Brijesh Kumar, Veer Pal Singh, Vikas Pathak and Akhilesh K. Verma
This paper aims to assess the effect of natural antioxidants (Tulsi, Lemon grass and Aloevera) on sensory and microbiological quality as well as on Thiobarbituric acid (TBA…
Abstract
Purpose
This paper aims to assess the effect of natural antioxidants (Tulsi, Lemon grass and Aloevera) on sensory and microbiological quality as well as on Thiobarbituric acid (TBA) values of Redplum and Sahiwal-based milk smoothies stored under refrigeration.
Design/methodology/approach
The smoothies were developed by incorporating optimum level of natural antioxidants, fresh red plum and Sahiwal milk. They were aerobically packaged in low-density polyethylene pouches and stored under refrigeration (4 ± 2°C) till its spoilage. These smoothies were assessed for various storage quality parameters like sensory parameters, microbiological quality and TBA values at regular interval of two days.
Findings
Smoothies made without using natural antioxidants were in good condition for four days, and treated smoothies were stored well for six days. The microbial profile showed significant (p < 0.05) increase in SPC and psychrophilic counts on advancement of storage days. However, no coliform and yeast and mould were detected in all variants of smoothies during storage. TBA values were also increased during storage. But microbial counts and TBA both were under the prescribed limit as described by various organizations. Smoothies treated with Tulsi were found best followed by lemongrass- and aloevera-treated products.
Research limitations/implications
Amino acid and fatty acid profiling may be incorporated to known how the exact nutritional value.
Practical implications
Developed milk smoothies using natural antioxidants may serve the purpose of functional food.
Social implications
As per the authors, today, world is seeking for health providing components with longer product shelf life. Therefore, the product may serve the purpose.
Originality/value
The paper has demonstrated that the Sahiwal milk and red plum-based smoothies were of high acceptability. Their shelf life was found best when treated with Tulsi, Lemon grass and Aloevera natural antioxidants. It was better in all spectrums like lower microbial counts, higher sensory attributes and lower TBA counts as compared to untreated products.
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Ashish Kumar Srivastava, Brijesh Sharma, Bismin R. Saju, Arpit Shukla, Ambuj Saxena and Nagendra Kumar Maurya
The development of a new class of engineering materials is the current demand for aircraft and automobile companies. In this context metal, composite materials have a widespread…
Abstract
Purpose
The development of a new class of engineering materials is the current demand for aircraft and automobile companies. In this context metal, composite materials have a widespread application in different areas of manufacturing sectors.
Design/methodology/approach
In this paper, an attempt is made to develop the aluminium-based nano metal matrix composite reinforced with graphene nanoparticles (GNP) by using the stir casting method. Different weight percentage (0.4%, 0.8% and 1.2% by weight) of GNPs are used to fabricate metal matrix composites (MMCs). The developed nanocomposites were further validated by density calculation and optical microstructures to discuss the distribution of GNPs. The tensile test was conducted to determine the strength of the developed MMCs and also supported by fractographic analysis. In addition to it, the Rockwell hardness test and impact test (toughness) with fracture analysis were also conducted to strengthen the present work.
Findings
The results reveal the uniform distribution of GNPs into the matrix material. The yield strength and ultimate tensile strength obtained a maximum value of 155.67 MPa and 170.28 MPa, respectively. The hardness value (HRB) is significantly increased and 84 HRB was obtained for the sample with AA1100/0.4% GNP, while maximum hardness value (94 HRB) was obtained for the sample AA1100/1.2% GNP. The maximum value of toughness 14.3 Jules/cm2 is recorded for base alloy AA1100 while increasing the reinforcement percentage, it decreases up to 9.7 Jules/cm2 for AA1100/1.2% GNP.
Originality/value
Graphene nanoparticles are used to develop nanocomposites, which is one of the suitable alternatives for heavy engineering materials such as steels and cast irons. It has improved microstructural and mechanical properties which makes it preferable for many engineering and structural applications.
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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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Vivek Singh, Brijesh Mishra and Rajeev Singh
Purpose of this study is to design a compact gap coupled anchor shape patch antenna for wireless local area network/high performance radio local area network and worldwide…
Abstract
Purpose
Purpose of this study is to design a compact gap coupled anchor shape patch antenna for wireless local area network/high performance radio local area network and worldwide interoperability for microwave access applications.
Design/methodology/approach
An anchor shape microstrip antenna is conceived, designed, simulated and measured. The anchor shape antenna is transformed to its rectangular equivalent by conserving the patch area. Modeling and simulation of the antenna is performed by Ansys high frequency structure simulator (HFSS) electromagnetic solver based on the concept of finite element method. The simulated results are experimentally verified by using Agilent E5071C vector network analyzer. Theoretical analysis of an electromagnetically gap coupled anchor shape microstrip patch antenna has been performed by obtaining the lumped element equivalent of the transformed antenna.
