bluuebunny/crossref_metadata_2025 huggingface dataset:
The Death of Vulcan: NEID Reveals That the Planet Candidate Orbiting HD 26965 Is Stellar Activity*
Authors: Burrows Abigail , Halverson Samuel , Siegel Jared C. , Gilbertson Christian , Luhn Jacob , Burt Jennifer , Bender Chad F. , Roy Arpita , Terrien Ryan C. , Vangstein Selma , Mahadevan Suvrath , Wright Jason T. , Robertson Paul , Ford Eric B. , Stefánsson Gumundur , Ninan Joe P. , Blake Cullen H. , McElwain Michael W. , Schwab Christian , Zhao Jinglin
Published: April 2024

We revisit the long-studied radial velocity (RV) target HD 26965 using recent observations from the NASA-NSF “NEID” precision Doppler facility. Leveraging a suite of classical activity indicators, combined with line-by-line RV analyses, we demonstrate that the claimed 45-day signal previously identified as a planet candidate is most likely an activity-induced signal. Correlating the bulk (spectrally averaged) RV with canonical line activity indicators confirms a multiday “lag” between the observed activity indicator time series and the measured RV. When accounting for this lag, we show that much of the observed RV signal can be removed by a linear detrending of the data. Investigating activity at the line-by-line level, we find a depth-dependent correlation between individual line RVs and the bulk RVs, further indicative of periodic suppression of convective blueshift causing the observed RV variability, rather than an orbiting planet. We conclude that the combined evidence of the activity correlations and depth dependence is consistent with an RV signature dominated by a rotationally modulated activity signal at a period of ∼42 days. We hypothesize that this activity signature is due to a combination of spots and convective blueshift suppression. The tools applied in our analysis are broadly applicable to other stars and could help paint a more comprehensive picture of the manifestations of stellar activity in future Doppler RV surveys.
Measuring the Chemodynamics and Ages of the M32 and M110 Dwarf Galaxies with APOGEE
Authors: Álvarez-Castro Alondra , Gibson Benjamin J. , Zasowski Gail
Published: April 2024

We present a full-spectrum-fitting analysis of the central kinematics and chemistry of the Andromeda dwarf satellite galaxies M32 and M110. We use an Markov Chain Monte Carlo routine to fit high-resolution, near-infrared, integrated-light spectra from APOGEE with empirical simple stellar population templates constructed from individual APOGEE stellar spectra. This yields the best-fitting mean radial velocity, velocity dispersion, metallicity, α abundance, and age for each spectrum. In general, our results are consistent with literature values where available, and we explore possible reasons where offsets are measured. This study was presented in a poster at the 243rd meeting of the American Astronomical Society in 2024 January.
First evidence of scavenging behaviour in Ichthyosaura alpestris (Laurenti, 1768)
Authors: Daftsios Thomas , Iakovidis Dionisios , Gogolos Nikolaos , Sagonas Kostas
Published: April 2024

The alpine newt is an opportunistic predator whose diet consists predominantly of aquatic and terrestrial invertebrates with Crustacea, Plecoptera, Collembola, Diptera, Isopoda and Gastropoda being the predominant prey groups. Consumption of amphibian eggs and larvae are another common food source. Here, we report the first documented case of adult Ichthyosaura alpestris feeding on a rodent carcass, thus adding to its menu a prey item that belongs to the Class Mammalia, while showcasing the previously unknown scavenging behaviour. This finding suggests that rodent carcasses can serve as an important resource for nutrients in remote, high-altitude populations of the alpine newt.
Formulation, characterization and evaluation of vildagliptin and metformin combined tablets
Authors: Mohamed Asmaa Abdelaziz , Hamed Hiba Ezzat , Rahi Firas Aziz
Published: April 2024

The current study was conducted to formulate and assess combined vildagliptin (VD) and metformin hydrochloride (MET) tablets. The formulations were developed by wet granulation to overwhelm the reduced compressibility of MET powder. Polymers like Kollidon K30 and K90 were used to prepare formulations. Micromeritics characteristics of blends were assessed. Subsequently, the tablets that had been manufactured were assessed for post-compression characteristics. The composition formula F7 was optimal due to having the best hardness, friability and good dissolution.
A new species of karst-associated kukri snake (Reptilia: Squamata: Colubridae: Oligodon Fitzinger, 1826) from southern Thailand
Authors: Pawangkhanant Parinya , Poyarkov Nikolay A. , Ward-Smith Harry , Grassby-Lewis Rupert , Sumontha Montri , Kliukin Nikita S. , Idiiatullina Sabira S. , Trofimets Alexei V. , Suwannapoom Chatmongkon , Lee Justin L.
Published: April 2024

