Browsing by Author "Hassan, Mehedi"

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A Comparative Study of Different Machine Learning Tools in Detecting Diabetes
(Scopus, 2021) Ghosh, Pronab; Azam, , Sami; Karim, Asif; Hassan, Mehedi; Roy, Kuber; Jonkman, Mirjam
A significant proportion of people around the world are currently suffering from the harmful effects of diabetes and a considerable number of them not being identified at an early stage. Over time this may result in serious health problem such as blindness and kidney failure. To accurately classify the disease, different machine learning (ML) approaches can be utilized. In this context, four separate ML algorithms, namely Gradient Boosting (GB), Support Vector Machine (SVM) AdaBoost (AB), and Random Forest (RF) are evaluated using the Pima Indians diabetes dataset, first with based on all features, then to the features selected with the Minimal Redundancy Maximal Relevance (MRMR) Feature Selection (FS) approach. Seven different types of performance evaluation metrics were computed with a 10-fold cross-validation (CV) approach. Computational complexity is also evaluated. The best results were obtained with the Random Forest approach, achieving an accuracy of 99.35%.
A Comparative Study of Different Machine Learning Tools in Detecting Diabetes
(Scopus, 2021) Ghosh, Pronab; Azam, Sami; Karim, Asif; Hassan, Mehedi; Roy, Kuber; Jonkman, Mirjam
A significant proportion of people around the world are currently suffering from the harmful effects of diabetes and a considerable number of them not being identified at an early stage. Over time this may result in serious health problem such as blindness and kidney failure. To accurately classify the disease, different machine learning (ML) approaches can be utilized. In this context, four separate ML algorithms, namely Gradient Boosting (GB), Support Vector Machine (SVM) AdaBoost (AB), and Random Forest (RF) are evaluated using the Pima Indians diabetes dataset, first with based on all features, then to the features selected with the Minimal Redundancy Maximal Relevance (MRMR) Feature Selection (FS) approach. Seven different types of performance evaluation metrics were computed with a 10-fold cross-validation (CV) approach. Computational complexity is also evaluated. The best results were obtained with the Random Forest approach, achieving an accuracy of 99.35%.
A comparative study of vibrational characteristics of carbon fiber composite sandwich plates with truss-cores of different lattice structures
(IUT, MCE, 2016-11-20) Hassan, Mehedi; Nayeem, Md. Abu
The effective vibrational characteristics of sandwich plates with truss-cores of pyramidal truss lattice structure and reciprocal double-pyramidal truss lattice structure made of carbon fiber composite have been investigated theoretically in this paper. Analytical models were developed using ANSYS® finite element analysis software. Mode shapes and natural frequencies were investigated in both structures using ANSYS® Modal and a frequency versus mode curve was generated for both of the cases. Modal analysis was also done in both structures at different fiber orientations and a natural frequency versus fiber orientation curve was generated for each cases. Frequency response analysis was done using ANSYS® Harmonic and an amplitude (in decibel) versus frequency curve was generated for both of the lattice structures. At last, all of the results for both pyramidal truss lattice structure and reciprocal double-pyramidal truss lattice structure were compared and a conclusion was drawn depending on the results obtained from the investigation
A Machine Learning Approach to Analyze and Reduce Features to a Significant Number for Employee’s Turn Over Prediction Model
(Scopus, 2020) Alam, Mirza Mohtashim; Mohiuddin, Karishma; Islam, Md. Kabirul; Hassan, Mehedi; Hoque, Md. Arshad-Ul; Allayear, Shaikh Muhammad
Turnover of employee considers as one of the major issue that every company faces. Especially, if the employee has advance skills at his/her working field, then the company faces great loss during that period. To find out the most dominant reasons of employee attrition, we approach by determining features and using machine learning algorithms where features have been processed and reduced beforehand. We have proposed a new model where particular attributes of employee turnover have been selected and adjusted accordingly. In first phase of our reduction method, Sequential Backward Selection Algorithm (SBS) has been used to reduce the features from a higher number to a relatively smaller significant number. After that Chi2 and Random Forest importance algorithm have been used together for the second phase of reduction to determine the common important features by both of the algorithms which can be considered as the foremost features that lead to employee turnover. Our two steps feature selection technique confirms that there are mainly three features that are responsible for employee’s departure. Later, these selected minimal features have been tested with state of the art algorithms of machine learning, such as Decision Tree, Random Forest, Support Vector Machine, Multi-layer Perceptron (MLP), K-Nearest Neighbor (kNN) and Gaussian Naïve Bayes. Lastly, the test result has been visualized by 3D representation to learn the features that are precisely involved for the employee’s turnover.
