Reviewerly/exHarmony huggingface dataset:
DEWPython: A Python Implementation of the Deep Earth Water Model

There are two main methods of calculating the thermodynamic properties of water and solutes: mass action (including the Helgeson-Kirkham-Flowers (HKF) equations of state and model) and Gibbs free energy minimization (e.g.[1]).However, the HKF model has certain regions of pressure and temperature where it predicts the speciation and concentration of solutes inaccurately(e.g.[2]).The Deep Earth Water (DEW) model is a series of HKF-type equations used to calculate the properties of water and solute concentrations at high temperatures (373.15-1473 K) and pressures (100 -6,000 MPa) (e.g.[3]; [4]).The DEW model is synthesized in an Excel spreadsheet and calculates ΔG f , ΔV f , and equilibrium constants of reactions.We validate DEW water properties against SeaFreeze, which computes properties for water and ice polymorphs Ih, III, V and VI at 220-500K and 0 -2300 MPa [5], and solute properties against SUPCRT96 [6].Combining a different model for the properties of water alongside DEW could prove robust in determining the composition and properties of high-pressure fluids in icy ocean worlds such as Jupiter's moons Europa, Ganymede and Callisto, and Saturn's moon Titan.We present an object-oriented Python implementation of the DEW model, called DEWPython.Our model expands on DEW by increasing efficiency, streamlining and automating the input process, and incorporating SUPCRT in-line.We constructed DEWPython to allow for high-resolution grid calculations of both SUPCRT and DEW data, enabling robust new visualizations.Additionally, our model incorporates minerals and aqueous species from the thermodynamic database slop16.dat[7].We also present a set of reactions relevant to icy ocean world interiors calculated with the DEWPython and their likelihood of formation.
Mockery identification utilizing AI calculations and django

The extended reputation of online casual associations, spammer finds these stage viably accessible to catch customers in noxious activities by presenting Spam messages on thwart spammers google secure examining and twitter's bootmaker contraptions comprehend and rectangular spontaneous mail tweets. These techniques can square hazardous associations, in any case they can't make sure about the customer consistently as in front of timetable as would be reasonable. Subsequently, industry and researchers have applied different approach to manage develop spam free relational association arrange. Some Of them are essentially chosen client features on the indistinguishable time as others rely on tweet basically based features in a way. In any case there is no finished system that would solid have the alternative to tweet's substance data close to the client based highlights. To adapt to this issue we exhort a structure which takes the supporter and tweet based features along the tweet content material issue to establishment the tweets. The inspiration driving using tweet content component is that we can see the spam tweets whether or not the spammer make another record which was unrealistic just with the customer and tweet based features. We have surveyed our answer with different AI estimations specifically - SVM, Neural Network (NN), Random Forest and Gradient Boosting. With neural network we will achieve a precision of over ninety% and beat the slicing zone relationship through circular 1
Pengembangan Song, Word Map, Game dan Role Play dalam Pembelajaran Bahasa Inggris untuk Meningkatkan Speaking Skill dan Keterlibatan Siswa Kelas III SD Kristen Pelita Bangsa Lumajang

Abstract — Speaking skill is one of productive skill in English subject but most of the third graders of Pelita Bangsa Christian Primary School Lumajang had diffculties to develop and increase their speaking ability. The result of students’ speaking test showed only 54% of students had passed the minimum score and 62% of students engaged during the class. This classroom action research aimed to improve the students’ ability to speak English and their engagement through the development of song, word map, game and role play technique. The subjects in this study were thirteen students of third grade in Pelita Bangsa Christian PrimarySchool Lumajang by using Kemmis and Taggart model. It was implemented through two cycles and conducted from November 2013 until May 2014. The results of students’ speaking test showed that the development of song, word map, game and role play technique improved the students’ speaking skill up to minimum score from 54% (before CAR) to 69% in cycle 1 and to 84,6 % in cycle 2. While the students’ engagement had increased from 62% (before CAR) to 85% in cycle 2. In conclusion, the development of song, word map, game and role play technique improved speaking skill and engagement of the third graders of Pelita Bangsa Christian Primary School Lumajang.Keywords — song, word map, game dan role play, speaking skill
Performance analysis of local binary pattern and k-nearest neighbor on image classification of fingers leaves

The K-Nearest Neighbor (KNN) method is often used by researchers for the classification process because it has a relatively great level of accuracy, however it also has a weakness which is sensitive of the noises. This research is aims to introduce an object recognition (identification) system of fingers leaves by classified using the KNN method. To resolves the weaknesses of the KNN method, the researcher has used the Local Binary Pattern (LBP) method to extract features of the leaves. For the comparison in feature extraction, the researcher has used the Gray Level Co-Occurrence Matrix (GLCM) method. The data that were used on this research are papaya leaves and chaya leaves (with the labels such as good and damage forms). In this research, an experimental design has been carried out that was differentiated by according to the comparison (of ratio) between training data and testing data (NI/Np), there were 90 training data and 45 testing data, where the feature extraction method used the 10 of features. Experimentally, it was shown that by using the ratio NI/Np = 67%:33%, the performance or system performance for classifying the images of fingers leaves by using the LBP extraction method showed that training data was obtained the results close to 95% and testing data was obtained the results close to 76%, while by using the GLCM extraction showed that training data was obtained the results close to 83% and testing data was obtained the results close to 58%.
Beyond Accuracy: A Consolidated Tool for Visual Question Answering Benchmarking.

