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Forecasting of Environmental Sustainability through Green Innovation of E-Vehicle Industry
E-mobility sustainability forecasting is getting more detailed with study, taking into account social cost in addition to technological, economic, or environmental factors. One solution for reducing greenhouse gas emissions is to implement green innovation in the transportation sector. The citizenrys view and acceptance of electric cars must be improved, more research into the social cost of these innovations is required. Consequently, the transportation industry might decarbonize more quickly. Another approach to do it is to advocate for more all-encompassing green innovations that can enhance sustainable development. Using Our Common Future, published in 1987 by the World Commission on Environment and Development [1], the commission emphasized the importance of sustainability while integrating social and economic development. Additionally, it recommended that governments take environmental factors into account while making decisions. The significance of sustainability was then increased and institutionalized, which meant that nations began passing laws that promoted sustainability. Consumer awareness of sustainability is rising largely from an economic and environmental standpoint. This also has an impact on the transportation industry and poses significant environmental, social, and economic difficulties. However, given that it generates close to 5% of the GDP and employs almost 11 million people, transportation is crucial from an economic standpoint. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Forecasting NIFTY 50 in Volatile Markets Using RNNLSTM: A Study on the Performance of Neural Network Models During the COVID-19 Pandemic
The COVID-19 pandemic has shown us how the market can be highly uncertain and volatile at certain times. This brings a new level of challenges to all the investors and active traders in the market, as they have not seen such a movement in the past. However, as technology is evolving, highly sophisticated tools and techniques are being used by hedge funds and other investment banks to track down these movements and turn this into an opportunity. In this paper, we try to analyse how recurrent neural network (RNN) with long- and short-term memory architecture performs under volatile market conditions. For this study, we tried to perform a comparative analysis between two models within two successive time periods, where one is trained in a volatile market condition and the other in a relatively low volatile market condition. The results showed that the RNN model is less accurate in predicting the prices in a volatile market compared to a relatively low volatile market. We also compared these two models to a separate model where we trained using the combined data from the two successive time periods. Even though the addition in data points for the neural network produced a better result compared to the model trained under volatile conditions, it did not significantly perform better than the model, which was trained in the low volatile period. 2022 Management Development Institute. -
Forecasting intraday stock price using ANFIS and bio-inspired algorithms
The main focus of this study is to explore the predictability of stock price with variants of adaptive neuro-fuzzy inference system (ANFIS) and suggests a hybrid model to enhance the prediction accuracy. Two variants of ANFIS model are designed which includes genetic algorithm-ANFIS (GA-ANFIS) and particle swarm optimisation-ANFIS (PSO-ANFIS) to forecast stock price more accurately. The standard ANFIS is tuned employing GA and PSO algorithm. The experimental data used in this investigation are stocks traded per minute price of four companies from NSE. Sixteen technical indicators are calculated from the historical prices and used as inputs to the developed models. Prediction ability of the developed models is analysed by varying number of input samples. Numerical results obtained from the simulation confirmed that the PSO-ANFIS model has the potential to predict the future stock price more precisely than GA-ANFIS as well as other earlier methods. Copyright 2021 Inderscience Enterprises Ltd. -
Forecasting gold prices based on extreme learning machine /
International Journal Of Computers Communications & Control, Vol.11, Issue 3, pp.372-380, ISSN: 1841-9836. -
Forecasting gold prices based on extreme learning machine
In recent years, the investors pay major attention to invest in gold market because of huge profits in the future. Gold is the only commodity which maintains its value even in the economic and financial crisis. Also, the gold prices are closely related with other commodities. The future gold price prediction becomes the warning system for the investors due to unforeseen risk in the market. Hence, an accurate gold price forecasting is required to foresee the business trends. This paper concentrates on forecasting the future gold prices from four commodities like historical data's of gold prices, silver prices, Crude oil prices, Standard and Poor's 500 stock index (S & P500) index and foreign exchange rate. The period used for the study is from 1st January 2000 to 31st April 2014. In this paper, a learning algorithm for single hidden layered Feed forward neural networks called Extreme Learning Machine (ELM) is used which has good learning ability. Also, this study compares the five models namely Feed forward networks without feedback, Feed forward back propagation networks, Radial basis function, ELMAN networks and ELM learning model. The results prove that the ELM learning performs better than the other methods. 2006-2016 by CCC Publications. -
Forecasting Demand for Paddy and Cotton in India: Empirical Analysis Using Machine Learning Models
India has a thriving and varied agricultural sector, which has long served as the foundation of the economy. Agriculture contributes significantly to Indias economy and is essential to the nations food security because a sizable percentage of the countrys agricultural population works in farming and associated industries. Indian farmers have managed to successfully produce a variety of commodities, including cash crops like cotton and sugarcane as well as staples like rice and wheat, despite confronting numerous obstacles like small landholdings, poor infrastructure, and unpredictable weather. In this context, it is crucial to examine the status of Indian agriculture at the moment, its advantages and disadvantages, and the possibilities and difficulties confronting farmers and policymakers. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Forecasting Bitcoin Price During Covid-19 Pandemic Using Prophet and ARIMA: An Empirical Research