A Machine Learning Approach to Analyze and Reduce Features to a Significant Number for Employee’s Turn Over Prediction Model
(Springer Nature, 2018-11-02) Alam, Mirza Mohtashim; Mohiuddin, Karishma; Islam, Md. Kabirul; Hassan, Mehedi; Hoque, Md. Arshad-Ul; Allayear, Shaikh Muhammad
Turnover of employee considers as one of the major issue that every company faces. Especially, if the employee has advance skills at his/her working field, then the company faces great loss during that period. To find out the most dominant reasons of employee attrition, we approach by determining features and using machine learning algorithms where features have been processed and reduced beforehand. We have proposed a new model where particular attributes of employee turnover have been selected and adjusted accordingly. In first phase of our reduction method, Sequential Backward Selection Algorithm has been used to reduce the features from a higher number to a relatively smaller significant number. After that Chi2 and Random Forest importance algorithm have been used together for the second phase of reduction to determine the common important features by both of the algorithms which can be considered as the foremost features that lead to employee turnover. Our two steps feature selection technique confirms that there are mainly three features that are responsible for employee’s departure. Later, these selected minimal features have been tested with state of the art algorithms of machine learning, such as Decision Tree, Random Forest, Support Vector Machine, Multi-layer Perceptron (MLP), K-Nearest Neighbor and Gaussian Naïve Bayes. Lastly, the test result has been visualized by 3D representation to learn the features that are precisely involved for the employee’s turnover.
A Mobile Application for Software Developers Community
(Daffodil International University, 2021-05-31) Hassan, Md. Mehedi; Hassan, Mehedi; Joy, Md. Jahedul Islam
In this project we tried to make a Social media app. We have looked at some other renowned Social media apps like Facebook , Instragram , Twitter , Telegram, We chat, Line, Viber, Imo etc. After this we have developed an android based application that works similarly to these above mentioned apps. In short we are going to call out the project as “Software Developers Community”. Here users can upload images and can comment on post and can also love react if a user wills to do so. ”. Here users can upload images and can comment on post and can also love react if a user wills to do so. Users can also chat in this app. We hope to create a platform where everyone can communicate with each other and interact with each other. Our main target is to create a platform for software developers where they can share their problems and get solution from other developers.
Activity Recognition of a Badminton Game Through Accelerometer and Gyroscope
(IUT, CSE, 2016-11-20) Anik, Md. Ariful Islam; Hassan, Mehedi
The scope for doing physical exercises in daily life is declining day by day. But, the importance of human physical exercise for a healthy life, remains the same. It is necessary to generate a solution to simulate the outdoor experience of physical exercises and sports inside our home. In this paper, we propose an idea of recognizing the activities of a badminton game which has the potential to be useful in simulating the Badminton Sport. We have used motion sensors (e.g. Accelerometer, Gyroscope) to recognize di erent activities like, serve, smash, backhand, forehand, return etc. We have collected data from a large set of users and labeled their data over several instances. We have applied the Root-Mean-Square(RMS),K-Nearest Neighbors (k-NN) and Support Vector Machines (SVM) and Dynamic Time Warping(DTW) classi ers and to recognize those activities. Existing approaches (e.g. Microsoft Xbox 360) used vision based techniques to recognize activities and use it in simulated games but we are using sensor based approach. Vision based approaches have some limitations such as the slow rate of data, illumination constraints, occluded backgrounds etc. Our approach gives a low cost solution with a classi cation technique which is faster. The experimental result shows a decent recognition rate.
