Browsing by Author "Hossain, Syed Akhter"

Now showing 1 - 20 of 102

A Bengali Text Generation Approach in Context of Abstractive Text Summarization Using RNN
(Lecture Notes in Networks and Systems, Springer, 2020-03-04) Abujar, Sheikh; Masum, Abu Kaisar Mohammad; Islam, Md. Sanzidul; Faisal, Fahad; Hossain, Syed Akhter
Automatic text summarization is one of the mentionable research areas of natural language processing. The amount of data is increasing rapidly, and the necessity of understanding the gist of any text is just a mandatory tool, nowadays. The area of text summarization has been developing since many years. Mentionable research has been already done through extractive summarization approach; in other side, abstractive summarization approach is the way to summarize any text as like human. Machine will be able to provide a new type of summarization, where the understanding of given summary may found as like as human-generated summary. Several research developments have already been done for abstractive summarization in English language. This paper shows a necessary method—“text generation” in context of Bengali abstractive text summarization development. Text generation helps the machine to understand the pattern of human-written text and then produce the output as is human-written text. A basis recurrent neural network (RNN) has been applied for this text generation approach. The most applicable and successful RNN—long short-term memory (LSTM)—has been applied. Contextual tokens have been used for the better sequence prediction. The proposed method has been developed in the context of making it useable for further development of abstractive text summarization.
A Comprehensive Study of Data Mining Techniques in Health-care, Medical, and Bioinformatics
(IEEE, 2018-09-20) Mia, Md. Robel; Hossain, Syed Akhter; Chhoton, Amit Chakraborty; Chakraborty, Narayan Ranjan
Data mining and Data warehousing is an imperative part of explore and is realistically worn in diverse domains resembling funding, quantifiable research, teaching, retail, e-business, marketing, health care etc. Many researchers have been systematically been reviewed and surveyed in health care, which is an active interdisciplinary area that is extent of data mining. The task of comprehension removal in the health care records is a demanding undertaking and intricate too. This review paper mainly focused on to find the existing data mining methods and techniques described in different academic literature based on health care data. Several data mining tools have been applied to set of selected diseases to find the accuracy of each particular tool. It is complicated to select one data mining tool for all kind of diseases analysis exhibition. Health care professionals can gain a solid understating from this study while selecting data mining tools to analyze their data.
A heuristic approach of text summarization for Bengali documentation
(IEEE Xplore, 2017-12-14) Abujar, Sheikh; Hasan, Mahmudul; Shahin, M.S.I; Hossain, Syed Akhter
Automated Text Summarization is a technique of summarizing any document or text automatically. Summarized text is the concise form of the given text. In Natural language processing many text summarization techniques are available for English language, but only a few for Bangla language. Bangla is one of the most taught and used language all over the world. Most of the text summarization techniques are implemented in two different ways, known as abstractive or extractive approach. This paper deal with the summarization of Bangla text based on extractive method. A new efficient extractive summarization method is proposed in this work. The other summarization tools developed for Bangla language seems not much appropriate from application point of view. The proposed analysis models are applicable for Bangla text summarization. In the proposed approach, basic extractive summarization is applied with new proposed model and a set of Bangla text analysis rules derived from the heuristics. Every Bangla sentences and words from original text is analyzed properly with Bangla sentence clustering method. This work proposed a new type of sentence scoring processes for Bangla text summarization. In the evaluation of this technique, the system reflects good accuracy of results, comparing to that of the human generated summarized result and other Bangla text summarization tools. Full Text Link: http://doi.org/10.1109/ICCCNT.2017.8204166
A Layered Framework for Virtual Guidance to Network Maintenance Based on Augmented Reality
(Springer, 2020-12-08) Hossain, Syed Akhter; Islam, Rishad; Rahman, Shahir; Nayeem, Shahriar
With the growing interest in Augmented Reality (AR) re-searchers and developers are engaged in developing systems with AR technologies. AR provides a unique experience in visualizing the solutions and provides an exciting way of interacting with the real world. The network management system is a complicated process that can be addressed efficiently by AR technologies. The visualization of network topology information of network devices decreases the burden of the network administrator to a great extent. In this paper, we proposed frameworks for both Platform Independent Model and Platform Specific Model which will be acting as a guide for the development of an application based on AR. We further developed a prototype for visualizing the network device information using the proposed framework. The prototype is acting as Proof of Principle (PoP) of our proposed framework. This prototype can be fully developed into a working application and installed in any organization with a network system as a guide for net-work device management and maintenance. The framework can also be modified to support various types of AR in different systems as per the requirement of the developer.
