Search results

This paper aims to propose a novel methodology for classifying the gestures using support vector machine (SVM) classification method. Initially, the Red Green Blue color hand gesture image is converted into YC_bC_r image in preprocessing stage and then palm with finger region is segmented by threshold process. Then, distance transformation method is applied on the palm with finger segmented image. Further, the center point (centroid) of palm region is detected and the fingertips are detected using SVM classification algorithm based on the detected centroids of the detected palm region.

Gesture is a physical indication of the body to convey information. Though any bodily movement can be considered a gesture, generally it originates from the movement of hand or face or combination of both. Combined gestures are quiet complex and difficult for a machine to classify. This paper proposes a novel methodology for classifying the gestures using SVM classification method. Initially, the color hand gesture image is converted into YC_bC_r image in preprocessing stage and then palm with finger region is segmented by threshold process. Then, distance transformation method is applied on the palm with finger segmented image. Further, the center point of the palm region is detected and the fingertips are detected using SVM classification algorithm. The proposed hand gesture image classification system is applied and tested on “Jochen Triesch,” “Sebastien Marcel” and “11Khands” data set hand gesture images to evaluate the efficiency of the proposed system. The performance of the proposed system is analyzed with respect to sensitivity, specificity, accuracy and recognition rate. The simulation results of the proposed method on these different data sets are compared with the conventional methods.

This paper proposes a novel methodology for classifying the gestures using SVM classification method. Distance transform method is used to detect the center point of the segmented palm region. The proposed hand gesture detection methodology achieves 96.5% of sensitivity, 97.1% of specificity, 96.9% of accuracy and 99.3% of recognition rate on “Jochen Triesch” data set. The proposed hand gesture detection methodology achieves 94.6% of sensitivity, 95.4% of specificity, 95.3% of accuracy and 97.8% of recognition rate on “Sebastien Marcel” data set. The proposed hand gesture detection methodology achieves 97% of sensitivity, 98% of specificity, 98.1% of accuracy and 98.8% of recognition rate on “11Khands” data set. The proposed hand gesture detection methodology consumes 0.52 s as recognition time on “Jochen Triesch” data set images, 0.71 s as recognition time on “Sebastien Marcel” data set images and 0.22 s as recognition time on “11Khands” data set images. It is very clear that the proposed hand gesture detection methodology consumes less recognition rate on “11Khands” data set when compared with other data set images. Hence, this data set is very suitable for real-time hand gesture applications with multi background environments.

The modern world requires more numbers of automated systems for improving our daily routine activities in an efficient manner. This present day technology emerges touch screen methodology for operating or functioning many devices or machines with or without wire connections. This also makes impact on automated vehicles where the vehicles can be operated without any interfacing with the driver. This is possible through hand gesture recognition system. This hand gesture recognition system captures the real-time hand gestures, a physical movement of human hand, as a digital image and recognizes them with the pre stored set of hand gestures.

On completion of this case study, students will be able to understand collaboration and synergy between farmers and organisations through value creation, like fundraising, based on the comprehension of the resource-based theory; understand the overview and concept of the value chain and supply chain management in the agribusiness to reduce costs of inventories; understand the concept of segmentation and positioning to increase revenue for organisations by leveraging existing resources – human and financial; and understand the branding strategy to create a sustainable competitive advantage for Suguna Foods.

Suguna was started by two brothers, B. Soundararajan and G.B. Sundararajan, to help other farmers. Suguna, with just 200 broilers in 1984, grew to be the number 1 poultry company across India. Soundararajan was a pioneer and innovator who started “contract farming” in India in 1991. This model helped both the farmers and the company to became successful. The farmers always struggled to pay the cost of feed and other materials, as credit was not readily and easily available from financial institutions. Suguna helped farmers by providing feed, medicines, etc., free of cost in return for the good rearing of chickens. Because of the success of this venture, they decided to continue with it. Today, Suguna is a successful company that sells chicken, eggs and processed meat. They modernised the retail chain to supply consumers with fresh, healthy and hygienic meat. Suguna’s vision was to “Energize rural India” by helping farmers succeed. They helped over 40,000 farmers from 15,000+ villages in 18+ Indian states. Although the growth helped both farmers and Suguna, the increased cost of raw materials for Suguna and increased input costs/power costs for farmers had to be tackled on a war footing so that both could have good income despite the increased inflation. Moreover, the retail price of live chicken was more or less stagnant in the past five years, especially after the start of the COVID-19 pandemic.

This case can be used as the basis for a 90-min class discussion. This case study is suitable for use in an master of business administration course module or in an executive education program on developing an understanding of value creation in the business model in a rural market and also how the supply chain works. This case study can also be used to teach pricing, segmentation in marketing and supply chain perspectives and decision-making skills.

Teaching notes are available for educators only.

CSS8: Marketing.

The primary purpose of this study is to examine the factors leading to shopping cart abandonment and construct a model depicting interrelationship among them using interpretive structural modeling (ISM) and Matriced Impact Croises Multiplication Appliquee an un Classement (MICMAC).

