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A Study of Simulated Working of A* and RRT* for Cargo Ship in ASVs
With the increased amount of algorithms for the path planning and collision avoidance of ASVs. The need for an unbiased protective path planning directs the need for decision in stochastic areas in the vast ocean for cargo ship. Autonomous surface vehicles should take appropriate decision on the path according to the dynamic environment and the obstacle that is before them. In some cases, environment, time, and size should be considered to acquire the fastest path and methods that could be suited for collision avoidance. This paper investigates the need for a well-known path planning method that has handled the situation based on the dynamic properties of the vehicle in the ocean. The simulated result shows a slight variation in their proposed path in terms of time and collision in terms of size. Therefore, using a realistic approach of the A* algorithm and the RRT*, we can handle the scenario of dynamic environment. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Collaborative intrusion detection system in cognitive smart city network (CSC-Net)
Smart environment is about incorporating smart thinking in the environment and implementing the technical intervention that improvise the city's environment. Artificial intelligence (AI) provides solutions in huge technological issues in various aspects of day-to-day life such as autonomous transportation, governance, healthcare, agriculture, maintenance, logistics, and education that are automated, managed, controlled, and accessed remotely with the aid of smart devices. Cognitive computing is denoted as a next-generation AI-dependent method that gives human-computer interactions with personalized services that replicate manual behavior. Simultaneously, massive data is generated from the applications of the smart city like smart transportation, retail industry, healthcare, and governance. It is necessary to obtain a reliable, sustainable, continuous, and secure framework in the cloud centralized infrastructure. In this research article, the authors proposed the architecture of cognitive smart city network (CSC-Net) that defines how data are collected from applications of smart city and scrutinized by cognitive computing. This research article predicts the mobile edge computing solution (MEC) that permits node collaboration between internet of things (IoT) devices for providing secure and reliable communication among smart devices and fog layer, conversely fog layer and cloud layer. This proposed work helps to reduce the excessive traffic flow in smart environment with the support of node to node communication protocols. Collaborative-dependent intrusion detection system (C-IDS) is proposed to solve the data security issues in fog and cloud layers. Copyright 2021, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. -
User request scheduling for multimedia resource using improved fuzzy logic with hybrid lyapunov based algorithm in hybrid cloud
The hybrid cloud provides vast opportunity to access the varied resources for effective provisioning of services to its users. The proposed scheduling algorithm uses the K-Nearest Neighbor(KNN) to locate the current location of the user and the nearest available computing resource. The Improved Fuzzy Logic (IFL) is applied for improving the resource balancing so that the resources are better utilized for the scheduling process. The wastage of resource usage and ideal resource are reduced considerably. The HLA scheduling is applied with the IFL, and based on the waiting of the jobs; the slots are allocated with jobs for execution. All the jobs are executed successfully with minimized execution time and makespan of the workflow application request. The performances of three algorithms are measured with parameters such as execution time, makespan time, in millisecond (ms). The execution speed is measured as throughput in MIPS (Millions of Instruction per Second). The resource utilization and usage of VMs are increased in the proposed scheduling algorithm resulting in a less number of ideal resources and reduced application cost. BEIESP. -
3D Modelling and Rendering Using Autodesk 3ds Max
This is outlined how to create a 3D custom kitchen design, including how to set up the sources, details, work with managing various modifiers like edit poly, slice, mesh select, turbo smooth, lattice, bend, shell modifier, so to provide the kitchen an authentic appearance. The method materials are fitted to the model output, together with illuminating the environment leveraging Arnold lights that are intended to be utilized with this renderer only. It has features that are optimised for rendering with Arnold. Procedures and methods regarding rendering are indeed specified. The final rendering was made out of several drawings. Our report's intention is to develop a kitchen design that enriches models with materials and ample shapes from standard extended primitive along with the mostly utilization of pro-boolean. Finally, a material editor was used to improve the model. target illumination, too. 2023 IEEE. -
Affecting computing in multimodal mobility
