Reviewerly/exHarmony huggingface dataset:
Much Course Fuses Teaching Pattern Research

According to the problem that the teaching effect of vehicle major courses, vehicle major basic courses and cultural basic courses is not obvious in Vocational and technical education, the teaching research method of the integration of professional basic courses and professional courses, cultural basic courses and professional basic courses is given. After analyzing the connotation significance of the integration of multiple courses and the obstacles of the implementation at this stage, the construction of multiple courses is put forward The implementation opinions of integrated teaching play an important role in promoting the popularization of multi course integrated teaching.
PENERAPAN LITERASI MEDIA TERHADAP PEMBELAJARAN BAHASA INDONESIA

This reseacrh is based on the lack of student interest in learning Indonesian, both from the material side and the teacher in providing material in the classroom. This is the concern of all of us, especially prospective educators, so that they are able to stimulate and stimulate students so that they can be more active and enjoy learning Indonesian. Media literacy is one solution to this problem, where teachers must be able to innovate by applying media literacy when learning Indonesian. This research is intended to find out prospective educators regarding their preparation for entering the world of education, thus learning cannot be sparated from the existence of innovation, on of which is the learning media that teachers must use. This study uses a qualitative descriptive method that describes data and facts in the from of descriptions  obtained through a questionnaire. The sample of this research was conducted on 10 students of IKIP Siliwangi. The results showed that of the entire sample, 10 students of IKIP Siliwangi knew about media literacy, 10 people said that the use of media literacy is appropriate for learning Indonesian, 10 people stated that media literacy can improve the quality of student learning, 9 people said that media literacy can be used at all levels of schooll and 1 person stated that media literacy cannot be used at all levels of schooll, and 3 people stated that conventional media is more effective than electronic and 7 people said conventional media was not effective than electronic media.
Study of Commonly Used Image Interpolation Techniques for Single Frame Super Resolution Methods

Image quality is defined with respect to the term known as resolution. Basically, resolution illustrates the clarity of an image. Feasible sensors can be implemented for achieving higher quality of images but it is not exorbitant. Instead of focusing on various image processing ways, our focus should be on preparing higher resolution images and it would also be affordable. The term which is used for this process, is known as Super Resolution Image Reconstruction which is used for improvement of image quality.The whole paper focuses of generation and analysis of multiple methods of super resolution. In the current days, satellite image processing, medical image processing and many other departments use these processes for obtaining excellent resolution images from. The editing applications also use these processes for generating high resolution images or hazy images. In recent years enhancing the quality of image using Super Resolution methods have got very famous and further researches are going on for rendering more efficient pictures.
SURVEI DAN ANALISIS PENGGUNAAN INTERNET DI UNIVERSITAS JANABADRA

This research was conducted with the aim to find out the largest absorption of bandwidth used to access anything (eg social media, youtube and others) and to find out the factors that make internet connections at Janabadra University often not connected or slow connections. The method used in this study is to use the method of distributing questionnaires to all internet users at Janabadra University both employees, lecturers and students then the results of the questionnaire are processed and analyzed using regression analysis. Meanwhile, to determine the amount of bandwidth traffic using Quality of Service (QoS) analysis namely throughput, jitter and delay. To measure the QoS, the software is wireshark. Wireshark is used to record or view internet access distribution traffic that is used by users in Janabadra University. The results obtained that the highest bandwidth uptake is used for access to YouTube, online games and social media live streaming and it is evident from the analysis of internet usage traffic at Janabadra University that due to bandwidth is often used for unsuitable access, it produces a very small throughput with an average 2,092 kbps average. Keywords : Delay, Jitter, Throughput, Quality of Service.
Penggunaan Algoritma Kruskal Dalam Jaringan Pipa Pendistribusian Air Perusahaan Daerah Air Minum (PDAM) Tirta Dharma Lamongan

Water is one of the important needs for living things, especially humans. Almost all human activities need air, especially drinking water. Lack of human awareness of air pollution and a great deal is needed to distribute clean air to the community with an optimal pipeline to minimize costs. Optimizing the distance of pipelines can be done by searching for a minimum spanning tree. In this study, tree trails were searched with a minimum network of PDAM Tirta Dharma Lamongan using the Kruskal Algorithm. The results obtained in this study are pipe networks that have the shortest distance. The distance between the primary pipeline network installed with the minimum spanning tree primary pipeline network is 14,243.6 meters.
PROTECTRAIL demonstration – UIC Communications

In FP7, PROTECTRAIL is one of the largest integrated projects on security and probably the most relevant initiative in railway security at present. The objective is to develop a global framework,…
Embedding Algorithms for Quantum Annealers with Chimera and Pegasus Connection Topologies.

