Browsing by Author "Sakib, Sadman"

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A convolutional neural network based model with improved activation function and optimizer for effective intrusion detection and classification
(BRAC University, 2020-04) Kabir, Solaiman; Sakib, Sadman; Hossain, Md. Akib; Islam, Safi; Hossain, Muhammad Iqbal
In today's world, technological advancements have entangled our nancial, social and many more other aspects of lives to the internet or some network. Moreover, with the development of IoT technologies, it has spread over to our transportation, home-appliances and more devices. It is also a security risk because all of our sensitive and private knowledge on the Internet is exposed to a growing amount of cyber-attacks. An Intrusion Detection System can identify a cyber-attack while it is ongoing or prior to it. We are conscious of the evolving Machine Learning and Deep Learning developments, the most sophisticated multi-functional methods created by humans that can be utilized to overcome this issue. Alongside identi fication, precise classi cation of intrusion is of considerable signi ficance for the administrator to take decisive actions. In this study, we have used the dataset CIC-IDS-2018 that is the biggest and most recent labeled dataset of intrusions. This dataset comprises of six varieties of attacks. Our thesis proposes a CNN Model with mish activation function and Ranger optimizer. The model reaches an accuracy of 0.989 that is the highest in multiclass classification with this dataset.
A modern technique to detect potholes by Computer Vision and Deep Learning
(BRAC University, 2022-09) Saif, Muntasir Mahmud; Badsha, Tanvir; Khan, Mohammed Arman; Sakib, Sadman; Bin Akbar, Rafeed; Karim, Dewan Ziaul
Roads are connecting lines between different places and are used in our daily life but anomalies in road surface not only impact road quality but also affect driver safety, mechanic structure of the vehicles, and fuel consumption. Several approaches have been proposed to automatic monitoring of the road surface condition in order to assess road roughness and to detect potholes. Potholes are one of the main reasons behind the occurrence of road accidents. According to a report submitted by The Roads and Highways Department (RHD), around 25% roads of Bangladesh under the RHD across the country are in ”poor, bad or very bad” condition. This causes a lot of hassle and issues on the road for both humans and vehicles. Very often be cause of these potholes road accidents occur. Techniques for detecting potholes on road surfaces are being developed to provide real-time or offline vehicle control (for driver assistance or autonomous driving) as well as offline data collecting for road repair. For these reasons, researchers have looked into ways for detecting potholes on roads all over the world. This paper begins with a quick overview of the area before categorizing developed strategies into various groups. Then, by developing method ologies for automatic pothole detection, we present our contributions to the field. For this reason, we propose a deep learning approach that allows us to automatically identify the different kinds of road surface and to automatically distinguish potholes from destabilizations produced by speed bumps or driver actions. The system can detect potholes in different environments, lighting and weather conditions. We have trained and tested our model with a custom dataset which contains raw 3000 images with 1500 normal road images and 1500 images with potholes using deep learning algorithms. We have augmented these images and turned them into 120000 images so that the model can understand any image input in any scenario. In particular, we have analyzed and applied different deep learning models such as convolutional neural networks (CNN) and Yolov4. With these models we have achieved 97.35% accuracy with the CNN model and 87.6% accuracy with the YOLOv4 model.
DC-DC and AC-DC Zeta and buck converter design and analysis for high efficiency application
(Department of Electrical and Electronic Engineering, Islamic University of Technology, 2017-11-15) Sakib, Sadman; Khan, Md. Fahim Hasan; Rahman, Md. Ashiqur; Reza, Md. Zamilur
The thesis work is carried out to design and analyze DC-DC and AC-DC converters. Two types of DC-DC converters, buck and zeta, are presented in this book with dc steady state analysis at continuous conduction mode, ac small signal analysis and simulation results. The analysis of DC-DC buck converter includes a switched capacitor buck converter and a switched inductor buck converter. These two converters have been proposed in a previously published article. But, the article did not show the detailed analysis. So, the detailed mathematical model has been developed for these two buck circuits. Another type of buck converter, based on switched inductor-capacitor, is presented briefly in chapter 5. This buck converter has been accepted in an IEEE conference. Two types of zeta converter, switched inductor and modified conventional, are shown in this book. The modified conventional zeta circuit is a new design while the other circuit is taken from a previously published article. The newly developed modified conventional zeta circuit improves the performance of conventional zeta circuit by increasing the efficiency above 95%. A two stage AC-DC converter based on switched inductor zeta circuit is designed and analyzed. The proposed AC-DC circuit improves the power quality compared to the conventional circuit. It raises the efficiency above 95%, increases the power factor (PF) by 6% compared to the conventional circuit and improve the total harmonic distortion (THD) by 2-3% with respect to the conventional circuit.
