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A closer look at industry-associated value premium: evidence from India
This paper examines whether the academic literature-promised value premium has any industry association in the Indian equity market and the relationship between stock returns, value, and size within and across industries. We examine all listed firms trading at BSE India between 1999-2020, using CAPM and Fama-French three-factor models on each firm-levels and industry-level portfolio. The positive and significant value effect was found to exist in 17 out of 21 industry groups. Both industry and firm-level value effects are identified; however, the firm-level effect seems more prominent. Furthermore, the value effect is most substantial in small-cap value stocks of value- and growth-oriented industries, large-cap value stocks of value-oriented industry groups, then small-cap growth stocks of value- and growth-oriented industries and large-cap growth stocks of value- and growth-oriented industries. We also show evidence confirming the claim that value premium results from investors challenging higher returns from firms and industries operating in higher risk and distressing constraints. Copyright 2022 Inderscience Enterprises Ltd. -
A Cognitive Architecture Based Conversation Agent Technology for Secure Communication
This paper outlines a multi-agent system-based approach to provider selection. Suppliers in the supply chain are different and the demand and supply levels are high. Buy agents will find the right supply agent in our approach. First, the multi-layer classification system is used to rationally arrange and overall selection on suppliers and buyers. Secondly, the purchase information is organized by the supplier agent to improve device performance. The assessment process is then used to select the suppliers initially. In addition to selecting the correct provider and maximizing the value of the purchaser, the time negotiating mechanism is implemented. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
A Cognitive Similarity-Based Measure to Enhance the Performance of Collaborative Filtering-Based Recommendation System
Advances in technology and high Internet penetration are leading to a large number of businesses going online. As a result, there is a substantial increase in the number of customers making online purchases and the number of items available online. However, with so many options available to choose from, users have to face the information overload problem. Several techniques have been developed to handle this, but the performance of the recommendation system (RS) has been recorded unprecedentedly. The collaborative filtering (CF) of RS is the most prevalent technique, which suggests personalized items to users based on their past preferences. The efficacy of this technique mainly depends on the similarity calculation, which the traditional or cognitive approach can ascertain. In the traditional approach, a similarity measure utilizes the user's ratings on an item to compute the similarity. Most similarity measures in this approach suffer from either data sparsity and/or cold-start problems. To address both of them, a new similarity measure based on the Jaccard and Gower coefficients, the efficient Gowers-Jaccard-Sigmoid Measure (EGJSM), is proposed in this article. It also includes a nonlinear sigmoid function to penalize the bad ratings. The performance of EGJSM is evaluated by conducting experiments on benchmark datasets, and the results depict that the proposed technique outperforms several existing methods. Along with this, a cognitive similarity (CgS) measure has been proposed, which considers cognitive features such as genre and year of release along with rating information, to calculate similarity. The CgS method also outperforms the proposed EGJSM method and produces almost 4% and 1% lower mean absolute error (MAE) and root-mean-squared error (RMSE) values than that. 2014 IEEE. -
A collaborative application of design thinking and Taguchi approach in restaurant service design for food wellbeing
Purpose: Innovative restaurant service designs impart food wellbeing to diners. This research comprehends customer aspirations and concerns in a restaurant-dining experience to develop a service design that enhances the dining experience using the design thinking approach and evaluates its efficiency using the Taguchi method of robust design. Design/methodology/approach: The sequential incidence technique defines diners' needs, which, followed by brainstorming sessions, helped create multiple service designs with important attributes. Prototype narration, as a scenario, acted as the stimulus for evaluators to respond to the WHO-5 wellbeing index scale. Scenario-based Taguchi experiment with nine foodservice attributes in two levels and the wellbeing score as the response variable helped identify levels of critical factors that develop better FWB. Findings: The study identified the best combination of factors and their preferred levels to maximize FWB in a restaurant. Food serving hygiene, followed by information about cuisine specification, and food movement in the restaurant, were important to FWB. The experiment revealed that hygiene perceptions are critical to FWB, and service designs have a significant role in it. Consumers prefer detailed information about the ingredients