Browsing by Author "Islam, Md. Rakibul"

Now showing 1 - 20 of 33

A Bioinformatics Analysis to Identify Hub Genes from Protein-Protein Interaction Network for Cancer and Stress
(Springer, 2020-07-30) Ahmed, Md. Liton; Islam, Md. Rakibul; Paul, Bikash Kumar; Ahmed, Kawsar; Bhuyian, Touhid
Cancer is a disease involving the uncontrollable growth of cells with potential strafe to other organs of the body. Stress is a state of the body a non-specific response to any demand for change. Cancer had a deep relation with stress. Activation of the stress response and exposure to the associated hormones could promote the growth and spread of tumors. The immune system can be important for finding and eliminating cancer cells. This study is based on Cancer and Stress. In this study, we collect responsible genes from NCBI’s Gene database individually for stress and cancer. After that, common responsible genes were collected by using Venny online tools. From the common genes, we had constructed a protein-protein interaction network using the STRING database. Afterward, the top 10 hub genes were identified by using CytoHubba. Hub genes were identified based on their degree value where degree value more than or equal 72 are considered as hub gene. These hub genes may use to design a potential drug for cancer and stress combine. We have collected 3264 and 9433 human genes for Cancer and Stress respectively. 2477 common genes are found through Venny. We have been identified the UBC, TP53, RPS3, RPL5, RPL11, RPS27A, RPL19, RPL3, RPS7, and CTNNB1 as targeted hub genes by using the CytoHubba plugin of Cytoscape.
A critical Legal analysis on Medical Negligence in Bangladesh
(Daffodil International University, 2025-02-11) Islam, Md. Rakibul
Medical negligence is when healthcare professionals fail to do their job properly, causing harm to the patient and violating their right to good health. Medical mistakes or errors are currently a well- known subject of focus and discussion in many advanced countries. As a result, several of these countries have put in place separate laws and courts to make healthcare laws stronger. However, in Bangladesh, there are no specific laws to stop medical mistakes, even though there are some legal rules in different laws that are not clearly written down. Additionally, doctors and healthcare workers need to know and understand the legal effects of their mistakes in providing medical care. They also need to focus on behaving ethically in order to avoid getting caught up in controversial situations and legal cases. Medical practitioners sometimes avoid taking responsibility for their actions because people are not willing to report them or take action against them. Many individuals lack sufficient knowledge about their legal rights when faced with instances of medical negligence. This paper tries to explain medical negligence, the laws about it in Bangladesh and their problems, gather the necessary legal information and suggests ways to prevent violations of healthcare rights.
A look into parkinson’s disease and the implications of gene therapy as a novel clinical approach
(BRAC University, 2022-02) Islam, Md. Rakibul; Alam, Marzia
"Parkinson’s Disease (PD) is considered as one of the highest occurring neurodegenerative disorders. Motor complexities are the major symptoms of this disease which mainly includes bradykinesia, rigidity and tremor. Moreover, the non-motor symptoms can be included as mental and psychological complexities. Injury to the dopamine pathways is considered as the primary pathological reason of PD. Although the older population represents the majority of the patients, 5- 10% of the patients are relatively younger. Currently, dopamine replacement therapy with levodopa is the most common mode of treatment for alleviating the symptoms and retaining the functional capabilities. Here, gene therapy can be a viable treatment approach for such neurodegenerative disorders since it serves by knocking down the pathological genes. Even though few questions are yet to be answered before incorporating gene therapy in Parkinson’s disease, this novel therapeutic method has the potential to reshape the future of neurologic therapeutics."
A Machine Learning Approach for Emotion Classification in Bengali Speech
(Institute of Electrical and Electronics Engineers Inc., 2023-01-01) Islam, Md. Rakibul; Akhi, Amatul Bushra; Akter, Farzana; Rashid, Md Wasiul; Rumu, Ambia Islam; Lata, Munira Akter; Ashrafuzzaman, Md.