A Layered Framework for Virtual Guidance to Network Maintenance Based On Augmented Reality
(Scopus, 2021) Hossain, Syed Akhter; Islam, Rishad; Rahman, Shahir; Nayeem, Shahriar
With the growing interest in Augmented Reality (AR) re-searchers and developers are engaged in developing systems with AR technologies. AR provides a unique experience in visualizing the solutions and provides an exciting way of interacting with the real world. The network management system is a complicated process that can be addressed efficiently by AR technologies. The visualization of network topology information of network devices decreases the burden of the network administrator to a great extent. In this paper, we proposed frameworks for both Platform Independent Model and Platform Specific Model which will be acting as a guide for the development of an application based on AR. We further developed a prototype for visualizing the network device information using the proposed framework. The prototype is acting as Proof of Principle (PoP) of our proposed framework. This prototype can be fully developed into a working application and installed in any organization with a network system as a guide for net-work device management and maintenance. The framework can also be modified to support various types of AR in different systems as per the requirement of the developer.
A Machine Learning Approach to Predict SEER Cancer
(Springer, 2022-07-27) Abid, DM. Mehedi Hasan; Islam, Tariqul; Zaman, Zahura; Yusuf, Fahim; Assaduzzaman, Md.; Hossain, Syed Akhter; Jabiullah, Md. Ismail
The SEER database is among the persuading stores regarding malignancy pointers inside us. The SEER list helps impact investigation for the gigantic measure of patients’ bolstered viewpoints for the most part ordered as an insightful segment and impact. Assistant careful proof nearly the carcinoma dataset is ordinarily started on the site of the National Cancer Institute. The main point of this work is that depending on the individual’s manifestations, and we will foresee whether individuals are in danger of malignant growth or not. Perseverance and desire for the benefit of malignant growth patients have the option to upsurge prophetic exactitude and limit in the end cause better-educated decisions. To the current end, various amendments smear AI to disease data of the surveillance, epidemiology, and end results database. It may be used to better forecast cancer in the medical sector, and these studies can give a good chance to enhance existing models and build new models for uncommon cancers of minority groups in particular. In this paper, the authors contribute to getting more predicted accuracy for SEER cancer and use it to better forecast cancer in the medical sector.
A Proposed Web-Based Architecture for Diabetes Awareness, Prevention, and Management
(Springer Nature, 2018-12-12) Islam, Md. Ariful; Hossain, Syed Akhter; Mamun, Khondaker Abdullah Al
Diabetes is a growing concern and number of diabetes patient is increasing worldwide. Diabetes causes complication which leads to death in a long term. Proper lifestyle management is the key to control this disease. Treatment of diabetes is costly and complication caused by diabetes requires additional treatment. In developing countries, the situation is even worse. To address this problem, an innovative and cost-effective solution is required which will prevent diabetes and helps patient to modify their lifestyle. Web-based architecture can be very fruitful in this regard as it can be accessed from anywhere with IT enabled devices. With the existing infrastructure it can be used as a tool to create awareness, share knowledge and it can also help people to manage their lifestyle effectively. Interactive web-based platform can be used to show tips, diet measurement information and generate preventive measures. In this paper we have reviewed ICT enabled services and articles for diabetes awareness and prevention and proposed a web-based framework that can be used for screening diabetes and educating people about it. We are optimistic that, our proposed framework can improve the healthcare services and reduce the cost of healthcare making life easier.
