bluuebunny/crossref_metadata_2025 huggingface dataset:
Adherence to the early essential newborn care guidelines at Dong Thap General Hospital in 2021
Authors:   Medical Center of Thanh Binh District, Dong Thap Province, Tong Thi Kim Phung , Huong Nguyen Thanh ,   Hanoi University of Public Health
Published: November 2022

Objectives: Describe the adherence to the early essential newborn care (EENC) guidelines in normal deliveries and influencing factors at Dong Thap General Hospital. Methods: This is cross-sectional study design applying mixed method. Quantitative data was collected by observing 90 normal deliveries using checklist following 40 steps of EENC procedure guideline of the Ministry of Health. Qualitative data were collected from 26 key informants including 4 in-depth interviews (IDIs) with Hospital managers and 3 focus group discussions (FGDs) with midwives. Quantitative data was analyzed using descriptive statistics. Qualitative data was recorded, transcribed, and analyzed by thematic coding. Results: The rate of 90 normal births that were fully adhered to all 40 steps of the EENC procedure by midwives was only 14.4%. The rate correctly following 35-39 steps was 55.6%, 30-34 steps was 28.9%, and 27-29 steps was 1.1%. Qualitative data showed that factors positively influenced the adherence to the EENC were managers’ commitment to implement the guideline, infrastructure investment, training on EENC for staff. Whereas, factors negative affected the adherence to the EENC were inappropriate procedure, ineffective supervision and monitoring, the lack of human resources and heavy workload, and lack of collaboration of mothers. Recommendations: Dong Thap General Hospital needs to review the content of the procedure, periodically to conduct more effective supervision and monitoring, improve workforce management at Obstetric Department to ensure the implementation of the procedure; promote communication/counseling for mothers and relatives to collaborate with midwives in implementing the EENC procedure. Keywords: Adherence to Early Essential Newborn Care (EENC) guideline/procedure, normal birth, influencing factors.
Current situation of outcome medical service quality and some factors affecting at Hoan My Binh Duong hospital in 2021
Authors:   Hoan My Binh Duong hospital, Tran Quoc Thanh
Published: November 2022

The study was carried out on 252 cases by a descriptive cross-sectional method combining qualitative and quantitative at Hoan My Binh Duong Hospital. The research method using the SERVPERF toolkit was tested through Cronbach's Alpha reliability coefficient, surveyed 252 patients who came for outpatient medical examination and treatment, and conducted in-depth interviews with a number of research participants including representatives of the leaders of the study. hospital director: 01 people; Leading representative of medical examination department 01 people; Doctor working at the medical examination department 01 people; Nurses working in the outpatient medical care area: 02 people; Customer care staff: 01 people. The research results show that the service quality in the outpatient clinic, through the assessment of the patients, results in an overall average service quality score of 4.33 (±0.55) on a scale of 4.33 (±0.55). 5. Service quality is assessed as good. From the research results, the author suggests that hospitals continue to promote their advantages and promote IT applications towards smart hospitals. Keywords: Service quality, SERVPERF, Outpatient examination, Tangible factors, Trust.
Roaring Storms in the Planetary-mass Companion VHS 1256-1257 b: Hubble Space Telescope Multiepoch Monitoring Reveals Vigorous Evolution in an Ultracool Atmosphere
Authors: Zhou Yifan , Bowler Brendan P. , Apai Dániel , Kataria Tiffany , Morley Caroline V. , Bryan Marta L. , Skemer Andrew J. , Benneke Björn
Published: November 2022

The photometric and spectral variability of brown dwarfs probes heterogeneous temperature and cloud distributions and traces the atmospheric circulation patterns. We present a new 42 hr Hubble Space Telescope (HST) Wide Field Camera 3 G141 spectral time series of VHS 1256-1257 b, a late L-type planetary-mass companion that has been shown to have one of the highest variability amplitudes among substellar objects. The light curve is rapidly evolving and best fit by a combination of three sine waves with different periods and a linear trend. The amplitudes of the sine waves and the linear slope vary with the wavelength, and the corresponding spectral variability patterns match the predictions by models invoking either heterogeneous clouds or thermal profile anomalies. Combining these observations with previous HST monitoring data, we find that the peak-to-valley flux difference is 33% ± 2% with an even higher amplitude reaching 38% in the J band, the highest amplitude ever observed in a substellar object. The observed light curve can be explained by maps that are composed of zonal waves, spots, or a mixture of the two. Distinguishing the origin of rapid light curve evolution requires additional long-term monitoring. Our findings underscore the essential role of atmospheric dynamics in shaping brown-dwarf atmospheres and highlight VHS 1256-1257 b as one of the most favorable targets for studying the atmospheres, clouds, and atmospheric circulation of planets and brown dwarfs.
The Exoplanet Radius Valley from Gas-driven Planet Migration and Breaking of Resonant Chains
Authors: Izidoro André , Schlichting Hilke E. , Isella Andrea , Dasgupta Rajdeep , Zimmermann Christian , Bitsch Bertram
Published: November 2022

