Reviewerly/exHarmony huggingface dataset:
The Magnetics Information Consortium (MagIC) Data Repository: Successes and Continuing Challenges

&amp;lt;p&amp;gt;MagIC (earthref.org/MagIC) is an organization dedicated to improving research capacity in the Earth and Ocean sciences by maintaining an open community digital data archive for rock and paleomagnetic data with portals that allow users access to archive, search, visualize, download, and combine these versioned datasets. We are a signatory of the Coalition for Publishing Data in the Earth and Space Sciences (COPDESS)'s Enabling FAIR Data Commitment Statement and an approved repository for the Nature set of journals. We have been in collaboration with EarthCube's GeoCodes data search portal, adding schema.org/JSON-LD headers to our data set landing pages and suggesting extensions to schema.org when needed. Collaboration with the European Plate Observing System (EPOS)'s Thematic Core Service Multi-scale laboratories (TCS MSL) is ongoing with MagIC sending its contributions' metadata to TCS MSL via DataCite records.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Improving and updating our data repository to meet the demands of the quickly changing landscape of data archival, retrieval, and interoperability is a challenging proposition. Most journals now require data to be archived in a &amp;quot;FAIR&amp;quot; repository, but the exact specifications of FAIR are still solidifying. Some journals vet and have their own list of accepted repositories while others rely on other organizations to investigate and certify repositories. As part of the COPDESS group at Earth Science Information Partners (ESIP), we have been and will continue to be part of the discussion on the needed and desired features for acceptable data repositories.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We are actively developing our software and systems to meet the needs of our scientific community. Some current issues we are confronting are: developing workflows with journals on how to publish the journal article and data in MagIC simultaneously, sustainability of data repository funding especially in light of the greater demands on them due to data policy changes at journals, and how to best share and expose metadata about our data holdings to organizations such as EPOS, EarthCube, and Google.&amp;lt;/p&amp;gt;
Recovering Secrets From Prefix-Dependent Leakage

Abstract We discuss how to recover a secret bitstring given partial information obtained during a computation over that string, assuming the computation is a deterministic algorithm processing the secret bits sequentially. That abstract situation models certain types of side-channel attacks against discrete logarithm and RSA-based cryptosystems, where the adversary obtains information not on the secret exponent directly, but instead on the group or ring element that varies at each step of the exponentiation algorithm. Our main result shows that for a leakage of a single bit per iteration, under suitable statistical independence assumptions, one can recover the whole secret bitstring in polynomial time. We also discuss how to cope with imperfect leakage, extend the model to k -bit leaks, and show how our algorithm yields attacks on popular cryptosystems such as (EC)DSA.
LibGuides: Citations for Archival Materials: Chicago

This guide will detail how to cite archival material located in the CSUDH Archives for MLA, APA, and Chicago citation styles.
Character-Level Neural Language Modelling in the Clinical Domain.

Word embeddings have become the predominant representation scheme on a token-level for various clinical natural language processing (NLP) tasks. More recently, character-level neural language models, exploiting recurrent neural networks, have again received attention, because they achieved similar performance against various NLP benchmarks. We investigated to what extent character-based language models can be applied to the clinical domain and whether they are able to capture reasonable lexical semantics using this maximally fine-grained representation scheme. We trained a long short-term memory network on an excerpt from a table of de-identified 50-character long problem list entries in German, each of which assigned to an ICD-10 code. We modelled the task as a time series of one-hot encoded single character inputs. After the training phase we accessed the top 10 most similar character-induced word embeddings related to a clinical concept via a nearest neighbour search and evaluated the expected interconnected semantics. Results showed that traceable semantics were captured on a syntactic level above single characters, addressing the idiosyncratic nature of clinical language. The results support recent work on general language modelling that raised the question whether token-based representation schemes are still necessary for specific NLP tasks.
Sobrevivência e características das revistas científicas de Minas Gerais instituídas na década de 1990

The aim of this paper is to identify the survival rate of scientific journals of Minas Gerais created in the 1990s. Based on those of Minas Gerais created in the 1990s, the question is: how long can a scientific journal be able to maintain your activities? What is the survival rate? It was characterized as descriptive and exploratory with quantitative and qualitative approach. The documentary research technique was adopted and used the following sources of data collection: ISSN Brazilian Center, National Collective Catalog, libraries of the Higher Education Institutions of the country and scientific journals. The survey identified 198 journals. The main findings were: 1997, 1998 and 1999 concentrated 47% of production in the period; most published twice a year (same fact at present); Higher Education Institutions are the major producers of the state; the most recurring subject was education; with reference to 2019, 19% are active; of the 81% inactive most survived 8 to 11 years; 96% of those who came out of paper stopped publishing and, at the other extreme, 89% of those born online remained in force. Noting the impact of the popularization of the personal computer and the Internet, more than half (58%) of Minas Gerais magazines created in 1990 migrated to open access online. The outlined panorama allowed to contribute to the historical memory of science and the state, to know the achievements of other generations and, consequently, to reflect on the directions to be pursued.
Rethinking Money, Rebuilding Communities. A Multidimensional Analysis of Crypto and Complementary Currencies

