Browsing by Author "Hasan, Nazmul"

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Bluebird Rent a Web Based house renting management system.
(Daffodil International University, 2024-01-26) Hasan, Nazmul
The Bluebird rent Renting Management System is a Web–based platform that simplify the houserenting process.Blubird rent are great resources for Family,bachelor who need house or flat for rent.By using Bluebird rent websites Family,bachelor can find flat or apartment from a variety of locations.The primary objectives of this websites is to reduce owner workload and reduce stress of the renter.Blubird rent offers the management of at poperties,bookings.It has interactive User Interface(UI) and improve the experience of the users.The Bluebird rent Management System Front-End building React.js and the Back-End building MongoDB(Node.js) based server.Now property owners can reduce workload.Using this web application renter can easily search property in their desire location from home and book propertytour
Design and development of a web based application named "Bluebird Rent"
(2024-01-26) Hasan, Nazmul
The Bluebird rent Renting Management System is a Web–based platform that simplify the houserenting process.Blubird rent are great resources for Family,bachelor who need house or flat for rent.By using Bluebird rent websites Family,bachelor can find flat or apartment from a variety of locations.The primary objectives of this websites is to reduce owner workload and reduce stress of the renter.Blubird rent offers the management of at poperties,bookings.It has interactive User Interface(UI) and improve the experience of the users.The Bluebird rent Management System Front-End building React.js and the Back-End building MongoDB(Node.js) based server.Now property owners can reduce workload.Using this web application renter can easily search property in their desire location from home and book property tour.
Design of a pure sine wave inverter for PV application
(BRAC University, 10/11/2011) Sayeed, Nuzhat Noor; Hossain, Ahmed Aaqib Sajjad; Hasan, Nazmul; Bhuiyan, Menhajul Abedin; Harun–Ur–Rashid, A.B.M
An inverter circuit by using Sinusoidal Pulse Width Modulation (SPWM) switching schemes is developed to run AC utilities. Inverter is a circuit that converts a DC source to an AC source. DC is one type of energy that is found in solar panels and can be stored in batteries for usage in future. Semiconductor device, Metal Oxide Field Effect Transistor (MOSFET) is used as switch in full bridge (H-Bridge) inverter configuration using Unipolar voltage switching . Driver circuit for MOSFET is also very important as it is used to interface between control circuits (Low voltage part ) and inverter (High voltage part ). PIC micro controller chip is used to generate modulating signals. The Programmable Interface Computer (PIC) is used PIC16F887 and MOSFET driver is IR2110. At the end of this project, the SPWM output signal is developed from the Micro-controller and applied to the MOSFET driver and the inverter .
Design of photovoltaic power conditioning incorporating maximum power point tracking of solar cell
(BRAC University, 2010) Syeed, Nuzhat Noor; Hossain, Ahmed Aaqib Sajjasd; Hasan, Nazmul; Bhiyan, Menhajul Abedin; Harun-Ur-Rashid, A.B.M
Identification of fake news using machine learning in distributed system
(BRAC University, 2021-06) Saif, Mehruz; Kanon, MD. Kamal Haque; Hasan, Nazmul; Hossen, MD. Shamim; Anannya, Fatema Zohra; Akhond, Mostafijur Rahman
The World Wide Web’s launch and the rapid adoption of social media platforms (such as Facebook and Twitter) paved the way for unparalleled levels of information diffusion in human history. Consumers are creating and sharing more information on social media platforms than ever before, some of it is erroneous, deceptive, or has no influence on reality. Access to news information has become considerably simpler and more comfortable thanks to the Internet and social media. Online users may often follow events of interest, and the widespread usage of mobile devices makes this process easier. However, with great potential comes enormous responsibility. There are also a number of websites dedicated nearly entirely to the dissemination of fake news. Since it’s a serious issue with a large-scale dataset, identification of fake news is very vital in this era, as social media and online newspapers are in large numbers in the web arena. That’s why it is easy to spread rumors and create chaos. Also, the size of data sets is increasing day by day. Data is expanding at a quicker rate than processing rates. As a result, algorithms that need a huge quantity of data and processing are frequently conducted on a distributed computing system that separates multiple nodes on several machines which have concurrency of components and lack of a global clock. Also, nobody has used a distributed system to detect fake news before. In our paper, we tried to run 4 PySpark algorithms based on SPARK-Context which provides massive storage for big data processing and analysis and also has been found to be 100 times quicker in-memory, while disk performance was shown to be 10 times quicker on several devices at the same time. So that we can control and real-time monitoring over the news and data before it goes viral in the media.