The size frequency distribution of exoplanet radii between 1 and 4R
⊕ is bimodal with peaks at ∼1.4 R
⊕ and ∼2.4 R
⊕, and a valley at ∼1.8 R
⊕. This radius valley separates two classes of planets—usually referred to as “super-Earths” and “mini-Neptunes”—and its origin remains debated. One model proposes that super-Earths are the outcome of photoevaporation or core-powered mass loss stripping the primordial atmospheres of the mini-Neptunes. A contrasting model interprets the radius valley as a dichotomy in the bulk compositions, where super-Earths are rocky planets and mini-Neptunes are water-ice-rich worlds. In this work, we test whether the migration model is consistent with the radius valley and how it distinguishes these views. In the migration model, planets migrate toward the disk’s inner edge, forming a chain of planets locked in resonant configurations. After the gas disk dispersal, orbital instabilities “break the chains” and promote late collisions. This model broadly matches the period-ratio and planet-multiplicity distributions of Kepler planets and accounts for resonant chains such as TRAPPIST-1, Kepler-223, and TOI-178. Here, by combining the outcome of planet formation simulations with compositional mass–radius relationships and assuming the complete loss of primordial H-rich atmospheres in late giant impacts, we show that the migration model accounts for the exoplanet radius valley and the intrasystem uniformity (“peas in a pod”) of Kepler planets. Our results suggest that planets with sizes of ∼1.4 R
⊕ are mostly rocky, whereas those with sizes of ∼2.4 R
⊕ are mostly water-ice-rich worlds. Our results do not support an exclusively rocky composition for the cores of mini-Neptunes.
Jupiter's Banding and Jets May Be Caused by Tides
Authors: Tyler Robert H.
Published: November 2022

The stratification parameters for Jupiter’s outer 3000 km shell are calculated using a density profile recently derived from observations of the NASA Juno spacecraft currently in Jovian orbit. Using these parameters, the equations of classical tidal theory for a stratified, nonhydrostatic, compressible fluid are numerically solved for sectoral tidal forcing by Io. The results support a long-standing though little discussed proposal that the banding/jets (and possibly the unexplained endogenic heat) are caused by the tides. First, general arguments from eigenmode analyses expect resonantly forced tidal modes and the scattering of the tidal response to higher spatial degrees by Jupiter’s fast rotation, with time-averaged tidal effects appearing in bands between critical latitudes (±50° for forcing by Io). Second, resonant tides and banding are specifically demonstrated in the tidal model configured with the Juno-derived stratification. While banding in the time-averaged tidal features is a robust expectation (from the well-prescribed forcing and rotation parameters) and is independent of the internal parameters, the details of the banding (e.g., number, width) are highly dependent. Hence, comparison of the tidal model with observations provides a test of the tidal hypothesis of the bands as well as assumptions of interior parameters and processes. Here, dissipation parameterized as a simple pressure relaxation term in the vertical balance equation shows a time-mean banded structure between the critical latitudes that can drive geostrophic jets matching the major observed features, including strong prograde flow at the equator. By contrast, alternate stratification/dissipation assumptions produce banded structures that do not agree with observations.
Synthesis and evaluation of inhibitory potentials of microbial biofilms and quorum-sensing by 3-(1,3-dithian-2-ylidene) pentane-2,4-dione and ethyl-2-cyano-2-(1,3-dithian-2-ylidene) acetate
Authors: Ngenge Tamfu Alfred , Boukhedena Wafia , Boudiba Sameh , Deghboudj Samir , Ceylan Ozgur
Published: November 2022

The virulence and resistance of pathogenic microorganisms are promoted by quorum-sensing (QS) mediated traits and biofilms. The development of antimicrobial agents which can reduce the incidence of microbial resistance by disrupting the establishment of biofilms and QS, constitute a suitable strategy to reduce the emergence of pathogenic strains that are resistant to antibiotics. In this study, 3-(1,3-dithian-2-ylidene) pentane-2,4-dione (1) and ethyl-2-cyano-2-(1,3-dithian-2-ylidene) acetate (2) were successfully synthesized and characterized using EIMS, 1H NMR and 13C NMR techniques. On S. aureus, both compounds had MIC (minimal inhibitory concentrations) of 0.625 mg/mL while on E. coli and C. albicans, compound 2 showed higher activity than compound 1. All compounds inhibited formation of biofilms by C. albicans and S. aureus at sub-MIC with compound 1 being more active than compound 2. On E. coli, only compound 1 inhibited biofilm formation. Violacein production of violacein in C. violaceum CV12472 and quorum sensing in C. violaceum CV026 were inhibited indicating that the compounds could block signal production and reception. Anti-quorum sensing at sub-MIC concentrations revealed by inhibition zones were 13.0±0.5 mm and 8.0±0.5 mm at MIC and MIC/2 respectively for compound 1 and for compound 2, they were 11.5±0.4 mm and 7.5±0.0 mm at MIC and MIC/2 respectively. Concentration-dependent swarming motility was exhibited by both compounds with compound 1 slightly more active than compound 2. The results indicate that the organosulphur compounds could be suitable candidates for modern antibiotics.
New faunistic records of the families Bolitophilidae and Keroplatidae (Diptera, Sciaroidea) from Morocco
Authors: Driauach Ouafaa , Chandler Peter J. , Amin El Mouden Mohamed , Belqat Boutaïna
Published: November 2022

