Swati Aggarwal

Swati Aggarwal
Molde University College · Department of Logistics

Bachelor of Engineering

About

74
Publications
16,575
Reads
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1,478
Citations

Publications

Publications (74)
Article
The gaze-independent brain–computer interface (BCI) device is used to re-establish interaction for individuals who have abnormal eye movement. It may be possible to control the BCI by shifting your attention spatially. However, spatial attention is rarely employed to increase the effectiveness of target detection and is typically used to provide a...
Article
Common misbehavior among children that prevents them from paying attention to tasks and interacting with their surroundings appropriately is attention-deficit/hyperactivity disorder (ADHD). Studies of children's behavior presently face a significant problem in the early and timely diagnosis of this disease. To diagnose this disease, doctors often u...
Article
Full-text available
The identification and classification of human brain activities are essential for many medical and Brain-Computer Interface (BCI) systems, saving human lives and time. Electroencephalogram (EEG) proves to be an efficient, non-invasive, and cost-effective means of recording electrical signals in the human brain. With the advancement in Artificial In...
Chapter
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental illness that is complicated, universal, and heterogeneous. Children with ADHD have a hard time staying focused and managing their activities. For children with ADHD, which is today a major issue, early screening and diagnosis are essential. The purpose of this research is to cr...
Chapter
Malaria is a potentially fatal disease caused by infected Anopheles mosquitoes. Traditional diagnosis of malaria involves examination of thin blood smear slides under a microscope by trained microscopists to detect infected blood cells. This process is expensive, and results depend both on the quality of smear and on the expertise of the microscopi...
Article
Hybrid brain computer interfaces (hBCIs) have emerged as a possible path to integrated brain-computer interaction in current history. hBCI, is a device formed by the amalgamation of control signal and bio-signal combination of control signal with one or more bio-signals that enhances system performance and usability. Assistive technology, spelling,...
Article
A brain computer interface (BCI) framework uses computer algorithms to detect mental activity patterns and manipulate external devices. Because of its simplicity and non-invasiveness, one of the most commonly used imaging technologies is electroencephalography (EEG). The evaluative method used in assessing the output of an EEG-based BCI system is c...
Chapter
In the domain of time series, cryptocurrency data is one of the most complex data available with its inherent volatility and non-linearity, thus making the task of analysis and prediction exceptionally challenging. The econometric models such as ARIMA and ARMA fail to capture the non-linearity of data putting forth the need to adopt other models fo...
Article
Rapid progress in expansion of the internet services have provided an alternative way for learning other than the traditional classroom learning. Due to the availability of multiple learning options, evaluating each option and judging the best use case plays a vital role. One of the most important characteristics that a human brain utilizes during...
Preprint
In the era of MOOCs, online exams are taken by millions of candidates, where scoring short answers is an integral part. It becomes intractable to evaluate them by human graders. Thus, a generic automated system capable of grading these responses should be designed and deployed. In this paper, we present a fast, scalable, and accurate approach towar...
Article
Full-text available
Hyperparameters are pivotal for machine learning models. The success of efficient calibration, often surpasses the results obtained by devising new approaches. Traditionally, human intervention is required to tune the models, however, this obtuse outlook restricts the proficiency and competence. Automating this crucial characteristic of learning su...
Article
Full-text available
Today, media outlets are known to report news in a biased way, potentially affecting the beliefs of news consumers and altering their behaviors. Therefore, tracking bias in everyday news and building a platform where people can receive neutral and unequivocal news information is important. This research investigates media outlets for subjectivity v...
Article
Full-text available
Closed Loop medical devices such as Closed Loop Deep Brain Stimulation (CL-DBS) and Brain Computer Interface (BCI) are some of the emerging neurotechnologies. New generations of implantable brain–computer interfaces have recently gained success in human clinical trials. These implants detect specific neuronal patterns and provide the subject with i...
Article
Multiplayer Online Battle Arena (MOBA) has become one of the most popular genre of online video games played by gamers worldwide. Previous studies have exhibited that excessive engagement in games can lead to Internet Gaming Disorder (IGD). Internet Gaming Disorder has been associated with psychological disorders like impulsivity, anxiety and Atten...
Article
Full-text available
Motor Imagery Brain Computer Interface (MI-BCI) provides a non-muscular channel for communication to those who are suffering from neuronal disorders. The designing of an accurate and reliable MI-BCI system requires the extraction of informative and discriminative features. Common Spatial Pattern (CSP) has been potent and is widely used in BCI for e...
Article
Full-text available