Abstract

We describe a new species of kukri snake (Oligodon Fitzinger, 1826) from the limestone karst formations of Satun and Trang Provinces in southern Thailand. Phylogenetic analyses based on three mitochondrial DNA fragments (12S–16S ribosomal rRNA and cytochrome b) recover the new species within the Oligodon cinereus species complex, where it forms a deeply divergent yet poorly supported clade sister to Oligodon saiyokSumontha et al., 2017 and another unnamed lineage currently referred to Oligodon cinereus (Günther, 1864) from southwest Myanmar. Morphologically, the new species is distinguished from all other members of the genus by the following combination of characters: ventral scales 189–193 with distinct lateral keeling; subcaudal scales 47–54, paired; anterior dorsal scale rows 17–19, with the reduction from 19 to 17 rows occurring above the 28th–30th ventral scale when present; maxillary teeth 8, blade-like and laterally compressed; dorsum olive–gray, plain; ventral surface white anteriorly, dark gray posteriorly; underside of tail dark gray, smeared with white. We briefly discuss the natural history and conservation status of this new species and provide observations of other kukri snakes inhabiting limestone karst habitats. Our study also incorporates genetic samples of four recently described Oligodon endemic to Thailand, all of which are recovered in the O. cinereus species complex. In agreement with previous studies, we demonstrate that species-level diversity within the O. cinereus species complex is underestimated, and additional sampling is necessary to revise this taxonomically challenging clade.
La Montessori way of life , une « bonne » manière d’être mère des classes moyennes ?
Authors: Kilic Aksel , Oller Anne-Claudine
Published: April 2024

Depuis plusieurs années, la pédagogie Montessori connait une diffusion dans les familles notamment grâce à des publications médiatisées ainsi qu’à des produits éducatifs comme des jeux ou des livres estampillés Montessori qui garnissent les rayons des librairies et des magasins. La tendance s’inscrit plus largement dans un mouvement d’évolution de la parentalité. Cet article portera la focale sur les mères qui pratiquent la pédagogie Montessori dans leur cercle familial. Pour l’ensemble des mères que nous avons rencontrées, la référence revendiquée à Maria Montessori et la mise en œuvre de pratiques s’en inspirant, dans la sphère familiale, sont considérées comme un moyen d’être une « bonne » mère. Être une bonne mère suppose également d’être un bon parent d’élève. Plus largement, s’inspirer de la pédagogie Montessori a-t-elle d’autres effets sur la vie de ces mères qui la pratiquent ? Nous postulons en effet que ces pratiques d’inspiration Montessori transforment le quotidien de ces mères de famille au point de constituer un véritable mode de vie que nous appelons « Montessori way of life  ». Notre propos s’appuie sur vingt entretiens semi-directifs approfondis réalisés auprès de femmes qui appartiennent toutes aux classes moyennes, dont les trois quarts aux franges supérieures, plus des trois quarts d’entre elles travaillent dans le champ de l’enfance et de la petite enfance.
Generalized Pareto distribution and income inequality: an extension of Gibrat's law
Authors: Tao Yong
Published: April 2024

Motivated by empirical observations, we proposed a possible extension of Gibrat's law. By applying it into the random growth theory of income distribution, we found that the income distribution is described by a generalized Pareto distribution (GPD) with three parameters. We observed that there is a parameter $ \eta $ in the GPD that plays a key role in determining the shape of income distribution. By using the Kolmogorov-Smirnov test, we empirically showed that, for typical market-economy countries, $ \eta $ is significantly close to 0, indicating that the income distribution is characterized by a two-class pattern: The bottom 90% of the population is approximated by an exponential distribution, while the richest 1%~3% is approximated by an asymptotic power law. However, we empirically found that in China during the period of the planned economy and the early stages of market reform (from 1978 to 1990), $ \eta $ deviated significantly from 0, indicating that the bottom of the population no longer conformed to an exponential distribution.
On oscillating radial solutions for non-autonomous semilinear elliptic equations
Authors: Al Jebawy H. , Ibrahim H. , Salloum Z.
Published: April 2024

We consider semilinear elliptic equations of the form $ \Delta u + f(|x|, u) = 0 $ on $ {\mathbb{R}}^{N} $ with $ f(|x|, u) = q(|x|)g(u) $. These type of equations arise in various problems in applied mathematics, and particularly in the study of population dynamics, solitary waves, diffusion processes, and phase transitions. We show that under suitable assumptions on the nonlinearity $ f $, there exists an oscillating radial solution converging to a zero of the function $ g $. We also study the oscillating and limiting behavior of this solution.
Research on a vehicle and pedestrian detection algorithm based on improved attention and feature fusion
Authors: Liang Wenjie
Published: April 2024