In this research work, we have presented a machine learning strategy for Bengali speech emotion categorization with a focus on Mel-frequency cepstral coefficients (MFCC) as features. The commonly utilized method of MFCC in speech processing has proved effective in obtaining crucial phoneme-specific data. This paper analyzes the efficacy of four machine learning algorithms: Random Forest, XGBoost, CatBoost, and Gradient Boosting, and tackles the paucity of research on emotion categorization in non-English languages, particularly Bengali. With CatBoost obtaining the greatest accuracy of 82.85%, Gradient Boosting coming in second with 81.19%, XGBoost coming in third with 80.03%, and Random Forest coming in fourth with 80.01%, experimental evaluation shows encouraging outcomes. MFCC features improve classification precision and offer insightful information on the distinctive qualities of emotions expressed in Bengali speech. By demonstrating how well MFCC characteristics can identify emotions in Bengali speech, this study advances the field of emotion classification. Future research can investigate more sophisticated feature extraction methods, look into how temporal dynamics are incorporated into emotion classification models, and investigate practical uses for emotion detection systems in Bengali speech. This study advances our knowledge of emotion classification and paves the way for more effective emotion identification systems in Bengali speech by utilizing MFCC and machine learning techniques. Our work addresses the need for thorough and efficient techniques to recognize and classify emotions in speech signals in the context of emotion categorization. Understanding emotions is essential for many applications, as they are a basic component of human communication. By investigating cutting-edge strategies that show promise for enhancing the precision and effectiveness of emotion recognition, this study advances the field of emotion classification.
Admission Helper: A Mobile Applications for Undergraduate Admission Applications
(Daffodil International University, 2019-12) Islam, Shaiful; Islam, Md. Rakibul; Das, Saikat; Opu, Sohel Rihan
Admission Test is a matter of concern for all the admitted candidates. So to minimize the sufferings of these aspirants, our admission test application made in a small effort. At present, the use of smartphones can be noticed everywhere. A large part of our admissions candidates live in the village or do not have admissions coaching in the city, so they are often unaware of all university admission tests, question patterns, exact time of form filling, and other important information. Therefore, if an admission examiner wants to install this application on his emperor's phone, he can benefit greatly through internet connection very easily, in a short time and with little effort. Our application has the advantage of almost all public and private information of Bangladesh, last year's question, the university's question pattern, and online test. Not only that through this application, but an examiner can also see the results of his or her examination from any university. Through this application, you can take the online test and know the result as well. Through which a student can verify himself which will increase their confidence.
Analysis different types of knitting faults occur in knitted fabric.
(Daffodil International University, 2018) Islam, Md. Rakibul; Biswas, Sumon Kumar
On this examination was finished distinctive kinds of single and double jersey machine faults and this article are cantered around wastage and how this sort of faults can be decreased. We likewise centred about various kind of issue those are face to done by the machine running. We get some issue. The real issue of these sorts of machine are wastage. We get some fault in dyeing and some other in finishing which we find out and doing develop of that faults .We plate how we might decrease the wastage of texture. Analyse the distinctive sort of existing procedure and creating procedure of that faults. It was very difficult to find out that faults and developing them in the same way. But in this experimental work we know how to do it and if we face any problem how to overcome that. For this study we collected different sample of common knit fabric fault and some quality inspection sheet done in 4 point system method from two reputed textile industry. Firstly we analysis the data from the quality inspection sheet and then we have analysed how changing the stitch length effects on the increasing or decreasing of majorly occurred faults on grey knit fabrics.
Automated License Plate Detection and Recognition
(Daffodil International University, 22-09-12) Rahman, Md. Habibur; Islam, Md. Rakibul
Automated license plate recognition is important in many contexts like security and law enforcement, monitoring vehicles, automated parking control, etc. To enable these automated services, we are reviewing and combining several established methods in this paper. There were three steps involved in reading car license plates: plate detection, plate extraction, and character recognition. Each stage has many sub-steps. For every sub-step, we have reviewed many methods, and chosen the one that proved to be the best solution after thorough testing and observation. The main objective of this research is to gain high accuracy using as less CPU Time as possible, keeping into consideration the facts like- lighting conditions, vehicle motion, noisy plates, and segmented words in the input image. Our primary target of this thesis is to extract a clean image of license plates of private or community vehicles. Although we target our system to be able to detect standard license plates, we also tested our methods on non-standard plates.