We propose two new algorithms – Spring-Based MinorMiner (SPMM) and Clique-Based MinorMiner (CLMM) – which take as input the connectivity graph of a Quadratic Unconstrained Binary Optimization (QUBO) problem and produce as output an embedding of the input graph on a host graph that models the topology of a quantum computing device. As host graphs, we take the Chimera graph and the Pegasus graph, which are the topology graphs of D-Wave’s 2000 qubit (first introduced in 2017) and 5000 qubit (expected 2020) quantum annealer devices, respectively. We evaluate our algorithms on a large set of random graph QUBO inputs (Erdős-Renyi \(G_{n,p}\), Barabasi-Albert and d-regular graphs) on both host topologies against other embedding algorithms. For the Pegasus topology, we find that CLMM outperforms all other algorithms at edge densities larger than 0.08, while SPMM wins at edge densities smaller than 0.08 for Erdős-Renyi graphs, with very similar transition densities for the other graph classes. Surprisingly, the standard D-Wave MinorMiner embedding algorithm – while also getting slightly outperformed by SPMM for sparse and very dense graphs on Chimera – does not manage to extend its overall good performance on Chimera to Pegasus as it fails to embed even medium-density graphs on 175–180 nodes which are known to have clique embeddings on Pegasus.
Plataformas para el aprendizaje en línea: La protección de datos en el ámbito educativo

espanolLa suspension de la actividad docente presencial, derivada de la crisis sanitaria ocasionada por laCOVID-19, ha tenido como consecuencia directa que las distintasAdministraciones educativas dirijan su mirada hacia la ensenanza a distancia. Principalmente, por la posibilidad de permitir compatibilizarla prevencion de la enfermedad con mantener una relacion interpersonal con el alumnadolo mas cercana posible. En este contexto, la utilizacion de distintas plataformas educativasse ha vuelto imprescindible y con ello la necesidad de trabajar con datos personalesde todos los intervinientes en el proceso, convirtiendo la seguridad y proteccion de los datosen una preocupacion de instituciones y gobiernosque debe ser gestionada desde todos los ambitos. El presente articulo tiene como finalidad hacer visible algunos de los aspectos mas complejosy relevantes en el tratamiento de datos personalespor parte de lasplataformas para el aprendizaje en linea, asi como determinar aquellas actuaciones de la Administracion o de los centros educativos que se deben seguir para una mejor proteccion delos usuarios, de conformidad con los derechos y obligaciones que impone la normativavigente. Para ello, y a modo de ejemplificacion, se analizan dos de las plataformasmas ampliamente utilizadas por el profesoradoy alumnado espanol:G Suite for Educationy Microsoft 365 Education EnglishThe suspension of face-to-face teaching activity, derived from the health crisis caused by COVID-19, had as a direct consequence that the different educational Administrations turned their eyes towards distance learning. Mainly, due to the possibility of making the prevention of the disease compatible with maintaining an interpersonal relationship with the students as closely as possible. In this context, the use of different educational platforms has become essential and with it the need to work with personal data of all those involved in the process, making the security and protection of data a concern of institutions and governmentsthat should be managed from all ambits involved.The purpose of this article is to make visible some of the most complex and relevant aspects in the treatment of personal data by online learning platforms, as well as to determine those actions by the Administration or educational centers that must be followedfor better protection of users, in accordance with the rights and obligations imposed by current regulations. For this, and as an example, two of the platforms most widely used by Spanish teachers and students are analyzed: G Suite for Education and Microsoft 365 Education
PEMBELAJARAN MENULIS TEKS EKSPLANASI MENGGUNAKAN METODE DISCOVERY LEARNING

Abstract The background of this research is the lack of students' interest in writing activities, especially writing explanatory texts. Writing is an activity to express ideas and ideas through writing media. These problems can occur due to several things, for example teacher and student factors who have an important role in the achievement of learning. Therefore, researchers try to provide solutions to these problems so that students' interest in writing explanatory text can increase. This study aims to describe: (1) the use of discovery learning method in class VIII students in learning to write explanatory text. (2) the results of the analysis of the students' ability in writing explanatory text using discovery learning methods. The research method used in this research is descriptive qualitative method. The subjects in this study were 29 students of class VIII. The results of this study indicate that the use of discovery learning method in learning to write explanatory text is carried out in accordance with the planned steps. In addition, the students' ability to write explanatory texts in grade VIII was quite good and the final average score obtained was 77.9.
Single Image Super-Resolution for Domain-Specific Ultra-Low Bandwidth Image Transmission