Computational models that simulate human emotions have witnessed a substantial development in recent years for widening the spectrum of applications. Emotional computation is becoming crucial in human-to-computer interactions with exponential growth of artificial intelligence. Normally referred to as emotion recognition, it is widely believed that the prospective detection of a person 's emotional state of mind should be computed from their facial expressions. Face-movement combinations may express many different emotion types, for instance, hate, anger, panic, joy, grief, surprise, shock, to name a few. The goal and emphasis of this manuscript is the deployment of different algorithms and computation models for emotions. Considerable advancements in this domain of emotion recognition can be made through AI model development that discusses the challenges of the system and Facial Action Coding as an integral part of the models. 2023, IGI Global. All rights reserved. -
Modeling requirements with diabetes using supervised machine learning techniques
Diabetes is characterized by either insufficient or inefficient insulin production by the body. High blood glucose levels result from this, which over time can harm a number of tissues and organs in the body. Diabetes can be brought on by a specific age, obesity, inactivity, insufficient physical activity, inherited diabetes, lifestyle, poor diet, hypertension, etc. This chapter explores modeling requirements with diabetes using supervised machine learning techniques. 2023, IGI Global. All rights reserved. -
Revolutionizing Circular Business Practices with Waste Reduction and Resource Optimization
The concept of the circular economy (CE) offers a transformative solution to pressing global challenges such as resource depletion, waste generation, and environmental degradation. By shifting from the traditional linear take-make-dispose model to a closed-loop system, the CE principles aim to enhance resource efficiency and sustainability. This paper proposes a Waste Reduction and Resource Optimization (WRRO)-oriented circular business model, offering a comprehensive theoretical framework to guide businesses in optimizing resource utilization and reducing waste. Through the exploration of academic literature and a practical case study, the paper illustrates how businesses can effectively transition to circular business models. It also addresses the challenges businesses face during implementation, providing actionable insights for both theory and practice. The papers key contribution lies in integrating circular economy principles with resource efficiency strategies, offering a novel approach that supports both environmental sustainability and economic performance. 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Bioactive Compounds and Biological Activities of Lotus (Nelumbo nucifera Gaertn.)
Nelumbo nucifera Gaertn. (Nelumbonaceae A. Rich.) is a beautiful aquatic flowering plant with a subterranean rhizome. With a vast array of culinary applications and a storehouse of bioactive compounds in its plant parts, N. nucifera functions as both an underground food crop and a valuable medicinal plant. With a more than 7,000-year history of cultivation, this plant is one of the few aquatic plants used as a vegetable. N. nucifera possesses copious amounts of alkaloids and flavonoids as phytochemicals, along with various other derivatives. The rhizome is consumed as a vegetable since it has more carbohydrates, proteins, and vitamins, and it also possesses phytocompounds that exhibit immunomodulatory, antiviral, and antioxidant properties. Many countries in Asia use N. nucifera starch as a major culinary ingredient. To date, many phytochemicals isolated from this plant are used in many medicinal systems, including traditional, Ayurvedic, herbal, and oriental medicine. The extracts of various organs of this plant are used to treat numerous types of cancers, cardiac diseases, liver ailments, diabetes, and nervous disorders. The flower extracts are effective against fever, adipsia, cholera, and diarrhea. Eaten raw or puffed, lotus seeds are high in protein and contain minerals like calcium, phosphorus, iron, and potassium. The seeds are used as antibiotics to cure skin diseases like leprosy. Chinese medicine uses lotus seeds to treat renal and cardiac problems. Accordingly, N. nucifera is employed in food, medicine, culture, and religion. Furthermore, N. nucifera is an excellent environmental adapter and has the capacity to modify its resistance to environmental stress in order to adapt to a variety of abiotic stresses including flooding, extremely high temperatures, salt, low light, and heavy metals. It can therefore be grown in a variety of environments. Although this aquatic crop is restricted to an extensive geographical region and has a huge variety of cultivars, many parts of the world are still uninformed about this crop. Therefore, it is crucial to comprehend the medicinal and nutritional benefits of this tuberous crop in order to investigate it as a potential replacement for present-day food crops as well as a source of medicine. In order to effectively utilize this aquatic underground crop, this chapter aims to embody the nutritional advantages, traditional uses, phytochemistry, and bioactivity of the phytocompounds from the various parts of N. nucifera. It also emphasizes lotus breeding to date, applications as food, cultural aspects, and future production of potential N. nucifera underground crops of the highest quality. 2023, Springer Science and Business Media B.V.. All rights reserved. -
Bioactive Compounds and Biological Activities of Lotus (Nelumbo nucifera Gaertn.)
