JANNAT PEYA - Academia.edu (original) (raw)

Papers by JANNAT PEYA

International Journal For Multidisciplinary Research

Cardiovascular diseases (CVD) are a type of illnesses in the cardiovascular system including coro... more Cardiovascular diseases (CVD) are a type of illnesses in the cardiovascular system including coronary, rheumatic heart and cerebrovascular. The leading causes of disease burden and mortality worldwide are CVDs. CVD can cause a wide range of consequences, which can lower standard of life and sometimes cause death. This emphasizes the requirement for the establishment of a technique that can ensure an exact and prompt prediction of the risk of CVD in patients. This study investigates effective CVD prediction system using several Machine Learning (ML) classification models. Rigorous data analysis through several preprocessing techniques as well as feature importance analysis has been performed through Spearman Correlation Analysis and XGboost feature importance technique. Finally, classification has been accomplished through Random Forest (RF), Support Vector Machine (SVM) and Logistic Regression (LR) using a standard benchmark dataset collected from IEEEDataPort. Highest accuracy of 9...

2022 12th International Conference on Electrical and Computer Engineering (ICECE)

2022 25th International Conference on Computer and Information Technology (ICCIT)

2021 IEEE International Conference on Biomedical Engineering, Computer and Information Technology for Health (BECITHCON)

Journal of Computer Science

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder relating to speech complications,... more Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder relating to speech complications, nonverbal and social communication, and repetitive behaviors. There is no remedy for ASD but early diagnosis, mediation, and supportive care can aid the development of language, conduct, and communication skills. As the cause of ASD is a neurodevelopmental disorder, its diagnosis based on brain function analyzing different brain signals, especially Electroencephalography (EEG), has drawn attention recently. Brain activity is recorded over time as an EEG signal from the scalp of a human and is used to investigate complicated neuropsychiatric disorders in the brain. In this study, the data from the EEG channels are translated into two-Dimensional (2D) form through correlation, and classification is performed using Convolutional Neural Networks (CNN), the well-known deep learning method for image analysis and classification. Two different CNN models are considered for classification purposes: Generic CNN and Residual Network (ResNet), a well-known deep CNN model. The proposed method with Resnet achieved 88% classification accuracy on a five-fold cross-validation mode, whereas it was 100 on 20% of test samples. Experimental evaluations using clinical EEG data revealed the efficacy of the proposed method outperforming other existing methods.

2020 IEEE Region 10 Symposium (TENSYMP)

Early diagnosis of autism or autism spectrum disorder (ASD) can help improving behavioral, langua... more Early diagnosis of autism or autism spectrum disorder (ASD) can help improving behavioral, language development and communication skill. As ASD is a neurodevelopmental disorder, brain signals are used to early diagnosis. Among different brain signals, electroencephalography (EEG) is the effective one. Electrical brain activity is measured through EEG signal from the scalp of human over a period of time and is used to analyze complex neuropsychiatric problems of brain. This study investigates an EEG based ASD detection using CNN, the well-known deep learning method for image analysis and classification. At first, the individual EEG channel data are transformed into 2D form using Pearson's Correlation Coefficient and then classification is carried out using the well-known CNN model residual neural network. Experiments performed on clinical EEG data show that the proposed approach achieved a classification accuracy of 100%.

2021 International Conference on Science & Contemporary Technologies (ICSCT)

Thyroid disease is a condition in which the thyroid gland does not produce enough hormones. The s... more Thyroid disease is a condition in which the thyroid gland does not produce enough hormones. The symptoms of thyroid disease vary depending on the type (hypothyroidism, hyperthyroidism, or other). Generally sleeping trouble, anxiety, losing weight, fatigue, gaining weight, forgetfulness, and many other complexities are caused by hyper and hypothyroidism. So, diagnosing thyroid diseases is a vital issue as the diseases can be cured through proper and timely diagnosis. Recently machine learning techniques are used for predicting thyroid diseases. In this study, we have proposed a thyroid diseases prediction model through three machine learning classification algorithms namely K-Nearest Neighbor (KNN), Naive Bayes, and Decision Trees. Experiments are performed on thyroid data of the UCI machine learning repository. The dataset has three classes named normal, hypothyroid, and hyperthyroid. Through 10-fold cross-validation, the performances of the three algorithms are tested on several parameters such as Accuracy, Precision, F-Measure, and Recall. The decision tree was the most accurate, with a 99.7% accuracy rate over Naïve Bayes and KNN in the three-class thyroid diseases classification problem.

