People, Technologies, and Organizations Interactions in a Social Commerce Era

Maurya, Maruti; Gayakwad, Milind

doi:10.1007/978-3-030-24643-3_98

Cited by 8 publications

(9 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The phases like data collection, pre-processing, Rule based Model, Hybrid Model, Distribution of the weights, Validation is discussed in detail. Section 4 deals with results One day data, Cisco Joy Meter [41][42] is used to collect features in coordination with Cyber Threat [43] Intelligence, Lancaster University [44][45] [46] gathered during the pre-processing, Feature extraction, Comparative analysis with other algorithms. The ROC curve, histogram, Correlation, tabulated form helps in understanding the output of the experiment.…”

Section: International Journal On Recent and Innovation Trends In Com...mentioning

confidence: 99%

Intrusion Detection System using the Hybrid Model of Classification Algorithm and Rule-Based Algorithm

Kadam,

Garg,

Gayakwad

et al. 2023

IJRITCC

View full text Add to dashboard Cite

Intrusion detection system ID is necessary to secure the system from various intrusions. Analysis of the communication to categorize the data as useful or malicious data is crucial. The cyber security employed using intrusion detection systems should not also cause the extra time to perform the categorization. Nowadays machine learning techniques are used to make the identification of malicious data or an intrusion with the help of classification algorithms. The data set used for experimenting is KDD cup 99. The effect of individual classification algorithms can be improvised with the help of hybrid classification models. This model combines classification algorithms with rule-based algorithms. The blend of classification using machine and human intelligence adds an extra layer of security. An algorithm is validated using precision, recall, F-Measure, and Mean age Precision. The accuracy of the algorithm is 92.35 percent. The accuracy of the model is satisfactory even after the results are acquired by combining our rules inwritten by humans with conventional machine learning classification algorithms. Still, there is scope for improving and accurately classifying the attack precisely.

show abstract

Section: International Journal On Recent and Innovation Trends In Com...mentioning

confidence: 99%

Intrusion Detection System using the Hybrid Model of Classification Algorithm and Rule-Based Algorithm

Kadam,

Garg,

Gayakwad

et al. 2023

IJRITCC

View full text Add to dashboard Cite

show abstract

“…The researchers have tried to implement these approaches on different datasets. A direct comparison or comment on the accuracy is difficult to make, as these approaches are not on the common ground (Gayakwad, 2020). Still, the common observation is about the accuracy which is better in the combined approaches rather than relying on a single algorithm or a single approach (Purba et al, 2021).…”

Section: Elsinoëampelina Elsinoaceae Incertaesedismentioning

confidence: 99%

Credibility Evaluation of User-generated Content using Novel Multinomial Classification Technique

Gayakwad¹,

Patil²,

Joshi³

et al. 2022

IJRITCC

View full text Add to dashboard Cite

Awareness about the features of the internet, easy access to data using mobile, and affordable data facilities have caused a lot of traffic on the internet. Digitization came with a lot of opportunities and challenges as well. One of the important advantages of digitization is paperless transactions, and transparency in payment, while data privacy, fake news, and cyber-attacks are the evolving challenges. The extensive use of social media networks and e-commerce websites has caused a lot of user-generated information, misinformation, and disinformation on the Internet. The quality of information depends upon various stages (of information) like generation of information, medium of propagation, and consumption of information. Content being user-generated, information needs a quality assessment before consumption. The loss of information is also necessary to be examined by applying the machine learning approach as the volume of content is extremely huge. This research work focuses on novel multinomial classification (based on multinoulli distribution) techniques to determine the quality of the information in the given content. To evaluate the information content a single algorithm with some processing is not sufficient and various approaches are necessary to evaluate the quality of content. We propose a novel approach to calculate the bias, for which the Machine Learning model will be fitted appropriately to classify the content correctly. As an empirical study, rotten tomatoes’ movie review data set is used to apply the classification techniques. The accuracy of the system is evaluated using the ROC curve, confusion matrix, and MAP.

show abstract

“…We want to improve practitioners' form, alignment, and posture by using open pose estimation technology [9] [10]. By doing so, we want to improve yoga practices and help practitioners' overall physical and mental health [11] [12].…”

Section: Introductionmentioning

confidence: 99%

Web Service Implementation “AI Yoga Trainer Using Human Pose Estimation” for Web Discovery

Milind Gayakwad

2024

jes

View full text Add to dashboard Cite

This research work is to create a application as web service to make it available on web for web service discovery. The most significant yoga stance is well-known on a global scale and supports the health advantages advocated by the ancient sages. OpenPose estimates that computer vision technology can help yoga practitioners achieve the greatest form and alignment. The integration of the OpenCV, Python, and MediaPipe frameworks is the main emphasis of this research project in order to develop an OpenPose estimation system for yoga poses. A camera is used to capture the yoga practitioner's motions, and a deep learning model is used to predict the important body parts. The algorithm then looks at these essential aspects to determine if the practitioner is doing the pose correctly or whether any adjustments are needed. The device gives the practitioner immediate feedback, allowing them to modify their alignment and posture as necessary. The OpenPose estimate system can help with the practice of yoga by offering detailed visualizations of the essential body parts throughout each posture in addition to providing real-time feedback Practitioners may more clearly understand the right form and alignment and make the required adjustments by utilizing this visualization. Additionally, the OpenPose estimation system enables the tracking of development over time. Practitioners who want to practice alone at home or may not have access to an instructor can also benefit from it. This paper offers a MediaPipe, OpenCV, and Python-based OpenPose estimation system for yoga positions. For optimal form and alignment, the tool may offer real-time feedback and visual representations of key body parts throughout each position. It is useful tool for yoga teachers and students, enhancing yoga's safety and efficacy while supporting the practice.

show abstract

People, Technologies, and Organizations Interactions in a Social Commerce Era

Cited by 8 publications

References 8 publications

Intrusion Detection System using the Hybrid Model of Classification Algorithm and Rule-Based Algorithm

Intrusion Detection System using the Hybrid Model of Classification Algorithm and Rule-Based Algorithm

Credibility Evaluation of User-generated Content using Novel Multinomial Classification Technique

Web Service Implementation “AI Yoga Trainer Using Human Pose Estimation” for Web Discovery

Contact Info

Product

Resources

About