The family Bolitophilidae is recorded for the first time from Morocco with one species Bolitophila (Bolitophila) saundersii (Curtis, 1836). Ten new species are added to the Moroccan fauna of Keroplatidae, known until now by only two species, raising the number of species currently known in Morocco to 12.
Le coaching et le tournant personnel du capitalisme
Authors: Salman Scarlett
Published: November 2022

Si les affinités entre développement personnel et capitalisme ont été soulignées, il importe d’investiguer les pratiques effectives qui s’en réclament. Cet article présente les principales conclusions d’une vaste enquête ethnographique menée dans le monde social du coaching en France à la fin des années 2000 et actualisée à la fin des années 2010. Il montre que le coaching est à la fois un révélateur et un vecteur des transformations du travail et des modes de mobilisation de ce dernier, qui dessinent un tournant personnel du capitalisme . L’ambiguïté est que le coaching se présente également comme un remède à ces évolutions et aux contradictions qu’elles entraînent. Il institue l’individu en régulateur des tensions professionnelles avec le paradoxe qu’il contribue ainsi à défausser l’organisation de ses responsabilités.
Très masculin, pas très féminine. Les variations sociales du genre
Authors: Trachman Mathieu
Published: November 2022

La majorité des femmes se disent plutôt féminines et la majorité des hommes plutôt masculins. On enregistre sans doute ici le sentiment d’être « normal » du point de vue du genre. Pour autant les positionnements de genre ne s’organisent pas de la même manière selon le sexe : un tiers des hommes se disent très masculins, alors que moins d’un quart des femmes se disent très féminines ; un peu plus de 9 % des femmes se disent « pas très féminines », alors que seuls 2 % des hommes se disent « pas très masculins ». Les variations du genre selon le sexe reflètent sans aucun doute une dévalorisation du féminin par rapport au masculin, mais aussi des questionnements sur ce qu’est être une femme ou un homme.
Job Satisfaction Among Nursing Faculty in Canada and the United States
Authors: Kippenbrock Thomas , Rosen Christopher C. , Emory Jan
Published: November 2022

Background:

Higher education wants a satisfied workforce to ensure the organization reaches their stated or evolving goals; however, if faculty are dissatisfied, there can be harmful and long-term consequences on productivity and organizational outcome. This study examined nursing faculty's job satisfaction and intent to stay in universities in the United States and Canada.

Method:

This study used a nonexperimental, survey research design with correlational analysis. The sample included 746 U.S. and Canadian nursing faculty. A secondary data source from the Collaborative on Academic Careers in Higher Education also was used; the data contained responses to an online survey.

Results:

Job satisfaction demonstrated statistically significant positive relationships with personal and family policies, collaboration, tenure clarity, institutional leadership, shared governance, and engagement.

Conclusion:

Understanding the different factors influencing job satisfaction and intent to stay is one step toward meeting the challenge of a diversified academic nursing workforce.

[
J Nurs Educ
. 2022;61(11):617–623.]
Monkeypox: How Globalization, Host Immunity, and Viral Evolution Create a New Pathogen
Authors: Barton Theresa , Oladokun Regina
Published: November 2022

Monkeypox is an
Orthopoxvirus
, endemic to West Africa and the Congo Basin. It causes an illness characterized by fever, myalgias, lymphadenopathy, and a disseminated vesicular rash. Although similar to smallpox, monkeypox is typically milder, with a lower mortality rate. Endemicity in Africa was previously reduced owing to cross-protection from smallpox vaccine but has been increasing since cessation of universal vaccination. Sporadic cases have been imported to the United States (US), with a few secondary cases. A large global outbreak in 2022 has demonstrated changing epidemiology and increased person-to-person transmission. In May 2022, a returned traveler in Massachusetts presented with monkeypox. As of October 7, 2022, 71,096 cases had been reported in 107 countries, and 26,577 of those were in the US. Most cases have been in younger people without previous smallpox vaccination and in men who have sex with men, a previously unrecognized mode of transmission.

[
Pediatr Ann
. 2022;51(11):e431–e435.]
A Review of Current Evaluation and Management Strategies in Pediatric Postacute Sequelae of COVID-19
Authors: Brugler Yonts Alexandra , Burton Justin , Jones Herbert Linda
Published: November 2022

Pediatric postacute sequelae of COVID-19 (pPASC), or long COVID, is a complex, heterogeneous, multisystem syndrome that leads to disruption in the lives of children and adolescents for months, and possibly years, after recovery from acute SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection. While the underlying pathophysiologic mechanisms of PASC are still under investigation, clinicians are facing the immediate challenges of treating these patients. In this article, we provide an overview of the current multidisciplinary evaluation of patients with pPASC. We also offer guidance on the medical, psychological, and rehabilitative management strategies based on experience with both pPASC and patients with other postviral syndromes.

