Reviewerly/exHarmony huggingface dataset:
An Optimized Approach for Underwater Image Dehazing and Colour Correction

Underwater image processing is essential to meet sustainable development goals. Underwater images are susceptible to colour loss, blurriness and are hazy in nature due to presence of suspended particles. Backscattering leads to haze content in image whereas absorption causes colour distortion. Due to scattering, absorption effects and varying wavelength of different colours, there is a problem of poor visibility, non-uniform illumination and colour fading. That’s why, for real time applications, underwater images demand high level colour correction and dehazing to ensure feature extraction, visibility enhancement, edge contrast improvement and preservation of image characteristics. Requirement is to design suitable underwater image processing technique that adapts according to perceived environment with different noise levels and non-uniform illumination. Algorithm should be efficient and possess higher functionality to enhance real-world ocean environment images.
Virtual reality technologies in the educational process: Prospects and dangers

The development and implementation of new information and communication technologies provide new forms of interaction between a computer and a person. One of these forms is virtual reality. The article examines immersive virtual reality and provides an analysis of 71 Russian and foreign works devoted to the latest research in the field of studying the phenomenon of virtual reality from the point of view of pedagogical and psychological sciences. Particular attention is paid to the impact of virtual reality on brain activity, behavior and learning. The study of these issues is necessary to analyze the possibility of using virtual reality in education. The sensation of being in a virtual environment in health and disease is considered, a description of the characteristics of virtual environments used in education is given. It is shown that the use of virtual reality demonstrates excellent opportunities in education, but it can also have some negative psychophysiological effects. The review discusses the data obtained by Russian and foreign researchers on the possible psychological risks of prolonged immersion of children and adolescents in virtual reality and suggests the use of virtual reality only on the basis of preliminary testing or questioning. It is concluded that virtual reality, like any other new phenomenon, requires further study.
PENGARUH MODEL PEMBELAJARAN TIPE KOOPERATIF TIPE SCRAMBLE TERHADAP HASIL BELAJAR SISWA PADA TEMA DAERAH TEMPAT TINGGALKU KELAS IV

The results of this study indicate that the pre test results are 60.1 and the post-test results are 80,0. This is supported by the results of the correlation coefficient test. It can be seen that the correlation coefficient value is 0,627. Which means rcount (0,627)rtable (0,361) then Ha is accepted. So there is a strong relationship and there is an influence between the Scramble model on learning outcomes. It can also be seen from the results of the t test hypothesis testing where tcount≥ttable is 4,2541,701 so that is states that the hypothesis Ha is accepted.Keywords: Scramble Learning Models, Learning Outcomes
Uncertain risk parity

Risk parity is a portfolio construction technique that scales sections of a portfolio (eg, stocks, bonds, currencies, commodities) so that forecasted contributions to net portfolio risk match the budget. Because risks are measured from a point estimate of covariance, the method is subject to problems of estimation error. This paper treats covariance as uncertain in order to find a risk parity weighting that does not count on perfectly optimized hedges and is robust to changes in regime. Separately, of general interest are the uncertain risk contributions calculated en route. Reporting a portfolio’s uncertain risk decomposition puts a band around numbers and reveals fragility. For example, a market could seem hedged in a long–short portfolio but surface as the biggest risk when parameters are considered across their error range.
Towards for Human Face Detection and Acknowledgment via Artificial Intelligence

Face area is a front vision of every things that remembers finding a face for the photo. Two of the primary perspectives inside the arrangement of the general examination of face affirmation by PCs that are discussed here: the face and features face ID and face affirmation or rather face assessment. Our ideas describe investigation progress towards a substitute method to manage face affirmation. Finally, we report, robotized face affirmation system. Face area is a notable subject in biostatistics. We have perception photographic camera transparently puts for video get similarly as security purposes. The guideline piece of elbowroom of this computation is altogether more the uniqueness and underwriting. Nonetheless, face acknowledgment actually a movement of a couple of related issues: Initially, look at the images and find all the appearances. Second, based on individually face and appreciate that whether or not the face is moved in the direction of a way that is particular or awful lighting, it is up till now a comparative person. Finally select features that can be used to uncommonly perceive every face as the size and shape of the eyes, face, etc at last, taking a gander at these structures of data we need to find the person's identified. Face acknowledgment improvement is generally determined by the advancement of employments, for instance, mastercard check, picture video perception, affirmation for banking and access security structures. Likewise, is separated into areas: Detection and checking a photograph with OpenCV and Deep Learning.
Developing Industry 4.0-Based English for Hospitality Business Learning Model