With the widespread integration of deep learning in intelligent transportation and various industrial sectors, target detection technology is gradually becoming one of the key research areas. Accurately detecting road vehicles and pedestrians is of great significance for the development of autonomous driving technology. Road object detection faces problems such as complex backgrounds, significant scale changes, and occlusion. To accurately identify traffic targets in complex environments, this paper proposes a road target detection algorithm based on the enhanced YOLOv5s. This algorithm introduces the weighted enhanced polarization self attention (WEPSA) self-attention mechanism, which uses spatial attention and channel attention to strengthen the important features extracted by the feature extraction network and suppress insignificant background information. In the neck network, we designed a weighted feature fusion network (CBiFPN) to enhance neck feature representation and enrich semantic information. This strategic feature fusion not only boosts the algorithm's adaptability to intricate scenes, but also contributes to its robust performance. Then, the bounding box regression loss function uses EIoU to accelerate model convergence and reduce losses. Finally, a large number of experiments have shown that the improved YOLOv5s algorithm achieves mAP@0.5 scores of 92.8% and 53.5% on the open-source datasets KITTI and Cityscapes. On the self-built dataset, the mAP@0.5 reaches 88.7%, which is 1.7%, 3.8%, and 3.3% higher than YOLOv5s, respectively, ensuring real-time performance while improving detection accuracy. In addition, compared to the latest YOLOv7 and YOLOv8, the improved YOLOv5 shows good overall performance on the open-source datasets.
Examining the Public Perception of Law Enforcement
Authors: Merlo Tereza Raquel , Pampapura Nayana Madali M. , Merlo Jason M.
Published: April 2024

The emergence of social media platforms has revolutionized communication and interaction across various domains, including law enforcement, and users have increasingly utilized these platforms to express their opinions and consume information. This research chapter focuses on evaluating user responses and behaviors on Twitter presenting an analysis of tweets mentioning the Dallas Police Department. Data analysis is performed to investigate tweet frequency and patterns related to the law enforcement agency. Additionally, sentiment analysis and topic modeling techniques are employed to gain deeper insights into the content and context of user tweets. The research findings reveal that users tend to increase their tweeting activity whenever there is an incident involving the agency. Moreover, the results indicate that users generally express a neutral sentiment towards the law enforcement agency, with their tweets largely reflecting personal opinions. Overall, this study provides valuable insights into user behavior and sentiments concerning the Dallas Police Department, demonstrating the significant role of social media platforms in shaping public perceptions and online interactions with the agency.
Role of Information Security and Protection in the Modern Era
Authors: Siddiqui Ahmad Tasnim , Jahangeer Gulshaira Banu , Basha Amjath Fareeth
Published: April 2024

The purpose of information security is to protect data by mitigating the risks associated with it. It refers to preventing unauthorized access to disclosure, destruction, disruption, modification of information and the information that they process, store, and transmit. Every information, especially sensitive or confidential, must be protected. It is essential to consider technology, policies, procedures, and people when implementing an effective information security system. In addition, emerging threats and vulnerabilities need to be monitored, assessed, and adapted continuously. Cybercrime, theft, and espionage are some of the threats we face trying to protect our valuable information assets. The goal of information security is to safeguard valuable information assets against a variety of threats. No matter how information is stored, whether electronically or on paper, it must be protected to ensure privacy, integrity, and availability. This chapter talks about the role of information security in modern days.
Implementing Information Governance in Academic Libraries
Authors: Zerangue Amanda , Clark Kristin , Shapiro Adrian
Published: April 2024

This chapter focuses on opportunities to implement an information governance framework within an academic library. Due to their mission and breadth of information management activities, academic libraries face numerous challenges in organizing and preserving information and records, and governing data. Implementing information governance strategies, specifically in the areas of records and information management, metadata creation, institutional repositories, digital preservation, and data management will result in well-informed and collaborative policies which protect the library as well as the institution. Developing this skill set within the library requires a culture shift towards transparency, collaboration, and accountability. Additionally, library and information science curricula should reflect the current demands of the academic library landscape and expand course offerings to build information governance competencies.
Information Governance for Public Authorities
Authors: Agarwal Kirt , Hooda Sneha , Maheshwari Shashank
Published: April 2024

In an era dominated by digital transformation, public authorities globally face a profound challenge in effectively managing and governing the burgeoning volumes of information under their purview. Using specific case study of teacher attendance monitoring system (TAMS) in State of Meghalaya, this chapter seeks to explore the landscape of information governance within the context of public authorities in India. As the country undergoes significant advancements in digital infrastructure and governance, understanding the nuances of information governance becomes imperative for ensuring transparency, accountability, and optimal service delivery. This chapter aims to provide a comprehensive analysis of the current state of information governance in Indian public authorities, identifying key challenges, proposing strategic solutions, and offering insights into the potential impact on public administration and citizen engagement.
Tax Authorities Big Data Analytics in Developing Countries
Authors: Hartanto Susanna
Published: April 2024

Nowadays, most tax authorities in the world are utilizing various technologies, including big data analytics to be more efficient and effective in their works. Utilization of big data analytics and business intelligence by tax authorities in developing countries can be used to help identify the non-compliance taxpayers and support other activities in order to explore potential tax revenues. Directorate General of Taxes, Indonesian Tax Autbority, uses combination of compliance risk management application and business intelligence. There are nine types of compliance risk management applications. Currently, seven types of compliance risk management applications have been launched and used by the directorate general of taxes. The last two compliance risk management applications will be released in the near future. The series of nine compliance risk management applications will be supported by four business intelligence. Those compliance risk management and business intelligence applications will lead directorate general of taxes to be data driven organization.
The Library and Information Science Perspective on Knowledge Management
Authors: Hendrawan Muhammad Rosyihan , Ariyani Luh Putu Sri , Bafadhal Aniesa Samira
Published: April 2024

