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                <text>An Image Quality Selection and Effective Denoising on Retinal Images Using Hybrid Approaches</text>
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                <text>Green Channel; Image Quality; Noise Filtering; Pre-Processing; Quality Score; Retinal Image</text>
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                <text>Retinal image analysis has remained an essential topic of research in the last decades. Several algorithms and techniques have been developed for the analysis of retinal images. Most of these techniques use benchmark retinal image datasets to evaluate performance without first exploring the quality of the retinal image. Hence, the performance metrics evaluated by these approaches are uncertain. In this paper, the quality of the images is selected by utilizing the hybrid naturalness image quality evaluator and the perception-based image quality evaluator (hybrid NIQE-PIQE) approach. Here, the raw input image quality score is evaluated using the Hybrid NIQE-PIQE approach. Based on the quality score value, the deep learning convolutional neural network (DCNN) categorizes the images into low quality, medium quality and high quality images. Then the selected quality images are again pre-processed to remove the noise present in the images. The individual green channel (G-channel) is extracted from the selected quality RGB images for noise filtering. Moreover, hybrid modified histogram equalization and homomorphic filtering (Hybrid G-MHE-HF) are utilized for enhanced noise filtering. The implementation of proposed scheme is implemented on MATLAB 2021a. The performance of the implemented method is compared with the other approaches to the accuracy, sensitivity, specificity, precision and F-score on DRIMDB and DRIVE datasets. The proposed schemes accuracy is 0.9774, sensitivity is 0.9562, precision is 0.99, specificity is 0.99, and F-measure is 0.9776 on the DRIMDB dataset, respectively.  2023 Baqiyatallah University of Medical Sciences. All rights reserved.</text>
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                <text>Saju B.; Rajesh R.</text>
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                <text>International Journal on Recent and Innovation Trends in Computing and Communication, Vol-11, No. 5, pp. 170-180.</text>
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                <text>Auricle Global Society of Education and Research</text>
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                <text>&lt;a href="https://doi.org/10.17762/ijritcc.v11i5.6603" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.17762/ijritcc.v11i5.6603&lt;/a&gt;
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                <text>ISSN: 23218169</text>
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                <text>Saju B., Department of Computer Science, Christ (Deemed to be University), Karnataka, Bengaluru, 560029, India; Rajesh R., Department of Computer Science, Christ (Deemed to be University), Karnataka, Bengaluru, 560029, India</text>
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                <text>Eye-Vision Net: Cataract Detection and Classification in Retinal and Slit Lamp Images using Deep Network</text>
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                <text>Aquila optimization; Be-resnet101; Cataract detection; Crnn; Dense cnn; Grade classification</text>
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                <text>In the modern world, cataracts are the predominant cause of blindness. Early treatment and detection can reduce the number of cataract patients and prevent surgery. However, cataract grade classification is necessary to control risk and avoid blindness. Previously, various studies focused on developing a system to detect cataract type and grade. However, the existing works on cataract detection does not provide optimal results because of high detection error, lack of learning ability, computational complexity issues, etc. Therefore, the proposed work aims to develop an effective deep learning techniques for detecting and classifying cataracts from the given input samples. Here, the cataract detection and classification are performed using two phases. In order to provide an accurate cataract detection, the proposed study introduced Deep Optimized Convolutional Recurrent Network_Improved Aquila Optimization (Deep OCRN_IAO) model in phase I. Here, both retinal and slit lamp images are utilized for cataract detection. Then, the performance of these two image datasets are analysed, and the best one is chosen for cataract type and grade classification. By analysing the performance, the slit lamp images attain higher results. Therefore, phase II uses slit lamp images and detects the type and grade of cataracts through the proposed Batch Equivalence ResNet-101 (BE_ResNet101) model. The proposed classification model is highly efficient to classify the type and grades of cataracts. The experimental setup is done using MATLAB software, and the datasets used for simulation purposes are DRIMDB (Diabetic Retinopathy Images Database) and real-time slit lamp images. The proposed type and grade detection model has an accuracy of 98.87%, specificity of 99.66%, the sensitivity of 98.28%, Youden index of 95.04%, Kappa of 97.83%, and F1-score is 95.68%. The obtained results and comparative analysis proves that the proposed model is highly suitable for cataract detection and classification.  2022, International Journal of Advanced Computer Science and Applications. All Rights Reserved.</text>
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                <text>Saju B.; Rajesh R.</text>
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                <text>International Journal of Advanced Computer Science and Applications, Vol-13, No. 12, pp. 211-221.</text>
