Machine learning models have been very popular nowadays for providing rigorous solutions to compl... more Machine learning models have been very popular nowadays for providing rigorous solutions to complicated real-life problems. There are three main domains named supervised, unsupervised, and reinforcement. Supervised learning mainly deals with regression and classification. There exist several types of classification algorithms, and these are based on various bases. The classification performance varies based on the dataset velocity and the algorithm selection. In this article, we have focused on developing a model of angular nature that performs supervised classification. Here, we have used two shifting vectors named Support Direction Vector (SDV) and Support Origin Vector (SOV) to form a linear function. These vectors form a linear function to measure cosine-angle with both the target class data and the non-target class data. Considering target data points, the linear function takes such a position that minimizes its angle with target class data and maximizes its angle with non-targ...
International Journal of Engineering & Technology , 2021
Progression in machine learning and statistical inference are facilitating the advancement of dom... more Progression in machine learning and statistical inference are facilitating the advancement of domains like computer vision, natural language processing (NLP), automation & robotics, and so on. Among the different persuasive improvements in NLP, word embedding is one of the most used and revolutionary techniques. In this paper, we manifest an open-source library for Bangla word extraction systems named BnVec which expects to furnish the Bangla NLP research community by the utilization of some incredible word embedding techniques. The BnVec is splitted up into two parts, the first one is the Bangla suitable defined class to embed words with access to the six most popular word embedding schemes (CountVectorizer, TF-IDF, Hash Vectorizer, Word2vec, fastText, and GloVe). The other one is based on the pre-trained distributed word embedding system of Word2vec, fastText, and GloVe. The pre-trained models have been built by collecting content from the newspaper, social media, and Bangla wiki articles. The total number of tokens used to build the models exceeds 395,289,960. The paper additionally depicts the performance of these models by various hyper-parameter tuning and then analyzes the results.
International Journal of Advanced Computer Science and Applications, 2021
A woman's satisfaction with childbirth may have immediate and long-term effects on her health as ... more A woman's satisfaction with childbirth may have immediate and long-term effects on her health as well as on the relationship with her newborn child. The mode of baby delivery is genuinely vital to a delivery patient and her infant child. It might be a crucial factor for ensuring the safety of both the mother and the child. During the baby delivery, decision-making within a short time becomes very challenging for the physician. Besides, humans may make wrong decisions selecting the appropriate delivery mode of childbirth. A wrong decision increases the mother's life risk and can also be harmful to the newborn baby's health. Computer-aided decision-making can be an excellent solution to this problem. Considering this scope, we have built a supervised machine learning-based decision-making model to predict the most suitable childbirth mode that will reduce this risk. This work has applied 32 supervised classifier algorithms and 11 training methods on the real childbirth dataset from the Tarail Upazilla Health complex, Kishorganj, Bangladesh. We have also analyzed the result and compared them using various statistical parameters to determine the bestperformed model. The quadratic discriminant analysis has shown the highest accuracy of 0.979992 with the F1 score of 0.979962. Using this model to decide the appropriate labor mode may significantly reduce maternal and infant health risks.
Machine learning and deep learning have been perceived as a commended technique for different pat... more Machine learning and deep learning have been perceived as a commended technique for different pattern recognition purposes among data. A chunk of consideration has been given to social and demographic research and with an amalgamation of various machine learning and deep learning algorithms. In this paper, we anticipate structuring a machine learning and deep neural network based mechanized system that can effectively induce religion, sexual orientation utilizing just the names of the masses. Additionally, our goal stretches out by inferring valuable demographic attributes like region and religious conversion using some additional information like age and parent's name of the individual. By and large 10 machine learning and 3 deep learning algorithms are implemented to assemble this model which can derive 4 particular religions (Hindu, Muslim, Buddhist, and Christian), Gender (Male and Female), 6 regions (Dhaka, Khulna, Rajshahi, Chittagong, Sylhet, Barisal), and religious conversions with the most raised exactness pace. We also analyzed the performance and compared among all algorithms by using different statistical methods.
The ultimate goal of this research paper is to introduce a robust machine learning algorithm call... more The ultimate goal of this research paper is to introduce a robust machine learning algorithm called Impact-Learning, which is being used widely to achieve more advanced results on many machine-learning related challenges. Impact learning is a supervised machine learning algorithm for resolving classification and linear or polynomial regression knowledge from examples. It also contributes to analyzing systems for competitive data. This algorithm is unique for being capable of learning from a competition, which is the impact of independent features. In other words, it is trained by the impacts of the features from the intrinsic rate of natural increase (RNI). The input to the Impact Learning is a training set of numerical data. In this work, we used six datasets related to regressions and classifications as the experiment of the Impact Learning, and the comparison indicates that at outperforms other standard machine learning regressions and classifications algorithms such as Random forest tree, SVM, Naive Bayes, Logistic regression and so forth.