This study aimed at developing English for Hospitality Business learning model which is adequate to Industry 4.0. This research applied the Research and Development research design. This study employed several research instruments, including a questionnaire, interview guide, observation field note, and expert judgment evaluation form. This study also invited a total number of six English lecturers and two experts on hospitality and management studies to participate in the study. As a result, a set of learning tools has been developed, including syllabus, lesson plan, and learning material. The syllabus made contains 14 learning outcomes distributed into sixteen learning topics in line with the hospitality management scope. The lesson plan developed has been arranged and organized with the combination of synchronous and asynchronous learning. The teaching and learning programs are designed for online and offline activities. The learning materials are arranged into a module covering learning materials, quiz, assignments, and discussion. The result of expert evaluation is 4.6 which can be classified as high-quality product. This learning model can be implemented for tourism vocational college, especially for hospitality management study program which needs the English subject as professional support to their career.
Machine Learning Based Crowd Behaviour Analysis and Prediction

Crowd behaviour has been widely known to have the ability to forecast the events a crowd could create. Crowd management can become extremely efficient if situations such as riots, mob lynching, traffic jams, accidents, stampede, etc. could be predicted beforehand. To this end many researchers have made their contributions in the past and there is still immense work being carried out currently. All the researches worked with different algorithms and techniques to analyze images or videos of crowd scenes for counting the number of people in the crowd, predicting the behaviour of the crowd and classifying an image or video as normal or abnormal crowd event. This paper, hence, is directed towards underlining the some of the major researches in this field, the approaches and algorithms adopted by them and their comparisons. Overall, this paper reviews the past researches and presents a summary of the techniques and strategies employed. At the end of this paper is the future scope of work possible in the field of crowd behaviour analysis, prediction and crowd counting.
Análisis en retrospectiva del uso de plataformas de aprendizaje virtual como estrategia para evitar la deserción de los estudiantes de nuevo ingreso en Facultades de Ingeniería

Mostly of the engineering schools in the world coincide in having high dropout rates during the first year of their new students, mainly caused by low performance in basic science subjects. Some of these academic institutions counteract this problem with the so-called “zero semester”, with face-to-face preparatory courses or, with some type of tutoring or accompaniment program for the new student; But what happens when these options are not possible to implement in the academic institution? In the Faculty of Engineering of the Autonomous University of Campeche, a leveling strategy was designed, through the implementation of a virtual propedeutic course using the academic content of the online learning platform Khan Academy. This strategy has been applied in the last two school years (2018-2019 and 2019- 2020) This project consists of a retrospective analysis of these two generations and a comparison is made with the 2017- 2018 school year, in which this strategy had not been implemented.
Assessing The Capabilities And Functionality Of The Token

At the present stage of the development of society, the digitalization of all processes of life and people's work as a new stage of its development becomes an important component.Increasingly, the population is using modern technological means for work, study, travel, etc.Most of the innovations and changes have been integrated into the economy and finance, reducing transaction costs, improving the efficiency of production and financial cycles, and ensuring the reliability and security of information resources.Modern means of payment, calculation, data analysis are all resources that directly affect the economies of individual companies, countries and regions.Innovative digital assets have found their application in various sectors of national production by being able to attract the necessary sources of financing to provide a quality new product, as well as the absence of restrictions on investment within one country.The international use of digital payment tools has led to the expansion of their use every year.Thus, in early 2017, the token was perceived only as another digital means of payment, but over time its functionality has undergone changes: tokens began to be used as securities, goods, and companies engaged in innovative technologies, began to consider this digital asset as a mechanism to protect cloud storage and, accordingly, user information.Thus, the relevance of the presented work is to study and analyze the new possibilities of the token.
COVID-19: Any Future Perspectives for Tourism in Italy?

The pandemic has strongly marked the Italian territory and had had consequences in the healthy sphere, as it is clear, and also in the social and economic fabric of the countries. The lockdown, the adoption of health safety measures and the closure of borders had immediate consequences in economies and territories. Thus, the health emergency became also a tourism and socio-economic issue. In particular, in Italy, tourism has been one of the pillars of the economic system, and certainly the impact of COVID-19 on the national tourism market has been dramatic. The tourism crisis highlighted some of the rooted tourist issues in Italy, involving, in particular, the tourist management of territories. In order to restart the design of a healthy tourism system, capable of promoting the survival of tourism and territories, had to be considered as necessary elements to restart Italian tourism such as the role of high education for quality tourism, the design of a hybrid offer to favor the development of domestic tourism and the exploration of the digital and technological field as a support tool for territorial, tourism and communication policies.
Study on LOD of Trace Elements by XRF Analysis Using BP &amp;amp; Adaboost and PLS Methods