Knowledge management (KM) creates value and competitive advantage via innovation. Library and information science (LIS) developed KM using social epistemology and varied scientific methods. LIS continued to study KM to guarantee its understanding and usage in the organization. KM attitudes and actions must also be agreed upon. This chapter discusses the LIS viewpoint on KM and delivers the fundamental point, which implies that LIS may advance knowledge management. Thus, readers should ask questions about LIS and all of the preceding advances, especially KM. The perception of data, information, and knowledge especially has changed significantly. LIS perspective should be dynamic, and librarianship has individuality and dignity with knowledge managing tradition. LIS and Librarianship roles, especially KM, may help drive these new advancements. Instead of only watching or ignoring improvements, active engagement and additional research are expected to raise LIS roles on KM.
Safeguarding Business in the Age of AI for Organizational Resilience and Risk Management
Authors: Dutta Pushan Kumar , Das Sulagna , Ganguly Devraj
Published: April 2024

As AI proliferates across sectors, it creates new cybersecurity risks from growing attack surfaces, data flows, and system complexity. This chapter outlines risk management frameworks to harness AI safely despite escalating threats. It establishes why traditional controls now fall short, necessitating updated cyber strategies centered on ethical “Secure AI by Design” governance. First, prominent threats like malware and denial-of-service attacks are analyzed. Technical safeguards such as authentication, encryption, and blockchain applications are suggested alongside auditing, transparency, and proactive risk monitoring to manage threats. Real-world critical infrastructure attack cases reveal current susceptibilities. esilience demands optimization coupled with defense-in-depth approaches across people, processes and system that gives advisory on adapting cybersecurity and a guide to securing AI innovation potential, aligning with the book's focus on OpenAI outlines steps around pipelines, red teams, and internal/external trust via auditing and transparency for cyber risk management
The Impact of OpenAI and MFP on the Labour Market Dynamics of Trinidad and Tobago
Authors: Doon Roshnie Anita
Published: April 2024

Open Artificial Intelligence (AI) is a research and operation company that seeks to ensure that persons around the world can reap the benefits of AI. Its focus is on developing a range of models that have the potential to revolutionize the labour market productivity of business enterprises across industries in Trinidad and Tobago. The use of AI-based tools can not only optimize every stage of the management and production process but from the perspective of Multi-Factor Productivity (MFP) can boost its efficiency. Even with such benefits, increased use of AI can displace workers, intensify educational and skills mismatch, and stimulate inequality between unskilled and highly skilled workers. This chapter examined the impact of Open AI and MFP on the Labor Dynamics of Trinidad and Tobago, using a secondary research methodology. This chapter delves into the connection between AI tools and MFP, its integration into the management and production process, and the impact that it has on the labour dynamics of domestic industries, and the future of work in Trinidad and Tobago.
Telework Perspectives of Employers, Managers, and Employees
Authors: Chandan Harish C.
Published: April 2024

The three stakeholders of work—employers, managers, and employees—have varying viewpoints about telework. During the COVID-19 pandemic, telework grew using the internet and video communication technologies. However, the nature of work is still evolving. This chapter examines the perspectives of employers, managers, and employees on telework and summarizes the most recent work trend of hybrid work. With the end of the pandemic, the hybrid work is becoming a popular choice as it combines the benefits of telework for the employees like flexibility and lack of commute and in-office work that promotes collaboration, innovation, and a sense of loyalty for the company.
AI-Powered Parallel Computing Architecture and Its Applications
Authors: Aswini J. , Sudha K. , Ganesh Gowri , Siva Subramanian  , Ghinea George
Published: April 2024

Addressing the increasing processing demands of contemporary applications has grown to rely heavily on parallel computing. The development of faster and more effective computing systems has been made possible by this paradigm change from sequential processing to parallel execution, which has allowed for the addressing of the ever-increasing needs of current applications across numerous areas. This comprehensive study goes into the world of parallel computing architectures, exposing their fundamental ideas and providing a wide-ranging overview of their applications in several fields. The chapter explores fundamental ideas, parallelism types, architectural models, programming paradigms, difficulties, and potential futures in the context of parallel computing. This chapter aims to be a valuable resource for researchers, practitioners, and enthusiasts alike by bridging the theoretical and practical implementation gaps and offering insights into the potential, difficulties, and future directions of parallel computing architecture and its transformative impact on various domains.
Autonomous Agriculture and Food Production
Authors: Rampalli Nikhil Sai , Sri Yanala Gnana , Sai Bhuvaneshwari K.
Published: April 2024

