bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Interpersonal relationship, Satisfaction in Major, and Resilience on Nursing Students’ Adaptation to College in COVID-19 Crisis Situation
Authors:   The Korean Data Analysis Society, Choi Shinae , Ryu Mihyun , Yoo Jihye , Park Soohyun
Published: February 2023

This study aims to identify the influence of interpersonal relationships, satisfaction in major, and resilience on nursing students' adaptation to college in COVID-19 crisis situation. This study is a descriptive study with convenience sampling on 156 first-year and second-year nursing students of E university in S city. The survey was conducted from April 19, 2021 to April 21, 2021 using a paper questionnaire including relationship change scale, satisfaction in major, resilience, and student adaptation to college Questionnaire. Data were analyzed by SPSS WIN 28.0 Program, independent t-test, ANOVA, Scheffe's test, Pearson correlation coefficient, and hierarchical regression analysis. Student adaptation to college is positively correlated with resilience (r=.70, p<<.001), satisfaction in major (r=.58, p<.001), interpersonal relationship (r=.51, p<<.001). Hierarchical regression analysis showed that satisfaction in major (β=.27, p<.001) and resilience(β=.54, p<<.001) were significant predictors of student adaptation to college. The total explanation power was 52%. It is recommended to develop a program that can enhance resilience to improve the ability to adapt to college life in the COVID-19 crisis situation.
Issue Analysis using Topic Modeling: Focusing on Hatred Articles in National Daily Newspapers
Authors:   The Korean Data Analysis Society, Lim Yon Soo
Published: February 2023

This study aims to explore the possibility of using topic modeling in terms of issue analysis in tracking and detecting social issues. Among the topic modeling methods, LDA(Latent Dirichlet Allocation) based topic analysis and STM(Structural Topic Modeling) need to be used separately according to the research approach. STM is suitable for Confirmatory Data Analysis for hypothesis test, and LDA is suitable for Exploratory Data Analysis, such as issue analysis on news media. Dynamic data analysis may be possible if document categories are classified using meta-information in documents in LDA based topic modeling. In order to empirically examine, an LDA based topic analysis was conducted on hatred articles reported by 10 major national daily newspapers in Korea. From the results, all newspapers mainly dealt with hatred crimes against women in 2021, and hatred politics of politicians showed an upward trend in 2022. The direction of news reporting on the hatred issue did not show much difference among newspapers, and the characteristics of news reporting due to political bias were not large. This indicates that the issue of hatred has not yet emerged as an important issue in news coverage. In conclusion, this study demonstrates through empirical analysis that LDA based topic modeling can be fully utilized for research activities that track and detect issues.
Model Selection with Coefficient of Determination in Linear Mixed Effects Model
Authors:   The Korean Data Analysis Society, Lee Yonghee
Published: February 2023

Coefficient of determination(R²) is most popular criteria for model selection in linear regression model since it is easy to use and also explain how much proportion the candidate mode can accounts among total amount of variation in data. In linear mixed effects model, however, it is not only easy to extend definition of R² but also it is hard to interpret since variation could be defined in various ways. This article provides brief review on several different coefficients of determination proposed for linear mixed effects model. We provides detailed review on the definition and estimation methods for two extended coefficient of determinations which are based on decomposition of total variation and conditional prediction, Also we demonstrate how to use and interpret different coefficients of determination for linear mixed effects model by providing real data example from national physical test 100 project.
Multifunctional nanoscale metal-organic frameworks-polymer composites for biomedical applications
Authors: Rasheed Tahir , Kausar Fahmeeda , Anwar Muhammad Tuoqeer , Jahangir Ayesha , Bilal Muhammad , Iqbal Hafiz M.N.
Published: February 2023

Metal-organic frameworks (MOFs) are an emerging class of materials with unique properties such as extensive surface area, good stability, and high porosity, which facilitate their deployment in various fields of science, including nanomedicine. Numerous strategies have been proposed for designing nanoscale MOF-polymer composites with tailored properties. Polymers can be incorporated inside and outside of the MOF pores to prepare such composites. Polymers are directly grafted to the MOF wall via covalent linkages or physical coordination with the host. Though MOFs are associated with drawbacks like unrestrained liberation, placing of biomolecules/drugs, and less resilience under various physical conditions, a set of advantageous attributes have also been noticed, such as tuning capability and pore size of undecorated MOFs. Novel strategies have been developed to improve MOFs' functioning for bio-imaging, cancer treatment, and drug delivery. For this, the introduction of polymers has proved helpful in expanding the functionalities and diversities of MOFs. Owing to the benefits like a controlled release of drugs in response to extrinsic stimuli, boosted inclination towards targeted cells, intensified MOF durability, and increased biocompatibility, MOF-polymer composites are excellent sources of helpful implementation in the biomedical field. This study provides insight into the synthesis and performance of MOF-polymer composite as a novel candidate in the biomedical sector.
ANDROGYNOUS FASHION AND SOCIAL IDENTITY - A FASHION DESIGNERS PERSPECTIVE
Authors: Jain Neeru , Mehta Rena
Published: February 2023

