Reviewerly/exHarmony huggingface dataset:
On the Nature of Fault Slip: From the Field to the Lab

&amp;lt;p&amp;gt;Modern geophysics highlights that the slip behaviour response of faults is variable in space and time and can result in slow or fast ruptures. Despite geodetical, seismological, experimental and field observations, the origin of this variation of the rupture velocity in nature, as well as the physics behind it, is still debated. Here, we first discuss the scaling relationships existing for the different types of fault slip observed in nature and we highlight how they appear to stem from the same physical mechanism. Second, we reproduce at the scale of the laboratory the complete spectrum of rupture velocities observed in nature. Our results show that when the nucleation length is within the fault length, the rupture velocity can range from a few millimetres to kilometres per second, depending on the available energy at the onset of slip. Our results are analysed in the framework of linear elastic fracture mechanics and highlight that the nature of seismicity is governed mostly by the initial stress level along the faults. Our results reveal that faults presenting similar frictional properties can rupture at both slow and fast rupture velocities. This combined set of field and experimental observations bring a new explanation of the dominance of slow rupture fronts in the shallow part of the crust and in areas presenting large fluid pressure, where initial stresses are expected to remain relatively low during the seismic cycle.&amp;lt;/p&amp;gt;
Gradual Semantics for Logic-Based Bipolar Graphs Using T-(Co)norms

In this paper we consider a bipolar graph structure encoding conflicting knowledge with logic formulas. Gradual semantics provide a way to assign strength values in the unit interval to nodes (i.e. logical inference steps) in the bipolar graph. Here, we introduce a new class of semantics based on the notions of T-norms and T-conorms and show that they handle circular reasoning and satisfy desirable properties such as provability and rewriting.
Comparative Analysis of Various Techniques Used to Obtain a Suitable Summary of the Document

An efficient summarizer that generates an appropriate summary of the document is the need of the hour. There are various models available for an extractive summary of a document. However, it has been observed that a comparative analysis of various techniques used, while obtaining a suitable summary of the text has been done rarely. So in this paper, a comparative analysis of different techniques used at different stages of obtaining a summary of the dataset provided was done. The paper discusses suitable combinations of the different techniques which can be used to obtain an effective summary for a given dataset. In order to carry out the main objective of comparative analysis for summarization techniques, four different sentence representations and three different similarity measures were used along with the K-means algorithm and cluster formation method.
Painting Outside as Inside: Edge Guided Image Outpainting via Bidirectional Rearrangement with Progressive Step Learning

Image outpainting is a very intriguing problem as the outside of a given image can be continuously filled by considering as the context of the image. This task has two main challenges. The first is to maintain the spatial consistency in contents of generated regions and the original input. The second is to generate a high-quality large image with a small amount of adjacent information. Conventional image outpainting methods generate inconsistent, blurry, and repeated pixels. To alleviate the difficulty of an outpainting problem, we propose a novel image outpainting method using bidirectional boundary region rearrangement. We rearrange the image to benefit from the image inpainting task by reflecting more directional information. The bidirectional boundary region rearrangement enables the generation of the missing region using bidirectional information similar to that of the image inpainting task, thereby generating the higher quality than the conventional methods using unidirectional information. Moreover, we use the edge map generator that considers images as original input with structural information and hallucinates the edges of unknown regions to generate the image. Our proposed method is compared with other state-of-the-art outpainting and inpainting methods both qualitatively and quantitatively. We further compared and evaluated them using BRISQUE, one of the No-Reference image quality assessment (IQA) metrics, to evaluate the naturalness of the output. The experimental results demonstrate that our method outperforms other methods and generates new images with 360{\deg}panoramic characteristics.
Novel Content Aware Pixel Abstraction for Image Semantic Segmentation

