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Customized mask region based convolutional neural networks for un-uniformed shape text detection and text recognition
In image scene, text contains high-level of important information that helps to analyze and consider the particular environment. In this paper, we adapt image mask and original identification of the mask region based convolutional neural networks (R-CNN) to allow recognition at 3 levels such as sequence, holistic and pixel-level semantics. Particularly, pixel and holistic level semantics can be utilized to recognize the texts and define the text shapes, respectively. Precisely, in mask and detection, we segment and recognize both character and word instances. Furthermore, we implement text detection through the outcome of instance segmentation on 2-D feature-space. Also, to tackle and identify the text issues of smaller and blurry texts, we consider text recognition by attention-based of optical character recognition (OCR) model with the mask R-CNN at sequential level. The OCR module is used to estimate character sequence through feature maps of the word instances in sequence to sequence. Finally, we proposed a fine-grained learning technique that trains a more accurate and robust model by learning models from the annotated datasets at the word level. Our proposed approach is evaluated on popular benchmark dataset ICDAR 2013 and ICDAR 2015. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Customized SEIR Mathematical Model to Predict the trends of Vaccination for Spread of COVID-19
The uncertainty in life plans, restrictions on physical classrooms, loss of jobs, large number of infections and deaths due to COVID-19 are some significant causes of concern for the public as well as Governments all over the globe. Moreover, the exponential increase in the number of infected people in a short time is responsible for the collapse of the health industry during the pandemic caused by COVID-19. The health experts recommended that the quick and early diagnosis followed by treatment of patients in isolation is a way to minimize its spread and save lives. The objective of this research is to propose a customized SEIR model to predict the trends of vaccination in the USA. The experimental results prove that the Moderna vaccine reports the efficacy of 93%, which is higher than the Pfizer and Johnson and Johnson vaccines. 2022 ACM. -
Cutting across the Durand: Water dispute between Pakistan and Afghanistan on river Kabul
All nations firmly believe in the absolute sovereignty over the waters flow in their areas and that only riparian states have any legal right, apart from an agreement, to use the water from the shared river. To address some of their water concerns, the co-riparian states compete to have more quantity of waters. Significantly, no water agreement exists between upper riparian Afghanistan and lower riparian Pakistan, despite sharing nine big and small rivers. The simmering water dispute between them on the River Kabul is rarely noted mainly because it is overshadowed by their political tensions, differences, and the dispute over the Durand Line. Using an analytical framework, this article examines three aspects of the River Kabul water dispute: its context, identifying the challenges that hinder a formalized bilateral agreement from being implemented, and its future. 2020 Policy Studies Organization -
Cyanogenic glycosides: A sustainable carbon and nitrogen source for developing resilient Janus reversible oxygen electrocatalysts for metal-air batteries
Most of the transition metal based heteroatom doped carbon electrocatalysts, utilizes the fossil fuel derived commercially available precursors as source of nitrogen and carbon which may question our environmental generosity. Herein, we have developed Ni-based efficient bifunctional electrocatalysts using apple seeds (that contains cyanogenic glycosides) as the precursor for nitrogen and carbon. With tuning the temperature, we were able to optimize the nitrogen doping up to ?3 at.%. The optimized electrocatalyst catalyses the oxygen reduction reaction (ORR) process with muted peroxide generation (for 0.7500.1 V the % HO2 ? generation ?3 - 2%), preferential 4e? reduction pathways (n ? 3.93 to 3.98 in 0.750.1 V range) and electron transfer via inner-sphere electron transfer mechanism which ensures the maximum utilization of instituted active centres owing to the direct interaction of reactant species. Alike to ORR, the superior oxygen evolution reaction (OER) performance with smaller Eonset, EJ=10, Tafel slope and enduring accelerated stability test advocates its potential as a bifunctional oxygen electrocatalyst. Moreover, smaller potential gap ?E (EJ10_OER - E1/2_ORR) of 0.845 V further warrants the energy efficient OER/ORR process. A porotype of Al-air battery system using our catalysts as oxygen electrode and chocolate wafer as anode material is well capable of powering the light emitting diodes. This study hopefully opens a new avenue to explore cyanogenic glycosides plants product to develop multifunctional electrocatalysts. 2019 Elsevier Ltd -
Cyber secure man-in-the- middle attack intrusion detection using machine learning algorithms