Algorithms for Intelligent Systems, 2021

Alcoholism is a term for any alcohol consumption leading to mental or physical health problems [1... more Alcoholism is a term for any alcohol consumption leading to mental or physical health problems [1]. Long-term alcohol consumption can cause a wide range of psychological issues. Excessive consumption of alcohol causes damage to the activity of the brain, and over time, mental health can become severely affected [1, 2]. Nowadays, alcohol misuse is related to increased risk of crime, including child neglect, domestic violence, burglary, fraud, road accidents, and assault [3]. Alcoholism is the most common psychological condition in the general population and the lifetime prevalence of alcohol dependence is 8-14% [4, 5]. Seeing alcoholism as a major burden for any modern society, physiological and neurological information relating to alcoholism is needed for the care of alcoholic patients. Alcoholism detection is an important issue nowadays. There exist a number of approaches to detect alcoholism. Among those methods, screening is a wellestablished method and recommended for over the age of 18 for the diagnosis of alcoholism [6]. Blood alcohol content (BAC) is another common test for actual alcohol use [7]. Screening and BAC tests do not provide any discriminating factors

Capacitated vehicle routing problem (CVRP) is a real life constraint satisfaction problem in whic... more Capacitated vehicle routing problem (CVRP) is a real life constraint satisfaction problem in which customers are optimally assigned to individual vehicles (considering their capacity) to keep total travel distance of the vehicles as minimum as possible while serving customers. Various methods are used to solve CVRP in last few decades, among them the most popular way is splitting the task into two different phases: assigning customers under different vehicles and then finding optimal route of each vehicle. Sweep clustering algorithm is well studied for clustering nodes. On the other hand, route optimization is simply a traveling salesman problem (TSP) and a number of TSP optimization methods are applied for this purpose. This study investigates a variant of Sweep algorithm for clustering nodes and different Swarm Intelligence (SI) based methods for route generation to get optimal CVRP solution. In conventional Sweep algorithm, cluster formation starts from smallest angle and consequ...

This thesis is submitted to the Department of Computer Science and Engineering, Khulna University... more This thesis is submitted to the Department of Computer Science and Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, May, 2016.

2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2020

Students are the future leaders and assets of a country. But in this era students are losing thei... more Students are the future leaders and assets of a country. But in this era students are losing their education level for drug addiction. So, a nation must be concerned about these students and this social problem. And we need to solve this problem as soon as possible. In this study, we have tried to find out the most significant causes of drug addiction for a student. We have also tried to find out the correlation among the factors. Those may help students and guardians to know about the main causes of drug addiction which are primary steps of drug addiction. For performing this study, we have collected 130 instances data from various universities from Bangladesh where each has 13 unique attributes. For processing dataset to select the significant attributes, we have used Machine learning techniques. And also for finding out the most correlated features of dataset we have used Association Rule Mining techniques. Apriori algorithm is used for implementing Rule Mining and we found 8 rules.

2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2021

Diabetes mellitus is a perdurable hyperglycemic disease. Various complications can be caused by t... more Diabetes mellitus is a perdurable hyperglycemic disease. Various complications can be caused by this disease. In line with the growing morbidness in the last few years, 642 million people can be infected with diabetes within 2040 which is one among 10 individuals. So undoubtedly this malady needs more attention. Nowadays the usage of machine learning is increasing. So, in many medical perspectives, this technique has been utilized. We have chosen methodologies that give the best performances for independent testing to confirm the universal applicability of the techniques. We have focused on early detecting this disease. We have collected data from Khulna Diabetes Center at Khulna where the instances is 289 and 13 features. In our study, we use the Logistic Regression model with 88%, XGboost 86.36% and Random Forest with 86.36% accuracy. We found that the random forest model performs the best output for diabetics detection.

