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Algorithmic Trading: Financial Markets Using Artificial Intelligence
This research study gives an in - depth view of the recent developments in the fields of Machine Learning (ML) and Reinforced Learning (RL) techniques as they are related to various models for forecasting and systems for financial trading. The practical usage of deep learning models, that incorporates Neural Networks such as Recurrent, Convolutional along with hybrid models integrating genetic algorithms with LSTM networks, for forecasting the stock market patterns as well as bank failures, and fluctuations in exchange rate which is addressed in this study in an in - depth review analysis of the latest literature. In addition to this it also investigates how trading algorithm performance as well as risk management can be enhanced by applying techniques of deep reinforcement learning. This study also demonstrates the enhanced, efficacy, precision and the profitability achieved by using these artificial intelligence methods as compared with conventional economic modelling and detailed technical study models by analysing a number of stock markets and different kinds of assets. 2024 IEEE. -
Ethical AI in Humanitarian Contexts: Challenges, Transparency, and Safety
This chapter elaborates on how emerging technologies for artificial intelligence (AI) can help create social change and solve worldwide problems. The chapter brings to light the issue of ethical matters and responsible AI practices that should be considered to avoid technology usage by the vulnerable population to harden already present inequalities. This chapter also examines the role of AI in ensuring that quality education is accessible to all, in addressing poverty through innovative approaches, and in the amplification quest of human rights advocacy by marginalized groups. This chapter presents a complete picture of the impact of AI on humanitarianism, exemplifying the devices of new horizons and emphasizing the necessity of responsible and inclusive applications. This chapter provides findings and advice for researchers, practitioners, policymakers, and all interested parties who are involved in using the new technologies to make their world fairer and well-sustained. The chapter aims to comprehend the AI-humanitarianism nexus and simultaneously proclaim safety measures and transparency for the sake of social upheaval. 2025 selection and editorial matter, Adeyemi Abel Ajibesin and Narasimha Rao Vajjhala; individual chapters, the contributors. -
Free COOH-tethered layered Co(ii) framework and flexible composite as a size-reliant, tandem and robust catalyst for mild and scalable synthesis of bioactive molecules
Pore-functionalization in metalorganic frameworks (MOFs) through the immobilization of free carboxylic sites offers a promising strategy for designing high-performance materials with potential applications, including selective and benign chemical transformations. However, this feat is tricky because of their extreme tendency to coordinate with the concerned metal ions. Herein, we developed a layer-stacked and thermo-chemically stable two-dimensional MOF, encompassing flanked carboxylic acid and [Co2(COO)4] unit-decked porous channel, using a mixed-ligand approach. The guest-free structure serves as a one-of-a-kind superior heterogeneous catalyst for tricomponent KnoevenagelMichael condensation, yielding a multitude of 2-amino-3-cyano-4H-pyrans with low catalyst loading, short duration and mild temperature compared to the majority of reported materials. The role of Lewis and Brsted acidic sites in the MOF catalyst is comprehensively supported by control experiments, analyte-induced emission articulation, inferior activity of a task-specific site-truncated iso-skeletal framework, and density-functional theory results. Importantly, the MOF demonstrated the first-ever deacetalization multi-component reaction (MCR) with admirable and recyclable conversion under relatively green conditions. Besides covering twenty-two electronically diverse substrates, the MOF can synthesize nine bioactive pyrans with excellent yield and gram scale. Notably, fifteen 4H-pyrans are first-time characterized in their purest forms via X-ray crystallography besides other spectro-analytical studies. Larger-sized substrates failed to diffuse inside MOF's micropores and illustrate unprecedented molecular-dimension-mediated MCR. The in situ-grafted MOF inside melamine-foam (MF) yielded a reconfigurable composite that promotes this one-pot reaction with similar activity and reusability to that of the sole MOF and demarcates a paradigm shift toward cutting-edge sustainable catalysis over a practical platform. This journal is The Royal Society of Chemistry, 2025 -
Novel Ovate Antenna for Wireless Communication: Characteristic Mode and Time Domain Analyses
