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Comprehensive Study on Sentiment Analysis: Types, Approaches, Recent Applications, Tools and APIs
Sentiment analysis can be considered a major application of machine learning, more particularly natural language processing (NLP). As there are varieties of applications, Sentiment analysis has gained a lot of attention and is one among the fastest growing research area in computer science. It is a type of data analysis which is observed from news reports, user reviews, feedbacks, social media updates etc. Responses are collected and analyzed by researchers. All sentiments can be classified into three categories-Positive, Negative and Neutral. The paper gives a detailed study of sentiment analysis. It explains the basics of sentiment analysis, its types, and different approaches of sentiment analysis. The recent tools and APIs along with various real world applications of sentiment analysis in various areas are also described briefly. 2020 IEEE. -
An Image Quality Selection and Effective Denoising on Retinal Images Using Hybrid Approaches
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. -
Eye-Vision Net: Cataract Detection and Classification in Retinal and Slit Lamp Images using Deep Network
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. -
A Comprehensive Study on Computer-Aided Cataract Detection, Classification, and Management Using Artificial Intelligence
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. -
Certificate Generation and Validation Using Blockchain
Verifying academic credentials is a standard procedure for employers when making job offers. After the interview procedure is complete, the employer takes a long time to supply the offer letter. The employer must have the certificate authenticated by the organization that issued it to confirm its originality. While confirming the authenticity of a certificate, the employer takes a long time. The selection procedure takes longer overall because of the long process involved in certificate verification. Blockchain offers a verified distributed ledger with a cryptography technique to combat academic certificate forgery to address this issue. The blockchain also offers a standard platform for document storage, access, and minimization of verification time. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Di-cationic ionic liquid catalyzed synthesis of 1,5-benzothiazepines
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. -
Exploration of the effects of anisotropy and rotation on RayleighBard convection of nanoliquid-saturated porous medium using general boundary conditions
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 & Francis Group. -
Predicting the Stock Markets Using Neural Network with Auxiliary Input
Predicting the stock market has always been a challenging task and has always had a certain appeal for researchers all around the world. Stock markets are supposed to be quite random and people with experience in the market strongly agree to the fact. Thus, predicting the stock market accurately paves the way for endless money. To date, no such algorithm has been devised that could even predict the stock market with a 90% accuracy rate. The difficulty lies in the randomness of the markets, and the various complexities involved in modeling market dynamics. Nevertheless, there have been algorithms with a decent success rate and researchers around the world have been in a constant attempt to improve over them. Thus, through this paper we attempt at predicting the return of a stock over a period of 10days after a particular news was out regarding the stock using the headlines of the news and certain other features important in determining the direction of a stock. The model was implemented with a sigma score of 0.81. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Malicious Botnet Traffic Detection Using Machine Learning
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. -
AI Healthcare Industry in Life Science Industry: A Perspective View
The main goal of this study is to look at how well the innovation system for AI healthcare technology is working in the life science business and find things that are getting in the way of progress. A lot of different types of research were used for this study. It combines both quantitative and qualitative data from tertiary studies, business-related written sources, and conversations with 21 experts and 25 life science management leaders to get new ideas. The results make it clear that innovation system performance is being held back by a lack of resources and poor communication from top healthcare experts about what they need to improve healthcare with AI technology innovations. The study says that to deal with these problems, policymakers need to make changes that increase the resources that are available and come up with clear goals and visions for how AI technology can improve healthcare. Using the socio-technical technological advancement System (TIS) approach in the healthcare setting, the study adds to our knowledge of how the innovation system works and how different parts of it affect each other. Overall, this study throws light on the complicated ways that innovation works in the life science field. It gives lawmakers, industry workers, and other interested parties useful information for pushing AI healthcare technology forward in a sociotechnical framework. 2024 IEEE. -
Enhancing Transparency and Trust in Agrifood Supply Chains through Novel Blockchain-based Architecture