Findings
The proposed antenna has a compact conducting patch of dimension 0.26λ × 0.12λ mm2 (λ is calculated at lower resonating frequency of 3.56 GHz) with impedance bandwidths of 100 and 140 MHz and antenna gains of 1.91 and 3.04 dB at lower resonating frequency of 3.56 GHz and upper resonating frequency of 5.4 GHz, with omni-directional radiation pattern.
Originality/value
In literature, one does not encounter anchor shape antenna using the concept of gap coupling and parasitic patches. The design has been optimized for wireless local area network/worldwide interoperability for microwave access applications with a relatively low patch area (291.12 mm2) as compared to other reported antennas for wireless local area network/worldwide interoperability for microwave access applications. Transformed antenna and the actual experimental antenna behavior varies, but the resonant frequencies of the transformed antenna as observed by theoretical analysis and simulated results (by high frequency structure simulator) are reasonably close, and the percentage difference between the resonant frequencies (both at lower and upper bands) is within the permissible limit of 1-2.5 per cent. Results confirm the theoretical proposition of transformation of shapes in antenna design, which allows a designer to adapt the design shape according to the application.
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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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Pooja Goel, Neeraj Kaushik, Brijesh Sivathanu, Rajasshrie Pillai and Jasper Vikas
The purpose of this study, a current systematic literature review, is to synthesize the extant literature on consumers’ adoption of artificial intelligence and robotics (AIR) in…
Abstract
Purpose
The purpose of this study, a current systematic literature review, is to synthesize the extant literature on consumers’ adoption of artificial intelligence and robotics (AIR) in the context of the hospitality and tourism sector (HATS) to gain a comprehensive understanding of it. This study also outlines insights for academia, practitioners, AI marketers, developers, designers and policymakers.
Design/methodology/approach
This study used a content analysis approach to conduct a systematic literature review for the period of 10 years (2011–2020) of the various published studies themed around consumer’s adoption of AIR in HATS.
Findings
The synthesis draws upon various factors affecting the adoption of AIR, such as individual factors, service factors, technical and performance factors, social and cultural factors and infrastructural factors. Additionally, the authors identified four major barriers, namely, psychological, social, financial, technical and functional that hinder the consumer’s adoption of artificial intelligence and robots in the hospitality and tourism industry.
Originality/value
To the best of the author’s/authors’ knowledge, this study is a first attempt to synthesize the factors that drive consumers’ adoption of artificial intelligence and robots in the hospitality and tourism industry. The present work also advances the tourism and consumer behavior literature by offering an integrated antecedent-outcome framework.
Visual abstract
Figure 2 The objective of the current systematic literature review is to synthesize the extant literature on consumer’s adoption of artificial intelligence and robotics (AIR) in the context of the hospitality and tourism sector (HATS) to gain a comprehensive understanding of it. For that purpose, authors conducted content analysis of extant literature on consumer’s adoption of AIR in HATS from 2011 to 2020. Authors presented an integrated antecedent outcome framework of the factors that drive consumer’s adoption of artificial intelligence and robots in the hospitality and tourism industry.
目的
这篇系统性文献综述的目的是综合现有关于消费者在酒店和旅游部门(HATS)中采用人工智能和机器人(AIR)的文献, 以便全面了解它。这项研究还概述了学术界、从业者、人工智能营销人员、开发人员、设计师和决策者的见解。
设计/方法论/方法
本研究使用内容分析方法对 10 年(2011–2020 年)期间的各种已发表研究进行系统的文献回顾, 主题围绕消费者在 HATS 中采用 AIR。
结果
本研究揭示了四大服务:自动化、定制、信息传播、旅游移动性和导航服务。 此外, 作者确定了阻碍消费者在酒店和旅游业采用人工智能和机器人的四大障碍, 即心理、社会、财务、技术和功能
原创性
本研究首次尝试综合推动消费者在酒店和旅游业中采用人工智能和机器人的因素。本文还通过提供一个综合的前因结果框架, 推进了旅游和消费者行为文献。
Resumen
Objetivo
El objetivo de la actual revisión sistemática literaria es sintetizar la literatura existente sobre la adopción de la inteligencia artificial y la robótica (IAR) por parte de los consumidores en el contexto del sector hotelero y turístico (SHT) para ganar un entendimiento comprensivo del mismo. Este estudio también traza visiones para los académicos, profesionales, comercializadores de AI, desarrolladores, diseñadores, y los elaboradores de las políticas a seguir.
