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Artificial Intelligence (AI) in CRM (Customer Relationship Management): A Sentiment Analysis Approach
The use of customer relationship management (CRM) in marketing is examined in this essay. It looks at how CRM makes it possible to use reviews, integrate AI, conduct marketing in real time, and conduct more regular marketing operations. CRM tactics are illustrated through case studies of businesses like Uber, T-Mobile, Amazon, Apple, and Apple. CRM offers centralized data, better marketing and sales, and better customer support. There is also a discussion of the ethical, private, security, adoption, and scalability challenges of AI in CRM. In general, CRM makes data-driven decisions and customer insights easier to achieve to increase growth, loyalty, and engagement. 2024 IEEE. -
We are Treated as Outsiders in Our Own City: Lived Experiences of Intersectional Stigma Against Sex Workers in Kolkata, India
Introduction: Sex workers in India experience intersectional stigma related to their gender identity, sexuality, and profession. The objective of the present study is to analyze the lived experiences of intersectional stigma against sex workers in Kolkata. Methods: We interviewed 30 cisgender female sex workers in March 2023 in Kolkata, India. Interviews were digitally audio recorded, translated from Bengali into English, and transcribed and coded using thematic analysis. Results: We identified five main themes regarding intersectional stigma: (1) internalized stigma regarding the shame associated with being a female sex worker, (2) perceived stigma of sex work as a dirty profession, associated with lower caste status, (3) enacted stigma against sex workers who are mothers, (4) enacted stigma against the children of sex workers, and (5) reduction of stigma through unionization/labor organizing. Conclusions: Intersectional stigma against sex workersis impacted by negative attitudes regarding gender, caste status, single motherhood, and occupation. We identified internalized stigma as a source of shame for sex workers. Sex workers also were perceived to beengaged in afilthy profession, associated with lower caste status. Those sex workers who were mothers experienced discrimination, as did their children. Respondents reported how collectivization has helped to address these experiences of stigma anddiscrimination. Policy Implications: Addressing the intersectional stigma against sex workers in Kolkata necessitates a shift in social attitudes.Findings underscore the urgent need for stigma reduction interventions and socialpolicies, including (1) labor protections for sex workers, (2) individual/community-level interventions for sex workers, and (3) media campaigns to address stigma reduction. By understanding the lived experiences of sex workers, we may develop better interventions to reduce stigma in the lives of sex workers in Kolkata and throughout India. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Design and development of a method for detecting sleep roll-over counts using accelerometer ADXL335
Sleep plays an important role as it helps human body to rejuvenate, boosts mental function and manage stress. Sleep is restorative function which enhances muscle growth, repairs tissues, maintains health and make physical appearance look or feel better. The lack of sleep in human body can increase the risk of diseases which are asthma, diabetes, depression. For healthy physiological function, sleep is essential and has strong relation to mental condition. Easy way of sleep management is considered for maintaining good mental health. Numerous scientists, doctors and researchers have proposed various ways to monitor sleep, some of those best tests are polysomnography test and actigraphy test. However, taking sleep test covering the whole body with wires and electrodes which is polysomnography test is uncomfortable for patients, and sensors used for different approaches like this are costly and often require overnight treatment and expert monitoring in clinics. Therefore, easy way of detecting roll-over movements which is convenient for patients to wear is proposed. Accelerometer ADXL335 sensor is taped on socks during sleep which is comfortable for patients to wear and do not cause any inconvenience during sleep. Algorithm is proposed to read the dataset and count the roll-over during the sleep based on threshold. Resulting the number of roll-over detected during a sleep period. Copyright 2020 Institute of Advanced Engineering and Science. All rights reserved. -
Characterization of product cordial dragon graphs
The vertices of a graph are to be labelled with 0 or 1 such that each edge gets the label as the product of its end vertices. If the number of vertices labelled with 0's and 1's differ by at most one and if the number of edges labelled with 0's and 1's differ by at most by one, then the labelling is called product cordial labelling. Complete characterizations of product cordial dragon graphs is given. We also characterize dragon graphs whose line graphs are product cordial. 2024 Azarbaijan Shahid Madani University. -
Parity labeling in Signed Graphs
Let S = (G; ?) be a signed graph where G = (V;E) is a graph called the underlying graph of S and ?: E(G) ? {+; -}. Let f: V(G) ? {1, 2, ..., |V(G)|} such that ?(uv) = + if f(u) and f(v) are of same parity and ?(uv) = - if f(u) and f(v) are of opposite parity. The bijection f induces a signed graph Gf denoted as S, which is a parity signed graph. In this paper, we initiate the study of parity labeling in signed graphs. We define and find `rna' number denoted as ?-(S) for some classes of signed graphs. We also characterize some signed graphs which are parity signed graphs. Some directions for further research are also suggested. 2021, Journal of Prime Research in Mathematics. All rights reserved. -
Characterizations of some parity signed graphs
