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HashPress: Building a Green Data Center for Tomorrow
Green data centers are a game-changer for the environment, offering substantial benefits over traditional data centers. They prioritize reducing carbon emissions, optimizing energy use, and enhancing overall energy efficiency. One of the key strategies involves using deduplication and compression technologies, which can significantly reduce the environmental footprint of data centers. By decoupling data-set sizes for compression and deduplication, these centers can optimize each process individually, ensuring that neither technique is compromised and both are fully leveraged for maximum efficiency. In this paper, the HashPress algorithm is introduced, which aims to further enhance the green credentials of data centers. This algorithm proposes innovative measures to optimize data handling processes, making them environment friendly. The empirical validation is conducted to support its efficacy, by improving storage efficiency and reducing energy consumption. The discussion highlights its potential in supporting the broader goal of establishing a green technology infrastructure. Through these advancements, green data centers not only decrease their environmental impact but also pave the way for a resource-efficient future in the technology industry. This paper also delves into the explosive growth of the green data center, importance of decarbonization and sustainability in reducing the environmental footprint and the current strategies and solutions being deployed by leading companies to address the challenge. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
FortGen IDS: The Fusion of SOAR and Hybrid IDS for Enterprise
In this data era, enterprise are encountering rise of challenges in detecting and responding to cyberattacks. There is a need for a sophisticated cyber approach that leverages cutting-edge technologies to fortify against the unexpected attacks. This paper presents FortGen IDS, a novel cybersecurity solution combining Security Orchestration, Automation, and Response (SOAR) with Hybrid Intrusion Detection Systems (IDS). The primary contribution of FortGen IDS is its innovative algorithm inspired by Genghis Khans military tactics, enhancing threat detection and response, particularly against Distributed Denial-of-Service (DDoS) attacks. The proposed model leverages advanced automation and orchestration capabilities to provide a more holistic approach to enterprise cybersecurity. Empirical validation studies have been carried out to determine the best algorithm for anomaly detection, also explicitly comparing the performance of FortGen and Hybrid IDS. It helps make businesses digital defenses stronger against evolving cyber threats. This approach has greater scope in improving cyber-defense in the context of enterprise security, ensuring that firms are well-fortified against potential cyber threats. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Empowering Renewable Energy Using Internet of Things
The massive communication of information over network gadgets associated with the internet trades data starting from one to another with no sort of human cooperation. As innovation is advancing, interconnected organizations give data to each other to impart. The energy utilization is happening at an extremely quick rate, debilitating the assets in delivering it at a similar rate, and the entirety of this requires a transformation to save energy. Information is the focal point of the Internet of Things (IoT), and it has all the information to which there was no entrance before; this information can be utilized in the revolution of the energy management framework. By utilizing advanced IoT innovations, the embracement of renewable can be upgraded signifcantly further. The reconciliation of IoT in renewable energy is empowering its development by and large. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
Machine learning approaches towards medical images
Clinical imaging relies heavily on the current medical services' framework to perform painless demonstrative therapy. It entails creating usable and instructive models of the human body's internal organs and structural systems for use in clinical evaluation. Its various varieties include signal-based techniques such as conventional X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US) imaging, and mammography. Despite these clinical imaging techniques, clinical images are increasingly employed to identify various problems, particularly those that are upsetting the skin. Imaging and processing are the two distinct patterns of clinical imaging. To diagnose diseases, automatic segmentation using deep learning techniques in the field of clinical imaging is becoming vital for identifying evidence and measuring examples in clinical images. The fundamentals of deep learning techniques are discussed in this chapter along with an overview of successful implementations. 2023, IGI Global. All rights reserved. -
Analysis and Prediction of Suitable Model for Coconut Production Estimates in South Indian States