Applied Mathematics and Sciences: An International Journal (MathSJ), 2019
The main purpose of this research is to find out the best method through iterative methods for so... more The main purpose of this research is to find out the best method through iterative methods for solving the nonlinear equation. In this study, the four iterative methods are examined and emphasized to solve the nonlinear equations. From this method explained, the rate of convergence is demonstrated among the 1st degree based iterative methods. After that, the graphical development is established here with the help of the four iterative methods and these results are tested with various functions. An example of the algebraic equation is taken to exhibit the comparison of the approximate error among the methods. Moreover, two examples of the algebraic and transcendental equation are applied to verify the best method, as well as the level of errors, are shown graphically.
Algorithms for Intelligent Systems, Springer Nature, 2020
Regression is a process to estimate the bond among variables. It is a statistical technique and i... more Regression is a process to estimate the bond among variables. It is a statistical technique and is used as prediction with the curve fitting in machine learning, data science, economics etc. Linear and Polynomial regression is widely used to fit a curve and forecasting result. In this exploration, we propose two new linear and non-linear regression techniques using the strategy of interpolation-extrapolation and bisection of numerical analysis. However, interpolation and extrapolation cannot be applied in regression because of over fitting curve. In our paper, we have developed a technique to reduce the curve fitting that will enable the interpolation's and extrapolation's scheme to use in regression. Another procedure is to find out an equation of curve fitting with an optimal way using the Bisection Method. We also demonstrate the graphical presentations and comparison through all the occurring iterations.
The Bangla Informative Question Answering System (BIQAS) is a significant Machine Learning (ML) t... more The Bangla Informative Question Answering System (BIQAS) is a significant Machine Learning (ML) technique that helps a user to trace relevant information by Bengali Natural Language Processing (BNLP). In this research paper, we have applied three mathematical and statistical procedures for BIQAS based on question answering data. These procedures are cosine similarity, Jaccard similarity, and Naive Bayes algorithm. The cosine similarity has interacted with dimension reduction technique SVD on user questions and questions answering data in order to reduce the space and time complexity. These procedures of this research are separated into two parts: pre-processing data and establishment of a relationship between user's questions and contained informative questions. We have got 93.22% accurate answer by using cosine similarity, 84.64% by Jaccard similarity and 91.31% by Naïve Bayes algorithm.
Type 2 Diabetes is a fast-growing, chronic metabolic disorder due to imbalanced insulin activity.... more Type 2 Diabetes is a fast-growing, chronic metabolic disorder due to imbalanced insulin activity. As lots of people are suffering from it, access to proper treatment is necessary to control the problem. Most patients are unaware of health complexity, symptoms and risk factors before diabetes. The motion of this research is a comparative study of seven machine learning classifiers and an artificial neural network method to prognosticate the detection and treatment of diabetes with a high accuracy, in order to identify and treat diabetes patients at an early age. Our training and test dataset is an accumulation of 9483 diabetes patients' information. The training dataset is large enough to negate overfitting and provide for highly accurate test performance. We use performance measures such as accuracy and precision to find out the best algorithm deep ANN which outperforms with 95.14% accuracy among all other tested machine learning classifiers. We hope our high performing model can be used by hospitals to predict diabetes and drive research into more accurate prediction models.
For the time being, Cricket is an indisputably one of the most interesting game in the world, esp... more For the time being, Cricket is an indisputably one of the most interesting game in the world, especially in the territory of South Asian. As human beings are prone to error, sometimes errors have happened to an umpire and about a constant time is taken by the third umpire for an exact decision of a review. The two different domains artificial intelligence and computer vision have become pop in cricket analysis and decision making. Using different types of computer vision's procedures in exploring several Cricket cases and automatically turning into decisions have become exoteric in recent days. In this research paper, we have propounded a classification method by the aids of Convolutional Neural Network (CNN) with Inception V3 in order to automatically unroll the decisions of third umpire and scoring system such as umpire signal detection. We have also proposed the deep CNN technique that aids to increase the performance of CNN.