Deepfake detection using neural networks
(BRAC University, 2021-09) Sakib, Sadman; Abid, Mir Tarid Al; Tiana, Nures Saba; Asha, Wajida Anwar; Huq, Syed Mahbubul; Hossain, Muhammad Iqbal; Abrar, Mohammed Abid
Deepfake is a sort of arti cial intelligence that forge original image or video and create persuading images, audio and video hoaxes by utilizing two contending AI algorithms-the generator and discriminator that form a generative adversarial net- work (GAN). The term `Deepfake' started in 2017, when a mysterious Reddit user called himself "Deepfakes." The user "Deepfakes" supplanted genuine faces with celebrity faces. With the rapid advancement of modern technology, Deepfakes have become an emerging problem, as deepfakes can threaten cybersecurity, political elec- tions, companies, individual and corporate nances, reputations, and more. There- fore, this makes deepfake detection more and more urgent. Although, a lot of techniques has been invented to detect deepfake but not all of them works perfectly and accurately for all cases. Also, as more up to date deepfake creation strategies are grown, ine ectively generalizing methodologies should be continually refreshed to cover these new techniques. Our research focuses on the recent techniques that are used to create manipulated videos and detect them though ensembling di erent CNN models.
Face recognition based home security system
(BRAC University, 2019-12) Sakib, Sadman; Wadud, M. M. Abdul; Arnob, Fakid Tazbid; Rahman, Md. Khalilur
With the help of recent technological advancement the world is moving towards an era of advance security systems. For every single purpose or system the main concern is safety. As software based security system creates a good vibe in the security industry because of its robustness so people are more interested to use it in different places like office or even at home. For ensuring an efficient security system and a solid surveillance camera vision has been used vastly nowadays. In this research an image processing based low cost home security system has been approached for home safety and surveillance. Different image processing algorithms based on python, deep learning, Convolutional Neural Networks has been used for better output. Algorithm based on Haar Cascade Classifiers using open CV gives the desired results for low cost components. An IOT based mobile application which is also a part of the total system helps the user to ensure a notification based surveillance system when the user is away from home. Different experimental analysis based on different data sets justify the efficiency as well as sustainability of the total system for real life scenario.
Hybrid Algorithm-Based Approach For Optimized PID Controller for Stability Analysis of DC-DC Interleaved-Buck Converter
(Department of Electrical and Electronic Engineering, Islamic University of Technology (IUT) The Organization of Islamic Cooperation (OIC) Board Bazar, Gazipur-1704, Bangladesh, 2022-05-30) Rahman, Kazi Asif; Sakib, Sadman; Ahmed, Moshiur
This thesis is an investigation of the stability analysis of the Interleaved Buck converter by inducing Nature-Inspired Algorithms to create an optimal PID controller. The applicability and compatibility of some algorithms such as PSO, Firefly Algorithm (FA), GWO and Cuckoo Search are used for optimizing the control mechanism of power converters. Improvements in performance parameters are noted, and the results are compared using multiple fitness functions. The thesis focuses on Interleaved converter which has the benefit of lowering ripple currents, simplifying EMI transmission, and faster transient response. The converters are constructed using the State Space Averaging (SSA) technique to provide promising feedback control and to evaluate the transfer functions. The Nature-Inspired Algorithms are non-linear optimization methods based on artificial intelligence. The above algorithms are based on swarm intelligence and operate in accordance with swarm creature customs. Swarm intelligence ensures better data exploitation, which concentrates the search method within the vicinity of optimal solutions while also assisting the procedure to escape the restriction of the local minima, resulting in successful exploration of the search space. With the help of these algorithms, we approached a hybrid algorithm named Hybrid Firefly Particle Swarm Algorithm (HFPSO). We also compared the performance according to the standard. As a result, the algorithms are evaluated for improved system performance using two fitness functions (ITAE, and ITSE) and performance parameters such as percentage of overshoot, rise time, settling time, and peak amplitude are all variables to consider. The procedure is carried using MATLAB. After studying the results, It is discovered that the percentage of HFPSO overshoot (ITSE) offers a lower for each of the error functions than PSO, CSA, FA, GWO, WOA.
Identify Possible Causes and Solutions of Traffic Jam of Dhaka City and Their Impact on Health.
(Daffodil International University, 2024-07-06) Shuvo, Faysal Ahmed; Sakib, Sadman
The capital of Bangladesh is Dhaka, bears the title of being the world's most denselypopulated city. As of 2022, the population of Dhaka was 10.2 million, and Greater Dhaka has about 22.4 million citizens. Dhaka faces the constant challenge of escalating congestion, particularly in its roadways. The city’s infrastructure struggles to cope with the increasing vehicles, resulting in extensive traffic jams. Contributing factors include faulty traffic signaling systems, insufficient personnel, limited road space, and aggressive driving habits. These traffic congestions adversely affect our health. To address this issue the government could consider various solutions such as constructing roads to improve east-west connectivity within Dhaka, putting in place a system of grade-separated roads, launching a BRT system, and creating a Metro-Rail system. By all evirating traffic congestion, Dhaka can play a significant role in enriching a healthier environment free from noise and pollution, thereby enhancing the quality of life for its residents.
