Reviewerly/exHarmony huggingface dataset:
Digital Geological Outcrops Using UAVs as a Tool to Improve The Quality of Geological Modeling

Summary Rock outcrops are one of the main analogs used in geological modeling. Their use makes it possible to improve the quality of exploration work, to obtain information about the internal structure and spatial relationship of facies, as well as to create new theoretical facies models based on the processing and analysis of digitized outcrops. However, due to the incompleteness of the database of outcrops, as well as the inaccessibility and laboriousness of the process of their digitization, the method is not widely used. The use of unmanned aircraft systems (UAS) provides unique information in a safe, inexpensive and fast way. Analyzing data from an unmanned aerial vehicle (UAV) is the key to speeding up and optimizing the exploration of the geological environment. This data can be used in workflows, interpreted using automated or machine learning tools. Also, the obtained data can be used to improve the qualifications of company employees, thereby reducing the cost of field trips and eliminating the risk of work stoppages due to the inability to travel to the sites. Using data in a virtual reality environment will allow you to quickly access a database of analogs in compliance with the true dimensions and geometry.
Analysis of the Maintain of Bali Traditional Games Through Photos and Videos of Games to Improve Digital Literacy

This research is a follow-up study on the development of a website about traditional Balinese games in the previous year, because the website developed did not fully contain the types of games and game media in the form of photos and videos.This website will contain information and traditional Balinese games by searching documents about traditional games in Bali which are then integrated into the form of text, images and videos that will be published on the website.Data collection techniques used are literature study and documentation studies, interviews (FGD), and questionnaires (questionnaires).The activity plan adopts a system development life cycle consisting of planning, analysis, design, implementation (build and coding), testing and maintenance.Based on this, it can be concluded that photo and video media on websites about traditional Balinese games are very much needed (95%) considering that there is no single website that can display traditional Balinese games as a whole, and also in the midst of declining interest in reading through books and developments.increasingly modern technology in the era of industry 4.0.This research is expected to be useful for educators, education and sports offices, and the department of education and culture as well as the wider community in the form of the availability of traditional Balinese games in the form of websites equipped with photos and videos, making it easier to understand, apply, educate, socialize traditions, and develop them. in the form of policy programs for the preservation of arts and culture/traditions, especially traditional Balinese games.
A Deep Learning Approach to Manage and Reduce Plastic Waste in the Oceans

The accumulation of plastic objects in the Earth’s environment will adversely affect wildlife, wildlife habitat, and humans. The huge amount of unrecycled plastic ends up in landfill and thrown into unregulated dump sites. In many cases, specifically in the developing countries, plastic waste is thrown into rivers, streams and oceans. In this work, we employed the power of deep learning techniques in image processing and classification to recognize plastic waste. Our work aims to identify plastic texture and plastic objects in images in order to reduce plastic waste in the oceans, and facilitate waste management. For this, we use transfer learning in two ways: in the first one, a pre-trained CNN model on ImageNet is used as a feature extractor, then an SVM classifier for classification, the second strategy is based on fine tuning the pre-trained CNN model. Our approach was trained and tested using two (02) challenging datasets one is a texture recognition dataset and the other is for object detection, and achieves very satisfactory results using two (02) deep learning strategies.
Suitability of Scala

: We all are not new to the fact that data is increasing exponentially. It is increasing more than ever before, from 2 zetabytes in 2010 to 59 zetabytes in 2020. Not only this, it is predicted to be 149 zetabytes by 2024. As the data is growing and that too how the traditional methods like SQL, Excel, etc., would not be enough and feasible to analyze or store huge amount of data as they have storage and processing restrictions. It was important to use tools which are much more efficient and much more effective. To handle this ‘Big Data’ various tools were created E.g.: Hadoop, Spark, NoSQL, etc., not only this various programming languages also came into picture. Scala is just one of them. In this paper we are trying to highlight the importance of Scala, and how it is so unpopular and under-rated as compared to other programming languages; despite the fact that it is a strong statically typedgeneralpurpose programming language which supports both object oriented language and functional programming. Also, it is easy to understand and use as compared to other programming languages. In this paper we will see and discuss how Scala has been beneficial and why do we want it to gain more popularity in the industry. We will also see the cons associated and if it’s worthy enough given its cons.
Study on Information Security in Cloud Computing

