Reviewerly/exHarmony huggingface dataset:
Development of a local impact-based Landslide Early Warning System using physically-based multi-hazards modelling and machine learning in Java, Indonesia.

&amp;lt;p&amp;gt;Early Warning Systems are one of the most effective tools for reducing disaster risk, however the development of Landslide Early Warning Systems (LEWS) is complicated due to the random nature of landslide occurrence and the uncertainty in mapping the parameters that cause them. Local LEWS have been effective for known landslides, but regional scale LEWS based on rainfall thresholds have not been very effective up to now. In recent years physically-based multi-hazard models have been developed which allow to predict mass movement hazards at a local scale. However, it is still difficult to apply these in LEWS in a local scale due to the coarse resolution of rainfall estimates and the high computational modelling requirements for running such models real-time. On the other hand, machine learning approaches have been used to assess the relationship between the distribution of the landslide hazard and the catchment morphometric features.&amp;lt;br&amp;gt;&amp;lt;br&amp;gt;This research applies a physically-based multi-hazard model combined with machine learning to forecast the mass movement impact, based on rainfall predictions in an area in Java, Indonesia. The landslide inventory was developed using a combination of local reporting data and machine learning techniques. The integrated physically-based multi hazard model OpenLISEM is used to create a database of hazard intensity maps under various rainfall scenarios. The resulting hazard intensity maps are subsequently used to subdivide the area in homogeneous zones for which warning levels are given. Machine learning is used to query the database and extract the most likely hazard intensity map based on the rainfall prediction. The intensity is then combined with exposure information of people, buildings, transportation infrastructure and agriculture to provide impact forecasts. The output of combining physically-based models with machine learning approaches has the potential to improve the prediction of landslide impact. The method also allows to make more specific local decisions related to the actions for various levels of warning (e.g. increased vigilance, removal of resources, evacuation of people). The method is currently under development as part of an Indonesian-Netherlands collaboration project to develop a blueprint to use tailored rainfall data, in combination with empirical and physically-based hydrological and landslide models, and historical landslide data for the development of thresholds for landslides and debris flows, as the basis for early warning at settlement level, applied to several test sites in Java.&amp;lt;/p&amp;gt;
Geothermal Surface Manifestation Identification Using Airborne Hyperspectral Imagery Case Study: Davis-Schrimpf Geothermal Field, Salton Sea, California

DOI:10.17014/ijog.9.1.119-130 Research on surface geothermal evidence has been done extensively using remote sensing techniques. For detailed remote sensing exploration on geothermal areas, UAV and airborne based were preferred over the satellite-based sensor. In this research, anomalies in surface temperature, mineral occurrence, and ammonia emission were studied on a set of airborne hyperspectral imagery from NASA, the Hyperspectral Thermal Emission Spectrometer (HyTES). High-resolution surface temperature and mineral maps were able to identify and describe the mineralogy of the mud pots and gryphons at the Davis-Schrimpf Geothermal Field, Salton Sea, California. From the surface temperature map, the surface temperature of the geothermal features was measured at approximately 314°K (40 o C) and higher. The purest pixels from MNF transformation of the first four cleanest bands of emissivity map produce endmembers that include the geothermal indicator minerals (barite, anhydrite, quartz, gypsum). Based on the mineralogy deposits, these manifestations are classified as potassic alteration types from a porphyry system that could be an indication of an active geothermal system. This also explains that the surface features are part of the upper reservoir of the Salton Sea Geothermal Field . On the other hand, ammonia detection that was performed in this research failed to get any clear recognition from the simple image processing. It is concluded that the airborne hyperspectral imagery could be a reliable option for remote sensing geothermal exploration, as it was able to characterize the surface geothermal manifestation with quite good detail using this imagery from a wide area of survey.
Digital competence with respect to ESD for science and technology student teachers