and recipe of the food they eat; being confident that there will be no unacceptable ingredients added to the food inspires their FWB. Research limitations/implications: Theoretically, this study contributes to the growing body of literature on design thinking and transformative service research, especially in the food industry. Practical implications: This paper details a simple method to identify and evaluate important factors that optimize FWB in a restaurant. The proposed methodology will help service designers and technology experts devise settings that consider customer priorities and contribute to their experience. Originality/value: This study helps to understand the application of design thinking and the Taguchi approach for creating robust service designs that optimize FWB. 2021, Emerald Publishing Limited. -
A collaborative defense protocol against collaborative attacks in wireless mesh networks
Wireless mesh network is an evolving next generation multi-hop broadband wireless technology. Collaborative attacks are more severe at the transport layer of such networks where the transmission control protocol's three-way handshake process is affected with the intention to bring the network down by denying its services. In this paper, we propose a novel collaborative defense protocol (CDP) which uses a handshake-based verification process and a collaborative flood detection and reaction process to effectively carry out the defense. This protocol presents a group of monitors that collaboratively entail in defending the attack; thus reduces the burden on a single monitor. Moreover, this paper proposes a novel transport layer post-connection flooding attack that occurs after establishing a TCP connection and we show that CDP can detect and mitigate this attack. The CDP protocol has been implemented in Java and its performance has been evaluated using essential metrics. We show that CDP is efficient and reliable and it can identify the attack before any major damage has occurred. Copyright 2021 Inderscience Enterprises Ltd. -
A colorimetric chemosensor for distinct color change with (E)-2-(1-(3-aminophenyl)ethylideneamino)benzenethiol to detect Cu2+ in real water samples
The study reports the synthesis of chemosensor (E)-2-(1-(3-aminophenyl)ethylideneamino)benzenethiol (C1), a highly sensitive, colorimetric metal probe that shows distinct selectivity for the detection of Cu2+ ion in various real water samples. Upon complexation with Cu2+ in CH3OH/H2O (60:40 v/v) (aqueous methanol), the C1 demonstrate significant enhancement in the absorption at 250nm and 300nm with a color change from light yellow to brown which was visualized using naked-eye. Therefore, these properties make C1 as an effective candidate for on-site Cu2+ ions detection. The emission spectrum of C1 illustrated TURN-ON recognition of Cu2+ with a limit of detection (LOD) of 46nM. Furthermore, Density Functional Theory (DFT) calculations were performed to better understand the interactions between C1 and Cu2+. The obtained results suggested that the electron clouds present around the NH2 innitrogen and sulfur in SH play a pivotal role in the formation of a stable complex. The computational results were in good agreement with the experimental UVvisible spectrometry results. Graphical abstract: [Figure not available: see fulltext.] 2023, The Author(s), under exclusive licence to The Japan Society for Analytical Chemistry. -
A common law in space for public health
Beyond the gravitational pull of Earth, space travel poses substantial public health hazards pertaining to the physical and mental well-being of astronauts and passengers, in addition to a possible threat to the populace of Earth upon re-entry. Exposure to cosmic radiation, cranial pressure from microgravity, weakened immunity to contagion, and the potential for depression and psychosis are all risks. Public health crises of this nature are to be expected as the duration of missions extends, as is the case with Mars settlement. In contrast to national space programmes, which have regarded these obstacles as human factors effecting the mission, public health law in common law British nations approaches them from the perspective of social justice and the preservation of human life and societal welfare. Countries including Australia, Canada, the United States, and the United Kingdom continue to apply traditional common law principles of public health law, which provide a sensible and enduring method for reconciling competing public and private interests. Common law permits the violation of civil liberties through the use of force in public health restraint, forced medication, and quarantine, but only if necessary, reasonable, and equitable. While the understanding of the health challenges associated with long-duration spaceflight may be in its infancy for national space programmes and civilian space ventures, the application of common law public health principles could aid in the establishment of health and safety protocols in which human reactions to crises in space resemble those observed on Earth. This may, nevertheless, necessitate the enactment of a more comprehensive federal public health statute. Embedded in both public health common law and international space law, the pre-eminence of preserving and respecting human life and well-being continues to be a cornerstone of humane justice despite the perilous conditions of space. 2024 IAA -