The main objective of this chapter is to enhance security system in network communication by using machine learning algorithm. Cyber security network attack issues and possible machine learning solutions are also elaborated. The basic network communication component and working principle are also addressed. Cyber security and data analytics are two major pillars in modern technology. Data attackers try to attack network data in the name of man-in-the-middle attack. Machine learning algorithm is providing numerous solutions for this cyber-attack. Application of machine learning algorithm is also discussed in this chapter. The proposed method is to solve man-in-the-middle attack problem by using reinforcement machine learning algorithm. The reinforcement learning is to create virtual agent that should predict cyber-attack based on previous history. This proposed solution is to avoid future cyber middle man attack in network transmission. 2020, IGI Global. -
Cyber secure man-in-the-middle attack intrusion detection using machine learning algorithms
The main objective of this chapter is to enhance security system in network communication by using machine learning algorithm. Cyber security network attack issues and possible machine learning solutions are also elaborated. The basic network communication component and working principle are also addressed. Cyber security and data analytics are two major pillars in modern technology. Data attackers try to attack network data in the name of man-in-the-middle attack. Machine learning algorithm is providing numerous solutions for this cyber-attack. Application of machine learning algorithm is also discussed in this chapter. The proposed method is to solve man-in-the-middle attack problem by using reinforcement machine learning algorithm. The reinforcement learning is to create virtual agent that should predict cyber-attack based on previous history. This proposed solution is to avoid future cyber middle man attack in network transmission. 2022 by IGI Global. All rights reserved. -
Cyber security laws in civil aviation in India: A critical analysis /
Cybersecurity in civil aviation is becoming increasingly critical as the aviation industry in India continues to grow and evolve. With the increasing use of technology and automation in aviation, there is a growing risk of cyber threats that can affect the safety and security of civil aviation operations. This paper provides a critical analysis of the current state of cybersecurity in civil aviation in India. It examines the various cyber threats facing the aviation industry, the legal and regulatory framework for cybersecurity in India, and the measures that can be taken to enhance cybersecurity in civil aviation. The analysis highlights the need for a comprehensive and proactive approach to cybersecurity in civil aviation in India, including the implementation of robust cybersecurity policies and procedures, the adoption of international best practices, and the establishment of a dedicated cybersecurity framework for the aviation industry. -
Cyber-Physical Systems: AI and COVID-19
Cyber-Physical Systems: AI and COVID-19 highlights original research which addresses current data challenges in terms of the development of mathematical models, cyber-physical systems-based tools and techniques, and the design and development of algorithmic solutions, etc. It reviews the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS) and reviews tools and techniques that can be used. This book will act as a resource to guide COVID researchers as they move forward with clinical and epidemiological studies on this outbreak, including the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS). The major problem in the identification of COVID-19 is detection and diagnosis due to non-availability of medicine. In this situation, only one method, Reverse Transcription Polymerase Chain Reaction (RT-PCR) has been widely adopted and used for diagnosis. With the evolution of COVID-19, the global research community has implemented many machine learning and deep learning-based approaches with incremental datasets. However, finding more accurate identification and prediction methods are crucial at this juncture. 2022 Elsevier Inc. All rights reserved. -
Cyber-Secure Framework for the Insecure Designs in Healthcare Industry
Sensitive data protection has been a top priority in the healthcare industry. This has led to the investigation of safe data storage and transaction. Despite various attempts to address this issue, data breaches continue to plague the healthcare industry. This study aims to investigate prevalent storage practices and security methodologies in the healthcare, recognizing the need for a robust framework. The work further extends with design of new security framework for healthcare industry. This framework identifies critical data and implement measures to prevent unauthorized access and data tempering. The industrial hype towards the implementation of adaptive machine learning craves the need for hybrid machine learning approaches to be adapted in the cyber secure framework. In order to improve security and confidentiality in the healthcare sector. Blockchain is used in the proposed cyber secure framework promising integrity of data with the features of immutability. This proposal aims to provide a comprehensive solution to the ongoing problem of protecting medical data. Grenze Scientific Society, 2024. -