Poisonous elements such as Cd, Hg, Pb, As, Zn, Cr, Ni, Cu etc. are commonly observed in polluted soil and hard to be removed by soil microbes. It is of significant importance to identify these poisonous elements in-situ and accurately both in qualitative and quantitative sense. In order to determine the Limit of Detection (LOD) for trace elements (e.g. Cadmium) in polluted soil samples based on Energy Dispersion X-ray fluorescence (ED-XRF) spectroscopy, approximately 60 national standard soil samples were collected and measured by an XRF equipment. The authors firstly utilize the Method Detection Limit (MDL) algorithm to calculate the LOD of trace elements, and then develop a new model called Back Propagation Adaboost (BP &amp; Adaboost) classification to determine the LOD based on a presumed tolerance error (e.g. 5%). Furthermore, the Multivariate- Partial Linear Squares Regression (M-PLSR) method is applied to regress the data and validate the LOD values. In this paper, the authors make a detailed comparison between the BP algorithm and the BP &amp; Adaboost classification algorithm under different presumed detection limits, and it is found that the detection results achieved the best qualitative prediction of Cd element (i.e. whether it exists in soil) based on the BP &amp; Adaboost algorithm. The experimental results indicate that the BP &amp; Adaboost algorithm is the most effective method to determine and decrease the LOD of trace element (such as Cd) in soil. The advantages are: It combines the classification effects of several weak classifiers, and determines that the LOD of element Cd is 0.5mg/kg with prediction error rate of 5%. Compared with the traditional methods like MDL, it is proved that the BP &amp; Adaboost algorithm is appropriate to be used in the terms of prediction accuracy. It is recommended that the BP &amp; Adaboost classification method shall be used for material analysis on XRF spectroscopy.
Background modeling from video sequences via online motion-aware RPCA

Background modeling of video frame sequences is a prerequisite for computer vision applications. Robust principal component analysis(RPCA), which aims to recover low rank matrix in applications of data mining and machine learning, has shown improved background modeling performance. Unfortunately, The traditional RPCA method considers the batch recovery of low rank matrix of all samples, which leads to higher storage cost. This paper proposes a novel online motion-aware RPCA algorithm, named OM-RPCAT, which adopt truncated nuclear norm regularization as an approximation method for of low rank constraint. And then, Two methods are employed to obtain the motion estimation matrix, the optical flow and the frame selection, which are merged into the data items to separate the foreground and background. Finally, an efficient alternating optimization algorithm is designed in an online manner. Experimental evaluations of challenging sequences demonstrate promising results over state-of-the-art methods in online application.
Revisiting the Intelligent Book: Towards seamless intelligent content and continuously deployed courses

In the early 2000s, colleagues and I developed The Intelligent Book – a suite of technologies for adaptive materials, that let students work with smart graphical exercises as if the AI was their partner rather than their marker. We envisaged a future where online content would be brimming with interactive models, lettings students explore and tinker with problems alongside AI that would guide students in their thinking. The browsers of the day were technically limited, but since then, the technological landscape of the web has transformed. Meanwhile, online education (especially during the Covid-19 pandemic) has grown the need for interactive materials that “understand what they teach” and can make explanations explorable and “proddable”. In online education, physical group activities (e.g., programming robots) are not available to us, and we see a growing need for digital experiences and models to replace the responsiveness that comes from tangible interaction with a device or experiment. Over the last two years, I have begun revisiting the ideas of the Intelligent Book for the modern technology landscape. This paper gives an early overview of the project, working once again towards infrastructure for self-publishable courses that can be full to overflowing with proddable and explorable models.
DIGITAL CURRENCIES AND THEIR POTENTIAL TO DISRUPT AND REPLACE FIAT MONEY: THE CASE OF BITCOINS