Bitcoin and other cryptocurrencies are the alternative and speculative digital financial assets in today's growing fintech economy. Blockchain technology is essential for ensuring ownership of bitcoin, a decentralized technology. These coins display high volatility and bubble-like behavior. The widespread acceptance of cryptocurrencies poses new challenges to the corporate community and the general public. Currency market traders and fintech researchers have classified cryptocurrencies as speculative bubbles. The study has identified the bitcoin bubble and its breaks during the COVID-19 pandemic. From 1st April 2018 to 31st March 2021, we used high-frequency data to calculate the daily closing price of bitcoin. The prophet model and Arima forecasting methods have both been taken. We also examined the explosive bubble and found structural cracks in the bitcoin using the ADF, RADF, and SADF tests. It found five multiple breaks detected from 2018 to 2021 in bitcoin prices. ARIMA(1,1,0) fitted the best model for price prediction. The ARIMA and Facebook Prophet model is applied in the forecasting, and found that the Prophet model is best in forecasting prices. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Forecasting a Fast-Moving Consumer Goods (FMCG) Company's Customer Repurchase Behavior via Classification Machine Learning Models
With numerous businesses offering clients equivalent products, the FMCG (Fast Moving Consumer Goods) industry is very competitive. Retaining client loyalty and encouraging them to return to make product purchases is a big concern for businesses in this sector. One of the main issues this bleak business needs to overcome is customer retention. Failure to repurchase by customers is a sign that they do not trust the brand, which will increase attrition rates and have an adverse effect on the company's revenue. These issues were addressed by attempting to predict the customer repurchase rate and approaching the target segments in accordance with that prediction, but this was done entirely from the perspective of the consumer and not from the retailer, and it ignores other factors like location, the salespeople they work with, the wholesaler they are affiliated with, and the customer programme they have chosen. The retailer's repurchase pattern must be predicted using a more accurate and effective model that considers all the variables. Retailers play a significant role in the supply chain for FMCG businesses. Different models like KNN, Nae Bayes and Logistic Regression was explored to find the best fit. By keeping them, the business can forge enduring connections that are crucial for preserving stabilityand dependability in the distribution network and having the resources necessary to serve its clients. 2023 ACM. -
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Forcing Parameters and Propagation Time of Certain Graph Classes
A branch of mathematics that treats vertices and edges of a graph is called graph theory. This theory is used to replicate many real-life situations and physical problems. Graph coloring problem is one of the prominent studies in extremal graph theory. Suppose information has to be communicated in a network or some product has to be marketed to all the people in a cluster then there are two types of cost that needs to be encountered, one the cost of selecting the initial set of vertices in a network and the second is, time it takes to propagate the information through the entire network. The sum of these two parameters is known as the total cost. Optimizing the total cost, which is the sum of vertices and the time it takes to propagate information through the entire network, is a challenging problem for any newlinegraph. Such an interesting and well-studied problem is called the dynamic coloring newlineproblem. The forcing problem also known as infecting or spreading problem is one newlinesuch dynamic coloring problem where two colors- white and black are used. Assume that a fxed set of vertices in a graph G are initially black and that the remaining vertices are considered white vertices. The aim of the forcing process is to obtain, fully black-colored vertices of the graph G by progressively applying the color change law, making sure that at least one white vertex is forced black in every discrete time interval. The forcing index is the minimum cardinality of the forcing sets. Diand#64256;erent types of forcing, such as one forcing, connected one forcing, k-forcing connected k-forcing etc., are defned based on the color change law. The one forcing is the basic form of forcing. A generalised form of one forcing is known as k-forcing where k lt V (G). The time taken by a forcing set to force the entire vertices of the graph G black is the propagation time or iteration index. The subject of study aims to fnd the one forcing number and k-forcing number of diand#64256;erent types of graph classes and derived graph classes. -
Forced Labour, Global Supply Chain and TNCs: Recent Trends and Practices
The abolition of forced labour is a fundamental element of contemporary international human rights law, but the idea has undergone a protracted and complex history, and the scope of the various international mechanisms that handle different aspects of it is not always precisely defined. Slavery, forced labour, and related practices are strictly prohibited under international law. Forced labour is a longstanding and complex obstacle in global supply chains, frequently associated with the desire for inexpensive products and the outsourcing of manufacturing processes to nations with lax labour regulations. The growing power of transnational corporations (TNCs) poses significant challenges to workers at the bottom of supply chains. However, disagreements have made it unclear how to deal with new forms of forced labour, or modern forms of slavery. This confusion highlights the need for a comprehensive approach to combating these issues. Efforts to stop or restrict forced labour will be made easier with a clear legal definition at both the national and international levels, particularly with an emphasis on the human rights perspective. 2024 Kluwer Law International BV, The Netherlands -