In this article, a novel ovate-shaped microstrip antenna (OMSA) is presented for the application in wireless communication. It covers the evolution of a new shape and delves deeper into the resonance mechanism of the proposed design using characteristic mode analysis (CMA). The OMSA resonates at 2.45 GHz and 2.69 GHz with the return loss of ?18.82 dB and ?31.84 dB, respectively. It offers an ultra-wideband performance with 91.46% measured bandwidth. The characteristic impedance and VSWR at 2.4 GHz are 49 ? and 1.3, respectively. By introducing performance enhancement techniques such as ground truncation and a notch in the patch, the antenna resonance characteristics have been enhanced. A prototype of the proposed OMSA has been fabricated and validated experimentally. The time domain characteristics of the proposed OMSA have been simulated for both face-to-face (FtF) and side-by-side (SbS) configurations. The FtF configuration offers better performance, showcasing the group delay of the OMSA < 2 ns and minimal variation along the operating band. The phase linearity is also maintained, minimizing any distortions. The time domain results demonstrate a maximum fidelity factor of 90.62%, reaffirming the suitability of the antenna for wireless communication. The suitability of the proposed OMSA for wireless applications is also validated experimentally by analyzing the group delay and S21 phase linearity of the received signal. 2026, Electromagnetics Academy. All rights reserved. -
Navigating the Labyrinth: Trauma and Memory in Donna Tartts The Goldfinch and Nathan Hills The Nix
This paper delves into the intricate interplay between trauma and memory in 21st-century American fiction, with a specific focus on Donna Tartts The Goldfinch (2013) and Nathan Hills The Nix (2016). Through a comparative analysis of these novels, the study explores how characters navigate the labyrinthine complexities of trauma and its impact on memory, identity, and narrative construction. Grounded in the theoretical framework of Dan P McAdams Narrative Identity Theory, the study employs a rigorous interdisciplinary approach, synthesizing textual analysis with theoretical inquiry to illuminate the nuanced dynamics at play within the selected texts. The paper examines how trauma disrupts and reshapes memory, leading to fragmented recollections, haunting flashbacks, and the blurring of past and present. Additionally, it investigates how memory serves as a tool for both coping with and perpetuating trauma, shaping characters perceptions of themselves and the world around them. 2025 IUP. All Rights Reserved. -
Irrigation water policies for sustainable groundwater management in irrigated northwestern plains of India
Increasing global water shortage emphasizes the need for demand-side water management policies, especially in the agriculture sector, being the largest consumer of freshwater. Such policies are relevant in India, where groundwater depletion may have severe implications at various socio-economic levels. In this study, using mathe-matical modelling, we assess the feasibility of two alter-native irrigation water pricing policies (i) uniform wa-ter pricing policy and (ii) differentiated water pricing policy, wherein farmers growing less water-requiring crops (<4488 m3/ha) get an incentive for saving water, while those growing water-intensive crops pay for it. Us-ing a case study of Punjab, the breadbasket and one of the fastest groundwater-depleting states in India, alter-native cropping patterns are also suggested. The findings reveal that the current rate of groundwater withdrawal could not sustain agricultural intensification in the state. Although optimization of resource allocation has the pote-ntial to save water by 8%, this alone is unlikely to break the ricewheat mono-cropping pattern in Punjab. The analysis of two different volumetric irrigation water pricing policies shows that differentiated water pricing would be more effective in halting groundwater deple-tion in the state. However, adequate investment in irri-gation water supply infrastructure, mainly for installing water meters, is required to implement the policy. 2022, Current Science. All Rights Reserved. -
Sustainable intensification of water guzzling crops: Identifying suitable cropping districts of India
With food sufficiency being achieved, emphasis of policy makers is now on to sustainable intensification in line with the objectives of Sustainable Development Goals (SDGs).Widening discrepancy between the water-resource supply and demand necessitates relook into the cropping pattern of the country.Based on district-level secondary data of area, productivity and level of groundwater extraction, this study aims to identify critical and potential area for cultivation of three major water-intensive crops, i.e.rice, wheat and sugarcane.Study found that 1.93 million ha of area under rice, mainly in north-western and western India, need a gradual shift.Nearly 43% of the rice cultivated area in eastern and north-eastern states of West Bengal, Odisha, Chhattisgarh and Assam has potential for further intensification of rice cultivation.In case of wheat, around 0.65 million ha of area, mostly in Rajasthan, is critical in terms of sustainability.Livestock is an integral part of agriculture in this region and hence diversification of wheat would require mixed strategy of shifting to alternative dual-purpose crops and wheat cultivation with water conservation technologies.Study ftirther found that around 13543 ha of sugarcane in mainly in western Uttar Pradesh and Tamil Nadu is deterring the groundwater resources.Recommendations emanating from the study include differentiates agricultural price policy, payment for ecosystem services and greater focus on productivity enhancement in eastern India. 2021 Indian Council of Agricultural Research. All rights reserved. -
Design and Verification of a Novel Anchor Shaped Double Negative Metamaterial Unit Cell