Synthefi – A Defi Application To Offer Tokenized Stocks Pegged to Real-World Stocks
(Daffodil International University, 23-01-29) Sakib, Sadman; Ahmed, MD. Azaz
The stock market, particularly the U.S. stock market, can have a high barrier to entry for some individuals. Especially for Non-US citizens. There are also regulatory requirements and fees associated with trading stocks, which can further increase the cost and complexity of entering the market. Blockchain technology could change how stocks are traded by making the market more open, fraud less likely, and the settlement process more straightforward. By using a decentralized ledger to record transactions, blockchain can provide a secure and immutable record of trades. It can increase confidence in the market and potentially lead to reduced costs for traders. Additionally, smart contracts on a blockchain platform could automate certain aspects of the trading process, further increasing efficiency. Despite these potential benefits, the adoption of blockchain in stock trading has needed to be faster to date, with regulatory and technical challenges remaining. Nevertheless, as technology develops and regulatory frameworks evolve, we will likely see increasing use of blockchain in the stock trading industry in the coming years. This thesis will examine the potential benefits and challenges of using blockchain in the stock trading industry and the technology's current and potential use cases. This thesis will explore the concept of stock as a synthetic asset and its potential benefits and challenges. It will examine the current state of the market for stock as a synthetic asset and consider the potential for its use in various sectors, including traditional finance and retail investing. The thesis will also consider the regulatory landscape surrounding stock as a synthetic asset and the potential impact of these assets on the broader financial system. Finally, the thesis will examine the technical considerations involved in creating and trading stock as a synthetic asset on a blockchain platform and the potential role of smart contracts in this process.
Technology adaptation barriers in data-driven business organizations
(BRAC University, 2023-05) Sakib, Sadman; Hasan, Najmul
This report shows that adapting technology in business processes is crucial to profitably and maintaining sustainability for any business. It is not enough for companies to use a traditional approach for their business processes anymore. Hence, to become efficient in conducting business operations, firms must integrate new technologies. This report also addresses the reasons why SMEs and large organizations are finding it hard to adapt to new technological changes over the years. Furthermore, the report also demonstrates several statistical analyses, charts, and tables proving the research significance as well as what variables are directly and indirectly connected to the issue. However, the report also points out other issues relating to the adaptation of technology in data-driven solutions and how businesses can overcome the barriers leading to great sustainable profitability. Therefore, after going through the report the reader would be able to understand the major barriers to technology adaptation and how they can be overcome.
The combination of bacteriophage therapy and antibiotic therapy
(BRAC University, 2021-06) Sakib, Sadman; Shounak, Samiha Kamal; Naser, Iftekhar Bin
Antibiotic resistance has become a major problem of current time. A lot of deadly bacterial pathogens have become resistant to antibiotics. In addition, pathogens like P.aeruginosa, E.coli, Acinetobacter baumannii and many other bacteria has strains which are resistant to multiple antibiotics. This has made these pathogens even more deadly. Also the overuse of antibiotics is harmful for human health. Thus this indicates to choose an alternative. However, the bacteriophage therapy could be a great and effective alternative. This review paper contains the effectiveness of the combined treatment of bacteriophage and antibiotics against deadly pathogens which have also become resistant to multiple drugs as well. Bacteriophages are viruses which infect and replicates within the specific bacterial cell. The phage virus is highly specific. This indicates that the phage virus will only infect the targeted bacterial pathogen and would not harm the surroundings. The combination of phage therapy with antibiotic therapy has showed positive results in many cases. Multiple experiments have showed significant success by using the combined therapy. The success rate of this combined treatment against pathogens like P.aeruginosa, E.coli or Acinetobacter baumannii and their multiple resistant strains is very promising. Although a lot of experiments should be done to achieve better results in this field.
Tunnel Analysis of Dhaka Subway using PLAXIS 2D Considering Different Groundwater Level Conditions
(Department of Civil and Environmental Engineering (CEE), Islamic University of Technology(IUT), 2022-05-30) Irtiza, Md. Rafid; Sakib, Sadman; Alam, Ishayet; Abrar, Farhan
Dhaka subway, which will be an underground structure is being considered to combat the rising congestion in the city. As the city is very congested special consideration must be given to ground movement and surface settlement during the planning of the subway. Also, the rise in water level as the city moves away from groundwater for its water supply must also be taken into consideration for the long-term design of the tunnel. In this study, 2D finite element analysis was carried out using Plaxis 2D. Different soil profile representing different areas of the Dhaka city was considered and the surface settlement due to tunnel excavation was investigated. It was found that as the depth of the tunnel excavation increases the surface settlement decreases and the settlement trough becomes wider. Also, the volume loss and the grouting pressure required for a specific surface settlement after the tunnel was constructed was also studied and it was found that both volume loss and grouting pressure required increases with the depth of the tunnel. And also, the lining stresses of the tunnel considering different groundwater conditions was analyzed. It was found that as depth of tunnel increases the axial forces experienced by the tunnel lining increases. Also, the axial forces, bending moments and shear forces mostly increases as the ground water level increases in the future.