Low-bandwidth communication, such as underwater acoustic communication, is limited by best-case data rates of 30--50 kbit/s. This renders such channels unusable or inefficient at best for single image, video, or other bandwidth-demanding sensor-data transmission. To combat data-transmission bottlenecks, we consider practical use-cases within the maritime domain and investigate the prospect of Single Image Super-Resolution methodologies. This is investigated on a large, diverse dataset obtained during years of trawl fishing where cameras have been placed in the fishing nets. We propose down-sampling images to a low-resolution low-size version of about 1 kB that satisfies underwater acoustic bandwidth requirements for even several frames per second. A neural network is then trained to perform up-sampling, trying to reconstruct the original image. We aim to investigate the quality of reconstructed images and prospects for such methods in practical use-cases in general. Our focus in this work is solely on learning to reconstruct the high-resolution images on real-world data. We show that our method achieves better perceptual quality and superior reconstruction than generic bicubic up-sampling and motivates further work in this area for underwater applications.
Design and Implementation of a Digital Evidence Management Model Based on Hyperledger Fabric

When a crime occurs, the information necessary for solving the case, and various pieces of the evidence needed to prove the crime are collected from the crime scene. The tangible residues collected through scientific methods at the crime scene become evidence at trial and a clue to prove the facts directly against the offense of the suspect. Therefore, the scientific investigation and forensic handling for securing objective forensic in crime investigation is increasingly important. Today, digital systems, such as smartphones, CCTVs, black boxes, etc. are increasingly used as criminal information investigation clues, and digital forensic is becoming a decisive factor in investigation and trial. However, the systems have the risk that digital forensic may be damaged or manipulated by malicious insiders in the existing centralized management systems based on client/server structure. In this paper, we design and implement a blockchain based digital forensic management model using Hyperledger Fabric and Docker to guarantee the reliability and integrity of digital forensic. The proposed digital evidence management model allows only authorized participants in a distributed environment without a central management agency access the network to share and manage potential crime data. Therefore, it could be relatively safe from malicious internal attackers compared to the existing client/server model.
Automating the pre-processing of time-domain induced polarization data using machine learning

&amp;lt;p&amp;gt;Exploring and studying the earth system is becoming increasingly important as the slow depletion of natural resources ensues. An important data source is geophysical data, collected worldwide. After gathering data, it goes through vigorous quality control, pre-processing, and inverse modelling procedures. Such procedures often have manual components, and require a trained geophysicist who understands the data, in order to translate it into useful information regarding the earth system. The sheer amounts of geophysical data collected today makes manual approaches impractical. Therefore, automating as much of the workflow related to geophysical data as possible, would allow novel opportunities such as fully automated geophysical monitoring systems, real-time modeling during data collection, larger geophysical data sets, etc.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Machine learning has been proposed as a tool for automating workflows related to geophysical data. The field of machine learning encompasses multiple tools, which can be applied in a wide range of geophysical workflows, such as pre-processing, inverse modeling, data exploration etc.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We present a study where machine learning is applied to automate the time domain induced polarization geophysical workflow. Such induced polarization data requires pre-processing, which is manual in nature. One of the pre-processing steps is that a trained geophysicist inspects the data, and removes so-called non-geologic signals, i.e. noise, which does not represent geological variance. Specifically, a real-world case from Grindsted Denmark is presented. Here, a time domain induced polarization survey was conducted containing seven profiles. Two lines were manually processed and used for supervised training of an artificial neural network. The neural net then automatically processed the remaining profiles of the survey, with satisfactory results. Afterwards, the processed data was inverted, yielding the induced polarization parameters respective to the Cole-Cole model. We discuss the limitations and optimization steps related to training such a classification network.&amp;lt;/p&amp;gt;
Seattle Kraken and Oak View Group lead the charge in stadium safety

The Seattle Kraken and Oak View Group are leading the way in figuring out best practices for getting fans back in arenas for entertainment events.
A study of the development of the different types of memory involved in processing visual information, from the ages of 5 to 50

In this paper, we present three studies. The objective of Study I (n= 260) is to examine the development of several types of visual and visual-spatial memories in young children (5–10 years), compared to young adults. The results of this show a differentiated development, particularly for the “Memory” (pictorial) test. In study II, a multivariate analysis shows that children have an undifferentiated visual-spatial memory (n= 306). Finally study III was conducted on a large age range, from 5 to 50 years old (n= 345) and shows that for visual memories, the highest performing age is 16. There are thus many visual memories, and the role of dual coding (verbal and pictorial) is proposed to explain the superiority of the “Memory” test at any age.
Är gymnasieskolans digitala säkerhet tillräcklig? : Risk- och sårbarhetsanalys, ur ett informationssäkert perspektiv

This work presents a study of how information security has been implemented in the municipal high school. The study covers applications' resistance to intrusion, hardware security, students & t ...
Grammatical Errors Made by Students in Writing English Descriptive Paragraph: A Study at English Department at Institut Agama Islam Negeri (IAIN) Kerinci