In this manuscript, a novel anchor-shaped double negative metamaterial is proposed. The structure is designed to resonate at 2.45 GHz. The unit cell is designed on a 1.6 mm thick FR4 substrate having a dielectric constant of 4.4, and simulated using Ansys HFSS. The unit cell exhibits a double negative behavior and negative refractive index behavior. The robust and popularly used Nicolson-Ross-Weir and Transmission-Reflection methods were implemented on MATLAB to extract and validate the metamaterial characteristics. This novel metamaterial unit cell covers 1 GHz to 4.8 GHz which is one of the most extensively researched and employed bands of the electromagnetic spectrum. The bandwidth performance of this new structure for double negative behavior is compared to other unit cells. It shows better performance with comparable size and outperforms the other geometries. This metamaterial is well-suited for a wide range of applications like wireless communication, biomedical applications in ISM (2.4 GHz) band and 5G communication services in the sub-6 GHz range. 2022 IEEE. -
FEC & BCH: Study and implementation on VHDL
Channel encoding and Forward Error Correction is a crucial element of any communication system. This paper gives a brief overview of the fundamentals, mechanism and importance of Forward Error Correction. The design and implementation of a (63,36,5) BCH Codec is also projected in the later sections. All simulations are made on MATLAB R2018b and the VHDL implementations have been carried out using Xilinx Vivado 2018.2. 2019 IEEE -
Comparative optimization studies (Isp 4 vs isp 3 vs isp 2 media) of mangrovian streptomyces pluripotens anukcjv1 for its ?-amylase production and geographical correlation of mangrovian actinomycetes strains
Streptomyces pluripotens ANUKCJV1 was isolated from Coringa Mangroves which was located along the South Indian Delta. The Current work which was in continuation to our previously reported work which suggests that Streptomyces pluripotens ANUKCJV1 was the potential strain and the same has been subjected to comparative optimization studies in the current work by employing three media: ISP 4; ISP 3; ISP 2 media for enhanced ?-Amylase Production. Physico-Chemical variables viz Incubation period, PH, Temperature, Carbon and Nitrogen sources with respect to three different media (ISP 4, ISP 3 and ISP 2) were tested and cumulative analysis of three different media for differential bioactivity of ?-Amylase was done. Results suggest that ISP 4 found to be the best medium with cumulative value of 24.2 U/mL, where as the cumulative value of ISP 3 and ISP 2 were 19.3 U/mL and 19.4 U/mL respectively. Peptone as Nitrogen source of ISP 4 found to be the favourite Individual variable among all with production value of 8.0 U/mL. Geographical correlation with respect to number of Actinomycetes strains and ?-Amylase Bioactivity depicts that Distant geographical soil samples from the shore found to be favourable for higher number of Actinomycetes strains: A1 soil samples (~ 500 m)-33 %; A2 samples (~ 400 m)-22 %. With regard to ?-Amylase Bioactivity, A5 samples (~ 100 m) analysed to be the potential geographical bioactive zone for ?-Amylase Production. From the study it can be concluded that since ISP 4 found to be the favourite medium of the potential strain, by employing the same large scale exploration of the Streptomyces pluripotens ANUKCJV1 of the Coringa Mangroves may be done to tap the industrial benefits of ?-Amylase. EM International. -
HRL-ViT: Human-Robot Collaborative Vision Transformer for AIoT-Enabled Leaf Disease Detection in Precision Agriculture
The combination of artificial intelligence and Internet of Things (AIoT) technologies is changing precision agriculture by making it possible to automatically check the health of crops. Early detection of leaf diseases is still important for stopping yield losses, but regular convolutional neural networks (CNNs) often don't work as well when they have to deal with different textures, lighting changes, and noise on the field level. To address these constraints, this study presents HRL-ViT, a Human-Robot Collaborative Learning framework that utilizes Vision Transformers for leaf disease identification. The frame-work merges the global attention feature of Vision Transformers with a human-in-the-loop approach, wherein predictions with low confidence are validated by experts and used to improve the model over time. The system is also made for edge-based AIoT deployment, which lets you analyze data in real time in agricultural settings. Experimental research utilizing both benchmark datasets and field-acquired images demonstrates that HRL-ViT consistently surpasses baseline CNN and Transformer models, attaining superior accuracy, precision, and recall while minimizing false detections. Transformers' attention maps can be visualized to make them even easier to understand, which helps users trust them and make decisions. In general, HRL-ViT shows a lot of promise for use in autonomous robotic platforms. It offers an explainable and scalable way to find diseases in precision agriculture. 2025 IEEE. -
Concerns in IoT Environments: Adoption, Architecture, and Innovation of Enterprise IoT Systems
