Reviewerly/exHarmony huggingface dataset:
Thresholds of Income Inequality That Mitigate the Role of Gender Inclusive Education in Promoting Gender Economic Inclusion in Sub-Saharan Africa

This study provides thresholds of inequality that should not be exceeded if gender inclusive education is to enhance gender inclusive formal economic participation in sub-Saharan Africa. The empirical evidence is based on the Generalized Method of Moments and data from 42 countries during the period 2004-2014. The following findings are established. First, inclusive tertiary education unconditionally promotes gender economic inclusion while the interaction between tertiary education and inequality is unfavorable to gender economic inclusion. Second, a Gini coefficient that nullifies the positive incidence of inclusive tertiary education on female labor force participation is 0.562. Second, the Gini coefficient and the Palma ratio that crowd-out the negative unconditional effects of inclusive tertiary education on female unemployment are 0.547 and 6.118, respectively. Third, a 0.578 Gini coefficient, a 0.680 Atkinson index and a 6.557 Palma ratio are critical masses that wipe-out the positive unconditional effects of inclusive tertiary education on female employment. Findings associated with lower levels of education are not significant. As the main policy implication, income inequality should not be tolerated above the established thresholds in order for gender inclusive education to promote gender inclusive formal economic participation. Other implications are discussed in the light of Sustainable Development Goals. This research complements the existing literature by providing inequality thresholds that should not be exceeded in order for gender inclusive education to promote the involvement of women in the formal economic sector.
Getting Started with R

In this book, we will be using the statistical computing environment R. R at its core is a programming language that specializes in statistics and data analysis. R comes with a complete set of standard packages that cover common routines in statistical analysis. However, the classic standard packages are known to be incomplete, inconsistent and difficult to master. In the past few years, Hadley Wickham has started an initiative known as the Tidyverse. Under this new dogma, a fast-growing collection of tidy packages emerged, which share a set of data engineering principles. This makes Tidyverse packages interoperable and easy to learn. This chapter introduces the reader to tidy R.
Agile Governance Guidelines for Software Development SMEs

This paper presents a PhD thesis proposal about agile governance for small and medium enterprises (SMEs) of software development. Agile adoption at the team level is now mainstream. However, many organizations continue to use traditional approaches to govern agile teams. This phenomenon, known as organizational type mismatch, has been found to have harmful effects on organizational performance and team morale. Although there are some solutions, they mostly focus on large organizations, while the SMEs domain remains unaddressed. This research proposes lightweight agile governance guidelines for software SMEs. To do this, we follow the design science framework to 1) harmonize the CMMI V2.0 governance practices with SAFe 5.0 practices; 2) contextualize the harmonization result for software development SMEs; and 3) apply a mixed-methods strategy to assess whether and, if so, to what extent our guidelines help SMEs to address the organizational type mismatch and reduce its impact.
Strategy Perspective I Learn at Home in Distance Education

The Estrategia Aprendo en Casa is a tactical direction adopted by the Ministry of Education due to the pandemic that was generated in to do the world. This study set out to determine the perception of parents of familia about the estrategia Aprendo enCasa in relation to education to distance through a cross-cutting descriptive study. A Likert-typequestioning has been used with 14 questions; this esudio showed that the parents of Familia work with thee strategia Aprendo at Home, these results are consistent with those carried out by Bustamante (2020) although the circumstances are not the same by which it can be concluded that this strategy is an alternative to continue the teaching-learning process and the parents of f amilia approve the strategy using it since they carry out activities fundamental to the well-being and development of students; proposes to collect evidence of the work done, as well as guiding families on the use of the devices.
View Synthesis: LiDAR Camera versus Depth Estimation