Nelumbo nucifera Gaertn.Nelumbo nucifera Gaertn.Lotus (Nelumbonaceae A. Rich.) is a beautiful aquatic flowering plant with a subterranean rhizome. With a vast array of culinary applications and a storehouse of bioactive compounds in its plant parts, N. nucifera functions as both an underground food crop and a valuable medicinal plant. With a more than 7,000-year history of cultivation, this plant is one of the few aquatic plants used as a vegetable. N. nucifera possesses copious amounts of alkaloids and flavonoids as phytochemicals, along with various other derivatives. The rhizome is consumed as a vegetable since it has more carbohydrates, proteins, and vitamins, and it also possesses phytocompounds that exhibit immunomodulatory, antiviral, and antioxidant properties. Many countries in Asia use N. nucifera starch as a major culinary ingredient. To date, many phytochemicals isolated from this plant are used in many medicinal systems, including traditional, Ayurvedic, herbal, and oriental medicine. The extracts of various organs of this plant are used to treat numerous types of cancers, cardiac diseases, liver ailments, diabetes, and nervous disorders. The flower extracts are effective against fever, adipsia, cholera, and diarrhea. Eaten raw or puffed, lotus seeds are high in protein and contain minerals like calcium, phosphorus, iron, and potassium. The seeds are used as antibiotics to cure skin diseases like leprosy. Chinese medicine uses lotus seeds to treat renal and cardiac problems. Accordingly, N. nucifera is employed in food, medicine, culture, and religion. Furthermore, N. nucifera is an excellent environmental adapter and has the capacity to modify its resistance to environmental stress in order to adapt to a variety of abiotic stresses including flooding, extremely high temperatures, salt, low light, and heavy metals. It can therefore be grown in a variety of environments. Although this aquatic crop is restricted to an extensive geographical region and has a huge variety of cultivars, many parts of the world are still uninformed about this crop. Therefore, it is crucial to comprehend the medicinal and nutritional benefits of this tuberous crop in order to investigate it as a potential replacement for present-day food crops as well as a source of medicine. In order to effectively utilize this aquatic underground crop, this chapter aims to embody the nutritional advantages, traditional uses, phytochemistry, and bioactivity of the phytocompounds from the various parts of N. nucifera. It also emphasizes lotus breeding to date, applications as food, cultural aspects, and future production of potential N. nucifera underground crops of the highest quality. Springer Nature Switzerland AG 2024. -
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Planetarism and eco humanism in the buddhist beat bards allen ginsberg and gary snyder an interdisciplinary thematic study on their literature philosophy and ecological perspectives
The Beat Generation, also known as the Beat movement, were a group of American writers who emerged in 1950s. Among its most influential members were Allen Ginsberg, Gary Snyder, Jack Kerouac, William Burrough, William Carlos Williams and Lawrence Ferlenghetti. What could be loosely described as the underlying philosophy was visionary enlightenment, Zen Buddhism, environmentalism and Amerindian culture. The Beat Generation invented a literary collage movement as a counter-brain wash method for reversing effect of Mass media-Military-Industrial-Communist-Capitalist-CIA-KGB disinformation reality image bank. A common theme that linked them together was a rejection of the newlineprevailing American middle class values, deterioration of the Planet s health, the newlinepurposelessness of modern society and the need for withdrawal and protest. The Beats have tried to break the restraints imposed on the western man s mind by the official ways of thinking. They find the official morality unacceptable and tried to arrive at metaphysical and ethical enlightenment through the methods adopted by the oriental thinkers like Gauthama Buddha, and Zen ascetics. They begin with the problems the western civilization is encountering, like the one of war and ecological degradation and use the concepts of oriental civilizations to find causes and remedies of the miseries people and the planet have been ecountering. The mechanistic paradigm underlying the industrial society gives way to the newlineviirealization that we belong to a living, self-organizing cosmos. General systems newlinetheory, emerging from the life sciences, brings fresh evidence to confirm ancient newlineindigenous teachings; the earth is live, mind is pervasive, all beings are our relations. newlineThe Beats rediscovered this perennial truth which changed our views about the planet newlineand its life systems. The beats were a product of the Second World War and of the cold war. -