Forbidden Cravings: Exploring socio-cultural ramifications of food practices in Aamis
Food choices represent conscious affirmation and expression of personal, group, ethnic or national identity. Due to its multidimensional role, food that we rely on sustenance is often politicised and used as a tool to create conflict amongst and within diverse social groups. Assamese cuisine includes a rich platter of authentic food varieties, often limited to the north-eastern region. Although food consumption is a subjective experience, cultural taboos within a community might be acceptable practices in another culture, creating conflicting notions of food practices. The balance between the twin axis of culture and politics regarding food is disrupted when heterogeneous cultural patterns and opposing political notions are in discord. Similarly, the solidarity within a cultural group becomes hostile when the authority of the individual concerning food choices is not aligned with the authority of the social structure. This discord from a political and cultural standpoint is evident in the Assamese socio-cultural scenario. Taking Bhaskar Hazarika's Ravening/Aamis (2019) as a case study, this paper proposes to analyse the representational troupe of food, through a structuralist anthropological lens, with respect to food politics to understand socio-cultural ramifications of Assamese food patterns. 2022 Aesthetics Media Services. All rights reserved. -
FOPID controller tuning: A comparative study of optimization techniques for an automatic voltage regulator
This study evaluated a fractional order proportional-integral-derivative (FOPID) controller optimization with a fractional filter for an automated voltage regulator (AVR) system. For the suggested controller, a variety of different parameters can be changed. For the purpose of creating the optimum PID controller for an automated voltage regulator system, comparative analysis using multiple optimization methodologies is carried out. The Salp Swarm Algorithm (SSA), Ant Lion Optimization (ALO), and Particle Swarm Optimization algorithm (PSO) are the techniques that are being examined in this study. The settling time, rising time, and overshoot performance indices is being used. The transient responsiveness of the AVR system was increased by each of the recommended optimization techniques in a different way, and early results were optimistic. The comparison with the most ideally tuned FOPID controllers for the AVR system also serves to support the superiority of the suggested controller. 2023 Author(s). -
Footloose Culture: Migrant Workers and Cultural Meanings of Labour
[No abstract available] -
Football Player Substitution Analysis using NLP and Survival Analysis
Football player substitution is extremely significant in situations where the team is down by goals or attempting to retain a lead that can add value to the team's performance. However, substituting players based on their prior performance would not assist the squad in making good decisions. In one of the papers, they used an inverse gaussian hazard model to determine the survival rate of players. However, the main issue arises when players do not give their all due to their mental state, which plays a critical role during the game. Furthermore, most of the research papers relied solely on past performance of players and various analyses, which was insufficient. This study discovered that the player's mindset should be mentally stable and competitive which is also very crucial during the match by reading various research articles. Hence, this study proposes a framework which comprises of two models, namely Survival Analysis (Kaplan-Meier Fitter) and Natural Language Processing (Sentimental Analysis). Sentimental Analysis would hel p in determining a player's mindset before the match and Kaplan-Meier Fitter is used to find out the survival rate of player's performance based on several factors like goal scored, passing accuracy etc. which would allow the team to make better informed decisions. Comparison of these two models would yield the best results for substitute players on the bench on the basis of their past performance and their mental health which will allow them to make team management to make better judgments. 2023 IEEE. -
Food wastage and consumerism in circular economy: a review and research directions
Purpose: Considering food waste as a global problem resulting from the wastage of valuable resources that could fulfil the requirements of malnourished people, the current research focusses on understanding consumerisms impact on this phenomenon. Additionally, the circular economy (CE) approach can be critical in reducing food waste and promoting sustainability. Design/methodology/approach: A systematic literature review was conducted using bibliometrics and network analysis. The study reviewed 326 articles within 10 years, from 2013 to 2023. Findings: The findings reveal four prominent factors behavioural, environmental, socioeconomic and technological in managing food waste (FW). Reducing FW at a holistic level can benefit individuals and the environment in several ways. Research limitations/implications: Consumers are encouraged to be more responsible for their food consumption by reducing food waste, as it affects societies and businesses both economically and environmentally. This can help promote a responsible consumption culture that values quality over quantity and encourages people to make more informed choices about what they eat and how they dispose of it post-consumption. All stakeholders, including firms, the government and consumers, must examine the motives behind inculcating pro-environmental behaviour. Originality/value: Addressing consumerism and the ability to decrease FW behaviour are complex issues that require a multidimensional approach. This study seeks to fill the gap in understanding consumerism and the capacity to reduce FW using the CE approach and understand the research gaps and future research trends. 2024, Emerald Publishing Limited. -
Food Security and Its Impact on Society: Cases of Developing World
