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Dirichlet Feature Embedding with Adaptive Long Short-Term Memory Model for Intrusion Detection System
Intrusion Detection System is applied in the network to monitor the network activity and detect the intruder to protect the user data. Various existing models have been applied in the intrusion detection system and have the limitations of high False Alarm Rate (FAR), overfitting problem and data imbalance problem. In this research, Dirichlet Feature Embedding based Adaptive Long Short Term Memory (DFE-LSTM) model is proposed to improve the efficiency of the intrusion detection. The Dirichlet Feature Embedding (DFE) method is applied to effectively represent the feature to analysis the multi-variate of the input data. The enhanced Adaptive Long Short Term Memory (ALSTM) model is applied to select the optimal parameter for the LSTM model to improve the learning rate. The proposed DFE-ALSTM model is compared to three datasets such as UNSW-NB15, NSL-KDD and Kyoto 2006+ for evaluate the efficiency. The proposed DFE-ALSTM model has the accuracy of 94.32 % and existing NB-SVM has 93.75 % accuracy in intrusion detection on UNSW-NB15 dataset. 2022, Success Culture Press. All rights reserved. -
Multifarious pigment producing fungi of Western Ghats and their potential
Concerns about the negative impacts of synthetic colorants on both con-sumers and the environment have sparked a surge of interest in natural col-orants. This has boosted the global demand for natural colorants in the food, cosmetics and textile industries. Pigments and colorants derived from plants and microorganisms are currently the principal sources used by mod-ern industry. When compared to the hazardous effects of synthetic dyes on human health, natural colors are quickly degradable and have no negative consequences. In fact, fungal pigments have multidimensional bioactivity spectra too. Western Ghats, a biodiversity hotspot has a lot of unique eco-logical niches known to harbor potential endophytic pigment-producing fungi having enumerable industrial and medical applications. Most of the fungi have coevolved with the plants in a geographical niche and hence the endophytic associations can be thought to bring about many mutually ben-eficial traits. The current review aims to highlight the potential of fungal pigments found in the Western ghats of India depicting various methods of isolation and screening, pigment extraction and uses. There is an urgent need for bioprospecting for the identification and characterization of ex-tremophilic endophytic fungi to meet industry demands and attain sustain-ability and balance in nature, especially from geographic hotspots like the Western Ghats. 2022 Horizon e-Publishing Group. All rights reserved. -
A novel free space communication system using nonlinear InGaAsP microsystem resonators for enabling power-control toward smart cities
Nowadays, the smart grid has demonstrated a great ability to make life easier and more comfortable given recent advances. This paper studies the above issue from the perspective of two important and very useful smart grid applications, i.e., the advanced metering infrastructure and demand response using the instrumentality of a set of well-known scheduling algorithms, e.g., best-channel quality indicator, log rule, round robin, and exponentialproportional fairness to validate the performance. To increase the data transmission bandwidth, a new concept of optical wireless communication known as free-space optical communication (FSO) system based on microring resonator (MRR) with the ability to deliver up to gigabit (line of sight) transmission per second is proposed for the two studied smart grid applications. The range between 374.7 and 374.79THz frequency band was chosen for the generation of 10 successive-carriers with a free spectral range of 8.87GHz. The ten multi-carriers were produced through drop port of the MRR. The results show up to 10 times bandwidth improvement over the radius as large as 600m and maintain receive power higher than the minimum threshold (? 20dBm) at the controller/users, so the overall system is still able to detect the FSO signal and extract the original data without detection. 2019, Springer Science+Business Media, LLC, part of Springer Nature. -
Heart Disease PredictionA Computational Machine Learning Model Perspective