Autonomous agriculture, driven by AI, robotics, and IoT, is revolutionizing food production. With automated machinery and advanced sensors, it optimizes crop conditions in real-time, reducing resource waste and enhancing yields. This not only addresses the challenge of feeding a growing global population but also promotes sustainability by minimizing environmental impact and supporting biodiversity. The technology's predictive capabilities contribute to increased food security, enabling farmers to mitigate crop diseases and extreme weather events. However, challenges such as data security, job displacement, and technology accessibility must be addressed. Despite these concerns, embracing autonomous agriculture is crucial for meeting the demands of a changing world, offering a path to efficient, sustainable, and secure food production.
Building a Self-Sustaining World
Authors: Samuel Prithi , K. Reshmy A. , Rajesh Sudha , A. Karthika R.
Published: April 2024

A review of artificial intelligence's (AI) impact on the realization of the sustainable development goals is necessary given its emergence and steadily expanding impact across many sectors. The authors discover that AI may facilitate the fulfillment of 134 targets for each of the goals using a consensus-based specialist elicitation process. It can also inhibit the achievement of 59 targets. However, current research priorities ignore crucial elements. In order to support AI's rapid development and promote sustainable development, regulatory oversight and knowledge are required. Inability to do so might lead to lapses in ethics, safety, and transparency. Generally speaking, there is no disputing that two significant developments are accelerating in the world we reside in: the rapid advancement of artificial intelligence and an increasing realization of the importance of sustainable practices.
Building Sustainable Smart Cities
Authors: Sharma Monika , Sharma Manju , Sharma Neerav
Published: April 2024

This chapter explores the integration of cloud technology and intelligent parking systems in creating sustainable smart cities. It emphasizes the interconnectedness of smart cities and sustainability, focusing on cloud technology's application in urban infrastructure. Intelligent parking systems are highlighted for their role in mitigating urban parking challenges and enhancing efficiency. The chapter highlights the benefits of integrating cloud technology and intelligent parking systems in urban planning, including improved traffic management, reduced environmental impact, and enhanced quality of life. It also addresses challenges like data security and stakeholder collaboration. The chapter provides a roadmap for researchers, policymakers, and urban planners.
Distributed and Lightweight Intrusion Detection for IoT
Authors: Gowthami D. , Vigenesh M.
Published: April 2024

The internet of things (IoT) represents a burgeoning paradigm extensively employed in crafting intricate real-time applications, fostering interconnectedness and convenience. IoT applications suffer from several cybersecurity vulnerabilities. In pursuit of this objective, an IDS model called lightweight pyramidal U-Net with dual inception fusion framework is proposed. The IoT device layer comprises devices that continually generate network traffic for cloud applications which are directed to the edge layer, where two operations occur: traffic filtering and pre-processing and feature extraction. The model incorporates feature attention in the encoder phase and multiscale pyramidal layers in the decoder phase to robustly extract network features by capturing interdependencies among them. Experimental results demonstrate the superiority of our approach over state-of-the-art methodologies.
EdgeAI in Self-Sustaining Systems With AI and IoT
Authors: Chenna Dwith
Published: April 2024

This proposed chapter aims to provide a deep dive into the integration of edge artificial intelligence (EdgeAI) within self-sustaining systems enabled by the internet of things (IoT). Specifically, the chapter will focus on the crucial aspect of optimization techniques within these systems. As self-sustaining systems become increasingly important for resource-efficient and autonomous operations, this chapter will explore how EdgeAI plays a pivotal role in optimizing data processing, resource allocation, and decision-making at the edge.
Nano-Composite Integration, IoT, and AI for Sustainable and Intelligent Smart Cities
Authors: Solaimalai Gautam , Mandipudi Raghunath , Thirumala Srinivas , Reddy P. Naresh Kumar , Anusuya M. , Subhi Boopathi.
Published: April 2024

Urbanization has led to the need for innovative solutions in civil construction to create sustainable and intelligent smart cities. This chapter explores the integration of nano-composite materials, IoT, and AI to enhance efficiency and functionality in civil construction projects. The chapter discusses the growing significance of smart civil construction in urban landscape development, nano-composite materials, IoT and AI, and their applications in construction. It highlights the synergies, challenges, and successful implementations of these technologies in smart cities, highlighting their potential for efficiency, sustainability, and economic benefits. The chapter predicts future trends in smart civil construction, emphasizing the need for robust security, privacy safeguards, and ethical AI practices.
Rating-Based Guidance System for Public Safety Using Classified Localities
Authors: Lokeswari Y. Venkataramana , D. Venkata Vara Prasad , Jacob Shomona Gracia , M. Mohamed Musaraf P. , Aravind Babu , Mohanram P. B.
Published: April 2024

To automate the manual SOS procedure given in Kavalan mobile application and to provide users a safe path by the given source and destination (from the users). This work uses regression algorithms such as linear regression, decision trees, or support vector machines (SVM) to predict the rating for a current zone which can be used as input for generating the graph with rating as weights and the graph is used as the input for the Dijkstra algorithm which produces the safest path based on the rating. Thus, this path can be used to navigate the public safely to their destination while avoiding unsafe zones. Furthermore, a feedback form is available using which the user can provide textual as well as numerical feedback regarding the places they travel. Decision tree regression provides an accuracy of 89.4% compared with the other regression models since the dataset is categorical and less in size. The safety path is also being produced using Dijkstra's algorithm and the feedback is analysed using the T5 model.
Smart Cities and Urban Sustainability With AI
Authors: Jeyalakshmi J. , Vijay K. , Eugene Berna  , Manohar Eashann
Published: April 2024