This paper aims to investigate how digital currencies have caused a drastic evolution, especially in the payment sector. It aims to further studies on how bitcoin is the most conspicuous digital currency and is perceived as disruptive innovation with the potential of replacing fiat currency. The study was employed through a case study to examine whether bitcoins are disruptive innovation or a threat to the Central Banks and Fiat money. The study adopted a mixed approach research design by using qualitative and quantitative research approaches. The literature reviewed journals were published in credible journals in various databases. The Time series analysis approach was used to forecast the future prices of bitcoins. The study used an in-sample and out-of-sample time series forecasting using the Gretl software. The ARIMA (1,2,1) Model was found to be a good fit with 85% accuracy (the Mean Absolute Percentage Error -MAPE was 15%) to forecast the future of bitcoin prices. The outcome of the forecast suggested that bitcoin price will have a gradual but insignificant increase. The results of this study also suggest that bitcoins fail to fulfill the functions of money as a store of value, medium of exchange, and unit of account. This is attributed to high price volatility, lack of centralization, and exposure to hackers and fraudsters. The study further suggests that bitcoins are not disruptive innovations and do not pose any threat to the Central banks and the Fiat currency in the future. The results support that bitcoin can benefit the community as well as attracting investors as a speculative investment mainly because the bitcoins are limited in transactions. The study recommends more research on the potential impact of the Central bank's digital currencies on National and Global currencies particularly because China launched its digital Yuan recently.&#x0D; &#x0D; JEL: G21; E58; E51; 031; C10&#x0D; &#x0D; &lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0790/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
Selection on <i>X</i><sub>1</sub> + <i>X</i><sub>2</sub> + ⋯ + <i>X</i><sub><i>m</i></sub> via Cartesian product trees

Selection on the Cartesian product is a classic problem in computer science. Recently, an optimal algorithm for selection on A + B , based on soft heaps, was introduced. By combining this approach with layer-ordered heaps (LOHs), an algorithm using a balanced binary tree of A + B selections was proposed to perform selection on X 1 + X 2 + ⋯ + X m in o ( n ⋅ m + k ⋅ m ), where X i have length n . Here, that o ( n ⋅ m + k ⋅ m ) algorithm is combined with a novel, optimal LOH-based algorithm for selection on A + B (without a soft heap). Performance of algorithms for selection on X 1 + X 2 + ⋯ + X m are compared empirically, demonstrating the benefit of the algorithm proposed here.
Resolving Interoperability Issues of Date with Null Value and Collection of Complex Data Types by Using JADE-WSIG Framework

In today’s world, the internet and distributed computing make things so convenient that web services can be easily built and fetch from any platform. Web services are loosely coupled, interoperable, and heterogeneous hence they help to connect web applications of different languages. Interoperability is the major factor while transferring web services from one platform to another platform.WS-I basic profile 1.0/1.1 organization provides guidelines to achieve interoperability of web services at a basic level but still, issues arise at a complex level. In this paper, we have discussed and shown the result of two interoperability issues i.e. Date with Null value and Collection of Complex data types of web services using JAVA and.NET environment. In the first issue.NET treat NULL as a value type and JAVA treats NULL as reference type in date-time data type. So, whenever a JAVA client fetches a web service built in.NET it will show a parsable error. In the second issue, a web service data structure contains elements of any type. Whenever, a web service built with the ‘ArrayOfAnyType’ data structure, it can be easily mapped to a.NET client but not to JAVA client. Hence, a data type mismatch issue arises here. To resolve these inter-platform issues, we have used JADE-WSIG as middleware between web services and agent-technology.
Ability to Pluralize Nouns

Every language has  its own  specific rules  in pluralizing noun s . This research found  the ability of students in pluralizing nouns  in English . Pluralizing nouns is divided into two forms, regular and irregular form. The objectives of the research  were to find out their  ab i l ity and problems to pluralize noun s . The instruments used in this research we re  test, and interview. The sample of this research  was  32 students. B ased  on the test, the number of the ability  was very good , 25%  (8 students) , good 38 %  (12 students), and medium , 15 %  (5  students) , while  bad  13 %  (4 students),  and very bad  9 %  (3  students).  The  pro blem s were  that  the students did not know accurately the rules or patterns how to pluralize noun in English especially the irregular ones  (63%), not understanding the materials of plural nouns (15%), feeling difficult to apply plural nouns in sentences related to concordances (13%), and Feeling confused with the process of pluralizing irregular nouns dealing with some exceptions (9%).
Effect of skill acquisition on youth employability in Nigeria

This study examined the effect of skill acquisition programme on youth employability in Nigeria.For the purpose of this study, undergraduate, graduates and post graduate individuals of Anambra State were used.The main instrument used was the structured questionnaire. 100 respondents were randomly selected from different local governments in Anambra State.Findings revealed that much emphasis on academic excellence, lack of quality skilled trainers, acute shortage of facilities, inconsistent follow up by government and poor funding are problems facing skills acquisition employment in Nigeria.Based on the premises of the findings it was recommended that teachers require professional skills development abilities, competence, years of experience through understanding of the subject matter and effective involvement of the student in the instructional delivery.