Gender did begin to categorize individuals but unfortunately ended up in a complex understanding of an individual's individuality. Fashion plays a crucial role in the gender-fluid movement for expressing oneself. The Present research investigates androgynous Fashion as a social identity of the wearer in context to a fashion designer's perception. It also intends to identify a designer's idea of the evolution of gender and social identity through clothing. Fashion comprises an intense sense of historical, sociological, and semiotic examination. Gender identity is what one has to be in the community's forward-facing and not expected. Fashion has contributed much to social discrimination and is considered to be a decisive part of society. Fashion Designers are crucial in creating the concept of gender fluidity amongst the wearers. An approach to understanding and making the designers aware of the zerotye concept will help erode the taboos of gender discrimination.
TRADITIONAL CRAFT SKILLS IN INDIA- REFLECTION OF SIKKI CRAFT OF BIHAR AND PATHWAYS TO SUSTAINABILITY
Authors: Mehta Rena , Kumar Rajesh
Published: February 2023

Indian Handicrafts have a value beyond the capacity to earn and make a profit. The myriad craft is the living links to the past, including the perseverance of cultural meaning for the future. The present research focuses on defending the traditional knowledge of the skills taught in the craftsmen of the villages of India. This paper is aimed at documenting the Sikki craft of Bakuli, Bihar, India. Exploring and reflecting cultural phenomena and overcome the problems of cultural loss and intellectual potential of the craftsmen. An ethnographic research design with visual documentation was used to collect the data regarding the production of the craft, to bump up the income of the products & to sustain the skills and protect the craftsmen traditional knowledge resources.The cultural loses can be resolved using the product diversification strategy and designing jewellery of the craft could be a possible path to attain a platform worldwide.
AN ANALYTICAL STUDY ON IMPACT OF INVESTORS’ PROTECTION MEASURES ON PERCEPTION AND SATISFACTION OF INVESTORS
Authors: Rabari Umesh , Shah Kamini
Published: February 2023

Strict Investors’ Protection measure is to create higher accountability, transparency and integrity in Various Investment Avenues. Investors’ Protection measures includes those policies that lead to increase the faith of Investors in Investment Avenue. The aim of Investors’ Protection Measures of SEBI is to create higher accountability, transparency and integrity in securities market. Through investors’ protection measures, awareness and satisfaction of the investor can be maintained and interest of investors can be safeguarded. In this study researchers have made attempt to analyse the perception and satisfaction of investors towards investors’ protection measures. Researchers have analyzed the relationship between Expectation and Experience of investors’ protection measures and found that the performance of investors’ protection measures in majority cases are below Expectation. Investors are either satisfied or highly satisfied in all statements pertaining to satisfaction.
Nonlinear Fast Magnetosonic Waves in Solar Prominence Pillars
Authors: Ofman Leon , Kucera Therese A. , DeVore C. Richard
Published: February 2023

We investigate the properties of nonlinear fast magnetosonic (NFM) waves in a solar prominence, motivated by recent high-resolution and high-cadence Hinode/Solar Optical Telescope (SOT) observations of small-scale oscillations in a prominence pillar. As an example, we analyze the details of the 2012 February 14 Hinode/SOT observations of quasi-periodic propagating features consistent with NFM waves, imaged in emission in Ca ii and in the far blue wing of Hα. We perform wavelet analysis and find oscillations in the 1–3 minutes period range. Guided by these observations, we model the NFM waves with a three-dimensional magnetohydrodynamics (3D MHD) model, extending previous 2.5D MHD studies. The new model includes the structure of the high-density, low-temperature material of the prominence pillar embedded in the hot corona, in both potential and non-force-free sheared magnetic field configurations. The nonlinear model demonstrates the effects of mode coupling and the propagating density compressions associated with linear and NFM waves. The guided fast magnetosonic waves, together with density compressions and currents, are reproduced in the 3D pillar structure. We demonstrate for the first time the dynamic effects of the Lorentz force due to the magnetic shear in the non-force-free field on the pillar structure and on the propagation of the waves. The insights gained from the 3D MHD modeling are useful for improving the coronal seismology of prominence structures that exhibit fast MHD wave activity.
A Complete HCN Survey of the Perseus Molecular Cloud
Authors: Dame T. M. , Lada Charles J.
Published: February 2023