Artificial intelligence (AI) is revolutionizing urban settings by improving traffic management, energy efficiency, waste reduction, and recycling. AI-powered traffic management systems improve urban mobility, optimize traffic signals, and reduce congestion. It also optimizes waste creation and promotes recycling, improving resource management. AI-driven environmental monitoring apps monitor pollution levels in real-time, allowing proactive measures to reduce environmental impact. AI also analyzes critical infrastructure assets, enhancing public services and quality of life. However, challenges arise, such as data privacy and security, algorithmic bias, and the digital divide. To achieve AI's sustainable potential, public understanding and acceptance, regulatory and ethical standards must be addressed. By addressing these challenges, cities can create smarter, more sustainable, and people-first cityscapes.
Cloud Infrastructure for Robotics
Authors: Harinakshi C. , Masooda A. , Suchetha G.
Published: April 2024

The integration of cloud infrastructure with robotics transforms the field by providing a cost-effective platform for developing, testing, and deploying robotic applications. Cloud's on-demand computing resources accelerate innovation, allowing developers to experiment with new algorithms efficiently. This global collaboration enables remote control and testing of robots worldwide, overcoming geographical constraints. Cloud infrastructure enhances deployment by offloading intensive tasks, reducing hardware requirements, and promoting cost-effectiveness. Centralized fleet management streamlines operations, ensuring uniform updates and security patches for system stability. Robust security measures, including encryption and authentication, address privacy concerns. Cloud robotics implement edge computing for local data processing, minimizing the risk of breaches. Scalability accommodates growing demands, enabling businesses to adapt without significant investments.
The Pioneering Convergence of Data Analytics and Predictive Maintenance
Authors: Kumar Devender , Batra Jyoti
Published: April 2024

In this digital age, every machine is full of data, telling stories about how it works, how much wear it's wearing, and what it's doing. In the middle of all this tech, the combination of advanced data analysis and predictive maintenance acts as a conductor, bringing machinery, data, and foresight together. Instead of just reacting to mechanical issues, industries can now anticipate them and turn potential downtime into organized maintenance periods. It's not just about fixing things before they break, it's a whole new way of understanding and working with industrial machines and robotics. Sensors, algorithms, and the power of data science are all part of this new era, where machines 'talk' to each other and let us know their health so we can act quickly. This combination of data analytics and proactive maintenance promises not only improved operational efficiency, but a jump towards safer, stronger, more resilient and more affordable industrial ecosystems. Read on to find out how this combination of data and foresight is transforming industries.
Cloud Robotics and the Power of Application Offloading Strategies
Authors: Gowda V. Dankan , Kadam Kirti Rahul , Shaik Nazeer , Prasad K. D. V. , Shaik Sofia Rani
Published: April 2024

In the face of the development of robotic technology, integration with cloud technologies is a big opportunity to greatly improve robots. This chapter will synthetize the spirit which robotic applications lacks to refine and add depth to it. Also, this procedure not only gives the robotic device more computing power, but also ups its storage capacities and resource management, all without rendering robotical atrophy. In this chapter, the authors examine several different forms of application running away from home. In particular, with the growing public interest in robotics, it is vital that not only participants from industry but also researchers and developers who should realize that through cloud-based offloading they really have a chance to create a revolution.
Communication Protocols in Cloud Robotics
Authors: Savidhan Shetty C. S. , Badiger Manjunatha
Published: April 2024

The advent of cloud robotics has transformed traditional robotic systems by integrating them with the vast computational power of cloud infrastructure. This chapter explores the pivotal role of communication protocols in facilitating seamless interactions between physical robots and the cloud. The foundation of cloud robotics lies in addressing specific challenges such as low-latency, reliability, scalability, and security. Various communication protocols, including MQTT, RESTful APIs, and WebSocket, are examined for their suitability in different applications, ranging from data offloading to real-time monitoring. Security considerations are paramount in the transmission of sensitive data between robots and cloud servers, necessitating encryption, authentication, and authorization mechanisms. The chapter also delves into the importance of standardization and interoperability to foster collaboration among diverse robotic systems.
Applications of Cloud Computing in Industrial Robotics
Authors: Sethuraman S. , Vikram S. , Dharma Surya R. , Singh Brijendra
Published: April 2024

