Reviewerly/exHarmony huggingface dataset:
Statewide Mapping of Mineral Hazards in California – A Model for Multiple Applications

Mineral hazards are a common, yet often less-recognized group of features compared to other types of natural and man-made hazards. We define “mineral hazards” in part as minerals and elements that occur naturally in elevated, potentially harmful, concentrations in rocks, soils, and certain fluids. Also included are features from human activities related to extraction of mineral and energy resources. Along with its large human population, extensive development, and diverse natural environment, California is very complex geologically, thus it contains many areas of mineral hazards that make it appropriate for such a study. Although mineral hazards have been investigated over several decades by the California Geological Survey (CGS), no systematic statewide assessment had been accomplished until recently when, at the request of the California Department of Transportation (Caltrans), the CGS completed a preliminary assessment of potential mineral hazards over the entire state. This work focused on natural and man-made minerals-related features that might adversely affect construction, use, and maintenance of state and federal highways under Caltrans jurisdiction. The features evaluated include: 1) geologic units that may contain naturally-occurring asbestos (NOA), fibrous erionite, or elevated concentrations of regulated metals (Ag, Ba, Be, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Tl, V, Zn) and metalloids (As, Sb, Se); 2) faults, which can be sites of increased potential for certain types of mineralization; 3) mines and prospects, which can be sources of anomalous concentrations of metals and ore-processing chemicals; 4) oil and natural-gas seeps; 5) thermal springs and fumaroles; and 6) oil, natural-gas, and geothermal wells. The methods and products developed during the Caltrans study can be applied worldwide to many other uses besides highways where there are obligations to protect public health and safety and the environment. The products include maps that highlight types and locations of potential mineral hazards, digital data in GIS format, and accompanying reports that provide details and additional information. Although they do not indicate risk or probability, these products can be applied by users from many backgrounds as screening tools to assess potential for the presence of mineral hazards.
Constrained Spectral Clustering Network with Self-Training

Deep spectral clustering networks have shown their superiorities due to the integration of feature learning and cluster assignment, and the ability to deal with non-convex clusters. Nevertheless, deep spectral clustering is still an ill-posed problem. Specifically, the affinity learned by the most remarkable SpectralNet is not guaranteed to be consistent with local invariance and thus hurts the final clustering performance. In this paper, we propose a novel framework of Constrained Spectral Clustering Network (CSCN) by incorporating pairwise constraints and clustering oriented fine-tuning to deal with the ill-posedness. To the best of our knowledge, this is the first constrained deep spectral clustering method. Another advantage of CSCN over existing constrained deep clustering networks is that it propagates pairwise constraints throughout the entire dataset. In addition, we design a clustering oriented loss by self-training to simultaneously finetune feature representations and perform cluster assignments, which further improve the quality of clustering. Extensive experiments on benchmark datasets demonstrate that our approach outperforms the state-of-the-art clustering methods.
The Role of Equity on the Relationship between Job Evaluation and Employee Performance in Jordan Industrial Estates

This study aimed to assess the extent of the mediation effect of equity on the relationship between job evaluation and employee performance. A self-administrated questionnaire was used to collect data from 646 employees working in the targeted industrial estates. The collected data was analysed using SPSS and AMOS software tools based on structural equation modelling (SEM). The results of the study indicated to a non-significant relationship between job evaluation and job performance. On the other hand, a significant relationship was found between equity and job performance as well as between job evaluation and equity. Moreover, the results of the study demonstrated a mediation role of equity on the relationship between job evaluation and job performance. The results of this study are expected to have a significant influence in filling the gap in the literature and enhancing employees' performance accordingly.
Bertinho: Galician BERT Representations

This paper presents a monolingual BERT model for Galician. We follow the recent trend that shows that it is feasible to build robust monolingual BERT models even for relatively low-resource languages, while performing better than the well-known official multilingual BERT (mBERT). More particularly, we release two monolingual Galician BERT models, built using 6 and 12 transformer layers, respectively; trained with limited resources (~45 million tokens on a single GPU of 24GB). We then provide an exhaustive evaluation on a number of tasks such as POS-tagging, dependency parsing and named entity recognition. For this purpose, all these tasks are cast in a pure sequence labeling setup in order to run BERT without the need to include any additional layers on top of it (we only use an output classification layer to map the contextualized representations into the predicted label). The experiments show that our models, especially the 12-layer one, outperform the results of mBERT in most tasks.
Battlefield Perception Data Fusion Based on Knowledge Graphs