Relying on medical instruments to predict heart disease is either expensive or inefficient. It is important to detect cardiac diseases early to avoid complications and reduce the death rate. This research aims to compare various machine learning models using supervised learning techniques to find a better model that gives the highest accuracy for heart disease prediction. This research compares standalone and ensemble models for prediction analysis. Six standalone models are logistic regression, Naive Bayes, support vector machine, K-nearest neighbors, artificial neural network, and decision tree. The three ensemble models include random forest, AdaBoost, and XGBoost. Feature engineering is done with principal component analysis (PCA). The experimental process resulted in random forest giving better prediction analysis with 92% accuracy. Random forest can handle both regression and classification tasks. The predictions it generates are accurate and simple to comprehend. It is capable of effectively handling big datasets. Utilizing numerous trees avoids and inhibits overfitting. Instead of searching for the most prominent feature when splitting a node, it seeks out an optimal feature among a randomly selected feature set in order to minimize the variance. Due to all these reasons, it has performed better. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Building Smarter Systems with Advanced Computational Techniques
The biological data analysis is a key approach that uses the genetic, transcriptomics, proteomics, metabolomics, or clinical data to discover diseases. Diabetes and leukemia are two independent medical disorders, but research has found that people with type 2 diabetes have a 20% higher chance of developing blood malignancies such as acute leukemia, showing a link between the two. Early identification of these disorders by studying biological datasets is critical for providing prognostic information. However, the class imbalance and high dimensionality problems in Machine Learning (ML)based techniques have often degraded effective analysis of clinical and genomic datasets for disease detection. This paper focuses on developing an efficient clinical decision support system using advanced metaheuristic and ML algorithms to solve class imbalance and high dimensionality problems. The first stage of the proposed approach utilizes an optional data augmentation and another pre-processing method for outlier detection and removal using Modified Z-Score (MZS) based on the Median Absolute Deviation (MAD) metric. Then, the optimal features/genes are selected using a hybrid Firefly Pearson's Correlation Coefficient (FPCC)-based Feature/Gene Selection method to reduce the higher feature dimensionality problem. Once the features/genes are selected, the proposed Ladybug Beetle Optimized Universum Learning-based Twin Boosted Adaptive Support Vector Machine (LBO-ULTBASVM) classifier detects the disease with reduced model complexity and error rates. LBO-ULTBASVM is developed by improving the Twin Support Vector Machine (TSVM) classifier by integrating the Universum Learning, Ladybug Beetle Optimization (LBO), and XGBoost for solving the class imbalance problem, reducing training time and improving disease accuracy. Experiments are conducted using PIMA Indians Diabetes and GSE9476 Leukemia datasets and the outcomes indicated that the LBO-ULTBASVM-based model increases the diabetes and leukemia detection accuracy with reduced model complexity and processing time. 2025 IEEE. -
Polyurethane nanocomposites for supercapacitor applications
Polymer nanocomposites have received a lot of interest recently in materials research as they display a variety of distinct properties compared to those of their counterpart polymer micro-composites, whose matrices include the same inorganic components. The flexible features of polyurethane (PU) nanocomposites, which may be easily adjusted to fulfill the specific needs in energy storage, have led to the rapid development of these materials in recent years. Numerous types of functional nanofiller integration have led to the advancement of PU-based nanocomposites. Details on PU nanocomposites' synthesis, characteristics, and uses in supercapacitors are covered in this chapter. There have been several approaches explored for the synthesis of various PU nanocomposites, including electrospinning, dip-coating, spray coating, and one-step carbonization. Recent advancements in the use of PU nanocomposites as supercapacitors, along with their challenges and possibilities in the future, are also discussed herein. This chapter also reviews recent developments in smart supercapacitors, including their various properties such as long-lasting cycling stability, excellent specific capacitance, high energy density, and good capacitance retention. Functions of supercapacitors include self-healing, shape memory, shape editing, and photodetection, along with specific emphasis on their recyclability and recoverability. 2026 Elsevier Ltd. All rights reserved. -
