Reviewerly/exHarmony huggingface dataset:
Empirical Analysis of Feature Points Extraction Techniques for Space Applications

Recently, space research advancements have widened the scope of many vision-based techniques.Computer vision techniques with manifold objectives require that valuable features are extracted from input data.This paper attempts to analyze known feature extraction techniques empirically; Scale Invariant Feature Transform (SIFT), Speeded up robust features (SURF), Oriented fast and Rotated Brief (ORB), and Convolutional Neural Network (CNN).A methodology for autonomously extracting features using CNN is analyzed in more detail.The autonomous process demonstrates the use of convolutional neural networks for feature extraction.Those techniques are studied and evaluated empirically on lunar satellite images.For analysis, a dataset containing different affine transformations of a video frame is generated from a sample lunar descent video.The nearest neighbor algorithm is then applied for feature matching.For an unbiased evaluation, a similar process of feature matching is repeated for all the models.Well-known metrics like repeatability and matching scores are employed to validate the studied techniques.The results show that the CNN features showed much better computational efficiency and stable performance concerning matching accuracy for lunar images than other studied algorithms.
Survey on Data Security in Cloud Environment

Cloud provides high quality computing services, also it’s provided high performance services in a low cost makes it becomes a popular paradigm. The infrastructure of cloud was flexible, net centric approach, and easy to access. But its widespread usage is reduced due to its security issues. In cloud computing environment data will be stored in the servers which are situate at various locations can be accessible by illegal parties may leads to different security problems. Different methods have been developed to overcome the security issues in cloud environment such as signcryption, which is a valuable cryptography skill, which can afford concurrently both the roles of encryption following signature in a reason step. Likewise, different method methods have been planned to overcome the security issues in cloud environment. This survey details the threats and security anxieties in cloud computing along with the Classification of Security in cloud environment. Also, the review grants the current explanations obtainable in the works to counter the security issues. Likewise, the comparison table has been presented for those methods; result has been analyzed and finally ends up with the conclusion.
Five-year management plan for establishing and operating NVEWS—The National Volcano Early Warning System

First posted October 5, 2021 For additional information, contact: Volcano Hazards ProgramU.S. Geological Survey12201 Sunrise Valley DriveReston, VA 20192Contact Volcano Hazards Program On March 12, 2019, Congress passed the John D. Dingell, Jr., Conservation, Management, and Recreation Act (Public Law 116–9; 133 Stat. 580), in which Title V, §5001 (43 U.S.C. 31k) authorized the establishment of the National Volcano Early Warning and Monitoring System (NVEWS) within the U.S. Geological Survey (USGS). Conceived by the USGS Volcano Hazards Program in 2005, NVEWS is designed to be a proactive, fully integrated national-scale volcano monitoring system to ensure that the 161 potentially active volcanoes in the United States and its territories are monitored at levels commensurate with the threat they pose. The core of this report is the first USGS NVEWS five-year management plan, which was presented to Congress on March 12, 2020, and which details the principal elements of NVEWS that will be developed over the next five years, pending sufficient funding. These elements are improvements and enhancements to the monitoring network, a National Volcano Data Center, an external grants activity, an Advisory Committee, an Implementation Committee, and partnerships, with estimated cost projections and annual milestones.
Natural-Scientific Cases As A Tool For The Development Of Critical Thinking

Critical thinking is recognized as a key skill of the 21st century. The basis for the development of critical thinking can be integrated scientific disciplines and the associated scientific method. The learning model should be based on the essence of science as a process of discovering something new and teaching materials should become simulators of 'making discoveries' by recreating the situation of scientific search. The article describes a relatively new type of educational materials – natural-scientific cases (NSC). NSC is based on real-world problem situations, which are solved with the help of a chain of tasks that guides the student along the path of the scientific method. The formulations of the tasks are aimed at the development and diagnosis of critical thinking. An experiment on the introduction of cases into the educational process of two Moscow universities is described in the article. The results obtained indicate that the use of a set of NSC has a double positive effect: the natural science complex serves as an excellent basis for the development of critical thinking, and an increase in the level of thinking contributes to a more productive assimilation of natural science material.
Artificial Neural Network Architecture and Orthogonal Arrays in Estimation of Software Projects Efforts

Accurate assessment of software project development using the proper artificial intelligence tools can be a significant challenge for success in the software industry. This paper aims to minimize the relative error in software estimation using the proposed model of an artificial neural network (ANN) based on Taguchi's orthogonal vector plan. By selecting methods of clustering and fuzzification of different project values within several used datasets such as COCOMO2000, NASA60, and Kemerer15, reducing the number and time of iterations minimizes Mean Magnitude Relative Error (MMRE) and include a wide range of observed data. Additional criteria, such as monitoring prediction, correlation, and comparison with RBF (Radial Basis Function) relative error, were used to confirm that the proposed model gives two to three times better results depending on the observed cluster. Based on the obtained results, the accuracy and reliability of the proposed model for estimating software projects were determined.
Characteristics of agricultural entrepreneurs and their agribusinesses in sub-Saharan Africa: Evidence from Benin.