Bengali Informative Chatbot (BIC) is an effective technique that helps a user to trace relevant i... more Bengali Informative Chatbot (BIC) is an effective technique that helps a user to trace relevant information by Natural Language Processing (NLP). In this research paper, we introduce an algorithmic Bengali Informative Chatbot (BIC) based on information that is significant mathematically and statistically. This paper is demonstrated by two algorithms for finding out the lemmatization of Bengali words such as Trie and Dictionary Based Search by Removing Affix (DBSRA) as well as compared with Edit Distance for the exact lemmatization. We present the Bengali Anaphora resolution system using the Hobbs' algorithm to get the correct expression of information. As the actions of chatbot replying algorithms, the TF-IDF and Cosine Similarity are developed to find out the accurate answer from the documents. In this study, we introduce a Bengali Language Toolkit (BLTK) and Bengali Language Expression (BRE) that make the easiest implication of our task. We have also developed Bengali root word's corpus, synonym word's corpus, stop word's corpus and gathered 672 articles as questions and answers form the popular Bengali newspapers 'The Daily Prothom Alo' is our inserted information. For testing this system, we have created 19334 questions from the introduced information and got 97.22% accurate answer by proposed BIC.
Applied Mathematics and Sciences: An International Journal, 2019
The main goal of this research is to give the complete conception about numerical integration inc... more The main goal of this research is to give the complete conception about numerical integration including Newton-Cotes formulas and aimed at comparing the rate of performance or the rate of accuracy of Trapezoidal, Simpson's 1/3, and Simpson's 3/8. To verify the accuracy, we compare each rules demonstrating the smallest error values among them. The software package MATLAB R2013a is applied to determine the best method, as well as the results, are compared. It includes graphical comparisons mentioning these methods graphically. After all, it is then emphasized that the among methods considered, Simpson's 1/3 is more effective and accurate subdivision is only even the when the condition of for solving a definite integral.
This Scientific Research paper is a procedure of an automated system "Doly: Bengali Chatbot" whic... more This Scientific Research paper is a procedure of an automated system "Doly: Bengali Chatbot" which gives a reply to a user query on behalf of a human for the education system in the Bengali language. This is an AI-based Chatbot, mainly based on machine learning algorithms and Bengali Natural Language Processing (BNLP). The machine gets embedded with this knowledge to identify the desired sentences and making a decision within itself, as a response to answer questions. There are many English Chatbot's which used in education, web query, banking sector & various sectors. In this research, we have propounded a complete data-driven retrieval based closed domain Chatbot which is easily colloquy in the Bengali language with the users. We've created the train function adapter to train the Doly by encoding (encoding="utf8") our corpus from bot data. An input adapter has been created to take input and for output, an output adapter has been created to generate automated responses to a user's input. We have also used a machine learning algorithm like search algorithm for finding an appropriate list of matching results from the corpus and use Naïve Bayesian algorithm to generate the right answer from data. The main aim of this Chatbot based system is to bridge the gap between the knowledge sources by providing instant replies to the questions and queries that have to ask in the Bengali language.
Applied Mathematics and Sciences: An International Journal (MathSJ), 2019
The main purpose of this research is to find out the best method through iterative methods for so... more The main purpose of this research is to find out the best method through iterative methods for solving the nonlinear equation. In this study, the four iterative methods are examined and emphasized to solve the nonlinear equations. From this method explained, the rate of convergence is demonstrated among the 1st degree based iterative methods. After that, the graphical development is established here with the help of the four iterative methods and these results are tested with various functions. An example of the algebraic equation is taken to exhibit the comparison of the approximate error among the methods. Moreover, two examples of the algebraic and transcendental equation are applied to verify the best method, as well as the level of errors, are shown graphically.
Applied Mathematics and Sciences: An International Journal(MathSJ), 2019
In Numerical analysis, interpolation is a manner of calculating the unknown values of a function ... more In Numerical analysis, interpolation is a manner of calculating the unknown values of a function for any conferred value of argument within the limit of the arguments. It provides basically a concept of estimating unknown data with the aid of relating acquainted data. The main goal of this research is to constitute a central difference interpolation method which is derived from the combination of Gauss's third formula, Gauss's Backward formula and Gauss's forward formula. We have also demonstrated the graphical presentations as well as comparison through all the existing interpolation formulas with our propound method of central difference interpolation. By the comparison and graphical presentation, the new method gives the best result with the lowest error from another existing interpolation formula.