The study attempts to forecast coconut production in major coconut-producing states in India. The future projections on coconut production have been calculated based on yearly data for 73 years (194950 to 202122) accessed from the database of Indiastat (2022). We have used prominent forecasting techniques for the purpose and a suitable model has been chosen based on the lowest results of MAPE. The damped linear trend has been chosen for forecasting coconut production in Karnataka whereas Differenced first-order Auto Regressive model with drift has been adopted for Kerala and Karnataka. This study has considered a large dataset compared to other existing works and has chosen states that produce coconut on a large scale in India. Along with this, this study also attempts to find which state will produce more nuts for the Indian coconut industry, which can help the concerned stakeholders to take necessary decisions. Future projections depict that Kerala will continue to be the largest producer of coconut and Karnataka will show remarkable performance in coconut production during the upcoming four years post-study period. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Rayleigh-Bard convection in mono and hybrid nanoliquids in an inclined slot
Linear stability analysis is conducted to investigate the longitudinal and transverse rolls (TRs) generated in Rayleigh-Bard convection in mono and hybrid nanoliquids confined between two infinite inclined parallel slots. Thermophysical properties of six mono nanoliquids and fifteen hybrid nanoliquids are calculated for different volume fractions (0.5%, 1%, 2%) using phenomenological laws and mixture theory. The shooting method is used to solve boundary eigenvalue problems to obtain the eigenvalues for 16 different boundary conditions. It is observed that as the inclination angle is increased, it delays the onset of longitudinal rolls in the case of all boundary conditions. However, it advances the onset of TRs except when the lower plate is adiabatic. The addition of mono and hybrid nanoparticles results in the advancement of the onset of convection. The addition of SWCNT and SWCNT Al 2 O 3 accelerates the onset of convection the most while Cu and Cu-Ag accelerates the onset of convection the least amongst the mono and hybrid nanoparticles considered in the study. 2023 IOP Publishing Ltd. -
Origami foldaway support for beginners using image processing
Various origami works are distributed as origami books in which a succession of collapsing operations with basic outlines is portrayed. In any case, the origami book reader often will give up the instruction of the book middle, because it is too difficult to understand a way to fold in accordance with the diagrams. This paper proposes an approach to find the next step how to do the folding operation, especially for origami beginners. First, a method of detecting the folding operation based on camera images is been detected by canny edge detection. Then, in order to get the next operation camera image is been compare with the database images with the help of Bag of a visual word and Speed up robust features(SURF) detector to detect the key points by finding out the nearest neighboring distance ration (NNDR) measures to find out the similarities. 2016 Authors. -
Degradation of azodyes in wastewater by using hydrodynamic cavitation technique
The organic waste water discharged from various industries consists of large amounts of dyes & cyanides & other toxic carcinogenic pollutants which are harmful to human health & ecosystem. Release of carcinogenic dyes is hazardous & has a detrimental effect on the well being of an individual. The present work is focussed at finding the viability of hydrodynamic cavitations process in the degradation of dyes. To study the degradation, influence of various parameters on degradation rate has been studied. BEIESP. -
Removal of Struvite in Wastewater Using Anammox Bacteria
Struvite precipitation in wastewater has proved to be an effective method in treating wastewater and has helped in the recovery of ammonia nitrogen and phosphate phosphorus. Nutrient recovery from wastewater has become a new trend attracting the interests of several researchers. Extraction of the nutrients based on struvite crystals as nutrition sources from wastewater has been acknowledged as a need of the hour solution to tackle the water pollution issue. This review focuses on the featured characteristics of struvite as a chemical fertilizer for plant and the struvite formation process related to physiochemical conditions in wastewaters. In the present work, struvite precipitation in the actual swine wastewater is studied by strategically controlling aeration, pH, and mixing of anammox bacteria. The effect of organic solids in the wastewater has also been studied. Laboratory experiments were conducted by optimizing pH value. pH was found to be an important parameter in the simultaneous removals of ammonium nitrogen and orthophosphate. This work reveals that the struvite removal from wastewater can be reduced to 80% using anammox bacteria. Springer Nature Singapore Pte Ltd. 2022. -
Defluoridation of Drinking WaterFluoride Wars
Fluorine is also known as two-edged sword. At lower doses, it influences tooth by inhibiting tooth caries, while in high doses, it causes dental and skeletal fluorosis. It is known that some quantity of fluoride is important for the formation of tooth enamel and mineralization in tissues. The present work aims at providing safe and potable water to rural areas where this element has created a menace. This work also suggests the use of few adsorbents such as paddy husk and coir pith which are affordable and removes fluorine to greater extent. The study concludes that materials which are used as adsorbents and can be safely inculcated as fluorine removal adsorbents which help people to have safe potable water. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Taxonomic revision and molecular phylogeny of flemingia subgenus rhynchosioides (Leguminosae)