Islam and prevention of cyber crime
(©University of Dhaka, 2022-07-20) Hasan, Nazmul
This research focuses on cybercrime and its prevention from the sight of Islam. Cyber crime is also referred to as computer crime. It is one of the major challenges of fifth industrial revolution of ICT. The governments across the world, jurisdictions units, police departments and intelligence units have started to react to cyber crime in both the way preventive and curative. Since cyber crime is multi directorial phenomena of existing social crimes so it is almost impossible to prevent cyber crime with only a precise legal framework that only identify cyber offenders and prosecute them. The present technical protection measures in the prevention of cyber crimes in the world there are many circles and cases wherein such technology is not available or failed or circumvented by a number of barriers. This study has provided an overview of cyber crime and attempted to find the preventive measures from the ideals of Islam based on the main statement of Al-Qur’an, Al-Hadith as well as the opinions of Islamic jurists and commentators of different eras. This thesis paper have been organised in four parts for research facilitating. Each part has numerous chapters, each of which covers a specific amount of articles for the dissertation. In the first part of this thesis, it is attempted to discuss the reality review of the research. In the second part of this dissertation, it has been strived to present definitions and classifications of crime, criminal and victims. It has also focused on the cyber crime attack tools, causes, process chart and its history. In the third part of this thesis, it has been intended to analyze cyber crime cases and end level user experience. This part also includes cyber crime in social media. In the fourth part of this dissertation, it has been pursued to explain crime and punishment in Islam along with Islamic approach for combating crime, distinguishing features, goals of the Islamic penal system, crimes in the sense of Islam and its category. It has been intended to explore Islamic ideals to prevent cyber crime that includes crimes in cyber space, preventing cyber crime in Islam by Islamic ethics in IT. Different means and methods of organizing cyber crime have been discussed by studying the various incidents of cyber crime, cyber criminal behavior and attitudes, the harm and behavior of the person confessing to the cyber crime. It has been found that every criminal has committed the crime by disobeying certain Islamic ideals and maximum victims have fallen into this problem because of not following certain Islamic principles and norms in his or her personal life. Important preventive measures of cyber crime have been recommended in the thesis based on the findings from the principles and philosophies mentioned in Al-Quran and Al-Hadith. In the thesis it has been argued that it is possible to build a prosperous, happy and secured Bangladesh by implementing the commands and instructions of the Quran and the Hadith at every stage of human life.
Knowledge Attitude and Practice (Kap) of Selected Hospital Staff on Health Care Waste Management
(DIU Press, 2022-01-04) Hasan, Nazmul; Khandker, Salamat; Khan, Manzurul Haque; Ahmad, Sheikh Akhtar; Asha, Mamtaz Mariam; Ullah, Abu Naser Zafar
This cross-sectional study was carried out in 8 secondary and tertiary level hospitals of Dhaka and Rajshahi division to assess knowledge attitude and practice among health care waste handlers’ combination of quantitative and qualitative research methods was used, and results were used for triangulation purposes. For quantitative data, a semi-structured questionnaire and observation checklists were developed. For qualitative data, 16 Key Informant Interview (KII) and 4 Focused Group Discussions (FGDs) were conducted. The intervention hospitals have waste storage area and waste management instruction materials are posted on the hospital wall, verbal communication is also maintained for waste management and plastic wastes are shredded. The waste handlers wear gowns during waste handling and use trolley or container to carry the hospital waste. The non-intervention hospitals have no such practices. Doctors of both the groups were aware of the waste management manual and Waste Management Law but they did not practice that law. Practice of maintaining documentation of waste management system was a problem for all the respondents. Respondents of both groups stressed regular monitoring and suggested arranging formal training on HCW management. The hospital Waste Management Team was functionally inactive and not visible. It was recommended that provide training to waste handlers, fill in manpower gap, supply of sufficient logistics, implement internal checklist for monitoring, control number of visitors in hospital and sincerity of the local management could vastly improve the hospital waste management system.