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                <text>&lt;a href="https://doi.org/10.14569/IJACSA.2022.0131227" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.14569/IJACSA.2022.0131227&lt;/a&gt;
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              <elementText elementTextId="110118">
                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 2158107X</text>
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                <text>Saju B., Department of Computer Science, Christ (Deemed to be University), Karnataka, Bengaluru, 560029, India; Rajesh R., Department of Computer Science, Christ (Deemed to be University), Karnataka, Bengaluru, 560029, India</text>
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                <text>A Comprehensive Study on Computer-Aided Cataract Detection, Classification, and Management Using Artificial Intelligence</text>
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          <element elementId="49">
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                <text>Artificial intelligence; Cataract; Machine learning</text>
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                <text>The day-to-day popularity of computer-aided detection is increasing medical field. Cataract is a main cause of blindness in the entire world. Compared with the other eye diseases, computer-aided development in the area of cataract is remaining underexplored. Several researches are done for automated detection of cataract. Many study groups have proposed many computer-aided systems for detecting cataract, classifying the different type, identification of stages, and calculation of lens power selection prior to cataract surgery. With the advancement in the artificial intelligence and machine learning, future cataract-related research work can undergo very useful achievements in the coming days. The paper studies various recent researches done related to cataract detection, classification, and grading using various artificial intelligence techniques. Various comparisons are done based on the methodology used, type of dataset, and the accuracy of various methodologies. Based on the comparative study, research gap is identified, and a new method is proposed which can overcome the disadvantages and gaps of the studied work.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Saju B.; Rajesh R.</text>
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                <text>Lecture Notes on Data Engineering and Communications Technologies, Vol-114, pp. 355-366.</text>
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                <text>Springer Science and Business Media Deutschland GmbH</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-981-16-9416-5_25" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-16-9416-5_25&lt;/a&gt;
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                <text>ISSN: 23674512</text>
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                <text>Saju B., CHIST (Deemed to be University), Bangalore, India, New Horizon College of Engineering, Karnataka, Bangalore, India; Rajesh R., CHIST (Deemed to be University), Bangalore, India</text>
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                <text> In modern world, Cataract is the predominant causative of blindness. Treatment and detection at the early stage can reduce the number of cataract sufferers and prevent surgery. Two types of images are generally used for cataract related studies- Retinal Images an Slit lamp Images. The quality of Retinal images is selected by utilizing the hybrid naturalness image quality evaluator (hybrid NIQE-PIQE) approach. Here, the raw input image quality score is and Deep newlinelearning convolutional neural network (DCNN) categorizes the images based on quality newlinescore. Then the selected quality images are again pre-processed to remove the noise present in the images. The individual green channel (G-channel) is extracted for noise filtering. Moreover, hybrid modified histogram equalization and homomorphic filtering (Hybrid GMHE-HF) is utilized for enhanced noise filtering. The Slit lamp image quality selection is done using Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) model. Further a new algorithm Normalization based Contrast limited adaptive histogram equalization (NCLAHE) is used for image enhancement. Images are pre-processed utilizing the wiener filtering (WF) with Convolutional neural network (CNN) with adaptive atom search optimization (CNN-AASO) for removing the noise. Further, the denoised image is enhanced by Gaussian mixture based contrast enhancement (GMCE) for contrast enhancement. The cataract detection and classification is performed using two phases. In phase I, the cataract is detected using Deep Optimized Convolutional Recurrent Network_Improved Aquila Optimization (Deep OCRN_IAO) model. Phase II uses slit lamp images and detects the type and grade of cataracts through proposed Batch Equivalence ResNet-101 (BE_ResNet101) model.This work also proposes the risk factors for cataracts and classify the cataracts risk using deep learning models. The dataset is pre-processed by missing values and the string values are converted into numeric values.</text>
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                <text>R, Rajesh</text>
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                <text>Di-cationic ionic liquid catalyzed synthesis of 1,5-benzothiazepines</text>
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                <text>1,5-Benzodiazepines; 1,5-Benzothiazepines; Cyclo-condensation reaction; gem-Dicationic ionic liquids; Reusability</text>
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                <text>A simple and elegant method for the synthesis of 1,5-benzothiazepines has been developed using di-cationic liquid as a solvent cum catalyst by the reaction of o-aminothiophenol with a variety of chalcones under mild reaction conditions. Furthermore the reusability of the catalyst has also been studied for three cycles. All the reactions are proposed to proceed through a 1,4-conjugate Michael addition followed by a cyclo-condensation reaction.  2018, Chemical Publishing Co. All rights reserved.</text>