We describe parity labellings of signed graphs: equivalently, cuts of the underlying graph that have nearly equal sides. We characterize the bal-anced signed graphs which are parity signed graphs. We give structural characterizations of all parity signed stars, bistars, cycles, paths and com-plete bipartite graphs. The rna number of a graph is the smallest cut size that has nearly equal sides; we find this for a few classes of graphs. The author(s). -
C-CORDIAL LABELING OF BIPARTITE SIGNED GRAPHS
Let ?:= (V, E) be a graph and ?:= (?, ?) be a signed graph with underling graph ?. Let : V (?) ?? {+, ?} be a C-marking. Then the function is called C-cordial labeling of signed graph ?, if |e? (?1) ?e? (1)| ? 1 and |v (?) ?v (+)| ? 1, where v (+) and v (?) are the number of vertices of ? having label + and ?, respectively under . In this paper, we have characterized signed cycles with given number of negative sections, which admit C-cordial labeling. We have also obtained a characterization of signed bistars which admit C-cordial labeling. 2021 Allahabad Mathematical Society. -
Navigating Financial Waters: Exploring the Intersection of Algorithmic Trading and Market Liquidity Dynamics
Algorithmic trading has ushered paradigm shift in trading. The market regulators although welcome this new technological advancement but are still keeping a tight leash. This can be owing to the contradicting and inconclusive evidence of its implications and impact on market microstructure. This study focuses on liquidity which is an integral part of a thriving stock market. We aim to examine if there is a statistical significance between volume of algorithmic orders and market capitalization. The liquidity provision is measured using Amihuds Illiquidity measure which is a proxy for measuring illiquidity. The liquidity measure is examined for chosen 8 stocks based on their market capitalization. The volume of algorithmic orders is examined using the Limit Order Book (LOB) data obtained from the BSE and orders for 23 trading days have been considered. We observe that large capitalization stocks display higher liquidity and algorithmic traders are able to contribute significantly to liquidity when compared to non-algorithmic traders. It was also looked at if there was a big difference in the amount of algorithmic trading done on stocks with big and small capitalization. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
We are Treated as Outsiders in Our Own City: Lived Experiences of Intersectional Stigma Against Sex Workers in Kolkata, India
Introduction: Sex workers in India experience intersectional stigma related to their gender identity, sexuality, and profession. The objective of the present study is to analyze the lived experiences of intersectional stigma against sex workers in Kolkata. Methods: We interviewed 30 cisgender female sex workers in March 2023 in Kolkata, India. Interviews were digitally audio recorded, translated from Bengali into English, and transcribed and coded using thematic analysis. Results: We identified five main themes regarding intersectional stigma: (1) internalized stigma regarding the shame associated with being a female sex worker, (2) perceived stigma of sex work as a dirty profession, associated with lower caste status, (3) enacted stigma against sex workers who are mothers, (4) enacted stigma against the children of sex workers, and (5) reduction of stigma through unionization/labor organizing. Conclusions: Intersectional stigma against sex workersis impacted by negative attitudes regarding gender, caste status, single motherhood, and occupation. We identified internalized stigma as a source of shame for sex workers. Sex workers also were perceived to beengaged in afilthy profession, associated with lower caste status. Those sex workers who were mothers experienced discrimination, as did their children. Respondents reported how collectivization has helped to address these experiences of stigma anddiscrimination. Policy Implications: Addressing the intersectional stigma against sex workers in Kolkata necessitates a shift in social attitudes.Findings underscore the urgent need for stigma reduction interventions and socialpolicies, including (1) labor protections for sex workers, (2) individual/community-level interventions for sex workers, and (3) media campaigns to address stigma reduction. By understanding the lived experiences of sex workers, we may develop better interventions to reduce stigma in the lives of sex workers in Kolkata and throughout India. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Algorithmic and Non-Algorithmic Trading Activity in the BSE Using Limit Order Book of Select Stocks
With the existence of a heterogeneous market compounded by asymmetric information, technology has become one of the major newlineenablers in stock market development. Introduction of algorithms for trading gave a fillip to many stock market participants and allowed them to trade rapidly and profitably. In the present day in Indian stock market, newlinewe have two types of market players; algorithmic traders and nonalgorithmic traders. The algorithmic traders are playing a dominant role in order placement, order modification and order execution while the newlinenon-algorithmic traders still continue to use their intuition. This study aims to understand the trading activity of both the market participants. The study uses the Limit Order Book data from Bombay Stock Exchange. newlineThe LOB data of selected nine stocks is considered for the study whose variables namely Order Added, Order Updated and Order Deleted data along with the Bid Ask Quotes are considered for measurement. Based on newlinethe Limit Orders it is observed that there is a statistically significant difference in the trading behavior of algorithmic and non-algorithmic traders based on stock market session timings and market capitalization. newlineThe market making ability of the algorithmic traders was examined using Order-to trade Ratio and it is observed that large number of orders are not executed indicating that there is no significant Market Making happening. newlineThe algorithmic traders possess an edge over the non-algorithmic traders in Order Modification resulting in dominance in the Stock market. The Mann Kendal Trend test indicates upward and downward trend in newlinevolume adjusted spread indicating that market making is happening especially in the stocks where algorithmic activity is high. This study enables regulatory authorities to monitor stock market activity especially during pre- open session. This study provides sufficient scope for further research on future of algorithmic trading activity and its ramifications on non-algorithmic trading activity in the future. -