LeukemiaCellNet: a hybrid CNN-transformer architecture for accurate classification of leukemia blood cells
(BRAC University, 2025-01) Hasan, Nazmul; Nahar, Syeda Rubaiya; Mostafa, Rakin; Mukta, Jannatun Noor
Timely and precise leukemia diagnosis remains a challenge in healthcare. This study improves accuracy utilizing powerful AI technologies, with a focus on deep learning models. This study examines CNN architectures, including VGG., Xception, Inception, ResNet, and DenseNet, together with transformer-based models like ViT, DaViT and MaxViT. A hybrid model merging ViT and ResNet50 was proposed, utilizing CNNs for image feature extraction and transformer networks for feature representation. Analysis using a medical-image dataset assessed the F1 score, recall, and precision of the model. Meanwhile, the model ResNet acquired an accuracy of 54.61% but the transformer models, MaxVit and Davit achieved 53%. However, ResNet50- ViT(Hybrid model) excelled all models, by attaining 92.87% accuracy with wellbalanced recall and precision. The findings illustrate the promise of fully automatic leukemia diagnosis as potentially disruptive, with the possibility of using hybrid AI models to address healthcare diagnostic problems in an accurate and timely manner. The combination of state-ofthe- art convolutional and attention mechanisms provides adequate solutions to the complexities associated with leukemia, setting a new standard for AI in hematology and opening new opportunities for the development of new automated diagnostic systems.
Leveraging Algorithms for depression detection in natural language processing
(Daffodil International University, 2024-01-25) Hasan, Nazmul
This research presents a comprehensive exploration of depression identification methodologies, employing a diverse array of classification algorithms, including Logistic Regression, Random Forest, Gradient Boosting, Multilayer Perceptron (MLP), and Long Short-Term Memory Networks (LSTMs). Utilizing a dataset comprising textual expressions, traditional machine learning models are juxtaposed against a deep learning paradigm, aiming to discern intricate patterns indicative of depression. Noteworthy outcomes emerge, with Logistic Regression and Random Forest achieving commendable accuracies of 95.60% and 95.69%, respectively. The study introduces an LSTM model, showcasing its potential in text-based depression identification, yielding an accuracy of 73.79%. Beyond quantitative assessments, the research delves into the societal impact, ethical considerations, and sustainability of the proposed models. Recognizing the significance of mental health awareness, this study contributes valuable insights into algorithmic frameworks for depression detection, fostering a nuanced understanding of their applicability, ethical considerations, and societal implications. The findings not only provide a comprehensive comparison of state-of-the-art models but also underscore the need for responsible deployment and sustainable practices in leveraging machine learning for mental health applications. As I navigate the complexities of mental health analysis, this research seeks to offer a holistic perspective, emphasizing ethical considerations and societal implications while opening avenues for future research and advancements in the domain.
Molecular detection of multi-drug resistant Enterococcus spp. from poultry in Chattogram, Bangladesh
(2024) Hasan, Nazmul
Enterococcus spp. are commensal bacteria found in the gastrointestinal tracts of both humans and animals. This can turn highly infectious when their relationship with the host is disrupted, particularly under stressful conditions. The objective of this study was to detect and characterize multi-drug resistant (MDR) Enterococcus spp, E. faecalis, and E. faecium in poultry cloacal samples from Chattogram, Bangladesh. A total of 60 cloacal samples from poultry (broiler, Sonali, and Deshi) were collected from live bird market (LBM) and commercial farm to detect Enterococcus spp., E. faecalis, and E. faecium. Antibiotic resistance profiles of these bacteria were determined using the disk diffusion method. Of the 60 cloacal samples from poultry, 40 (66.7%, 95% CI: 53.3%-78.3%) tested positive for Enterococcus spp. Among all the samples, only 2 (3.3%; 95%CI: 0.4%-11.5) were identified as Enterococcus faecalis. However, no E. faecium were detected in this study. Antibiotic susceptibility testing revealed that all Enterococcus spp isolates (n=40) frequently exhibited phenotypic resistance to sulfamethoxazole-trimethoprim and ciprofloxacin (80%), vancomycin (62.5%), ampicillin (55%). Moderate to lower resistance of Enterococcus spp. isolates were detected against gentamicin (47.5%), tigecycline (42.5%) and nitrofurantoin (30%). Out of 38 Enterococcus spp. isolates, 30 isolates (78.9%; 95% CI: 62.7%-90.4%) exhibited a phenotypic multidrug-resistant (MDR) profile. The multiple antibiotic resistance (MAR) indices of Enterococcus spp. isolates ranged from 0.14 to 1. Bivariate analysis revealed a high significant positive correlation between resistance profiles of tigecycline and ampicillin, vancomycin and ampicillin, nitrofurantoin and ampicillin, gentamycin and ciprofloxacin, vancomycin and tigecycline, nitrofurantoin and tigecycline, nitrofurantoin and vancomycin. The presence of MDR Enterococcus in poultry is alarming, as it highlights a potential public health threat due to their possibility to enter into the food chain.