In the current scenario of global crisis, our official monetary system's inadequacy to provide solutions to the numerous serious problems affecting our society has become increasingly evident. This has led to the emergence of an astonishing number of projects that aim to rethink money. In order to make sense of these projects, it is necessary to explore the deepest meanings of money, as a multidimensional institution whose concrete nature and functioning are still object of a whole set of unsolved disputes. Under these premises, this article proposes an interdisciplinary reading of crypto and complementary currencies. The goal is twofold: on the one hand, the authors aim to shed light on the conditions which have to be met for the establishment of a sustainable monetary innovation; on the other hand, the article constitutes an attempt to use ongoing experiences as a lens through which to gain new insights into the general phenomenon of money and as a laboratory for exploring the possibility to move towards new socio-economic paradigms.
PENERAPAN METODE QUANTUM WRITER UNTUK MENINGKATKAN KEMAMPUAN MENULIS PUISI PADA SISWA SMK TELEKOMUNIKASI DARUL’ULUM

Quantum Writer method is good way to help student more easy and attractive to write. Quantum Writer method is contains four steps teaching learning writing ang can be easy to with PAK ! namely: concentrate (P), arrange (A), composing (K), the best (!). This method used to finished that problem appear (1) How to proces learning poerty at begining with Quantum Writer method, (2) How to proces learning poerty when student is writing poerty with Quantum Writer method, (3) How to proces learning poerty at the finishing or after writer poerty with Quantum Writer method, in this case every statement of the problem given student score. This Action Research (PTK) used descriptive kealitatif method is doing two steps is that observation student SMK Telekomunikasi Darul’Ulum. The data take from pre writing is contain students ability to mention theam. Then the result take from when student is writing poerty. With Quantum Writer merhod. Second step is that finished to write the result contains are reading a poerty, give suggestion with friend’s poetry, and revisi again based on friend’s suggestion. The result of the observation is that appliying Quantum Writer writer method can be increase to writing poetry very good for student. Students ability to writing poetry more increase every steps. And the response of the student increase.
Design of Interactive English Reading Teaching System Based on Hybrid Communication Network

In order to overcome the problem of long response time and poor interaction in traditional English reading teaching system, an interactive English reading teaching system based on hybrid communication network is proposed. The hardware part of the system is composed of seven modules, among which the course management module mainly adopts the combination of file system and multimedia attribute database to manage the uploaded data of teachers. Students use the hyperlink location field to mark the connection location of the media, can see more colourful learning pages, to achieve the interactive design of the teaching system. In the software part, the learning evaluation model is constructed by covering method or error method to realise the comprehensive evaluation of students' learning state. Simulation results show that this method can comprehensively understand and evaluate students' learning status and knowledge points, shorten the response time of the system, and has great advantages.
Similarity Evaluation Based on Contextual Modelling

Measuring Text similarity problem still one of opened fields for research area in natural language processing and text related research such as text mining, Web page retrieval, information retrieval and textual entailment. Several measures have been developed for measuring similarity between two texts: such as Wu and Palmer, Leacock and Chodorow measure and others . But these measures do not take into consideration the contextual information of the text .This paper introduces new model for measuring semantic similarity between two text segments. This model is based on building new contextual structure for extracting semantic similarity. This approach can contribute in solving many NLP problems such as te xt entailment and information retrieval fields.
Dynamic Epistemic Logic in Game Design

Dynamic Epistemic Logics are a set of multimodal logics that deal with knowledge and change. We argue that the theory for this formalism is mature enough to start a practical implementation, while at the same time having a sizable amount of theoretical expansions. We also claim that these two factors make it an attractive formalism for new features in games featuring an agent’s internal model, like planning for gathering information, acting without revealing one’s goals or feeding possibly false information to a set of agents to influence their beliefs, augmenting already existing mechanisms.
Traffic issues categorization of Indian Cities using Word2Vec by Social Media Data