Natech guide words: A new approach to assess and manage natech risk to ensure business continuity
The risk posed by natural hazards to the technological systems is known as Natech risk. It is different from the more widely known and studied risk posed by such sites to the environment and society. Though currently, available risk assessment techniques recognize Natech, the specific qualitative technique for Natech risk assessment and reduction has not yet been developed. After analyzing past data of Natech accidents, relevant guide words have been suggested in this study. These guide words will help anticipate Natech risk and visualize the Natech scenario. Once the Natech risk is identified, corresponding risk reduction measures can be taken to avoid possible Natech accidents and consequences. 2021 Elsevier Ltd -
Bridging neural technologies with financial decision-making in neurofinance
This book chapter delves into neurofinance, an interdisciplinary domain merging neuroscience, psychology, and financial economics to investigate the neural mechanisms driving financial decision-making. It highlights the role of brain regions such as the prefrontal cortex, amygdala, and striatum in processing emotions, risks, and rewards, alongside the influence of neurotransmitters like dopamine and serotonin. The chapter discusses technological tools like fMRI, EEG, and BCIs, emphasizing their application in studying biases, risk tolerance, and reward anticipation. Practical implications include personalized investment strategies, improved financial planning, and enhanced market stability. Addressing ethical concerns and methodological challenges, the chapter underscores the potential of neurofinance to transform financial systems by integrating neural insights with AI and emerging technologies for better decision-making. 2025, IGI Global Scientific Publishing. All rights reserved. -
Study of Low-Mass Stars and Brown Dwarfs In Star Forming Regions of Diverse Environments
The formation and evolution of low-mass stars and brown dwarfs is an intricate process orchestrated by the environmental conditions in which they form. As a natural byproduct of this process, circumstellar disks are formed, whose dynamic relationship with the environment plays a pivotal role in determining the fate of the star and the timescale for planet formation. While low-mass stars are a dominant product of the star formation process, brown dwarfs occupy a unique position, bridging the gap between newlinelow-mass stars and planets. In this thesis, we have examined the low-mass stars and brown dwarfs in young clusters located at different distances with diverse UV radiation felds and stellar densities to decode the role of environment in shaping the IMF, its inand#64258;uence on disk evolution and to understand the formation of brown dwarfs. We have targeted three young star forming regions for the newlinestudy namely and#963; Orionis, twin clusters IC 1848-East and West, and IC 1396 using deep multi-wavelength photometry as well as near-IR spectroscopy with 4m and 10m class facilities. For the and#963; Orionis cluster we used deep CFHT-WIRCAM near-IR data and the novel water-band photometry technique along with Gaia DR3 to identify the candidate low-mass members. Spectroscopic follow-up observations conducted with IRTF-SpeX validated the selection of the candidates by this technique with a 100% effcacy. We then compiled a comprehensive membership catalog for a mass range and#8764;19-0.004 Mand#8857;. The form of the stellar-substellar IMF was found to be consistent with other nearby star forming regions suggesting a lack of signifcant environmental inand#64258;uence. Further, we analysed the evolutionary class of the members based on the mid-IR slope of the SED to study their disk properties. We estimated the disk fraction of the low-mass sources to be consistent with other star form ing regions considering the age of the cluster. This showed that in this region, external photoevaporation does not play a major role in the inner disk evolution. -
Twins in diversity: Understanding circumstellar disc evolution in the twin clusters of W5 complex