A Proposed Web-Based Architecture for Diabetes Awareness, Prevention, and Management
(Scopus, 2020) Islam, Md. Ariful; Hossain, Syed Akhter; Mamun, Khondaker Abdullah Al
Diabetes is a growing concern and number of diabetes patient is increasing worldwide. Diabetes causes complication which leads to death in a long term. Proper lifestyle management is the key to control this disease. Treatment of diabetes is costly and complication caused by diabetes requires additional treatment. In developing countries, the situation is even worse. To address this problem, an innovative and cost-effective solution is required which will prevent diabetes and helps patient to modify their lifestyle. Web-based architecture can be very fruitful in this regard as it can be accessed from anywhere with IT enabled devices. With the existing infrastructure it can be used as a tool to create awareness, share knowledge and it can also help people to manage their lifestyle effectively. Interactive web-based platform can be used to show tips, diet measurement information and generate preventive measures. In this paper we have reviewed ICT enabled services and articles for diabetes awareness and prevention and proposed a web-based framework that can be used for screening diabetes and educating people about it. We are optimistic that, our proposed framework can improve the healthcare services and reduce the cost of healthcare making life easier.
A Simple and Mighty Arrowhead Detection Technique of Bangla Sign Language Characters with CNN
(Scopus, 2020) Islam, Md. Sanzidul; Mousumi, Sadia Sultana Sharmin; Rabby, AKM Shahariar Azad; Hossain, Syed Akhter
Sign Language is argued as the first Language for hearing impaired people. It is the most physical and obvious way for the deaf and dumb people who have speech and hearing problems to convey themselves and general people. So, an interpreter is wanted whereas a general people needs to communicate with a deaf and dumb person. In respect to Bangladesh, 2.4 million people uses sign language but the works are extremely few for Bangladeshi Sign Language (BdSL). In this paper, we attempt to represent a BdSL recognition model which are constructed using of 50 sets of hand sign images. Bangla Sign alphabets are identified by resolving its shape and assimilating its structures that abstract each sign. In proposed model, we used multi-layered Convolutional Neural Network (CNN). CNNs are able to automate the method of structure formulation. Finally the model gained 92% accuracy on our dataset.
A Systematic Way of Collecting Data of Insomniac Patients
(IEEE, 2020-07) Islam, Md. Muhaiminul; Masum, Abu Kaisar Mohammad; Abujar, Sheikh; Hossain, Syed Akhter
Insomnia (a sleeping disorder) can also be defined as sleeplessness that means facing trouble in falling or staying asleep. In this 20 th century, this disorder is very common among the olds and also teenagers. This disorder can harm vastly in our physical and mental health. So this is a serious fact in medical science. But these patients are rarely been hospitalized. Doctors usually predict this disorder considering the symptoms of patients. They use a questionnaire for it. Sleeping status, mental and physical conditions of patients both include in it. From the early days, it was a challenge for researchers to collect the data of these patients and analyze it. And the collection of these kinds of data is also a very difficult task to do. As this disorder expresses the mental and physical condition of a patient, one feels very uncomfortable to share their personal information with others. So there is no standard dataset available related to Insomnia. We have decided to collect the data of insomniac people for further research in the medical field. And an intelligent method is developed for the collection of data. Our dataset is preserved in such a way that machine learning algorithms can classify them in categories. Therefore the main objective of this study is to clarify the symptoms of this disorder and make a large dataset of it so that researchers can easily analyze the data and can make the appropriate output from their researches.
A Universal Way to Collect and Process Handwritten Data for Any Language
(Elsevier B.V., 2018-11-19) Rabby, AKM Shahariar Azad; Haque, Sadeka; Shahinoor, Shammi Akther; Abujar, Sheikh; Hossain, Syed Akhter
In recent years researches based on Machine learning and Deep learning have achieved much interest and one of its handwritten recognition. Handwritten recognition is very difficult due to its lack of dataset and also for collecting data from people. This research introduces a fast and comprehensive way to collect and process handwritten data to develop a way of Handwritten Recognition (HWR) algorithm for any languages. In this research handwritten characters wrote on a paper and then scanned to get the data into a JPEG format. We also focused on some of the other issues and requirements while collecting handwritten data, creating form, data collection methodology, process, using software and relevant tools. We described these issues in the context of our own effort to create a handwritten database for the Bangla language. Our designed Graphical User Interface (GUI) is also able to process 100 scanned images per minute where each scanned image contains 120 characters.