Lipreading is the process of understanding and interpreting speech by observing a speaker’s lip movements. In the past, most of the work in lipreading has been limited to classifying silent videos to a fixed number of text classes. However, this limits the applications of the lipreading since human language cannot be bound to a fixed set of words o...
Article
Full-text available
In the era of MOOCs, online exams are taken by millions of candidates, where scoring short answers is an integral part. It becomes intractable to evaluate them by human graders. Thus, a generic automated system capable of grading these responses should be designed and deployed. In this paper, we present a fast, scalable, and accurate approach towar...
Chapter
Real-world data generally deals with inconsistency. The uncertain k-means (UK-means) clustering algorithm, a modification of k-means, handles uncertain objects whose positions are represented by probability density functions (pdfs). Various techniques have been developed to enhance the performance of UK-means clustering algorithm but they are all c...
Chapter
The use of EEG signals for measuring cognitive development is an upcoming field of research for a strong cognitive analysis to revolutionize the field of biomedical informatics and neuroscience. This paper highlights the importance of EEG signals in cognitive development experimentation and the challenges faced in conducting an EEG experiment and i...
Chapter
Machine learning is being used in every field. In almost all technical and financial domains, machine learning is being used enormously from predicting new outcomes to classifying a given data into multiple sets. In this research work it has been tried to build and expand upon previously built binary classifiers to develop a unique classifier for s...
Chapter
Incomplete data has emerged as a prominent problem in the fields of machine learning, big data and various other academic studies. Due to the surge in deep learning techniques for problem-solving, in this paper, authors have proposed a deep learning-metaheuristic approach to combat the problem of imputing missing data. The proposed approach (DL-GSA...
Chapter
High dimensionality problems have become prevalent in present day machine learning applications. The voluminous datasets acquired from sources like cameras, spectroscopes, and other sensors need to be analysed and modelled in a way that uses the available computational resources most efficiently. The paper proposes a genetic algorithm optimised neu...
Research
Full-text available
Neutrosophic Sets and Systems (NSS) is an academic journal that has been created for publications of advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics etc. and their applications in any field.
Chapter
In the medical field diagnosis of a disease at an early stage is very important. Nowadays soft computing techniques such as fuzzy logic, artificial neural network and Neuro-fuzzy networks are widely used for the diagnosis of various diseases at different levels. In this chapter, a hybrid neural network is designed to classify the heart disease data...
Chapter
In the medical field diagnosis of a disease at an early stage is very important. Nowadays soft computingtechniques such as fuzzy logic, artificial neural network and Neuro- fuzzy networks are widely used forthe diagnosis of various diseases at different levels. In this chapter, a hybrid neural network is designedto classify the heart disease data s...
Article
Trust is an important term in the context of E-Commerce. It lies at the top in the present trend of E-Commerce. Trust lists the diverse prospects of trustworthiness that exist between the merchant and customer, inducing a better customer liking and Business-to-Customer (B2C) E-Commerce. Considering the imprecise nature of E-Commerce trust, various...
Conference Paper
Data imputation is the process of filling in the missing value to generate complete records. Complete databases can be analyzed more accurately in comparison to incomplete databases. This paper implements a 2-stage hybrid model for filling in the missing values. Also the effect of the proposed model over simple and complex dataset with varying perc...
Article
This paper employs a new soft computing based methodology for identifying and analyzing the relationships among the causes and implications of the two challenging problems in India: unbalanced sex ratio and poverty.
Conference Paper
Fuzzy classification is very necessary because it has the ability to use interpretable rules. It has got control over the limitations of crisp rule based classification. This paper mainly deals with classification using fuzzy probability and Neutrosophic probability. Classification based on Neutrosophic probability employs Neutrosophic logic and Ne...
Article
These days corruption can be seen in every section of society. If certain changes are not made, corruption will continue to be an issue in the society. This paper surveys and discusses various issues related to the causes of corruption using soft computing technique known as FCM (Fuzzy Cognitive Mapping) and E-FCM (Extended Fuzzy Cognitive Maps). A...
Conference Paper
Mobile robots have the capability to navigate in the environment. We need some approaches for their collision-free and stable navigation. Authors have given their own algorithm and have implemented in C- language to move a robot from initial to final position. They have also shown the comparison in path length required by robot with the model propo...
Conference Paper
Nowadays soft computing techniques such as fuzzy logic, artificial neural network and neuro- fuzzy networks are widely used for the diagnosis of various diseases at different levels. These diagnosing systems help in early detection of diseases and assist the patient to get proper medication in time. In this paper, the artificial neural network such...