A Compact Super Wideband Antenna with Controllable Dual Notch Band Capability
In this paper, a novel super wideband (SWB) antenna with dual band notch capability is designed and analyzed for wide band applications. The proposed antenna consists of a pentagonal shaped radiator, beveled-shaped partial ground plane with slot and U-shaped parasitic strips. The beveled-shaped defected ground structure with rectangular slot helps to realize wideband characteristics from 2.4 to 28.2 GHz. Independent control of the notch band's center frequency and bandwidth is achieved by using U-shaped parasitic strips. This key feature is achieved in the WiMAX (3.3 to 3.7 GHz) and WLAN (5.1 to 5.9 GHz) bands. Furthermore, it exhibits a stable radiation pattern and offers acceptable gain over the entire operating bandwidth with sharp decrease in gain at the notches. The percentage bandwidth of 169% is achieved with a bandwidth dimension ratio (BDR) of 6986. Group delay is less than 1 ns in the entire operating bandwidth except at the notch bands. The measured reflection and radiation characteristics of fabricated SWB antenna are in good agreement with the simulation results. The proposed antenna has the advantage of simple design and compact size with an overall dimension of 18 x 21 x 1.6 mm3. The performance of the proposed antenna is superior compared to reported antenna designs in terms of controllable sharp notches and size for the bandwidth achieved. 2022 IAMOT -
A Compact Workflow Model for Cloud Computing
Scheduling tasks in the cloud computing environment, particularly for data intensive applications is of great importance and interest. In this paper, we propose a new workflow model presented in a rigorous graph-Theoretic setting. In this new model, we would like to incorporate possible similarities between requisite files which are needed to complete the given set of tasks. We show that it is NP-Complete to compute the make span in this model even with oracle access to the cost of retrieving a file. 2015 IEEE. -
A Comparative Analysis of Autonomous Ledger Systems for Enhanced Blockchain Computing Applications
Due to its potential to completely transform a number of sectors thanks to its irreversible and decentralized ledger system, the use of blockchain technology has recently attracted a lot of interest. Blockchain-based systems still face considerable issues with regard to scalability and effectiveness. This study compares autonomous ledger systems and examines how they are used in blockchain technology computation. With their capacity for self-management and resource allocation optimization, autonomous ledger systems provide intriguing answers to these problems. As examples of autonomous ledger systems, we look at self-care networks, adaptable consensus techniques, and autonomous government systems. We compare them and assess how well they function to improve the speed, security, and scalability of blockchain networks. We also examine the real-world uses of these independent ledger systems in industries including logistics management, banking, and medical services. With the goal of advancing blockchain computing and enabling more reliable and effective decentralized applications, this study intends to shed light on the possibilities of autonomous ledger systems. 2023 IEEE. -
A Comparative Analysis of Biodiesel Properties Derived from Meat Stall Wastes through Optimized Parameters
Biodiesel is considered as alternative green fuels that can be used in Internal Combustion engines as a replacement fuel for conventional diesel. Biodiesel is extracted from vegetable and animal sources which are rich in triglycerides. In this work, an attempt has been made to obtain and characterize the biodiesel from animal wastes such as chicken skin and pig tallow which are available in abundance and at an economical cost within the authors' geographical location. Initially, the feedstock is decontaminated and subjected to conventional heating to convert it into fatty oil. Heating is carried out at different temperatures and for varying time to find out the optimal combination of time and temperature, which would result in maximum fat yield. The fatty oil is then subjected to the trans-esterification process with methyl alcohol in the presence of a catalyst to extract crude biodiesel. A de-canter funnel is used to separate the glycerine and biodiesel from the crude extract. The extracted biodiesel is mixed in different volume percentages with conventional diesel, and various thermochemical properties were evaluated as per ASTM standards. The test result indicated that the properties of the biodiesel blends were well within the limits as prescribed by ASTM standards. Published under licence by IOP Publishing Ltd. -
A COMPARATIVE ANALYSIS OF CHEVROLET PRINT ADVERTISEMENTS FROM 1960S TO 2000S
The appeal of print advertisements have always been said to have both short term and long term effect and the advertisements that feature the much needed product in a clear and appealing manner deserve to stay in the minds of the readers. Talking about the print advertisements of vintage cars and the present day advertisements of cars of the same brands, there has been a change or so as to say a vast modification from what we had in the past and what we have now. The cars of Chevrolet over the years have developed in terms of features, style and power and variety of cars have been remodelled and made more presentable according to the needs and requirements of that particular generation hence making few vehicles of Chevrolet available for the third generation as well. The study would examine the different features used in print advertising by the Chevrolet car manufacturing company (a brand that goes back to the 1950s and 1960s) to woo its potential customers. -