Entrepreneurship in the sub-Saharan African agricultural sector has been growing in recent years because of increasing unemployment and underemployment. In Benin, policies and programs are encouraging individuals to start their own agribusinesses. To further sharpen these policies and programs to improve agricultural entrepreneurship's contribution to the economy, it is essential to avail information on the entrepreneurs, their businesses, and the typologies of agribusinesses. Such information is limited, which reduces the ability to develop evidence-informed policies and programs. This research aims to fill the gaps by describing the features of agricultural entrepreneurs in Benin. A random sample of 819 agricultural entrepreneurs was used, and data were collected on entrepreneurs and their businesses. Descriptive analysis and hierarchical clustering of principal components were performed. The study found that women’s participation in agricultural entrepreneurship in terms of new business formation is still low. Also, the agricultural entrepreneurs are more driven by necessity than opportunity, although they have a highly positive personality, mainly in terms of optimism and risk. At the enterprise level, most agribusinesses have been in operation for more than three years, but only one out of ten entrepreneurs felt that their business was at a mature phase. The research also evidenced that informality in the agribusiness sector is high because almost half of the agribusinesses were not registered with any formal governmental entity, and only three out of ten complied with tax regulations. Agricultural entrepreneurs were active in knowledge networks to expand their activities and improve their performance. Three categories of agribusiness were defined with the cluster analysis: ‘informal agribusinesses’ essentially built for profit, not registered, and owned by not highly educated adult entrepreneurs; ‘professional new agribusinesses’ were mainly operated by young entrepreneurs with a university education and agricultural professional training; and ‘mature agribusinesses’ were mostly formally registered and owned by highly educated entrepreneurs. This research will be instrumental for policymakers and practitioners to better understand agricultural entrepreneurship and improve its economic outcomes. It provides a strong evidence base to support the ongoing motivation of policymakers to provide solutions to unemployment and underemployment through agricultural entrepreneurship.
Bin Code: Encoding and Decoding of Picture Embedded Barcodes by Novel Intensity Bin

Objectives: To introduce a new algorithm for embedding pictures into barcodes, thereby facilitating the barcodes to hold the picture about its carrying information.This facilitates easier storage and faster retrieval, thereby avoiding manual errors and time consumption.Methods: The message to be embedded is encoded using Reed Solomon code and then embedded into the image by the proposed modulation method, finally generating a picture embedded barcode.Findings: The image quality and the information embedding capacity achieved by this method are proved to be higher than the previous works.Novelty: This study proposed an encoding/ decoding method for barcodes with pictures with the novel Intensity bins to generate a barcode with maximum visual quality.
USE OF CLOUD-BASED MULTIMEDIA EDUCATIONAL RESOURCES IN THE PREPARATION OF FUTURE PRIMARY SCHOOL TEACHERS

Most educational support materials include graphics, animation, audio and video snippets, infographics, and text that can be accessed through the Internet. In recent years attention paid to the pedagogical design of teaching and learning tools using cloud-based technologies (CBT) has been increasing in the world. Such facilitates as the friendly interface of computer-based and web-based applications, the speed, availability and security of CBT provoke higher interest among educators to the constant use of products offered by these technologies. The above-mentioned points to the problem of designing a quality cloud-based multimedia educational resource (CBMER), as well as the need to determine the effectiveness of the use of projected CBMER in the educational process. Based on the analysis of scientific articles and research by specialists in the educational sphere the stages of designing were distinguished, the basic principles (didactic, qualitative and technical) which should be observed during introduction in the educational process were described; the functions that perform CBMER and the operating modes were specified. For the use of the author's CBMER in the educational activities of teachers of higher education institutions, a number of recommendations have been put forward and the author's system of evaluation of the quality of the multimedia educational resource has been proposed. The peculiarities of teaching with the use of CBMER are described in detail based on the case of the discipline «Special Workshop on Informatics» for students of specialty «013. Primary education» of Borys Grinchenko Kyiv University. It is statistically justified that the author's CBMER containing interactive tasks, dynamic elements, audio and video elements contribute to the formation of professional competences.
Teaching English Strategies During Covid-19 Pandemic at SMKN 1 Lembah Melintang