Depth-Image-Based Rendering (DIBR) can synthesize a virtual view image from a set of multiview images and corresponding depth maps. However, this requires an accurate depth map estimation that incurs a high compu- tational cost over several minutes per frame in DERS (MPEG-I’s Depth Estimation Reference Software) even by using a high-class computer. LiDAR cameras can thus be an alternative solution to DERS in real-time DIBR ap- plications. We compare the quality of a low-cost LiDAR camera, the Intel Realsense LiDAR L515 calibrated and configured adequately, with DERS using MPEG-I’s Reference View Synthesizer (RVS). In IV-PSNR, the LiDAR camera reaches 32.2dB view synthesis quality with a 15cm camera baseline and 40.3dB with a 2cm baseline. Though DERS outperforms the LiDAR camera with 4.2dB, the latter provides a better quality-performance trade- off. However, visual inspection demonstrates that LiDAR’s virtual views have even slightly higher quality than with DERS in most tested low-texture scene areas, except for object borders. Overall, we highly recommend using LiDAR cameras over advanced depth estimation methods (like DERS) in real-time DIBR applications. Neverthe- less, this requires delicate calibration with multiple tools further exposed in the paper.
A Survey on Protecting Confidential Data over Distributed Storage in Cloud

Cloud Computing facilitates business by storing an enormous amount of data in the cloud transmitted over the Internet with seamless access to the data and no hardware compatibility limitations. However, data during transmission is vulnerable to man in middle, known plain text, chosen cipher text, related key and pollution attack. Therefore, uploading data on a single cloud may increase the risk of damage to the confidential data. Existing literature study uncovered multiple cryptography techniques such as SA-EDS, Reliable Framework for Data Administration (RFDA), Encryption and Splitting Technique (EST) to secure data storage over multi-cloud. However, existing methods are vulnerable to numerous attacks. This article emphasis on data security issues over multi cloud and proposes a Multi Cloud Security Technique (MCST). MCST divides the data is into two categories; normal and sensitive, furthermore the sensitive data is further divided into two parts. Each part is encrypted and distributed over multi-cloud whereas the normal data is uploaded on a single cloud in encrypted form. At the decryption stage, sensitive data is merged from multi-cloud. The MST is tested against multiple attacks and it has been concluded that it is resistant to related key attack, pollution attack, chosen ciphertext attack, and known plain text attack. Furthermore, MCST has less computational time as compared to the STTN and RFD encryption method.
Ranking earthquake forecasts: On the use of proper scoring rules to discriminate forecasts

&amp;lt;p&amp;gt;Recent years have seen a growth in the diversity of probabilistic earthquake forecasts as well as the advent of them being applied operationally. The growth of their use demands a deeper look at our ability to rank their performance within a transparent and unified framework. Programs such as the Collaboratory Study for Earthquake Predictability (CSEP) &amp;amp;#160;have been at the forefront of this effort. Scores are quantitative measures of how well a dataset can be explained by a candidate forecast and allow forecasts to be ranked. A positively oriented score is said to be proper when, on average, the highest score is achieved by the closest model to the data generating one. Different meanings of closest lead to different proper scoring rules. Here, we prove that the Parimutuel Gambling score, used to evaluate the results of the 2009 Italy CSEP experiment, is generally not proper, and even for the special case where it is proper, it can still be used improperly. We show in detail the possible consequences of using this score for forecast evaluation. Moreover, we show that other well-established scores can be applied to existing studies to calculate new rankings with no requirement for extra information. We extend the analysis to show how much data are required, in principle, to distinguish candidate forecasts and therefore how likely it is to express a preference towards a forecast. This introduces the possibility of survey design with regard to the duration and spatial discretisation of earthquake forecasts. Our findings may contribute to more rigorous statements about the ability to distinguish between the predictive skills of candidate forecasts in addition to simple rankings.&amp;lt;/p&amp;gt;
Improvement of 3D Point Cloud Alignment for Super-Resolution Applications