Cloud computing is defined by the National Institute of Standards and Technology (NIST) as a model for providing convenient, on-demand network access to a shared pool of configurable computing resources which can be quickly provisioned and released with minimal management effort or cloud provider interaction. Cloud Computing refers to the following concepts of Grid Computing, Utility Computing, software as a service, storage in the cloud and virtualization. A client accessing a provider's service remotely is referred to as cloud. Cloud computing has the ability to redefine how businesses handle information technology while also changing the economics of hardware and software. Cloud computing promised to bring a new breed of entrepreneur to the fore, allowing them to launch their business with no upfront investment in IT equipment. The main purpose of this work is to identify privacy and security concerns among cloud computing participants and consumers in a distributed environment.
Directors &amp; Officers: just because they don’t perform technical or operational work, doesn’t mean they aren’t personally involved

In spite of the fact that modern information security and privacy attacks are now reaching epic proportions, and also gravely damaging both business and government, there remains a widespread misconception amongst the ranks of directors and officers. That misconception holds that they – the directors and officers – don’t need to personally get involved in this vitally important area. The truth is that just because they don’t do hands-on technical or operational work, that doesn’t mean they aren’t required to play a critically important role addressing these issues. Their required participation is clearly and irrefutably in evidence in authoritative legal sources such as laws, regulations, court opinions, settlement agreements, etc. The hands-off attitude, this distance from the urgency and difficulty of dealing with the problems, has unfortunately had many serious and damaging consequences. For example, the directors and officers at Equifax recently settled a breach-related lawsuit with plaintiff lawyers, to the tune of $149 million (2020, See In Re Equifax Inc. Securities Litigation, U.S. Dist. Ct. (N. Dist. Georgia, 2020), Consolidated Case No. 1:17-cv-03463-TWT). That lawsuit was based on an Equifax 2017 breach where the credit reports of some 143 million customers were disclosed to unauthorized parties. Before that, the directors and officers at Yahoo! settled a shareholders’ derivative action to the tune of $29 million (2019, For specifics, see In re Yahoo! Inc. Customer Data Sec. Breach Litig., 2019 U.S. Dist. LEXIS 15034 (2019)). The latter lawsuit was based on several breaches at Yahoo! between 2013 and 2016 involving the release of sensitive user information, and then concealment from investors of the facts about those breaches. These and other recent cases make it clear what the scope of the role, for directors and officers, is now being illuminated. To be specific, their role is in fact now sufficiently clear and documented that it can be used as a reference point in various tasks, such as independent audits that green-light certain high-risk transactions. This reference point can also be used for a number of critical governmental actions, such as annually approving the actions taken by corporate senior management in response to a consent decree. Illustrating the contours of this new role, this article provides a brief overview of the minimum legal obligations of corporate directors and officers when it comes to information security and privacy.
Evaluation of Force Sensation Presentation by PWM Control of Vacuum Brakes

In recent years, with the development of Virtual Reality (VR) technology such as Head Mounted Display (HMD), the importance of technology to reproduce the sense of touch in VR space has increased, and various haptic devices have been proposed. On the other hand, there are some problems in presenting force sensation in VR space, such as the size of the device. We have proposed a method of presenting force sensation by using a device equipped with a vacuum brake on an omni-directional vehicle. In this paper, we report experimental results of the force sensation subjectively felt by the subject at different duty ratios when the solenoid valve is PWM controlled.
Limiting Choices with Toggles, Steppers, and Sliders

Ideally, you want to limit the user to select only valid options. That keeps the user from entering invalid data such as spelling out a number (such as thirty-seven) instead of typing out the number (37). Three additional ways to restrict the user into selecting only valid data are toggles, steppers, and sliders.
TĒCIYA TOṬAKKAPPAḶḶIKAḶIL TAMIḺAI IRAṆṬĀM MOḺIYĀKA KAṞKUM MĀṆAVARKAḶIṈ VĀCIPPU MAṞṞUM EḺUTTUT TIṞAṈ AṬAIVUNILAI [READING AND WRITING SKILLS PERFORMANCE LEVEL OF STUDENTS LEARNING TAMIL AS A SECOND LANGUAGE IN NATIONAL PRIMARY SCHOOL]

The objective of this study is to identify the Tamil reading and writing skills achievement of non- native students who learn Tamil as their second language in the first year of national primary schools. This is a qualitative research which used purposive sampling. The data for the study has been collected as statistics through the questionnaire and analyzed. The results show that the basic Tamil reading and writing skills are in satisfactory level while writing comprehension and reading comprehension skills are at a low level of achievement. The data obtained through this study will create awareness among teachers who teach Tamil as a second language regarding the Tamil reading and written skills achievement of their students and will encourage them to adopt suitable learning teaching approach for their students to achieve the best attainment in these skills.
Sinusoids and Fourier Series