A Review of Optimization Algorithms Used in Proportional Integral Controllers (PID) for Automatic Voltage Regulators
The voltage in electrical grids is maintained at its nominal value by automatic voltage regulators (AVR). In AVR systems, proportional-integral-derivative (PID) is the most popular controllers due to their robust performance and simplicity. Controlling the parameters of proportional-integral-derivative (PID) controllers, which are used in AVR technology, is a nonlinear optimization problem. Optimization issues are of great importance to both the industrial and scientific worlds. A PID controller's objective function is designed to minimize the settling time, rise time, and overshoot of the step response of the resultant voltage. This paper presents the performance comparison of six optimization algorithms such as Enhanced Crow Search Algorithm (ECSA-PID), Slime Mould algorithm (SMA-PID), Future Search Algorithm (FSA-PID), Whale Optimization Algorithm (WOAPID), Equilibrium Optimizer (EO-PID) and Archimede's Optimization algorithm (AOA-PID) used in recent literatures. The Electrochemical Society -
Optimal design of controller for automatic voltage regulator performance enhancement: a survey
For regulating the Synchronous Generator (SG) output voltage, the Automatic Voltage Regulator (AVR) system is a significant device. This work propounds a survey on Optimization Algorithms (OAs) utilized for tuning the controller parameters on the AVR system. A device wielded for adjusting the SGs Terminal Voltage (TV) is named AVR. A Controller is utilized for improving stability and getting a superior response by mitigating maximum Over Shoot (OS), reducing Rise Time (RT), reducing Settling Time (ST), and enhancing Steady State Error (SSE) since output voltage has a slower response and instability. The controllers utilized here are Proportional-Integral-Derivative (PID), Intelligent Controller (IC), along with Fraction Order PID (FOPID). Owing to the occurrence of time delays, nonlinear loads, variable operating points, and others, OAs are wielded for tuning the controller. (a) Particle Swarm Optimization (PSO), (b) Genetic Algorithm (GA), (c) Gray Wolf Optimizer (GWO), (d) Harmony Search Algorithm (HSA), (e) Artificial Bee Colony (ABC), (f) Teaching Learned Based Optimization (TLBO), et cetera are the various sorts of OA. For enhancing the TV response along with stability, various OAs were tried by researchers. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
A hybrid technique linked FOPID for a nonlinear system based on closed-loop settling time of plant
Wind and hydroelectric systems are more cost-effective and environmentally beneficial. A hybrid technique is proposed for the fractional-order proportional-integral-derivative (FOPID) controller to regulate the wind and hydro system. The proposed hybrid technique combines the feedback-artificial-tree (FAT), and atomic-orbital-search (AOS); together known as FAT-AOS approach. The proposed technique is utilized to decide the optimum controller parameters, and it guarantees system constancy in large disturbances using less computation and overshoot by restraining the parameter variation. The FAT is used to predict the optimum gain parameter of FOPID, and minimizing the system error is accomplished with the AOS approach. The performance metrics are peak time, rise time, settling time, and peak overshoot, are analyzed. The performance of the proposed method is done in the MATLAB platform. The simulation result of proposed approach for the rise time as 0.001 sec, settling time is 0.012 sec, and the overshoot percentage is 0.02 %. By comparing the existing methods, like Ant lion optimizer (ALO), Salp swarm algorithm (SSA), Particle swarm optimization (PSO), the proposed approach rise time and settling time overshoot, is less. The comparison proves that the proposed system delivers improved outcome than existing systems. 2024 -
The Hubble tension: Change in dark energy or a case for modified gravity?