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                <text>Asian Journal of Chemistry, Vol-30, No. 1, pp. 107-115.</text>
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                <text>&lt;a href="https://doi.org/10.14233/ajchem.2018.20920" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.14233/ajchem.2018.20920&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037991750&amp;amp;doi=10.14233%2Fajchem.2018.20920&amp;amp;partnerID=40&amp;amp;md5=366f01fb197ddd17e1910cc13f7c3497" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037991750&amp;amp;doi=10.14233%2fajchem.2018.20920&amp;amp;partnerID=40&amp;amp;md5=366f01fb197ddd17e1910cc13f7c3497&lt;/a&gt;</text>
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                <text>All Open Access; Bronze Open Access</text>
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                <text>Sakirolla R., Department of Chemistry, Central University of Karnataka, Kadaganchi, Aland Road, Kalaburagi, 585 367, India; Tadiparthi K., Department of Chemistry, Christ University, Hosur Road, Bangalore, 560 029, India; Yaeghoobi M., Department of Chemistry, University of Malaya, Kuala Lumpur, 50603, Malaysia; Rahman N.Abd., Department of Chemistry, University of Malaya, Kuala Lumpur, 50603, Malaysia</text>
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                <text>Exploration of the effects of anisotropy and rotation on RayleighBard convection of nanoliquid-saturated porous medium using general boundary conditions</text>
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                <text>anisotropy; Convection; general boundaries; nanoliquid; porous medium; rotation</text>
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                <text>This paper presents an analysis of RayleighBard convection (RBC) of a Newtonian-nanoliquid-saturated anisotropic porous medium in the presence of rotation (RayleighBardTaylor convection). The investigation is performed using non-classical boundary conditions. The effect of various parameters on the onset of convection is presented graphically. The system sees stabilisation due to an increase in the rotation rate and thermal anisotropy parameter whereas the system destabilises due to an increase in the mechanical anisotropy parameter. The results of 82 limiting cases can be extracted from the current work. The results of free-free, rigid-free and rigid-rigid isothermal/adiabatic boundaries are obtained from the present study by considering appropriate limits. The results of the limiting cases of the present study are in excellent agreement with those observed in earlier investigations.  2024 Informa UK Limited, trading as Taylor &amp;amp; Francis Group.</text>
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                <text>Detection of incorrect and malign data transfers in the Internet of Things (IoT) network is important for IoT safety to observe an eye on and prevent unwelcomed traffic flow to the network of IoT. For it, Machine Learning (ML) strategic methods are produced by several researchers to prevent malign data flows through the network of IoT. Nonetheless, because of the wrong choice of feature, a few malign Machine Learning models differentiate especially the movement of malign traffic. Still, what matters is the problem that needs to be deliberated in-depth to select the best features for better malign traffic acquisition in the network of IoT. Dealing with the challenge, a new process was proposed. 1st, the metric method of selecting a novel feature called the proposed CorrAUC, and hinged on CorrAUC, a new highlight for choosing the Corrauc algorithm name is also being developed, designed hinged on the system folding filter features precisely and select the active features of the choose ML method using AUC metric. After that, we apply a combined application Order of Preference by Similarity to Ideal Solution Using Shannon Entropy (TOPSIS) built on a bijective set which is soft to verify selected features for identification of malign 1traffic in IoT network. We test our method using data set of Bot-IoT and 4 dissimilar ML classifiers. Practical outcomeanalysis showed that our proposed approach works as well and can achieve greater than 96% results on average.  2022 Wolters Kluwer Medknow Publications. All rights reserved.</text>
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                <text>Sakthivel M., Department of CSE, Sree Vidyanikethan Engineering College, Andhra Pradesh, Tirupati, India; Sivanantham S., Department of CSSE, Sree Vidyanikethan Engineering College, Andhra Pradesh, Tirupati, India; Akshaya V., Department of CSE, Sree Vidyanikethan Engineering College, Andhra Pradesh, Tirupati, India; Sivakumar D., Department of CSSE, Sree Vidyanikethan Engineering College, Andhra Pradesh, Tirupati, India; Karthikeyan H., School of Engineering and Technology, CHRIST (Deemed To Be University), Karnataka, Bengaluru, India</text>
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                <text>Saldanha A., Department of Marketing, St Josephs Institute of Management, Bangalore, India; Aranha R., School of Business and Management, Christ University, Bangalore, India</text>