Conference Paper
Trust lies at the acme in this competitive trend of E-Commerce. Trust enumerates the different prospects of trustworthiness that are sculpted between the vendor and customer, inducing a better customer satisfaction and Business-to-Customer (B2C) E-Commerce. Considering the vagueness and ambiguity of E-Commerce trust different trust models coupled w...
Conference Paper
Database store datasets that are not always complete. They contain missing fields inside some records, that may occur due to human or system error involved in a data collection task. Data imputation is the process of filling in the missing value to generate complete records. Complete databases can be analyzed more accurately in comparison to incomp...
Article
Ontology helps us to think about the real world with its semantic constraints. But there exist different uncertainties and ambiguities that cannot be considered using traditional ontologies. This paper mainly deals with classification using fuzzy ontology and Neutrosophic ontology. Classification based on Neutrosophic ontology employs Neutrosophic...
Article
Prof. L. A. Zadeh recognized that to simulate soft knowledge of human reasoning it is essential to use some formal approach to knowledge processing. So he pioneered by taking first step by proposing a novel logic, fuzzy logic in 1965, by releasing constraints imposed on existing formalisms to accommodate important properties of natural inference. T...
Conference Paper
Full-text available
Fuzzy logic given by Zadeh is a dominant and one of the extensively researched components in the domain of soft-computing. It deals with the representation of real-world data/information and enables reasoning that is approximate in nature. Lately, the focus has shifted to the reliability of the information, that is an important aspect for any sound...
Conference Paper
Full-text available
In areas ranging from medical analysis to stock market prediction; weather prediction to game playing; almost every domain that we can think of, decision making is one component that is common in all. Decision making theory is an active research area that finds applications in numerous fields like computer science, management science, finance and o...
Article
Fuzzy classification has become of great interest because of its ability to utilize simple linguistically interpretable rules and has overcome the limitations of symbolic or crisp rule based classifiers. This paper introduces an extension to fuzzy classifier: a neutrosophic classifier, which would utilize neutrosophic logic for its working. Neutros...
Article
Fuzzy classification has become of great interest because of its ability to utilize simple linguistically interpretable rules and has overcome the limitations of symbolic or crisp rule based classifiers. This paper introduces an extension to fuzzy classifier: a neutrosophic classifier, which would utilize neutrosophic logic for its working. Neutros...
Book
Real world problems have been effectively modeled using fuzzy logic that gives suitable representation of real-world data/information and enables reasoning that is approximate in nature. It is quite uncommon that the inputs captured by the fuzzy models are 100% complete and determinate. Though, humans can take intelligent decisions in such situatio...
Article
Full-text available
Soft computing is an enriching domain that helps to encode uncertainty and imprecision that exists in real world. Integration of soft computing techniques in the systems lends added advantage to the existing systems to allow solutions to otherwise unsolvable problems. Fuzzy architecture has been extensively researched and applied in medical domain....
Article
The paper introduces various methods for classification like fuzzy logic, and its combination with artificial neural networks. Datasets from UCI Repository have been used for the implementation of classification models using Matlab 7.0 for Fuzzy Inference System(FIS) and Anfis and Matlab R2007b for Anfis with variable labels and different membershi...
Conference Paper
Full-text available
Prof. L. A. Zadeh recognized that to simulate soft knowledge of human reasoning it is essential to use some formal approach to knowledge processing. So he pioneered by taking first step by proposing a novel logic, fuzzy logic in 1965, by releasing constraints imposed on existing formalisms to accommodate important properties of natural inference [1...
Conference Paper
Full-text available
Quite recently, Neutrosophic Logic has been proposed by Florentine Smarandache which is based on non-standard analysis that was given by Abraham Robinson in 1960s. Neutrosophic Logic was developed to represent mathematical model of uncertainty, vagueness, ambiguity, imprecision, incompleteness, inconsistency, redundancy and contradiction in data [4...
Article
Quite recently, Neutrosophic Logic has been proposed by Florentine Smarandache which is based on nonstandard analysis that was given by Abraham Robinson in 1960s. Neutrosophic Logic was developed to represent mathematical model of uncertainty, vagueness, ambiguity, imprecision, incompleteness, inconsistency, redundancy and contradiction in data.
Article
Quite recently, Neutrosophic Logic has been proposed by Florentine Smarandache which is based on nonstandard analysis that was given by Abraham Robinson in 1960s. Neutrosophic Logic was developed to represent mathematical model of uncertainty, vagueness, ambiguity, imprecision, incompleteness, inconsistency, redundancy and contradiction in data.

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