Reviewerly/exHarmony huggingface dataset:
Lakehouse: A Unified Data Architecture

There is no doubt that the industries are going ablaze with the huge eruption of data.None of the sectors have remained untouched by this drastic change in a decade.Technology has crept inside each business arena and hence, it has become an essential part of every processing unit.However, the data these companies are dealing with is of a different type, size and is coming with high velocity.Well, there are so many challenges with the traditional data lake and thus companies are looking for a solution to get rid of the traditional lakes.Hence, to overcome these challenges, Lakehouse came as a Solution. I. TRADITIONAL DATA LAKE A. Data WarehouseIn the early 1980s, when the data warehouse was evolving there was a mass majority of the companies using Data Warehousing which helped companies taking advantage of Massive Parallel Processing to process a high volume of data.While Data Warehouse only supports Structured Data, it became challenging for organizations to handle Unstructured & SemiStructured Data.Even it is not possible to apply DataScience, Machine learning Stuff for analytics.Thus, Data Warehouse is not suited for many of these use cases & is not very cost-efficient.As data volumes grew even larger (big data), and as the need to manage unstructured and more complex data became more important, data warehouses had limitations: 1) Data warehouses for a huge IT project can involve high maintenance costs.2) Data warehouses only support business intelligence (BI) and reporting use cases.3) There's no capability for supporting ML use cases.4) Data warehouses lack scalability and flexibility when handling various sorts of data in a data warehouse.
ASSESSING MANDARIN PRONUNCIATION FOR TIBETAN LEARNER BY ARTIFICIAL INTELLIGENT SPEECH TECHNOLOGY

Motivation:Mandarin is the national standard language in China, which means it needs to be popularized in ethnic minority areas. Tibetan is one of the ethnic minorities with many people, and it is located in remote areas. A shortage of qualified teachers makes it difficult for Tibetan students to learn Mandarin. Various mispronunciation detection systems using speech recognition algorithms have been proposed, but no personalized feedback with native language for assessment results. Therefore, this paper proposed a method to assist Tibetan students' Mandarin pronunciation using artificial intelligent speech technology.Method: We used the hybrid Connectionist Temporal Classification (CTC) and self-attention speech recognition model to convert speech features into phonemes for detecting pronunciation errors. Then emotional speech synthesis is adopted to feedback results to the learner. In this stage, firstly, we trained the Tacotron2 model with a large scale neutral Mandarin corpus and a small scale neutral Tibetan corpus. Secondly, we added a text analyzer by front-end for obtaining the input sentence’s emotion label. Thirdly we were fine-tuning the Tacotron2 model that we trained with few emotional corpora while the emotional label was added to the Pre-net of the model. Finally, our model can synthesize Tibetan-Mandarin speech with positive and negative emotion.Result: The word error of the hybrid CTC speech recognition model is 26.5% when the CTC decoding weight is 0.2. The subjective evaluation demonstrates that synthesized emotional speech can get 4.0 of the emotional mean opinion score. We synthesized Mandarin utterances with a few mispronunciations and were repeatedly played these utterances to the 20 Tibetan students. After listening for a while, the students are asked to reread the original material. We find that the pronunciation error rate is reduced, and accuracy is enhanced. Further, 20 Tibetan students are randomly divided into two groups, and each group consists of 10 students. The first group received personalized feedback in Mandarin and Tibetan after the assessment, while the second group received neutral Mandarin feedback after the assessment. The correct pronunciation numbers of the first group are increased by 12.2%.Conclusion: We build a systematic modeling framework for Tibetan students' Mandarin mispronunciation detection. It can be applied to Tibetan Mandarin education and will effectively assist the Tibetan student to learn Mandarin. The result shows that learning Mandarin's accuracy will improve by using Mandarin-Tibetan emotional speech for positive and negative feedback.
Children’s participation rights of observed by prospective childcare teachers during their daily routines of practicum in child care center

