Bhumeshwar Patle, Shyh-Leh Chen, Brijesh Patel, Sunil Kumar Kashyap and Sudarshan Sanap
With the increasing demand for surveillance and smart transportation, drone technology has become the center of attraction for robotics researchers. This study aims to introduce a…
Abstract
Purpose
With the increasing demand for surveillance and smart transportation, drone technology has become the center of attraction for robotics researchers. This study aims to introduce a new path planning approach to drone navigation based on topology in an uncertain environment. The main objective of this study is to use the Ricci flow evolution equation of metric and curvature tensor over angular Riemannian metric, and manifold for achieving navigational goals such as path length optimization at the minimum required time, collision-free obstacle avoidance in static and dynamic environments and reaching to the static and dynamic goals. The proposed navigational controller performs linearly and nonlinearly both with reduced error-based objective function by Riemannian metric and scalar curvature, respectively.
Design/methodology/approach
Topology and manifolds application-based methodology establishes the resultant drone. The trajectory planning and its optimization are controlled by the system of evolution equation over Ricci flow entropy. The navigation follows the Riemannian metric-based optimal path with an angular trajectory in the range from 0° to 360°. The obstacle avoidance in static and dynamic environments is controlled by the metric tensor and curvature tensor, respectively. The in-house drone is developed and coded using C++. For comparison of the real-time results and simulation results in static and dynamic environments, the simulation study has been conducted using MATLAB software. The proposed controller follows the topological programming constituted with manifold-based objective function and Riemannian metric, and scalar curvature-based constraints for linear and nonlinear navigation, respectively.
Findings
This proposed study demonstrates the possibility to develop the new topology-based efficient path planning approach for navigation of drone and provides a unique way to develop an innovative system having characteristics of static and dynamic obstacle avoidance and moving goal chasing in an uncertain environment. From the results obtained in the simulation and real-time environments, satisfactory agreements have been seen in terms of navigational parameters with the minimum error that justifies the significant working of the proposed controller. Additionally, the comparison of the proposed navigational controller with the other artificial intelligent controllers reveals performance improvement.
Originality/value
In this study, a new topological controller has been proposed for drone navigation. The topological drone navigation comprises the effective speed control and collision-free decisions corresponding to the Ricci flow equation and Ricci curvature over the Riemannian metric, respectively.
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Brijesh H. Patel and Pulak Mohan Pandey
Natural elements in the biological organs of plants and animals consist of repetitive geometries, which often form the basis for the new lattice structure design with improved…
Abstract
Purpose
Natural elements in the biological organs of plants and animals consist of repetitive geometries, which often form the basis for the new lattice structure design with improved performance. The purpose of this study is to investigate the energy absorption capabilities and deformation behavior of lattice structures inspired by Helleborus petticoat flower and fish scale patterns.
Design/methodology/approach
The authors designed arc-shaped strut lattice structures by incorporating the geometrical features of Helleborus petticoat flower and fish scale pattern into lattice strut configuration. The structures were printed from thermoplastic polyurethane (TPU) material using fused deposition modeling process and tested under uniaxial compression. The energy absorption parameters, such as specific energy absorption (SEA), mean plateau stress, onset densification strain and absorption efficiency were determined, and deformation mechanism under static compression was analyzed. The SEA of proposed structures was compared with other TPU structures in the reported literature.
Findings
The results show that the lattice strut configuration affects the mechanical properties, energy absorption characteristics and deformation behavior of the proposed bio-inspired structures. The SEA was found to be in the range of 0.34–0.97 kJ / kg. Overall, the novel flower-inspired structure displayed significantly higher SEA (+185%), compared to fish scale-derived structure.
Originality/value
To the best of the authors’ knowledge, the authors have designed the proposed lattice structures for the first time. The energy absorption characteristics and deformation behavior of proposed lattice structures had never been reported previously.
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Kinjal Bhargavkumar Mistree, Devendra Thakor and Brijesh Bhatt
According to the Indian Sign Language Research and Training Centre (ISLRTC), India has approximately 300 certified human interpreters to help people with hearing loss. This paper…
Abstract
Purpose
According to the Indian Sign Language Research and Training Centre (ISLRTC), India has approximately 300 certified human interpreters to help people with hearing loss. This paper aims to address the issue of Indian Sign Language (ISL) sentence recognition and translation into semantically equivalent English text in a signer-independent mode.