Bangladesh Mathematical Society National Mathematics Conference, 2018
Fraud detection which is a discussible phenomenon to many bounds together with financial sectors,... more Fraud detection which is a discussible phenomenon to many bounds together with financial sectors, banking, insurance as well as diverse forms of industries. Nowadays fraud endeavors are being amplifying with rampant pace especially via the development of technology, so building fraud discovery more significant than ever before. In this paper, we analyzed the fraud operations by managing "Banking Fraud Detection" database by the combination of mathematical, statistical as well as machine learning ways and tried to spectacle a comparison among this ways. We narrated the elementary explorations by the combining methods such as mathematical, statistical as well as machine learning to equip the ways of insidious banking transactions.
Information Retrieval System is an effective process that helps a user to trace relevant informat... more Information Retrieval System is an effective process that helps a user to trace relevant information by Natural Language Processing (NLP). In this research paper, we have presented present an algorithmic Information Retrieval System(BIRS) based on information and the system is significant mathematically and statistically. This paper is demonstrated by two algorithms for finding out the lemmatization of Bengali words such as Trie and Dictionary Based Search by Removing Affix (DBSRA) as well as compared with Edit Distance for the exact lemmatization. We have presented the Bengali Anaphora resolution system using the Hobbs' algorithm to get the correct expression of information. As the actions of questions answering algorithms, the TF-IDF and Cosine Similarity are developed to find out the accurate answer from the documents. In this study, we have introduced a Bengali Language Toolkit (BLTK) and Bengali Language Expression (BRE) that make the easiest implication of our task. We have also developed Bengali root word's corpus, synonym word's corpus, stop word's corpus and gathered 672 articles from the popular Bengali newspapers 'The Daily Prothom Alo' which is our inserted information. For testing this system, we have created 19335 questions from the introduced information and got 97.22% accurate answer.
Algorithms for Intelligent Systems, Springer, 2020
In this research, we have examined type 2 diabetics treatment and medication detection using seve... more In this research, we have examined type 2 diabetics treatment and medication detection using seven classifier algorithms. We have created a decision tree-based procedure with genetic and clinical features such as Fasting, 2 h after the glucose load, BMI, Duration (years), Age, gender-specific, and blood pressure for the treatment of type 2 diabetic patients. Medical treatment prevents some complications, but does not usually restore normoglycemia or remove all the adverse consequences. The tool here is to give a correct report to justify the right medications for a patient. Imparting a fivefold cross-validation process, the operation of applying clinical features of 666 type 2 diabetic patients in 7 classifiers Logistic Regression, Linear Discriminant Analysis, k-nearest neighbors, Decision Tree, Naive Bayes, support vector machine, and Random forest classifier. In this paper, this system support to change lifestyle and right medications for treatment, which assists to reduce the probability of type 2 diabetes in persons.
The Bengali Informative Intelligence Bot (BIIB) is an effective Machine Learning (ML) t... more The Bengali Informative Intelligence Bot (BIIB) is an effective Machine Learning (ML) technique that helps a user to trace relevant information by Bengali Natural Language Processing (BNLP). In this book, we introduce two mathematical and statistical procedures for BIIB based on information of Noakhali Science and Technology University (NSTU) that is significant mathematically and statistically. In the preprocessing part, this book is demonstrated by two algorithms for finding out the lemmatization of Bengali words such as Trie and Dictionary Based Search by Removing Affix (DBSRA) as well as compared with Edit Distance for the exact lemmatization. We present the Bengali Anaphora Resolution system using the Hobbs‘ algorithm to get the correct expression of consequence questions. In order to reduce the time complexity of searching questions and reply from inserted information, we have used Non-negative Matrix Factorization (NMF) as the topic modeling technique, and the Singular Value Decomposition (SVD) as to reduce the dimension of questions. TF-IDF (Term Frequency-Inverse Document Frequency) has been used to convert character and/or string terms into numerical values, and to find their sentiments. For the action of chatbot in replying questions, we have applied the TF-IDF, cosine similarity and Jaccard similarity to find out the accurate answer from the documents. In this study, we introduce a Bengali Language Toolkit (BLTK) and Bengali Language Expression (BRE) that make the easiest implementation of our task. We have also developed Bengali root word‘s corpus, synonym word‘s corpus, stop word‘s corpus, and collected 74 topic related questions and answers from the information of NSTU which are actually our inserted informative questions. For verifying our proposed systems, we have created 2852 questions from the introduced topics. We have got 96.22% accurate answer by using cosine similarity and 84.64% by Jaccard similarity in our proposed BIIB.