A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety in Students
(Scopus, 2021) Tamal, Maruf Ahmed; Akter, Rabia; Hossain, Syed Akhter; Rezaul, Karim Mohammed
The purpose of the current study was to develop an effective scale that can be used to assess the severity level of Mathematics Anxiety (MA) among students. Generally, measures for assessing MA adopt primitive questionnaires and unweighted rating-scale based approaches which are predominantly intended for a particular range of students. As a consequence, this type of approach is inherently static and not effective to be used widely. To bridge this gap, considering the view of 839 students, the present study has proposed a Weighted Scoring Based Mathematics Anxiety Rating Scale (WSB-MARS) which represents a more reliable, valid, generalized, and new approach to assess the severity level of mathematics anxiety in students. Besides, the proposed scale can be implemented as a mobile application that is applicable to the research & education field.
Abstractive Method of Text Summarization with Sequence to Sequence RNNs
(Scopus, 2019-07-08) Masum, Abu Kaisar Mohammad; Rabby, AKM Shahariar Azad; Talukder, Md. Ashraful Islam; Abujar, Sheikh; Hossain, Syed Akhter
Text summarization is one of the famous problems in natural language processing and deep learning in recent years. Generally, text summarization contains a short note on a large text document. Our main purpose is to create a short, fluent and understandable abstractive summary of a text document. For making a good summarizer we have used amazon fine food reviews dataset, which is available on Kaggle. We have used reviews text descriptions as our input data, and generated a simple summary of that review descriptions as our output. To assist produce some extensive summary, we have used a bi-directional RNN with LSTM's in encoding layer and attention model in decoding layer. And we applied the sequence to sequence model to generate a short summary of food descriptions. There are some challenges when we working with abstractive text summarizer such as text processing, vocabulary counting, missing word counting, word embedding, the efficiency of the model or reduce value of loss and response machine fluent summary. In this paper, the main goal was increased the efficiency and reduce train loss of sequence to sequence model for making a better abstractive text summarizer. In our experiment, we've successfully reduced the training loss with a value of 0.036 and our abstractive text summarizer able to create a short summary of English to English text.
AI and Blockchain Integration
(IEEE, 2020-06) Chavali, Bhaskar; Khatri, Sunil Kumar; Hossain, Syed Akhter
AI and Blockchain are two disruptive technologies that have the potential to change business models and impact the society. Their integration can lead to Decentralized AI, which enables analysis, decisions and self-learning on trusted and shared data stored on the Blockchain. Autonomous agents in a multi agent environment can collaborate, act and take decisions. Decentralized AI can help improve system performance by processing relevant data, as well as perform parallel processing across nodes based on different objectives. This paper reviews concepts of Blockchain, AI, power of combining these two technologies, and different platforms providing these capabilities.
Algorithms for synthesis and average distribution of variable sized MOS components for efficient Analog VLSI devices
(IEEE Xplore, 2008-07-25) Faisal Al Ameen, Mahmudul; Islam, Md. Didar; Hossain, Syed Akhter
In the field of Analog VLSI layout design, large variation of MOS component sizes causes mismatches and reduces the performance and splitting is necessary to reduce the variation. On the other hand, intensity of imposing always varies during fabrication. In this ongoing research, the solutions of above problems are introduced with some algorithm implementations. Two different sizes of components can be split into optimized number of pieces and an algorithm distributes them in an average and symmetrical (better) arrangement such that it can ensure average imposing and the efficiency increases. The computer generated solutions are compared with other possible solutions and proved better. Full Text Link: http://doi.org/10.1109/ICCITECHN.2007.4579437
An Approach for Bengali Automatic Question Answering System using Attention Mechanism
(IEEE, 2020-07) Bhuiyan, Md. Rafiuzzaman; Masum, Abu Kaisar Mohammad; Abdullahil-Oaphy, Md.; Hossain, Syed Akhter; Abujar, Sheikh
Question answering is a set of tools for obtaining detailed answers from user questions. At present, it is gaining very popularity day by day in the area of NLP research. There is a lot of work done in English. Still, become the seventh spoken language has not notable development at all. In Bengali very little work we've seen so far. Many types of problems can be solved by answering questions. Automatic question answering system is very much needed to solve various problems through Q&A. It is a very challenging task to create this type of system. In our paper we developed an automatic context based Question&Answering system using sequence to sequence architecture. An encoder layer will be used with a bi-directional LSTM and a decoder layer followed by an attention mechanism. The main challenge of this work is - data collection, finding the right vocabulary for word mapping and lots more. The main function of our model is to answer the questions. We have been able to successfully answer the question and reduce our training loss to 0.003.