Image semantic segmentation is one of the recently researched topics due to the rise in visual deep learning-based applications. These applications work on the meaningful segments of the visual scene created by the application base. The literature identifies the current research status and highlights the existing problems of image semantic segmentation algorithms. These problems include the handling of complex images. Complex images can be of form high/low pixel intensities or dense structure regions of the image. Existing state-of-the-art deep learning algorithms fail to segment complex images semantically. For semantic segmentation of complex images, deep learning algorithms are proposed to be accompanied by pixel abstraction algorithm. The pixel abstraction algorithm creates atomic segments of the visual scene called super-pixels.  Super-pixels generate feature vectors supporting the same regions. These feature vectors reduce the computational complexity to create semantic segments of the visual scene. The pixel abstraction algorithms lack functionality due to different aspects, one of which is the initial hand-crafted seed from the user to create super-pixels that do not work for all types of visual scenarios to create accurate semantic segments. The second aspect that limits pixel abstraction algorithms' functionality is the distance measure used for super-pixel (cluster) creation. The distance measures employed in existing algorithms do not capture content-aware information of visual scene; instead, end-up creating super-pixels based on Euclidean distance, which is based on straight line distance. Hence, the created pixels are distorted and irregular. For proving the flawed functionality of the existing super-pixel creation algorithm, detailed visual analysis is presented, uncovering the indicators for future research towards the development of a novel algorithm creating continuous and regular super-pixels. For creating content-aware super-pixels, the article describes an automatic super-pixel creation algorithm based on the idea of capturing image information in relevance to the content present in it. For example, we illustrate the proposed framework in detail as two modular approaches to improve the resulting super-pixels' quality. Firstly, to automate the entire process, the probability density function is proposed to initialize the cluster centers such that hand-crafted seed is not required from the user. Secondly, to retrieve fine-grained object boundaries, a novel distance measure with induced content-aware nature and complex image handling is proposed. The novel algorithm has the potential to tackle the problem of discontinuity and irregularity of retrieved segment boundaries. Keywords:  Super-Pixels, Simple Linear Iterative Clustering, Distance Measures.
Panduan Alih Media Karya Tugas Akhir Teknik Mesin Menggunakan Aplikasi Nitro Pro 8

AbstractTransfer of media to digital format is an alternative choice to preserve the information content of library materials, because this format can be stored on relatively large capacity and durable storage media. In making this Media Transfer guide the Nitro Pro 8 application is used. The reason is that it is easier in the process of transferring information from word to pdf, as well as the availability of various menu options used to support the transfer process. Nitro Pro 8 itself is a software that we can use to read, create, edit and share PDF files. Nitro Pro allows us to process the batch file to convert documents to pdf. Nitro Pro is often called Nitro Pro PDF, which means a very good software for handling PDF files.Keywords: transfer, digital, Nitro Pro 8, library
FAIR access to soil and agricultural research data: The BonaRes Data Repository

&amp;lt;p&amp;gt;In the frame of the joint research project BonaRes (&amp;amp;#8220;Soil as a sustainable resource for the bioeconomy&amp;amp;#8221;, bonares.de) a data repository was set-up to upload, manage, and provide soil-, agricultural- and accompanying environmental research data. Research data are stored consistent and based on open and widely used standards within the repository over the long-term. Data visibility as well as its accessibility, reusability, and interoperability with international data infrastructures is fostered by rich description with standardized metadata and DOI allocation.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The specially developed metadata schema combines all elements from DataCite and INSPIRE. Metadata are entered by an online metadata editor and include thesauri (AGROVOC, GEMET), use licenses (Creative Commons: CC-BY for research data, CC-0 for metadata), lineage elements and data access points (geodata portal with OGC services). The repository meets thus the needs of the FAIR principles for research data.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this paper we present and discuss functionalities and elements of the BonaRes Data Repository, show a typical data workflow from data owner to data (re-)user, demonstrate data accessibility and citeability, and introduce to central data policy elements, e.g. embargo times and licenses. Finally we provide an outlook of the planned integration and linkage with other soil-agricultural repositories within a government-funded comprehensive national research data infrastructure NFDI (NFDI4Agri, Germany).&amp;lt;/p&amp;gt;
Securing Election Infrastructure with Hand-Marked Paper Ballots

American democracy is critically threatened by the use of insecure voting systems. Many existing electronic voting machines have malfunctioned during recent elections, and many are also vulnerable to hacking (Appel et al. 2019, Blaze et al. 2019, Blaze 2020). Most states have switched to secure, hand-marked paper ballots, but roughly 30% of Americans will continue to vote using vulnerable voting machines in 2020 (Cordova et al. 2019, Bajak 2020). While Congress allocated $380 million in 2018 and $425 million in 2020 to improve election security, these funds were neither targeted at nor sufficient for replacing all electronic voting machines. We propose that Congress (1) allocate $110 million exclusively for transitioning away from electronic voting machines and (2) prohibit the use of federal funds for purchasing voting systems that do not primarily use hand-marked paper ballots. This one-time transition cost is much smaller than even annual expenditures on other critical infrastructure (Copeland 2010; Halderman 2019). Replacing electronic voting machines with hand-marked paper ballots is the most affordable and secure option.
MGD-GAN: Text-to-Pedestrian generation through Multi-Grained Discrimination