Education for sustainable development (ESD) and digital competence are important issues in education that are rarely discussed in relation to each other. This chapter presents the collaboration and exchange of experiences of science and technology teacher educators in South Africa and Sweden, on the relationship between ESD and digital competence. Both countries have recently implemented digital competence in the curriculum for compulsory school, and teacher education in both countries is facing changes in preparing future teachers to teach digital competence incorporated with sustainability issues. The chapter's aim is to analyse and compare the curricula of the two countries to establish similarities and differences that could inform the discussion on the extent the involved teacher education institutions prepare science and technology teachers for teaching digital competence with respect to ESD, and what more should be done. The findings show that the compulsory curricula have broad coverage of digital competencies, but their relation to sustainability issues is vague. Further, the involved teacher education institutions need to broaden the coverage of digital competencies and incorporate this with ESD where sustainability issues are made explicit in relation to the potential, the challenges and the consequences of digital technologies on human, society and the environment.
Developing a Conceptual Prototype for Teaching English as a Foreign Language Based on Local Culture

&#x0D; &#x0D; &#x0D; Lumajang Regency, East Java, Indonesia, is known as a tourist destination, everyone is expected to be able to provide correct information to foreigners about Lumajang Regency, so that they will not lose the opportunity to get a job in the field of tourism, public service agencies and government related to tourism. Thus, the importance of maintaining local culture in teaching foreign languages should not be ignored. The researcher aims to develop a conceptual prototype for teaching English as a foreign language based on local culture. A conceptual prototype means a standard or typical example which is designed lessons that focus on the concept instead of individual facts. The significances of the study are to describe the factors that become obstacles in teaching English at STKIP PGRI Lumajang and describe the conceptual prototype developed in the process of learning English towards local culture. This research is a qualitative descriptive study on STKIP PGRI Lumajang students and the sample selection used a multi-stage sampling technique. The data generated are conceptual prototypes of learning English in universities which containing English competency standards, basic competencies, materials that must be taught to achieve competence, approaches, methods/strategies, and assessments used to assess student competence in learning English.&#x0D; Keywords: conceptual prototype, local culture, competence&#x0D; &#x0D; &#x0D;
@FARMAMENSEÑA: IT TOOLS TO IMPROVE AND REFRESH TEACHING-LEARNING PROCESSES

A. Sanchez-Ruiz, C. Martín-Álvarez, A. Sousa-Hervés, J. Tolosa-Barrilero, G. Blázquez-Abellán, P. Clemente-Casares, M.T. Alonso-Martínez, M.L. Nueda-Sanz, J.C. García-Martínez, I. Bravo-Pérez, V. Rodríguez-Robledo, A. Garzón-Ruiz, M.R. Fernández-Santos, C. Alonso-Moreno, J.A. Castro-OsmaUniversidad de Castilla-La Mancha (SPAIN)
DESIGN SPRINT IN HIGHER EDUCATION, GOING FROM FACE-TO-FACE TO REMOTE MODE

This paper discusses experiences of running intensive service design courses, namely Design Sprints, and the steps of moving from face-to-face to remote mode.The cases discussed are intensive courses in Finnish Bachelor education in multidisciplinary settings at Haaga-Helian University of Applied Sciences and an international intensive programme in a Nordplus programme offered to universities in the Nordic and Baltic region.Design Sprint is a service design model developed by Google Ventures (hereafter GV) is a five-day process to be used in business to find answers to and accelerate product development and solving of in-service business problems.The Design Sprint is a cost-effective way to develop and test ideas in a short time.Each sprint has a commissioner with real-life needs or problems to be solved.This customer centred method starts with gathering customer understanding, continues to generate and iterates ideas, creating prototypes, and testing them.The process combines best practices from business strategy, innovation, behaviour science and design thinking.The Design Sprint is used in business companies, public sector services and educational institutions around the world.The Design Sprint has been part of the curricula at the Porvoo campus of Haaga-Helia University of Applied Sciences since 2018.The sprint is arranged for third semester students of various disciplines with the objective of offering an intensive and hands-on insight into design thinking and product development with focus on customer understanding.Furthermore, commissioners are provided a swift experience of product and service development.The second experiences come from an international Nordplus project Eko Tek that offers students in the Nordic-Baltic area to experience and participate in an intensive programme of Design Spring offered by a network of universities and companies in the Nordic-Baltic region.The paper will discuss steps taken to move the Design Sprint intensive programme from face-to-face and international visits to remote sprints, the tools used to enable remote collaboration, student, and teacher experiences of the remote experience.In the end, the paper suggests how the experience might be used in similar intensive programmes in the future benefitting the student participants and enhancing collaboration.
PENGARUH PENERAPAN TEKNOLOGI INFORMASI BERBASIS WEB TERHADAP MOTIVASI BELAJAR SISWA PADA MATA PELAJARAN PKN KELAS X DI SMK PGRI 1 PALEMBANG