Young star-forming regions in massive environments are ideal test beds to study the influence of surroundings on the evolution of discs around low-mass stars. We explore two distant young clusters, IC 1848-East and West located in the massive W5 complex. These clusters are unique due to their similar (distance, age and extinction) yet distinct (stellar density and far-ultraviolet radiation fields) physical properties. We use deep multiband photometry in optical, near-infrared and mid-infrared wavelengths complete down to the substellar limit in at least five bands. We trace the spectral energy distribution of the sources to identify the young pre-main sequence members in the region and derive their physical parameters. The disc fraction for the East and West clusters down to 0.1?M was found to be 2 per?cent (N = 184, N = 492) and 1 per?cent (N = 173, N = 814), respectively. While no spatial variation in the disc fraction is observed, these values are lower than those in other nearby young clusters. Investigating the cause of this decrease, we find a correlation with the intense feedback from massive stars throughout the cluster area. We also identified the disc sources undergoing accretion and observed the mass accretion rates to exhibit a positive linear relationship with the stellar host mass and an inverse relationship with stellar age. Our findings suggest that the environment significantly influences the dissipation of discs in both clusters. These distant clusters, characterized by their unique attributes, can serve as templates for future studies in outer galaxy regions, offering insights into the influence of feedback mechanisms on star and planetary formation. 2024 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. -
Protoplanetary disks around young stellar and substellar objects in the ? Orionis cluster
Understanding the evolution and dissipation of protoplanetary disks are crucial in star and planet formation studies. We report the protoplanetary disk population in the nearby young ? Orionis cluster (d? 408 pc; age ? 1.8 Myr) and analyse the disk properties, such as dependence on stellar mass and disk evolution. We utilize the comprehensive census of 170 spectroscopic members of the region refined using astrometry from Gaia DR3 for a wide mass range of ? 190.004 M? . Using the near-infrared (2MASS) and mid-infrared (WISE) photometries, we classify the sources based on the spectral index, into class I, class II, flat spectrum and class III young stellar objects. The frequency of sources hosting a disk with stellar mass <2 M? in this region is 41 7 %, which is consistent with the disk fraction estimated in previous studies. We see that there is no significant dependence of disk fraction on stellar mass among T Tauri stars (<2 M?), but we propose rapid disk depletion around higher mass stars (>2 M?). Furthermore, we found the lowest mass of a disk-bearing object to be ? 20 MJup and the pronounced disk-fraction among the brown dwarf population hints at the formation scenario that brown dwarfs form similar to low-mass stars. 2023, Indian Academy of Sciences. -
A Novel Survey for Young Substellar Objects with the W-band Filter. VI. Spectroscopic Census of Substellar Members and the IMF of the ? Orionis Cluster
Low-mass stars and substellar objects are essential in tracing the initial mass function (IMF). We study the nearby young ? Orionis cluster (d ? 408 pc, age ? 1.8 Myr) using deep near-infrared (NIR) photometric data in the J, W, and H bands from WIRCam on the Canada-France-Hawaii Telescope. We use the water absorption feature to select brown dwarfs photometrically and confirm their nature spectroscopically with IRTF-SpeX. Additionally we select candidate low-mass stars for spectroscopy and analyze their membership and those of literature sources using astrometry from Gaia DR3. We obtain NIR spectra for 28 very-low-mass stars and brown dwarfs and estimate their spectral type between M3 and M8.5 (masses ranging between 0.3 and 0.01 M ?). Apart from these, we also identify five new planetary-mass candidates which require further spectroscopic confirmation of youth. We compile a comprehensive catalog of 170 spectroscopically confirmed members in the central region of the cluster, for a wide mass range of ?19-0.004 M ?. We estimate the star-to-brown-dwarf ratio to be ?4, within the range reported for other nearby star-forming regions. With the updated catalog of members we trace the IMF down to 4 M Jup and we find that a two-segment power law fits the substellar IMF better than a log-normal distribution. 2023. The Author(s). Published by the American Astronomical Society. -