We present a survey of the Perseus molecular cloud in the J = 1 → 0 transition of HCN, a widely used tracer of dense molecular gas. The survey was conducted with the CfA 1.2 m telescope, which at 89 GHz has a beamwidth of 11′ and a spectral resolution of 0.85 km s−1. A total of 8.1 deg2 was surveyed on a uniform 10′ grid to a sensitivity of 14 mK per channel. We compared the survey with similar surveys of CO and dust in order to study and calibrate the HCN line as a dense-gas tracer. We find the HCN emission to extend over a considerable fraction of the cloud. We show that the HCN intensity remains linear with H2 column density well into the regime where the CO line saturates. We use radiative-transfer modeling to show that this likely results from subthermal excitation of HCN in a cloud where the column and volume densities of H2 are positively correlated. To match our HCN observations the model requires an exponential decrease in HCN abundance with increasing extinction, consistent with HCN depletion onto grains. The modeling also reveals that the mean volume density of H2 in the HCN-emitting regions is ∼104 cm−3, well below the HCN critical density. For the first time, we obtain a direct measurement of the ratio of dense-gas mass to HCN luminosity for an entire nearby molecular cloud: α(HCN) = 92 M
⊙/(K km s−1 pc2).
Modeling Solar Energetic Neutral Atoms from Solar Flares and CME-driven Shocks
Authors: Li Gang , Shih Albert Y. , Allen Robert C. , Ho George C. , Cohen Christina M. S. , Desai Mihir , Dayeh Maher A. , Mason Glenn M.
Published: February 2023

We examine the production of energetic neutral atoms (ENAs) in solar flares and coronal mass ejection (CME)-driven shocks and their subsequent propagation to 1 au. Time profiles and fluence spectra of solar ENAs at 1 au are computed for two scenarios: (1) ENAs are produced downstream at CME-driven shocks, and (2) ENAs are produced at large-scale post-flare loops in solar flares. Both the time profiles and fluence spectra for these two scenarios are vastly different. Our calculations indicate that we can use solar ENAs as a new probe to examine the underlying acceleration process of solar energetic particles (SEPs) and to differentiate the two acceleration sites: large loops in solar flares and downstream of CME-driven shocks, in large SEP events.
A High-pressure Filled Ice in the H2O–CO2–CH4 System, with Possible Consequences for the CO2–CH4 Biosignature Pair
Authors: Levi A. , Bansal A. , Sasselov D.
Published: February 2023

Here we constrain the speciation of carbon that may outgas in ocean exoplanets. Ocean exoplanets likely have at least a few percent by mass of water, which is sufficient to build a high-pressure ice layer between a rocky interior and the outer hydrosphere. We study the possible formation of a filled ice in the ternary system H2O–CO2–CH4. The incorporation of CH4 and CO2 in filled ice would be an important mechanism for transporting carbon across a high-pressure ice mantle into the atmosphere. The CH4–CO2 pair is also important as a potential biosignature. We find that a filled ice in the system H2O–CO2–CH4 is possible though enriched in CH4. CO2 cannot account for more than 15% by mole of the carbon content of the filled ice. Such a filled ice is less dense than an overlying ocean and would therefore discharge into the ocean, depressurize, and outgas its carbon content into the atmosphere. A high-pressure, water-rich mantle in ocean worlds may therefore support the transport of carbon from the interior into the atmosphere. More than 75% by mole of this carbon would be reduced. As long as CH4 exists/is produced in the interior and the ice mantle convects, thus transporting chemical species outward, a flux of carbon enriched in CH4 would outgas. If this persists over geological time it would negate atmospheric sinks for CH4, and explain low concentrations of atmospheric CO2. If the contrary is correct than the interior of the planet may be oxidizing.
Scattering Delay Mitigation in High-accuracy Pulsar Timing: Cyclic Spectroscopy Techniques
Authors: Turner Jacob E. , Stinebring Daniel R. , McLaughlin Maura A. , Archibald Anne M. , Dolch Timothy , Lynch Ryan S.
Published: February 2023

We simulate scattering delays from the interstellar medium to examine the effectiveness of three estimators in recovering these delays in pulsar timing data. Two of these estimators use the more traditional process of fitting autocorrelation functions to pulsar dynamic spectra to extract scintillation bandwidths, while the third estimator uses the newer technique of cyclic spectroscopy on baseband pulsar data to recover the interstellar medium’s impulse response function. We find that either fitting a Lorentzian or Gaussian distribution to an autocorrelation function or recovering the impulse response function from the cyclic spectrum are, on average, accurate in recovering scattering delays, although autocorrelation function estimators have a large variance, even at high signal-to-noise ratio (S/N). We find that, given sufficient S/N, cyclic spectroscopy is more accurate than both Gaussian and Lorentzian fitting for recovering scattering delays at specific epochs, suggesting that cyclic spectroscopy is a superior method for scattering estimation in high-quality data.
Simple Physics and Integrators Accurately Reproduce Mercury Instability Statistics
Authors: Abbot Dorian S. , Hernandez David M. , Hadden Sam , Webber Robert J. , Afentakis Georgios P. , Weare Jonathan
Published: February 2023

