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Cyber security laws in civil aviation in India: A critical analysis /
Cybersecurity in civil aviation is becoming increasingly critical as the aviation industry in India continues to grow and evolve. With the increasing use of technology and automation in aviation, there is a growing risk of cyber threats that can affect the safety and security of civil aviation operations. This paper provides a critical analysis of the current state of cybersecurity in civil aviation in India. It examines the various cyber threats facing the aviation industry, the legal and regulatory framework for cybersecurity in India, and the measures that can be taken to enhance cybersecurity in civil aviation. The analysis highlights the need for a comprehensive and proactive approach to cybersecurity in civil aviation in India, including the implementation of robust cybersecurity policies and procedures, the adoption of international best practices, and the establishment of a dedicated cybersecurity framework for the aviation industry. -
Cyber secure man-in-the-middle attack intrusion detection using machine learning algorithms
The main objective of this chapter is to enhance security system in network communication by using machine learning algorithm. Cyber security network attack issues and possible machine learning solutions are also elaborated. The basic network communication component and working principle are also addressed. Cyber security and data analytics are two major pillars in modern technology. Data attackers try to attack network data in the name of man-in-the-middle attack. Machine learning algorithm is providing numerous solutions for this cyber-attack. Application of machine learning algorithm is also discussed in this chapter. The proposed method is to solve man-in-the-middle attack problem by using reinforcement machine learning algorithm. The reinforcement learning is to create virtual agent that should predict cyber-attack based on previous history. This proposed solution is to avoid future cyber middle man attack in network transmission. 2022 by IGI Global. All rights reserved. -
Cyber secure man-in-the- middle attack intrusion detection using machine learning algorithms
The main objective of this chapter is to enhance security system in network communication by using machine learning algorithm. Cyber security network attack issues and possible machine learning solutions are also elaborated. The basic network communication component and working principle are also addressed. Cyber security and data analytics are two major pillars in modern technology. Data attackers try to attack network data in the name of man-in-the-middle attack. Machine learning algorithm is providing numerous solutions for this cyber-attack. Application of machine learning algorithm is also discussed in this chapter. The proposed method is to solve man-in-the-middle attack problem by using reinforcement machine learning algorithm. The reinforcement learning is to create virtual agent that should predict cyber-attack based on previous history. This proposed solution is to avoid future cyber middle man attack in network transmission. 2020, IGI Global. -
Cyanogenic glycosides: A sustainable carbon and nitrogen source for developing resilient Janus reversible oxygen electrocatalysts for metal-air batteries
Most of the transition metal based heteroatom doped carbon electrocatalysts, utilizes the fossil fuel derived commercially available precursors as source of nitrogen and carbon which may question our environmental generosity. Herein, we have developed Ni-based efficient bifunctional electrocatalysts using apple seeds (that contains cyanogenic glycosides) as the precursor for nitrogen and carbon. With tuning the temperature, we were able to optimize the nitrogen doping up to ?3 at.%. The optimized electrocatalyst catalyses the oxygen reduction reaction (ORR) process with muted peroxide generation (for 0.7500.1 V the % HO2 ? generation ?3 - 2%), preferential 4e? reduction pathways (n ? 3.93 to 3.98 in 0.750.1 V range) and electron transfer via inner-sphere electron transfer mechanism which ensures the maximum utilization of instituted active centres owing to the direct interaction of reactant species. Alike to ORR, the superior oxygen evolution reaction (OER) performance with smaller Eonset, EJ=10, Tafel slope and enduring accelerated stability test advocates its potential as a bifunctional oxygen electrocatalyst. Moreover, smaller potential gap ?E (EJ10_OER - E1/2_ORR) of 0.845 V further warrants the energy efficient OER/ORR process. A porotype of Al-air battery system using our catalysts as oxygen electrode and chocolate wafer as anode material is well capable of powering the light emitting diodes. This study hopefully opens a new avenue to explore cyanogenic glycosides plants product to develop multifunctional electrocatalysts. 2019 Elsevier Ltd -
Cutting across the Durand: Water dispute between Pakistan and Afghanistan on river Kabul