Application of web-based information technology to student learning motivation on PKn subject at the class X students of SMK PGRI 1 Palembang. The formulation of the problem in this research is "how is the application of web-based information technology to student learning motivation on PKn subject at the class X students of SMK PGRI 1 Palembang". The purpose of this research is to find out the students learning motivation using a web-based learning model on PKn subject at the class X students of SMK PGRI 1 Palembang. The method used in this study is the experimental method, the variables used in this study are the web-based as independent and students learning motivation as the dependent variables. The population in this study is all class X totaling 198 students, while the sample consists of class X AKL 1 (33 students) and class X AKL 2 (33 students), thus the total number of samples was 66 students. The data collection technique used is through the normality and homogeneity test steps of the data and the data is analyzed using statistical analysis (the t test).The results of the research proves that the use of web-based learning media is able to increase students learning motivation. It can be seen from the results of observation of motivation before being given the application of web-based learning media. It appears that the motivation aspect has an interest of 5.97% attention of 5.49% concentration with 5.27% persistence of 5.39%. And after being treated with web-based learning media it appears that the aspects of student learning motivation have an interest with a success percentage of 8.88% attention with a success percentage of 8.64% concentration with a success percentage of 7.10% persistence with a success percentage of 9.86%. From the data above, it can be obtained an average of 8.12 or an increase of 12.36%. This proves that there is a significant effect between web-based learning models on student learning motivation. It means that the web-based learning model influences in incresing the student learning motivation
They Who Hesitate: The Influencing Factors of Hesitation Phenomena in Students’ Speaking at IAIN Langsa

This research is carried out to investigate the influencing factors of the Hesitation phenomena in students’ speaking. The participant of this research is five students of seventh semester from English Department of IAIN Langsa in academic Years 2017-2021 who have been selected through purposive sampling based on certain characteristics. This research used qualitative method to gain the data, observation and interview. Based on the results, there are five factors lead the students to hesitate during speaking, which is breathing, pragmatic reason, cognitive process, linguistic planning, and nervousness. Therefore, one of the participants blamed that breathing can be the solution to overcome hesitation in speaking as well as practice and preparation. The researcher has several suggestions for this research. Specifically, first, the students should be aware of the existence of the hesitation phenomena during their speaking. Second, it is necessary to raise the lecturers' awareness since the hesitation phenomenon is an important factor that affects students speaking performance and difficulty. Finally, due to the limitation of this study, further investigation hopes to explore more with a larger population and different groups of students. Therefore, further research about certain approaches or methods to reduce hesitation phenomena in speaking is needed.
Insights from the LGBTQIA+ working group at EGU 2022