A Comparative Analysis of Competition Law Regimes with the Increase of E-Commerce in India and U.S.A
The growth in analytics and cloud technologies has provided an interface where it is more interactive and approachable for the consumer to decide about purchases and varieties. The authors in this paper will be addressing the existence of anti-competitive practices in India, US and provide a comparative study of the enforceability of Competition laws in these countries respectively. India is primarily considered as one of the lucrative markets with highest usage of mobile phones and data and growing demand for the same, the new entrants in the market are finding it difficult with the anti-competitive aspects for instance unfair practices by gate keepers. The authors will research on the need to promote economic growth post pandemic and the necessary steps to be incorporated in such promotions so as to increase the demand and supply but at the same time maintain the competition. The Electrochemical Society -
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A comparative analysis of KFC video advertisements and the impact on its customers of Bengaluru /
In India, today fast food being one of the most successful businesses and also all over the world because of the economic development, increase in per capita income, people having less time to cook, people having no time to wait in restaurants and people are ready to spend. One popular fast food chain in India is KFC and one of the tools of KFC to reach its customers is through visual advertisements. -
A Comparative Analysis of LSB & DCT Based Steganographic Techniques: Confidentiality, Contemporary State, and Future Challenges
In order to maintain anonymity and security, the steganography is the technique of cloaking confidential data within what seems like harmless digital material. Several steganographic methods have been established devised over time, but those centered around the discrete cosine transformation (DCT) and the least significant bit (LSB) have drawn the most consideration. In this study, two common steganographic methods are compared and contrasted with an emphasis on the secrecy they can keep, the usage they are now receiving, and any potential difficulties in the future. As an alternative, the DCT-based method uses the frequency domain properties of cover media to obfuscate hidden information. Since it spreads the concealed information across several frequency coefficients, it provides greater security than LSB-based techniques. The resilience and imperceptibility of the concealed data are improved by a variety of DCT-based algorithms, such as the modified quantization and matrix encoding approaches, which we explore in detail. We also give a general summary of both approaches'current state in terms of their application, constraints, and areas in which they may be used. We evaluate the benefits and drawbacks of each approach, considering elements like payload size, computing difficulty, and detection resistance. 2023 IEEE. -
A Comparative Analysis of Machine Learning Algorithms for Image Classification: Evaluating Performance
Image classification plays a crucial role in various applications, and selecting the most effective machine learning algorithm is essential for achieving accurate results. In this study, we conducted a comparative analysis of several well-known supervised machine learning techniques, including logistic regression, support vector machine (SVM), k-nearest neighbours (kNN), nae Bayes, decision trees, random forest, AdaBoost, and artificial neural networks (ANN). To assess the performance of these algorithms, we utilised different fonts of the English alphabet as our dataset and performed the analysis using the R programming language. We evaluated the algorithms based on standard performance criteria, such as the area under the Receiver Operating Characteristic curve (ROC), accuracy, F1 score, precision, and recall. Our research findings demonstrated that the classification performance varied depending on the training size of the dataset. Notably, as the training size increased, neural networks exhibited superior performance compared to other machine learning techniques. Consequently, we conclude that neural networks and SVM are the most effective algorithms for image classification based on our study. By conducting this comprehensive analysis, we contribute valuable insights into selecting appropriate machine learning algorithms for image classification tasks. Our findings emphasise the significance of considering the training dataset size and highlight the advantages of neural networks and SVM in achieving high classification accuracy. This study provides valuable guidance for practitioners and researchers in choosing the most suitable machine learning algorithm for image classification, considering their specific requirements and dataset characteristics. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