Cyber-Threat Landscape in Healthcare Industry and Legal Framework Governing Personal Health Information in India
2021 and 2022 have been the years of frequent cyberattacks. India remains in the top 25 countries severely affected by the continuous cyber-attacks and tops the list. The healthcare department is amongst the most affected area. In 2020, the healthcare department suffered a severe impact with around 348K cyber-attacks alone on Indian healthcare infrastructure. The recent occurrence of cyber-attack on AIIMS hospital in December 2022 followed by several other incidences of data breaches have made the concerned authorities pro-active on exercising vigilance and reforming the legal and technical system to protect the health infrastructure. This paper has been developed on extensive literature and focuses on describing the nature of electronic health records, the risks they are exposed to along with as to why they are so susceptible to these cyber-risks. Furthermore, the paper also deals with different kinds of threats affecting the privacy and security of electronic health records specifically. The paper analyzes Indian legal framework, briefly compares it with international legal framework (specifically US & EU) and highlights the shortcomings in Indian legislative framework followed by laying down certain recommendations primarily highlighting the possible changes required in Indian legal framework and practices that can be adopted at organizational level to overcome and mitigate such risks. N. Raizada, P. Srivastava, 2024. -
Cybercrimes in the Associated World
Phrases that scarcely existed a decade ago are now a part of our day-to-day lifestyle, as criminals use malicious new technologies to commit cyber attacks against businesses, individuals, and governments. These crimes cause serious harm and impose real threats to victims worldwide either physically or virtually. There are no borders in cyberspace. Attacks can come from any place and at any time. Cybercrime can take many forms, but they all have a digital platform/environment in common. It can be done with both good and bad intentions. But, nowadays, the most common types of cybercrime activities such as phishing scams, identity theft, Internet frauds, online intellectual property or patent infringements, online harassment, and cyber stalking are sadly very widespread in todays associated world. Cyber bullying and online harassment activities spread casually in social media posts and comments or through direct messages and also via emails. The main motive of these messages is to threaten either an individual or a group. Such kinds of cybercrime activities are extremely damaging to the victims mental health. Government agencies working to investigate cybercrimes have reported multiple records of victims developing mental illnesses and even ending up committing suicide. On the other hand we have phishing scams, one of the widespread crime activities. Organizations have detected an increase in the ratio of phishing emails to professional emails from unknown or anonymous service providers appending fake attachments and invoices. These files and attachments may contain malicious payloads to scam people and to create a backdoor in that system, so the attacker can gain access to the system anytime and from anywhere without the victims knowledge. This has been considered as one of the major advantages for the attacker. Cybercrimes have not restricted to only these forms of criminal activities. A wide variety of new attacks have been created and have spread all over the world through commonly used platforms such as social media sites, blogs, and news portals. We are living in a digital world where all our activities are being monitored by someone, somewhere - even keystrokes are being monitored using keyloggers. Nothing seems to be secret and protected unless you are tech savvy. National agencies are keeping a close watch on all individual online activities to prevent illegal activities from happening. No longer the delete option is possible in this digital world; rather, only migration of data from one location to another or from a local server to a cloud server is possible. In our day-to-day lives, several new viruses and attack mechanisms are triggered by attackers by following very new tactics with the help of more complex algorithms. So, its time to advance our knowledge on protecting our valuable assets by spending time in learning and following proper online practices. 2024 selection and editorial matter, S. Vijayalakshmi, P. Durgadevi, Lija Jacob, Balamurugan Balusamy, and Parma Nand; individual chapters, the contributors. -
Cybersecurity Disclosure and Corporate Reputation: Rising Popularity of Cybersecurity in the Business World