pandemic that was claimed from Wuhan, China at the conclusion of 2019 has exchanged to nations over the world at the starting of 2020.This widespread has proposed new era in each perspective of human life, economy or commerce, social, wellbeing, and instruction as well.In instruction segment, Indonesian Instruction and Culture Serve, Mr. Nadiem Anwar Makarim requested all students counting college student to think about from domestic.Descriptive research is used to conduct this research.The aims of this research is to find out the English strategies that used by the teacher during pandemic.The result of the research found that (1) The teachers utilize diverse methodologies since the anticipated ability yield are distinctive, for composing abilities the teacher employments 3 methodologies to be specific arranging, drafting, and altering.As for tuning in aptitudes, the teacher applies a few strategies such as tuning in to melodies, composing melody verses, coordinating verses, and at last singing test.Both of them utilized the video-based learning show up moreover virtual instruction through WhatsApp.(2) Methodologies in direction through e-learning classes within the middle of the COVID-19 wide essentially made a difference instructors inside the teaching and learning arrange to realize learning goals.
Data Mining for Determining The Best Cluster Of Student Instagram Account As New Student Admission Influencer

Purpose: This study aims to apply the web data extraction method to extract student Instagram account data and the K-Means data mining method to perform clustering automatically to determine the best cluster of students' Instagram accounts as influencers for new student admissions.Design/methodology/approach: This study implemented the web data extraction method to extract student Instagram account data. This study also implemented a data mining method called K-Means to cluster data and the Silhouette Coefficient method to determine the best number of clusters.Findings/result: This study has succeeded in determining the seven best student accounts from 100 accounts that can be used as influencers for new student admissions with the highest Silhouette Score for the number of influencers selected between 5-10, which is 0.608 of the 22 clusters.Originality/value/state of the art: Research related to the determination of the best cluster of students' Instagram accounts as new student admissions influencers using web data extraction and K-Means has never been done in previous studies.
PENGEMBANGAN MEDIA AUDIO VISUAL BERBASIS APLIKASI CANVA MATERI BANGUN RUANG LIMAS

The purpose of this study is to determine the validity, practicality, and effectiveness of audio-visual media based on the canva application for pyramids in VIII grade SMP Islam Al Azhaar Tulungagung with 27 students. The approach used in this study is R&amp;D with ADDIE steps; Analysis, Design, Development, Implementation, and Evaluation. The data collection method used is a questionnaire and test. The results of the material expert validation were 3.40 (good criteria) and the media expert validation 3.50 (very good criteria). So that it can be categorized as a criteria. The practicality test of students with an average of 89.25 of the criteria is very practical. Based on the percentage of students’ effectiveness of 92.59% the criteria is very good. Based on the validation process, practicality, and effectiveness test of audio-visual media based on the canva application the pyramid material is valid, practical, and effective. The developed media can increase students’ learning motivation. So it can be used to support the implementation of direct or online learning for VIII grade Junior High School.
Mapping Solar Pond by GIS and Analytic Hierarchy Process

In terms of the importance of solar radiation sustainability in Egypt, this research was initiated with the objective of mapping solar ponds to provide solar energy by Geographic Information Systems (GIS) and multi-criteria decision-making method to ensure their efficiency, in terms of cost. Primarily, literature in the field of solar ponds and clean energy was assembled, reviewed, analyzed and categorized to deduce data about solar pond locations and analyze such data. Accordingly, different variables were considered such as power line stations, road networks and cities). In addition, land cover as environmental parameter was considered. Furthermore, technical variables like direct normal radiation, temperature, wind and relative humidity were taken into account. ArcGIS process was applied and solar pond technique locations were selected. The deduced data were comprehended, analyzed, and presented to perceive a complete data picture about Egypt, from which it was apparent that different zones have different characteristics, in terms of the capability of encompassing solar ponds. Based on the investigation results, it was concluded that Al Wadi Al Jadid Governorate and some spatial areas show in mapping satisfies the renewable energy potential. In addition, it was recommended to implement solar ponds in their vicinity, as they satisfy the solar pond requirements, in terms of efficiency and cost.
Study on the Clinical Characteristics and Treatment of Obstetric Hypertension with Sequence Pattern Mining Algorithm