International Journal of Advanced Computer Science and Applications, 2019

The Capacitated Vehicle Routing Problem (CVRP) is an optimization problem owing to find minimal t... more The Capacitated Vehicle Routing Problem (CVRP) is an optimization problem owing to find minimal travel distances to serve customers with homogeneous fleet of vehicles. Clustering customers and then assign individual vehicles is a widely-studied way, called cluster first and route second (CFRS) method, for solving CVRP. Cluster formation is important between two phases of CFRS for better CVRP solution. Sweep (SW) clustering is the pioneer one in CFRS method which solely depends on customers' polar angle: sort the customers according to polar angle; and a cluster starts with customer having smallest polar angle and completes it considering others according to polar angle. On the other hand, Sweep Nearest (SN) algorithm, an extension of Sweep, also considers smallest polar angle customer to initialize a cluster but inserts other customer(s) based on the nearest neighbor approach. This study investigates a different way of clustering based on nearest neighbor approach. The proposed Distance based Sweep Nearest (DSN) method starts clustering from the farthest customer point and continues for a cluster based on nearest neighbor concept. The proposed method does not rely on polar angle of the customers like SW and SN. To identify the effectiveness of the proposed approach, SW, SN and DSN have been implemented in this study for solving benchmark CVRPs. For route optimization of individual vehicles, Genetic Algorithm, Ant Colony Optimization and Particle Swarm Optimization are considered for clusters formation with SW, SN and DSN. The experimental results identified that proposed DSN outperformed SN and SW in most of the cases and DSN with PSO was the best suited method for CVRP.

Oriental journal of computer science and technology, 2018

Capacitated Vehicle Routing Problem (CVRP) is anoptimization task where customers are assigned to... more Capacitated Vehicle Routing Problem (CVRP) is anoptimization task where customers are assigned to vehicles aiming that combined travel distances of all the vehicles as minimum as possible while serving customers. A popular way among various methods of CVRP is solving it in two phases: grouping or clustering customers into feasible routes of individual vehicles and then finding their optimal routes. Sweep is well studied clustering algorithm for grouping customers and different traveling salesman problem (TSP) solving methods are commonly used to generate optimal routes of individual vehicles. This study investigates effective CVRP solving method based on recently developed adaptive Sweep and prominent Swarm Intelligence (SI) based TSP optimization methods. The adaptive Sweep cluster is a heuristic based adaptive method to select appropriate cluster formation starting angle of Sweep. Three prominent SI based TSP optimization methods are investigated which are Ant Colony Optimization,...

International Journal of Advanced Computer Science and Applications, 2017

Vehicle Routing Problem (VRP) has become an integral part in logistic operations which determines... more Vehicle Routing Problem (VRP) has become an integral part in logistic operations which determines optimal routes for several vehicles to serve customers. The basic version of VRP is Capacitated VRP (CVRP) which considers equal capacities for all vehicles. The objective of CVRP is to minimize the total traveling distance of all vehicles to serve all the customers. Various methods are used to solve CVRP, among them the most popular way is splitting the task into two different phases: assigning customers under different vehicles and then finding optimal route of each vehicle. Sweep clustering algorithm is well studied for clustering nodes. On the other hand, route optimization is simply a traveling salesman problem (TSP) and a number of TSP optimization methods are applied for this purpose. In Sweep, cluster formation staring angle is identified as an element of CVRP performance. In this study, a heuristic approach is developed to identify appropriate starting angle in Sweep clustering. The proposed heuristic approach considers angle difference of consecutive nodes and distance between the nodes as well as distances from the depot. On the other hand, velocity tentative particle swarm optimization (VTPSO), the most recent TSP method, is considered for route optimization. Finally, proposed adaptive Sweep (i.e., Sweep with proposed heuristic) plus VTPSO is tested on a large number of benchmark CVRP problems and is revealed as an effective CVRP solving method while outcomes compared with other prominent methods.