The Internet of Things (IoT) has received a lot of interest in recent times. IoT depicts the upcoming internet and is defined as an environment of linked gadgets, computational processes, and other items that collaborate to transmit information or data with greater ease and economic advantages. Nevertheless, because of the presence of numerous concerns, IoT adoption, architecture, and innovation continue concerns. As a result, the purpose of this study was to identify and analyze the concerns in the adoption, architecture, and innovation of IoT systems in construction enterprises in the Indian environment. The research analysis and professional comments have been employed to identify the barriers to IoT adoption, architecture, and innovation. This research may assist professionals and policymakers in addressing barriers to successful IoT adoption and spread. At last, findings and potential research possibilities are provided. 2024 selection and editorial matter, Prof. (Dr.) Dorota Jelonek, Prof. (Dr.) Narendra Kumar, Prof. (Dr.) Mamta Chahar, Prof. (Dr.) Rusudan Kinkladze and Prof. (Dr.) Lilla Knop; individual chapters, the contributors. -
PBIB-designs and association schemes arising from minimum bi-connected dominating sets of some special classes of graphs /
Afrika Matematika, Vol.29, Issue 1-2, pp.47–63, ISSN: 1012-9405. -
Business Intelligence in Action: Way of Successful Implementation of Automated Systems
This chapter presents an overview of the role of automated systems in Business Intelligence (BI). BI has emerged as a critical element for modern organizations in decision-making processes by analyzing large volumes of data. Automated BI systems offer several advantages over traditional manual systems, including increased efficiency, accuracy, and customized insights. Despite these benefits, there are several limitations and challenges associated with the implementation of automated BI systems. This chapter examines the benefits and limitations of automated BI systems and identifies common success factors for successful implementation. The chapter also explores different types of automated systems, including predictive analytics, machine learning, natural language processing, and robotics process automation. These systems can help organizations analyze and interpret large amounts of data more quickly and accurately, enabling them to make informed decisions. However, despite the potential benefits of automated BI systems, there are several challenges associated with their implementation, including technical expertise and integration issues. To address these challenges, careful planning, collaboration, and ongoing monitoring are essential. In conclusion, this chapter highlights the importance of automated BI systems in modern businesses and provides valuable insights into their benefits and limitations. The chapter also emphasizes the need for careful planning, collaboration, and monitoring for the successful implementation of automated BI systems. 2024 selection and editorial matter, Nidhi Sindhwani, Rohit Anand, A. Shaji George and Digvijay Pandey; individual chapters, the contributors. -
Sales Prediction Scheme Using RFM based Clustering and Regressor Model for Ecommerce Company
Machine learning models are being used for better insights and decision making across many industries today. It shows to be quite useful for businesses in the ecommerce industry as well due to the vast amount of data generated and its potential. This research aimed to find insights on future sales of an ecommerce company [1]. The vast number of variables including both categorical and continuous variables under product data, customer information, transaction information, led us to implement a prediction model using regressors rather than just time series forecasting techniques. First an RFM (Recency, Frequency and Monetary) based clustering algorithm was used to get customer related information and then integrate those results into a regressor to achieve the desired goal of prediction of sales. Two schemes were tested one being predictions on individual clusters and the other where the clusters were one hot encoded back into the main data. Results show quite high accuracy of prediction. The high R-squared also indicated that our hypothesis of including the variables contributed significantly to the predicted sales values was correct in this case. This research fulfills an identified need to understand how machine learning algorithms can be implemented by multiple algorithms being integrated in sequential and logical orders thus helping derive business specific strategies rather than making it a mere technical process by providing empirical results about how the predicted sales values along with given inputs can contribute in business decision making relating to marketing, inventory management, dynamic pricing or many more such strategies. 2022 ACM. -
Impact of online cooperative learning strategies on self-directed learning among pre-service teachers
Self-directed learning (SDL) often drives learners to engage with what they want to learn. Thus, investigating teaching-learning strategies that drive SDL gains importance in this technology-driven era. The present study investigates the impact of online cooperative learning (OCL) strategies on SDL skills among pre-service teachers (PST). The study engaged 130 PSTs using a quasi-experimental non-equivalent control group design with a pretest and posttest. The study divided PST into a control group and an experimental group. The experimental group underwent OCL strategy, and the control group had a traditional online lecture method. The researchers measured the SDL of PST using the SDL scale. The paired sample t-test results indicated a significant enhancement in SDL skills among the experimental group compared to the control group. The findings underscore the importance of integrating cooperative learning (CL) strategies in online instruction to foster SDL ability among learners. Further studies may create user-friendly features in video-conferencing platforms that provide more opportunities to engage students with CL pedagogies. 2025, Intelektual Pustaka Media Utama. All rights reserved. -