In the past few decades, robots have played a significant role in both industrial and technological advancements. Cloud-integrated industrial robotics provide a vast network of machines to industries. The integration of robotics with cloud computing offers increased computational power for various applications of industrial, communication, healthcare, disaster management, defence systems, and space exploration missions. It also provides reliable and extensive accessibility across a network of devices. In this chapter, the authors delve into the fundamentals of robotics and cloud computing. They introduce the core concepts of robotics and cloud computing, followed by their integration. Subsequently, they explore communication in cloud robotics, encompassing machine-to-machine (M2M) and machine-to-cloud (M2C) communication. They then examine the major applications in industrial robotics and types of robots that leverage cloud robotics technology. They conclude by addressing security issues and challenges in cloud robotics.
Modern-Day Healthcare With Cloud-Enhanced Robotics
Authors: Raj E. Fantin Irudaya , Manimala K. , Pushparaj T. Lurthu , Thanu M. Chithambara
Published: April 2024

Modern healthcare is undergoing a transformative evolution with the integration of cloud computing and robotics. This chapter delves into the convergence of these two technologies, defining and exploring the concept of cloud-enhanced robotics in healthcare. Through real-world case studies, the chapter highlights the wide array of applications for cloud-enhanced robotics, such as telemedicine, diagnostics, and data analytics, and how they are enhancing patient care. The benefits of cloud-enhanced robotics are manifold, including improved patient outcomes, enhanced precision, cost reduction, and increased access to expertise. This chapter explores both the advantages and challenges, offering insights into the potential future developments of cloud-enhanced robotics in healthcare.
Cloud-Enhanced Robotics in Healthcare
Authors: Masooda A. , Harinakshi C. , Suchetha G.
Published: April 2024

Cloud-enhanced robotics is reforming the healthcare sector through adventures. Cloud-enhanced healthcare robots aimed to provide potential support to medical professionals by accurately providing services like nursing, diagnosing, and executing critical surgeries. In the domain of healthcare, cloud robotics technology facilitates real-time data exchange, enabling professionals to deliver optimal services and care. Tasks ranging from laboratory testing to medication distribution can now be automated, and cloud-enhanced robotics have reached a level of proficiency that significantly lowers the risk of human faults in critical surgeries. This chapter explores the architecture and components of cloud-enhanced healthcare robots, provides various applications in the field, assesses the advantages and disadvantages of healthcare robots, and scrutinizes the security implications associated with cloud-enhanced robots.
Disaster Response and Recovery Role of Cloud-Enhanced Robotics
Authors: Singh Chandra , Bekal Anush , Ashoka A. , Dsouza Lanlyn Samuel , Abhishek A. B. , Shreesha P. U.
Published: April 2024

There is an urgent need for innovative and efficient disaster response and recovery solutions. This chapter investigates the use of cloud technologies in conjunction with robotics to improve disaster management operations. Cloud-enhanced robotics (CER) appears as a significant innovation, offering a synergistic approach in which cloud-enabled robots provide a more dynamic, adaptable, and robust response to catastrophic occurrences. CER enables robots to access huge computational resources and data, improving operational efficiency, decision-making, and problem-solving abilities. This connection improves real-time data analysis, coordination, and deployment tactics, resulting in a more effective reaction to crisis scenarios unfolding. Furthermore, it encourages greater coordination and resource sharing among different robots and reaction teams, hence maximizing overall recovery operations.
Night Vision-Based Human Identification and Path Planning in Rescue Operations Using an Autonomous Robot
Authors: Bhat Sandeep
Published: April 2024

This chapter provides a progressive thing classification and the most limited organising approach for robot-assisted night-time salvaging jobs. In reality, people are sorted using a system for determining skin tone. Boundaries were identified using the skin colour based (SCB), pixel count based (PCB), correlation coefficient based (CCB), and histogram draws near techniques in this study. The PCB, CCB, and SCB calculations are all utilised to snag distinct proof in order. The SCB calculation, on the other hand, gradually determines whether the observed entity is human or nonhuman. It also distinguishes between live and nonliving impediments, allowing for more efficient salvage efforts (except for flies, mosquitoes, and different creepy crawlies). According to continuous testing data, the accuracy of the CCB, PCB, and SCB calculations is 87.5%, 88.8%, and 90.9%, respectively, and the time length of the CCB, PCB, and SCB calculations is 6.27 seconds, 6.50 seconds, and 6.57 seconds, respectively.
Cloud Robotics in Education
Authors: Sai Venkatramana Prasada G. S. , Rashmi P. C.
Published: April 2024

Education is continually evolving to adapt to the ever-changing technological landscape of the 21st century. The integration of robotics into classrooms has opened up new horizons for both educators and students. Robotics serves as a powerful tool for engaging students in hands-on learning, problem-solving, and critical thinking. However, as the world becomes increasingly interconnected, cloud technology has emerged as a game-changer in education, particularly in the realm of robotics. Cloud-enhanced robotics is transforming the educational landscape, offering students and educators unprecedented access to resources, remote control capabilities, and collaborative programming platforms. This chapter delves into the potential of cloud robotics in education, including its applications, benefits, and challenges, while providing insights into prominent robotics programming platforms and remote learning opportunities.
Addressing Issues and Challenges Using AI in Pharmacy
Authors: Siraj Muzzammil , Siraj Hasnain , Shoaib Muhammad , Miran Safdar , Mahmood Asif , Hussain Fida
Published: April 2024

The complications and difficulties relating to the application of AI in pharmacy events are systematically scrutinized in this chapter. AI technologies have momentous potential to aid in pharmacy and healthcare settings as they advance. However, numerous challenges must be overcome before AI may be successfully executed in pharmacies. Integration, data security and privacy, regulatory compliance, ethical issues, user acceptability and training, clinical efficacy, and validation are just a few of the major problems covered in this chapter. Every impediment is thoroughly inspected, offering valuable perceptions of the particulars related to the integration of AI in pharmaceutical settings. The chapter provides a nuanced standpoint that can guide strategic decision-making in the ever-changing geography of AI integration in apothecaries by bridging the gap between academic knowledge and practical factors.
Human Microbiota Impact on the Efficacy of Pharmacological Treatments
Authors: Siraj Muzzammil , Siraj Hasnain , Miran Safdar , Hussain Fida
Published: April 2024

The objective of this review is to systematically examine several papers that observe the complex relationships between pharmaceutical treatments and human microbiota, highlighting how these relations may affect the course of treatment. To assure a thorough analysis of the data of current literature, the review was voted for to make use of several databases. PubMed, Open University, Academia Sinica, Southern Methodist University, Yale University, and Google Scholar were the central databases. This study analyzes the 1300 articles from the first search. After eradicating duplicate papers (348), 952 articles endured for abstract screening. After abstracts were observed, 212 publications were excluded. After a full-text screening process, 641 of the 740 remaining articles were estimated ineligible conferring to predetermined inclusion criteria. 99 papers that fulfilled all inclusion requirements were incorporated into the final analysis. The examination of 99 publications published between 2010 and 2023 has provided important new information about the complex interplay among human microbiota and pharmaceutical treatments effectiveness. Even with the countless advancements in microbiome research, there are still numerous unanswered questions. The systematic analysis of 99 publications covering a wide range of medical specialties has significant implications for practical applications as well as guidelines for future study. To understand the dynamic nature of these interactions, longitudinal studies monitoring variations in the composition of the microbiota and medication responses over time are important.
IoT Smart Healthcare Security Challenges and Solutions
Authors: Shah Imdad Ali , Jhanjhi N. Z. , Brohi Sarfraz Nawaz
Published: April 2024

The primary objective of this chapter is to examine the security concerns of people in their smart homes and focus on the healthcare equipment that comes packaged with future homes that are vulnerable to cyber-attacks, resulting in data breaches. Patients not physically present in a healthcare institution can have their health metrics, such as heart rate, blood pressure, temperature, and more, automatically collected by IoT devices. This eliminates the need for patients to travel to the doctor or gather the data themselves. A crucial component of healthcare procedures is patient care, healthcare IoT applications can potentially improve patient outcomes and the calibre of care given by physicians, nurses, clinicians, pharmaceutical companies, and the government. Wireless healthcare monitoring devices are regarded as a medical revolution widely utilized in hospitals and other healthcare settings. However, on the internet of items paradigm, security and privacy for interconnected items should be considered. A systematic approach to security and privacy safeguards must be employed in creating devices, connecting objects, communicating, handling, and storing data, and destroying such devices and data in the context of healthcare and remote health monitoring. In recent years, smart homes and healthcare have become increasingly popular. It is required to use a more secure method to assure security and privacy. As a result, these techniques can provide security and privacy in Smart health regarding remote patient monitoring and healthcare, communications, data handling, and device failure due to data loss. The smart house and its services, as we currently understand them, create a highly heterogeneous context, posing a substantial problem for future consumers and producers. Healthcare services expose vulnerabilities in interconnected medical devices and pose an unknown threat to human life. This study helps new researchers and related healthcare institutions.
Use of Emerging Technologies in Healthcare 4.0
Authors: Shah Imdad Ali , Jhanjhi N. Z. , Brohi Sarfraz Nawaz
Published: April 2024

Since its launch, Healthcare 4.0 has made it possible to create and enhance the quality of healthcare services by integrating cutting-edge technologies. We have focused this study on a few of the cutting-edge studies that have the potential to significantly impact advancing healthcare 4.0 systems in the future. We have identified the critical research gaps and introduced the Healthcare IoT Application and Service Stacks, representing the state-of-the-art in contemporary healthcare systems. Additionally, we discussed the most recent paradigm for wireless body area networks and focused on the importance and how advanced technology helps next-generation health applications, such as big data analytics, software-defined networking, blockchain, cloud computing, edge/fog computing, telehealthcare, edge/fog computing, and machine learning. We have conducted a comparative analysis of several architectural implementations, considering their benefits, drawbacks, and needs for quality of service. We greatly emphasize the significance of the various developing technologies, outlining the prospects they present and their ability to improve healthcare solutions and deliver higher-quality services. The primary objective of this chapter is to focus on the fundamentals of establishing security and privacy in the future healthcare system.