A taxonomic revision of Flemingia subg. Rhynchosioides based on morphology and molecular information (matK and ITS) is presented. The subgenus comprises six herbaceous taxa (F. gracilis, F. mukerjeeana, F. nilgheriensis, F. rollae, F. tuberosa and F. vestita). All species except F. vestita are endemic to India. Morphological evidence and molecular phylogeny revealed that the subgenus is monophyletic. Nevertheless, the systematic position of F. tuberosa remains unclear on account of its unique ecology and inflorescence. A new species, F. mukerjeeana, is described and four binomials, namely F. gracilis, F. nilgheriensis, F. tuberosa and F. vestita have been lectotypified. Furthermore, all species have been described, illustrated and their ecology discussed. A taxonomic key including the recently described species from Thailand, F. sirindhorniae, is also provided for easy identification. 2019 Naturalis Biodiversity Center. -
Capitalizing on diversity: Role of entrepreneurial and firm attributes in rural MSMEs financial accessibility
Consistent access to credit from formal financial institutions has been a significant challenge for micro-, small, and medium-sized enterprises (MSMEs) in rural areas. Despite contributing to a majority of the workforce in the economy, their failure rates continue to rise. These often indicate an inadequacy in internal determinants, such as limited access to infrastructure, inefficient managerial competencies, low entrepreneurial orientation, and other firm-related attributes. This article investigates how entrepreneurial and firm-specific traits influence the financial accessibility of rural MSMEs in the northeastern state of Assam in India while also considering the role of credit rationing. The current study data were collected from MSME entrepreneurs and analyzed using thematic analysis to explore the variables impacting credit accessibility. The results reveal that entrepreneurial (motivation, education, entrepreneurial orientation) and firm characteristics (firm size, infrastructure, technical know-how) are critical in assessing lenders perception toward borrowers in the complex loan processes. 2025 International Council for Small Business. -
Intelligent Manufacturing Components, Challenges, and Opportunities
Intelligent Manufacturing shows transformative paradigms in the manufacturing industry; leveraging advanced technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and robotics, to develop highly automated and adaptive production systems. This chapter outlines the Intelligent Manufacturing process, including its key principles, components, challenges, and opportunities. The combination of Machine Learning (ML) techniques and AI enables decision-making, real-time optimisation, and predictive analytics of manufacturing processes, productivity, and quality of products. Robotics and IoT devices play critical roles in enabling automation, data collection, and connectivity within Intelligent Manufacturing environments. Additionally, Digital Twin technology facilitates virtual simulation, modelling, and optimisation of production systems. While Intelligent Manufacturing offers significant benefits, it also presents challenges viz. high investments, integration complexity, and workforce reskilling requirements. Overcoming the challenges requires a holistic approach involving collaboration between industry stakeholders, government agencies, academia, and technology providers. Overall, Intelligent Manufacturing represents a promising future for the manufacturing industry, offering opportunities for innovation, competitiveness, and sustainable growth in a rapidly evolving global economy. 2025 selection and editorial matter, Alka Chaudhary, Vandana Sharma, and Ahmed Alkhayyat individual chapters, the contributors. -
ESG Narrative Quality in Green Bond Disclosures: Implications for Risk Perception, Transparency, and Market Trust
This research evaluates the extent to which firms green bond disclosures create and convey a meaningful representation of their Environmental, Social, and Governance (ESG) commitments. Additionally, this research explores how investors distinguish between disclosures that represent genuine commitment to sustainability and those that may be indicative of greenwashing, and how such distinctions impact their assessment of an issuers credibility as well as the issuers performance subsequent to the issuance of a green bond. The methodology employed in this research employs a convergent mixed-methods approach that combines quantitative methods (Natural Language Processing (NLP), financial modeling, etc.) with qualitative methodologies (case studies, interviews). The NLP methodology employed in this research includes sentiment analysis, topic modeling, and ambiguity measurement in order to determine the tone, thematic content, and linguistic clarity of the disclosure texts. Subsequently, the results of the NLP methodologies are correlated with firm level outcomes using cross validated partial least squares regression (PLS-R), event study methodologies, and one way ANOVA to test for temporal and industrial variability. Finally, the results of the computational and financial methodologies are supplemented by qualitative case studies and interviews to provide context for the patterns identified in the computational and financial methodologies. In summary, the results of this research demonstrate that firms that communicate in a clear, balanced, and verifiable manner experience better market reaction and more favorable accounting results subsequent to the issuance of a green bond than do firms whose communications are vague, overly optimistic, or lacking in consistency. Conversely, the findings suggest that investors have become increasingly sensitive to potential greenwashing and therefore are less likely to respond favorably to communications characterized by the aforementioned characteristics. 2025 by the authors. -