본 연구는 예비보육교사가 하루일과를 통해 본 영유아참여권은 어떠한지 그들의 생생한 목소리를 담아내고 탐색해보고자 보육실습을 경험한 예비보육교사들의 저널을 수집, 분석하였다. 하루일과를 통해 본 영유아참여권의 모습은 몇몇 유아, 일부의 참여로도 진행되는 대·소집단활동, 영유아가 주도적으로 놀이해야 진정한 자유선택놀이, 놀이할 공간 선택에 참여하고픈 바깥놀이, 유아가 선택하지 않아 집중이 어려운 특별활동, 즐거움을 나누고 싶은 식사시간, 휴식을 명분으로 강요가 될 수 있는 낮잠시간, 배변의사보다는 실수하지 않는 것이 더 중요해질 수 있는 배변시간으로 나타났다. 이와 같은 연구결과는 보육현장에서의 영유아참여권 존중에 대한 실제를 이해하는데 도움이 될 것이고, 교사양성과정의 내용구성에 있어 영유아의 삶과 연결된 권리존중이 이루어질 수 있도록 하는데 기초자료로서 활용되어질 수 있을 것이다.In this study, the vivid witnesses and journals of the prospective childcare teachers, who had experienced the practicum in child care center, about children’s right of participation during their daily routines were obtained and investigated. Daily routines in which the children’s rights of participation should have been guaranteed were as follows: large- or small-group activities, which can be progressed with a couple of or some children; free playtime, which would be truly free when children select what to play; outdoor playtime, where children might always want to play; special activities, during which children might not concentrate because they did not choose to do those activities; mealtime, during which children would not enjoy if they are forced to eat; nap time during which children might be forced to sleep; and toilet training time, during which making no mistakes might be more important than willing to pee or poop. The results of this research would be beneficial to understand actuality of respect for children’s right of participation in the field of child care, and to use as basic data for making teacher training courses to respect children’s rights that are connected to their life.
Improved defogging algorithm for sea surface images based on dark channel prior theory

To improve the quality of the sea surface image under foggy weather, we propose an innovative single-image defogging algorithm based on the dark channel prior principle. The median filter is combined with the minimum filter for the purpose of obtaining accurate dark channel values in areas where the depth of field changes sharply. Then, the algorithm constructs a fog density detection model to obtain the atmospheric light value from the dense fog area and effectively eliminate the interference of bright spots. Subsequently, the atmospheric scattering model is applied to obtain a preliminary fog-free image. Finally, an adaptive logarithmic mapping algorithm is introduced to enhance the visual effect of the defogged image. Experimental results show that the proposed algorithm can effectively improve image quality degradation and avoid halos in the intersection region of sky and sea, Moreover, the method does not require guided filtering for transmittance refinement, which greatly improves the execution speed of the algorithm.
Noise Qualification in Bali Palm Leaf Image with Gaussian Filter Method

In improving the quality of the image basically makes the appearance of an image better than before. One thing that is done in improving the image quality is noise qualification. This noise qualification aims to reduce the level of noise contained in a digital image. In this study, the image used is the image of Bali palm leaf. There are many methods that can be used to qualify for noise. One of them is the Gaussian filter. In this study, Gaussian Filter is used as a method to qualify the noise contained in the palm leaf image. The image quality after the noise qualification process is calculated using PSNR (Peak Signal to Noise Ratio). The higher the PSNR value obtained, the better the image quality. In this study, the PSNR value obtained in the palm leaf image after processing the noise qualification is 54.7625 db.&#x0D; Keywords: Gaussian Filter, Noise, PSNR, Bali Palm Leaf, Image
Looking for the Optimal Cryptocurrency Portfolio: Benefits of Diversification