Initially, 20 factors leading to shopping cart abandonment were extracted through a systematic literature review and expert opinions. Fifteen factors were finalized using the importance index and CIMTC method, for which consistency has been checked in SPSS software through a statistical reliability test. Finally, ISM and MICMAC approach is used to develop a model depicting the contextual relationship among finalized factors of shopping cart abandonment.

The ISM model depicts a technical glitch (SC8), cash on delivery not available (SC4), bad checkout interface (SC9), just browsing (SC11), and lack of physical examination (SC12) are drivers or independent factors. Additionally, four quadrants have been formulated in MICMAC analysis based on their dependency and driving power. This facilitates technical managers of e-commerce companies to focus more on factors leading to shopping cart abandonment according to their dependency and driving power.

Taking an expert’s opinion as a base may affect the results of the study due to biases based on subjectivity.

This study’s outcomes would accommodate practitioners, researchers, and multinational or national companies to indulge in e-commerce to anticipate factors restricting the general public from online shopping.

For the successful running of an e-commerce business and to retain the confidence of e-shoppers, every e-commerce company must make a strategy for controlling factors leading to shopping cart abandonment at the initial stage. So, this paper attempts to highlight the main factors leading to shopping cart abandonment and interrelate them using ISM and MICMAC approaches. It provides a clear path to technical heads, researchers, and consultants for handling these shopping cart abandonment factors.

The continuous presence and intensity of the Internet of things (IoT) in our lives and the risk of security breaches in traditional transactional and financial platforms are the major cause of personal and organizational data losses. Blockchain emerges as a promised technology to ensure higher levels of data encryption and security. Thus, this study aims to develop a systematic literature review analyzing the previous literature and to purpose of a framework to better understand the process of blockchain security.

The 75 articles reviewed were obtained through the Scopus database and a bibliographic-coupling analysis was developed to identify the main themes of this research area, via VOSviewer software.

The results enable the categorization of the existing literature revealing four clusters: 1) feasibility, 2) fintech and cryptocurrency, 3) data trust and share and 4) applicability. Blockchain technology is still in its early stage of development and counting on researchers in security and cryptography to take it further to new highs, to allow its applicability to different areas and in long-term scenarios.

This systematic literature creates a base to reduce the blockchain security literature gap. In addition, it provides a framework that enables the scientific community to access the main subjects discussed and the articulation between concepts. Furthermore, it enhances the state-of-the-art literature on blockchain security and proposes a future research agenda.

While the disruptive potential of artificial intelligence (AI) has been receiving growing consensus with regards to its positive influence on entrepreneurship, there is a clear lack of systematization in academic literature pertaining to this correlation. The current research seeks to explore the impact of AI on entrepreneurship as an enabler for entrepreneurs, taking into account the crucial application of AI within all Industry 4.0 technological paradigms, such as smart factory, the Internet of things (IoT), augmented reality (AR) and blockchain.

A systematic literature review was used to analyze all relevant studies forging connections between AI and entrepreneurship. The cluster interpretation follows a structure that we called the “AI-enabled entrepreneurial process.”

This study proves that AI has profound implications when it comes to entrepreneurship and, in particular, positively impacts entrepreneurs in four ways: through opportunity, decision-making, performance, and education and research.

The framework's practical value is linked to its applications for researchers, entrepreneurs and aspiring entrepreneurs (as well as those acting entrepreneurially within established organizations) who want to unleash the power of AI in an entrepreneurial setting.

This research offers a model through which to interpret the impact of AI on entrepreneurship, systematizing disconnected studies on the topic and arranging contributions into paradigms of entrepreneurial and managerial literature.

This paper aims to examine the presence of impulsive and compulsive buying among consumers. It studies the various factors that affect and moderate the impulsiveness and compulsiveness of buying.

Literature review resulted in four constructs – social media influence, social media preferences, hedonic motivation and shop in COVID-19. On conducting factor analysis in statistical package for the social sciences, the variables were divided under the influence of social media, social commerce, electronic word of mouth (EWOM) of social commerce, hedonic happiness, hedonic fun and shopping in times of COVID-19. Structural equation modeling is conducted in AMOS (statistical software) for a diagrammatic representation of the relationship between the variables. Regression analysis is used to re-affirm the above relationship. Testing of hypotheses is done with the help of the chi-square test.

All six latent variables are significantly related to impulsive and compulsive buying. However, the regression analysis shows social media influence as the strongest predictor for impulse buying and hedonic happiness for compulsive buying. Also, the presence of the pandemic COVID-19 leads to impulsive buying as well as compulsive buying in the apparel and accessory segment.

Marketers should capitalize on spontaneous buying in both forms – impulsive buying and compulsive buying. Social media influencers, as well as more consumer engagement on social media, can promote impulsive buying. However, compulsive buyers will be more attracted towards great in-store experiences or hedonically driven advertisements, as they do not just shop for buying the product; they shop for the experience of shopping.

This study uncovers the difference in factors that affect impulsive and compulsive buying. Though both behaviours seem points of the same scale, they are inherently different and can be predicted with social media influence and hedonic happiness.