Recently, much controversy has been raised about the cosmological conundrum involving the discrepancy in the value of the Hubble constant as implied by Planck satellite observations of the CMBR in the early Universe and that deduced from other distance indicators (for instance using standard candles like supernovae, tip of the red giant branch, etc.) in the present epoch. The Planck estimate is about 67km-1Mpc-1, while that deduced from distance indicators at the present epoch is around 73-74km-1Mpc-1. Also the independent determination of the local value of the Hubble constant based on a calibration of the tip of the red giant branch and applied to Type Ia supernovae found a value of 69.8km-1Mpc-1. Here we propose a modification of the gravitational field on large scales as an alternate explanation for this discrepancy in the value of the Hubble constant as implied in the above-mentioned method, i.e., by Planck observations of the CMBR in the early Universe, and that deduced from other distance indicators in the present epoch. 2021, Indian Association for the Cultivation of Science. -
Reimagining Future of Future by redesigning Talent Strategy in the Age of Distraction and Disruption
The coronavirus 2019 (COVID-19) pandemic promoted the development of Industry 4.0 leading to the fifth industrial revolution (Industry 5.0). It brought in new ways of working and the role of the office in the future. It redesigned the workplace to support organizational priorities and resize the footprint creatively. Digitalization and globalization have sparked radical shifts in how employees live and work. In an age of digital disruption, companies and HR leaders are forced to revise organizational on how they organize, recruit, develop, manage and engage the 21st-century workforce. The big questions are: how can HR help business leaders reconstruct the workforce of the future? What effort has the company take to change future work and their workforce today so that it looks different 15 years later? Organizational agility, careers and learning disruption, talent disruption, rethinking performance management and people analytics in addition to creating the right structure, analysis, and standardized people metrics are the key to success and critical drivers to design talent strategy. This study aims to identify the magic ingredient (or strategies) behind managing an organization's talent in creating business success. We further examined and mathematically modelled these strategies in attracting and retaining high-quality employees, developing their skills, and continuously motivating them to improve their performance in the age of distraction and disruption. 354 employees from IT companies participated in the survey. The findings of the study show, as expected, that a compelling employer brand is the most effective talent management strategy of all when it combines three key drivers: organizational culture, organization goodwill and competition for talent. Gender was statistically, significantly and positively associated with the imperatives to reset the future of work agenda. 2021. All Rights Reserved. -
Key challenges in developing and executing higher education learners' learning outcomes
This chapter examines higher education institutions' complex obstacles in developing and implementing effective learning outcomes. It emphasizes the need for outcomes that include subject-specific and general skills, meet students' diverse requirements, align with market demands, and incorporate emerging technologies. To facilitate student success in the 21st century, institutions must address these. It examines multidisciplinary programs, technology integration, faculty training, and student participation in outcome formation. It proposes enhancing outcomes through emerging technologies, social and emotional learning, global citizenship education, and entrepreneurship education, emphasizing student-centred approaches. Effective learning outcomes are essential for fostering student success in a constantly changing environment. Case studies from India, the United Kingdom, and the United States provide insights, emphasizing India and lessons from the US and UK experiences. 2024, IGI Global. All rights reserved. -
Environmental Management: Pragmatic Suitability of Low Cost Activated Carbon in Lead (II)Ion Removal by Continuous Mode of Adsorption
Heavy metals such as chromium, lead, and arsenic are usually present in trace amounts in natural waters but many of them are toxic even at very low concentrations. An increasing quantity of heavy metals in our resources is currently an area of greater concern, especially since a large number of industries are discharging their metal containing effluents into freshwater without any adequate treatment. Activated carbons show a significant ability in removing heavy metal ions from an aqueous solution by adsorption, which has been examined by many researchers. Activated carbon derived from Manilkarazapota tree-wood (MZTWAC), which was found to be a suitable adsorbent for the removal of lead ions through continuous adsorption mode, was examined in this paper. A breakthrough curve has been plotted to find the effect of initial concentration and adsorbent bed height in the adsorption of lead (II)ion through MZTWAC. The breakthrough time and the saturation time increased as the initial concentration increased from 40 mg.L-1 to 60 mg.L-1. The saturation time was in the incremental mode when the bed height was increased from 5 cm to 7 cm bed thickness for 40 mg.L-1 concentration. Adams-Boharts model perfectly fits with this fixed-bed column in the removal of lead(II) from an aqueous solution using MZTWAC. Activated carbon derived from MZTWAC is better suited for the purpose of detoxifying metal-contaminated wastewater. 2021 Technoscience Publications. All rights reserved. -