A concise introduction to geophysical data processing - many of the techniques associated with the general field of time series analysis - for advanced students, researchers, and professionals. The textbook begins with calculus before transitioning to discrete time series via the sampling theorem, aliasing, use of complex sinusoids, development of the discrete Fourier transform from the Fourier series, and an overview of linear digital filter types and descriptions. Aimed at senior undergraduate and graduate students in geophysics, environmental science, and engineering with no previous background in linear algebra, probability, or statistics, this textbook draws scenarios and datasets from across the world of geophysics, and shows how data processing techniques can be applied to real-world problems using detailed examples, illustrations, and exercises (using MATLAB or similar computing environment). Online supplementary resources include datasets for students, and a solutions manual and all the figures from the book as PowerPoints for course instructors.
On the Development of an Empirical Model for Carcinomic Treatment using Chaotic Hyper-Heuristic Algorithm

A new dimension in the field of computational intelligence was introduced in the late nineties to comprehend a vivid combination of several multi-disciplinary areas. The coalescence biology along with data mining and statistical learning have given birth to Bioinformatics that provides various paradigms for studying the behaviour of unknown patterns at the micro level. In the present work, a recently developed human inspired optimization algorithm called search and rescue (SAR) optimization is employed with an improved version of parameters using Chaos theory. CSARO (Chaotic search and rescue optimization algorithm) unlike other existing algorithms has proven to be a better choice for optimising the gene selection mechanism as well as the control parameters of the learning model. This hyper heuristic algorithm obtained by the inclusion of chaos in SAR mainly aims at enhancement of its global search mobility and prevents from getting trapped in the local optimum. A comparative study with other existing techniques on seven benchmark datasets is performed. The performance of the algorithm is tested using evaluation metrics.
Least Squares and Correlation Filters

A concise introduction to geophysical data processing - many of the techniques associated with the general field of time series analysis - for advanced students, researchers, and professionals. The textbook begins with calculus before transitioning to discrete time series via the sampling theorem, aliasing, use of complex sinusoids, development of the discrete Fourier transform from the Fourier series, and an overview of linear digital filter types and descriptions. Aimed at senior undergraduate and graduate students in geophysics, environmental science, and engineering with no previous background in linear algebra, probability, or statistics, this textbook draws scenarios and datasets from across the world of geophysics, and shows how data processing techniques can be applied to real-world problems using detailed examples, illustrations, and exercises (using MATLAB or similar computing environment). Online supplementary resources include datasets for students, and a solutions manual and all the figures from the book as PowerPoints for course instructors.
EASYDAB (Earth System Data Branding): Enhancing the Findability and the Reuse of FAIR and Open Data

Even though in Earth System Sciences (ESS) the importance of good research data management has been widely discussed, the easy discoverability of quality-checked data has not yet been addressed in detail.This is the aim of the Earth System Data Branding (EASYDAB).EASYDAB is a branding to highlight FAIR and open data from Earth System Sciences that are published with DataCite DOIs.The EASYDAB guideline defines principles on how to achieve high metadata quality of ESS
Presenting the sensation of flying with flapping virtual wings independent of the limbs

Since ancient times, people have longed to fly in the sky. Actual flying involves risks and costs, but using a VR device makes it easy to experience flight. In this study, we propose a method of presenting the sensation of flying with flapping virtual wings independent of the limbs, such as the Draco．Unlike studies that presents the sensation of flapping wings by moving the arms, new applications that use the limbs during the flight experience can be expected by flying without moving the limbs. In this paper, we proposed a method of presenting the sensation of manipulating the wing without using the limbs and a method of transmitting the force acting on the wing to humans. We conducted experiments using these methods and obtained subjective evaluations.
Application of Fourier Methods and Discrete-Cosinus Transformation in the Process of Processing of TV Images

This article describes the Fourier and discrete-cosine transform methods in the processing of TV images. The methods used in the processing of color and TV images, based on different physical effects, information processing technologies and hardware. The images obtained using these methods will have their own specifics. This, in turn, causes a wide variety of approaches both to the assessment of the quality of TV images and to the processing of such images.
Reallocating resources for digitalisation in response to COVID-19: Health, education and Industry 4.0