Machine learning models have been very popular nowadays for providing rigorous solutions to compl... more Machine learning models have been very popular nowadays for providing rigorous solutions to complicated real-life problems. There are three main domains named supervised, unsupervised, and reinforcement. Supervised learning mainly deals with regression and classification. There exist several types of classification algorithms, and these are based on various bases. The classification performance varies based on the dataset velocity and the algorithm selection. In this article, we have focused on developing a model of angular nature that performs supervised classification. Here, we have used two shifting vectors named Support Direction Vector (SDV) and Support Origin Vector (SOV) to form a linear function. These vectors form a linear function to measure cosine-angle with both the target class data and the non-target class data. Considering target data points, the linear function takes such a position that minimizes its angle with target class data and maximizes its angle with non-targ...
International Journal of Engineering & Technology , 2021
Progression in machine learning and statistical inference are facilitating the advancement of dom... more Progression in machine learning and statistical inference are facilitating the advancement of domains like computer vision, natural language processing (NLP), automation & robotics, and so on. Among the different persuasive improvements in NLP, word embedding is one of the most used and revolutionary techniques. In this paper, we manifest an open-source library for Bangla word extraction systems named BnVec which expects to furnish the Bangla NLP research community by the utilization of some incredible word embedding techniques. The BnVec is splitted up into two parts, the first one is the Bangla suitable defined class to embed words with access to the six most popular word embedding schemes (CountVectorizer, TF-IDF, Hash Vectorizer, Word2vec, fastText, and GloVe). The other one is based on the pre-trained distributed word embedding system of Word2vec, fastText, and GloVe. The pre-trained models have been built by collecting content from the newspaper, social media, and Bangla wiki articles. The total number of tokens used to build the models exceeds 395,289,960. The paper additionally depicts the performance of these models by various hyper-parameter tuning and then analyzes the results.
International Journal of Advanced Computer Science and Applications, 2021
A woman's satisfaction with childbirth may have immediate and long-term effects on her health as ... more A woman's satisfaction with childbirth may have immediate and long-term effects on her health as well as on the relationship with her newborn child. The mode of baby delivery is genuinely vital to a delivery patient and her infant child. It might be a crucial factor for ensuring the safety of both the mother and the child. During the baby delivery, decision-making within a short time becomes very challenging for the physician. Besides, humans may make wrong decisions selecting the appropriate delivery mode of childbirth. A wrong decision increases the mother's life risk and can also be harmful to the newborn baby's health. Computer-aided decision-making can be an excellent solution to this problem. Considering this scope, we have built a supervised machine learning-based decision-making model to predict the most suitable childbirth mode that will reduce this risk. This work has applied 32 supervised classifier algorithms and 11 training methods on the real childbirth dataset from the Tarail Upazilla Health complex, Kishorganj, Bangladesh. We have also analyzed the result and compared them using various statistical parameters to determine the bestperformed model. The quadratic discriminant analysis has shown the highest accuracy of 0.979992 with the F1 score of 0.979962. Using this model to decide the appropriate labor mode may significantly reduce maternal and infant health risks.
Machine learning and deep learning have been perceived as a commended technique for different pat... more Machine learning and deep learning have been perceived as a commended technique for different pattern recognition purposes among data. A chunk of consideration has been given to social and demographic research and with an amalgamation of various machine learning and deep learning algorithms. In this paper, we anticipate structuring a machine learning and deep neural network based mechanized system that can effectively induce religion, sexual orientation utilizing just the names of the masses. Additionally, our goal stretches out by inferring valuable demographic attributes like region and religious conversion using some additional information like age and parent's name of the individual. By and large 10 machine learning and 3 deep learning algorithms are implemented to assemble this model which can derive 4 particular religions (Hindu, Muslim, Buddhist, and Christian), Gender (Male and Female), 6 regions (Dhaka, Khulna, Rajshahi, Chittagong, Sylhet, Barisal), and religious conversions with the most raised exactness pace. We also analyzed the performance and compared among all algorithms by using different statistical methods.
The ultimate goal of this research paper is to introduce a robust machine learning algorithm call... more The ultimate goal of this research paper is to introduce a robust machine learning algorithm called Impact-Learning, which is being used widely to achieve more advanced results on many machine-learning related challenges. Impact learning is a supervised machine learning algorithm for resolving classification and linear or polynomial regression knowledge from examples. It also contributes to analyzing systems for competitive data. This algorithm is unique for being capable of learning from a competition, which is the impact of independent features. In other words, it is trained by the impacts of the features from the intrinsic rate of natural increase (RNI). The input to the Impact Learning is a training set of numerical data. In this work, we used six datasets related to regressions and classifications as the experiment of the Impact Learning, and the comparison indicates that at outperforms other standard machine learning regressions and classifications algorithms such as Random forest tree, SVM, Naive Bayes, Logistic regression and so forth.