The long-term stability of the solar system is an issue of significant scientific and philosophical interest. The mechanism leading to instability is Mercury’s eccentricity being pumped up so high that Mercury either collides with Venus or is scattered into the Sun. Previously, only three five-billion-year N-body ensembles of the solar system with thousands of simulations have been run to assess long-term stability. We generate two additional ensembles, each with 2750 members, and make them publicly available at https://archive.org/details/@dorianabbot. We find that accurate Mercury instability statistics can be obtained by (1) including only the Sun and the eight planets, (2) using a simple Wisdom–Holman scheme without correctors, (3) using a basic representation of general relativity, and (4) using a time step of 3.16 days. By combining our solar system ensembles with previous ensembles, we form a 9601-member ensemble of ensembles. In this ensemble of ensembles, the logarithm of the frequency of a Mercury instability event increases linearly with time between 1.3 and 5 Gyr, suggesting that a single mechanism is responsible for Mercury instabilities in this time range and that this mechanism becomes more active as time progresses. Our work provides a robust estimate of Mercury instability statistics over the next five billion years, outlines methodologies that may be useful for exoplanet system investigations, and provides two large ensembles of publicly available solar system integrations that can serve as test beds for theoretical ideas as well as training sets for artificial intelligence schemes.
An Enhanced Testing Approach for Mobile Applications
Authors: Samir Amira , Amin Maghawry Huda , Badr Nagwa
Published: February 2023

Nowadays, there is an enormous number of mobile applications that are continuously being launched to the market. As a result of this rapid process, there is a need to increase the speed of testing process using enhanced approaches. This research aims to increase the effectiveness of the graphical user interface testing process of mobile applications. This is achieved by proposing an enhanced combinatorial-based metaheuristic approach. The proposed approach aims to maximize statement and branch coverage by applying Cuckoo search, for event selection. The approach was compared to monkey, frequency, random and greedy approaches. Experiments were conducted on different mobile applications. During the same testing time duration, the proposed approach achieved higher coverage than the other approaches. The proposed approach proved its effectiveness in mobile application testing compared to the other approaches. 
L’amour au temps de la rémission : le devenir de la sexualité de femmes sous hormonothérapie après un cancer du sein
Authors: Bethemont Donatienne
Published: February 2023

Cet article émane d’un travail de fin d’études en sexologie qui visait à interroger de quelle façon les incertitudes existentielles liées à la phase de rémission d’un cancer du sein, intensément réactivées par la persistance des effets secondaires des traitements passés comme par l’actualité de ceux de l’hormonothérapie en cours, affectent le vécu sexuel de la femme.
Une pratique vagabonde des histoires de vie : réflexion sur une utopie spatiale de la formation pour adultes en cabane itinérante
Authors: Hanser Christian H.
Published: February 2023

La Cabane Itinérante de l’infrastructure associative La Rêv’othèque/The Welcome Hut est un projet transnational qui vise l'accès aux pratiques des histoires de vie dans des lieux publics à travers un geste artistique d’hospitalité. Le partage de rêveries biographiques a lieu autour du poêle à bois d'une cabane de berger mobile, dans l'esprit de la tradition des veillées paysannes. La pratique avait été initialisée avec l'ambition de se situer en dehors les murs des universités et formations continues afin de proposer une spatialité d’écoute improvisée et horizontale dans les lieux de vie où le capital biographique des habitants reste souvent inexploré et marginal au discours public.
Al-wasīṭ
Authors: Blalack July
Published: February 2023

Le nom de Mauritanie ou La Mauritanie ayant été imposé à ce qui est aujourd’hui La République islamique de Mauritanie par les autorités coloniales, les Mauritaniens arabophones préfèrent souvent évoquer l’imaginaire saharien du Bilād Shinqīṭ dans les textes culturels, littéraires et historiques actuels. Cependant, si le Bilād Shinqīṭ est aujourd’hui utilisé comme remplaçant l’authenticité culturelle précoloniale, le concept lui-même était à l’origine aussi exogène que La Mauritanie . Cet article retrace l’évolution du Bilād Shinqīṭ à travers les histoires littéraires arabes et soutient que c’est en grande partie Aḥmad ibn al-Amīn al-Shinqīṭī (1863-1913) dans son Kitāb al-Wasīṭ fī Tarājim Udabā' al-Shinqīṭ (« Le livre de référence des littéraires shinguitiens », 1911) qui a popularisé une identité shinqīṭī , car aucun terme unitaire renvoyant à l’ensemble des tribus et émirats de langue ḥassānīya n’était largement utilisé avant lui.
Saharan sediment
Authors: Ould Moctar Hassan
Published: February 2023

Cet article interroge le rapport entre le désert du Sahara et l’imaginaire national de la Mauritanie comme « trait d’union ». Il en expose quatre niveaux imbriqués. D’abord, le Sahara a fourni aux fondateurs de l’État mauritanien les moyens de se protéger des revendications sécessionistes avant la déclaration de l’indépendance. Deuxièmement, le processus du développement urbain est formé par le milieu du désert de la capitale de Nouakchott. Troisièmement, cette expansion urbaine est aujourd’hui poussée par des rapports sociaux hiérarchiques qui incarnent à la fois l’imaginaire national moderne ainsi que des systèmes sociaux plus anciens du Sahara. Finalement, le désert fournit aux habitants des marges urbaines les moyens narratifs de relayer des expériences qui nuancent et recadrent l’imaginaire national mauritanien.
Connecting with unseen waters
Authors: Usman Saquib Ali
Published: February 2023