An Approach for Bengali Text Summarization using Word2Vector
(Scopus, 2019-12-30) Abujar, Sheikh; Masum, Abu Kaisar Mohammad; Mohibullah, Md.; Ohidujjaman; Hossain, Syed Akhter
Text Summarization is one of the mentionable research areas of Natural language processing. Several approaches have already been developed in this concern. Such as - Abstractive approach and extractive approach. Most recent recurrent neural network methods are producing much better results. Several mentionable research has already been discussed for English language summarizer, but a few have already done for the Bengali language. There are so many prerequisites for data analysis purpose-word2vector is one of them. Understanding the vector representation of any text leads the way to identify the key main points of that specific text and helps to measure the relationship of that text with other texts in similarity/dissimilarity [11]. Generated matrix using word2vector can easily applicable for identifying top-ranked sentence/words, either domain specific or in general form. In this paper, a word2vector approach has been discussed in the context of text summarization for the Bengali language.
An Approach for Mango Disease Recognition using K-Means Clustering and SVM Classifier
(IEEE, 2019-11) Mia, Md. Robel; Chhoton, Amit Chakraborty; Mozumder, Mahadi Hasan; Hossain, Syed Akhter; Hossan, Awolad
Bangladesh extensively depends on agriculture in terms of economy as well as food security for its huge population. For this reason, it is very important to efficiently grow a plant and enhance its yield. We often face some problem which need to be solved. We build a Mango Disease Recognition system which can recognize the mango disease. It's Very useful to the farmers because using this system they can easily identify their mango disease which is very important to produce more fruits. Using our system user can easily identify the problem and they can take action for better production. There also some existing project of similar topic but theses project are not available to the all users. More over some system recognize disease very poorly and there have less accuracy and it's a huge problem to use the system. Comparing other system our system can be use more efficiently. Recognition of Mango diseases poses two challenging problems, i.e. detection and classification of disease. In here we used K means clustering for feature extraction and SVM for classification. The novelty of our work is that here we recognize the mango diseases which is not existing and our project accuracy is 94.13%. So we think user will be benefited from our project to produce more product which can effect in our economy.
An Attention Based Approach for Sentiment Analysis of Food Review Dataset
(IEEE, 2020) Bhuiyan, Md. Rafiuzzaman; Mahedi, Mahmudul Hasan; Hossain, Naimul; Tumpa, Zerin Nasrin; Hossain, Syed Akhter
Sentiment Analysis is a technique related to text analysis and natural language processing used to detect various types of insights or information from a portion of text. Over the past few years, researchers have done many works regarding this. In Bangladesh, many online services like-e-com become very popular day by day. One of them is online food delivery services. We can order various foods of our choice from online and sometimes people gives reviews based on that food. Those reviews are usually discarded as unstructured data which of them have no work in further. In this piece of research focus primarily on those unstructured data to analyze them in a correct manner to find insight into customers' behavior and their reactions on those online platforms. To do this experiment first we collect data from websites. Later deep learning-based techniques applied here. For baseline structure, we have used both CNN and LSTM models. Then for improving the model accuracy an attention mechanism applied followed by CNN which gives us 98.45% accuracy. We've also evaluated our model performances with some evaluation metrics also. From them, CNN based attention model gives a higher f1-score of 0.93.
An Effective Implementation of Web Crawling Technology to Retrieve Data from the World Wide Web (WWW)
(International Journal of Scientific and Technology Research, 2020) Shamrat, F. M. Javed Mehedi; Tasnim, Zarrin; Rahman, A.K.M Sazzadur; Nobel, Naimul Islam; Hossain, Syed Akhter
: Internet (or just the web) is enormous, well off, best, easily accessible and proper wellspring of data and its clients are expanding quickly now daily. To rescue data from the web, web indexes are utilized which access pages according to the prerequisite of the clients. The size of the web is exceptionally wide and contains organized semi-organized and unstructured information. The greater part of the information present on the web is unmanaged so it is absurd to expect to get to the entire web without a moment's delay in a solitary endeavor, so web crawlers use web crawlers. A web crawler is a fundamental piece of the web search tool. Data Retrieval manages to look and recovering data inside the reports and it likewise looks through the online databases and the web. In this paper, discussed, developed and programmed a web crawler to fetch the information from the internet and filter data for useable and graphical purpose for users.