Normalized Attention Neural Network with Adaptive Feature Recalibration for Detecting the Unusual Activities Using Video Surveillance Camera
Over the past few years, surveillance cameras have become common in many homes and businesses. Many businesses still employ a human monitor of their cameras, despite the fact that this individual is more probable to miss some anomalous occurrences in the video feeds owing to the inherent limitations of human perception. Numerous scholars have investigated surveillance data and offered several strategies for automatically identifying anomalous occurrences. Therefore, it is important to build a model for identifying unusual occurrences in the live stream from the security cameras. Recognizing potentially dangerous situations automatically so that appropriate action may be taken is crucial and can be of great assistance to law enforcement. In this research work, starting with an MRCNN for feature extraction and AFR for fine-tuning, this architecture has a number of key components (AFR). To increase the quality of the features extracted by the MRCNN, the AFR replicas the inter-dependencies among the features to enhance the quality of the low- and high-frequency features extracted. Then, a normalized attention network (NAN) is used to learn the relationships between channels, which used to identify the violence and speeds up the convergence process for training a perfect. Furthermore, the dataset took real-time security camera feeds from a variety of subjects and situations, as opposed to the hand-crafted datasets utilized in prior efforts. We also demonstrate the method's capability of assigning the correct category to each anomaly by classifying normal and abnormal occurrences. The method divided the information gathered into three primary groups: those in need of fire protection, those experiencing theft or violence, and everyone else. The study applied the proposed approach to the UCF-Crime dataset, where it outperformed other models on the same dataset. 2023 WITPress. All rights reserved. -
AI-powered marketing strategies in the tourism and hospitality sector
A highly competitive environment with increased demand for personalized services drives the tourism and hospitality industry to embrace immersive and intelligent technologies. Smart technologies like artificial intelligence (AI) and virtual reality (VR) assist in promotions, marketing brands, customer analysis, and ultimately leading to sustainable businesses. Marketing research is an inevitable element for any businesses that helps in understanding their customers, catering their needs, and turning them into loyal customers. Marketing strategies incorporated with smart technologies are gaining high importance in the tourism and hospitality industries due to three major outcomes such as experience enhancement, revenue improvement and effective operations. Artificial intelligence revamped the hospitality industry with customized services and tailored recommendations based on a wholesome of customer data. Virtual reality technology provides high immersive experience to boost tourism, to enhance customer experience, to influence positive travel decisions. 2024, IGI Global. All rights reserved. -
Analyzing the Virtual Reality Experiential Dimensions at the Game Centers of Tourist Destinations
Virtual Reality (VR) games have attracted the attention of customers lately since they have been offering the most immersive experience through amusement park rides such as VR roller coasters and VR games related to adventure, thrill, scare, etc. Bangalore being a gem of the tourist destination and an IT hub was chosen for the study as it has the greatest potential of offering various VR experiences to the customers. The top 6 of Bangalore's VR game centers were selected based on the popularity and review count from Trip Advisor and Google reviews websites. Analyzing user-generated content has become an intriguing part of business research to find valuable marketing insights for better decisionmaking. The empirical findings show that the majority of the customers are extremely satisfied with the VR experiences and illusion emerges to be the major influencing factors for experiential satisfaction and customers are ready to spend for VR when the VR experiential dimensions meet the expected standards. 2024, Journal of Toursm & Development. All rights reserved.