Cet article explore comment les habitants du Sahara établissent des liens avec l’eau, en considérant la pratique de la radiesthésie et l’histoire de la création des puits dans la région du Hodh en Mauritanie, et en explorant le rôle crucial de l’eau et des puits dans la vie sociale et culturelle du Sahara. Il présente des matériaux ethnographiques relatifs à la carrière d’un sourcier éminent, qui a joué au cours de sa vie un rôle essentiel dans le développement des ressources en eau souterraine en Mauritanie et dans les pays voisins. Cette contribution montre comment la pratique culturelle de la radiesthésie génère un savoir sur l’environnement, en (re)produisant des cartographies locales de l’abondance, en établissant des connexions avec des volumes d’eau invisibles dans les mondes souterrains, et en forgeant des relations sociales, spatiales et familiales à travers les masses d’eau et les puits.
Theoretical analysis of induced MHD Sutterby fluid flow with variable thermal conductivity and thermal slip over a stretching cylinder
Authors: Abbas Nadeem , Shatanawi Wasfi , Shatnawi Taqi A. M. , Hasan Fady
Published: February 2023

In the current analysis, steady incompressible Sutterby fluid flows over a stretching cylinder are studied. The influence of variable thermal conductivity is considered in the presence of thermal slip, Darcy resistance, and sponginess. The impact of the induced magnetic field is considered to analyze the results at the cylindrical surface. The governing equations are established as partial differential equations using the boundary layer approximation. Appropriate transformations are used to convert partial differential equations into ordinary differential equations. The numerical technique, namely (bvp4c), is applied to ordinary differential equations to develop the results. The numerical results, such as heat transfer rate and skin friction, are revealed by tabular form to demonstrate the physical impact of governing factors. The physical impact of governing factors on induced magnetic hydrodynamic, velocity, and temperature profiles is presented through various graphs. The velocity function deteriorated due to the augmentation of the Sutterby fluid parameter.
Existence of solutions by fixed point theorem of general delay fractional differential equation with $ p $-Laplacian operator
Authors: Kaushik Kirti , Kumar Anoop , Khan Aziz , Abdeljawad Thabet
Published: February 2023

In this manuscript, the main objective is to analyze the existence, uniqueness, (EU) and stability of positive solution for a general class of non-linear fractional differential equation (FDE) with fractional differential and fractional integral boundary conditions utilizing $ \phi_p $-Laplacian operator. To continue, we will apply Green's function to determine the suggested FDE's equivalent integral form. The Guo-Krasnosel'skii fixed point theorem and the properties of the $ p $-Laplacian operator are utilized to derive the existence results. Hyers-Ulam (HU) stability is additionally evaluated. Further, an application is presented to validate the effectiveness of the result.
Stakeholder Network, Relationship Marketing, and Business Model
Authors: Amine Meryem El Alaoui , Ouhna Laila
Published: February 2023

The aim of this chapter is to analysis how stakeholders' network can affect business models, and more precisely, how relationship marketing through trust and commitment intervenes in this relationship. In fact, a firm is perceived to be embedded in a network of relationships within which value is jointly created and shared in stakeholders' interactions. The relationship between a company and its stakeholders in a network provides different values and resources that can influence a business model. The strength of the ties in a network can be achieved through relationship marketing which aims the creation, development, and maintaining of a sustainable exchange relation. Indeed, relationship marketing acts through the establishment of a climate of trust and commitment between the company and the various stakeholders. This study wraps up with a proposal of a conceptual model, linking the different components of our research. The chapter has theoretical contributions, particularly in terms of the creation and development of relational value in a network .
The Influence of IT Governance Mechanisms and Value-Based Selling in an IT Supplier-SME Collaboration
Authors: Bruvik Asger Moesgaard , Larsen Tove Zöga
Published: February 2023

To be competitive, small- and medium-sized enterprises (SMEs) need information technology (IT) to enhance and support their business models. IT governance (ITG) is common in large enterprises but is poorly suited to SMEs. To provide benefits to SMEs, it is therefore essential for IT suppliers to recommend appropriate ITG mechanisms and collaborate with their SME customers. Through the structured use of ITG mechanisms and value-based selling, IT suppliers can develop suitable products and strengthen both the customers' and their own businesses. In this study, the authors used qualitative interviews to explore how IT suppliers perceive the issues their SME customers face regarding their IT and business strategies and how they handle those issues. The findings highlight the challenges that SME customers must deal with when making IT strategic decisions and investments.
Digital Transformation and Brokerage Organizing
Authors: Søndergaard Birger
Published: February 2023

This chapter focuses on managerial implications when implementing changes such as digital transformations and by doing so needing new organizing. Digital transformation has become a disruptive imperative for how to do business worldwide. A particular organizing function of brokerage will be described and discussed. The broker is an employee whose role is to promote digital innovation through changes in strategic networks of change. The broker role is articulated strategically in the organization, but the employee most often has to create results by gaining influence without formal authority. In the chapter, the role will be discussed from a managing perspective along with suggestions on how to organize and advice when recruiting for this function. Afterward, the broker function will be discussed from an employee perspective with 10 tips and tricks for employees in this role.
Culturally-Biased Language Assessment
Authors: Ulum Ömer Gökhan , Köksal Dinçay
Published: February 2023