All nations firmly believe in the absolute sovereignty over the waters flow in their areas and that only riparian states have any legal right, apart from an agreement, to use the water from the shared river. To address some of their water concerns, the co-riparian states compete to have more quantity of waters. Significantly, no water agreement exists between upper riparian Afghanistan and lower riparian Pakistan, despite sharing nine big and small rivers. The simmering water dispute between them on the River Kabul is rarely noted mainly because it is overshadowed by their political tensions, differences, and the dispute over the Durand Line. Using an analytical framework, this article examines three aspects of the River Kabul water dispute: its context, identifying the challenges that hinder a formalized bilateral agreement from being implemented, and its future. 2020 Policy Studies Organization -
Customized SEIR Mathematical Model to Predict the trends of Vaccination for Spread of COVID-19
The uncertainty in life plans, restrictions on physical classrooms, loss of jobs, large number of infections and deaths due to COVID-19 are some significant causes of concern for the public as well as Governments all over the globe. Moreover, the exponential increase in the number of infected people in a short time is responsible for the collapse of the health industry during the pandemic caused by COVID-19. The health experts recommended that the quick and early diagnosis followed by treatment of patients in isolation is a way to minimize its spread and save lives. The objective of this research is to propose a customized SEIR model to predict the trends of vaccination in the USA. The experimental results prove that the Moderna vaccine reports the efficacy of 93%, which is higher than the Pfizer and Johnson and Johnson vaccines. 2022 ACM. -
Customized mask region based convolutional neural networks for un-uniformed shape text detection and text recognition
In image scene, text contains high-level of important information that helps to analyze and consider the particular environment. In this paper, we adapt image mask and original identification of the mask region based convolutional neural networks (R-CNN) to allow recognition at 3 levels such as sequence, holistic and pixel-level semantics. Particularly, pixel and holistic level semantics can be utilized to recognize the texts and define the text shapes, respectively. Precisely, in mask and detection, we segment and recognize both character and word instances. Furthermore, we implement text detection through the outcome of instance segmentation on 2-D feature-space. Also, to tackle and identify the text issues of smaller and blurry texts, we consider text recognition by attention-based of optical character recognition (OCR) model with the mask R-CNN at sequential level. The OCR module is used to estimate character sequence through feature maps of the word instances in sequence to sequence. Finally, we proposed a fine-grained learning technique that trains a more accurate and robust model by learning models from the annotated datasets at the word level. Our proposed approach is evaluated on popular benchmark dataset ICDAR 2013 and ICDAR 2015. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Customers satisfaction towards online banking services of public sector banks
At present the banking industry around the world has been undergoing a rapid transformation. The deepening of information technology has facilitated better tracking and fulfillment of commitments, multiple delivery channels for online customers and faster resolution of issues. Customer satisfaction is important criteria for banks sustenance, now banks are offers online banking services according to the customer needs and requirements. This study analysed customers satisfactions towards online banking services of public sector banks in Tiruchirappalli district. It is understand from the present study that bank websites and technology platforms has to offer various knowledge features on financial services. To retain the existing customers, banks has to conduct regular surveys on the customer satisfaction. The results of the study shows that variables like prompt response, security and Website design and ease of use are top three factors affected customer satisfaction. IJSTR 2020. -
Customers response to online food delivery services during COVID-19 outbreak using binary logistic regression
This study aims to empirically measure the distinctive characteristics of customers who did and did not order food through Online Food Delivery services (OFDs) during the COVID-19 outbreak in India. Data are collected from 462 OFDs customers. Binary logistic regression is used to examine the respondents characteristics, such as age, patronage frequency before the lockdown, affective and instrumental beliefs, product involvement and the perceived threat, to examine the significant differences between the two categories of OFDs customers. The binary logistic regression concludes that respondents exhibiting high-perceived threat, less product involvement, less perceived benefit on OFDs and less frequency of online food orders are less likely to order food through OFDs. This study provides specific guidelines to create crisis management strategies. 2020 John Wiley & Sons Ltd -