Algorithms Research, 2012

The Mult i-Depot Veh icle Routing Problem (MDVRP), an extension of classical VRP, is a NP-hard pr... more The Mult i-Depot Veh icle Routing Problem (MDVRP), an extension of classical VRP, is a NP-hard problem for simu ltaneously determining the routes for several vehicles fro m mu ltip le depots to a set of customers with demand and then return to the same depot. Main goal of this thesis is to solve MDVRPSD in three phases. Firstly we've used nearest neighbour classification method for grouping the customers, then Su m of Subset method have been used for routing. Finally the routes are optimized using greedy method. The routes obtained using these methods are better for the vehicles considering demands of the customers. As an input we consider here some customers position, the depots position. Also the demand is in itialized randomly. Here we solve the problem for 4 depots to 10 depots. The input customer ranges fro m 20 to 50. Then by using the three-phases the problem is solved for the input combinations. Actually the main target to solve this problem is to reduce the number of vehicles needed to serve the customers. We have to serve the customers of a definite route by a vehicle. So if the routes are min imized then number of needed vehicles is also min imized. The t ime is also an impo rtant issue. So the time is also measured for solving the whole problem with three-phases. So at the last part of the paper the performance is measured according to time for solving the problem and the number of vehicle needed for each of the problem.

2015 2nd International Conference on Electrical Information and Communication Technologies (EICT), 2015

Capacitated Vehicle Routing Problem (CVRP) is a real life constrain satisfaction problem in which... more Capacitated Vehicle Routing Problem (CVRP) is a real life constrain satisfaction problem in which customers are optimally assign to individual vehicles (considering their capacity) to keep total travel distance of the vehicles as minimum as possible while serving customers. Various methods are investigated to solve CVRP in last few decades, the most popular way of solving CVRP is splitting the task into two different phases: firstly, assigning customers under different vehicles and secondly, finding optimal route of each vehicle. Sweep clustering algorithm is well studied for clustering nodes. On the other hand, route optimization is simply a traveling salesman problem (TSP) and a number of TSP optimization methods are investigated for this purpose. This study investigates a variant of Sweep algorithm for clustering nodes and different SI based methods for route generation to get optimal CVRP solution. In conventional Sweep algorithm, cluster formation starts from 0° and consequently advance toward 360° to consider all the nodes. In this study, Sweep cluster are considered from different starting angle. On the other hand, two well-known Swarm Intelligence (SI) methods (i.e., Ant Colony Optimization and Particle Swarm Optimization (PSO)) and two recent SI based algorithms (i.e., Producer-Scrounger Method and Velocity Tentative PSO) are considered for route optimization. We have compared the performance of these methods to solve CVRP. The experimental results on a large number of benchmark CVRP reveal that different starting angle has positive effect on Sweep clustering and finally, VTPSO is able to produce better solution than other methods.

Journal of engineering science, Jan 15, 2023

Autism Spectrum Disorder (ASD), simply autism, is a complex neurodevelopmental disorder that lead... more Autism Spectrum Disorder (ASD), simply autism, is a complex neurodevelopmental disorder that leads to serious social, communication, and behavioral challenges. The impact of ASD on the family, general well-being, society, and economy is becoming increasingly important due to its high prevalence and the extensive range of clinical treatments required for affected children. Early ASD detection is important because it could help improve access to intervention measures and may help improve developmental outcomes. Autism exposes a critical issue for developing countries, especially in South Asian countries. In the South Asia region, a few institutes are available in the capital or a few big metropolitan cities for diagnosing ASD. Generally, ASD is diagnosed through some conventional methods (e.g., screening). As a neurodevelopmental condition, ASD can be detected through brain signals. On account of easy operation and to maintain low-risk factors, only noninvasive neuroimaging methods, such as electroencephalography (EEG) are considered to measure a child's neural behaviors for classifying ASD. Machine learning methods are used with EEG signals for classifying ASD subjects in different studies than conventional methods. The main concern of this study is to provide some guidelines for machine learning-based automatic ASD detection through EEG signals which might be a prospectus for South Asian countries. Through the advanced system, people from all areas of the country will get proper ASD diagnosis and treatment facilities. Therefore, it is a timely approach of employing brain signals (especially EEG signals) and machine learning-based effective techniques for ASD detection in South Asian countries.