Aiming at the difficulty in setting the support threshold for sequential pattern mining algorithms and improving the effectiveness of the support threshold setting without the guidance of domain experts' experience, an improved SPADE (sequential pattern discovery using equivalence classes) algorithm is proposed. By analyzing the relationship between the number of frequent sequences and the support threshold, the support threshold is dynamically selected. Using the electronic medical record data from a medical centre, the time-series relationship of the drugs taken by hypertension patients was extracted as the drug sequence dataset. By determining the optimal support threshold of the dataset, the frequent sequence set is mined, and the sequence rules are generated from the obtained regular sequences to visualize the sequence rules. The sequence rules of medication for hypertensive patients were combined with the patients' physical indicators for the recommendation. For patients with obstetric hypertension, a combination of nifedipine and captopril is recommended. Through the comparison of the observation group and control group, we study the curative effect of various drugs. The results showed that the total effective rate of the observation group was about 96.6%; compared with the control group, the result indicated that the difference was significant (P < 0.05). The comparison of blood pressure levels between the two groups after treatment also showed that the results of the observation group were ideal (P < 0.05). In addition, the incidence of postpartum haemorrhage and perinatal complications in the observation group was also significantly reduced (P < 0.05). Therefore, the combination of medication for pregnancy hypertension syndrome can effectively improve the treatment effect of the disease and reduce the rate of postpartum haemorrhage and the incidence of perinatal complications.
Pengaruh Biaya Produksi Dan Biaya Operasional Terhadap Laba Bersih

The purpose of this study is to determine the effect of production costs and operating costs on net income in the consumer goods industry sector for the 2015-2019 period. The sample selection uses a sampling technique. In order to obtain a sample of 15 companies and a total of 75 data. The regression analysis analysis method used is multiple linear regression analysis through classical assumption tests and hypothesis testing. Based on the results of this study indicate that partially production costs have an effect on net income and other research results partially operational costs have a significant effect on net income. Simultaneously, production costs and operating costs have a significant influence on net income&#x0D; Keywords: Production Costs, Operational Costs, and Net Profits
A super-grayscale and real-time computer-generated Moiré profilometry using video grating projection

Abstract By using the time-division multiplexing characteristics of the projector and the integral exposure characteristics of the charge coupled device (CCD) camera, a super-grayscale and real-time computer-generated Moiré profilometry based on video grating projection is proposed. The traditional digital static grating is of 256-grayscale at most. If an expected super-grayscale grating with a maximum grayscale of 766 is designed and divided into three 256-grayscale fringe patterns with balanced grayscale as far as possible, they can be synthesized into a repeated playing video grating instead of the traditional static grating. When the video grating is projected onto the measured object, as long as the exposure time is set to three times the refresh cycle of the video grating, the super-grayscale deformed patterns in the 766-grayscale can be captured with a 10-bit CCD camera, so that the deformed patterns are realistic. The digital error in computer-generated Moiré profilometry is effectively reduced. In addition, this method can expand the linear range of the deformed pattern by 20% in computer Moiré profilometry. Therefore, the proposed method has the perspectives of high accuracy and real-time measurement. Theoretical analysis and experimental results demonstrate the validity and capability of the proposed method.
The method of student's query analysis while intelligent computer tutoring in SQL

Recently, IT specialties have become one of the most demanded specialties in the world labor market. Simultaneously the traditional teaching in conditions of mass production, even with a professional teacher, has a significant drawback – the fundamental impossibility of adapting to each student. Since the 60s of the twentieth century, researchers worldwide have been developing various computer-tutoring tools that have, less or more, adaptive functions. Nevertheless, the task of the perfect computer tutor development is still far from being solved. The article's research subject is the process of student requests analyzing during intelligent computer tutoring in SQL. The main goal is to develop a method for analyzing the student's SQL queries. The purposes: to form a general scheme and features of the method for analyzing student’s SQL queries based on the principles of technical diagnostics and methods of lexical, syntactic analysis of computer programs; to develop methods for parse tree construction; to create methods for comparing reference and real SQL queries according to their similarity rate; to demonstrate the function ability of the developed methods on specific examples. The methods used computer programs the automatic testing method, the computer programs lexical and syntactic analysis methods, the computer programs parsing trees construction methods, the objects diagnosing method based on comparison with a reference, the strings analysis methods, the method of q-grams. The following results were obtained: the student’s SQL queries analysis method was formed based on a system approach including automatic testing on real data, building query-parsing trees, comparison with a reference, and comprehensive determination of the queries similarity rate. The scientific novelty is the improvement of the method for the student's SQL query analysis during intelligent computer training in SQL query composition.
Real vs Simulated Foveated Rendering to Reduce Visual Discomfort in Virtual Reality

In this paper, a study aimed at investigating the effects of real (using eye tracking to determine the fixation) and simulated foveated blurring in immersive Virtual Reality is presented. Techniques to reduce the optical flow perceived at the visual field margins are often employed in immersive Virtual Reality environments to alleviate discomfort experienced when the visual motion perception does not correspond to the body's acceleration. Although still preliminary, our results suggest that for participants with higher self-declared sensitivity to sickness, there might be an improvement for nausea when using blurring. The (perceived) difficulty of the task seems to improve when the real foveated method is used.