This paper contributes to the literature on cryptocurrencies by examining performance of naïve (1/N) and individual cryptocurrency portfolio of ten largest cryptocurrencies.We employ daily data and two time durations for each type of portfolio.For the investing in individual cryptocurrency portfolio, the first time duration is the full time duration from the earliest day in our data sample.The second time duration is after Covid-19.(after 1st of January 2020).For the naïve portfolio, the first time duration is the same as individual cryptocurrency portfolio.However, the second time duration is when all ten cryptocurrencies are available.(after November 10th 2018) Our result shows that investing in single cryptocurrency portfolio outperforms than naïve portfolio in both time duration.Further research could add the better performing cryptocurrency portfolio to the traditional assets portfolio and examine the performance of the combining portfolio in different time duration.
PROSPECTS FOR THE INTRODUCTION OF CLOUD TECHNOLOGIES IN THE EDUCATIONAL PROCESS OF HIGHER EDUCATION

The article explores the prospects of the introduction of cloud technologies in higher education, reveals the advantages and disadvantages of using cloud technologies in higher education. Itis determined that therelevance of the use of cloud technologiesin education is that they not only perform the functions of tools, but also provide qualitatively new learning opportunities, the formation of skills of independent learning activities, contribute to the creationof new forms of learning and education. Itis proved that competently built educational process allows to solve the main goal set by the higher school: qualitative preparation in the chosen direction of study for becoming and development of a competitive specialist. The basic direction of introduction of cloud technologies in the educational process of high school is defined qualitative preparation in the chosen direction of study for the formation and development of a competitive specialist in the professional ISSN1998-6939. Information Technologies in Education. 2020. No 1(42)31field. The most common ways of working with cloud technologies in educational institutions are identified, such as distance learning, student collaboration on projects and documents. The virtual space of the university, which aims at supporting the distance learning, management and optimization of business processes of higher education, is outlined. The cloud model, which promotes accessibility, is characterized by five basic elements, such as self-service, compatible resource, network access, separatelocation, flexibility, measured services.It is determined that the use of cloud technologies in the educational process of higher education is an important step, especially in the conditions of limited resources and the constant need for updating both software and technical component of computing laboratories, which provides the possibility of using cloud technologies and will allow to support the computer equipment of higher education facilities at a high modern level with minimalcost. It is emphasizedthat the only vulnerability of innovation is the complexity of regularly installing broadband Internet access.
Pavel A. FLORENSKIJ. Simboli dell’Eternità. Meditazioni e preghiere

It's a review of the work: Pavel A. Florenskij. Simboli dell’Eternita. Meditazioni e preghiere, editing by Anežka Žakova and Lubomir Žak (Italian language). Roma: Lipa, 2020. 248 pp. ISBN: 9788889667972.
Reducing Racial Bias in Facial Age Prediction using Unsupervised Domain Adaptation in Regression

We propose an approach for unsupervised domain adaptation for the task of estimating someone's age from a given face image. In order to avoid the propagation of racial bias in most publicly available face image datasets into the inefficacy of models trained on them, we perform domain adaptation to motivate the predictor to learn features that are invariant to ethnicity, enhancing the generalization performance across faces of people from different ethnic backgrounds. Exploiting the ordinality of age, we also impose ranking constraints on the prediction of the model and design our model such that it takes as input a pair of images, and outputs both the relative age difference and the rank of the first identity with respect to the other in terms of their ages. Furthermore, we implement Multi-Dimensional Scaling to retrieve absolute ages from the predicted age differences from as few as two labeled images from the domain to be adapted to. We experiment with a publicly available dataset with age labels, dividing it into subsets based on the ethnicity labels, and evaluating the performance of our approach on the data from an ethnicity different from the one that the model is trained on. Additionally, we impose a constraint to preserve the sanity of the predictions with respect to relative and absolute ages, and another to ensure the smoothness of the predictions with respect to the input. We experiment extensively and compare various domain adaptation approaches for the task of regression.
Troublehacking as a profession of the future