With the prevalence of 3D scanners and 3D printers, manufacturing various 3D objects has become easier in recent years. When measuring the surface shape of an object using a 3D scanner, it is desirable to perform measurements at the highest possible resolution. However, there are many objects for which the resolution of commercial 3D scanners is insufficient. One solution to this problem is to apply super-resolution technology by measuring 3D data multiple times. It is crucial to align the 3D point clouds generated by multiple measurements accurately, but the conventional alignment methods are not accurate enough. This study aimed to improve the accuracy of the alignment process for 3D point clouds. The proposed method consists of the following four steps: (1) 3D point clouds are adaptively sampled. (2) A fast point feature histogram is used to extract features from the sampled point clouds. (3) The random sample consensus method is used to estimate an initial alignment. (4) The iterative closest point method is used to perform a precise alignment procedure. The feasibility of the proposed method is verified through experiments using real objects.
Global Scientific Output on Online Education during the Covid-19 Pandemic: Analysis of the 2020-2021 Periods

The study aims to characterize the global scientific production on online education during the Covid-19 pandemic in the period 2020-2021. To this end, the databases Scopus, Web of Science, Google Scholar, PubMed, Microsoft Academic, Dimensions and Crosreff were analyzed between January 2020 and April 2021. We worked with a universe of 1,411 articles obtained, in which the bibliometric indicators were measured using the Publish or Perish v. 7.19 software and the same analytical software of the databases chosen. The results showed a total of 3,293 citations with an average of 548.30 citations per year; 3.16 citations per article and 294.71 citations per author. On average, the publications have an h-index of 9.00, a g-index of 14.50 and an e-index of 11.54. Finally, the AW index was 15.75 and the AWCR was 401.17. These results show that the production of scientific articles on online education during the pandemic has experienced significant growth, which demonstrates the need to investigate this activity in order to measure its impact.
CHALLENGES OF THE TRANSITION FROM CLASSICAL TEACHING TO ONLINE TEACHING IN ROMANIAN SCHOOLS AS A RESULT OF THE COVID-19 PANDEMIC

Significant challenges for the education system worldwide have been generated by the COVID-19 pandemic. The article is an approach to diagnose the situation of the Romanian education system in terms of digital infrastructure, noting that, given the complexity of this issue, a comprehensive approachto all aspects and actors involved is difficult to achieve through a timely study such as the present one. Given these aspects, the analysis focused on the main actors of the educational process: school (digital integration analysis), teachers (digital skills analysis) and students (households'access to the Internet and financial possibilities). The research emphasises the key challenges for digital education in Romania.
Towards Fair Principles for Research Information: Report on a Series of Workshops

This is a summary report of the series of workshops on FAIR research information in open infrastructures that was jointly organised by the State Scientific and Technical Library of Ukraine (SSTL) and Leibniz Information Centre for Science and Technology (TIB) which have been collaborating under the framework of Joint German-Ukrainian project supported by the Federal Ministry of Education and Research of Germany and the Ministry of Science and Education of Ukraine. The workshops successfully harnessed the enthusiasm and experience of librarians, researchers, software providers, public funding body representatives, content providers, scientometricians and information specialists in an attempt to shed light and define criteria which assist discovery and reuse of research information by third-parties and make it FAIR. The series of workshops consisted of four separate workshops which addressed single aspects of FAIR – findability, accessibility, interoperability and reuse concerning research information. Due to Covid-19 travel restrictions workshops were held online between September 2020 and January 2021.
Unlocking the Full Potential of Small Data with Diverse Supervision

Virtually all of deep learning literature relies on the assumption of large amounts of available training data. Indeed, even the majority of few-shot learning methods rely on a large set of "base classes" for pre-training. This assumption, however, does not always hold. For some tasks, annotating a large number of classes can be infeasible, and even collecting the images themselves can be a challenge in some scenarios. In this paper, we study this problem and call it "Small Data" setting, in contrast to "Big Data." To unlock the full potential of small data, we propose to augment the models with annotations for other related tasks, thus increasing their generalization abilities. In particular, we use the richly annotated scene parsing dataset ADE20K to construct our realistic Long-tail Recognition with Diverse Supervision (LRDS) benchmark, by splitting the object categories into head and tail based on their distribution. Following the standard few-shot learning protocol, we use the head classes for representation learning and the tail classes for evaluation. Moreover, we further subsample the head categories and images to generate two novel settings which we call "Scarce-Class" and "Scarce-Image," respectively corresponding to the shortage of training classes and images. Finally, we analyze the effect of applying various additional supervision sources under the proposed settings. Our experiments demonstrate that densely labeling a small set of images can indeed largely remedy the small data constraints. Our code and benchmark are available at https://github.com/BinahHu/ADE-FewShot.
Aproximación ao STEAM