Automatic Power Theft Protection Using Arduino
(Daffodil International University, 2018-12) Islam, Md. Rakibul; Amin, Md. Nurul
Energy stealing is a highly general complication among countries as Bangladesh where consumers of energy are attractive consistently as the demography increment. Necessity in electricity process are ruiming the sum of produce every year remaining to energy stealing. It is perfectly unattainable to check and make up out stealing by going each customer’s door to door. In this project, a new method is pursued based on Microcontroller Atmega328P to find out and monitoring the energy meter from power stealing and it by remotely disconnect and reconnecting the service line of a particular consumer. An SMS will be sent automatically to the utility central server through GSM module whenever unauthorized activities detected and a separate message will send back to the microcontroller in order to disconnect the unauthorized supply.
Common Gene Regulatory Network for Anxiety Disorder Using Cytoscape
(Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer, 2019-04-13) Islam, Md. Rakibul; Ahmed, Md. Liton; Paul, Bikash Kumar; Asaduzzaman, Sayed; Ahmed, Kawsar
Data mining, computational biology and statistics are unified to a vast research area Bioinformatics. In this arena of diverse research, protein - protein interaction (PPI) is most crucial for functional biological progress. In this research work an investigation has been done by considering the several modules of data mining process. This investigation helps for the detection and analyzes gene regulatory network and PPI network for anxiety disorders. From this investigation a novel pathway has been found. Numerous studies have been done which exhibits that a strong association among diabetes, kidney disease and stroke for causing most libelous anxiety disorders. So it can be said that this research will be opened a new horizon in the area of several aspects of life science as well as Bioinformatics.
Comparative Study on Different Types of Sewing Faults for Different Factories
(Daffodil International University, 2022-03-12) Islam, Md. Rakibul; Akhter, Forida; Karim, Rezaul; Ahammed, Md. Al Shafe
Now a days Garments defect is one of the most important factors of the apparel manufacturing industry because it creates a negative effect on actual productivity. This paper aims with Different types of Defects which are the common term in the garment industry. In this research we have found that it is very essential to know about different types of Garments Defects. In garments industry these defects are dependent upon the classification of defects and an inspector’s ability to make decisions. If there is no idea of garments defects identification then it will be a tough job, but if it is known properly then it is an easy task to identify defects. So must know all types of Garments defects if we are involved with the apparel industry. It is the responsibility of the garments manufacturers to maintain a required Garments quality standard for each and every product they are offering or delivering to the buyers. After reading this project we have found that the idea about all types of garments defects sewing defects.
Compression Schemes for High Dimensional Data based on Extendible Multidimensional Arrays
(Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh., 2015-03) Islam, Md. Rakibul; Hasan, Dr. K. M. Azharul .
Traditional Multidimensional Array (TMA) is an important data structure for handling large scale multidimensional dataset, but they are not extendible during run time. Another problem for representing the real life data by multidimensional arrays is that it creates high degree of sparsity. Due to this sparsity problem and increasing size of the data structures, it becomes necessity to develop a suitable scheme to compress the multidimensional array in an efficient way so that it takes comparatively low memory storage. To minimize both of these sparsity and reorganization problem novel schemes are proposed to compress high dimensional data based on dynamically extendible array. In this research work we propose compression schemes based on Extendible multidimensional array. The proposed compression schemes are Extendible array based Compressed Row Storage (EaCRS) scheme, Linearized Extendible array based Compressed Row Storage (LEaCRS) scheme and Extendible array based Chunk Offset Compression Scheme (EaChOfJ. The main idea of both the EaCRS and LEaCRS scheme is to compress the subarrays independently found from the existing extendible array. LEaCRS scheme differs from EaCRS scheme only in the way that the LEaCRS scheme needs to linearize each subarray first and then compresses the subarray independently. EaChOJj scheme linearizes each subarray independently and breaks a large multi dimensional extendible array into chunks for compressing. In this scheme, a maximum size of each chunk is considered and chunks are formed by one or more subarrays. We evaluated our proposed schemes by comparing compression ratio, data retrieval time and extension cost with CR3 on TMA and ChunkOJjei Compression on TMA. Both analytical analysis and experimental tests were conducted. The analytical analysis and experimental results show that the proposed schemes have better range of usability and compression ratio for practical applications than traditional schemes. Furthermore, we found that the retrieval time of the proposed compression schemes are independent of different dimensions. The increment operation will be efficient in the proposed compression schemes than the existing traditional compression schemes because it increments without reorganizing the previous data.