The modern information wars demand higher efficiency in decision-making and response, and the efficiency in understanding the battlefield perception data becomes the key to the success and failure of combat squads. Based on the knowledge graph technology, to meet the needs for battlefield perception data fusion, this paper designs a battlefield perception data fusion system based on knowledge graphs and designs the functional modules of the system to provide a technical basis for combat squads to respond quickly to the battlefield.
ANALISIS KESALAHAN MORFOLOGI DALAM KARANGAN NARASI BERDASARKAN CERITA FANTASI IRISAN PADA SISWA KELAS VII SMP NEGERI 1 BANDAR LAMPUNG

The purpose of this study was to find out and describe morphological errors in terms of writing narrative essays based on sliced ​​fantasy stories, especially in the use of affixation, reduplication and combination of words. To achieve the objectives of the study, a qualitative descriptive method was used, which was presented in the form of words with a model of morphological error data, discussed its errors and carried out repairs but still by presenting numerical data as needed. The results showed that VII grade students of Odd Semester 1 Bandar Lampung Middle School 2018/2019 Academic Year had not been able to use affixes correctly, as well as writing reduplication and writing of combined words. This is seen from the results of narrative essays based on sliced ​​fantasy stories, the researchers analyzed morphological errors which were limited only to the use of affixation, reduplication and combination of words. In the misuse of affixation there are 44 errors that indicate that the percentage calculation results reached 54.32%, which means the level of mastery is lacking. As with the use of reduplication, there were 31 errors which showed that the percentage of mastery was less than 38.27%. Whereas, the percentage of errors in the use of word combinations shows 7.40% or in the level of mastery enough that there are 6 errors.
Quantum computing

Quantum computing offers the potential for compelling performance improvement on important high performance computing applications such as the simulation of materials and chemical systems. In constructing a full-stack quantum computing system, there are many interdisciplinary research questions that cross the boundaries between physics, engineering and computer architecture. This talk will describe the promise and challenges of bringing quantum computing out of the lab and into a commercial full computer system and will give an overview of Intel's quantum computing research and system development.
LibGuides: Cataloging Toolbox for International Government Information: Help/Contact

Cataloging, classification and subject vocabularies used in creating metadata description for International Governmental Organizations.
Simulation of Physics in Python

Physics is the study of objects, motion, dynamics, kinematics where the students have to learn difficult formulas. Projectile fly without air resistance swings at specific angles, orbits are always circular, and no more than two particles move together at any same time. These are the main aspects of physics because you are trying to learn the basic laws of nature. As compared to the real world it is far more complicated to study, students have to learn these laws and have to apply them to complex problems. In modern advances, computers make it possible to perform extremely lengthy and complex calculations in a negligible amount of time and period. These days, computers offer the best method for applying the basic laws of nature to complex and realistic physical systems. Using a computer program for simulations plays a crucial part in modern science and engineering. A program that simulates the model of the behavior of a physical system is called Computer Simulation.
An Analysis on Gender Classification using Face Images Using DWT, (2D)2PCA and SVM

Abstract Classifying gender compared to others and is used in this work. Biometry is the use of physical characteristics like face, fingerprints, iris, etc. of an individual for personal identification. Some of the difficult issues of face biometrics are face detection, face recognition, and face identification. These problems are being researched by the computer vision community for the last few decades. Considering the big population, the authentication process of an individual usually consumes a significant amount of time. One of the attainable solutions is to divide the population into two halves supported gender. This will facilitate to scale back the search area of authentication to nearly half the present information and save substantial quantity of your time. Gender identification through face demands use of sturdy discriminative options and strong classifiers to separate the feminine and male faces with no ambiguity. In this thesis, an investigation has been created on gender classification through facial pictures mistreatment principal part analysis ((2D) 2 PCA), and support vector machine (SVM). Principle Component Analysis (PCA) could be a spatial property reduction technique, which is used to represent each image as a feature vector in a low dimensional subspace. SVM could be a binary classifier that PCA is the input within the style of options and predicts which of the two attainable categories forms the output. Initially face region is extracted employing a planned complexion segmentation approach. The face region is then subjected to PCA for feature extraction that encodes second order statistics of information. These principal elements area unit fed as input to SVM for classification. Keywords: Biometrics, face detection, gender classification, (2D) 2 PCA, SVM
IMPROVING READING COMPREHENSION THROUGH STORY MAPPING STRATEGY