This chapter suggests that culture and evaluation are inextricably linked. Therefore, culture should not be regarded as a phenomenon that needs to be controlled for in assessments; rather, it should be regarded as a fundamental component of assessment, beginning with its conceptualization and continuing through its design, construction, and interpretation of student performance. This study aims to discuss the relationship of culture to language assessment, teachers' awareness of cultural and linguistic bias in testing, and the negative effect of test bias on learners' motivation and performance; the ways of minimizing linguistic and cultural bias in language tests and maximizing cultural validity in classroom-based language assessment; to find out how learners and teachers from different cultures view success from a language learning perspective; and to find out how learners and teachers from different cultures view success from a cultural perspective.
CRÍTICA A UM FUTURO DETERMINADO
Authors: Rios Maria Beatriz Lugão , Alvarenga Marcia Soares de
Published: February 2023

O presente artigo, escrito em caráter de ensaio, tem por objetivo analisar as projeções do relatório “O mundo em 2021”, publicado pela revista inglesa The Economist, no qual são apontadas perspectivas para um futuro próximo, buscando desvelar seus conflitos, que não foram expressas pela visão hegemônica representada por esta publicação. A partir desta fonte documental, o artigo apresenta um breve resumo da história, ideologia e estrutura da revista. Em seguida, realiza o recorte de dois temas, dentre os vinte abordados pelo relatório, que constituem particular interesse para os estudos do campo trabalho e educação: a redução da força de trabalho, o fortalecimento do ensino híbrido  em contexto pós-pandêmico. Para análise dos temas, o artigo é apoiado no diálogo com autores do campo do materialismo histórico-dialético, destacando as formulações de Antonio Gramsci, István Mészarós, Georg Lukács, Dermeval Saviani, Gaudêncio Frigotto, a partir dos quais são apresentados contrapontos críticos aos pressupostos deterministas do que é apontado pelo referido relatório como o novo processo econômico/social. Nas considerações finais discute-se as repercussões para o sistema escolar: a universalização da ocupação laboral produtiva remunerada e a universalização da educação escolarizada em uma pauta geral de transformações das relações de trabalho acentuadas pela atual crise sanitária.

 

Palavras-chave: Trabalho e Educação. Formação Humana. The Economist. Crise sanitária.
Deep Learning-Based Speech Emotion Recognition
Authors: Sinha Arryan , Suseela G.
Published: February 2023

Speech Emotion Recognition, as described in this study, uses Neural Networks to classify the emotions expressed in each speech (SER). It’s centered upon concept where voice tone and pitch frequently reflect underlying emotion. Speech Emotion Recognition aids in the classification of elicited emotions. The MLP-Classifier is a tool for classifying emotions in a circumstance. As wave signal, allowing for flexible learning rate selection. RAVDESS (Ryerson Audio-Visual Dataset Emotional Speech and Song Database data) will be used. To extract the characteristics from particular audio input, Contrast, MFCC, Mel Spectrograph Frequency, & Chroma are some of factors that may be employed. To facilitate extraction of features from audio script, dataset will be labelled using decimal encoding. Utilizing input audio sample, precision was found to be 80.28%. Additional testing confirmed this result.
Introspection of Availability in Service Based Smart Systems Using Internet of Things (IoT)
Authors: Ramalingam Hariharan , Venkatesan V. Prasanna
Published: February 2023

Conventional systems are electrical, electro mechanical and heavy-duty industry appliance relying on monitoring, reporting, alert mechanism that are manual or semi-automated for services. As the number of systems increase, the services to these conventional systems are labor intensive, adds complexity and service time is a challenge. Internet of Things (IoT) bridges the physical world data to applications in cloud and acts as a critical interface for driving the Digital Infrastructure for organizations. Current IoT systems design is largely driven by the edge environmental parameters and requirements from software-based applications in the cloud. The constraints of the design that are governed by resources available at the edge. There are multiple use cases for IoT which includes Enterprise, consumer and Industrial applications. The design requirements such as Availability, Security, Energy savings & safety have to be considered for enabling smartness for the conventional systems which also influences cost and resources of support infrastructure. In this paper the modelling design parameters such as availability in service based smart systems is discussed and detailed using mathematical models.
Secure Online Voting System Using Blockchain
Authors: Thirumaran M. , Tiroumalmouroughane S. , Sathish Kanna M.
Published: February 2023

In large democracy like India with about 83.4 crore voters it is estimated that about 50,000 crore rupees is spent on election and it takes about 6 weeks to conduct election. So the approach of election followed in India is costly both in terms of time and money. In order to reduce the cost of time and money, in last few decades numerous methods have already been developed and one of them is to use online voting system that providers the comfort of voting from remote location. But traditional online system has its own drawbacks like data tampering, privacy breach, etc. Blockchain technology is proposed, that incorporates cryptographic properties. Blockchain technology is simply defined as a decentralized, distributed ledger that maintains the provenance of a digital asset and is considered to be utmost secure. To avoid single point of failure, two step authentication process is used which include OTP verification and Biometric authentication. To ensure the anonymity of the votes, Identity-based ring signature scheme is used.
Data Analysis and Price Prediction of Stock Market Using Machine Learning Regression Algorithms
Authors: Gavin Abishek L. , Prasanna P.K. Venkatesh , Vedha C. Veena , Sinduja A.
Published: February 2023