In this paper, we investigate the problem of text-to-pedestrian synthesis, which has many potential applications in art, design, and video surveillance. Existing methods for text-to-bird/flower synthesis are still far from solving this fine-grained image generation problem, due to the complex structure and heterogeneous appearance that the pedestrians naturally take on. To this end, we propose the Multi-Grained Discrimination enhanced Generative Adversarial Network, that capitalizes a human-part-based Discriminator (HPD) and a self-cross-attended (SCA) global Discriminator in order to capture the coherence of the complex body structure. A fined-grained word-level attention mechanism is employed in the HPD module to enforce diversified appearance and vivid details. In addition, two pedestrian generation metrics, named Pose Score and Pose Variance, are devised to evaluate the generation quality and diversity, respectively. We conduct extensive experiments and ablation studies on the caption-annotated pedestrian dataset, CUHK Person Description Dataset. The substantial improvement over the various metrics demonstrates the efficacy of MGD-GAN on the text-to-pedestrian synthesis scenario.
GUIDING QUESTIONS TECHNIQUE TO IMPROVE STUDENTS’ WRITING SKILLS: RECOUNT TEXT

This research aimed to find out whether there was an improvement of the students’ skills in writing recount text after using guiding questions as a technique of writing. The method applied in this research was a quantitative method which use one group pre-test and post-test design. Random group sampling is used as the technique in taking a sample. Afterthat, the researcher took one class consist of 31 of second grade students as research participants. This research was held in 6 meetings involved pre-test, four meetings for treatment, and post-test. The instrument of data collecting was a written test. In analyzing the data, the researcher used SPSS v.16 and t-test.
Regional Educational Space and the Regional Education System: the Relationship of Concepts

The article deals with the study of regional characteristics of education. The purpose of the research is to clarify the categories of “regional educational space” and “regional system of education”, as well as to determine their relationship. The main research method is the analysis of scientific and pedagogical literature on the problem. The author proposes to consider pedagogical regionalology as a scientific and theoretical basis for a comprehensive study of the education of the regions. Pedagogical regionology is presented as a direction integrating pedagogical, socio-philosophical and socio-psychological, geographical, historical, socio-economic aspects of studying the system of education. The definitions of the concepts “regional educational space” and “regional education system” are clarified, their interconnections and correlations are revealed. Тhe author concludes that these concepts are close and related, but not identical. The regional educational space is widely considered as the totality of all natural, socio-economic characteristics of the territory in their relationship with education. The regional system of education is presented as a component of the educational space of the region, which has a regulatory status and institutional organization. The structure of the regional system of education is presented from the standpoint of a functional approach. It is concluded that the socio-economic characteristics of the region affect the regional system of education, and education system, in turn, changes the territorial organization of public life.
Construction of Management Information System for Small and Medium-Sized Enterprises under Cloud Computing Environment

In China, with the continuous advance of cloud computing technologies such as virtualization technology and big data processing technology, small and medium-sized enterprises are constantly updating and improving their management information system. In recent years, computer network technology and information technology have been gradually applied to enterprise management. With the development of enterprises, a large number of heterogeneous software services deployed on different servers are accumulated in enterprises. Cloud computing can not only reduce the cost of informatization construction of small and medium-sized enterprises, strengthen the integration of information resources, promote resource sharing, but also promote enterprise management and service innovation. In view of the development of social economy and the advance of the industry, if the enterprise wants to be better based on the market, it must realize the scientific management mode, and constantly improve the efficiency and quality of work. Through the cloud computing model, this paper introduces the system construction of the management information system for small and medium-sized enterprises in the cloud computing environment and the implementation scheme of enterprises in the cloud computing environment.
Sensitivitas Sistem Pencarian Artikel Bahasa Indonesia Menggunakan Metode n-gram Dan Tanimoto Cosine

The human need for technology and the availability of adequate infrastructure is evidence that technology is now a part of basic human needs. The increasing number of journals and scientific papers, it must be more selective in selecting and sorting even though there are already many online service providers and journal portals. Research on search engines and plagiarism and recommendation systems has been carried out with various methods deemed appropriate to improve the performance of the system itself, this paper has the purpose of calculating the similarity between one article with another article by implementing n-gram and tanimoto cosine. The number of articles tested was forty-three titles and abstracts, tested fifty times with randomly selected keywords, by breaking down each title and abstract sentence into n characters (n = 2 to 8) including spaces and punctuation, then counted similarity with the query or keyword used for system testing. The test was conducted using several threshold variations from n = 2 to 8. After observing fifty times the threshold test of 0.15 has the highest accuracy at n = 4 at 0.92, the highest precision at n = 3 at 0.42 and the highest recall at the test n = 2 = 0.44 .
Neural Topic Modeling by Incorporating Document Relationship Graph