[
Pediatr Ann
. 2022;51(11):e421–e425.]
A deep learning approach for vehicle velocity prediction considering the influence factors of multiple lanes
Authors: Xu Mingxing , Lin Hongyi , Liu Yang
Published: November 2022

Predicting the future velocity of vehicles is essential for the safety of autonomous driving and the Intelligent Transport System. This study investigates how the surrounding vehicles influence a driving vehicle. Based on the HighD dataset, a scenario that considers the current lane and the neighboring lanes is selected while the drivers' visual angles and visual gap angles along with other parameters in the dataset are characterized as features. To predict the velocity of a driving vehicle and calibrate the influence of surrounding vehicles, a Transformer-based model integrating the features of multiple vehicles is proposed, and different features are added to the layers while constructing the model. Moreover, the information from previous timestamps of the vehicle state is integrated to estimate the duration of the influences, since the influence of an incident is not instantaneous. In our experiments, we find that the duration of the influence on the driving state perfectly fits the driver's reaction time when maneuvers occur in the surrounding vehicles. In addition, we further quantify the importance of the influence on the vehicle velocity prediction based on the Random Forest and obtain some practical conclusions, for instance, the velocity of a vehicle is more influenced by the front vehicle in the left lane than that in the right lane, but is still mainly influenced by the front vehicle in the current lane.
Common fixed point, Baire's and Cantor's theorems in neutrosophic 2-metric spaces
Authors: Ishtiaq Umar , Ahmad Khaleel , Asjad Muhammad Imran , Ali Farhan , Jarad Fahd
Published: November 2022

These fundamental Theorems of classical analysis, namely Baire's Theorem and Cantor's Intersection Theorem in the context of Neutrosophic 2-metric spaces, are demonstrated in this article. Naschie discussed high energy physics in relation to the Baire's Theorem and the Cantor space in descriptive set theory. We describe, how to demonstrate the validity and uniqueness of the common fixed-point theorem for four mappings in Neutrosophic 2-metric spaces.
Analysis of stochastic disease including predator-prey model with fear factor and Lévy jump
Authors: He Xueqing , Liu Ming , Xu Xiaofeng
Published: November 2022

In this paper, we investigate the dynamical properties of a stochastic predator-prey model with a fear effect. We also introduce infectious disease factors into prey populations and distinguish prey populations into susceptible prey and infected prey populations. Then, we discuss the effect of Lévy noise on the population considering extreme environmental situations. First of all, we prove the existence of a unique global positive solution for this system. Second, we demonstrate the conditions for the extinction of three populations. Under the conditions that infectious diseases are effectively prevented, the conditions for the existence and extinction of susceptible prey populations and predator populations are explored. Third, the stochastic ultimate boundedness of system and the ergodic stationary distribution without Lévy noise are also demonstrated. Finally, we use numerical simulations to verify the conclusions obtained and summarize the work of the paper.
Engaging Students Through Creative Assignments and Best Practices
Authors: Tatlock Julie C. , Reiter Paula J. , Korytova-Magstadt Stepanka C.
Published: November 2022

This chapter offers several models teachers can use to better engage students in content through the use of creative assignments. It begins with the importance of effective online orientation and building student learning outcomes specific to online classes. That is followed by examples of how to use the traditional discussion forum in new ways to encourage true intellectual exchange. The chapter ends with a series of sample creative assignments that help students personalize and fully integrate complex content.
Tracing Bias in a World of Binary
Authors: Kontny Jennifer
Published: November 2022

The chapter details how the first-year writing program at a small, highly diverse, private university in the Midwest responded to the pandemic and the social unrest of the time by engaging in a wholesale revision of the information literacy curriculum. The authors aimed to build a pedagogical framework that would acknowledge the power, influence, and lure of digitally but simultaneously would trace its complex biases. In sharing the curriculum that aims to recoup central critical questions—a more holistically imagined, digital curriculum designed to bolster anti-racist pedagogy—this chapter will answer the following questions: What does digital, anti-racist, and culturally responsive information literacy curriculum look like in this moment? and What kinds of methodologies for teaching information literacy might we follow to help make space for the continual evolution required when teaching through an anti-racist, culturally responsive lens?
Diversity and Inclusive Leadership
Authors: Puntaier Elmar , Zhu Tingting
Published: November 2022

The purpose of this chapter is to assess the link between diversity and inclusive leadership from the entrepreneurial perspective. If the entrepreneur is the efficient decision maker, there is an expectation that the benefits of diversity are harnessed through an inclusive leadership mindset. Yet the literature on the diversity-inclusive leadership relation is limited, scattered across a broad field, and largely omits the entrepreneurial dimension. This chapter makes an attempt to consolidate the existing literature by conducting a systematic literature review and proposes the extension of the diversity-inclusive leadership construct by adding the entrepreneurial perspective. The inclusive entrepreneur recognizes diversity as an opportunity and adopts attitudes that promote an inclusive organizational culture that is dynamic and sustainable.
Management of Inclusion in Organizations
Authors: Calixto Sandoval Nancy Patricia , Rincon Gonzalez Victor Andres
Published: November 2022

