Reviewerly/exHarmony huggingface dataset:
DEVELOPMENT TECHNOLOGY OF SOCIAL SKILLS OF STUDENTS’ CRITICAL THINKING

At the beginning of the 20th century, the writer, founder of the drama and novel in the Kazakh language, scientist, enlightener, teacher, and psychologist Zh. Aymauytov said that, "Teaching is not just ordinary skill, it is the art of finding new from new." Modern society needs a free, creative personality with certain qualities of thinking that meets the needs of the times. Therefore, the main task of the university is to reveal the abilities of students, to develop their social skills of critically thinking and learn independently, ready for a competitive world.
Large Majorities Favor Congressional Proposals Limiting Negative Consequences of Criminal Records

In the innovative survey by the Program for Public Consultation (PPC) at the University of Maryland, respondents were given relevant background information for each proposal. They then evaluated a series of strongly stated arguments for and against each proposal before making their final recommendation. The briefing material and arguments were reviewed by experts representing the range of opinions on the issue to assure that the briefings were accurate and balanced and that the arguments were the strongest ones being made.
Use Case Building from Gathered Requirements based on Story Telling Techniques for Design Development

During software planning, the duration of time and budget for development are the important factors estimated. When they are not estimated correctly for the software projects, there is a fall in software projects development due to unrealistic estimates. The core reason for fluctuation in the estimation is, thelack of understanding of the requirements properly. These problems have to be assessed at the time of requirements analysis in the requirement engineering phase so that the deflection is not high. Hence the requirement level computing, is often is weighted of a high score. To evaluate each criteria the story telling concept can be used for reducing the deflection of the estimation. In this method, we can understand the stakeholders’ role the requirements which are the base and the business value of each requirement. Hence the analyzing of requirements in view of the stakeholders with regards to the various implementation ways is easier to estimate its need. This research aims to develop a support tool for stakeholders and the requirements engineers to useit in thegathering and analysis of requirements. Implementing the story concept is estimated to reduce the deviations of time and budget plan to near accuracy. The result shows a 75 percentreduction of deviation by using the prediction methods. The prediction method involves Taylors series and exponential methods for evaluation of the requirements to extract the information from the contexts. This method has high accuracy with only about 0.5 percent deviation.
Improve Creativity in Future-Oriented Design with the Prospective Persona

As ergonomics is confronted with future-oriented design projects, ergonomists must investigate how design could create novel and adapted ideas. In often ill-defined contexts, prospective ergonomics proposes to rely on methods and knowledge related to creativity, to foster the design process. In this paper, we introduce the prospective persona method, which is the implementation of the persona method applied to individuals who experience uses or artefacts that are identified as being precursory. The objective of this persona is to improve constraints management by adding the description of needs little known to designers. The study presented in this paper aims to compare the quality of ideation during a creativity task using ordinary persona, prospective persona or no persona. Our results show an effect of prospective persona on creativity. Prospective persona allows for a higher number of new ideas than ordinary persona and is the source of more feasible ideas the non-use of persona. We therefore recommend the use of prospective persona in future-oriented creativity design phase.
Google Colaboratory for HDF-EOS

Google provides a free Jupyter notebook environment called Colaboratory (also known as Colab). It is simple, easy, and awesome Python environment for data scientists. We present how NASA Earthdata in HDF can be used with Google Colab using the existing comprehensive example on HDF-EOS Tools and Information Center website (http://hdfeos.org/zoo). We also present how OPeNDAP can be used with Colab to achieve 100%-cloud data analysis.This presentation was given in July 2019 at the Earth Science Information Partners (ESIP) Summer Meeting held in Tacoma, Washington.
Improving students' vocabulary mastery by using role play atSMP Muhammadiyah 12 Binjai The Academic year 2019/2020

This research was aimed to find out the improving students‟ vocabulary mastery by using Role Play. The subject of this research was seventh grade of SMP 12 MUHAMMDIYAH BINJAI 2019-2020Academic Year. It was nconsisted of one class and 21 students as respondents. The object of this research was to improve students‟ vocabulary mastery by using role play.The research of this study was conducted by using calssroom action research. The technique of analyzing the data of this research was applied by qualitative and quantitative data. The qualitative data were taken from observation sheet, interview, and documentation. The quantitative data were taken from the test. Data was taken from test result which was carried out in two cycles. And two cycles conducted in four meetings. The test was given to the students in form ofpre-test, post test in the first cycle, and the post-test in the second cycle.The result of the analyzing the data showed that there was an improving on the students‟ vocabulary mastery from each cycles. It was showed from the meann of pre-test was 63.95. Where, there were 6 students got successfull score criteriaor it was only 29 % and 15 students‟ got unsuccessful or it was 71%. After doing cycle I by using role play, there was an improving of the result of the students‟ mean was 72.23. Where, 8 students got successful criteria score or it was only 38% and 13 students‟ got unseccessful criteria score or it was 62%. Then doing repairing for second cycle after reflection on the first cycle, there was improving of students‟ mean was 83.19. Where, 18 students‟ got successfulcriteria score or it was 86% and 3 students‟ got unsuccessful criteria score or it was 14%. In other words, the students‟ vocabulary mastery was improved. And based on interviewed, observation sheet, and photographs, it showed that theexpression and excitement of the students were also improve
INDONESIAN HUMAN CHARACTER AND DIGITAL LITERATION