Technology Transfer, Innovation, and Equitable Development: A Business-Centric Approach
In an era of rapid technological innovation, significant global disparities in access persist, impeding sustainable development. This chapter examines technology transferthe dissemination of knowledge and tools across bordersas a catalyst for equitable growth. Analyzing mechanisms such as licensing, joint ventures, and FDI, it elucidates how businesses can utilize these strategies for market expansion addressing barriers including restrictive intellectual property regimes, cultural incongruities, and regulatory fragmentation. Case studies, encompassing Kenya's M-Pesa mobile payments and COVID-19 vaccine inequities, underscore the dual potential for empowerment and exploitation. The chapter posits the necessity for ethical frameworks that balance profit and equity, urging stakeholdersgovernments, corporations, and international bodiesto implement tiered pricing, reform IP laws, and invest in local capacity. Prioritizing inclusive innovation, technology transfer can mitigate disparities, unlock $12 trillion in market opportunities by 2030, ensuring progress benefits to humanity. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Precision Corn Price Prediction with Advanced ML Techniques
In the ever-evolving corn market, accurate price prediction is imperative for informed decision-making. This research introduces an innovative predictive model that integrates and external factors to enhance forecasting accuracy in the corn market. By exploring historical trends, comparing machine learning algorithms, and employing advanced feature selection methods, the study addresses the complexities of the corn market, emphasizing economic indicators, geopolitical events, and demand-supply dynamics. Informed by a literature review, the research underscores the necessity of dynamic models in corn price forecasting. Utilizing machine learning models such as linear regression, random forest, SVM, Adaboost, and ARIMA, coupled with the interpretability of SHAP values, the study aims to improve prediction accuracy in the corn market. With a robust methodology and comprehensive evaluation metrics (MAE, RMSE, MAPE), the research contributes valuable insights into corn market dynamics, providing a variable dictionary for clarity and emphasizing the strategic implications of the superior random forest model for stakeholders in the corn sector. 2024 IEEE. -
Indias role in kazakhstans multi-vector foreign policy
?fter the disintegration of the Soviet Union, Kazakhstans economy was weak since most of the industrial en-terprises were located in Russia. To attain economic growth, Kazakhstan crafted a unique foreign policy known as the multi-vec-tor foreign policy, which facilitated an easy inflow of direct foreign investments into the state economy. After economic liberalization in 1991, India took a serious interest in Cen- tral Asia, and since then the two nations have come a long way marked by complex interde-pendence in the international arena. They have demonstrated a successful and sus-tained upward trend in their bilateral relationship through soft power, trade and long-standing historical connections. Thus, the prospects of mutual cooperation between Central Asia, particularly Kazakhstan, and India are quite promising in the near future. 2021, CA and C Press AB. All rights reserved. -
Exploring silenced subaltern voices of three-fold oppressed dalit women in Akkarmashi by Sharankumar Limbale : A postcolonial reading /
Roots International Journal Of Multidisciplinary Researches, Vol.2, Issue 3, pp.13-15, ISSN No: 2349-8684. -
Diaspora Experience Between the Creation and the Creator : A Closer Look at the Diaspora Connected Character in Anita Desai's 'Fasting, Feasting'
Quest International Multidisciplinary Research Journal, Vol-1 (2), pp. 83-86. ISSN-2278-4497 -
Enhancing Cybersecurity: Machine Learning Techniques for Phishing URL Detection
Phishing attacks exploit user vulnerabilities in cybersecurity awareness by tricking them to fake websites designed to steal confidential data. This study proposes a method for detecting phishing URLs using machine learning. The proposed method analyzes various URL characteristics, such as length, subdomain levels, and the presence of suspicious patterns, which are key indicators of phishing attempts. Gradient Boosting was selected due to its robustness in handling complex, non-linear relationships between features, making it particularly effective in distinguishing between legitimate and phishing URLs, by evaluating the Gradient Boosting classifier on a dataset with 10,000 entries and 50 features, the method achieves an accuracy of 99%.This approach has the potential to enhance web browsers with add-ons or middleware that alert users from potential phishing sites which will be based solely on URL. 2024 IEEE.