Customer Segmentation in the Field of Marketing
The motive of this work is to classify and categorize customers depending on their familiar traits/characteristics so as to enable a company or a firm to adequately market their products to each category more attractively and competently. It is imperative for a firm to educate themselves with each and every detail about the customer, such as age group, sexuality, social class, purchase pattern etc as it paves way for customer segmentation. Businesses may utilize segmentation to make better use of their marketing resources, get a competitive advantage over competitors, and, most importantly, display a deeper understanding of their consumers' requirements and desires. Customer segmentation, when combined with customer targeting and positioning, creates the foundation for strategic marketing. A manager can find new marketing possibilities and create or adjust the product to satisfy the demands of potential clients using the notion of strategic marketing. The product's quality level determines its position in the market's overall offering. It's a crucial aspect in selecting which market segment a collection will target. The commercial world has gotten more competitive over time, as enterprises like these have to fulfil their consumers' demands and aspirations, attract new customers, and enhance their bottom lines. In this research, I have put the spotlight on the information used by firms for the purpose of customer segmentation in the most valuable manner. In addition to that, I have portrayed different models of customer segmentation and the benefits reaped by a business in implementing them. 2022 IEEE. -
Customer Segmentation and Future Purchase Prediction using RFM measures
Winning in the E-Commerce business race at a competitive age like this requires proper usage of Customer data. Using that database and grouping it in similar segments in terms of spending expenditure, observation time, sex, and location so that every customer falls in a segment of characteristics. This mechanism is called Customer Segmentation. In the modern era of highly compatible technological advancements, Machine Learning Algorithms are being vastly used to bring solutions to these difficult yet essential services. In the field of research methods like simple clustering based on purchase behaviour, buyer targeting or automated customer promotion mechanism by dividing into two major categories, have been worked on. However, ensemble algorithms have come handy where different clustering algorithms are combined to deliver best segmentation. Lately combination techniques like clustering and classification mechanism have also delivered good results where, not only segmentation is done but also classification of existing and new customers are possible into the clusters. Depending on that an effective customer relationship management can really benefit the company to a huge extent. Unlike other studies where clustering was performed directly on RFM table, a different approach was taken in this study where, one dimensional clustering was done individually on Recency, Frequency, Monetary columns, then an overall score was calculated and customers were classified into three segments. However, for a new customer depending on his purchase behaviour he/she also can be classified into any of the categories. 2022 IEEE. -
Customer relationship management system and method of taking feedback thereof /
Patent Number: 202241008325, Applicant: Dr. Rashmi Rai.
A customer relationship management system (1) and method of taking feedback thereof comprising a feedback button (2), a mobile application (2A), an electronic unit (4), a computer (5), a mobile (6), a network (7), a server (8), a database (9). The invention provides a feedback button may be a physical three-way button (2) or a three-way digital button. One of them is visible on mobile applications and the second one is visible in the room. -
Customer relationship management system and method of taking feedback thereof /
Patent Number: 202241008325, Applicant: Dr. Rashmi Rai.
A customer relationship management system (1) and method of taking feedback thereof comprising a feedback button (2), a mobile application (2A), an electronic unit (4), a computer (5), a mobile (6), a network (7), a server (8), a database (9). The invention provides a feedback button may be a physical three-way button (2) or a three-way digital button. One of them is visible on mobile applications and the second one is visible in the room. -
Customer relationship management system and method of taking feedback thereof /
Patent Number: 202241008325, Applicant: Dr. Rashmi Rai.