The aim of this paper is to study and describe the Industry 4.0 (I4.0) concept in the retail industry by identifying the technology enablers, the benefits and the challenges involved in adopting these technologies.

The work is built on a systematic literature review (SLR) about the I4.0 concept within retail studies through the enablers codified by the Industry 4.0 literature.

The concept of Industry 4.0 within the retail context is presented through three relevant technology enablers I4.0 emerges as a latent concept represented by technologies adopted to study customer behaviour and manage customer relationships and, partially, to optimise retail management. Furthermore, the paper highlights the benefits and challenges stemming from the adoption of I4.0 technology enablers in the retail industry.

The use of a SLR to describe the I4.0 concept in the retail industry identifying the relevant technology enablers and their relations. The article lays the foundations for future studies on the integrated effects of the contemporary actions of multiple technologies on retail management.

This paper aims at examining the potentiality of using Hibiscus sabdariffa L. calyces’ (Hs) aqueous extract to remove soot stains from the surface of fire-damaged silver gelatin prints. It further studies the cleaning efficiency and impact of both a contact method and a noncontact method with argon dielectric barrier discharge plasma (DBD Ar. plasma) on the different properties of silver gelatin prints. Accordingly, it prompts using economic, eco-friendly materials and methods in the photograph conservation field.

To achieve the aims of this paper, four silver gelatin prints were stained with soot and treated with the Hs aqueous extract as a contact method and DBD Ar. plasma combined with the aqueous extract as a noncontact method. The assessment was carried out using digital microscopy, atomic force microscopy and spectrophotometer to study the efficiency of the tested treatments and their impact on the surface of the photographs. Fourier transform infrared was used to monitor the state of the binder after cleaning. Furthermore, the pH and the mechanical properties were measured.

The contact method resulted in lower concentrations of Hs extract that efficiently cleaned the surface without causing any stains or damage to the treated photographs. The noncontact method (plasma with an aqueous extract) proved to be less effective in cleaning and made the binder more susceptible to deterioration.

This paper reveals the success of Hs aqueous extract in cleaning soot on vulnerable photographs' surfaces.

Security is the most important issue in Internet of Things (IoT)-based smart cities and blockchain (BC). So, the present paper aims to detect and organize the literature regarding security in the IoT-based smart cities and BC context. It also proposes an agenda for future research. Therefore, the authors did a statistical review of security in IoT and BC in smart cities. The present investigation aims to determine the principal challenges and disturbances in IoT because of the BC adoption, the central BC applications in IoT-based smart cities and the BC future in IoT-based smart cities.

IoT) has a notable influence on modernizing and transforming the society and industry for knowledge digitizing. Therefore, it may be perceived and operated in real time. The IoT is undergoing exponential development in industry and investigation. Still, it contains some security and privacy susceptibilities. Naturally, the research community pays attention to the security and privacy of the IoT. Also, the academic community has put a significant focus on BC as a new security project. In the present paper, the significant mechanisms and investigations in BC ground have been checked out systematically because of the significance of security in the IoT and BC in smart cities. Electronic databases were used to search for keywords. Totally, based on different filters, 131 papers have been gained, and 17 related articles have been obtained and analyzed. The security mechanisms of BC in IoT-based smart cities have been ranked into three main categories as follows, smart health care, smart home and smart agriculture.

The findings showed that BC’s distinctive technical aspects might impressively find a solution for privacy and security problems encountering the IoT-based smart cities development. They also supply distributed storage, transparency, trust and other IoT support to form a valid, impressive and secure distributed IoT network and provide a beneficial guarantee for IoT-based smart city users’ security and privacy.

The present investigation aims to be comprehensive, but some restrictions were also observed. Owing to the use of some filters for selecting the original papers, some complete works may be excluded. Besides, inspecting the total investigations on the security topic in BC and the IoT-based smart cities is infeasible. Albeit, the authors attempt to introduce a complete inspection of the security challenges in BC and the IoT-based smart cities. BC includes significant progress and innovation in the IoT-based smart cities’ security domain as new technology. Still, it contains some deficiencies as well. Investigators actively encounter the challenges and bring up persistent innovation and inspection of related technologies in the vision of the issues available in diverse application scenarios.

The use of BC technology in finding a solution for the security issues of the IoT-based smart cities is a research hotspot. There is numerable literature with data and theoretical support despite the suggestion of numerous relevant opinions. Therefore, this paper offers insights into how findings may guide practitioners and researchers in developing appropriate security systems dependent upon the features of IoT-based smart city systems and BC. This paper may also stimulate further investigation on the challenge of security in BC and IoT-based smart cities. The outcomes will be of great value for scholars and may supply sights into future investigation grounds in the present field.

As the authors state according to their knowledge, it is the first work using security challenges on BC and IoT-based smart cities. The literature review shows that few papers discuss how solving security issues in the IoT-based smart cities can benefit from the BC. The investigation suggests a literature review on the topic, recommending some thoughts on using security tools in the IoT-based smart cities. The present investigation helps organizations plan to integrate IoT and BC to detect the areas to focus. It also assists in better resource planning for the successful execution of smart technologies in their supply chains.