Organizations that have inclusion policies and programs that encourage ethnic, cultural, ability, and gender diversity have higher probabilities of being more profitable, taking into account that this fact stimulates innovation and minimizes risks when making decisions. Inclusion management based on a culture of diversity seeks to promote the strengthening of innovative organizations and achieve a higher level of commitment and responsibility from employees with the company, in the development of their daily tasks in favor of achieving strategic objectives of the organization they belong. By acknowledging these arguments and understanding the importance of managing inclusion and diversity in contemporary organizations, which find themselves in a time of dynamic and turbulent environments, this chapter will cover some aspects as fundamental pillars that are suggested being implemented as pillars for the design of policies and strategies suited to each organization to advance in order to achieve greater productivity and competitiveness in the current market.
Transformational Leadership in a Diverse and Inclusive Organizational Culture
Authors: Ince Fatma
Published: November 2022

The long term and recent effects of globalization and increasing ethnic and gender diversity are turning the attention of leaders to the management of cultural differences in a diverse and inclusive organizational culture. The pressure to change or adapt requires organizations to value diversity in order to increase organizational effectiveness and synergy. Starting from this point of view, this chapter reviews and offers suggestions on how transformational leadership in an inclusive culture can create a commitment, higher performance, and sustainability with diversity management in a public organization. Understanding expectations in different circumstances is crucial to creating passionate employees with a positive attitude for the organization.
Trends in Human Talent Management of and Impact on Inclusive Organizational Culture
Authors: Ospina Bermeo Javier , Perez Miguel Angel
Published: November 2022

The purpose of the chapter is to establish a relationship between the trends in human talent management observed in the management of organizations and their impact on the construction of an inclusive organizational culture in today's business world. The relationship of these topics is intended for businessmen, managers, academics, and other interested parties to observe the importance of generating and developing an organizational culture by the new demands and trends that organizations are going through to guarantee a productive and competitive path with a sense of business sustainability. Once the concepts have been described and understood, proceed to establish a relationship that allows to intertwine them and find points of convergence that enable the organization to promote an inclusive organizational culture, considering the human talent management trends incorporated in the current organizational landscape so that organizations can better fulfill their strategic purposes.
Psychological Marketing
Authors: Kuzmanović Vladan
Published: November 2022

The chapter discusses some important questions of auto-suggestion, affirmation processes, auto and autonomous psychology, spiritual marketing, and the use of psychological techniques and health management. Psychological marketing is a set of psychological techniques, tests, and forms that individual transfer contributes to the growth of performance: repeated purchases, satisfaction, personal relationships. Auto-psychology is a psychological discipline that deals with individual psychological techniques applied by an individual in order to affirm and achieve individual goals such as happiness, affirmation, satisfaction. Self-marketing or psychological marketing is a set of individual training, psychological tests, techniques, simple rituals, or psychological protocols. Psychological marketing is spiritual marketing that applies positive and psychological practices of Zen, Taoism, Shintoism, Hinduism, and Animism. Some of the main techniques or tools are feng shui, wabi-sabi, trigram, zen office, logo, kōan, breathing techniques, anti-stress therapy, self-control, and yogi office.
Green Organizational Culture, Green Innovation, and Green Performance for Achieving Environmental Sustainability
Authors: Vargas-Hernández José G. , Maillard Carlos Alberto Rodriguez , Vargas-González Omar C.
Published: November 2022

The aim of this study is to analyze the relationships among green organizational culture, green innovation, and green performance for achieving environmental sustainability. It is assumed that green organizational culture, green innovation, and green performance are supported by environmental responsible principles, assumptions, shared values, attitudes, behaviors, initiatives, and practices in organizations. The method used is the descriptive, analytic, and reflective based on a theoretical and empirical review of the literature. The analysis concludes that alignment of green organizational culture to green innovation and green technology led to green practices and performance in the organization.
The Insider Threat Landscape and the FinTech Sector
Authors: Abaid Zainab , Saadat Ahsan , Mirza Baria Mubashar
Published: November 2022

The increased reliance on online services during the recent pandemic has compelled businesses and operations to make a major technological shift to ensure online presence. However, this online paradigm shift has also attracted malicious agents who aim to benefit from vulnerabilities in the cyber world. These attackers target a wide spectrum of sectors including healthcare, government agencies, education, and financial services. In this chapter, the impact of insider security attacks on FinTech applications is discussed. A detailed account of insider attacks applicable on FinTech applications is provided. Moreover, solutions and recommendations are provided to make FinTech applications more secure by preventing and defending against insider attacks benefitting from emerging fields like crypto-currency, micro-finance, and robo-advisors. Successful prevention and defense against these attacks will ensure that the FinTech industry can be secure and can contribute in, as laid out in UN's Sustainable Development Goals, decent work and economic growth for the masses.
Data Leakage in Business and FinTech
Authors: Chaudhry Usama Habib , Arshad Razi , Abbas Naveed Naeem , Zeerak Adeel Ahmed
Published: November 2022