Computational Modeling and Analysis of Gene Regulatory Interaction Network for Metabolic Disorder: a Bioinformatics Approach
(Biointerface Research in Applied Chemistry, 2020-04-22) Ahmed, Md. Liton; Islam, Md. Rakibul; Paul, Bikash Kumar; Ahmed, Kawsar; Bhuyian, Touhid
In this study, we generate a PPI network and co-regulatory networks to understand the mechanisms of metabolic disorder more clearly. This study also analyzes the relevance of genes that are responsible for Cardiovascular (CVD), Obesity (OBS), Type 2 diabetes (T2D) and Hypertension (HT). It also showed the common genome among CVD, OBS, T2D, and HT. Using Bioinformatics approaches, drugs are possible to design. For this study gene was collected from NCBI (National Center for Biotechnology Information) using R language. Primarily, 7197 genes were found for CVD, 3140 are for OBS, 3283 genes were for T2D and 2237 are for HT which were responsible for all species. Among those genes, 12 top-weighted common genes were selected for this research. Using these liable common genes, a protein-protein interaction network (PPI) and a regulatory interaction network were constructed. The PPI network shows the interaction among those genes. And the regulatory interaction network defines the direct and indirect connection among selected genes. The PPI network will help to design more reliable drug targets.
Deep Learning based Approach for Effective Hate Speech and Offensive Language Classification
(DAFFODIL INTERNATIONAL UNIVERSITY, 2024-08-14) Islam, Md. Rakibul
As hate speech is becoming more prevalent on social media platforms and has a negative impact on both individuals and groups, it is crucial to identify and mitigate hate speech in online environments. To solve this issue, the study suggests a method for automatically categorising tweets into three groups: Hate, Offensive, and Neither. We perform an extensive process of data collecting, preprocessing, and augmentation using a publicly available tweet dataset. Social media is used to collect initial datasets, which are then carefully cleaned to eliminate noise and unnecessary information. Synthetic data generation is usedto balance the dataset to overcome the prevalent problem of class imbalance in hate speech detection placement. To generate an innovative deep learning model that will improve the high accuracy detection and classification of hate speech and abusive language. We conduct experiments to construct LSTM and Bi-LSTM models along with a transfer learning strategy based on pre-trained language models, DistilBERT and BERT. While the BERT model performs better at capturing contextual information, we focus special attention to it. The performance of the models is greatly enhanced by the addition of synthetic hate speech data. After assessment the model on test data, we achieve an accuracy of over 91 percent. Additionally, this leads to better performance in the hate speech class. use of BERT's bidirectional training approach, which improves the capacity for local contextual understanding and classification. The work also advances the area by investigating advanced techniques for producing synthetic data, which results in a more evenly group instruction dataset. This method not only increases the generalizability of the model but also provides the way to more effective management of sensitive and contextually complicated hate speech. Social media platforms and brands could more effectively regulate and lessen the negative effects of toxic content by utilising the study's strong and scalable hate speech detection technology. By shielding users from offensive words, this method fosters a more secure and friendly online community. Furthermore, the study provides a standard for subsequent research, guiding the creation of deep learning models that are more effective at detecting hate speech in a variety of languages and cultural contexts.