Attendance Management System Using Face Recognition Model
(Daffodil International University, 2025-05-14) Hassan, Mehedi
In academical institutions, teachers are dependent on laborious, prone to mistakes, and easily misused methods, like fingerprint scanners or roll calls, to track attendance. This project offers a more suitable solution: a WEB-based facial recognition school management system. This technology takes students face data by a web cam or other camera connected to the system, checks them to match with the registered image, and automatically marks their attendance to provide a seamless and easy attendance system. This platform is so user-friendly as React and Django is used in frontend and backend. The features for the teachers are to select their assigned courses, to take attendance and of course to log in safely using JWT authentication. Each attendance record is linked with individual courses, so, the chance of duplication and proxy attendance is reduced. The system also provides the facility for downloadable attendance excel file and also have chances to make improvement like using as a mobile application and attendance-based research and monitoring
Bengali sentiment analysis based on product reviews: unveiling consumer voices
(BRAC University, 2024) Hassan, Mehedi; Pritom, Mujtaba Wasif; Fuad, Shahidul Islam; Sifat, Saif Ahmmed; Karim, Dewan Ziaul; Ahmed, Md Faisal
"These days, customers are more keen to buy products online rather than going to a shop or market. However, they often fear about the quality of products, as there is no way to measure them before buying them. As a result, most buyers rely on the reviews of other customers who have already purchased the product. For this reason, customer reviews are very crucial for the e-commerce industry. A popular method for assessing the quality of a product is opinion mining, which is also called sentiment analysis. It is a method of extracting emotion from a text using natural language processing (NLP). In this study, we have collected data from an e-commerce site named Daraz and introduced a new dataset that contains Bengali reviews. A total of 48000 reviews were collected, of which 22000 were Bengali. 15000 are in English, while the rest of 9000 are in “Banglish” (Romanized Bengali). Several data preprocessing techniques were used to introduce a new clean dataset that only contains Bengali reviews. Five machine learning algorithms—Naive Bayes, Random Forest, Gradient Boosting Classifier, Logistic Regression, and Support Vector Machine (SVM)—and three deep learning models—BiLSTM, Multilingual BERT, and BanglaBERT—were implemented to evaluate our work. Our work should help the sellers filter out the best products that are popular among consumers. "
Damping Performance Enhancement of a Power System by STATCOM and its Frequency Stability Consideration
(Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh., 2016-12) Hassan, Mehedi; Roy, Dr. Naruttam Kumar
This thesis investigates the damping performance of power systems through eigenvalue analysis and the impact of cyber-attack on power systems in frequency disturbing aspects during sudden changes of load. It also proposes a solution method to make the system stable. The analysis is firstly carried out on the Western System Coordinating Council (WSCC) 9-bus test system to find the impact of location of Flexible AC Transmission System (FACTS) devices on the static voltage stability. The maximum loadability of the load buses is determined using continuation power flow method with static var compensator (SVC) and static synchronous compensator (STATCOM). The result shows that the reactive power support from the FACTS devices depends on the proper placement of the FACTS devices in the network. The analysis is then conducted on an IEEE 14-bus test system. The maximum loading limits of the load buses are determined using continuation power flow method and a static synchronous compensator (STATCOM) is installed as an objective to increase the systems loadability. Then, the dominant modes and associated states that affect the damping of the system are identified and an oscillation damping controller is designed. The result shows that the proposed damping controller equipped with STATCOM can improve the damping performance of the system significantly. In order to analyze the impact of cyber attack on power systems, the stable limit of speed regulation for load frequency control (LFC) and integral controller gain for automatic generation control (AGC) is derived from their characteristic equations. Depending upon the nature of cyber-attack (positive biased or negative biased attack), simulations are performed to show the frequency deviations and oscillations of the power system. Finally, a feedback LFC block with a three input switch is proposed to remove these oscillations.