Online Freelance Market Place “EarnBan” in Bangladesh
(Daffodil International University, 2021-05) l Islam, Md. Tariqu; Hasan, Nazmul
The project "Earnban" is a Bangladeshi freelance platform that we have created for people who are willing to work freelance or looking for workers. This project will play a helpful role in reducing the unemployment rate in our country. It is growing anxiously day by day and there is no freelance platform like this. So, we try to create a website for people who are looking for freelance work. In our project, people will have the opportunity to do their skill development. After finishing this project we tested the way we know as much as possible and it works successfully.
Remedial Effects of Homeopathic Drugs against Chronic Suppuration of Ear Caused by Pathogenic Microorganisms
(2019-10-07) Hasan, Nazmul
Chronic Suppurative Otitis Media (CSOM) is known as one of the most common infectious disease and is characterized by a persistent discharge from the middle ear through a perforated tympanic membrane. CSOM is considered as one of the most common cause of hearing impairment in the developing countries. Use and misuse of antibiotics for treating CSOM promotes antibiotic resistance leading to accelerated public health risks. Homeopathic medicines are mostly free from side effects, and therefore, this study was performed to evaluate the effects of homeopathic medicines for remedies of CSOM symptoms. A total of 70 subjects were included in this study; among them, 40 were suffering from CSOM and 30 were healthy control. The CSOM patients were randomly assigned for daily administration of homeopathic medicines such as tellurium metallicum in 6C potency (n=17), mercurius solubilis in 200C potency (n=13 ) and calcarea sulphurica in 30C potency (n=10 )for 8 weeks. Aural swab of the patients were examined to assess microbiological infection. Identification of the isolated microorganisms such as Staphylococcus sp., E coli, klebsiella sp. was confirmed with Analytical Profile Index (API ). The homeopathic medicines did not show significant antibacterial activity when assessed by agar disc diffusion; however, they reduced average microbial load significantly. Ear suppuration was prevented in all of the patients treated with the medicines. The patients were also examined with otoscope to observe the level of their tympanic membrane perforation and the healing of the perforated membrane after treatment. Among the seventeen (17) patients suffering from CSOM associated with membrane perforation, 9 patients’ (52.9% ) membranes were healed when treated with tellurium metallicum. Calcarea sulphurica also healed perforated tympanic membranes of 50% patients, however, mercuris solibulis failed to trigger membrane healing in treated patients. It was next examined whether the patients also had hearing impairment compared to healthy control subjects. The average hearing thresholds of the control subjects (n=30) at 1, 4, 8 and 12 kHz frequencies were 13.55 ± 1.57, 15.58 ± 1.12, 27.58 ± 2.00 and 32.57 ± 2.45 dB SPL, respectively. When the average hearing thresholds of the CSOM patients (n=40) were measured at all of the above frequencies, the values became 30.25 ± 1.75, 36.80 ± 3.25, 50.75 ± 2.35, and 59.50 ± 2.96 dB SPL, respectively. This result indicated that the CSOM patients were suffering from hearing loss as the average hearing thresholds of the CSOM patients at all the frequencies tested were significantly higher (p<0.05)than that of the control subjects. To our surprise, treatment for 8 weeks with all three homeopathic medicines significantly reduced (p<0.05) hearing thresholds of the patients at all the frequencies. This result clearly indicated that the patients experienced dramatic improvement in hearing by the homeopathic medicines. This study, therefore, provides conclusive evidence that homeopathic medicines prevent ear suppuration in CSOM patients as well as reduce microbial load, heal perforated membrane and improve hearing.