At present, the world is witnessing a rapid change in all the fields of human civilization business interests and goals of all the sectors are changing very fast. Global changes are taking place quickly in all fields manufacturing, service, agriculture, and external sectors. There are plenty of hurdles in the emerging technologies in agriculture in the modern days. While adopting such technologies as transparency and trust issues among stakeholders, there arises a pressurized necessity on food suppliers because it has to create sustainable systems not only addressing demandsupply disparities but also ensuring food authenticity. Recent studies have attempted to explore the potential of technologies like blockchain and practices for smart and sustainable agriculture. Besides, this well-researched work investigates how a scientific cum technological blockchain architecture addresses supply chain challenges in Precision Agriculture to take up challenges related to transparency traceability, and security. A robust registration phase, efficient authentication mechanisms, and optimized data management strategies are the key components of the proposed architecture. Through secured key exchange mechanisms and encryption techniques, client's identities are verified with inevitable complexity. The confluence of IoT and blockchain technologies that set up modern farms amplify control within supply chain networks. The practical manifestation of the researchers' novel blockchain architecture that has been executed on the Hyperledger network, exposes a clear validation using corroboration of concept. Through exhaustive experimental analyses that encompass, transaction confirmation time and scalability metrics, the proposed architecture not only demonstrates efficiency but also underscores its usability to meet the demands of contemporary Precision Agriculture systems. However, the scholarly paper based upon a comprehensive overview resolves a solution as a fruitful and impactful contribution to blockchain applications in agriculture supply chains. Copyright 2024 KSII. -
Mass layoffs at BYJUS founders dilemma
Learning outcomes: This case study provides students/managers an opportunity to learn about the following: to infer the challenges involved in the downsizing of employees; to asses and evaluate BYJUS organizational culture; and to determine the impact of workplace toxicity. Case overview/synopsis: The focus of this case is the controversy faced by BYJUS due to its mass layoffs and toxic work culture. This case discusses the CEOs dilemma in resolving the controversy. Two rounds of mass layoffs at BYJUS are discussed in detail. The industrial dispute filed by Employees Union against BYJUS accusing it of denying due compensation to laid-off employees is also discussed. This case consists of a section explaining the toxic work culture at BYJUS, which is supported by employee complaints. The CEOs justification and apology have been illustrated in this case. The case ends with a closing dilemma and challenges faced by the CEO. Complexity academic level: The case is best suited for undergraduate students studying Human Resources Management subjects in Commerce and Business Management streams. The authors suggest that the instructor inform students to read the case before attending the 90-min session. It can be executed in the classroom after discussing the theoretical concepts. Supplementary material: Teaching notes are available for educators only. Subject code: CSS 6: Human Resource Management. 2024, Emerald Publishing Limited. -
Coca-Cola product placement strategy backfires a case of celebrity activism
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. -
Pricing and content Netflixs dilemma in India
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. -
Good-looking step in bad direction RBI Internal Working Group proposal
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. -
Zomato Instant - "10-Minute Delivery Plan" Controversy
[No abstract available] -
Zomatos dilemma a case of disgruntled delivery partners at Zomato
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. -
Desiri Naturals: sustainable agriculture and eco-friendly business
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. -
Crisis Faced by a B-School
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. -
Influence of Consumers Self Perception on Devaluation of Ugly Produce Marketing Strategies to Reduce Food Waste in the Indian Context
Ugly produce refers to aesthetically imperfect fruits and vegetables and also fruits and vegetables with minor blemishes. Ugly produce does not refer to spoilt, rotten, or germ-infected fruits and vegetables. The basic premise of this study is from self-signaling and self-perception theories. The self-signaling theory states that when people make a choice, they disclose something of their character and personality not just to others, but also to themselves. Self-perception theory (SPT) developed by psychologist Daryl Bem asserts that people develop their attitudes by observing their own behavior and further concluding what attitudes must have caused it. Classically, consumers undervalue ugly produce because of altered self-perceptions; simply visualizing the consumption of imperfect produce acts as a self-indicative signal that negatively affects how consumers view themselves. Due to this, the unattractive produce, even though perfectly edible and with the same taste and nutritional value, is rejected by consumers merely based on shape or some other cosmetic blemish. We discussed the strategies adopted by Indian startups and organizations to reduce food waste. Deep discounting is the strategy followed by food retailers worldwide to sell ugly produce, however, this is not the best strategy as it leads to losses for both the retailers as well as the farmers. We suggested alternative strategies successfully followed by foreign retailers, such as spreading awareness, boosting self-confidence and esteem among consumers, attracting kids, etc., which can be followed by Indian food retailers for selling ugly fruits and vegetables. 2022, Associated Management Consultants Pvt. Ltd.. All rights reserved.