Applied Mathematics and Sciences: An International Journal (MathSJ), 2019
The main purpose of this research is to find out the best method through iterative methods for so... more The main purpose of this research is to find out the best method through iterative methods for solving the nonlinear equation. In this study, the four iterative methods are examined and emphasized to solve the nonlinear equations. From this method explained, the rate of convergence is demonstrated among the 1st degree based iterative methods. After that, the graphical development is established here with the help of the four iterative methods and these results are tested with various functions. An example of the algebraic equation is taken to exhibit the comparison of the approximate error among the methods. Moreover, two examples of the algebraic and transcendental equation are applied to verify the best method, as well as the level of errors, are shown graphically.
Algorithms for Intelligent Systems, Springer Nature, 2020
Regression is a process to estimate the bond among variables. It is a statistical technique and i... more Regression is a process to estimate the bond among variables. It is a statistical technique and is used as prediction with the curve fitting in machine learning, data science, economics etc. Linear and Polynomial regression is widely used to fit a curve and forecasting result. In this exploration, we propose two new linear and non-linear regression techniques using the strategy of interpolation-extrapolation and bisection of numerical analysis. However, interpolation and extrapolation cannot be applied in regression because of over fitting curve. In our paper, we have developed a technique to reduce the curve fitting that will enable the interpolation's and extrapolation's scheme to use in regression. Another procedure is to find out an equation of curve fitting with an optimal way using the Bisection Method. We also demonstrate the graphical presentations and comparison through all the occurring iterations.
The Bangla Informative Question Answering System (BIQAS) is a significant Machine Learning (ML) t... more The Bangla Informative Question Answering System (BIQAS) is a significant Machine Learning (ML) technique that helps a user to trace relevant information by Bengali Natural Language Processing (BNLP). In this research paper, we have applied three mathematical and statistical procedures for BIQAS based on question answering data. These procedures are cosine similarity, Jaccard similarity, and Naive Bayes algorithm. The cosine similarity has interacted with dimension reduction technique SVD on user questions and questions answering data in order to reduce the space and time complexity. These procedures of this research are separated into two parts: pre-processing data and establishment of a relationship between user's questions and contained informative questions. We have got 93.22% accurate answer by using cosine similarity, 84.64% by Jaccard similarity and 91.31% by Naïve Bayes algorithm.
Type 2 Diabetes is a fast-growing, chronic metabolic disorder due to imbalanced insulin activity.... more Type 2 Diabetes is a fast-growing, chronic metabolic disorder due to imbalanced insulin activity. As lots of people are suffering from it, access to proper treatment is necessary to control the problem. Most patients are unaware of health complexity, symptoms and risk factors before diabetes. The motion of this research is a comparative study of seven machine learning classifiers and an artificial neural network method to prognosticate the detection and treatment of diabetes with a high accuracy, in order to identify and treat diabetes patients at an early age. Our training and test dataset is an accumulation of 9483 diabetes patients' information. The training dataset is large enough to negate overfitting and provide for highly accurate test performance. We use performance measures such as accuracy and precision to find out the best algorithm deep ANN which outperforms with 95.14% accuracy among all other tested machine learning classifiers. We hope our high performing model can be used by hospitals to predict diabetes and drive research into more accurate prediction models.
For the time being, Cricket is an indisputably one of the most interesting game in the world, esp... more For the time being, Cricket is an indisputably one of the most interesting game in the world, especially in the territory of South Asian. As human beings are prone to error, sometimes errors have happened to an umpire and about a constant time is taken by the third umpire for an exact decision of a review. The two different domains artificial intelligence and computer vision have become pop in cricket analysis and decision making. Using different types of computer vision's procedures in exploring several Cricket cases and automatically turning into decisions have become exoteric in recent days. In this research paper, we have propounded a classification method by the aids of Convolutional Neural Network (CNN) with Inception V3 in order to automatically unroll the decisions of third umpire and scoring system such as umpire signal detection. We have also proposed the deep CNN technique that aids to increase the performance of CNN.