Design, modeling and control of a manipulator with bio-inspired soft robotic gripper
(BRAC University, 2026-01) Hassan, Mehedi; Anik, Tasnim Mahmud; Ahmed, Shafin; Talha, Abu; Rahman, Touhidur; Alam, Shahed; Oni, Atib Mohammad
Safe manipulation of delicate and irregularly shaped objects remains a major challenge for conventional rigid robotic systems due to their limited compliance and adaptability during physical interaction. To address this issue, this project presents a soft robotic manipulation system that integrates a 4-degree-of-freedom (4-DoF) rigid manipulator with a bio-inspired soft gripper, enabling adaptive grasping while supporting both manual and autonomous control modes. The system is developed using a structured, model-based design approach, beginning with theoretical kinematic and dynamic analysis, along with payload torque calculations to guide actuator selection and mechanical configuration. Based on these analyses, the manipulator and gripper are designed and evaluated in Autodesk Fusion 360, including static stress and motion studies, and subsequently fabricated using 3D printing. For modeling and control, a URDF-based robot description is implemented in a ROS2 and MoveIt2 environment, enabling collision-aware motion planning, workspace analysis, and repeatable end-effector positioning in both simulation and hardware. Numerical workspace sampling shows that the manipulator achieves an asymmetric reachable volume of approximately 0.77 m³ under joint and self-collision constraints. Autonomous perception is achieved using a vision-based object detection pipeline, where four deep learning models - YOLOv11-m, Faster R-CNN, RF-DETR, and RTMDet-m, are trained and evaluated on an 11-class manipulation dataset. Among these, YOLOv11-m provides the best overall balance of accuracy and efficiency, achieving 94.7% precision, 94.3% recall, and a [email protected]:0.95 of 0.86. The complete perception, planning, control pipeline is validated through simulation and real-world experiments using a ROS2 distributed architecture. Control performance is evaluated across randomized target poses, in simulation autonomous control achieves a mean positioning accuracy of 98.99% with an average execution time of 4.06s, compared to 70.08% accuracy and 46.72s for manual control. Physical experiments on fragile objects demonstrate grasp success rates of 33% in fully autonomous mode with an average execution time of 23s and 66% positioning accuracy under manual teleoperation with an average execution time of 51s. The results confirm the feasibility of the proposed soft robotic manipulation system while highlighting current hardware and actuation limitations. This project provides a practical foundation for low-cost soft robotic manipulators and offers clear opportunities for future improvement in autonomous performance, making it suitable for applications in industrial automation, agriculture, and service robotics where safe and compliant interaction is required.
Equity analysis & loan and advances of Mutual Trust Bank Limited (MTBL)
(BRAC University, 5/27/2015) Hassan, Mehedi; Siddiqui, Sayla Sowat
Now-a day‟s banking sector is modernizing and expanding its hand in different financial events every day. At the same time the banking process is becoming faster, easier and is becoming wider. There is a great supportive role of banking system in human society. It plays a vital role for the economic development of a country. The banking system of Bangladesh is backward, compared to many other nations. The local banks which are rendering services to mass people of the country are following the traditional system, which are no longer followed by bank in other development countries. It brings Bangladesh people to the touch of modern technology. Banking System of Bangladesh has gone through three phases of development – Nationalization, Privatization and lastly Financial Sector Reform. Mutual Trust Bank Ltd. (MTBL, the 3rd generation bank) has started its journey as a private commercial bank on 29 September, 1999. The Company (Bank) operates financial activities through its Head Office situated at Dhaka and 101 branches. The Company/ Bank carry out international business through a Global Network of Foreign Correspondent Banks. In this study, a fervent appeal has been made to demonstrate and analyze the equity part and Loan & Advance the subsequent outcome of Mutual Trust Bank Ltd. (MTBL), which is passing its childhood period to establish an iconic threshold in the banking arena. The title of the report is the “Internship Report Equity Analysis and Credit of Mutual Trust Bank Limited”. In the first chapter of this report the equity analysis part are stated with the financial statement of past 5 year. Using this financial figure the growth of the MTBL has been calculated and after that future five year financial statement has been forecasted. This is the first chapter of the report. Main part contains the forecasted Balance sheet of 2015 to 2019. The growth rate has been calculated on basis of calculating of past five year in a sequential face. This chapter also contains the Profit and Loss statement of Passed five 2009 to 2014 and using this financial figure future 5 year 2015 to 2019 year‟s profit and loss statement has been forecasted. After that main calculation has been started. Using this forecasted data Operating cash flow of 2015 to 2019 has been calculated. Then Change in net working capital and capital spending has been deducted from Operating cash flow with the resulted findings of Project cash flow of 2015 to 2019. Then here Net Present Value has been calculated of Project Cash Flow. This NPV figure is divided by the number of share outstanding of 31 Dec, 2014. Then the calculation ended by get the price of share to find out that share price is undervalued. Second main part contains the Loan and Advance details of Mutual trust bank. Mutual Trust Bank Ltd. offers different type of loan. The categories are divided according to the purpose of the loan. MTBL Offers mainly five types of Loan, these are MTB Personal Loan, MTB Auto Loan, MTB Home Loan, MTB Home and Equity Loan and MTB Professional Loan. These types of loan acquire different features as well as facilities. These loans are functioned according to the category. Difference in the loans category is amount, target customer, interest rate, loan process and etc. Different types of loan are as follow.