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                <text>Research methodology: A secondary research method was used to collect data for this case. The authors have made use of newspaper articles and published articles written by journalists and experts which are available in the public domain. Case overview/synopsis: Instances of celebrity activism such as athlete activism are rising. Social media has amplified the voice of celebrities and given them a personal channel to directly communicate with their fans without any media censorship. The same is true especially concerning endorsement by sports superstars, who now seem to have a mind of their own, independent of the official line of clubs, tournament organizers or sponsoring companies. This case discusses the embarrassment and financial loss faced by soft drinks giant Coca-Cola due to the public snub by football superstar Cristiano Ronaldo during an official press conference of the EURO 2020 championship. Complexity academic level: Undergraduate and postgraduate students studying marketing management and brand management courses in business management and commerce streams can use this case. This case can also be used for marketing specialization students at the undergraduate and postgraduate levels.  2023, Emerald Publishing Limited.</text>
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                <text>CASE Journal, Vol-19, No. 5, pp. 737-745.</text>
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                <text>Saldanha A., Department of Marketing, St. Joseph's Institute of Management, Bangalore, India; Aranha R., Department of HR, School of Business and Management, CHRIST (Deemed to be University, Bangalore, India</text>
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                <text>Learning outcomes: The learning outcomes of this study are as follows:1. Analyze the pricing strategy followed by Netflix in India;2. Examine the challenges faced by media companies, including over-the-top (OTT) service providers, in developing content for target consumers in emerging markets; and3. Evaluate the dynamics of the Indian OTT industry and understand the effect of external and internal factors on the growth of Netflix in India. Case overview/synopsis: This case discusses the dilemma faced by Netflix in India regarding pricing and content. Netflix was accused of hurting the religious and political sentiments of Indians by broadcasting bold shows such as Sacred Games and A Suitable Boy. Netflix is caught in a dilemma between its pursuit to achieve its target of achieving 100 million subscribers from India versus continuing its profitable high pricing strategy. Another key dilemma is regarding the streaming of attractive bold content which may occasionally hurt the religious/political sentiments of some Indians or stream only safe content which may be deemed as boring by its young target audience. Complexity academic level: Undergraduate and postgraduate students studying Marketing courses in Commerce and Business Management streams can use this case. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 8: Marketing.  2022, Emerald Publishing Limited.</text>
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                <text>Learning outcomes: After discussing this case, the authors expect that the students will have the following learnings: critically analyse the latest Reserve Bank of India (RBI) banking proposal, which was proposed by the Internal Working Group (IWG) in November 2020. Understand concepts such as connected lending, crony capitalism and financial crisis. Have a basic idea about the Banking Regulations Act, 1949 and regulatory framework in the Indian banking sector. Case overview/synopsis: This case is an analysis of the recent RBI proposal on banking regulations in India. The authors have referred secondary data in terms of published papers by stalwarts and experts in the banking and economics field. This case analyses the pros and cons of the IWG proposal to RBI governing body. The case also touches upon interesting banking and macroeconomics concepts. What makes this case interesting is that RBI is open to receive comments from all the stakeholders till January 2021. Complexity academic level: Applicable to undergraduate and postgraduate students studying banking and finance specialisation in commerce and business management streams. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 1: Accounting and Finance.  2021, Emerald Publishing Limited.</text>
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                <text>Emerald Emerging Markets Case Studies, Vol-11, No. 3, pp. 1-14.</text>
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                <text>Asian Case Research Journal, Vol-27, No. 1, pp. 43-58.</text>
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                <text>Saldanha A., Department of Marketing, St. Joseph's Institute of Management, Karnataka, Bengaluru, India; Aranha R.H., School of Business and Management Christ (Deemed to Be University), Karnataka, Bengaluru, India</text>
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                <text>Learning outcomes: This case study provides students/managers an opportunity to learn about:??Learning objective 1: Critically analyse reasons for the disgruntlement of delivery partners of Zomato.??Learning objective 2: Evaluate Zomatos moral obligations to gig workers in the absence of government regulations.??Learning objective 3: Analyse the drivers of well-being affecting e-commerce delivery partners.??Learning objective 4: Evaluate the welfare schemes undertaken by Zomato for its delivery partners and infer well-being measures that can be adopted to improve worker engagement. Case overview/synopsis: The focus of this case was the crisis at Zomato as a result of the protests by gig workers engaged as delivery partners at the company. This case discussed the CEOs dilemma in resolving the crisis. Zomato's business model was discussed to provide students an overview of the dynamics and challenges of online food delivery business; the companys initiatives to enhance the robustness of its business model and the resulting media backlash questioning some of these initiatives that could endanger the lives of its delivery partners. In addition, this case explored the lack of regulatory provisions for gig workers in India. Finally, the options available to the protagonist to mitigate the crisis were discussed. The focal point was the well-being initiatives that the protagonist could consider implementing to address the concerns voiced by the delivery partners and encourage them to engage in Zomato's business with positivity. Complexity academic level: The case is best suited for postgraduate and executive students studying Human Resources subjects in Commerce and Business Management streams. Supplementary material: Teaching notes are available for educators only. Subject code: CSS 6: Human Resource Management.  2022, Emerald Publishing Limited.</text>