Bengali Informative Chatbot (BIC) is an effective technique that helps a user to trace relevant i... more Bengali Informative Chatbot (BIC) is an effective technique that helps a user to trace relevant information by Natural Language Processing (NLP). In this research paper, we introduce an algorithmic Bengali Informative Chatbot (BIC) based on information that is significant mathematically and statistically. This paper is demonstrated by two algorithms for finding out the lemmatization of Bengali words such as Trie and Dictionary Based Search by Removing Affix (DBSRA) as well as compared with Edit Distance for the exact lemmatization. We present the Bengali Anaphora resolution system using the Hobbs' algorithm to get the correct expression of information. As the actions of chatbot replying algorithms, the TF-IDF and Cosine Similarity are developed to find out the accurate answer from the documents. In this study, we introduce a Bengali Language Toolkit (BLTK) and Bengali Language Expression (BRE) that make the easiest implication of our task. We have also developed Bengali root word's corpus, synonym word's corpus, stop word's corpus and gathered 672 articles as questions and answers form the popular Bengali newspapers 'The Daily Prothom Alo' is our inserted information. For testing this system, we have created 19334 questions from the introduced information and got 97.22% accurate answer by proposed BIC.
Applied Mathematics and Sciences: An International Journal, 2019
The main goal of this research is to give the complete conception about numerical integration inc... more The main goal of this research is to give the complete conception about numerical integration including Newton-Cotes formulas and aimed at comparing the rate of performance or the rate of accuracy of Trapezoidal, Simpson's 1/3, and Simpson's 3/8. To verify the accuracy, we compare each rules demonstrating the smallest error values among them. The software package MATLAB R2013a is applied to determine the best method, as well as the results, are compared. It includes graphical comparisons mentioning these methods graphically. After all, it is then emphasized that the among methods considered, Simpson's 1/3 is more effective and accurate subdivision is only even the when the condition of for solving a definite integral.
This Scientific Research paper is a procedure of an automated system "Doly: Bengali Chatbot" whic... more This Scientific Research paper is a procedure of an automated system "Doly: Bengali Chatbot" which gives a reply to a user query on behalf of a human for the education system in the Bengali language. This is an AI-based Chatbot, mainly based on machine learning algorithms and Bengali Natural Language Processing (BNLP). The machine gets embedded with this knowledge to identify the desired sentences and making a decision within itself, as a response to answer questions. There are many English Chatbot's which used in education, web query, banking sector & various sectors. In this research, we have propounded a complete data-driven retrieval based closed domain Chatbot which is easily colloquy in the Bengali language with the users. We've created the train function adapter to train the Doly by encoding (encoding="utf8") our corpus from bot data. An input adapter has been created to take input and for output, an output adapter has been created to generate automated responses to a user's input. We have also used a machine learning algorithm like search algorithm for finding an appropriate list of matching results from the corpus and use Naïve Bayesian algorithm to generate the right answer from data. The main aim of this Chatbot based system is to bridge the gap between the knowledge sources by providing instant replies to the questions and queries that have to ask in the Bengali language.
Applied Mathematics and Sciences: An International Journal (MathSJ), 2019
The main purpose of this research is to find out the best method through iterative methods for so... more The main purpose of this research is to find out the best method through iterative methods for solving the nonlinear equation. In this study, the four iterative methods are examined and emphasized to solve the nonlinear equations. From this method explained, the rate of convergence is demonstrated among the 1st degree based iterative methods. After that, the graphical development is established here with the help of the four iterative methods and these results are tested with various functions. An example of the algebraic equation is taken to exhibit the comparison of the approximate error among the methods. Moreover, two examples of the algebraic and transcendental equation are applied to verify the best method, as well as the level of errors, are shown graphically.
Applied Mathematics and Sciences: An International Journal(MathSJ), 2019
In Numerical analysis, interpolation is a manner of calculating the unknown values of a function ... more In Numerical analysis, interpolation is a manner of calculating the unknown values of a function for any conferred value of argument within the limit of the arguments. It provides basically a concept of estimating unknown data with the aid of relating acquainted data. The main goal of this research is to constitute a central difference interpolation method which is derived from the combination of Gauss's third formula, Gauss's Backward formula and Gauss's forward formula. We have also demonstrated the graphical presentations as well as comparison through all the existing interpolation formulas with our propound method of central difference interpolation. By the comparison and graphical presentation, the new method gives the best result with the lowest error from another existing interpolation formula.