A customer relationship management system (1) and method of taking feedback thereof comprising a feedback button (2), a mobile application (2A), an electronic unit (4), a computer (5), a mobile (6), a network (7), a server (8), a database (9). The invention provides a feedback button may be a physical three-way button (2) or a three-way digital button. One of them is visible on mobile applications and the second one is visible in the room. -
Customer preferences to select a restaurant through smart phone applications: An exploratory study
The increasing number of Smart Phone Applications (SPA) user and fast growing restaurant industry proves the great potential of using SPA as business marketing opportunity in Malaysia. The constant growth in mobile technology has created a prospect for the restaurant industry to use SPA as a restaurant promotion tool. The growing attention of use of SPA among the Malaysian customer, marketing research remains understudied in the field of SPA based restaurant promotion activities. The aim of this study is to explore the increase in customer acceptance to use SPA based restaurant promotion and to identify the customer preference to use SPA to select the restaurant. Thus, this paper mainly focuses on restaurant information on product and promotion as antecedents of customer acceptance of smart phone apps by underpinning the Unified theory of acceptance and use of technology (UTAUT) model. A conceptual model and hypotheses are tested with a sample of 116 students from a private university at Selangor district, Malaysia. The findings indicate that there is a positive relationship to increase customer acceptance level through SPA based restaurant product information and also strong relationship with the restaurant promotion information. It also indicates that customer acceptance of SPA through experience and satisfaction has a positive significant effect on customer preference to select a restaurant. Based on the results, this paper rounds off with conclusion, recommendations for future marketing research and provides a new marketing strategy to formulate among the restaurant business sector. 2015 American Scientific Publishers. All rights reserved. -
Customer Perspective through Artificial Intelligence: Forecasting Green Products Sustainable Development
The idea of planned behavior was developed in 1980 as a philosophy of deliberate action to interpret human behavior. The primary element of this theory is an individuals purpose, which is impacted by the attitude of expecting that the behavior will result in the desired result. This theory has helped in determining certain characteristics of an individual that includes smoking, drinking, services, and so on. The theory states that the behaviors are achieved through motivation and control. These characteristics developed are completely voluntary which can sometimes help in the betterment and improvement in any field. The name of the theory itself gives us a clarity that it is a well-planned formation of behaviors different from his or her normative and preconceived beliefs and norms. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Customer perspective on a curated gift-box service: A study in Sikkim, India
Due to the proliferation of choices and brands, accessibility to information, and new communication mediums, consumer behavior, particularly decision-making processes, has been altered by the spending power of various segments. In the Indian environment, although product appearance has been identified as a significant factor in influencing customer behavior, its effect on decision making when combined with other factors such as cost, features, and intrinsic psychological factors has not been studied thoroughly. This study aims to highlight consumers' perspective on a curated gift-box service in Sikkim. Focusing on gifting during special occasions, impulse buying, and self-gift opportunities, this study stands on the possibility that there is a need for such service in the market. 2023, IGI Global. -
Customer Perception and Receptivity to Loyalty Programs offered by Organised Retailers
The Indian Retail Industry is growing at a fast pace. This growth to a large extent is driven by the organised retail market, with more and larger retail organisations investing heavily in increasing their store networks and improving in-store offerings. Apparel, accessories and related merchandise form a considerable chunk of the organised retail space and is in the ambit of a handful of established players vying to capture & increase larger portions of the available market using new strategies. Increased customer satisfaction and service is one of the means through which they will be able to fulfill their goals. The use and implementation of Customer Relation Management tools like Loyalty Programs is one of the ways in which they can achieve customer satisfaction. According to Sharp and Sharp (1997) loyalty programs are structured marketing efforts, which reward and encourage the loyal behaviour of their members. Capizzi et al (2004) defined it as the business process of identifying, maintaining and increasing the yield from best customers through interactive,value-added relationships.Loyalty programs are thereby are a rhetoric of relationship marketing in gaining customer loyalty.