With the advent of the internet and day-by-day advancement in technology, traditional services started to utilize technology to offer better, digitized, cutting-edge services. Financial services called FinTech are one such example of the adoption of cutting-edge technologies. On the other hand, with the adoption of technologies comes to the cybersecurity risks associated with them. Data leakage is one big issue in FinTech and business-related applications and services. The main aim of this chapter is to identify different ways and methods by which data leakage occurs and its adverse effects on organizations providing FinTech services. Furthermore, this chapter explores the various solutions and challenges in their implementation. It is concluded that no single solution can handle data leakage from all perspectives. Multiple solutions need to be combined and utilized to handle all scenarios.
Organisational and Individual Behavioural Susceptibility and Protection Approach for Ransomware Attacks
Authors: Bello Abubakar , Aigbefo Queen
Published: November 2022

Ransomware attacks have become complex due to the ability of networked-systems constantly used as attack-vectors for propagating the ransomware payload to victims. The threat is socially engineered, making it difficult for victims to protect their data. Confidential information resources and assets are lost and rarely recovered in an attack resulting in financial losses amounting to millions of dollars. Ongoing research is exploring avenues to solve this problem including cybersecurity awareness and training from a singularised perspective, not pluralistic, to educate users of the consequences of their actions. The purpose of this study is to gain perceptions of several industries to develop insights on how to protect organisations from becoming victims of socially engineered ransomware attacks. Using a qualitative approach, critical themes on behavioural susceptibility to socially engineered ransomware were obtained, as well as the demand for applying behavioural theories and technical controls to develop effective training and education initiatives for resisting these attacks.
Privacy-Preserving Computing via Homomorphic Encryption
Authors: Naeem Noshaba , Khan Fawad , Yaqoob Tahreem , Tahir Shahzaib
Published: November 2022

In the era of IoT and big data, an enormous amount of data being generated by various sensors and handheld devices and for sectors not limited to healthcare, commerce, smart driving, smart grids, and fintech requires privacy and security. Although security can be ensured once the data is in transit or at rest, for certain application domains need to ensure privacy computations over encrypted data. Homomorphic encryption (HE) is one mechanism that allows parties to compute any arbitrary functions in an encrypted domain. Homomorphic encryption schemes have been employed in various applied sectors for privacy preservation; however, the limiting factor of these schemes is the computational and communication overhead and associated security. This chapter reviews the types of HE schemes, the application domains, and the associated costs for privacy preserving computing and discusses the underlying mathematical hardness problems, security in the classical and post quantum era, and challenges and recommendations for tradeoff in applied domains.
Open Governance in Budgeting and Financial Reporting
Authors: Khan Md. Abir Hasan , Oulasvirta Lasse O. , Anttiroiko Ari-Veikko
Published: November 2022

This chapter discusses the adoption of open governance in public finance with a particular view to citizen-friendly budgeting and consistent financial reporting in local government in the developing country context. The authors are interested in how a concept that was developed in the Western world is adopted in developing countries. The objective is to shed light on local councilors' understanding of the conditions and development needs of open governance in budgeting and financial control in Bangladeshi municipalities. According to our survey conducted in 2018 with municipal managers and councilors, the key institutional actors consider that the conditions of open governance in local public finance are fairly good, financial information is provided systematically, and the competence level is sufficient among both citizens and representatives of local government. However, participatory methods and the utilization of digital tools in budgeting and financial reporting are still in their infancy.
The Role of Data Governance in Cybersecurity for E-Municipal Services
Authors: Çubuk Ecem Buse Sevinç , Zeren Halim Emre , Demirdöven Burcu
Published: November 2022

The “e-Municipality Project” in Turkey has developed information systems (IS) for electronic municipal services since May 2017. This chapter discusses the role of data governance in relation to implementing an effective cybersecurity strategy for the project. Data were collected using a workshop with information technology (IT) officials of municipalities and semi-structured interviews with eight information IS managers about their experiences in the project. The research revealed that good data governance has been a prerequisite for any organization focused on its potential to transform processes, decision making and performance. Data governance delivers the insights that organizations need to identify their high-value and high-risk data sets and allocate additional or specific resources to protect this data. Good data governance for secured municipal services is related to a number of trade-offs between the different actors and their responsibilities. The dichotomy between centralization and decentralization of data governance can help to understand the management of cyber risks.
How Could Machine Learning Help Healthcare Informatics Predict Coronavirus?
Authors: Strang Kenneth David
Published: November 2022

This chapter differs from most healthcare informatics studies because the focus is on conceptual COVID-19 SARS-CoV2 (coronavirus) prediction rather than detection. The research question was how state-of-the-art informatics software could be used to detect coronavirus based on the analysis of hospital patient medical records. Healthcare practitioners need artificial intelligence (AI) software to predict what has not yet happened to prepare in advance. Therefore, this chapter proposes and tests a generic AI approach to predict first-time coronavirus infection for discharged hospital patients based on data collected from their medical records. This idea could allow healthcare informatics practitioners to leverage AI software to predict which patients will be more likely to become infected by specific viruses or diseases. The concept rather than the actual model is the most valuable outcome of the study.
Overview of Operations in Health Informatics
Authors: Smith Andrew
Published: November 2022