Bangladesh Mathematical Society National Mathematics Conference, 2018
Fraud detection which is a discussible phenomenon to many bounds together with financial sectors,... more Fraud detection which is a discussible phenomenon to many bounds together with financial sectors, banking, insurance as well as diverse forms of industries. Nowadays fraud endeavors are being amplifying with rampant pace especially via the development of technology, so building fraud discovery more significant than ever before. In this paper, we analyzed the fraud operations by managing "Banking Fraud Detection" database by the combination of mathematical, statistical as well as machine learning ways and tried to spectacle a comparison among this ways. We narrated the elementary explorations by the combining methods such as mathematical, statistical as well as machine learning to equip the ways of insidious banking transactions.
Information Retrieval System is an effective process that helps a user to trace relevant informat... more Information Retrieval System is an effective process that helps a user to trace relevant information by Natural Language Processing (NLP). In this research paper, we have presented present an algorithmic Information Retrieval System(BIRS) based on information and the system is significant mathematically and statistically. This paper is demonstrated by two algorithms for finding out the lemmatization of Bengali words such as Trie and Dictionary Based Search by Removing Affix (DBSRA) as well as compared with Edit Distance for the exact lemmatization. We have presented the Bengali Anaphora resolution system using the Hobbs' algorithm to get the correct expression of information. As the actions of questions answering algorithms, the TF-IDF and Cosine Similarity are developed to find out the accurate answer from the documents. In this study, we have introduced a Bengali Language Toolkit (BLTK) and Bengali Language Expression (BRE) that make the easiest implication of our task. We have also developed Bengali root word's corpus, synonym word's corpus, stop word's corpus and gathered 672 articles from the popular Bengali newspapers 'The Daily Prothom Alo' which is our inserted information. For testing this system, we have created 19335 questions from the introduced information and got 97.22% accurate answer.
Algorithms for Intelligent Systems, Springer, 2020
In this research, we have examined type 2 diabetics treatment and medication detection using seve... more In this research, we have examined type 2 diabetics treatment and medication detection using seven classifier algorithms. We have created a decision tree-based procedure with genetic and clinical features such as Fasting, 2 h after the glucose load, BMI, Duration (years), Age, gender-specific, and blood pressure for the treatment of type 2 diabetic patients. Medical treatment prevents some complications, but does not usually restore normoglycemia or remove all the adverse consequences. The tool here is to give a correct report to justify the right medications for a patient. Imparting a fivefold cross-validation process, the operation of applying clinical features of 666 type 2 diabetic patients in 7 classifiers Logistic Regression, Linear Discriminant Analysis, k-nearest neighbors, Decision Tree, Naive Bayes, support vector machine, and Random forest classifier. In this paper, this system support to change lifestyle and right medications for treatment, which assists to reduce the probability of type 2 diabetes in persons.
The Bengali Informative Intelligence Bot (BIIB) is an effective Machine Learning (ML) t... more The Bengali Informative Intelligence Bot (BIIB) is an effective Machine Learning (ML) technique that helps a user to trace relevant information by Bengali Natural Language Processing (BNLP). In this book, we introduce two mathematical and statistical procedures for BIIB based on information of Noakhali Science and Technology University (NSTU) that is significant mathematically and statistically. In the preprocessing part, this book is demonstrated by two algorithms for finding out the lemmatization of Bengali words such as Trie and Dictionary Based Search by Removing Affix (DBSRA) as well as compared with Edit Distance for the exact lemmatization. We present the Bengali Anaphora Resolution system using the Hobbs‘ algorithm to get the correct expression of consequence questions. In order to reduce the time complexity of searching questions and reply from inserted information, we have used Non-negative Matrix Factorization (NMF) as the topic modeling technique, and the Singular Value Decomposition (SVD) as to reduce the dimension of questions. TF-IDF (Term Frequency-Inverse Document Frequency) has been used to convert character and/or string terms into numerical values, and to find their sentiments. For the action of chatbot in replying questions, we have applied the TF-IDF, cosine similarity and Jaccard similarity to find out the accurate answer from the documents. In this study, we introduce a Bengali Language Toolkit (BLTK) and Bengali Language Expression (BRE) that make the easiest implementation of our task. We have also developed Bengali root word‘s corpus, synonym word‘s corpus, stop word‘s corpus, and collected 74 topic related questions and answers from the information of NSTU which are actually our inserted informative questions. For verifying our proposed systems, we have created 2852 questions from the introduced topics. We have got 96.22% accurate answer by using cosine similarity and 84.64% by Jaccard similarity in our proposed BIIB.
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