A comparative analysis of opinions and sentiments on clean India campaign and sustainability goals of 2030
Human are blessed with natural intelligence. Artificial Intelligence can help human minds to make a best usage of machines to handle huge amount of data with accuracy and precision. AI has a widespread application in 21st century. Opinion mining is an application of artificial intelligence. The opinions expressed in social media can be extracted using python which can be used as an input for various machine learning algorithms to identify many patterns which can help policy makers to make effective policies. Clean India Campaign started in India with a set of goals to be achieved. Sustainability goals of 2030 given by United Nations puts light on many important aspects which need immediate attention in the next 9 years. Current pandemic Covid-19 has also triggered the necessity behind putting immediate attention for a better tomorrow. Without proper awareness programs, brainstorming knowledge cultivation, orienting minds towards the "what-why-where"aspects of sustainable growth in each sphere of life, aligning industrial development and digital era towards sustainable industrial development in digital era, sustainable economy, sustainable care of each natural resource; it is not easy to accomplish the sustainability goals of 2030 given by United Nations.This work emphasizes on the case study conducted as an initiative to motivate future policy makers to be aware of the different dimension of 2030 United Nations Agenda and the clean India campaign to take initiatives as a professional through the skills learned focusing on India. Realizing Individual social Responsibility can make a big difference in the planning and implementation of the goals and missions. Swachch Bharat Abhiyan (Clean India Campaign) started Swachch Bharat Mission-Urban (SBM-U) with a few objectives to make India Clean.This work has proposed two phases for analyzing opinions. This research have provided a methodology to apply AI to improve the opinion mining. The conventional opinion analysis is limited by reachability but the automated opinion analysis can be scaled up using artificial intelligence based applications. The uniqueness of the work lies in its focus on 'one-three verticals' in phase 1 of the methodology. Many prominent regions of India are considered as a part of the study. It helps us to provide a clearer picture across different regions of India. It also provide an avenue to list tasks to be done for each region and a set of ways which could be adopted by the future professionals and current stakeholders of higher education institute. Phase 2 focusses on more number of opinions collected from across the globe through digital platforms. 2021 Author(s). -
A COMPARATIVE ANALYSIS OF PRINT ADVERTISEMENTS OF THE YEARS 1990 AND 2000
This content analysis of a sample of advertisements of 20 print copies of various Indian products during the 1990s and 2000 examined the impact of the national economic conditions on advertising and its effect on 4 major aspects- text, visuals, typeface and layout. This study suggests that the impact of national economic conditions and the prevailing culture in the 1990s and 2000 on the use of advertisement elements in the different FMCG (Fast Moving Consumer Goods) product advertisements seemed visible. Advertising is part of the changing social, economic, and cultural environment, and its visuals might have been created in a way that could reflect those changes that people would want to adjust themselves to. Another way of linking advertising and its visuals to society and culture is the cultural approach to advertising. Cultural historians argue that advertising is an important window through which different aspects of society and culture can be explained. But also, the advertising itself can be explained to determine how it might have been shaped by society. While identifying the purpose of this study, more knowledge about the evolution in print advertisements is acquired. The research has given a better idea in recognizing the past advertisements which were during the beginning of the Globalization period and has compare it with print advertisements of the year 2000. -
A Comparative Analysis of Sentiment Analysis Using RNN-LSTM and Logistic Regression
Social media analytics makes a big difference in the success or failure of an organization. The data gathered from social media can be used to get a hit type product by analyzing the data and getting important information about the need of the people. This can be done by implementing sentiment analysis on the available data and then accessing the feelings of the customers about the product or service and knowing if it is actually being liked by them or not. Tracking data of the customers helps the organization in many ways. This study was done to get familiarized with the concept of data analytics and how social media plays an important role in it. Furthermore, Web scraping of Twitter and YouTube data was done following which a standard dataset was selected to do the other analytics. The field of sentiment analysis was used to get the emotions of the people. Logistic regression and RNN-LSTM models were used to perform the same, and then, the results were compared. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.