Diseño/metodología/enfoque
El presente estudio siguió un enfoque de análisis de contenido para realizar una revisión sistemática de la literatura durante el período de 10 años (2011–2020) de los diversos estudios publicados y basados en la adopción de IAR en SHT, por parte de los consumidores.
Los hallazgos
Este estudio desvela cuatro grandes servicios: automatización, personalización, difusión de información, movilidad turística y servicios de navegación. Adicionalmente, los autores identificaron cuatro barreras principales, a saber; psicológicas, sociales, financieras, técnicas y funcionales, que impiden la adopción de la inteligenica artificial y la robótica por parte del consumidor, en la industria de la hospitalidad y el turismo.
Originalidad
Este estudio es un primer intento de sintetizar los factores que impulsan la adopción de la inteligencia artificial y la robótica por parte de los consumidores en la industria hotelera y turística. El presente trabajo también fomenta la literatura sobre el turismo y el comportamiento del consumidor, ofreciendo un marco integrado de resultados precedentes.
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Rajasshrie Pillai and Brijesh Sivathanu
The purpose of this paper is to investigate the adoption of Internet of Things (IoT) in the agriculture industry by the farmers' in India using the theoretical lens of the…
Abstract
Purpose
The purpose of this paper is to investigate the adoption of Internet of Things (IoT) in the agriculture industry by the farmers' in India using the theoretical lens of the behavioral reasoning theory (BRT).
Design/methodology/approach
A survey on farmers was conducted to examine the adoption of IoT in agriculture industry (IoT-A) using BRT. The data analysis of the primary survey was done by applying the structural equation modelling (SEM) technique.
Findings
The ‘reasons for’ adoption of IoT-A were as follows: Relative advantage, social influence, perceived convenience, and perceived usefulness. The ‘reasons against’ adoption were as follows: Image barrier, technological anxiety, perceived price and perceived risk. The BRT theory provides the platform to discuss the psychological processing of acceptance of IoT in agriculture industry by the farmers.
Practical implications
This research has unique implications as it studies the rural consumers’ behavior of innovation adoption namely IoT in agriculture. It provides the specific reasons ‘for’ and ‘against’ IoT adoption in agriculture, which will give directions to the marketers of IoT technology to develop suitable marketing strategies to improve the adoption in rural areas.
Originality/value
This research takes the first step in the direction toward deliberation of the adoption of IoT-A by farmers in an emerging Indian economy using the BRT theory, which discusses the ‘reasons for’ and ‘reasons against’ adoption in a proposed model.
Details
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Rajasshrie Pillai and Brijesh Sivathanu
Human resource managers are adopting AI technology for conducting various tasks of human resource management, starting from manpower planning till employee exit. AI technology is…
Abstract
Purpose
Human resource managers are adopting AI technology for conducting various tasks of human resource management, starting from manpower planning till employee exit. AI technology is prominently used for talent acquisition in organizations. This research investigates the adoption of AI technology for talent acquisition.
Design/methodology/approach
This study employs Technology-Organization-Environment (TOE) and Task-Technology-Fit (TTF) framework and proposes a model to explore the adoption of AI technology for talent acquisition. The survey was conducted among the 562 human resource managers and talent acquisition managers with a structured questionnaire. The analysis of data was completed using PLS-SEM.
Findings
This research reveals that cost-effectiveness, relative advantage, top management support, HR readiness, competitive pressure and support from AI vendors positively affect AI technology adoption for talent acquisition. Security and privacy issues negatively influence the adoption of AI technology. It is found that task and technology characteristics influence the task technology fit of AI technology for talent acquisition. Adoption and task technology fit of AI technology influence the actual usage of AI technology for talent acquisition. It is revealed that stickiness to traditional talent acquisition methods negatively moderates the association between adoption and actual usage of AI technology for talent acquisition. The proposed model was empirically validated and revealed the predictors of adoption and actual usage of AI technology for talent acquisition.
Practical implications
This paper provides the predictors of the adoption of AI technology for talent acquisition, which is emerging extensively in the human resource domain. It provides vital insights to the human resource managers to benchmark AI technology required for talent acquisition. Marketers can develop their marketing plan considering the factors of adoption. It would help designers to understand the factors of adoption and design the AI technology algorithms and applications for talent acquisition. It contributes to advance the literature of technology adoption by interweaving it with the human resource domain literature on talent acquisition.
Originality/value
This research uniquely validates the model for the adoption of AI technology for talent acquisition using the TOE and TTF framework. It reveals the factors influencing the adoption and actual usage of AI technology for talent acquisition.