Network Based Study to Explore Genetic Linkage Between Diabetes Mellitus and Myocardial Ischemia
(Gene Reports, Elsevier, 2020-12) Hasan, Md. Tanvir; Hassan, Mehedi; Ahmed, Kawsar; Islam, Md. Rakibul; Islam, Kabirul; Bhuyian, Touhid; Uddin, Muhammad Shahin; Paul, Bikash Kumar
Globally, diabetes mellitus (DM) is one of the most occurred metabolic diseases, involving an increased level of blood glucose in the body. In general, DM patients grow many comorbidities including coronary heart disease, overweight gain, and stroke. Myocardial ischemia (MI) is a type of coronary heart disease, it occurs when heart muscles lost the ability to pump blood accurately. Though DM and MI are not associated but many biological functions of both disease match with each other. Our objectives were to uncover the association between the DM and MI using a bioinformatics approach with bio-molecular signature. We compare both datasets with the Venn diagram, the outcomes showed that 144 genes were overlapped in both disease. The GO analysis revealed that the majority amount of genes were connected with the cytokine-mediated signaling pathway, cytokine activity, and membrane raft. Pathway analysis explored the common 144 genes that were enriched with the AGE-RAGE signaling pathway in diabetic complications, malaria, and pathways in cancer. A protein-protein interaction (PPI) network was constructed using the Cytoscape. From where we identified 10 significant genes (INS, ALB, IL6, TNF, VEGFA, IL10, CCL2, IL1B, CXCL8, and ICAM1) according to their connectivity range using cytoHubba tool. Drug target analysis reveals that the dexamethasone CTD 00005779 target is the most associated with all the hub genes. Our analysis showed the genetic and biological functional associations between DM and MI. The outcomes of the study will help in future medications development of DM and MI.
Prediction of production rate for cultivable land correlating soil quality parameters and weather condition
(BRAC University, 2023-07) Hassan, Mehedi; Rahman, S.M. Mushfiqur; Sobhani, Shadman; Alam, A.M.Esfar-E-
In the modern time due to increasing global warming, the change of weather patterns and increase in pollution, the amount of crop production has been adversely affected. While on the other hand farmers trying to prevent this have been starting to use harmful fertilizers, insecticides and better growing crops. While doing that farmers are decreasing the soil fertility at an unnatural fast rate and making agricultural products that are becoming more and more harmful for human consumption in the long run. This has been having harmful effects on the human body like heart, liver and pancreatic problems or decrease in both male and female fertility. Bangladesh is a small riverain country with the staple food production of rice. It is the most commonly consumed food among the people. We believe that by analyzing the weather pattern of the previous years and analyzing the soil fertility with modern technologies it is possible to tackle the problems while making a cheaper investment by the farmers in the land on natural fertilizers and less pesticides. This paper intends to focus on the development of crop production in the agricultural field through comparing soil test data and weather conditions. The analysis of parameters can be proven to be accurate and less time-consuming as compared to traditional approaches. Moreover, the prediction can help the farmer to know the number of crops that can be grown in the next session.