In traditional ways, traffic related and road and transport related issued are highlighted and detected by mostly physical place visit in most of the world. New research area aims to use Social Media data and Classification techniques to detect Road and Transport Related issues. As current work has been done using Twitter data using Word2Vec classification algorithm to detect various issues at major cities of India. During our research work we plan to use Social Media Data and News Data with Word2Vec classification algorithm. We also intend to include tweets from local languages .We also planned to apply Word2Vec classification for Multi-Class Classification Problem and NLP for feature extraction. We have used cosine similarity function to find similarity among tweets and after find similarity we have obtained result from tweets into positive, negative, neutral with the help of semantic analysis.
Development of Teaching Material for Narrative Writing Skills Using Brainwriting Models in Elementary Schools: Pengembangan Bahan Ajar Keterampilan Menulis Narasi Menggunakan Model Brainwriting di Sekolah Dasar

This study aims to describe the process of developing narrative writing teaching materials and producing narrative writing teaching materials using Brainwriting for teachers and fifth grade elementary school students that are valid, practical, and effective.Type of research and development. The development model used by the 4-D model. This research was conducted at SDN 18 Sitiung. The subject of the research was the fifth grade elementary school students. Validity test research data obtained through the validation sheet of teaching materials. Practicality data was collected through observation sheets of the implementation of the lesson plans, teacher and student response questionnaires, and observations of the use of teaching materials. Based on the validity test, obtained data that the average percentage of RPP obtained 90.2% of the expert validator and practitioner validator with a category that is very valid. The results of the average percentage of teaching materials obtained 92.43% of expert validators in the category of very valid, from the practitioner validator is 94.7% the category is very valid. The practicality test results of the implementation of the RPP with a percentage of 87.71% category is very practical. Teacher response assessment obtained 91.8% and assessment of student responses 89.2% very valid category.
LibGuides: Embedded Tutoring: Overview & Objectives

This guide provides instructions, tips, resources, and research to support the embedded tutoring model employed in co-requisite courses funded by Title V. Mission
Effective visualization of sparse image-to-image correspondences

This work has been partially funded by the Spanish Ministry of Economy and Competitiveness and FEDER Grant TIN2017-88515-C2-1-R.
PERSONAL NON-PROPRIETARY INTELLECTUAL PROPERTY RIGHTS TO A CINEMATOGRAPHIC WORK

The legislative list of the latter is analyzed and the content of personal non-proprietary intellectual property rights in the cinematographic sphere is determined.In addition, personal non-property intellectual
Effectiveness of Sniffer Using Natural Language in Learning Computer Network Traffic

Computer networks are currently very active in the development of technology that is around us. Seeing this, of course knowledge of the network will be needed if there is a problem on the network. Scapy is a Python module that allows for sending, sniffing and dissecting a packet on a network. This capability allows users to create an application that can dissect how the workings of a network packet. Researchers will create a protocol traffic learning application on a computer network using Scapy and natural language to convey the results of the ongoing sniffing process. The application uses natural language to convey the translation of the sniffing process. The translation result of the sniffing process by using the natural language of this application is expected to be effective and can facilitate and make users understand and learn about the work process of a network packet. To measure the effectiveness of the use of natural language for the translation of the sniffing process a questionnaire was distributed to students of the SMKN 1 Denpasar school majoring in Computer and Network Engineering. The results of the distribution of the questionnaire were then calculated using a Likert scale and then the results obtained that the original results of the sniffing process got a Likert scale value of 37%. While the results of sniffing that have been translated get a value of 73%. This shows respondent better understands the results that have been translated compared to the original results that have not been translated. &#x0D;
Optimal multiclass overfitting by sequence reconstruction from Hamming queries

A primary concern of excessive reuse of test datasets in machine learning is that it can lead to overfitting. Multiclass classification was recently shown to be more resistant to overfitting than binary classification. In an open problem of COLT 2019, Feldman, Frostig, and Hardt ask to characterize the dependence of the amount of overfitting bias with the number of classes $m$, the number of accuracy queries $k$, and the number of examples in the dataset $n$. We resolve this problem and determine the amount of overfitting possible in multi-class classification. We provide computationally efficient algorithms that achieve overfitting bias of $\tilde{\Theta}(\max\{\sqrt{{k}/{(mn)}}, k/n\})$, matching the known upper bounds.
Face Feature point detection using hybrid method

