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"Kumar, Rahul"
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Principles of entrepreneurship in the industry 4.0 era
\"The feature that distinguishes this book from all other books on entrepreneurship is the comprehensive discussion of the challenges and opportunities that entrepreneurs encounter in the Industry 4.0 era. It enables readers to start dreaming big, visualizing, and encourages them to think clearly and creatively. The book emphasizes creativity and innovation as the core of entrepreneurship, by stretching imagination, thinking about problems and solutions, and visualizing their ventures at the local, national, and global scale. It also discusses the role of women in private enterprise, and entrepreneurship in the post COVID-19 world\"-- Provided by publisher.
Book
Morphometric delineation of administrative boundaries and classification of threatened categories of small watersheds in transboundary rivers
The ecological conservation of large rivers is impossible unless immediate attention is given to protecting their small tributaries at local levels. The natural boundaries of large river basins are shrinking because their tributaries and streams of different orders are disappearing at an unprecedented rate. Delineation of the fixed administrative boundaries (AB) to protect the natural boundary of small rivers and their classification into appropriate threatened categories, the present study was carried out on the 54.08 km long Banki River in the Ganga River basin. The > 70% irreversible loss in the number of streams (Nu), length of streams (Lu), and drainage density (Dd) resulted in the conversion of the 6th order Banki into the 4th order river. The extreme morphometric changes result in the Banki watershed being under the “Critically Endangered” category. The drainage density ratio (DdR) and mean stream width (M
sw
) were used to determine the width of AB (W
AB
). The “River Red List Categories and Criteria” are being proposed to strengthen global initiatives at the local levels to protect and conserve inland water bodies and transboundary rivers.
Journal Article
Python : beginner's guide to artificial intelligence : build applications to intelligently interact with the world around you using Python
This Learning Path offers practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis. You will be introduced to various machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. You'll find a new balance of classical ideas and modern insights into machine learning. You will learn to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open-source Python libraries. From back cover.
Book
Faculty members’ use of artificial intelligence to grade student papers: a case of implications
This paper presents the case of an adjunct university professor to illustrate the dilemma of using artificial intelligence (AI) technology to grade student papers. The hypothetical case discusses the benefits of using a commercial AI service to grade student papers—including discretion, convenience, pedagogical merits of consistent feedback for students, and advances made in the field that yield high-quality work—all of which are achieved quickly. Arguments against using AI to grade student papers involve cost, privacy, legality, and ethics. The paper discusses career implications for faculty members in both situations and concludes with implications for researchers within the discourse on academic integrity.
Journal Article
Magnetic Field Sensing Using Tapered Small-Core Optical Fibre Surrounded by Different Concentrations of Magnetic Fluid
In this paper, a high-sensitivity magnetic field sensor based on a single-mode–tapered small-core–single-mode (STSCS) optical fibre structure is investigated. The tapered small-core section of STSCS is surrounded by magnetic fluid (MF) containing ferromagnetic particles (FMPs) of different concentrations. The FMPs align themselves along the magnetic field, depending on the strength of the magnetic field. This alignment of FMPs changes the refractive index around the tapered small-core section, which in turn changes the output spectral response of the STSCS optical fibre structure. The change in spectral response is then calibrated for sensing the magnetic field strength. This paper also investigates the effect of both the taper waist diameter of the STSCS optical fibre structure and the concentration of MF surrounding it on the magnetic field sensitivity. The maximum sensitivity demonstrated in this paper is 0.46 nm/mT for a taper waist diameter of 10 μm surrounded by 1.22% FMPs in the MF. The magnetic sensor demonstrates reversible results, and its effects on the orientation of the magnetic field along the X–Y, X–Z and Y–Z axes are also investigated, which suggest that the sensor is capable of vector magnetic field measurement.
Journal Article
A Comprehensive Review of Conventional and Intelligence-Based Approaches for the Fault Diagnosis and Condition Monitoring of Induction Motors
This review paper looks briefly at conventional approaches and examines the intelligent means for fault diagnosis (FD) and condition monitoring (CM) of electrical drives in detail, especially the ones that are common in Industry 4.0. After giving an overview on fault statistics, standard methods for the FD and CM of rotating machines are first visited, and then its orientation towards intelligent approaches is discussed. Major diagnostic procedures are addressed in detail together with their advancements to date. In particular, the emphasis is given to motor current signature analysis (MCSA) and digital signal processing techniques (DSPTs) mostly used for feature engineering. Consequently, the statistical procedures and machine learning techniques (stemming from artificial intelligence—AI) are also visited to describe how FD is carried out in various systems. The effectiveness of the amalgamation of the model, signal, and data-based techniques for the FD and CM of inductions motors (IMs) is also highlighted in this review. It is worth mentioning that a variety of neural- and non-neural-based approaches are discussed concerning major faults in rotating machines. Finally, after a thorough survey of the diagnostic techniques based on specific faults for electrical drives, several open problems are identified and discussed. The paper concludes with important recommendations on where to divert the research focus considering the current advancements in the FD and CM of rotating machines.
