substrates.Therefore, detecting extremely small amount of biomolecules for clinical application is significantly limited. In this STTR Phase II research, we propose to develop ultrasensitive (1012~1014 enhancement factors) SERS substrates with universally availableRaman hot spots for well-reproducible biomolecule detection by combining optical field enhancements from both resonant photonic devices and metallic nanoentities. Compared with existing SPR substrates made by spin-coating colloidal nanoparticles or nanowire solutions, we engineer the SERS substrate using silica nanotubes coated with universally distributed silver nanoparticles, which can dramatically increase the density of the Raman scattering hot spots . We also employ highly robust Si3N4 guided-mode-resonance (GMR) gratings and resonant microcavity array to achieve even higher local electric field for SERS sensing. To link these two innovations, we will apply a highly exquisite tool---electric tweezers, to assemble the SPR-active nanotubes into the resonant photonic devices with unbeatable spatial precision of at least 150 nm. In our Phase I program, we have theoretically simulated and experimentally demonstrated SPR-active silica nanotubes with nanometer-size gaps, and detected Rhodamine 6G down to 100fM (single-molecule level) with enhancement factors of 1.1x1010. Moreover, we fabricated Si3N4 GMR gratings using state-of-the-art nanofabrication processes and experimentally achieved ~10? enhancement factors in addition to the existing SERS effect fromthe SPR-active silica nanotubes. In the Phase II program, we will continue to optimize the SERS substrates for ultrahigh sensitivity up to 1012~1014 enhancement factors, improve the detection probability of ultralow concentration biomolecules in real biological samples, and apply the SERS substrates in various biomedical applications. Most of all, we will resolve potential technical challenges for product commercialization, including lowering the fabrication cost, increasing the throughput, packaging the SERS substrate with fiber-optic systems and evaluating the device reliability. PUBLIC HEALTH RELEVANCE PUBLIC HEALTH RELEVANCE: Surface Enhanced Raman Scattering (SERS) has significant potential in biomolecule detection due to its extremely high sensitivity in hot spots . However, the average sensitivity, repeatability, and reliability of current SERS techniques cannot meet the requirements of many biomedical applications. This project focuses on the development of SERS substrates with universallyavailable Raman hot spots for ultrasensitive and well- reproducible biomolecule detection through the combination of resonant photonic devices and metallic nanoentities, which has significant potential for early disease detection and personal diagnostics.
Ahmed F.,Prime University |
Ali M.L.,Bangladesh University of Engineering and Technology |
Asad M.I.H.B.,Bangladesh University of Engineering and Technology
8th International Conference on Electrical and Computer Engineering: Advancing Technology for a Better Tomorrow, ICECE 2014 | Year: 2015
System-on-a-chip (SoC) is now a trend in digital design because it gives a lot of advantages over discrete electronic based product such as higher speed, lower power consumption, smaller size, lower cost etc. Reconfigurable platforms such as FPGA, CPLD, and PLD are now being used for designing and implementing SoC due to their low cost, high capacity and tremendous speed. In this project single chip Orthogonal Frequency Division Multiplexing (OFDM) transmitter and receiver have been designed using Verilog HDL. OFDM is a multi carrier modulation technique used in the various digital communication systems like 3G GSM, WiMAX and LTE etc. The main advantage of this transmission technique is its robustness to channel fading in wireless communication environment. There are many applications of OFDM in communication such as digital audio broadcasting, Asynchronous Digital Subscriber Line (ADSL) and High bit-rate Digital Subscriber Line (HDSL) systems. In OFDM, two algorithms digital signal processing algorithm Fast Fourier transform (FFT) and Inverse Fast Fourier Transform (IFFT) are mainly involved. The 8-point IFFT/FFT Decimation-In-Frequency (DIF) with radix-2 algorithm has been analyzed and incorporated in the design. The design has been simulated on the FPGA platform with Altera's Quartus II simulator. Simulation results show that each of the modules of the proposed OFDM is working as desired. The test output achieved from the simulation result of the OFDM has been verified with that of the MATLAB output. © 2014 IEEE.