A Facial Feature point analysis and face feature categorization is essentialprocedure in face recognition and facial emotion recognition. Facial emotionrecognition is utilized in security systems, government application, academic applications. Currently, facial emotion recognition system identifiesdifferentexpressions from face like happy, sad, disgust, neutral, angry, fear, surprise and contempt. This facial emotion recognition technique used forhugesizeinformationcollectioncapturedbelow independent lightning conditionsand different emotions of face. The suggested facial emotion recognitionsystem exists hybridization of Histogram of Gradient (HOG), Local Binary Pattern (LBP), Gabor Wavelet feature (GFeature), and Discrete CosineTransform (DCT) for facial key point identification. Facial key points are extracted using this hybrid method. The proposed method uses the kaggledataset which has 3,386 sample images of 1,711 people having eight expression of each person with variation is facial emotions. Using this database, weare extracting 157 feature points and we will extract some important features among them for further classification. The performance of feature pointdetection is achieving good using this hybrid method.
A STEGANOGRAPHY TECHNIQUE BASED ON MULTIPLE-IMAGE INTERFERENCE

Steganography is the science of camouflaging message, video, image or any other data within another file, which can be any multimedia file.The purpose of this technique is to hide the existence of the message in cover file from unauthorized party.It takes the advantages of limited perception of human to observe subtle changes in images, sound etc.Here our concern is about digital images as they are more frequent over the internet.In spy/hacker world Steganography and Cryptography are cousins.Cryptography alters a message so it cannot be understood whereas Steganography hides the message so that it cannot be read.An approach for Steganography Technique Based on multipleimage Interference and position multiplexing is proposed based on the interference principle.
You should lead a session on running ...

You should lead a session on running and personal websites at @IndieWebCamp this weekend. I have been trying to do this myself but I am
Author Correction: Search and rescue at sea aided by hidden flow structures

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Google has nest. Amazon has Echo and Alexa. Savant systems Has—GE lighting! The luxury home-automation company has its sights set on high-quality mass-market home networking - [Spectral Lines]

IF YOU WERE TRYING TO IDENTIFY THE HANDFUL of companies that created a business out of the emergence of electrical engineering in the Victorian era, certainly the list would have to include General Electric. GE's lighting business was established by Thomas Edison in 1892, and it was just sold to engineering wunderkind Robert Madonna and his team at Savant Systems, in Hyannis, Mass. Savant builds high-end home-networking systems for the well-heeled.
Knowledge and Participation: Empowering Indian Urban Poor for Accessing Public Services

The paper focusses on three aspects of our work with the urban poor: utilization of participatory research methodologies to elicit local knowledge in forms that do not require traditional education; building capacities to create active organized citizenry through catalysing Settlement Improvement Committees, which are representative bodies (involving youth, women and men) of the urban poor aimed at advocating interests of the community, and planning for collective positive action; and enabling communities and their organizations to utilize technology-enabled mobile surveys to collect their own data, leading to the demystification of technology and allowing for utilization of data for planning (for individual and community-level action), monitoring the implementation of these plans, as well as seeking access to services from state actors. This paper was presented in an International Research Symposium on “Other ways of knowing and doing”, organized by the O.P Jindal Global University. The symposium was an opportunity to discuss the utilization of technology combined with participatory methods for the production of knowledge, and catalyzing social change actions by the urban poor in selected Indian cities.
Penerapan Modeling Instruction Dan Simulasi PhET Dalam Meningkatkan Kemampuan Menganalisis

This study aims to determine the increase in students' ability to analyze by applying modeling instruction and simulation media PhET. The research method used is a quasi experimental method with one group pretest posttest design. In this study, samples were taken as many as 33 people. The instrument used in the study was a multiple choice test. This test consists of 5 questions in the analyze category. Data analysis in this study used the Gain Normality Test. From the calculation results obtained an average value of N-gain of 0.7, it can be concluded that the application of modeling instruction and simulation media PhET can improve the ability to analyze students. DOI: 10.29408/kpj.v4i1.1820
Szakértői heurisztika alkalmazása a FRIQ-learning megerősítéses tanulási módszerben

The paper introduces expert knowledge as a priori heuristic application and its effect on the FRIQ-learning methodology. In general, the reinforcement learning methods, like the FRIQ-learning system, start with an empty knowledge base then the system builds the final knowledge base incrementally by the properly defined reward function. The main goal of the paper is to introduce the new developed version of the FRIQ-learning. In this case, the system starts the learning phase with not an empty knowledgebase but with an expert-defined, a priori knowledgebase. The introduced methodology is suitable for adapt expert knowledge in the FRIQ-learning system. Furthermore, the expert knowledge adaptation and its effect on the system are also discussed in the paper through the „mountain car” application example.