Design/methodology/approach
This study presents an approach that translates ISL sentences into English text using the MobileNetV2 model and Neural Machine Translation (NMT). The authors have created an ISL corpus from the Brown corpus using ISL grammar rules to perform machine translation. The authors’ approach converts ISL videos of the newly created dataset into ISL gloss sequences using the MobileNetV2 model and the recognized ISL gloss sequence is then fed to a machine translation module that generates an English sentence for each ISL sentence.
Findings
As per the experimental results, pretrained MobileNetV2 model was proven the best-suited model for the recognition of ISL sentences and NMT provided better results than Statistical Machine Translation (SMT) to convert ISL text into English text. The automatic and human evaluation of the proposed approach yielded accuracies of 83.3 and 86.1%, respectively.
Research limitations/implications
It can be seen that the neural machine translation systems produced translations with repetitions of other translated words, strange translations when the total number of words per sentence is increased and one or more unexpected terms that had no relation to the source text on occasion. The most common type of error is the mistranslation of places, numbers and dates. Although this has little effect on the overall structure of the translated sentence, it indicates that the embedding learned for these few words could be improved.
Originality/value
Sign language recognition and translation is a crucial step toward improving communication between the deaf and the rest of society. Because of the shortage of human interpreters, an alternative approach is desired to help people achieve smooth communication with the Deaf. To motivate research in this field, the authors generated an ISL corpus of 13,720 sentences and a video dataset of 47,880 ISL videos. As there is no public dataset available for ISl videos incorporating signs released by ISLRTC, the authors created a new video dataset and ISL corpus.
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Brijesh Sivathanu, Rajasshrie Pillai, Mahek Mahtta and Angappa Gunasekaran
This study aims to examine the tourists' visit intention by watching deepfake destination videos, using Information Manipulation and Media Richness Theory.
Abstract
Purpose
This study aims to examine the tourists' visit intention by watching deepfake destination videos, using Information Manipulation and Media Richness Theory.
Design/methodology/approach
This study conducted a primary survey utilizing a structured questionnaire. In total, 1,360 tourists were surveyed, and quantitative data analysis was done using PLS-SEM.
Findings
The results indicate that the factors that affect the tourists' visit intention after watching deepfake videos include information manipulation tactics, trust and media richness. This study also found that perceived deception and cognitive load do not influence the tourists' visit intention.
Originality/value
The originality/salience of this study lies in the fact that this is possibly among the first to combine the Media Richness Theory and Information Manipulation for understanding tourists' visit intention and post-viewing deepfake destination videos.
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Brijesh Sivathanu and Rajasshrie Pillai
This study aims to investigate the effect of deepfake video advertisements on hotel booking intention by applying the media richness theory (MRT) and information manipulation…
Abstract
Purpose
This study aims to investigate the effect of deepfake video advertisements on hotel booking intention by applying the media richness theory (MRT) and information manipulation theory (IMT).
Design/methodology/approach
A quantitative survey was conducted using a structured questionnaire to understand the effect of deepfake hotel video advertisements on booking intention. A large cross-section of 1,240 tourists was surveyed and data were analyzed with partial least squares structural equation modeling (PLS-SEM).
Findings
The outcome of this research provides the factors affecting the booking intention due to deepfake hotel video advertisements. These factors are media richness (MR), information manipulation (IM) tactics, perceived value (PV) and perceived trust (PT). Cognitive load and perceived deception (DC) negatively influence the hotel booking intention.
Practical implications
The distinctive model that emerged is insightful for senior executives and managers in the hospitality sector to understand the influence of deepfake video advertisements. This research provides the factors of hotel booking intention due to deepfake video advertisements, which are helpful for designers, developers, marketing managers and other stakeholders in the hotel industry.
Originality/value
MR and IMT are integrated with variables such as PT and PV to explore the tourists' hotel booking intention after watching deepfake video advertisements. It is the first step toward deepfake video advertisements and hotel booking intentions for tourists. It provides an empirically tested and validated robust theoretical model to understand the effect of deepfake video advertisements on hotel booking intention.
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R. L. Bhardwaj and Urvashi Nandal
The purpose of this paper is to summarize the scientific information of various qualities of bael fruit juice used in traditional system of medicine for variety of purposes…
Abstract
Purpose
The purpose of this paper is to summarize the scientific information of various qualities of bael fruit juice used in traditional system of medicine for variety of purposes. Utilization of bael fruit juice in day-to-day life has great nutritional, therapeutic, and commercial importance. Bael fruit contains nutrients like vitamins (riboflavin), minerals, trace elements, energy and phytochemicals, including flavonoids, polyphenols and antioxidants, that have been shown to have varied health benefits. In past few decades, bael has been extensively studied for its medicinal properties by advanced scientific techniques, and a variety of bioactive compounds like marmelosin, tannins, alkaloids, coumarins, steroids, rutacine, y-sitosterol, psoralin, xanthotoxin, scopolotein, aegelemine, aegeline, marmeline, fragrine, dictamine, cinnamide and different derivatives of cinnamide have been isolated from its fruit juice.