Stock analysis and forecasting is a very challenging study due to the unpredictable and volatile database environment. However, their patterns are often unique as they are influenced by many uncertainties, such as financial results of companies (Earnings per share), risk transactions, market sentiment, government policies, and conditions such as epidemics. Even though they are challenging our goal is to predict the accurate values within a shorter span of a dataset. In this paper we have compared and analyzed the best ML model that predicts the exact closing amount of the next few days, using three to four months of nifty50 Indian stock from Yahoo Finance. Five regression models are involved in this analysis, Linear Regression (LR), Decision Tree (DT), Support Vector Regression (SVR), SARIMAX (Integrated Seasonal Integrated Season with EXogenous features), Gated Recurrent Unit (GRU – deep learning). The performance metrics like RMSE (Root Mean Squared Error), MAE (Mean Absolute Error) and MAPE (Mean Absolute Percentage Error) are used. On the basis of our comparison, we would like to conclude that GRU provides a low error value in all three performance metrics and also gives accurate predictions compared to the other five regression models used.
Self-Driving Car Using Supervised Learning
Authors: Collins Ryan , Kumar Maurya Himanshu , Ragul Raj S.R.
Published: February 2023

In the growing field of autonomous driving, minimizing human errors lead to fatal accidents. Many companies and research groups have been working for years to achieve a fully autonomous vehicle. Self-driving cars are inevitably the future. The system to be implemented is to train and directly translate images from three cameras to steering commands. The proposed method is expected to work on local roads with or without lane markings. With just the images generated and the human steering angle as the training signal, the proposed method is expected to automatically recognize important road characteristics. A simulator (Udacity) is used to generate data for the proposed model.
Predicting and Classifying Diabetic Retinopathy (DR) Using 5-Class Label Based on Pre-Trained Deep Learning Models
Authors: Karthika S. , Durgadevi M.
Published: February 2023

Diabetic Retinopathy (DR) is a condition in which damage to the eyes occurs as a result of diabetes mellitus. It is the most frequent diabetes-related eye condition. It can also cause full blindness and vision loss. With effective eye treatment, the majority of new occurrences of diabetic retinopathy can be reduced. Early detection helps to avoid total vision loss. However, detecting it early can be difficult because it may not present symptoms in the early stages. The wide selection of fundus imaging makes classification challenging, mainly in Proliferative_DR, which includes the formation of new vessels in retina and bleeding. Pre-trained deep learning model is used on the publicly accessible retinal fundus image dataset on kaggle in this paper (APTOS 2019 Blindness Detection). Pre-processing and augmentation procedures are used to increase the accuracy of the models that have been pre-trained. The training accuracy of 8-Layer Convolutional Neural Network (CNN) and MobileNetV2 obtained is 83.07% and 85.21%. Testing accuracy achieved 71.93% using CNN & MobileNetV2 is 83.42%. The most often employed measures, such as the F1 Score, precision, and recall is used to ignore class level of label disagreement, which aids in diagnosing all phases of diabetic retinopathy. The results using a confusion matrix is analyzed, which is useful for categorising different stages of diabetic retinopathy according to severity. It also takes into account the degree of mismatch between the actual and anticipated labels.
Prediction of Eligibility for Covid-19 Vaccine Using SMLT Technique
Authors: Bisht Prajwal , Bora Vinayak , Poornima S. , Pushpalatha M.
Published: February 2023

The worldwide society was devastated by the 2019 coronavirus illness (COVID19) epidemic in Wuhan, China, which overloaded advanced medical systems around the world. The World Health Organization (WHO) is constantly monitoring and responding to the pandemic. The current rapid and exponential development in patient numbers necessitates the use of AI technology to forecast possible outcomes of infected individuals in order to provide suitable therapy. The goal is to find the machine learning-based solution that best fits the Covid19 vaccination predictions with the highest accuracy. Variable identification, univariate analysis, bivariate and multivariate analysis, missing value handling and data validation analysis, data cleaning / preparation, and data validation analysis are all accomplished using supervised machine learning technology (SMLT). Various types of data, such as visualisation, are gathered. For the entire given dataset. Proposal of a machine learning-based method for accurately predicting the suitability of Covid19 vaccine prediction.
Book Recommendation Based on Emotion in the Online Library Using CNN
Authors: Srinath R. , Ravindran Gunnapudi Sai Siddharth , Kokkalla Laxmi Narasimha
Published: February 2023