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                <text>Saldanha A., Department of Marketing, St. Josephs Institute of Management, Bangalore, India; Balasundaram S., School of Business and Management, CHRIST (Deemed to be University, Bangalore, India; Aranha R., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India</text>
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                <text>Desiri Naturals: sustainable agriculture and eco-friendly business</text>
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                <text>Awareness; Business model; Entrepreneurship; Green marketing; Marketing; Marketing management; Operations management; Organic products; Packaging; Pricing; Social marketing; Sustainability</text>
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                <text>Learning outcomes: After completion of the case study, the students will be able to critically analyze the business model of Desiri Naturals, analyze the pricing strategy of Desiri Naturals, examine the importance of experiential marketing in the success of an environment-friendly business, identify the challenges faced by new entrepreneurs and evaluate the sustainability practices of Desiri Naturals. Case overview/synopsis: This case study discusses the business model of an environmentally friendly business. The challenges and obstacles faced by entrepreneurs are illustrated in this case. The entrepreneurs vision to provide chemical-free food is highlighted and their business operations as a means to fulfill this vision are explained. Desiri used an age-old bull-driven method of oil extraction (Ghana). Challenges in pricing due to the availability of low-priced mass-produced edible oil using the solvent extraction process are presented in this case. The entrepreneurs faced the pricing dilemma at the inception of the business, as oil produced using the natural cold pressing method cost three times the selling pricing of solvent-extracted oil. Innovative methods of experiential marketing such as Ghana tourism are explained in this case. This case study also explains the sustainable and natural farming techniques propagated through its network of farmers. This case study provides insights into the scalability of this model and the scope for employment generation in rural India. The environmentally friendly practices followed by Desiri, such as the use of glass bottles and reusable steel containers for packaging oil are emphasized. Finally, this case presents the marketing and operational challenges faced by entrepreneurs in their quest to expand their operations. Complexity academic level: This case study can be used by postgraduate and undergraduate students studying marketing, entrepreneurship, sustainability and operations management courses in commerce and business management streams. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS8: Marketing.  2024, Emerald Publishing Limited.</text>
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                <text>Saldanha A., Department of Marketing, St. Josephs Institute of Management, Bangalore, India; Veigas O., Department of General Management, St. Josephs Institute of Management, Bangalore, India; Aranha R., School of Business and Management, Christ University, Bangalore, India</text>
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                <text>This article discusses the marketing missteps made by a prestigious B-school, exploring key concepts such as improper positioning and the imperative for repositioning. It provides an in-depth analysis of the decline in admissions at this well-established institution, culminating in a crisis. Additionally, the article explores a range of strategies available to the B-schools founder and top management team to enhance the institutions visibility and bolster its brand. Furthermore, it sheds light on the challenges the B-school faces, including inadequate infrastructure and other weaknesses, such as subpar research output, moderate placement offers and a low ranking in national B-school surveys. The case meticulously examines the errors made by the B-schools leadership team, such as discontinuing advertising and the ill-advised decision to withdraw from B-school surveys. Ultimately, this article epitomizes the predicament faced by an institution that relied on its historical strengths and failed to adapt to the evolving demands of its environment. It concludes by presenting short-term and long-term strategies available to decision-makers for crisis mitigation. It highlights digital marketing as one of the short-term solutions earnestly considered by the B-schools management to enhance brand awareness among its target audience.  2024 Lahore University of Management Sciences.</text>
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                <text>Asian Journal of Management Cases</text>
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                <text>&lt;a href="https://doi.org/10.1177/09728201231215965" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1177/09728201231215965&lt;/a&gt;
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                <text>Saldanha A.T., St Josephs Institute of Management, Karnataka, Bangalore, India; Aranha R., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bangalore, India</text>
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