This article analyzes the prospects of modern Russian development of &amp;ldquo;troublehacking&amp;rdquo; as a profession of the future. Troublehacking, as the methodology for system improvement, is founded on the two step-by-step algorithms of actions: basic algorithm for effective solution of the problems, and a simplified vector. The first one is based on the systemic analysis, risk theory, and instruments of the theory of the resolution of invention-related tasks. The second one is based on the launch of associative thinking through the analysis of register of inventive ideas of troublehacking. Troublehacking is the innovative methodology aimed at functional improvement of social systems on several levels simultaneously: from corporate to private life. In the context of school pedagogy, troublehacking is within the logic of competence approach. The authors prove that troublehacking, as a profession of the future, has great potential, as it can be implemented in both, engineering-technical and social-humanistic spheres, and is based on the competences that underlie the register of most promising professions that are recognizes as such on the international level. While the classical concept of profession is being transformed and diluted, troublehacking is open to the constantly changings social diversity. Therefore, unlike other professions, it would continue to be in high demand due to the featured universal set of competences.
[Design of Detection Module in Coagulometers Based on Dual-magnetic Circuit Beads Method].

Coagulometer, known as blood coagulation analyzer, is a product that can provide accurate test results for medical diagnosis and treatment analysis by detecting a series of items closely related to thrombosis and hemostasis in coagulation reaction. On the basis of previous traditional methods, and with our deep understanding about the principles of hemagglutination detection, we propose a hemagglutination detection method by using the dual-magnetic circuit beads method. Then, the corresponding hemagglutination detection module is designed. The coagulation time of plasma can be measured by detecting the movement of the magnetic beads when the magnetic field intensity is appropriate. The activated partial thromboplastin time(APTT) of plasma is tested when the most suitable magnetic field intensity is found. The results preliminarily show that this blood coagulation test method is valid and the corresponding test module has a potential value in business.
A Study of the Rater Training Effect in English Speaking Assessment

This paper reports the findings of an experimental study on the effect of the rater training on L1 and L2 English teacher raters in the criteria application. This study answers to the question of whether the rater training has an effect on their ratings in their test scores based on the constructs presented. The data for the study are derived from two sources: pre- and post-training ratings. The result analysis shows that the training has a considerable effect on the rating patterns, in which fluency and pragmatic resources increase significantly, while demeanor decreases after the training. It is found that the pre-trained teacher raters tend to be more severe and less consistent in their ratings than the post-trained raters. It is evident that the training has a positive effect on the criteria application. However, the English teacher raters, regardless of their L1 nativeness, still have some rating problems even after the training, although consistency has improved a lot for most constructs. All these results support the conclusion that teacher training is successful in helping the raters to give more reliable scores, but it still has limitations and has to be improved.
Residuality and Learning for Nondeterministic Register Automata

We are motivated by the following question: which data languages admit an active learning algorithm? This question was left open in previous work, and is particularly challenging for languages recognised by nondeterministic automata. To answer it, we develop the theory of residual register automata, a subclass of nondeterministic register automata. We prove that this class has canonical representatives, which can always be constructed via a finite number of observations. This property enables active learning algorithms, and makes up for the fact that residuality - a semantic property - is undecidable for register automata. Our construction for canonical residual automata is based on a machine-independent characterisation of residual languages, for which we develop new results in nominal lattice theory. Studying residuality in the context of nominal languages is a step towards a better understanding of learnability of automata with some sort of nondeterminism.
An extension of Jónsson-Tarski representation and model existence in predicate non-normal modal logics

In this paper, we give an extension of the Jónsson-Tarski representation theorem for both normal and non-normal modal algebras so that it preserves countably many infinitary meets and joins. To extend the Jónsson-Tarski representation to non-normal modal algebras we consider neighborhood frames instead of Kripke frames just as Došen's duality theorem for modal algebras, and to deal with infinite meets and joins, we make use of Q-filters instead of prime filters. Then, we show that every predicate modal logic, whether it is normal or non-normal, has a model defined on a neighborhood frame with constant domains, and give completeness theorem for some predicate modal logics. We also show the same results for infinitary modal logics.
Quantum Image Watermarking Based on Wavelet and Geometric Transformation