The present pandemic situation has made people not go out anywhere because it’s getting difficult to learn the concepts briefly for both lecturers and students. Concepts are learned through videos, but reading is also an important aspect of learning. This paper talks about providing books and notes in online mode to read and recommend books based on facial expressions captured from the user. This paper aims to extract faces from an image, extract the expression (eyes and lips) from it and also classify them into six types of emotions, which are Happy, Fear, Anger, Surprise, Neutral and Sad. The algorithm used for facial expression recognition is the Convolutional Neural Network algorithm, also known as CNN.
Music Recommendation System Using Machine Learning
Authors: Rajput Vinay , Rajput Hemakshi , Padmanabhan P.
Published: February 2023

Usually, people really need advice in deciding their choices. Whether it's the movie to watch on Friday night or there are some exciting new things available on e-business. In this distinctive situation, we tend to build a framework which will thus bring down new melodies to shoppers supported their previous history of listening. Now many companies today use the recommendation systems to their advantage such as flip kart and Amazon for the sale of products (e-commerce), ganna.com and music for streaming music, for the sale of clothes, for the films. It assists each business and customers as businesses get financial advantages by attracting customers and users pick up services. Nowadays, everyone uses recommender systems in various forms and they are getting better and better day by day because researchers are trying to cause them to higher and higher each day because of the sturdy competitiveness of the marketplace to provide higher and higher offerings and entice peoples. This project mainly focuses on music only for the music lovers to help them listen to songs they might love. This project allows customers to find new collections or the songs by making the lovey the list accessible for the tuning. Along these lines, the executive can assess which artist or collection would co-ordinate the client's inclinations towards the customers. For the music lovers, music is lifeline and music are a lovely part of the everyone's life because everything in this world can be related to frequency and vibrations. According to all the good things about the music and the high demand for recommendation systems in the market, we chose to do music recommendation system.
Voter Verification in an Election Using Merkle Tree
Authors: John Binoy , Singh Aakash Kumar , Sabarinathan C.
Published: February 2023

In this paper we propose a new way to verify eligible voters in a blockchain election. Usually verifying a voter in a list of eligible voters is done using linear search-based algorithms which runs with a worst-case time complexity of O(N) or O(kN). Our system shall use a Merkle tree to implement a search algorithm which runs with a worst-case time complexity of O(Log (N)). Under normal circumstances, when there are 1,000,000 eligible voters, the server would have to scan through 1,000,000 voter address hashes in order to verify a voter. In our system, only 20 hashes will be checked in order to verify a voter. The number of hashes required to calculate the number of hashes needed to process can be found out by getting the logarithm value of the number of hashes, to the base 2 since our Merkle tree has a branching factor of 2. A logarithmic algorithm will exponentially reduce the time and make the eligibility verification process more efficient. Since we are hashing the addresses of the voters before creating the tree, the privacy of the voters shall also be maintained. Instead of using a centralized database for handling the vote requests, we shall use a blockchain database in order to make this system decentralized. Making the system decentralized will make it almost impossible to tamper with the results of the election as once the election is deployed, even the owner of the election that is, the address that deploys the smart contract cannot tamper with the results or the functions in the deployed smart contract.
Transformer: Health Monitoring System Based on IoT
Authors: Mishra Naman , Yadav Avinash , Yadav Arzoo , Yadav Pritam , Yadav Pinki
Published: February 2023

Distribution Transformers performs a critical role and is one of the maximum critical electric gadget in electricity device network. For the reliability of the electricity device network, protection and tracking of transformer will become our first precedence. But sometimes due to overloading, leakages in transformer oil, overheating and overcurrent faults occurs in distribution transformer. To overcome such problems proper tracking of distribution transformer will become essential. This paper gives the one of the approach used for tracking of distribution transformer that's primarily based totally on IoT. This proposed device is designed and manufactured to screen and locate the faults of distribution transformer and straight away dispatched the message concerning fault to authenticated or related person. This approach may be very green and correct for tracking of fitness of distribution transformer.
Movie Recommendation System Using Machine Learning
Authors: Arokiaraj P. , Sandeep D.K. , Vishnu J. , Muthurasu N.
Published: February 2023

There are more number of movies has been released the user gets confusion, which movie is suit for them and difficult to choose, so to become easier the recommendation system comes into play if the user search a movie it gives a accurate result with similar various suggestion . The suggestion movies are given by the recommendation system by the user search e.g., if the movie is action, love, crime, drama or by the director the similar movies will be suggested. The recommendation systems are used to recommend movies using the user previews choice. The Sentiment Analysis which helps to analyse the users sentiments, which is based on their choice.In recent year, the sentimental analysis became one of most major things for many of the recommendation systems
Speech Accent Recognition
Authors: Shantoash C. , Vishal M. , Shruthi S. , Bharathi Gopalsamy N.
Published: February 2023

The speech accent demonstrates that accents are systematic instead of merely mistaken speech. This project allows detecting the demographic and linguistic backgrounds of the speakers by comparing different speech outputs with the speech accent archive dataset to work out which variables are key predictors of every accent. Given a recording of a speaker speaking a known script of English words, this project predicts the speaker’s language. This project aims to classify various sorts of accents, specifically foreign accents, by the language of the speaker. This project revolves round the detection of backgrounds of each individual using their speeches