This research aims to prove whether or not theimplementation of story mapping strategy can improve reading comprehension of the eighth grade students of SMP Negeri 9 Palu. This research applied quasi-experimental research design in which the sample consisted of two groups which were experimental and control groups. The sample is selected by using cluster sampling technique whichconsisted of 30 students as experimental group and consisted of 30 students as control group. The experimental group was given treatment by applying story mapping strategy in teaching reading, while the control group was taught by using general way as the teacher applied. The instrument of data collection was a test. The result of the data analysis shows that there is a significant difference between the result in the pretest and the posttest. By applying 0.05 level of significance and 58 degree of freedom (df), the researcher found out that the value of t-counted is 5.11 and t-table is 1.672. The t-counted value was higher than the t-table value, which means that the research hypothesis is accepted. In other words, the implementation of story mapping strategy can improve reading comprehension of the eighth grade students of SMP Negeri 9 Palu. Keywords: Improving, Reading Comprehension, Story Mapping Strategy.
Chaos Blend LFSR—Duo Approach on FPGA for Medical Image Security

In recent years, encryption of medical images has been given much importance and several cryptographic algorithms and principles have been made and designed for secure communication. One such approach has been proposed in this work using pixel scrambling and diffusion techniques governed through linear feedback shift register (LFSR) and modified logistic map (MLM). The main advantage of this work is its concurrent encryption through which the scrambling and diffusion have been performed on the fly without any additional delays. The proposed design has been implemented on Intel Cyclone IV E FPGA using Quartus II Electronic Design Automation (EDA) tool. Further, the functional verification of LFSR and MLM has been carried out through ModelSim simulation. The design occupies 3580 logic elements and 135 logic registers to encrypt 256 × 256 × 16 bits of DICOM image at 216 mS when it was operated with 50 MHz frequency. Also, this work achieves near-zero correlation, and the statistical properties of the encryption have been tested through standard metrics.
Twitter Sentiment Analysis

The goal of tweet sentiment analysis is to find the positive, negative, or neutral sentiment part in the tweeter data. Sentiment analysis can help any organization to find people's opinions of their company and products. We have applied sentiment analysis on twitter data set. Our model takes input tweet, sentiment, and output selected text starting and ending in input tweet. We are using the BERT(Bidirectional Encoder Representations from Transformers) model with one more layer to find sentiment positions in tweets. The extra layer is used to find the sentiment part of a tweet. Our model is able to achieve 70 percent accuracy on the validation data set.
Correction to: Is it possible to disregard obsolete requirements? A family of experiments in software effort estimation

A correction to this paper has been published: https://doi.org/10.1007/s00766-021-00354-4
Pelatihan Penggunaan Aplikasi SILPPM Pada Lembaga Penelitian dan Pengabdian Kepada Masyarakat di Universitas Mohammad Husni Thamrin

In the midst of the lively development of information technology applications nowadays, it has a good impact from various aspects. There are several aspects that have been affected by the development of information technology applications, one of which is administration in an organization or institution. Therefore, on this occasion we will take advantage of information technology applications to support administration in data collection at the Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) at Universitas Mohammad Husni Thamrin (UMHT) so that it can be done using applications or programs. The application or Sistem Informasi Lembaga Penelitian dan Pengabdian kepada Masyarakat (SILPPM) is expected to improve LPPM's performance in terms of data collection for lecturers. In recording or collecting data in terms of activities related to LPPM such as research activities, publication of lecturers' articles, scientific works and others. To apply the SILPPM application to LPPM UMHT, socialization is needed to the user so that this application can be used properly. Therefore, it is necessary to hold this community service activity with the aim of disseminating the SILPPM application to admins or users of LPPM employees by providing training in accordance with the modules (manual books) that have been prepared in advance.
Using Dependency-Based Contextualization for transferring Passive Constructions from English to Spanish

We hypothesize that parallel corpora as well as machine translation outputs contain many literal translations that are the result of transferring the constructions of the source language to the target language. When translating passive expressions from English to Spanish, there are several constructions available, however, both automatic and human (if of low quality) translations tend to select the periphrastic structure, which is the literal construction. The objective of this article is to make use of strategies trained on monolingual corpora to translate English passive expressions into Spanish so as to verify whether unsupervised translation with monolingual corpora benefits syntactic diversity. Special attention will be given to the monolingual-based strategy relying on dependency-based contextualization. The results of the experiments carried out show that the methods relying on monolingual corpora tend to offer more non-literal translations (middle-voice) than those trained on parallel corpora.
Digital mock-up and voice of the customer in the context of physical product development