This chapter emphasizes the importance of cybersecurity for a corporation as todays organizations are more vulnerable than ever and their enemies are in the form of viruses and malware. The work provides evidence that cybersecurity can have an impact on brand value, market value, and overall corporate reputation. It focuses on depicting the global scenario with reference to cybersecurity disclosures by corporations and how it is important in todays digitized era where data is the most valuable and vulnerable asset. With rapid digitalization, cybersecurity has become a major concern for all businesses, especially when there is financial and reputational damage to cybersecurity breaches and incidents. Even in the absence of clear cybersecurity laws and regulations, corporations are opting for voluntary disclosure. Existing literature explains this as an attempt to mitigate any potential risk or occurred risk through increased transparency which will build the trust of all stakeholders. 2023 by IGI Global. All rights reserved. -
Cybersecurity Threats Detection in Intelligent Networks using Predictive Analytics Approaches
The modern scenario of network vulnerabilities necessitates the adoption of sophisticated detection and mitigation strategies. Predictive analytics is surfaced to be a powerful tool in the fight against cybercrime, offering unparalleled capabilities for automating tasks, analyzing vast amounts of data, and identifying complex patterns that might elude human analysts. This paper presents a comprehensive overview of how AI is transforming the field of cybersecurity. Machine intelligence can bring revolution to cybersecurity by providing advanced defense capabilities. Addressing ethical concerns, ensuring model explainability, and fostering collaboration between researchers and developers are crucial for maximizing the positive impact of AI in this critical domain. 2024 IEEE. -
Cyclic property of iterative eccentrication of a graph
The eccentric graph of a graph G, denoted by Ge, is a derived graph with the vertex set same as that of G and two vertices in Ge are adjacent if one of them is an eccentric vertex of the other. The process of constructing iterative eccentric graphs, denoted by Gek is called eccentrication. A graph G is said to be ?-cyclic(t,l) if G,Ge,Ge2,...,Gek,Gek+1,...,Gek+l are the only non-isomorphic graphs, and the graph Gek+l+1 is isomorphic to Gek. In this paper, we prove the existence of an ?-cycle for any simple graph. The importance of this result lies in the fact that the enumeration of eccentrication of a graph reduces to a finite problem. Furthermore, the enumeration of a corresponding sequence of graph parameters such as chromatic number, domination number, independence number, minimum and maximum degree, etc., reduces to a finite problem. 2023 World Scientific Publishing Company. -
Cytogenetic Consequences Of Food Industry Workers Occupationally Exposed To Cooking Oil Fumes (Cofs)
Background: Cooking oil fumes (COFs) with smoking habits is a substantial risk that aggravates genetic modifications. The current study was to estimate the biological markers of genetic toxicity counting Micronucleus changes (MN), Chromosome Aberrations (CA) and DNA modifications among COFs exposures and control subjects inherent from South India. Materials and Methods: Present analysis comprised 212 COFs with tobacco users and equivalent number of control subjects. Results: High frequency of CA (Chromatid type: and chromosome type) were identified in group II experimental subjects also high amount of MN and DNA damage frequency were significantly (p < 0.05) in both subjects (experimental smokers and non-smokers). Present analysis was observed absence of consciousnessamong the COFs exposures about the destructive level of health effects of tobacco habits in working environment. Conclusion: COFs exposed workers with tobacco induce the significant alteration in chromosomal level. Furthermore, a high level of rate of genetic diseases (spontaneous abortion) were identified in the experimental subjects. This finding will be helpful for preventive measures of COFs exposed workers and supportive for further molecular analysis 2021,Asian Pacific Journal of Cancer Prevention. All Rights Reserved. -
Cytokine see-saw across pregnancy, its related complexities and consequences
During pregnancy, a woman's immune system adapts to the changing hormonal concentrations, causing immunologic transition. These immunologic changes are required for a full-term pregnancy, preserving the fetus' innate and adaptive immunity. Preterm labor, miscarriage, gestational diabetes mellitus, and pre-eclampsia are all caused by abnormal cytokine expression during pregnancy and childbirth. A disruption in the cytokine balance can lead to autoimmune diseases or microbiologic infections, or to autoimmune illness remission during pregnancy with postpartum recurrence. The cytokine treatments are essential and damaging to the developing fetus. The current review summarizes the known research on cytokine changes during pregnancy and their possible consequences for pregnant women. Studies suggest that customizing medication for each woman and her progesterone levels should be based on the cytokine profile of each pregnant woman. Immune cells and chemicals play an important function in development of the placenta and embryo. During pregnancy, T cells divide and move, and a careful balance between proinflammatory and anti-inflammatory cytokines is necessary. The present review focuses on the mother's endurance in generating fetal cells and the immunologic mechanism involved. 2022 International Federation of Gynecology and Obstetrics. -