Robust and reliability-based multidisciplinary optimization of injection molding system
(Department of Industrial & Production Engineering, BUET, 2020-02-19) Hasan, Nazmul; Zaman, Dr. AKM Kais Bin
This thesis focuses on multidisciplinary design optimization (MDO) of amulti-cavity injection mold insert taking into account the multidisciplinary nature of the injection molding system. The proposed modifications in the conventional multi-cavity insert will allow flexibility in the production of a specified plastic part family. The use of the proposed flexible multi-cavity injection mold insert can contribute to the reduction of overall mold manufacturing costs. Aninjection molding machine using flexible multi-cavity inserts need to mold different part family members, whose specifications vary within a permissible limit. Hence, there exists uncertainty in the input variables. Two approaches: robustness-based design optimization (RDO) and reliability-based design optimization (RBDO) are used to handle the uncertainty in the input variables.The optimal design for the proposed multi-cavity insert considers the minimization of cycle time and pressure drop simultaneously. Therefore, a multi-objective optimization method is used in the problem formulation. Thus, this thesis solves the design problem using two formulations: the first oneintegrates MDO, RDO, and multi-objective optimization; the second oneintegrates MDO, RBDO, and multi-objective optimization.A numerical illustrationof the design problem is presented specifying a part family with respect to a particular model of injection molding machine and a particular polymermaterial. Finally, Pareto optimal solutions are obtained includingalternative combinations of cycle time and pressure drop. The flexiblemulti-cavity insert can be manufactured using the optimal values of the design variables corresponding to the selected combination of cycle time and pressure drop. The proposed moldinsert will be aneconomical solution forthe production of small plasticparts having dimensional similarity,e.g.,components of toys, cosmetic boxes, household containers, electric switches, etc.
Skill Evaluation and Career Mapping
(Daffodil International University, 2021-05-31) Badhon, Shourav Roy; Hasan, Nazmul; Zaman, Nadira
Software development is an emerging sector with a very big potential in Bangladesh. This is a sector where there is a need for professionals with knowledge of various methodologies, tools, and techniques. To have a knowledge of the requirements for the software industry is essential for job seekers in this sector. It is also required for universities and training centers for setting their curriculum. However, determining the necessary skills for a job and associating them with a job seeker is a difficult challenge. There is no easy way to find out requirements for specific types of job within the software development industry. For that reason, we have gone through 708 job ads from the Bangladesh software industry and made a dataset. Only technical skills were used to create the dataset. Soft skills such as teamwork, communication and customer orientation were excluded. Machine learning classifiers were used in the dataset to correlate different technical skills with different types of jobs. We have reported findings of various performance evaluation metrics that were used to evaluate this work. We found the best result from the Random Forest classifier. We have then used the best classifier to make a model. Using the model, we have developed an application where someone can check which type of job is suited for their skills. The purpose of this study is to help job seekers better understand the requirements of the Bangladesh software industry.
Sms Based Remote Control Device
(Daffodil International University, 2013-01-01) Hasan, Nazmul
This project is on “SMS Based Remote Control Device”, which presents a system of the PC remote Controlling with the Mobile Telephone through accessing the main PC ports; USB and parallel. USB port for transferring data from Mobile phone to PC and parallel port for interfacing PC with real time controlling hardware. The system is implemented by using the SMS (Short Message Service) as associated with Nokia mobile phone devices which support Nokia pc suite version 6 and mobile telecommunication networks. Nokia mobile phone device and with ordinary type of PC that run under Windows XP or compatible. The software for system is divided into two parts; Mobile to PC through USB port is a general commercial program that associated with the Nokia mobile devices, and second which access SMS file and control all parts of system is designed by using Microsoft Visual basic (vb 2008) . Such idea is quiet new and represents the ability of anyone who has Mobile and PC to control remotely major devices in his/her home, office and etc.
Socioeconomic Factors and Economic Performance of Different Scale Broiler Farms in Debidwar Upazila, Cumilla: A Questionnaire-Based Analysis.
(Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University, Khulshi, Chattogram-4225, Bangladesh, 2024-08) Hasan, Nazmul
Broiler farming in Bangladesh primarily consists of small-scale independent operations that have driven the industry's growth. Additionally, there is an experimental contract farming model currently under development. This study examined how small-scale broiler farms operate and how their size affects farmers' decisions. The research found that farm size significantly influences farmers' approaches and attitudes, which are crucial for improving broiler production. Data was collected from small-scale farms in Cumilla, Bangladesh. The study found that small-scale broiler farming is a profitable venture for rural farmers. On the contrary, larger farms with over 5,000 birds were significantly more profitable than smaller ones. Additionally, the costs associated with running larger farms were lower per bird, leading to improved economic efficiency. Farmers are drawn to broiler farming because it requires limited investment, space, and can be managed with family labor, providing rapid returns. Understanding how farmers think and act is vital for developing strategies to improve small-scale broiler farming.
The Prospect of Cloud Computing inTelecommunication Sector of Bangladesh
(Department of Computer Science and Engineering, Military Institute of Science and Technology, 2013-12) Islam, Raisul; Hasan, Nazmul; Riasat Ahmed, Mohammad
In the ﬁeld of IT cloud computing introduces a new era. Almost every part of the IT depends on this cloud computing. It is the latest technique of providing computational resources as a service. It reduces many hurdles in the ﬁeld of IT. This technology allows for much more efﬁcient computing by centralizing data storage, processing and bandwidth. The popularity of cloud computing is in creasing day by day. The main objective of this thesis is to introduce a cloud based mobile SIM card registration system that can be implemented with the help of a central database. In this research, the central database is the cloud storage which comprises with overall in formation of a citizen of any age. The database will enrich with one’s personal information(such as name, parents name, present and permanent address etc) phone number, mobile number, passport number, voter id number, educational and job experience related information. It should be mentioned that this central database can only be implemented by the Government and the proposed mobile registration system is completely count on it. This proposed system is online based, authenticated and efﬁcient. It minimizes the persecution of mobile SIM card registration as well as the volume of crime rate. This research paper has focused on the implementation processes, performance analysis and other inputs/outputs of the proposed system are provided in this paper. Finally, future expansion along with possibilities of practical execution is also drawn in this paper.
Traffic Sign Recognition System (TSRS)
(Daffodil International University, 2020-07-18) Hasan, Nazmul; Anzum, Tanvir
TSRS (Traffic Sign Recognition System) may play a significant role in a self-driving car, artificial driver assistances, traffic surveillance as well as traffic safety. Traffic sign recognition is necessary to overcome traffic-related difficulties. The traffic sign recognition system consists of two parts- localization and recognition. In the localization part, where traffic sign region is located and identified by creating a rectangular area. After that, in the recognition part, the rectangular box provided the result for which traffic sign is located in that particular region. In this paper, we describe an approach towards traffic signs recognition system. Here, we worked on 12 selected signs for traffic sign detection and recognition purpose. In this intention, we used Support Vector Machine (SVM) and Convolutional Neural Network (CNN) individually to detect and recognize the traffic signs. We obtained 98.33% accuracy for SVM with an 80:20 train and test data ratio. On the other hand, the test result was 96.40% accurate for CNN.
Traffic Sign Recognition System (Tsrs)
(Scopus, 2021) Hasan, Nazmul; Anzum, Tanvir; Jahan, Nusrat
TSRS (Traffic Sign Recognition System) may play a significant role in the self-driving car, artificial driver assistance, traffic surveillance as well as traffic safety. Traffic sign recognition is necessary to overcome the traffic-related difficulties. The traffic sign recognition system consists of two parts—localization and recognition. In the localization part, traffic sign region is located and identified by creating a rectangular area. After that, in recognition part, the rectangular box provided the result for which traffic sign is located in that particular region. In this paper, we describe an approach toward the traffic signs recognition system. Here, we worked on 12 selected signs for traffic sign detection and recognition purpose. In this intention, we used a support vector machine (SVM) and convolutional neural network (CNN) individually to detect and recognize the traffic signs. We obtained 98.33% accuracy for SVM with an 80:20 train and test data ratio. On the other hand, the test result was 96.40% accurate for CNN.