&amp;lt;p&amp;gt;Geoscientists identifying as LGBTQIA+ (Lesbian, Gay, Bisexual, Trans, Queer, Intersexual, Asexual, plus) are currently likely to face several more obstacles throughout their career compared to their cisgender/heterosexual colleagues. Additionally, they could experience the cumulative effect of an intersection of sexism, racism, and colonialism, if coming from one or more under-represented communities. With the aim to gather an EGU-based LGBTQIA+ group to coordinate and encourage a positive change within EGU and the broader geoscience community, a first social event was organized during the General Assembly (GA) in 2019, followed by a similar event during the GA in 2020 and 2021. Last year, the working group (WG) created a Discord forum to meet more frequently online and have a place for mutual support. The series of bottom-up initiatives - all community-driven -&amp;amp;#160; aimed at raising awareness or promoting initiatives for changes. These have included thus far: gathering feedback, promoting initiatives toward the inclusion of LGBTQIA+ scientists in the EGU community, and doing research in general (i.e., conducting fieldwork as LGBTQIA+ individuals in locations where it can be considered more dangerous, due to the illegality of belonging to the LGBTQIA+ community). An additional task the WG has undertaken is to engage with the wider community via webinars and represent the WG in meetings with other stakeholders. The WG also works closely with the Equality, Diversity, and Inclusion (EDI) Committee of EGU for improving the representation and inclusion of their members at EGU and across the scientific organizations. In this presentation, we summarise our work since the last General Assembly and highlight areas where we hope to attract further support for institutional and cultural changes that will foster an inclusive culture for LGBTQIA+ geoscientists.&amp;lt;/p&amp;gt;
A small step to AR. A big upgrade to fun

Nreal, founded in 2017, is dedicated to realizing consumer-facing Mixed Reality (MR) user experiences around the world. Nreal's flagship Nreal Light MR glasses are lightweight, comfortable and sport a wide Field of View (FoV). First unveiled at 2019's Consumer Electronics Show (CES) in Las Vegas, Nreal Light was unanimously critically acclaimed for its wearability and digital interactions. Nreal was awarded Engadget's "Best of CES Award" and the first Chinese startup to win this since the award's inception.
Education and children`s rights

The paper addresses a very interesting issue of children`s rights. Children`s rights need for children to know what rights mean. Unfortunately for many years there were no children`s rights and soviet regime believed that everything in the Soviet Union was perfect in this respect. The modern social environment, the educational space, the family needs the right orientation in these issues or, to put simply, upbringing and imparting knowledge.The whole educational space and social environment should try to bring the adolescent in this direction.
COMPARISON OF C4.5 ALGORITHM WITH THE NAVE BAYES CLASSIFIER ALGORITHM FOR CLASSIFICATION OF NUTRITIONAL STATUS OF TOODLER

So far, Body Mass Index (BMI) is used as a measuring tool to assess a person's nutritional status. If there are two who have the same weight and height, they may have different nutritional status. Anthropometric measuring tools play a very important role in determining the nutritional status. The anthropometric guidelines for determining nutritional status are the parameters chosen and recommended, which include an assessment of age, weight, body length or height. On the other hand, technological developments are currently increasing and giving a great influence in almost every sector of life and the state. The process of globalization that occurs in every country in the world today also supports the development and use of technology. The need for information will increase along with the development of technology. Several methods are used to process large data to find the patterns contained in them, including the C4.5 Algorithm and the Naïve Bayes Classification Algorithm which are algorithms from the decision tree method and Bayes theorem. The C4.5 and NBC algorithms will be used for the classification of the nutritional status of children under five, which will be classified into five classes, namely normal, fat, very fat, thin, or very thin.
Frame Attention Recurrent Back-Projection Network for Accurate Video Super-Resolution

In this study, we aim to recover high-resolution (HR) images from multiple low-resolution images using a multi-frame super-resolution (SR) or video SR to increase the resolution of surveillance camera images. The challenge of the multi-frame method is the high-precision alignment between frames, and many techniques have been proposed recently to solve it using convolutional networks, e.g., in the state-of-the-art method (i.e., recurrent back-projection network), the residuals between frames are calculated as subtle changes in the frames and back-projected onto the input image to achieve HR, including alignment. However, since the method uniformly concatenates multiple HR feature maps generated between each frame, it is impossible to focus on extracting important features for HR. Therefore, this study proposes a frame attention recurrent back-projection network for accurate video SR by emphasizing the essential frame features.
IMPLEMENTATION OF SPECIFIC EDUCATIONAL ACTIVITIES IN THE PROCESS OF EDUCATING PRIMARY SCHOOL STUDENTS IN ORDER TO REDUCE THE RISK OF BULLYING