Design/methodology/approach
The medicinal value of bael fruit is very high when the harvests just begin to ripen. As a result, it has a high demand as alternative medicine for curing the diseases like diabetes, high cholesterol, peptic ulcer, inflammation, diarrhea and dysentery, constipation, respiratory infection. Furthermore, the bael fruit juice has anticancer, cardio protective, antibacterial, antifungal, radio protective, antipyretic, analgesic, antioxidant, antiviral, anthelmintic and anti-inflammatory, hepatoprotective, wound healing properties. The ripe fruit juice is aromatic, has cooling and laxative effects, and arrests secretion or bleeding.
Findings
The unripe or half-ripe fruit juice is good for digestion, useful in preventing or curing scurvy, and it strengthens the stomach action. It helps in the healing of ulcerated intestinal surfaces and has appreciable activity against intestinal pathogenic organisms. The present review summarizes the scientific information of various qualities of bael fruit juice used in traditional system of medicine for a variety of purposes.
Originality/value
It is quite evident from this review that bael is an important medicinal herb and extensively used in Ayurveda, Siddha and other medicinal systems. Bael fruit juice is an excellent source of water and natural sugar and is important principally for containing vitamins, minerals, phytochemicals, antioxidants, pigments, energy, organic acids, dietary fiber and other food components, which are the key factors in the medicinal value of this plant. Moreover, mechanisms of action of a few bioactive compounds have been identified so far.
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Brijesh Sivathanu, Rajasshrie Pillai and Bhimaraya Metri
The purpose of this study was to investigate the online shopping intention of customers by watching artificial intelligence (AI)–based deepfake video advertisements using media…
Abstract
Purpose
The purpose of this study was to investigate the online shopping intention of customers by watching artificial intelligence (AI)–based deepfake video advertisements using media richness (MR) theory and Information Manipulation Theory 2 (IMT2).
Design/methodology/approach
A conceptual model was developed to understand customers' online shopping intention by watching deepfake videos. A quantitative survey was conducted among the 1,180 customers using a structured questionnaire to test the conceptual model, and data were analyzed with partial least squares structural equation modeling.
Findings
The outcome of this research provides the antecedents of the online shopping intention of customers after watching AI-based deepfake videos. These antecedents are MR, information manipulation tactics, personalization and perceived trust. Perceived deception negatively influences customers' online shopping intention, and cognitive load has no effect. It also elucidates the manipulation tactics used by the managers to develop AI-based deepfake videos.
Practical implications
The distinctive model that emerged is insightful for senior executives and managers in the e-commerce and retailing industry to understand the influence of AI-based deepfake videos. This provides the antecedents of online shopping intention due to deepfakes, which are helpful for designers, marketing managers and developers.
Originality/value
The authors amalgamate the MR and IMT2 theory to understand the online shopping intention of the customers after watching AI-based deepfake videos. This work is a pioneer in examining the effect of AI-based deepfakes on the online shopping intention of customers by providing a framework that is empirically validated.
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Rajasshrie Pillai, Yamini Ghanghorkar, Brijesh Sivathanu, Raed Algharabat and Nripendra P. Rana
AI-based chatbots are revamping employee communication in organizations. This paper examines the adoption of AI-based employee experience chatbots by employees.
Abstract
Purpose
AI-based chatbots are revamping employee communication in organizations. This paper examines the adoption of AI-based employee experience chatbots by employees.
Design/methodology/approach
The proposed model is developed using behavioral reasoning theory and empirically validated by surveying 1,130 employees and data was analyzed with PLS-SEM.
Findings
This research presents the “reasons for” and “reasons against” for the acceptance of AI-based employee experience chatbots. The “reasons for” are – personalization, interactivity, perceived intelligence and perceived anthropomorphism and the “reasons against” are perceived risk, language barrier and technological anxiety. It is found that “reasons for” have a positive association with attitude and adoption intention and “reasons against” have a negative association. Employees' values for openness to change are positively associated with “reasons for” and do not affect attitude and “reasons against”.
Originality/value
This is the first study exploring employees' attitude and adoption intention toward AI-based EEX chatbots using behavioral reasoning theory.