This study aimed at describing the types of grammatical errors made by the in writing English descriptive text. The participants of the study consisted of 47 students of English department at Institut Agama Islam Negeri (IAIN) Kerinci. The data were collected from the students’ compositions. The data were analyzed by using Error Analysis (EA). The grammatical errors in the students’ compositions were identified and classified. Each grammatical error was counted and calculated into percentage for frequency. The results revealed that the grammatical errors made by the students fell into seven categories: errors in using verb tense, singular and plural form, articles, prepositions, pronouns, word order (disordering/inversion of subject and verb) and word choice. The number of the errors in each type was apparently different. The most dominant errors were the errors in the use of preposition. There were 23 errors related to the use of preposition (33.3 % of the total errors). Compared to the total errors made by the students, there was only 1 error (1.4 %) in the use of pronouns
REALISATION OF REGULATORY REQUIREMENTS FOR EFL TEACHERS ICT-COMPETENCY FORMATION

Purpose of the study: The article examines regulatory requirements for the formation of competence in the field of ICT for EFL teachers, declared by UNESCO and the Council of Europe, and ways of their practical implementation. The purpose of this study is to assess the effectiveness of the methodology for the formation of ICT-competency, developed and implemented by the authors to prepare competent and competitive EFL teachers.&#x0D; Methodology: A comparative analysis method was selected to compile a review of regulatory documents. Then a critical analysis was used to specify the content and structure of EFL teachers ICT competency and to develop a methodology for the formation of the competency mentioned above. During the experimental training, we used pre-experimental and post-experimental testing for data collection, and statistical analysis methods for pedagogical research.&#x0D; Main findings: Relying on the analysis of the conducted experimental training data, the authors have concluded that the developed methodology significantly contributes to the formation of the ICT-competency of an EFL teacher. Therefore, we can use the methodology mentioned above as one of the ways of realisation of regulatory documents requirements.&#x0D; Application of this study: This study can be useful for educational institutions of various levels that prepare EFL teachers and want the graduates to be competent and competitive in today’s labour market. The methodology of ICT-competency formation described in the article can be implemented by those educators, who are looking for a way of practical realisation of the regulatory requirements of EFL teachers ICT-competency.&#x0D; Novelty of this study: This study has proposed a new methodology of an EFL teacher ICT-competency formation based on today’s most authoritative regulatory documents – UNESCO ICT-Competency Framework for Teachers 2018 edition and Common European Framework of Reference for Languages 2018 edition.
Estimation of Red Blood Cell-Count using Neural Networks

Quantification through image analysis is used in a multitude of fields, and often requires algorithms tailored to the specific task and object that needs to be quantified. The need for flexibility means that such segmentation algorithms are quickly becoming outdated with the advent of convolutional neural networks, which can be trained to fit the specific requirements of the user. One of the fields in which quantification image analysis is of particular importance is that of hematology, where an estimation of the number of blood-cells in an image can give fast preliminary results on tests such as Complete Blood Count (CBC). In this project the use of neural networks as a means of estimating red blood-cell count in microscopic images taken at 50x magnification is investigated, and compared to a state-of-the-art segmentation algorithm designed for red blood-cell detection. The convolutional neural networks are trained to perform regression using data annotated only with the blood-cell count of the image, and the use of both synthetic data training and pre-trained models is investigated. The developed network demonstrates both higher accuracy, five times faster evaluation time, and a higher stability being able to better distinguish between overlapping red blood-cells - a major source of error for the segmentation algorithm. In addition to this, qualitative results from the network's computer vision demonstrates the network's ability to differentiate between different cell types. (Less)
Subject guides: Text and data mining: 6. Tools and resources

An introduction to text and data mining concepts and an overview of the steps involved in undertaking text and data mining as part of a research project.
CJEU rules that notion of ‘address’ in the Enforcement Directive is limited to one’s own postal address

Court of Justice of the European Union, Case C-264/19, Constantin Film Verleih GmbH v YouTube LLC and Google Inc., EU:C:2020:542, 9 July 2020 Agreeing with the Opinion of Advocate General Saugmandsgaard Øe in the same case (EU:C:2020:261), the Court of Justice of the European Union has ruled that the notion of ‘address’ in Article 8(2)(a) of the Enforcement Directive 2004/48 is limited to one’s own postal address, and does not include one’s own email and IP address or telephone number. However, since the Enforcement Directive is a measure of minimum harmonization, individual Member States are entitled to grant more extensive protection. The dispute between film producer Constantin Film and YouTube and its parent company Google arose further to the refusal, by the latter, to disclose details of users who had uploaded on YouTube unlicensed full-length versions of Constantin Film’s productions Parker and Scary Movie 5....