Graph Neural Networks (GNNs) that capture the relationships between graph nodes via message passing have been a hot research direction in the natural language processing community. In this paper, we propose Graph Topic Model (GTM), a GNN based neural topic model that represents a corpus as a document relationship graph. Documents and words in the corpus become nodes in the graph and are connected based on document-word co-occurrences. By introducing the graph structure, the relationships between documents are established through their shared words and thus the topical representation of a document is enriched by aggregating information from its neighboring nodes using graph convolution. Extensive experiments on three datasets were conducted and the results demonstrate the effectiveness of the proposed approach.
THE EFFECT OF USING QUESTION AND ANSWER RELATION-SHIP (QAR) STRATEGY ON READING COMPREHENSION

Problem in this research is how to improve reading comprehension by using Question and Answer Relationship (QAR) strategy at the X Grade of SMA Negeri 1 Batangtoru. Thus, the objective of this research is to know if there is any significant effect of using Question and Answer Relationship (QAR) strategy to students’ reading comprehension at the X grade of SMA Negeri 1 Batangtoru. Experimental research method is the research method that is used by the researcher to conduct this research. Population  of this research was the X students of SMA Negeri 1 Batangtoru, namely 151 students while for tecnique of taking the sampling by using cluster sampling that is 36. The instrument of this research is test about reading comprehension.Based on the data that has been analyzed, it can be found that (1) the students’ achievement in reading comprehension by  using Question and Answer Relationship (QAR) strategy) at the X grade of SMA Negeri 1 Batangtoru is “enough” (69.72), (2) their value before  using Question and Answer Relationship (QAR) strategy at the X grade of SMA Negeri 1 Batangtoru can be categorized “enough” (61.94), and (3) there was a significant effect of using Question and Answer Relationship (QAR) strategy on reading comprehension at the X Grade of SMA Negeri 1 Batangtoru. It meant that the hypothesis was accepted.
Development of a Common Syllabus and Educational Video Materials for “Chemical Engineering” by Collaboration Project of National Institute of Technology (KOSEN) in Chugoku-Shikoku Region

Four schools of National Institute of Technology (KOSEN) in Chugoku-Shikoku region have collaborated to develop a common syllabus for “Chemical Engineering” and educational video materials. The teaching materials were prepared for each unit and used for preparation, review and classes. This article reports on the results of lessons using the video materials.
Matrix Encryption Standard

AES (Advanced Encryption Standard) is a standard for encrypting electronic data. AES operates on a column-major order array of bytes. The operations in the matrix are also performed on the polynomials in a special finite field and using S-box. We firstly recall necessary information about matrix algebra. In the present work, we examine the AES encryption method. We create a new encryption algorithm called matrix encryption standard (MES). MES is performed by similar steps to the AES algorithm over 16x16 matrices with elements {0,1} without using polynomials operations and S-box in the AES algorithm. So, we provide 256-bits plain text to be encrypted by passing it through certain rounds with the 16x16 matrix key. In order to decrypt the cipher text, we take the reverse of the 16x16 key matrix through the computer and perform the decryption process by performing a certain number of reverse rounds.
Research on the evaluation model of college English teaching based on The Data mining technology

The teaching evaluation refers to the process of teaching quality evaluation. With the continuousinnovation of college English teaching methods, the issue of improving the quality of the college Englishteaching has attracted more and more attention. In view of the quality , colleges in China should establish aquality guarantee system for teaching, which will mainly be used to improve the teaching methods and promote the teaching quality by finding out the problems in teaching through the evaluation of the teaching system. In the evaluation system based on The Data mining(DM) technology, the quality is excavated and analysed in a targeted way, and the problem factors influencing the quality are found out in a large number ofdata, so as to improve the teaching methods and improve the quality of college English teaching.
THE INFLUENCE OF THE PRINCIPAL COMPONENT ANALYSIS OF TEXTURE FEATURES ON THE CLASSIFICATION QUALITY OF SPONGE TISSUE IMAGES

The aim of this article was to determine the effect of principal component analysis on the results of classification of spongy tissue images. Four hundred computed tomography images of the spine (L1 vertebra) were used for the analyses. The images were from fifty healthy patients and fifty patients diagnosed with osteoporosis. The obtained tissue image samples with a size of 50x50 pixels were subjected to texture analysis. As a result, feature descriptors based on a grey level histogram, gradient matrix, RL matrix, event matrix, autoregressive model and wavelet transform were obtained. The results obtained were ranked in importance from the most important to the least important. The first fifty features from the ranking were used for further experiments. The data were subjected to the principal component analysis, which resulted in a set of six new features. Subsequently, both sets (50 and 6 traits) were classified using five different methods: naive Bayesian classifier, multilayer perceptrons, Hoeffding Tree, 1-Nearest Neighbour and Random Forest. The best results were obtained for data on which principal components analysis was performed and classified using 1-Nearest Neighbour. Such an algorithm of procedure allowed to obtain a high value of TPR and PPV parameters, equal to 97.5%. In the case of other classifiers, the use of principal component analysis worsened the results by an average of 2%.