(Minami & Dawson ,2008) . Loyalty programs, however serve dual purposes of the organisation ?? acquisition of customer spending related information and ensuring that they patronise their store. According to Peters (1988) the costs of retaining customers are about 80 percent lower than acquiring new customers. This explains why there is a high degree of proliferation of retailer loyalty programs. Loyalty Programs today have become an inseparable part of the Customer Relationship Management (CRM) strategy of todays retailers. It is vital to gauge how successful these programs are as CRM tools. This study is concerned with how customers perceive such programs and how receptive they are towards these programs. The sample size consisted of 168 usable samples of member customers of loyalty programs of four competing departmental stores who were members of the stores. The study was confined to the city of Bangalore. Convenience sampling was used for the purpose of data collection. Data was collected through questionnaires and was subjected to descriptive analysis and inferential analysis. The reliability of the perceptual scale was found to be 0.766. The major findings of the research are: ? Lifestyle is the most frequented store and Shoppers Stop has the most attractive loyalty program. ? Customers have more important reasons for preference of a store than holding membership to the stores loyalty program ? Customers perceive that a loyalty program membership makes them enjoy monetary benefits. Offers and discounts followed by redeemable points are the most popular form of monetary benefits. ? Customers seek ??real and value creating benefits from loyalty programs ? There is a significant relationship between customer perception of loyalty program benefits and purchase behaviour. ? There is a significant relationship between customer perception of loyalty program benefits and store attractiveness and loyalty. The study will help retail organisations understand their customers better and help them in designing and implementing more satisfying, value creating and differentiated programs as a CRM tool to retain customers and build loyalty. -
Customer Lifetime Value Prediction: An In-Depth Exploration with Regression, Regularization and Hyperparameter Tuning
In today's dynamic business environment, companies have been strategically shifting towards a customer-centric approach from their traditional product-centric focus. The main goal of this paper is to estimate customer lifetime value of 5,000 customers in the retail industry. This research follows a step-by-step approach to construct a multiple regression machine learning model. The model used in the study is based on the nine features to predict the customer life time value. First basic train-test split model is developed, which predicted 74% of variation in the customer lifetime value. This necessitates to improve the model performance, hence to address the multicollinearity problem lasso regularization is used. After lasso regularization , final model is trained with hyperparameter turning for further model performance improvement. The results show significant improvements in predicting customer lifetime value with the final model. This study suggests that the machine learning regression models can help to businesses to better understand how much value they can generate from individual customer.This deep understanding about customers helps retail businesses to align their customer engagement strategies to create a positive impact on the profitability and maximizing overall value offered to the customers. 2024 IEEE. -
Customer Behavior Analysis Using Unsupervised Clustering and Profiling: A Machine Learning Approach
Now-a-days, client conduct models are reliably established on information mining of client information, and each model is supposed to answer one solicitation at one point on schedule. Anticipating client conduct is a problematic and irksome task. Thus, making client conduct models requires the right strategy and approach. Right when an estimate model has been fabricated, it is challenging to restrict it for the motivations driving the advertiser, to pick the very thing displaying moves to make for every client or for the party of clients. Notwithstanding the multifaceted nature of this arrangement, most client models are completely fundamental. As the need might arise, most client conduct investigation models ignore such endless proper factors that the gauges they make are overall not altogether strong. This paper plans to encourage a connection rule mining model to expect client conduct using a typical electronic retail store for data combination and concentrate critical examples from the client conduct data. In this undertaking, a solo grouping of information on the customer's records from a regular food item company's data set will be played out. Customer segmentation is the act of clustering customers into bunches that reflect likenesses among customers in each group. Customers are separated into sections to advance the meaning of every customer to the business. To change items as indicated by unmistakable requirements and practices of the customers. It additionally assists the business with obliging the worries of various kinds of customers. Customers were clustered using a technique known as agglomerative clustering, which is a type of hierarchical clustering. Agglomerative clustering is a method for clustering data in a hierarchical order. It entails merging cases until you reach the appropriate number of clusters. The number of clusters to be produced is determined using the Elbow Method. 2022 IEEE.