Ethical living and work self efficacy beliefs of academicians of higher education in ASIA: A key determinant of one's belief in one's ability to achieve the desired result in a precise state of affairs
Ethical academicians are perfectly virtuous. They always strive for greater virtue and follow strictly the moral stands of their profession. The ethical living and self-efficacy are important to them because of being fair and honest in their academics. Determinants of ethics include knowledge, values, attitude and intention. The domain-specific framework developed by Verbeke et al. (2004) has been considered as fundamental for identifying the dimensionality of work Self-efficacy and ethical challenges of academicians. A comprehensive literature review is undertaken regarding the concept of work Self-efficacy to assess workers' confidence and their ethical living in the workplace. This article examines theoretically and analytically the antecedent processes and information cues involved in the formation of work self-efficacy. Theoretical and numerical analysis of the key determinants of work self-efficacy increases the understanding of moral values, truthful fair and honest. Factors which decisively affect ethical living were identified from literature collected from the academicians who are working in the Five Regions of Asia-Central Asia (Tajikistan, Uzbekistan, Kazakhstan, Turkmenistan, Kyrgyzstan) East Asia (China, Mongolia, North Korea, South Korea, Japan, Hong Kong, Taiwan, Macau) South Asia (Sri Lanka, Bangladesh, India, Afghanistan, Pakistan, Bhutan, Nepal, the Maldives) through Google classroom. Methods of Statistical Analysis of self-efficacy data are descriptive statistics, Pearson Correlation Coefficient and Kolmogorov-Smirvnos normality test and KruskalWallis one-way analysis of variance and Principal Component Analysis. Positive, mastery experiences give academicians a sense of accomplishment when they have faced a challenge ethically. Positive Zeal during Academic interaction, vicarious experiences that occur when academician see others succeed and feel an increased sense of their own ability to succeed. Sincere & deeper self, mingling with students, Social persuasion increase a teachers sense of confidence and ability to succeed. A proper plan of action has drawn special attention, and inferences pertaining to future research are discussed at the end of the critique. 2019, Sciedu Press. All rights reserved. -
Nurturing the Rudiments and Use Cases of Ongoing Natural Language Generation for a Future Profitable Business More Profitable
Decoding the world of artificial intelligence and its usage in the current intelligence landscape enhance bottom-up growth in building resilient global business. The areas of artificial intelligence (AI) concerned with human-to-machine and machine-to-human interaction. The Next Wave in AI-driven speech is Natural Language Generation (NLG). Natural Language Generation (NLG) is the use of artificial intelligence (AI) programming to produce written or spoken narrative from a dataset. NLG is related to computational linguistics, natural language processing (NLP) and natural language understanding (NLU). NLG research often focuses on building computer programs that provide data points with context. Sophisticated NLG software has the ability to mine large quantities of numerical data, identify patterns and share that information in a way that is easy for humans to understand. The speed of NLG software is especially useful for producing news and other time-sensitive stories on the internet. At its best, NLG output can be published verbatim as web content. The goal of Natural language generation (NLG) is to use AI to produce written or spoken narrative from a dataset. Therefore, this study aims to study how NLG enables machines and humans to communicate seamlessly, simulating human to human conversations and using NLG how organizations are building new customer experiences, monetizing information assets, introducing new offerings and streamlining operational costs. Therefore, the coverage of this chapter will answer to the industrialists and new start-ups. What can NLG do for business? and what are the future applications of NLG? 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Upskilling and Curating the Potentials of IoT Enabled Smart Cities: Use Cases and Implementation Strategies
The reason for opting the Internet of Things in the smart city system was to manage assets, resources and services efficiently and improve the operations across the city. This will be achieved by the inception of cognitive technologies, including the Internet of things (IOT). The IoT enabled Smart cities enables the utilities for improving transportation and accessibility, improve social services, promote sustainability, and give its citizens a voice. However, the barriers to smart cities are siloed, piecemeal implementations, growing expectations, uninformed citizens and shrinking budgets and little or no investment capital. Smart streetlights, lighting adapts to the activity on the street. Parking sensors provide real time information on an app where to find vacant parking spaces. Garbage sensors and automated waste collection are recent eras of smart cities. Overall it improves the operational efficiency and provides better quality of service. Thus, India thought of IoT enabled Smart cities which include housing, schools, offices and retail. In this paper, we examine significant aspects of an IoT infrastructure for smart cities, outlining the innovations implemented in the cities of India as use cases and Implementation Strategies. Exceptional attention is devoted to the potential applications of smart cities. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Global Governance of Artificial Intelligence: Ethical, Legal Challenges and Changes in Economy and Business