Damaged Relay Station: EEG Neurofeedback Training in Isolated Bilateral Paramedian Thalamic Infarct
Stroke is a major public health concern and leads to significant disability. Bilateral thalamic infarcts are rare and can result in severe and chronic cognitive and behavioral disturbances - apathy, personality change, executive dysfunctions, and anterograde amnesia. There is a paucity of literature on neuropsychological rehabilitation in patients with bilateral thalamic infarcts. Mr. M., a 51 years old, married male, a mechanical engineer, working as a supervisor was referred for neuropsychological assessment and rehabilitation with the diagnosis of bilateral paramedian thalamic infarct after seven months of stroke. A pre-post comprehensive neuropsychological assessment of his cognition, mood, and behavior was carried out. The patient received 40 sessions of EEG-Neurofeedback Training. The results showed significant improvement in sleep, motivation, and executive functions, however, there was no significant improvement in memory. The case represents the challenges in the memory rehabilitation of patients with bilateral thalamic lesions. 2024 Neurology India, Neurological Society of India. -
Dampers to Suppress Vibrations in Hydro Turbine-Generator Shaft Due to Subsynchronous Resonance
There are numerous applications to evaluate the damage caused by subsynchronous resonance (SSR) to a turbine-generator shaft. Despite multiple applications, there are relatively few studies on shaft misalignment in the literature. In this paper, stresses in the existing turbine-generator shaft due to subsynchronous resonance were studied using finite element analysis (FEA). The 3D finite element model reveals that the most stressed part of the shaft is near the generator terminal. A new nonlinear damping scheme is modeled to reflect the torsional interaction and to suppress the mechanical vibration caused by subsynchronous resonance (SSR). Stresses developed due to the addition of capacitors in the system at high rotational speeds and deformation of the shaft during various modes of oscillations were evaluated. Experimental investigations are carried out in reaction turbine connected to a 3kVA generator. Simulation is carried out for the experimental setup using ANSYS. According to the simulation results, the damper installed near the generator terminal provides satisfactory damping performance and the subsynchronous oscillations are suppressed. 2021, Springer Nature Singapore Pte Ltd. -
Dandelion Algorithm for Optimal Location and Sizing of Battery Energy Storage Systemsin Electrical Distribution Networks
This paper describes a new way to improve the performance of an EDN by integrating distributed battery energy storage systems (BESs) in the best way possible. This method is based on the Dandelion Algorithm (DA). The search space for BES locations is first predetermined using loss sensitivity factors (LSFs), and then DA is used to determine the optimal locations and sizes. The reduction of real power distribution loss is regarded as the primary objective function, and the impact of BESs is extended to examine the network voltage profile, voltage stability, and GHG emissions. IEEE 33-busEDN is used to calculate the computational efficiency of LSF-DA. Results show that DA is more efficient than Archimedes optimization (AOA), future search algorithm(FSA), pathfinder algorithm(PFA), and butterfly optimization algorithm(BOA) algorithms. Furthermore, the results show that the proposed DA enhances all technological and environmental factors and RDN performance. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
DarcyForchheimer Nanoliquid Flow and Radiative Heat Transport over Convectively Heated Surface with Chemical Reaction
Abstract: Improving the heat transport of energy transmission fluids is a vital challenge in numerous engineering applications such as photovoltaic thermal management, heat exchangers, transport and energy-saving processes, solar collectors, automotive refrigeration, electronic equipment refrigeration, and engine applications. Nanofluids address the challenges of thermal management in engineering applications. The DarcyForchheimer flow of magneto-nanofluid initiated by a stretched plate is investigated with application of the Buongiorno model. The features of the nth order chemical reaction, Rosseland thermal energy radiation, and non-uniform heat sink/source are also scrutinized. The Buongiorno nanoliquid model is implemented, which includes the frenzied motion of the nanoparticles and the thermal diffusion of the nanoparticles (NPs). Thermal and solutal convection heating boundary conditions are also incorporated. Boundary layer approximations are used in the mathematical derivation. The non-linear control problem is deciphered with application of the RungeKutta shooting method (RKSM). The results for the relevant parameters are analyzed in dimensionless profiles. In addition, the friction factor on the plate, the heat transport rate, and the mass transport rate of the nanoparticles are calculated and analyzed. 2022, Pleiades Publishing, Ltd.