The presence of digital technology is a necessary reality. But inevitability is not matched by the ability of most humans to use it productively. As a tool, digital technology is able to make human life good or bad, individually and socially. At the national level, the impact is also on a national scale, where Indonesian people represent the character of a nation.With that digital literacy needs to be strengthened to build the character of the nation. Theoretically, the digital literacy perspective includes tools and systems, information and data, sharing and creation, historical and cultural contexts. From that perspective, technically speaking, digital literacy learning materials and methods can be developed formally and informally.
Serum-based assay for adnexal mass risk of ovarian malignancy.

5551 Background: A Deep learning neural network was developed to assess ovarian cancer risk in women presenting with adnexal mass into risk categories. The algorithm shows potential to improve on the performance of CA-125 as the standard biomarker to monitor women as a clinical management metric to trace increased risk of malignancy. Methods: Serum specimens from an enriched biobank (N = 2688) were collected during previous clinical studies from women presenting with an adnexal mass at risk of ovarian cancer. Protein biomarker data from these specimens were used to develop a novel neural network for binary stratification of ovarian cancer risk assessment. These specimens were divided between training and testing data sets using 5-fold cross validation during training. A randomized, separate sample set was withheld from use in training and testing the algorithm for independent validation purposes. As algorithm inputs seven biomarkers are used in the network: cancer antigen 125, human epididymis protein, beta-2 microglobulin, apolipoprotein A-1, transferrin, transthyretin, and follicle stimulating hormone. In addition to these biomarkers, the patient’s age and menopausal status are used. Menopause was defined as the absence of menses for ≥12 months. The algorithm uses supervised learning with known histopathology diagnoses as the labels for training. The algorithm is a classification deep feedforward neural network. The neural network is regularized using node dropout to reduce overfitting. The final layer of the neural network has two nodes and uses the softmax function to assign a binary classification of low or high-risk of malignancy. Results: Algorithm performance metrics are also shown comparing predicted results from the algorithm to the known malignancy diagnoses. The performance metrics are also compared below to the standard of care biomarker test, cancer antigen 125 (CA125), reporting increased sensitivity by 26.1%, and failure to reject the null hypothesis of equivalent specificity. Conclusions: The algorithm detected 91% of malignancies in the independent validation data. This high sensitivity in malignancy detection paired with the failure to reject the null hypothesis of equivalent specificity (Pearson’s chi-squared test p-value of 0.281) and negative predictive value (NPV) suggest the algorithm could be used two-fold. First, surgical referral to gynecological oncologists for women classified in the high-risk cohort. The second as a goal with future clinical validation, is that women with a low risk of malignancy might be able to delay surgery and enter into a serial monitoring clinical management care pathway.[Table: see text]
VALIDITY OF THE DIGITAL BOOK FORMED ELECTRONIC PUBLISHER THEMED CLIMATE CHANGING TO TRAIN DIGITAL LITERATION OF VII JUNIOR HIGH SCHOOL

This experiment is purposed to produce digital book eligibility by reviewing the validity to train 7th grade student’s digital literation at Junior High School. Method used for developing this digital book is Research and Development (RnD). The instruments used in the study were the digital book review sheet and validation sheet. Methods of data collection were validation. The data analysis technique used the Likert scale. Eligibility of validity is consists of content aspect, presentation, literature, and the dimension of digital literation. The digital book validity is reviewed by two lecturers and one science teacher. Eligibility of content aspect is 3.82, eligibility of presentation is 3.70, egibility of literature is 4.00, eligibility of dimension of digital literation is 3.70. Based on the result, digital book is eligible in term of validity. Key word: Digital book, digital literature
Cloud Security Challenges Amidst the Implementation of Learning Management System in the New Normal