Artificial intelligence (AI) and global governance are an inclusive platform to discover the policy challenges worldwide augmented by artificial intelligence. The platform has three predominant subjects: AI and the global order, governance of AI, insights on the platform consider for mapping of AI futures. AI has great impact in revolution of geopolitical order and the reaction of multifaceted organizations which minimize AI risks and unpremeditated significances and its social aids are maximized through governance structures. It focusses on setups, collaborations, and tensions between different actors responsible for plan, deployment, support and governance of AI. AI improves the benefit for human well-being, productivity, social good, and safety with substantial risks for workers, developers, firms, and governments. The actors and organization begin to realize the ethical, legal, and regulatory challenges associated with AI. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Harnessing nanotechnology applications and solutions for environmental and climate protection-an overview
Nanotechnology is an emerging technology that has drawn considerable interest from environmentalists. Numerous nano techniques identify Nanotechnology applications as having the potential for imperative advantages and innovation. This work offers a wide-overview of the main beliefs that strengthen s nanotechnology. We focus on the potential applications of nanotechnology for environmental protection and management by thoroughly reviewing past literature. To our understanding, this is an academic, peer-reviewed work to deliver a systematic review of nano-activities in the areas of environmental and climate protection. Our study has been systematically arranged into two different groups (1) Potential applications of nanotechnology in r environmental protection and (2) The best part of Nanotechnology that combats Climate Change. For each of these cases, our contribution is twofold: First, in identifying the technical ways by which nanotechnology can solve environmental risks, and secondly, in briefly presenting its potential advantages. The paper ends with deliberation of challenges and operational barriers that technology needs to overcome to prove its commercial viability and for being adopted for commercial use. 2021 Author(s). -
Unlocking the potentials of using nanotechnology to stabilize agriculture and food production
In the face of alarmingly increasing climate change, agricultural sector is exposed to innumerable and unprecedented challenges globally. This has led to food insecurity worldwide and in order to achieve the required food security at the global level, various methods and techniques have been put forth by researchers from around the world for boosting crop production and ensuring sustainability. Advanced nano-engineering is found to be of great import in improving production in agriculture and increasing input efficiency and minimization of losses. The fertilizers and pesticides, used for increasing and protecting the crop production respectively, can gain not only specific but also wider surface area with the help of nanomaterials, which serve as exclusive agrochemical carriers and assure facilitation of nutrients to target areas with the help of delivery monitoring techniques. Nanobiosensors, an example of the wide ranging nanotools, scaffold the growth of high-tech agricultural farms and also stand proof for the practical and proposed applications of the nanotools in terms of agricultural inputs control and their management precision. Nanosensors the off-spring of the culmination of biology and nanotechnology has an increased potential level in sensing and identifying both the advantageous and adverse conditions of the environment. The other applications of nano-technology include nanofertiliers with release-control techniques for healthy growth and rich yield and productivity of crops, nano-based target delivery approach, also referred to as gene transfer technique, for improved quality of crops, nanopesticides for effective protection of crops and other nanomaterials for promotion of stress tolerance among plants and enhancement of quality of soil [4]. In our review paper, we intend sum up the recent research and studies on the nanotechnology's innovative uses in agriculture to cope up with the ever-increasing necessity for food and sustenance of environment. 2021 Author(s). -
Unraveling the Potential of Artificial Intelligence-Driven Blockchain Technology in Environment Management
Blockchain as an emerging technology provides a ray of hope to the most intensive environmental issues facing the planet. Blockchain with its decentralized business model has great relevance not only in the field of finance but also in environmental sustainability. The World Economic Forum has identified blockchain as a repair mechanism to the most challenging global environmental issues. It is a highly promising technology gaining traction in diverse fields. Blockchain through this technology unveils its capabilities as a decentralized ledger of all dealings across peer-to-peer networks, where participants can ratify transactions without any central authority. Blockchain technology is an indestructible electronic ledger of transactions designed to record and store everything of value in addition to financial transactions. Blockchain can ensure a shift to cleaner and more resource conserving decentralized solutions, unravel natural capital and to empower communities. This chapter attempts to study the applicability of blockchain in protecting and sustaining the global environment at various levels including life on land, life below the earth and climate changes. Deployment of blockchain technology is needed in areas like climate change, biodiversity conservation and healthy water bodies to overcome the threats they face. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.