Health systems are highly integrated organizations with complex inner workings that require efficient operational processes to succeed. The value of health systems is that they treat patients, support the treatment of patients, and ensure the information about the health and care of those patients is distributed throughout the system. Within a crisis, health systems are stressed operationally, and it takes a direct focus and strategic plan to ensure every aspect of the health data and value output is accounted for appropriately. This focus can be summarized across strategy for operations, understanding health service as a product, prioritizing health care staff and planning, and understanding how to execute an efficient business continuity plan.
Telemedicine and Digital Public Health in Pandemic Times
Authors: Eappen Philip , Olujinmi Tosin Dotun
Published: November 2022

The use of modern technologies to meet individual and population health requirements during the pandemic is analyzed and discussed, including how these advances minimized healthcare delivery challenges and aided the public health response to the pandemic. To address healthcare and population requirements, the pandemic's unprecedented challenges call for new and cutting-edge tools, including telemedicine and digital public health. Telemedicine enables medical professionals to treat patients from a distance and allows patients to get care from their homes. Telemedicine enabled medical staff to avoid needless contact with COVID-19 patients, reducing the spread of diseases within healthcare facilities. Healthcare professionals were able to treat patients remotely because of telemedicine. The efficacy of telemedicine use in the healthcare community was put to the test by the coronavirus pandemic. The coronavirus pandemic assisted in developing policies for patient and professional safety and testing the effectiveness of the healthcare community's prior use of telemedicine.
Applications of Big Data Analytics in Healthcare Informatics
Authors: Putchala Bhuvanendra , Kanala Lasya Sreevidya , Donepudi Devi Prasanna , Kondaveeti Hari Kishan
Published: November 2022

Most of the research data and medical notes are unstructured or semi-structured and can't be processed using conventional data processing techniques, which creates a surge for big data analytics. In this chapter, the authors discuss big data analytics in healthcare, sources of healthcare big data, electronic health records, and much more. The authors talk about different analytic techniques involved, as well as different big data tools such as Hadoop. This chapter explains all the applications of big data analytics in healthcare, including EHR. This chapter elaborates and explains how big data analytics is used during pandemics and its future scope in the areas of healthcare, including real-time alerts and how big data is useful in the financial management of healthcare and the use of AI and big data in strategic planning, telemedicine, and medical imaging and diagnostics. Thus, this chapter is helpful for academics, health informatics professionals, healthcare stakeholders, clinical researchers, and pharmaceutical companies interested in big data analytics in healthcare.
The Road to Data-Driven Public Health Emergency Response in the Overseas Territory of Puerto Rico
Authors: Delgado Joshua E. Villafañe , López Fabiola Cruz , Álvarez Wilmarí de Jesús , Fontán Mónica Robles , Rivera Danilo T. Pérez , Feliciano Lorenzo González
Published: November 2022

Lingering economic troubles, natural disasters, and governmental instability placed Puerto Rico in uncertainty upon the emergence of the COVID-19 pandemic. In the lack of data and urgency to establish public health strategies, young scientists in Puerto Rico developed an epidemiological and health informatics system to collect, analyze, and monitor data in real time. The work done by the interdisciplinary team resulted in real-time decisions for public health policy as insights were gleaned about the dynamics of COVID-19 propagation. In this chapter, the authors describe an eight-month project which includes a structural assessment, information flow optimization, systemic expansion and enforcement, and data-driven decision-making enhancements to health informatics systems built in Puerto Rico as a model for global health systems.
Study of Neural Machine Translation With Long Short-Term Memory Techniques
Authors: Ramaiah Mangayarkarasi , Datta Debajit , Vanmathi C.  , Agarwal Rishav
Published: November 2022

The growing demand for having a conversation amongst people who come from different areas, across the globe, resulting from globalization, has led to the development of systems like machine translations. There are techniques like statistical models, Bayesian models, etc. that were used earlier for machine translations. However, with growing expectations towards better accuracies, neural networks aided systems for translations termed as neural machine translations (NMT) have come up. Models have been proposed by several organizations like Google NMT (G-NMT) that are widely accepted and implemented. Several machine translations are also based on RNN models. This work studies neural machine translations with respect to long short-term memory (LSTM) network and compares them on the basis of several widely accepted accuracy metrics like BLEU score, precision, recall, and F1 score. Further, a combination of two LSTM models is implemented for better accuracy. This work analyzes the various LSTM models on the basis of these metrics.
Cloud Hosted Ensemble Learning-Based Rental Apartment Price Prediction Model Using Stacking Technique
Authors: Rajkumar S.  , Mary Nikitha K.  , Ramanathan L.  , Ramalingam Rajasekar , Jantwal Mudit
Published: November 2022