Regulatory considerations and commercialization of 3D printed MN mediate vaccine delivery
(BRAC University, 2020-09) Hassan, Mehedi; Uddin, Md. Jasim
3D printing or additive manufacturing is a process first introduced at 1980s. Since then, it showed great achievements in fabricating complex structures with ease in sectors such as industry as well as medical and pharmaceutical sectors. Creation of complex structures such as scaffolds, patient specific implants and MNs are few example of 3D printing in medical and pharmaceutical sector. Although the setup of 3D printer and workstation is costly, novel techniques and development of novel biomaterials are showing promising future of 3D printing in pharmaceutical sectors. Over the past decade, the benefits of a MNs in TDD and several applications and benefits of MN were found out. In this review article, commercialization of 3D printing MNs were brought into lime light along with the probable cost, regulatory affairs and consequences of mass production of 3D printed microneedle.
Risk Factors Categorizations of Ischemic Heart Disease in South-Western Bangladesh
(China Science Publishing & Media Ltd., 2024-09-06) Raihan, M.; Azam, Sami; Akter, Laboni; Hassan, Mehedi; Quadir, Ryana; Karim, Asif; Mondal, Saikat; More, Arun
Ischemic heart disease (IHD) is one of the leading causes of death worldwide. However, different geographic regions show different variations of the risk factors of this disease based on the different lifestyles of people. This study examines the current IHD condition in southern Bangladesh, a Southeast Asian middle-income country. The main approach to this research is an AI-based proposal of a reduced set of the greatest impact clinical traits that may cause IHD. This approach attempts to reduce IHD morbidity and mortality by early detection of risk factors using the reduced set of clinical data. Demographic, diagnostic, and symptomatic features were considered for analysing this clinical data. Data pre-processing utilizes several machine learning techniques to select significant features and make meaningful interpretations. A proposed voting mechanism ranked the selected 138 features by their impact factor. In this regard, diverse patterns in correlations with variables, including age, sex, career, family history, obesity, etc., were calculated and explained in terms of voting scores. Among the 138 risk factors, three labels were categorized: high-risk, medium-risk, and low-risk features; 19 features were regarded as high, 25 were medium, and 94 were considered low impactful features. This research’s technological methodology and practical goals provide an innovative and resilient framework for addressing IHD, especially in less developed cities and townships of Bangladesh, where the general population’s socio-economic conditions are often unexpected. The data collection, pre-processing, and use of this study’s complete and comprehensive IHD patient dataset is another innovative addition. We believe that other relevant research initiatives will benefit from this work.
Risk Factors of Stomach Cancer Bangladesh Perspective
(Scopus, 2021) Royel, Md. Rejaul Islam; Hassan, Mehedi; Masud, Fuyad Al; Jaman, Md. Ajmanur; Ahmed, Arzo; Muyeed, Abdul
Background: Stomach cancer is known as gastric cancer. Knowing any disease risk factors is an important task which is varied from country to country. In this study, we aim to find out all possible preoperative significant risk factors for stomach cancer and increase awareness among the people of Bangladesh. Methodology: Personal interview methods have been applied and the same questionnaire is maintained to collect Case and Control Group Data. The total number of sample size is 300 (Case = 150 and Control = 150). Case group people’s data are collected from the National Institute of Cancer Research and Hospital (NICRH) Bangladesh and Control groups data are collected from outside of the hospital. The entire analysis took place by frequency distribution with P-value and finally doing binary logistic regression modeling by odds ratio. Results: After analyzing 300 subjects’ records with 26 risk factors, we have received 21 statistically significant (P< 0.05) risk factors where “Skin Color Turn into Pale” including (P<0.001, OR =139.462), and “Abdominal Pain” are the first and second most pre-operative risk factors of stomach cancer including (P<0.001, OR = 66.769). Besides, we have found other significant high-risk factors like “Age”, “BMI”, “Education Level”, “Get Ill Too Much (frequently affected by the disease)”, “Working Status”, “Monthly Income”, “Family Member”, “Blood Group”, “Daily Food Intime”, “Take Spicy and Salted Food”, “Menetrier Disease”, “Previous Stomach Surgery” and so on. Conclusion the investigated outcomes of this study will help to increase awareness among the people of Bangladesh as well as the rest of the world.