Software development requires urgency in its launch in the market. Based on this, Agile Project Management has been introduced to reduce the time gap between idea and product release. Several studies have been developed to combine the qualities of Agile Management with those of the traditional Project Management for the application in physical products. Based on these studies, the following question has arisen: how can digital mock-ups be used to implement a hybrid (agile combined with traditional) project management approach, with customer participation, for physical products? In the present research, a development case study on a car steering wheel was conducted using digital mock-ups and the customer's voice. The study was applied to an audience of approximately 500 people. Results show the possibility of using digital mock-ups as a support for the development of physical products through the hybrid approach. For the generalisation of the method, more research must be conducted using different products from different areas.
Special issue: Advanced Intelligent Computing Theory and Applications in Big Data Era

Depth cues with affluent spatial information have been proven beneficial in boosting salient object detection (SOD), while the depth quality directly affects the subsequent SOD performance. However, it is inevitable to obtain some low-quality depth cues due to thelimitations of its acquisition devices, which can inhibit the SOD performance. Besides, existing methods tend to combine RGB images and depth cues in a direct fusion or a simple fusion module, making them not effectively exploit the complex correlations between the two sources. Moreover, few methods design an appropriate module to fully fuse multi-level features, resulting in cross-level feature interaction insufficient. To address these issues, we propose a novel Multi-level Cross-modal Interaction Network (MCI-Net) for RGB-D based SOD. Our MCI-Net includes two key components: 1) a cross-modal feature learning network, which is used to learn the high-level features for the RGB images and depth cues, effectively enabling the correlations between the two sources to be exploited; and 2) a multi-level interactive integration network, which integrates multi-level cross-modal features to boost the SOD performance. Extensive experiments on six benchmark datasets demonstrate the superiority of our MCI-Net over 14 state-of-the-art methods, and validate the effectiveness of different components in our MCI-Net. More important, our MCI-Net significantly improves the SOD performance as well as has a higher FPS.
Complementary time-lapse datasets of x-ray computed tomography and real-time strain mapping for an ex-situ study of non-crimp glass fibre composites under fatigue loading

Data published in this paper corresponds to a time-lapse ex-situ experiment aimed at analyzing the tension-tension fatigue damage in non-crimp glass-epoxy composites by multi-scale x-ray computed tomography (XCT) of the damage features and their timeline. This is then correlated with the strain fields obtained through digital image correlation (DIC). The XCT - DIC datasets by is acquired by interrupting mechanical fatigue tests at three time-steps, after the material has undergone 0 cycles, 70,000 cycles, 80,000 cycles, and 120,000 cycles. This is one of the first multi-modally correlated datasets available for these types of non-crimp glass fibre composites, which explore the structure-property relationship in a time-dependent behavior. This dataset can be used to explore glass-fibre composites microstructure under a progressive damage scheme and can be used to test and train a plethora of image processing and analysis techniques. This dataset can also be used as an attempt to model the fatigue behavior of quasi-unidirectional non-crimp fibre composites by image-based simulations.
Distance Education in Times of COVID-19 in Mexico

The objective of the chapter is to assess distance education in times of COVID-19 through the implementation of the Virtual Plan for Academic Continuity of the Instituto Politécnico Nacional (IPN) in order to identify good educational practices at the postgraduate level. A quantitative methodology with an exploratory-descriptive scope was used. The participants of the study were students who were pursuing a graduate degree during confinement. The main results are a positive assessment of distance education in terms of the incorporation and continuous use of digital resources, the use of continuous evaluation, the usefulness of technological tools, as well as an interaction with the teaching staff to review the academic progress of the student.
LibGuides: Cataloging Toolbox for International Government Information: United Nations

Cataloging, classification and subject vocabularies used in creating metadata description for International Governmental Organizations.
Monetáris politikai kihívások a szubszaharai régióban

The monetary policy of the Sub-Saharan countries is a lesser-known field for those Hungarian readers who are interested in Africa. In the last few decades several fundamental changes took place so a short synthesis is badly needed to better understand this issue. Apart from the fact that this study tries to shed light on the monetary policy challenges of different periods, it also places much emphasis on the contemporary issues in central banking.After the turn of the new millenium the central banks have been struggling with unpredictable fiscal policies, the appropriate treatment of the revenues of the natural resources, not to mention the inflow of foreign aid. It is also highly important to monitor the frequency of the supply shocks and the efficiency of the monetary transmission mechanism. After shedding more light on these issues, the paper tries to focus on the role of the exchange rates, the room for manoeuvre of the central banks in the financial stability and the adequate management of the revenues stemming from the export of natural resources.