In this chapter, online rental listings of the city of Hyderabad are used as a data source for mapping house rent. Data points were scraped from one of the popular Indian rental websites www.nobroker.in. With the collected information, models of rental market dynamics were developed and evaluated using regression and boosting algorithms such as AdaBoost, CatBoost, LightGBM, XGBoost, KRR, ENet, and Lasso regression. An ensemble machine learning algorithm of the best combination of the aforementioned algorithms was also implemented using the stacking technique. The results of these algorithms were compared using several performance metrics such as coefficient of determination (R2 score), mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), and accuracy in order to determine the most effective model. According to further examination of results, it is clear that the ensemble machine learning algorithm does outperform the others in terms of better accuracy and reduced errors.
Acceleration of Image Processing and Computer Vision Algorithms
Authors: Ravikumar Aswathy , Sriraman Harini
Published: November 2022

Image processing combined with computer vision is creating a vast breakthrough in many research, industry-related, and social applications. The growth of big data has led to the large quantity of high-resolution images that can be used in complex applications and processing. There is a need for rapid image processing methods to find accurate and faster results for the time-crucial applications. In such cases, there is a need to accelerate the algorithms and models using the HPC systems. The acceleration of these algorithms can be obtained using hardware accelerators like GPU, TPU, FPGA, etc. The GPU and TPU are mainly used for the parallel implementation of the algorithms and processing them parallelly. The acceleration method and hardware selection are challenging since numerous accelerators are available, requiring deep knowledge and understanding of the algorithms. This chapter explains the deployment of HPC accelerators for CNN and how acceleration is achieved. The leading cloud platforms used in computer vision for acceleration are also listed.
Role of Deep Learning in Image and Video Processing
Authors: Ramaiah Alageswaran , K. S. Arun , D. Yathishan , J. Sriram , S. Palanivel
Published: November 2022

Image and video processing research is becoming an important area in the field of computer vision. There are challenges such as low-resolution images, poor quality of videos, etc. in image and video data processing. Deep learning is a machine learning technique used in the creation of AI systems. It is designed to analyse complex data by passing it through many layers of neurons. Deep learning techniques have the potential to produce cutting-edge results in difficult computer vision problems such as object identification and face recognition. In this chapter, the use of deep learning to target specific functionality in the field of computer vision such as image recovery, video classification, etc. The deep learning algorithms, such as convolutional neural networks, deep neural network, and recurrent neural networks, used in the image and video processing domain are also explored.
Hand-Crafted Feature Extraction and Deep Learning Models for Leaf Image Recognition
Authors: Gladston Angelin , B. Sucithra
Published: November 2022

Plant leaf recognition has been carried out widely using low-level features. Scale invariant feature transform technique has been used to extract the low-level features. Leaves that match based on low-level features but do not do so in semantic perspective cannot be recognized. To address this, global features are extracted and used. Similarly, convolutional neural networks, deep learning networks, and transfer learning-based neural networks have been used for leaf image recognition. Even then there are issues like leaf images in various illuminations, rotations, taken in different angle, and so on. To address such issues, the closeness among low-level features and global features are computed using multiple distance measures, and a leaf recognition framework has been proposed. Two deep network models, namely Densenet and Xception, are used in the experiments. The matched patches are evaluated both quantitatively and qualitatively. Experimental results obtained are promising for the closeness-based leaf recognition framework as well as the Densenet-based leaf recognition.
Real-Time Torpidity Detection for Drivers in Machine Learning Environments
Authors: B. Sreedevi , Karthik Durga
Published: November 2022

The World Health Organization (WHO) has conducted a survey on road accidents around the world. According to the survey, 13.5 lakh die each year due to road casualties and more concerning is that India accounts around 1.5 lakh road deaths every year. Major factors to blame on road accidents are driver carelessness, drowsiness, traffic discipline, vehicle faults, or even animal crossing. Different sensors, stability control systems, anti-breaking systems, navigation are added in the vehicles to make driving easier. Still, road accidents happen due to human mistakes. Drinking and driving and tiredness may cause a driver to go for torpidity. A machine learning system is developed to monitor the eye movements to detect if the driver is sleepy or not. If found, an alarm is issued to warn the driver to wake up or else to stop the vehicle and have a nap. In addition, if neither response is made, water sprinkling is automated on the driver's face.
A Combined Feature Selection Technique for Improving Classification Accuracy
Authors: Meganathan S. , Sumathi A. , Hanees Ahamed Lebbe
Published: November 2022

Feature selection has become revenue to many research regions that manage machine learning and data mining since it allows the classifiers to be cost-efficient, time-saving, and more precise. In this chapter, the feature selection strategy is consolidating by utilizing the combined feature selection technique, specifically recursive feature elimination, chi-square, info-gain, and principal component analysis. Machine learning algorithms like logistic regression, random support vector machine, and decision trees are applied in three different datasets that are pre-processed with combined feature selection technique. Then these algorithms are ensembled using voting classifier. The improvement in accuracy of the classifiers is observed by the impact of the combined feature selection.