Deep Learning-Based Chest X-Ray Analysis for Detection of Lung Diseases
(Daffodil International University, 2024-07-24) Islam, Md. Rakibul; Rifat, Sabbir Hossain
Early and accurate lung disease prediction and detection is very important for our patient. chestX-ray diagnosis methods are timeconsuming and sesitive process This research exploresdeep learning techniques to automate lung disease classification from chest X-ray images, enhancing diagnostic efficiency and accuracy. We focus on five conditions: Edema, Pneumonia, Tuberculosis, COVID-19, and the normal state.Due to privacy concerns inobtaining X-ray images directly from medical facilities, we utilized a Kaggle, nis.govandv7labs.com datasets of 14,631 chest X-ray images, verified by medical professionals. Thedataset was separated into 80% learning., 10% for testing,10% for assurance. To ensurearobust model, data augmentation techniques such as gamma correction, Image resizing, dataaugmentation, histogram equalization, noise reduction were applied, enhancing the dataset andimproving model performance.We evaluated several CNN model, including (CNN), ResNet50, VGG16, and DenseNet. Each model was assessed based on its training and validationaccuracies. DenseNet is became a very good model, gaining a training accuracy of 99.01%, testing accuracy of 89%, and validation accuracy of 88%, outperforming the other models. VGG16 and CNN also demonstrated high performance, with accuracies around 87%, whileResNet50 gained an accuracy of 80%.DIU Project ReportOur work underscores the potential of advanceddeeplearning models in classifying and identifying lung conditions based on chestX-ray pictures, highlighting a significant improvements in diagnostic efficiency and accuracy that thesetechnologies can offer.
Design Proposal of an Automatic Smart Multiinsect (Mosquito) Killing System
(Proceedings of 2019 3rd IEEE International Conference on Electrical, Computer and Communication Technologies, IEEE, 2019-02-22) Zeyad, Mohammad; Ghosh, Susmita; Islam, Md. Rakibul; Ahmed, S.M. Masum; Biswas, Prodip; Hossain, Eftakhar
The aim of this work is to create an automatic and low-cost mosquito killing device which will help to save human life from mosquito bite which is responsible for creating non-invented medicine diseases. This paper illustrates an idea of simple but smart mosquito catching window system. Due to the electrocution between the mesh structures of the device, mosquitoes as well as insects will be instantly killed when they will try to make their way through the window. Compared to available mosquito killing bat in the market, this system will hold up very low voltage that is enough to kill mosquito and concurrently not harmful for human being. This process uses microcontroller, ATmega328p that receives data from the adapter and helps to measure the input current and voltage which is displayed in an LCD Display (16*2) by using a logic algorithm code. It also consists of a power supply unit which is mainly used to charge the battery. The controls are made by a mini switch and have one LED power indicator.
Design Simulation and Performance Analysis of Microstrip Patch Array Antenna using HFSS
(East West University, 8/1/2015) Ahmed, Rizvi; Islam, Md. Rakibul
An antenna is a device (usually metallic) for sending or receiving electromagnetic waves. The antenna is an important part of radio equipment. The antenna has to be tuned to the right frequency or the radio waves can neither be emitted nor captured efficiently. In transmission, a radio transmitter applies a radio frequency to the terminals of the antenna and then the antenna radiates the energy from the antenna as electromagnetic waves. In reception, an antenna intercepts some of the power of an electromagnetic wave to produce a radio frequency at its terminals that is applied to a receiver in order to be amplified and demodulated. In some cases the same antenna can be used for both transmitting and receiving. There are several different kinds of antennas available at Future Electronics. We stock many of the most common types categorized by several parameters including operating frequency, power handling, gain, operating temperature range and type. These types include rubber ducky, embedded, conformal and weatherized.