Navigating Financial Waters: Exploring the Intersection of Algorithmic Trading and Market Liquidity Dynamics
Algorithmic trading has ushered paradigm shift in trading. The market regulators although welcome this new technological advancement but are still keeping a tight leash. This can be owing to the contradicting and inconclusive evidence of its implications and impact on market microstructure. This study focuses on liquidity which is an integral part of a thriving stock market. We aim to examine if there is a statistical significance between volume of algorithmic orders and market capitalization. The liquidity provision is measured using Amihuds Illiquidity measure which is a proxy for measuring illiquidity. The liquidity measure is examined for chosen 8 stocks based on their market capitalization. The volume of algorithmic orders is examined using the Limit Order Book (LOB) data obtained from the BSE and orders for 23 trading days have been considered. We observe that large capitalization stocks display higher liquidity and algorithmic traders are able to contribute significantly to liquidity when compared to non-algorithmic traders. It was also looked at if there was a big difference in the amount of algorithmic trading done on stocks with big and small capitalization. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Automatic Generation Control of Multi-area Multi-source Deregulated Power System Using Moth Flame Optimization Algorithm
In this paper, a novel nature motivated optimization technique known as moth flame optimization (MFO) technique is proposed for a multi-area interrelated power system with a deregulated state with multi-sources of generation. A three-area interrelated system with multi-sources in which the first area consists of the thermal and solar thermal unit; the second area consists of hydro and thermal units. The third area consists of gas and thermal units with AC/DC link. System performances with various power system transactions under deregulation are studied. The dynamic system executions are compared with diverse techniques like particle swarm optimization (PSO) and differential evolution (DE) technique under poolco transaction with/without AC/DC link. It is found that the MFO tuned proportional-integral-derivative (PID) controller superior to other methods considered. Further, the system is also studied with the addition of physical constraints. The present analysis reveals that the proposed technique appears to be a potential optimization algorithm for AGC study under a deregulation environment. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
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Valorisation of starfruit waste derived pectin for biodegradable sheet fabrication: A comprehensive study on extraction and characterization
This research work focuses on the extraction and characterization of pectin from starfruit peel and its application for fabrication of pectin film. Starfruit is chosen as the source for pectin extraction as the data regarding pectin extraction starfruit is relatively scarce in the available literature. Conventional organic acid based extraction using citric acid is employed for pectin extraction as it is eco-friendly and cost effective. The yield of pectin was found to be 8.22 1.018 (w/w). Fourier-transform infrared spectroscopy (FT-IR), analysis is used to identify functional groups present in the extracted pectin and X-ray Powder Diffraction (XRD) is done to check its crystallinity. Furthermore, scanning electron microscopy (SEM) characterization was performed to deduce the morphological characteristics of the extracted biopolymer. The particle size was found to be between 1m and 20 m. Fabrication of pectin based film was done using solvent cast method. The biodegradable film developed was found to be transparent and flexible. This work highlights the use of starfruit as a cost effective substrate for pectin extraction. Future studies should aim at exploring various applications of pectin and utilizing its potential in diverse applications. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). -
Food Recommendation System using Custom NER and Sentimental Analysis
In today's fast-paced lifestyle, the need for efficient and personalized solutions is paramount, especially in the category of dining experiences. This research responds to this demand by proposing a better food recommendation system for Zomato reviews. It targets the audience who are not aware of the best cuisines and search for user reviews online. Utilizing custom Named Entity Recognition (NER) and sentiment analysis, the system seeks to understand and cater to individual food preferences extracted from user Reviews. Specifically, improving the analysis by extracting reviews for ten restaurants in the city of Kolkata. By providing a specific solution to address the current research gap in the area of restaurants recommendation systems, the system recommends top choices for neighboring restaurants and best food based on the sentimental analysis of the chosen menu items. 2024 IEEE. -