Online cooperative learning: exploring perspectives of pre-service teachers after the pandemic
Mainly, research has explored pre-service teachers perspectives toward cooperative learning within face-to-face teaching. However, in a post-pandemic scenario, previous research has yet to effectively explore pre-service teachers (PSTs) perspectives toward online cooperative learning (OCL) in teacher education programs. So, recognizing the gap in the literature, this paper aims to explore the perspectives of PSTs towards OCL. The researchers employed a qualitative research design for the present study. The researchers conducted semi-structured interviews with 10 PSTs who underwent OCL during the pandemic. These PSTs may possess digital proficiency, virtual collaboration abilities, flexibility in evolving educational environments, and an enhanced understanding of online cooperative learning methodologies within modern education. Researchers employed a thematic analysis to analyze the qualitative data obtained. The various themes that emerged from the study are perceived benefits of OCL, challenges to OCL, technological proficiency, learning strategies and support, and building a supportive online learning community. Future researchers may contribute to advancing effective online learning practices by gaining a deeper understanding of pre-service teachers perspectives towards OCL through research on a larger scale, including various teacher education programs in various countries. 2024, Institute of Advanced Engineering and Science. All rights reserved. -
Migrant minds, shifting selves: Navigating relationships and identity in internal migration
Human migration brings about changes in personal, social, cultural, political, and economic facets of life. This study examined the pre-migratory and post-migratory contexts of emerging adults in India to explore their connection to the existing relationships at migration origin, and upcoming interactions at migration destination. A qualitative method was used to capture the subjective experiences of emerging adults from middle SES, who migrated for education or employment reasons from rural, semi-urban, or urban areas. The migration experiences of these 1829 year-old emerging adults were analyzed through the lens of the social-cognitive model of transference. Semi-structured interviews of 17 internal migrants were conducted to learn about their experience residing away from home. Data analysis revealed schemas concerning significant others interfering with their new relationships at migration destination. Narratives of attachment, support, and conflict shaped their new relationship and self-perception at the migration destination. 2026 Elsevier Ltd. -
Contemporary Indian Way of Settling Down: Emerging Adults Perspective
Settling down in India historically entailed a culturally constructed notion for individuals, focusing on marriage. An exploration of the modern Indian idea of Settling down was explored in light of the driving forces of globalization and increased migration. The current study explored the concept of Settling down among emerging adults aged between 18 and 29 years who had migrated within the borders of India for education or employment purposes. To this end, semi-structured interviews were conducted. The reflexive thematic analysis method was employed for analysing the data. Emerging themes unveiled that despite marriage being endorsed by a few of the participants, co-habiting relationships were convenient and burden-free. Employment, financial independence, and professional stability emerged as the primary markers of Settling down among migrant emerging adults. It was also recognized that migration had a critical impact on peoples decisions about settling down.. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Yellow leaf disease, climate change, and its impact on the life of farmers in Sullia
Sullia taluk of Dakshina Kannada district has been receiving heavy rainfall for the past few years, having a huge impact on agriculture. Yellow leaf disease spreads from one fully grown tree to another and gradually to the adjacent trees. Arecanut plantations across the region developed the disease, reducing arecanut production. It has hit the livelihood of many farmers whose only source of income was the harvest of arecanuts. Apart from the fungal infection causing financial loss, farmers also face the brunt of gradually reducing agricultural yield in consecutive years. It is yet to be tackled with chemical treatment and hence stands tall as a problem causing an impact on the lives of farmers in Sullia. The current study explored the problem of climate change resulting in yellow disease and its impact on the well-being of plantation owners and workers in the context of Sullia whose culture is rooted in the land. A lack of awareness about mental health influencing the understanding of an epidemic interfering with the local way of life has been emphasized. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.