Spectrum allocation in cognitive radio networks based on shapley value
(BRAC University, 8/21/2017) Azad, Tabassum Binte; Hassan, Mehedi; Mahmud, Sejan; Jasmin, Humyra; Chakrabarty, Dr. Amitabha
In the era of spectrum allocation Cognitive Radio (CR) is a favorable solution to the lack of spectrum which is static for each type of communication device and operator causes the waste of a lot of idle spectrum. So that, Significant amount of research are focused on the application of game theory in effective spectrum allocation problem in cognitive radio. Proper utilization of spectrum is needed where the demand of the wireless communication rate is increasing. For fairly distributing those spectrum to unlicensed user by CR without creating interference to authorized users here we will provide a large content or scope to give a better allocation model based on Shapley Value of cooperative Game theory, which will contribute a detail inspection of flexible and logical spectrum allocation in wireless networks through general infrastructure. In this paper, shapely value algorithm has been applied for dynamic network where both authorized and unauthorized users can utilize the radio frequency at the same time with maximum throughput without interfering the authorized users. The allocation process is allowed only when a spectrum has been requested and idle spectrum is present in the network. Fair policy in the spectrum for the unauthorized users has been ensured with a universal price function. Here, results of the proposed method has been compared with other game theory’s (VCG model, Cournot , Bertrand) which have been applied for spectrum allocation in cognitive radio.
Spectrum allocation in cognitive radio networks based on Shapley value
(BRAC University, 8/21/2017) Azad, Tabassum Binte; Hassan, Mehedi; Mahmud, Sejan; Jasmin, Humyra; Chakrabarty, Dr. Amitabha
In the era of spectrum allocation Cognitive Radio (CR) is a favorable solution to the lack of spectrum which is static for each type of communication device and operator causes the waste of a lot of idle spectrum. So that, Significant amount of research are focused on the application of game theory in effective spectrum allocation problem in cognitive radio. Proper utilization of spectrum is needed where the demand of the wireless communication rate is increasing. For fairly distributing those spectrum to unlicensed user by CR without creating interference to authorized users here we will provide a large content or scope to give a better allocation model based on Shapley Value of cooperative Game theory, which will contribute a detail inspection of flexible and logical spectrum allocation in wireless networks through general infrastructure. In this paper, shapely value algorithm has been applied for dynamic network where both authorized and unauthorized users can utilize the radio frequency at the same time with maximum throughput without interfering the authorized users. The allocation process is allowed only when a spectrum has been requested and idle spectrum is present in the network. Fair policy in the spectrum for the unauthorized users has been ensured with a universal price function. Here, results of the proposed method has been compared with other game theory’s (VCG model, Cournot , Bertrand) which have been applied for spectrum allocation in cognitive radio.
Traffic Prioritization Using Packet Aggregation in Saturated WSN
(IUT, MCE, 2016-11-20) Hassan, Mehedi; Ibne Alam, Zubair
In the sensor networks, network tra c prioritization is gaining attention in the WSN community, as more and more features are being integrated these networks. Real-world deployment experience suggests that WSN brings new challenges to existing problems, such as resource constraints, low data-rate radios, and diverse application scenarios. But most of tra c prioritization problems deals with how to handle the HP (high-priority) data packet ignoring the LP (Low-Priority) data packet. Whenever any HP data packet arrives, LP data packet transmissions are suspended. This results in a loss of LP packets due to network congestion in a saturated network, weak radio signal, multi-path fading or cache over ow. We propose a framework that that will not suspend the LP data packet completely when any HP data packet has arrived. The framework will cache and aggregate the LP data packets and transmits the LP data packet after certain interval while transmitting the HP data packets. We di erentiate between the HP and LP data by leveraging transmission power di erence and radio-capture e ect. We classify the LP data tra c by using a hierarchical aggregation algorithm for data reduction of similar data. 5