The article makes an approach to the STEAM educational approach, its defining characteristics and the relevance of its incorporation in the different educational stages. The integrative and interdisciplinary nature of the approach is highlighted, comprising and combining science, art, technology and the humanities.
Measuring Maintainability of Object Oriented Design (MMOOD)

Measuring maintainability early in the software development life cycle mainly at design phase is a landmark of crucial significance to software designers, developers and quality controllers. Initial Measurement of object oriented software maintainability, absolutely at design phase supports designers to increase their designs before the coding starts. Practitioners and developers repeatedly advocate that maintainability Measurement should be planned at design phase of development life cycle. This paper proposes a Maintainability Measurement Model that works at design phase of system development life cycle. Furthermore, statistical test is performed to justify the correlation of Maintainability with its key contributors Modifiability and Analyzability. The developed model has been authenticated using investigational tryout. In decision, it contains the empirical authentication of the developed maintainability measurement model.
Alteration effects in the oceanic crust: Review and recommendations

The investigation of hydrothermal seawater-oceanic crust interaction is of great scientific and practical importance. The problem is to evaluate actual hydrothermal alteration effects, including chemical element migration within the global rift systems and intraplate volcanic zones through time.
A Critical Study on the Self-esteem in Meritocracy Education : Exploring the Complementation of Self-respect Aspect

이 글의 목적은 능력주의 프레임의 교육에서 권장되는 ‘자존감’의 특성을 비판적으로 고찰하고 이를 보완하기 위한 자기관계로서 ‘자기존중’의 교육적 의미를 밝히는 데 있다. 이를 위해 먼저 사회철학 담론에서 자존감(self-esteem) 개념이 사회의 재화와 명예가 차등적으로 분배되는 데 영향을 받는 자기평가라는 점을 제시하고, 이러한 특성이 능력주의와 밀접한 관련이 있음을 논한다. 이어 교육이 능력주의 이념에 종속되어 높은 학력을 위한 경쟁의 각축장이 되는 가운데 학생들에게 자존감을 가질 것을 권장한다면, 이때의 자기평가를 위한 기준은 가시적이고 외적인 결과에 토대할 뿐만 아니라 경쟁의 승자와 패자 모두 오만과 분노를 내면화하고 인간다움을 상실할 수 있는 위험에 노출될 수 있음을 주목한다. 그리하여 인간다움을 회복하고 내적인 자기평가 기준을 마련하는 데 기여할 수 있는 개념적 자원으로서 자기존중(self-respect)을 제안한다. 자기존중 개념은 스스로에게 내리는 자기평가임에도 불구하고 타인과의 관계 속에서 형성되는 특성이 있다는 것을 밝히면서, 이를 위한 교육적 접근에서 착안할 지점을 인간다움의 표현 및 태도의 형성 측면에서 논한다. 궁극적으로 자존감과 자기존중은 상호보완적인 개념으로 이해될 수 있으며, 교육이 능력주의의 작동을 위해 일정한 역할을 할 수밖에 없지만 그 원리의 작동 바깥에서 ‘삶을 살아내는 능력’을 키우는 데에도 기여할 수 있어야 함을 제안한다.The purpose of this paper is to examine the characteristics of self-esteem recommended in education based on the Meritocracy and to clarify the educational meaning of self-respect as a self-relationship to complement it. To this end, I suggest that the concept of self-esteem in the social philosophy discourse is a self-evaluation influenced by the differential distribution of goods and honor in society and discuss these characteristics are closely related to Meritocracy. Next, it is noted that if the students are recommended to have self-esteem while education becomes a battleground for competition for high academic achievement under the Meritocracy, the criteria for self-evaluation will not only base visible and external results, but could expose both winners and losers of competition to the risk of losing their humanity. Thus, I suggest self-respect as a conceptual resource that can contribute to restoring humanity and establishing internal self-evaluation criteria. Although the concept of self-respect is self-evaluation, it has characteristics that are formed in relationships with others. I discuss the points to focus on in the educational approach for this in terms of the expression of humanity and the formulation of attitude. Ultimately, self-esteem and self-respect can be understood as complementary concepts, suggesting that although education has no choice but to play a certain role for the operation of Meritocracy, it can also contribute to developing the ‘ability to live life’ outside the operation of the principle of Meritocracy.
PERINGKAT KOMPETENSI MEMBACA SISWA SMPDI ANTARA NEGARA-NEGARA ASEAN BERDASARKAN PISA