Journal Article
Room-Temperature Gas Sensors Under Photoactivation: From Metal Oxides to 2D Materials
HighlightsOperations of metal oxide semiconductors gas sensors at room temperature under photoactivation are discussed.Emerging two-dimensional (2D) materials-based gas sensors under light illumination are summarized.The advantages and limitations of metal oxides and 2D-materials-based sensors in gas sensing at room temperature under photoactivation are highlighted.Room-temperature gas sensors have aroused great attention in current gas sensor technology because of deemed demand of cheap, low power consumption and portable sensors for rapidly growing Internet of things applications. As an important approach, light illumination has been exploited for room-temperature operation with improving gas sensor’s attributes including sensitivity, speed and selectivity. This review provides an overview of the utilization of photoactivated nanomaterials in gas sensing field. First, recent advances in gas sensing of some exciting different nanostructures and hybrids of metal oxide semiconductors under light illumination are highlighted. Later, excellent gas sensing performance of emerging two-dimensional materials-based sensors under light illumination is discussed in details with proposed gas sensing mechanism. Originated impressive features from the interaction of photons with sensing materials are elucidated in the context of modulating sensing characteristics. Finally, the review concludes with key and constructive insights into current and future perspectives in the light-activated nanomaterials for optoelectronic gas sensor applications.
Journal Article
Understanding PSE students’ reactions to the postplagiarism concept: a quantitative analysis
This study examines postsecondary education (PSE) students’ perspectives on postplagiarism—a framework that reconceptualizes academic integrity in response to generative artificial intelligence (GenAI). Through a quantitative survey of 581 PSE students across five English-speaking countries, the research investigated student responses to the six tenets of postplagiarism articulated by Eaton (Int J Educ Integr 19:23, 2023a). The findings reveal a complex pattern of acceptance and resistance: while students broadly embrace the integration of GenAI in academic work, with 93.1% acknowledging the normalization of hybrid human–AI writing, significant concerns persist. Notable resistance emerged regarding the distinction between human and AI-generated content (65.92%), the potential impact of AI on human creativity (60.76%), and the retention of human agency in writing (32.7%). The study also validates a novel instrument for measuring postplagiarism perspectives, achieving acceptable internal consistency (Cronbach’s alpha = 0.718) while identifying areas for refinement. These insights suggest that educational institutions must develop nuanced policies that address student concerns while facilitating ethical AI integration, particularly in areas of attribution, creative expression, and academic agency. The findings contribute to our understanding of how academic integrity frameworks can evolve to remain relevant in an AI-integrated educational landscape.
Journal Article
Disease Detection in Apple Leaves Using Deep Convolutional Neural Network
The automatic detection of diseases in plants is necessary, as it reduces the tedious work of monitoring large farms and it will detect the disease at an early stage of its occurrence to minimize further degradation of plants. Besides the decline of plant health, a country’s economy is highly affected by this scenario due to lower production. The current approach to identify diseases by an expert is slow and non-optimal for large farms. Our proposed model is an ensemble of pre-trained DenseNet121, EfficientNetB7, and EfficientNet NoisyStudent, which aims to classify leaves of apple trees into one of the following categories: healthy, apple scab, apple cedar rust, and multiple diseases, using its images. Various Image Augmentation techniques are included in this research to increase the dataset size, and subsequentially, the model’s accuracy increases. Our proposed model achieves an accuracy of 96.25% on the validation dataset. The proposed model can identify leaves with multiple diseases with 90% accuracy. Our proposed model achieved a good performance on different metrics and can be deployed in the agricultural domain to identify plant health accurately and timely.
Journal Article
Rotating black hole in Rastall theory
Rotating black hole solutions in theories of modified gravity are important as they offer an arena to test these theories through astrophysical observation. The non-rotating black hole can be hardly tested since the black hole spin is very important in any astrophysical process. We present rotating counterpart of a recently obtained spherically symmetric exact black hole solution surrounded by perfect fluid in the context of Rastall theory, viz, rotating Rastall black hole that generalize the Kerr–Newman black hole solution. In turn, we analyze the specific cases of the Kerr–Newman black holes surrounded by matter like dust and quintessence fields. Interestingly, for a set of parameters and a chosen surrounding field, there exists a critical rotation parameter (\\[a=a_{E}\\]), which corresponds to an extremal black hole with degenerate horizons, while for \\[aa_{E}\\] with value \\[a_E\\] is also influenced by these parameters. We also discuss the thermodynamical quantities associated with rotating Rastall black hole, and analyze the particle motion with the behavior of effective potential.
Journal Article