The COVID-19 pandemic spurred rapid digitalisation worldwide, especially in the delivery of health and education services. This chapter explores the digitalisation of the health and education sectors in Emerging Asia. Country-level responses are examined, as are the challenges countries still face in this process, which will likely not be met for some time. Such challenges include poor infrastructure and affordability of access to digital services, which can exacerbate existing inequalities, or skill deficiencies in medical and educational staff that prevent the full potential of these technologies from being realised. The chapter explores possible solutions to these challenges, including the positive contribution of TVET to lifelong learning. The chapter also stresses the need for regional co-operation on cybersecurity and data privacy regulations to foster trust in digital systems. Finally, the chapter reviews each country’s state of play regarding Industry 4.0 and provides policy recommendations for completing the implementation process.
Blockchain Based Smart Auction Mechanism for Distributed Peer-to-Peer Energy Trading

Blockchain based framework provides data immutability in a distributed network.In this paper, we investigate the application of blockchain for peer-to-peer (P2P) energy trading.Traditional energy trading systems use simple passing mechanisms and basic pricing methods, thus adversely affect the efficiency and buyers' social welfare.We propose a blockchain based energy trading mechanism that uses smart passing of unspent auction reservations to (a) minimise the time taken to settle an auction (convergence time), (b) maximise the number of auction settlement; and (c) incorporate second-price auction pricing to maximise buyers' social welfare in a distributed double auction environment.The entire mechanism is implemented within Hyperledger Fabric, an open-source blockchain framework, to manage the data and provide smart contracts.Experiments show that our approach minimises the convergence time, maximises the number of auction settlement, and increases the social welfare of buyers compared to existing methods.
Glioblastoma Synthesis and Segmentation with 3D Multi-Modal MRI: A Study using Generative Adversarial Networks

The Grade IV cancer Glioblastoma is an extremely common and aggressive brain tumour. It is of significant consequence that histopathologic examinations should be able to identify and capture the tumour’s genetic variability for assistance in treatment. The use of Deep Learning - in particular CNNs and GANs - have become prominent in dealing with various image segmentation and detection tasks. The use of GANs have another importance - to expand the available training set by generating realistic pseudomedical images. Multi-modal MRIs, moreover, are also crucial as they lead to more successful performances. Nonetheless, accurate segmentation and realistic image synthesis remain challenging tasks. In this study, the history and various breakthroughs/challenges of utilising deep learning in glioblastoma detection is outlined and evaluated. To see networks in action, an adjusted and calibrated Vox2Vox network - a 3D implementation of the Pix2Pix translator - is trained on the biggest public brain tumour dataset BraTS 2020. The experimental results demonstrate the versatility and improvability of GAN networks in both fields of augmentation and segmentation. Overall, deep learning in medical imaging remains an extremely intoxicating field full of meticulous and innovative new studies.
The Impact of COVID 19 Pandemic on Service Quality Concerns and Expectations of Passengers towards Public transport Systems in Kerala

COVID 19 pandemic due to the coronavirus has caused a severe crisis situation all over the world to people especially passengers, who were highly dependent on public transportation facilities.This adverse condition at present had severely hit the smooth transportation modes of the entire state of Kerala.The current research paper focuses on framing the relationship between passenger's anxiety and worries and also their expectations towards the quality of services provided by the various modes of transportation in Kerala namely roadways, railways, airways and waterways during this pandemic condition.The scope of this study is limited to the passengers belonging to the three districts of Kerala each one from north (Kozhikode), central (Kottayam) and south (Thiruvananthapuram) zones and are using the busses, trains, metro, flights and boat services as the means of transport.The data have been collected through a structured Google form questionnaire from 100 frequent passengers of the three districts.The results of the study reveals that there is a high degree of positive correlation coefficient between the COVID 19 worries and anxieties towards the service quality concerns and expectations of passengers using public transportation systems.
Analysis of the Intention to Use of Virtual Reality-Based Nursing Education Program in Nursing Student Based on Extended Technology Acceptance Mode

The purpose of this study was to identify the intention to use of virtual reality-based education program for the nursing student on extended technology acceptance model. The data were collected 100 nursing students from January to February, 2021. According to the results, the mean perceived usefulness score was 3.92 points out of 5, perceived enjoyment was 3.81 points out of 5, and intention of use was 3.89 points out of 5. There was a positive relation among perceived usefulness, perceived ease of use, personal innovation, perceived enjoyment, and intention to use. The explaining 70.9% of the variance, and the influence the intent to use a virtual reality-based education program for the nursing student is perceived usefulness, and perceived enjoyment. Therefore, it is considered that technology development these factors will be necessary for nursing student to increase the intent to use of virtual reality-based nursing clinical education program. This study is meaningful in that it has identified the degree of intent to use and influencing factors of virtual reality devices for nursing student. This study could be used as basic data for the development of technologies for virtual reality-based nursing education program.