Food security is a matter of concern in the twenty-first century as is evident from the importance given to it in the United Nations Sustainable Development Goals. Despite attempts to address food scarcity concerns at global conventions such as the World Food Summit of 1996, food remains scarce. Scholars further suggest that though food scarcity is a global issue, its roots and impact is local. Consequently, a study of food must study the major challenges that converge to undermine food security worldwide including conflicts, climate change, global policies and in recent times even the Covid 19 pandemic. However, at a fundamental level food scarcity is the by-product of not just a legacy of past failures to build more just, sustainable, and resilient food systems, but rather a by-product of our inability to be responsible and sustainable consumers. This chapter highlights that despite surplus food production, developing nations often face food insecurity owing to the diversion of food towards developed nations. These nations, instead of sharing global resources (including food and agricultural labour), often contribute towards the global food crisis. Moreover, some of these developed nations engage in an industrialised system of food produc-tion which might meet the nations food requirements but are not sustainable modes of production and pose a serious threat to the environment. Nevertheless, the indis-cretions of the developed nations affect the developing nations economically as well as socially. As social outcasts, marginalised communities and individuals within the developing world are worst affected. As a result, this chapter offers insight into the social struggle brought on by inaccessibility to food. The chapter further suggests that addressing concerns of food security is not only a matter of addressing the inequalities manifest in the production, distribution and consumption of food but also learning to be responsible and sustainable consumers. Simply stated, the chapter recommends connecting SDG 2 with SDG 12. This chapter would also include the position of India in GHI, the Ukraine crisis and its aftermath in various developing countries, the earthquake in Turkey and how it affects the food security, and a few instances from Africa to highlight the concepts of food security and its correlation with sustainability of any society. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Food Security and Global Institutions: A Global Justice Perspective
Food security refers to a condition where all people have physical and economic access, at all times, to sufficient, safe and nutritious food that meets their needs and food preferences to lead an active and healthy life. Universal Declaration of Human Rights, 1948 (UDHR) declares the right to food as a basic human rights. International Covenant on Economic, Social and Cultural Rights, 1976 (ICESR) explicitly recognises the right of everyone to food and mandates all state parties for its realization; also it recognizes everyones right to be free from hunger as a fundamental right. Further, it instructs the state parties to ensure equitable distribution of world food supplies to achieve the right of everyone to be free from hunger. Rome Declaration on World Food Security, 1996 reaffirmed the right of everyone to access to safe and nutritious food compatible with right to adequate food and also right to be free from hunger. United Nations Millennium Declaration set the goal for fighting hunger and resolved to reduce the proportion of people suffering from hunger to half by 2015, then Sustainable Development Goals were floated, inter alia, to end extreme poverty and achieve the target of zero hunger and food security by 2030. Regardless of its being a universal human rights, food security scenario across the globe is far from satisfactory and fair. Post COVID 19 scenario has seen a surge in undernourishment and food insecurity. According to The State of Food Security and Nutrition in the World, 2022, 3.1 billion people across the globe are unable to afford a healthy diet. At this juncture we are living in a deeply connected and globalized world run not by national institutions but by global institutions. The role of global institutions assume significance in a globalized world. Justice demands that policy planning and legal framework on food security should be fair and equitable; they should be based on the idea of entitlement and obligation. To achieve the goal of zero hunger and food security, what is required is an equitable and unified global governance approach premised upon the idea of global justice which shall fix obligations on global institutions. This chapter aims at examining the issue of food security from a global justice perspective and how it can be sustainably achieved. It will explain the concept of global justice and obligations of global institutions by relying upon few legal and political theories. Further, the chapter will explain the human rights perspective of the food security and the challenges involved with it. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
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. -
Food quality traceability prototype for restaurants using blockchain and food quality data index
As competition between organizations are evolving into competition between supply chains, to survive and indeed grow, it is necessary to deliver added value to customers. Traceability has emerged as one of the key measures of operational efficiencies within supply chains and ultimately, customer service. Over the years, organizations have deployed number of methods in delivering food traceability. This paper examines major methods of food traceability currently in existence and proposes a restaurant prototype for implementing more reliable food traceability using Blockchain and product identifiers. The prototype captures data from various stakeholders across the food supply chain, segregates it and finally, applies the Food Quality Index (FQI) algorithm to generate an FQI value. The FQI value helps in identifying whether the food is good for consumption on specified parameters. FQI value is generated based on extant standard storage and handling regulations specified by food safety authorities, and checks whether value so derived, is within the permissible range. The prototype helps in grading food quality for human consumption besides strengthening food (product) traceability. This prototype can be customized to address future requirements of traceability triggered through new information emanating from any stakeholder or the node in the supply chain. 2019 Elsevier Ltd