The upcoming opening of the school year is fast approaching there are several questions on how to deal with the implementation of the learning management system in both primary, secondary, tertiary, and the graduate school program in the new normal. How secured the learning management systems to be implemented in terms of cloud security and vulnerable there learning management systems in other schools and universities this coming new normal. The researcher will be conducting a thorough study on how to select and implement secured learning management systems in terms of cloud security. Learning management system has become one of the most influencing educational paradigms devoted to improving teaching and learning through the use of modern technology.
READING LITERACIES THROUGH EVIETA-BASED LEARNING MATERIAL: STUDENTS’ PERCEPTIONS (Study Case Taken from Vocational School – IPB University)

Communities with high literacy rates usually have low crime rates and high intelligence. This is precisely the responsibility of universities and schools in increasing reading interest and literacy skills in a country. From this context, it is hoped that the educational community will really apply it, especially in juxtaposing it with online learning and several applications. The purpose of this study was to collect information about the preferences of critical vocational students in their reading interests and reading skills. It is very useful to foster interest in reading and online learning to increase cultural values ​​and social literacy. The reading literacy development model used is the Plomp model: preliminary research, prototyping, and evaluation. The Evieta application, which is online learning belonging to the Vocational School of IPB University, is expected to fulfill these goals. Educators are expected to use related applications in their learning and lead reading and writing movements in schools. The results of the validation of teaching materials show that the Evieta IPB application is important and can be tested.
Design and Implementation of Self-Driving Vending Robot

This paper proposes a novel design of a self-driving vending-robot and describes the prototype implementation results. The proposed robot generates the global rotational path from the waypoints selected by the human operator. Subsequently, the robot repeatedly drives itself along the global path. In the autonomous driving process, when the robot recognizes a person with a target gesture (i.e., purchaser), it approaches the purchaser and sells the products. Once the selling process has been completed, the robot returns to the global path and resumes driving on the path. To generate the global path and ensure that the robot can move along the path, we introduce a waypoint-based path generation and navigation algorithm. Furthermore, we develop a deep-learning-based purchaser recognition algorithm. To validate the proposed self-driving vending robot design, we implement the prototype on the ROS framework. The prototype robot can successfully operate under four scenarios, and the findings validate the proposed design for a self-driving vending robot.
Deep ordinance location and mapping case study

PreviousNext You have accessSymposium on the Application of Geophysics to Engineering and Environmental Problems 2021Deep ordinance location and mapping case studyAuthors: Mario Di BelloFabian StickelMario Di BelloFoerster InstrumentsSearch for more papers by this author and Fabian StickelFoerster InstrumentsSearch for more papers by this authorhttps://doi.org/10.4133/sageep.33-106 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Proposed discussion of GPS Georeferenced mapping project for international work detailing UXO location and mapping for remediation. Hand-held, mobile cart, and towed fluxgate magnetometer arrays were used to build a magnetic map of an area encompassing several square kilometers. The magnetic data was processed and analyzed using proprietary software to locate and identify UXO targets. Location, depth, and orientation were noted and provided to remediation contractors for removal and disposal of ordinance. Methods of detection, review of magnetic map, and review of target list will be discussed, as well as general method of target identification algorithm. Certain details of project may be limited due to the proprietary nature of the work and the location of the project. All non-proprietary aspects of the project may be discussed. Keywords: algorithm, GPS, magnetometer, arrays, mappingPermalink: https://doi.org/10.4133/sageep.33-106FiguresReferencesRelatedDetails Symposium on the Application of Geophysics to Engineering and Environmental Problems 2021ISSN (online):1554-8015Copyright: 2021 Pages: 349 publication data© 2021 Published in electronic format with permission by the Society of Exploration Geophysicists and Environment and Engineering Geophysical SocietyPublisher:Environmental & Engineering Geophysical Society HistoryPublished: 11 Jun 2021 CITATION INFORMATION Mario Di Bello and Fabian Stickel, (2021), "Deep ordinance location and mapping case study," Symposium on the Application of Geophysics to Engineering and Environmental Problems Proceedings : 199-199. https://doi.org/10.4133/sageep.33-106 Plain-Language Summary KeywordsalgorithmGPSmagnetometerarraysmappingPDF DownloadLoading ...
The Effects Of Sleep Deprivation Towards The Academic Performance Of Ustp-Oroquieta Students

This study determined the effects of sleep deprivation on the academic performance of 2nd-year education students of the University of Science and Technology of Southern Philippines. Specifically, it sought to answer the following: (1) correlation and comparison of difference between number of hours sleep and academic performances in Eng111 and Educ90; (2) difference on students’ flexibility towards sleep deprivation and demographic profile; and (3) correlation between the number of hours sleep and academic performances in terms of Cognitive, Psychomotor/Physical, and Environmental Factors Correlational-descriptive research design was used in the study. A census was used in the collection of data in which 122 respondents participated. A researcher-made questionnaire was utilized. The analytical design used consisted of statistical procedures such as hypothesis testing, correlation, averages, standard deviations, and T-test.The results showed that as the number of hours of sleep increased, students’ academic performance in Eng111 and Educ 90 get better. Furthermore, a significant difference in both subjects and grades was found. With all the variables taken in this study, it can be inferred that without proper sleep, the brain's function such as the ability to concentrate, store data, and other cognitive activities will be hampered and/or paralyzed..
Study on prediction errors caused by image zooming in execution phase of remote operation and possibility of compensation