: Indonesia still has a lot of homework, including unequal infrastructure, access to andquality of education, reading resistance, and learning orientation. All of this has an impact on thereading ability of Indonesian students. This article aims to conceptually describe the PISA reportrelated to reading ability compared to ASEAN countries. According to PISA, the reading ability ofIndonesian students is functioning 71 out of 79 countries with a score of 371. It is behind Malaysia(56), Brunei (59), and Thailand (66). Only 30% of Indonesian students show good performance atreading level 2, compared to Malaysia (59%), Thailand (40%), Brunei (38%), and the Filipina(19%). In the other hand, the trend of reading ability of Indonesian students is not progressing.Indonesia has a reading trend that is like a hump, while Malaysia and Thailand tend to be flat.This problem of reading skills can be improved by involving many groups: teachers, librarians,parents and government.Kata Kunci: PISA, literasi, OECD, skor, ketahanan membaca
Encryption and decryption of big data streams using Lightweight asymmetric method in WSN

Resource constrained devices are used in critical fields such as agriculture, smart health, industries and others. These devices produce an immense amount of data. These data streams are used for the analysis and making proper decision related to the applications. It is having restricted processing and storage capabilities which provide maximum data outcomes using less power consumption. An attacker may tamper or access data these data’s and is one of the key challenges faced by these devices. These systems are vulnerable to different security threats. Various lightweight cryptographic methods are there for solving issues like authenticity, confidentiality and data integrity. Most of these methods provide security from the attacks, but was completely secure or take more time for performing the security related encryptions steps. In this paper, a lightweight asymmetric algorithm based on RSA with key extension is proposed to provide security to the data sources generated by WSN. The enhancement is RSA is done by changing the key generation method. The system will satisfy all the key security properties. Here the proposed system is compared with existing methods in the perspective of computation time. The comparison is done for finding the better method.
Never ever or no matter what: Investigating adoption intentions and misconceptions about the corona-warn-app in Germany

To help tackle the COVID-19 pandemic, the tech community has put forward proximity detection apps to help warn people who might have been exposed to the coronavirus. The privacy implications of such apps have been discussed both in academic circles and the general population. The discussion in Germany focused on the trade-off between a centralized or decentralized approach for data collection and processing and their implications. Specifically, privacy dominated the public debate about the proposed “Corona-Warn-App.” This paper presents a study with a quota sample of the German population (n = 744) to assess what the population knew about the soon-to-be-released app and their willingness to use it. We also presented participants potential properties the app could have and asked them how these would affect their usage intention. Based on our findings, we discuss our participants' views on privacy and functionality, including their perception of selected centralized and decentralized features. We also examine a wide range of false beliefs and information that was not communicated successfully. Especially technical details, such as that the app would use Bluetooth, as opposed to location services, were unknown to many participants. Our results give insights on the complicated relationship of trust in the government and public communication on the population's willingness to adopt the app. © is held by the author/owner. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee.