Reviewerly/exHarmony huggingface dataset:
Access to EXCITE: A European infrastructure to promote electron and X-ray microscopy of earth materials

Understanding earth materials is essential for the creation of a sustainable, carbon-neutral society. Earth materials control the feasibility of subsurface energy storage, geothermal energy extraction, and are a source of critical elements for future-proof battery technologies. To tackle the current, pressing scientific questions related to sustainable development for a circular economy, there is an urgent need to make multi-scale, multi-dimensional characterisations of earth materials available to a broad spectrum of earth-science disciplines. Besides society-relevant topics, the properties of earth materials determine how the Earth works on the most fundamental level.To overcome this challenge, 15 European institutes joined forces to establish EXCITE, providing free-of-charge access to 24 state-of-the art microscopy and x-ray tomography facilities in Europe. EXCITE can help you gain insight into the processes governing the behavior of the Earth crust through microchemical analyses and 2D- to 4D imaging, and down to nanometer resolution.&amp;#160;In particular, the EXCITE strategy integrates joint research programs with networking, training, and trans-national access activities, thereby enabling both academia and industry to answer critical questions in earth-materials science and technology.&amp;#160;EXCITE is building a community of highly qualified earth scientists, develops correlative imaging technologies providing access to world-class facilities to particularly new and non-expert users that are often hindered from engaging in problem-solving microscopy of earth-materials. EXCITE is building a community of highly qualified earth scientists, develops correlative imaging technologies providing access to world-class facilities to particularly new and non-expert users that are often hindered from engaging in problem-solving microscopy of earth-materials. Access to EXCITE can be requested by applying to our bi-annual call. Interested? Have a look on the EXCITE website (https://excite-network.eu) &amp;#8211; and apply!
An Artificial Intelligence-based platform for volcanic hazard monitoring

Satellite remote sensing data are suitable to monitor global scale volcanic hazards in an efficient and timely manner. The development of monitoring systems which automatically collect and process satellite data is crucial during a volcanic crisis. The huge amount of multispectral satellite data available requires new approaches capable of processing them automatically and artificial intelligence (AI) addresses these needs. Machine learning, a type of AI in which computers learn from data, is gaining importance in volcanology. The combination of ML algorithms and satellite remote sensing in volcano monitoring has the potential of analyzing global data in near real-time for mapping and monitoring purposes. Here, an AI-based platform was developed to monitor in near real-time the volcanic activity from space. AI algorithms are used to retrieve information about the ongoing volcanic activity. Under this perspective, a key role is played by ML since it overcomes the issues related to hard coded/explicit rules by implicitly learning them from historical satellite data. Volcanic eruptions are then fully characterized in terms of their energy release, e.g. volcanic radiative power (VRP), effusive rate, quantification of the erupted products, i.e. volume, spatial extension, volcanic cloud composition. This task is achieved by combining a variety of freely available satellite datasets, i.e. infrared (IR) data with different spatial, temporal and spectral features.&amp;#160; In particular, both a geostationary satellite sensor, i.e. SEVIRI (Spinning Enhanced Visible and InfraRed Imager, on board Meteosat satellites), and several mid-high spatial resolution polar satellite sensors, e.g. MODIS (Moderate Resolution Imaging Spectroradiometer, on board Terra and Aqua satellites), VIIRS (Visible Infrared Imaging Radiometer Suite, on board the Suomi-NPP and NOAA-20 satellites), SLSTR (Sea and Land Surface Temperature Radiometer, on board Sentinel-3A and Sentinel-3B satellites), MSI (MultiSpectral Instrument, on board Sentinel-2), are adopted. We demonstrate the potential of this web-based satellite-data-driven platform during the recent eruptive events on Stromboli and Etna.&amp;#160;
Restating Research Findings in Research Articles Discussion Section: A Corpus Analysis of Linguistic Cues and Lexical Bundles

The discussion section is considered one of the most crucial sections of a research article (RA). It is challenging and problematic for both novice and native writers due to its argumentative nature. This section serves various functions such as restating results, interpreting the results, comparing them with the literature, and presenting claims and contributions. However, the focus of this paper is on a particular move function which is Restating Research Findings. Although this communicative move has been found to be obligatory or conventional in recent studies that investigated different disciplines, the present paper is only concerned with medical science discipline. Every communicative move serves a certain function that may be initiated by formulaic expressions, known as ‘lexical bundles’ (LBs) which are realised by the use of certain linguistic devices. This study explores these linguistic devices and the lexical bundles associated with move Restating Research Findings in the discussion section of medical research articles (MRAs). The analysed corpus is 50 discussions of research articles published in high impact journals. The findings showed that this move appeared in all the selected discussions. The move of Restating Research Findings was realised by the employment of reporting verbs (e.g., find, show) and first person plural pronouns (we, our). Also, the move was initiated by a number of 3-word and 4-word LBs such as Our study shows that and Our results revealed that . These findings could guide research writers in the field of medicine to produce a clearly presented discussion section.
Gender Detection Via Voice Using Artificial Intelligence Algorithms

As a result of the developments in science and technology, all our living spaces, from health, education, and trade to our social life, have been moved to the digital environment.With this process, artificial intelligence, which is the ultimate goal of creating systems that think and act like human beings, has started to be used in all areas of our lives.This study focuses on gender determination by using artificial intelligence algorithms on voice data.Thanks to this determination, significant contributions will be made in various fields such as social engineering and cyber security such as fraud, person detection, and advertising investments.In the analysis of the study, R application, a completely open-source, for various artificial intelligence algorithms has been used.In this way, a solution has been provided to take the security as mentioned above measures with low cost instead of highcost systems and increase the sales figures in areas such as marketing.In the study, supervised learning artificial intelligence algorithms have been examined.The artificial intelligence analysis results of the study have shown that the gender of the person could be determined above % 97 successful rates through the voice data.
E-Book Berbasis Elaborasi Gambar Sebagai Penguatan Kognitif Siswa

The development resulted in an e-book based on image elaboration as a learning medium for cognitive strengthening. Luther-Sutopo's version of the MDLC (Multimedia Development Life Cycle) includes: concept, design, material collecting, assembly, testing, and distribution is a method for development. Data analysis used quantitative and qualitative. The e-book has been declared valid and suitable for use in learning based on the results of the validation of media experts 95.83 percent and material experts 100 percent. Students have stated that ebooks are effective 86.5 percent. E-books provide cognitive reinforcement to students' analytical skills based on increasing pretest and posttest scores.AbstrakPengembangan menghasilkan E-book berbasis elaborasi gambar sebagai media pembelajaran untuk penguatan kognitif. MDLC (Multimedia Development Life Cycle) versi Luther-Sutopo meliputi: Konsep, Desain, Pengumpulan materi, Pembuatan, Pengujian, dan Distribusi merupakan metode untuk pengembangan. Analisis data menggunakan kuantitatif dan kualitatif. E-book telah dinyatakan valid dan layak digunakan dalam pembelajaran berdasarkan hasil validasi ahli media 95.83 persen dan ahli materi 100 persen. Siswa telah menyatakan bahwa ebook efektif 86.5 persen. E-book memberikan penguatan kognitif pada kemampuan analisis siswa berdasarkan peningkatan nilai pretest dan posttest.
Calculation of the ground and exited states of the Ising model using Quantum Approximate Optimization Algorithm(QAOA)‎

The one-dimensional quantum Ising model is used to describe many physical systems, therefore the calculation of ground and excited state energies of Ising model that has many applications in statistical mechanics, has been paid attention. We obtain the ground and excited states of this model by using the Quantum Approximate Optimization Algorithm(QAOA), which is a kind of hybrid quantum-classical algorithms. For this purpose, first, we find the ground state with quantum approximate optimization algorithm, then we generalize this algorithm by adding an overlap term to obtain excited states. We calculated ground state energy and excited states energies for different coupling coefficients which is compatible with exact calculation.
Image Processing Based Pattern Recognition and Computerized Embroidery Machine

In the last decades, embroidery getting much attention in industries and academics. Although the technique is very old, it is still very much adopted. The current era of machine learning and smart devices makes this method even more attractive, easy to adopt and high accuracy. The proposed research work aims to highlight the implementation of new smart devices in this field, and the work is based on microcontrollers. Adopting the proposed work will be very easy and feasible to transform from the old sewing machine to a new smart method. Using smart devices, it is very easy and precise to get the embroidery fulfilling the user's demands. It gives simple raster images, which are used to convert into digital images to portray any new product. The current work is a novel idea of generating simple images rather than complicated ones, which are difficult to draw. In our method, we introduce the digitization process to input any image file used for vectorizing raster images, where vector images can easily convert into a DST embroidery file, a commonly used embroidery format originally from Tajima. It also has a Gcode file. The machine runs on a Gcode file which can be easily generated and runs on a product.
Analysis of Research Trends for Self-encouragement Programs for Children

In this study, by examining research trends in self-encouragement-related dissertations and academic dissertations for children, this study examines research related to encouragement and provides directions and basic data for follow-up research.It was carried out for the purpose of presenting future self-encouragement research directions by arranging research results and trends through analysis.Using the Academic Research Information Service (RISS), we searched for degree thesis and domestic academic thesis published in Korea for 11 years from 2010 to 2020.After searching for keywords such as 'Encouragement group program' and 'Children', 37 articles related to encouragement were selected for children.Among the articles searched for 'Encourage others' and 'Children', two articles were included, excluding duplicate articles.Among them, 20 research studies and 41 experimental studies were finally selected, excluding papers that could not be viewed in the original text.The characteristics analysis criteria of the research subjects can be explained by dividing them into individual factors and environmental factors.Individual factors were divided into 'general', 'school violence', 'learning difficulty', and 'maladjustment'.'General' was classified as students with normal cognitive and emotional levels, and 'School Violence' was classified as students who experienced violence due to exposure to school violence.'Difficulty in learning' refers to children who have difficulties in any one of poor learning, learned helplessness, low achievement motivation, and high test anxiety.were classified as children with.
The Way to picture Reality: A Review, Evaluation and Recipe of Image Harmonization

Abstract Image harmonization is an interesting but challenging task in image processing. The task is to adjust the visual information between the foreground and background in the picture, so that the overall picture becomes a harmonious and unified process. Compared to traditional unsupervised methods for image processing, recent developments in deep learning have brought new opportunities to the field. Since 2019, related image harmonization papers have begun to appear on a large scale. In order to better sort out the development of this field, we summarize the field from two aspects of supervised learning and unsupervised learning, and also deeply integrate the existing image harmonization dataset and related index evaluation. We then conduct a detailed comparison and analysis of the existing models. Finally, the current challenges and future research directions of deep learning in image harmonization are discussed.
Sentencing data-driven cybercrime. How data crime with cascading effects is tackled by UK courts

This paper contributes to research seeking to understand if and how legislation can effectively counter cybercrimes that compromise personal data. These ‘data crimes’, which are the ‘dark side’ of big data and the data economy enabled by cloud computing, display cascading effects, in that they empower disparate criminals to commit further crimes and victimise a broad range of individuals or data subjects. The paper addresses the under-researched area of sentencing, which, as the last step of the judicial process, plays a crucial role in how the law is interpreted and implemented. This paper investigates courts’ approach to the evolving technological environment of cybercrime captured by data crime and the cascade effect and whether the cascade effect can assist courts in dealing with data-driven cybercrime. The paper examines original data collected from UK courts, namely 17 sentencing remarks relating to cybercrime court cases decided in England & Wales between 2012 and 2019. The analysis shows that courts appreciate the impact of data crime and their cascading effects, but that the complexity of the offences is lost at sentencing, arguably due to the negative impact of systemic factors, such as technology neutral law and the lack of legal authorities. After examining such systemic factors, the paper suggests how the cascade effect could aid sentencing by adding specificity and context to data crime. The paper ends with avenues for further research relating to debates on fair cybercrime sentencing and open justice.
Blockchain Digital Health care use cases

The blockchain is a powerful piece of technology that enables many individuals to access data and exchange it with one another in a protected environment. This presents a significant challenge in the field of digital health, where it is of the utmost importance to protect patient privacy and security but where it is impossible to improve care quality without improved patient data management across the entire healthcare system, and the ability to use analytics on patient data gathered at the population level. To summarise, blockchain technology has the potential to improve digital health by making it simpler and safer to communicate patient data across extremely decentralized healthcare systems. This would result in an overall improvement in digital health.
ERFORMANCE ANALYSIS OF ALEXNET CONVOLUTIONAL NEURAL NETWORK (CNN) ARCHITECTURE WITH IMAGE OBJECTS OF RICE PLANT LEAVES

Rice is a staple food consumed by Indonesian people, even 75% of the world's population consumes rice and it is mostly found in Asia. Rice derived from pounded rice is a staple food so it can be consumed. In the process of planting rice, pests and diseases are not spared so that it can affect crop yields. Pest and disease attacks need fast, accurate and precise handling so that crop failures. In this paper, we will discuss the classification of leaf diseases of rice plants using the Convolutional Neural Network (CNNN) algorithm, especially the Alexnet architecture. There are 4 types of disease, namely Brown spot, Leafblast, Hispa and Healthy. Models built based on the Alexnet architecture may have differences in the level of accuracy and loss compared to other architectures due to the different stages in the sequential model formation. The dataset used is public data from Kaggle consisting of 4 classes with a total of 1,600 images. In each class the dataset is divided for training, testing and validation datasets with a ratio of 70:20:10. As for tools in the process of training datasets using Google Colab from Google. After going through the stages of the research, the research results obtained are accuracy worth 99,22%, mean average precision worth 0,24 and loss worth 0,05.
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The paper examined the contributions of party system to democratic development in Africa. Democratic governance and meaningful elections have long been considered unachievable in the absence of political parties and party competition. This is because party system institutionalization is important for the consolidation of democracy. Democracy instead of being the bedrock of good governance stayed on as an unfulfilled promise because the method of power acquisition remained basically authoritarian and functioned on the basis of a hierarchy of networks and alliances with local tribe, ethnic group or through top-down utter sovereignty of institutions that choke the grassroots politicization of society which had been the moral fibre of the process of democratization. To this end, it was discovered that the relationship between political parties, electoral volatility and democracy in Africa cannot be addressed unconnectedly. The paper therefore recommends that; assumptions about the trajectory and outcomes of democratic development in Africa need to be more effectively investigated on the basis of empirically informed analysis of operationalized politics in these systems. It is important to bear in mind that most of the electoral systems, laws, institutions and constitutions that govern elections in Africa were inherited from colonialism. Electoral politics came as a proposed solution to other socio-economic and political problems. This therefore calls for an amendment to these electoral processes in order to mirror the present realities in Africa as well as adhere to best practice as it is in developed democracies. It is contended that if an electoral system is to append value to democracy, it must promote the accountability of the elected representatives to their constituencies which could be furnished through strong political parties. The paper relied on secondary data using descriptive analytical method.
A Qualitative Study on the Differences in Perception between the Elderly and Social Workers Using the Elderly Welfare Center for Non face-to-face Education

This study was conducted to find out the difference in perception between social workers and the elderly who experienced non-face-to-face education during the COVID-19 period, and to find the role and direction of senior welfare centers in the post-COVID-19 era.To this end, individual interviews were conducted with 5 social workers and 11 elderly people, and the collected data were analyzed by qualitative research methods.As a result, non-face-to-face education experienced and recognized by social workers was found to be "inefficient but suboptimal choice," "non-face-to-face contact with users," "overweight due to non-face-to-face provision," and "confusion in job identity."On the other hand, the elderly were analyzed as 'self-development using non-face-to-face education', 'need non-face-to-face education', 'desperate for digital device education', and 'welfare center daily life'.Based on the results of the study, it was derived that there is a difference between non-face-to-face education recognized by social workers and the elderly, and suggestions for future non-face-to-face education such as coordination of work, supporting non-face-to-face work, and strengthening digital education for the elderly.
Clinical Trial Testing the Effectiveness of Prenatal Environmental Program using YouTube for Pregnant Women: Protocol for a Nonrandomized Study

This study developed the environmental health behavior educational intervention for pregnant women using YouTube.The intervention program consisted of eight session You-Tube: Endocrine disruptors, chemical exposure, heavy metals, nutrition, drug effect, micro-dust exposure, electromagnetic wave, and environmental toxin release during pregnancy.The subthemes contained lead, mercury, cadmium, micro plastic, genetically modified organism, anticoagulant, hormone,
Implementasi Metode Perceptual Hash Untuk Deteksi Plagiarisme Tugas Mata Kuliah Software Modeling

Plagiarism is a crime that is no stranger to the world of education in Indonesia. Plagiarism can be done in the form of text or images. One example of plagiarism in the form of images is when submitting assignments for the Software Modeling course at the STIKOM PGRI Banyuwangi Campus. One example of plagiarism that was carried out at the STIKOM PGRI Banyuwangi Campus was when a student copied a drawing assignment from another student. However, only changed in a few elements.Therefore, we need a mechanism that can detect plagiarism in the form of images.One method that can be used to detect the similarity of image sources is to use the perceptual hash algorithm. The algorithm is applied to compare one image with another image that is suspected of plagiarism. In applying this perceptual hash method, it requires a program using the PHP programming language.The results of this study are to detect plagiarism with an 8x8 image resize which has the fastest computing time of 0.437 seconds. When tested, the perceptual hash method was able to detect plagiarism with a success rate of 70.7% with a threshold value of 75% for the similarity level. However, it is not capable of images that change position. Thus, the perceptual hash method is capable of detecting plagiarism of sequence diagram images without changing position or normally.
Aplikasi Web Pelayanan Kesehatan Masyarakat Di Kelurahan Singonegaran Dengan Metode Rapid Aplication Development

Health services to the community are the duties of the Public Health Center (Puskesmas) formed by the government. However, it cannot reach the entire community. Posyandu to be formed to carry out community self-help activities in the health sector carried out in the Kelurahan. Singonegaran Village is one that has a posyandu to serve public health in its environment. In serving the health of the community, it is necessary to process data. Data processing is carried out by cadres and health workers. Data processing carried out by cadres at Posyandu Kelurahan Singnegaran still uses book recording methods. This resulted in several problems such as the process of inputting, processing and retrieving old data. Therefore we need a system or application that can overcome these problems. Then a web-based health service application was made in Singnegara Village. The development of public health service applications in Singonegaran Village uses the Rapid Application Development (RAD) development method with the blackbox testing method. From the results of the application development it was declared successful in testing.