In this study, how to improve usability and quality of the remote participation experience using remote-controlled robots to support the active social participation of people who have mobility issues were investigated. Specifically, to reduce the prediction error caused when using remote-controlled robots revealed in the previous study and thus the burden of the remote operation, a series of experimental results was discussed. In these experiments, the error between the stop position of the robot that cannot be directly seen on the robotic perspective image and the target position was measured. The results show that (1) the zooming image from the robotic perspective during the execution phase induces a negative prediction error. The error might be caused when the information of the current position of the robot is inconsistent with that of the stop position. This result is an extension of our previous study. (2) The above situation needs to be considered because it is assumed in the application of remote operations using robots, such as the need to observe the target information in detail like face-to-face communication. (3) Depth cognition is important for remote control using images from the robotic perspective, and it was found that the information of the optic flow, which was thought to affect the depth motion perception involuntarily, significantly affected the size cue regarding the target position.
A Study on Deep Learning-Based Super-Resolution Network Architecture for Military SAR Image

The Republic of Korea military is using SAR(Synthetic Aperture Radar) geographic intelligence to deal with security threats. However, human experts have difficulty on analyzing acquired SAR images and identifying military targets due to low resolution. In this paper, we study the deep learning-based network architecture fit for the super-resolution of military SAR images. Previous military SAR image super-resolution studies mainly conducted on improving the results of super-resolution, but it was difficult to find studies on network architecture. The proposed neural network is a deep learning-based super-resolution networks. And it consists of input, learning, upsampling, and output layers with real military SAR images. We show and experiment with networks for super-resolution of military SAR images, while focusing on the input and upsampling layers. Experiment results show that we able to find a suitable architecture of input and upsampling layers is discussed.
THE EFFECT OF ROLE PLAY TECHNIQUE ON STUDENTS’ SPEAKING ACHIEVEMENT

This research deals with finding students’ achievement in using Role-Play technique. The objective of the study is to prove whether Role-play technique there is an effector not on students’ speaking achievement. The research was conducted in SMA Imelda Medan of XI grade students of 2018/2019 Academic year, which consists of 48 students. The data were collected by applying several techniques including pre-test and post-test. To break down the quantitative information, the specialist applied an expressive measurement, including the most elevated and least scores and means. The different score of pre-test and post-test are respectively 72.5 and 84.3 in experimental class. From the calculations, it is obtained that t obs is higher than t table namely 6 > 1.717. It means that the alternative hypothesis (H a ) is accepted. The research findings shows that Role-play technique can increase students’ speaking achievement 11.8% while the conventional just 5.2%. There were 45.8% of the students are excellent enough, 12.5% are very good, 33.3% are satisfactory, and 8.2 % are very good. So, that teaching speaking using Role-play technique really gives a high contribution on students’ speaking achievement.
Introduction to Data Science and Machine Learning Algorithms

Data science has gained importance since available data and hardware facilities have been ubiquitous. Algorithms to process a huge amount of data and extract information were developed decades ago. However, due to the lack of high-capacity computers, it was not possible to use them on real-life data and problems. Today, from finance to medicine data science plays an important role to solve problems. Suffice it to say, machine learning algorithms are the core of this new phenomenon besides data itself. Artificial neural networks, deep learning, Support Vector Machines, Decision Tree Learning Models, and related algorithms have been used successfully and yielded very important results recently. On the other hand, text data have also gained importance being the fuel of machine learning in data science. Especially the emergence of social media and communication technology contributed to the popularity of texts in data science. In this chapter, concise introductions have been given about the most popular and also successful machine learning algorithms. This chapter will be helpful for those readers who do not have enough information about machine learning and its algorithms.
Mechanisms and Models of Risk Management Process of Educational Activity of Higher Education Institutions

An approach to the risk management process based on the traditional principles of risk management is used in this article as the basis for constructing a risk management model for the educational activities of higher education institutions.The mechanisms that ensure the effective functioning of the system that ensures the reduction or compensation of the risks of educational activities proposed in this material can be adapted and used to create an integrated risk management system for any educational institution.The approach to the system of risks of the educational activity has a number of features and nuances, some of which this article tries to cover. The key principles proposed in it are of practical application and tested in the course of the experiment.