Information about the paper titled "IMPLEMENTATION OF SPECIFIC EDUCATIONAL ACTIVITIES IN THE PROCESS OF EDUCATING PRIMARY SCHOOL STUDENTS IN ORDER TO REDUCE THE RISK OF BULLYING" at IATED Digital Library
SELECTIVE CHAOTIC GENERATION AND MULTI-MODALITY DIGITAL IMAGE CRYPTO SYSTEM USING HAAR WAVELETS

The importance of secured image transmission plays a significant role in this information era. The hackers hack the medical data in the form of images that costs more in terms of claiming insurances. It is necessary to secure the images that cannot be accessed by the unauthorized persons. Among the many types of image crypto systems, the chaos based image crypto systems is best known for its key insensitive to attack or hacking. The properties of the chaos play a major role in the generation of key for the secured transmission and reception. The Haar wavelet transform is yet simpler transform used to compress the input image in terms of approximate and detailed coefficients. The incorporation of the key in the approximate coefficients of the input image provides an efficient encryption when compared to other image crypto schemes. The encryption quality is evaluated using the histogram analysis of the encrypted of cipher image with different keys generated using respective chaotic maps. The framed image crypto system is designed and simulated using MATLAB software package. KEYWORDS: image cryptosystems, chaos theory, Haar wavelet transform, encryption, key generation.
Face Mask Detection in Crowd Areas using Deep Learning for Avoid Spreading of Covid-19 Corona Virus

Object discovery, focused on robotically noting device factors on snap shots or movies, expands the photo kind. In the previous couple of years, smart traveler manipulate has been appreciably utilized in small matters detection methods made use of in website vacationer manage, shrewd radar to manipulate structures, armed forces matters detection tools in the Navy. Great for beneficial treatments made use of to discover. Positioning of scientific tools made use of within the navy, medical navigating, operations, and so forth. COVID-19, a special corona virus dispersing in overdue 2019, stands for a opportunity for public fitness. Numerous international locations demand that everybody wear a public masks to keep away from the unfold of the Corona virus. To prevent the unfold of the Corona virus, an item discovery method just like a unmarried shot detector focuses on specific in addition to real-time popularity of face mask in supermarkets. Contributions are made with 3 parts: 1) to attract out the functions used by the lightweight spine network, that's primarily based upon SSD and additionally exquisite separable convection, which enhances discovery charge and Satisfies real-time detection wishes. 2) Suggest Feature Improvement Module (FEM) to strengthen the CNN fashions' deeper capabilities to beautify tiny things feature examples. 3) Develop a COVID-19-Mask, a big facts set to decide if customers are sporting mask, by gathering snap shots in 2 supermarkets. The corporation goals to reap high detection accuracy and also real-time efficiency of the proposed components.
Adjusting Parametersin Optimize Function PSO

Particel Swarm Optimization (PSO) is a form of population evolutionary algorithm introduced in the early 1995 by two American scientists, sociologist James Kennedy and electrical engineer. Russell. This thesis mainly deals with the PSO optimization algorithm and the methods of adaptive adjustment of the parameters of the PSO optimization. The thesis also presents some basic problems of PSO, from PSO history to two basic PSO algorithms and improved PSO algorithms. Some improved PSO algorithms will be presented in the thesis, including: airspeed limit, inertial weighting, and coefficient limit. These improvements are aimed at improving the quality of PSO, finding solutions to speed up the convergence of PSO. After presenting the basic problems of the PSO algorithm, the thesis focuses on studying the influence of adjusting parameters on the ability to converge in PSO algorithms. PSO algorithms with adaptively adjusted parameters are applied in solving real function optimization problems. The results are compared with the basic PSO algorithm, showing that the methods of adaptive adjustment of the parameters improve the efficiency of the PSO algorithm in finding the optimal solutions.