E-Commerce Based Agricultural Web Application
(Daffodil International University, 2020-12-31) Halder, Partho Protim; Kaium, Md.Hasan Abdul; Islam, Md. Rakibul
Sabuj Chashi is an “E-commerce Based Agricultural Web Application” for the root level clients, fundamentally for the farmers to sell or purchase their produced items inside a good cost. Sabuj Chashi is mainly focusing on selling or purchasing rice at a lowest but acceptable price comparing with the government price. Our platform will also have the facilities of buying or selling of green plants & plantation related products. Our aim is to ensure the food at a lowest cost to everyone & also to ensure a greener Bangladesh. Within our platform, farmers will have the option to straightforwardly reach to the resellers that will give them the conceivable outcomes of getting additional costs of their items. It will diminish the middle of the road layers between the ranchers and the affiliates. Subsequently ranchers will have the option to get the real cost of their products. Thus both producers & consumers will be satisfied. When rice sellers will advertise their good through our platform, firstly we will verify them comparing with the government provided rice price list & afterwards if everything is perfect it will be visible to the consumers. Using our platform users will be able to get plant & others related products sitting at home. They just have to order their required items, rest responsibilities is ours. Thus we are going to create an e-gardening platform. We also have included agricultural supporting section within our platform. Through our supporting feature, users will be able to get the solution of their agricultural related problems from our enlisted agricultural specialists.
Exploring the World of Online News Portal at Dhaka Tribune
(BRAC University, 2022-09) Islam, Md. Rakibul; Chowdhury, Rukhsana Rahim
Generation and Operation of Ashuganj Power Station Company LTD.
(Daffodil International University, 2018-12) Islam, Md. Rakibul; Islam, Mohitul
Bangladesh is a developing country. Where lifestyle is much more improving and the mills and factories are growing not accordingly but in a great number. We need electric energy like our daily food. Overwhelming increasing number of office, apartments, mills, factories, schools, colleges and universities needs more and more electric energy. Besides, electricity demands are uprising day by day. To meet up the increasing demand we need to generate huge amount of electricity and there is only way to face this challenge either we increase the number of Power Plant in our country or fully renovate the old Power Plant in operation. On the other hand, increasing the number of power plant will surely redeemed the scarcity of the electric energy but may be it would become the hardest thing for the common people. By calculating the efficiency and economic statement a tariff should be imposed which will may remove the hardness of common people. In the meantime APSCL is the biggest Power Plant in the country in the generation of electric energy according to the other generation company in Bangladesh so far. Its’ installed capacity is 1875 MW which is fully functional and more capacity will be installed soon. In this theses we will know from Generation to Distribution and Instruments they uses. We can also know how it is transferred and where it is transferred. This will lead us to know better about power plant generation. And also know the economic and environmental aspects of APSCL production Process.
Identification of Molecular Biomarkers and Key Pathways for Esophageal Carcinoma (EsC)
(Daffodil International University, 2022-01-12) Islam, Md. Rakibul; Alam, Mohammad Khursheed; Paul, Bikash Kumar; Koundal, Deepika; Zaguia, Atef; Ahmed, Kawsar
Esophageal carcinoma (EsC) is a member of the cancer group that occurs in the esophagus; globally, it is known as one of the fatal malignancies. In this study, we used gene expression analysis to identify molecular biomarkers to propose therapeutic targets for the development of novel drugs. We consider EsC associated four different microarray datasets from the gene expression omnibus database. Statistical analysis is performed using R language and identified a total of 1083 differentially expressed genes (DEGs) in which 380 are overexpressed and 703 are underexpressed. The functional study is performed with the identified DEGs to screen significant Gene Ontology (GO) terms and associated pathways using the Database for Annotation, Visualization, and Integrated Discovery repository (DAVID). The analysis revealed that the overexpressed DEGs are principally connected with the protein export, axon guidance pathway, and the downexpressed DEGs are principally connected with the L13a-mediated translational silencing of ceruloplasmin expression, formation of a pool of free 40S subunits pathway. The STRING database used to collect protein-protein interaction (PPI) network information and visualize it with the Cytoscape software. We found 10 hub genes from the PPI network considering three methods in which the interleukin 6 (IL6) gene is the top in all methods. From the PPI, we found that identified clusters are associated with the complex I biogenesis, ubiquitination and proteasome degradation, signaling by interleukins, and Notch-HLH transcription pathway. The identified biomarkers and pathways may play an important role in the future for developing drugs for the EsC.