Like the digital watermark, which has been highlighted in previous studies, the quantum watermark aims to protect the copyright of any image and to validate its ownership using visible or invisible logos embedded in the cover image. In this paper, we propose a method to include an image logo in a cover image based on quantum fields, where a certain amount of texture is encapsulated to encode the logo image before it is included in the cover image. The method also involves transforming wavelets such as Haar base transformation and geometric transformation. These combination methods achieve a high degree of security and robustness for watermarking technology. The digital results obtained from the experiment show that the values of Peak Signal Noise Ratio (PSNR) and Mean Squared Error (MSE) that apply to one of the set cover images were 68.74 and 0.093, respectively.
A Critical Analysis of Information Security -A Case Study of Cognizant Technology Solutions

Security was not a major concern of the past in Information Technology Organizations. Butpresently, due to the vast growth in fraud and hacking techniques, the security of organizationsis a great concern. Organizations usually spend millions every year just to protect theirenvironment and to maintain security. Yet, no company claims to be a hundred percent secureas fraudulent techniques are more tricky and latest. As the hackers are becoming hard andtricky, the major Information Technology (IT) Organizations are willing to pay a large sum ofmoney for providers offering services of enterprise security schemes. The hackers are alwaysready to intrude into the company's valuable information sources. As per the recent survey by'Security Week', nearly seventy percentages of respondents have faced a security threat whichended up in the loss of valuable information or the collapse of functioning last year. Anemployer of the company can indeed be a major attacker than an outside intruder. An employeeof the company is already having all privileges to use resources of the company while variousother ways are needed for an outer intruder for accessing the same company's network or data.Cisco, the networking giant has a major focus on Enterprise Security Policies. The companyhas seen a valuable improvement in the last few decades, which shows the importance ofsecurity. Cisco had recently released data that showed a lack of security policies in about 23percentages of companies worldwide. More than 70% of Information Technology persons saythat their organizations lack behind in areas of security policy. Large numbers of IT peoplefail to practice security policies as they are not easily understandable. For every organization,policies are the building blocks. They function as road maps which each employee of thecompany uses in various ways. Developing a well-defined policy requires artistic skill. Federalagencies have a Statutory obligation is available for federal agencies for maintaining day-today security policies. The primary Information Security Officer (ISO) is usually pledged forimplementing these policies and the Chief Executive Officer (CEO) of the Company as well.The best security policies consider the vision and mission of companies, the important assetsthat need security, and security threats imposed against certain factors. All these come underrisk management which needs defect identification by business impact policies. The weaknessof a company has to be identified to find the vulnerability ratio of that company. Designing asecurity policy is not a nightmare once the major scope of policy design is identified. Themajor challenge lies in identifying the scope and threat areas for security policy. The policy isnothing but a collection of guidelines and procedures on what and how it can be implemented.In this paper, we are analyzing how Cognizant Technology Solutions (CTS) maintaining itsstandards, policies, technologies, and management policies which are defined for securing dataof an organization.
The differences of achievement of the national olympiad in chemistry at the public and private senior high school by utilizing quizizz media

This research is a quantitative study which aims to determine the results differences of the 2nd National Chemistry Olympiad at the public and private senior high school using quizizz media. All participants of the population were sampled in the determination, the sampling technique used was saturated samples. The results of the prerequisite test on the data from this study showed that the data were normally and homogeneous. For normality and homogeneity tests, obtained sig &gt; 0.05. Data analysis using SPSS 24, carried out One Way Anova test, obtained sig.0.01 with a significance level of 5%, these results indicate that there are differences in the results of the 2nd National Chemistry Olympiad (OKN) level is low, the public high school participants results with an average score of 59.48 and private high schools with an average score of 41.95 by utilizing Quizizz media. Keywords: Chemistry, Olympics, Learning, Quizizz