Integrating Machine Learning with Financial Risk Modeling for Portfolio Management
Financial markets may be unpredictable and volatile; the ability to perform proper risk forecasting and effectiveness in performing an efficient portfolio is of primary importance when making wise investment choices. The nonlinear trends, and time dependence applied in financial data are usually not captured in conventional predictive models. The research is suggesting a new hybrid architecture LSTXplain that combines with and is afforded capabilities of SHAP, and exogenized with LSTM networks as well as Experimental learning. The aim of this paper, which is entitled Integrating Machine Learning with Financial Risk Modeling to Portfolio Management is to combine sequential learning with interpretability in an attempt to deepen financial risk prediction and portfolio optimization. The model is intended to forecast various measurements of financial risk, such as volatility and Value-at-Risk, and is also likely to establish the causes of each of these estimates. LSTXplain uses historical stock prices, technical features and optionally, sentiment scores designed using financial news to train a robust deep learner. Model outputs are then fed through SHAP that allocates a value of importance of a feature and discover that this allows analysts to know and trust what the model does. In order to compare the framework, Yahoo Finance data was applied, and the findings were compared to the traditional models ARIMA, SVM, Random Forest, and MLP. It has a prediction accuracy of over 98 percent which does not just complement the risk forecasting but enables a portfolio management to act. The analysis is a bridge between the performance of DL and explainable AI in the financial risk prediction. Statistical significance were applied to prove that such improvements are significant, and it is established that results are significant at p<0.05. 2025 IEEE. -
Reinforcement Learning for Language Grounding: Mapping Words to Actions in Human-Robot Interaction
Within the domain of human-robot communication, effective communication is paramount for seamless and smooth collaboration between humans and robots. A promising method for improving language grounding is reinforcement learning (RL), which enables robots to translate spoken commands into suitable behaviors. This paper presents a comprehensive review of recent advancements in RL techniques applied to the task of language grounding in human-robot interaction, focusing specifically on instruction following. Key challenges in this domain include the ambiguity of natural language, the complexity of action spaces, and the need for robust and interpretable models. Various RL algorithms and architectures tailored for language grounding tasks are discussed, highlighting their strengths and limitations. Furthermore, real-world applications and experimental results are examined, showcasing the effectiveness of RL-based approaches in enabling robots to understand and execute instructions from human users. Finally, promising directions for future research are identified, emphasizing the importance of addressing scalability, generalization, and adaptability in RL-based language grounding systems for human-robot interaction. 2024 IEEE. -
A Reverse Firewall & Re-Encryption Model Supported Peks Model for Security in Health Based Applications
Combining reverse firewalls and reencryption in a PEKS (Public Key Encryption with Keyword Search) model introduces a powerful way to mitigate malicious client behaviour and enhance privacy, especially in untrusted or semi-trusted environments. A reverse firewall is a client-side monitor or proxy that sits between a cryptographic application and the network. Its goal is to ensure that compromised software does not leak any information, even if the software is compromised. In this context a reverse firewall supported with Proxy re-encryption (PRE) supports a secured scheme for applications which require high level of security in public domain scenarios like Cloud for data sharing forms. For schemes which require good level of Identity applications and also needs the support of data Integrity, reverse firewall associated with Re encryption may be a suitable choice. The model is refined with conditional time stamp in accepting the keys for re encryption process. As this model can use different random numbers at different levels of Reverse firewall and re encryption, makes the work free from Chosen cipher text attacks. Also, the proposed model supports Design, Modelling and security analysis in a real time environment. 2025 IEEE. -
Enhancing authentication in blockchain bridges: A smart contract-based approach leveraging polynomial interpolation
This work focuses on the integration of blockchain for enhancing the security, privacy, and trust management within Vehicle Ad Hoc Networks (VANETs). In the context of smart transportation, VANETs offer essential safety but the open and dynamic nature of these networks makes secure, anonymous authentication a major challenge. Blockchain's decentralized nature can provide a secure, tamper- resistant ledger for managing data across the network nodes, helping address these security concerns. Cross- chain bridges enable the transfer of data, money and assets across blockchains. It has thus become important to enhance existing authentication mechanisms in blockchain bridges. In this research, we analyze existing authentication approaches, highlighting their limitations, such as reliance on centralized entities, private key leaks and weakness in smart contract functions. We then propose a novel approach to strengthen existing authentication mechanisms with the combined capabilities of Smart Contracts and Polynomial Interpolation, to establish a secure authentication layer. 2025, IGI Global Scientific Publishing. All rights reserved.