On the way towards general Visual Question Answering (VQA) systems that are able to answer arbitrary questions, the need arises for evaluation beyond single-metric leaderboards for specific datasets. To this end, we propose a browser-based benchmarking tool for researchers and challenge organizers, with an API for easy integration of new models and datasets to keep up with the fast-changing landscape of VQA. Our tool helps test generalization capabilities of models across multiple datasets, evaluating not just accuracy, but also performance in more realistic real-world scenarios such as robustness to input noise. Additionally, we include metrics that measure biases and uncertainty, to further explain model behavior. Interactive filtering facilitates discovery of problematic behavior, down to the data sample level. As proof of concept, we perform a case study on four models. We find that state-of-the-art VQA models are optimized for specific tasks or datasets, but fail to generalize even to other in-domain test sets, for example they can not recognize text in images. Our metrics allow us to quantify which image and question embeddings provide most robustness to a model. All code s publicly available.
Make this tango viral: Touching toward the untouchable in tele-synaesthesia performance

The COVID-19 pandemic has created an uncanny rift between tact and touch as it expands the virtual towards its potential. Layer upon layer of new information has been repeatedly revising and reformulating our sense of touch. The unconditional freedom of touch needs to be rendered accountable in this rift of time and space. The act of touching entails individual acknowledging the risk of reaching towards the unknown or the known. Tracing with a tactile sense of touch is to be tactful about how, where and what can such act of touching could reach, especially in the context of communicative technology. This article focuses on the possibility of virtual sensibility by challenging ways to feel touched beyond the nostalgic narratives that attempt to indict communicative technology with the loss of touch. To replenish and reinstate touch through tele-synaesthesia performance, I ask: how to elongate our somatosensensation and echo the embodied experience of touching through virtual connectivity? Tele-synaesthesia performance joints telematic and synaesthetic experience together to embody the incorporeality of touch through virtual connectivity. It embodies the injunction of physical contact and challenges what can and cannot be touched by suturing one sensuous modality to another. Inspired by Paul Sermon’s artistic production of Telematic Quarantine (2020) and Pandemic Encounters (2020), that tele-presents the stories of self (isolation), I have created The Best Facial (2021): a series of one-to-one participatory tele-synaesthesia performances, where I became a virtual aesthetician and performed ‘virtual facial care’ on Zoom amid the second wave of the pandemic in the United Kingdom. In this article, I will discuss how tele-synaesthesia performance could trigger tactile experiences in the participants in reference to Michel Foucault’s concept Heterotopia (1986) that allegorically address the incompatible physical places in the society. I discuss how to elicit an affective sensory response from non-tactile senses through virtual touch, as stated by Naomi Bennett’s ‘Telematic connections: sensing, feeling, being in space together’ (2020). I refer to Legacy Russell’s discussion on glitch (2020) to analyse the possible future of tele-synaesthesia performance and its potential for expanding virtual connectivity with an ethical touch of a non-performative refusal of the present.
LibGuides Home: Lyman Beecher Brooks Library Virtual Assistance (ENG 102.45A): Virtual Help

This guide will show you how to search for various library resources to support your assignment..  Click on one of the tabs below to get more information
Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces

Structured latent variables allow incorporating meaningful prior knowledge into deep learning models. However, learning with such variables remains challenging because of their discrete nature. Nowadays, the standard learning approach is to define a latent variable as a perturbed algorithm output and to use a differentiable surrogate for training. In general, the surrogate puts additional constraints on the model and inevitably leads to biased gradients. To alleviate these shortcomings, we extend the Gumbel-Max trick to define distributions over structured domains. We avoid the differentiable surrogates by leveraging the score function estimators for optimization. In particular, we highlight a family of recursive algorithms with a common feature we call stochastic invariant. The feature allows us to construct reliable gradient estimates and control variates without additional constraints on the model. In our experiments, we consider various structured latent variable models and achieve results competitive with relaxation-based counterparts.
Predicting Security-Vulnerable Developers Based on Their Techno-Behavioral Characteristics

Assigning developers for highly secured software projects requires identifying developers’ tendency to contribute towards vulnerable software codes called developer-centric security vulnerability to mitigate issues on human resource management, financial and project timelines. There are problems in assessing the previous codebases in evaluating the developer-centric security vulnerability level of each developer. Thus, this paper suggests a method to evaluate this through the techno-behavioral features of their previous projects. Consequently, we present results of an exploratory study of the developer-centric security vulnerability level prediction using a dataset of 1827 developers by logically selecting 13 techno-behavioral features. Our results depict that there is a correlation between techno-behavioral features and developer-centric security vulnerability with 89.46% accuracy. This model enables to predict developer-centric security vulnerability level of any developer if the required techno-behavioral features are available avoiding the analysis of his/her previous codebases.
SOCIETY SPEAKING CLUB SEBAGAI SARANA PENINGKATAN KEMAMPUAN KETERAMPILAN KOMUNIKASI BAHASA INGGRIS LISAN UNTUK MASYARAKAT

English oral communication proficiency is one of the absolute needs of adult learners in entering the digital industrialization era 4.0, where opportunities and competitions are more massive. Several limitations that are implemented as a response to the Covid-19 pandemic have made it difficult for most adult learners to practice their English communication skill intensively. This community service program aims to provide adult learners with the opportunities to practice English speaking skill through an interactive webinar and online group discussions. The Society Speaking Club was conducted in four meetings with the topics of mental health, diversity, environment, and entrepreneurship. The topics were selected so as to allow participants to relate the discussions to their life more easily, as well as to be more aware about the recent issues. This community service program has benefited the participants in a way that they became more confident and fluent in communicating their ideas effectively. In addition, the participants admitted that they got new insights on the issues being discussed, and they were called into actions for maintaining mental health, promoting and respecting diversity, preserving the environment, and developing entrepreneurial skills.
Mathematics education in the digital age - learning, practice and theory

Mathematics education in the digital age - learning, practice and theory, contains a collection of 12 chapters contributed by scholars who lay out a wide range of impacts that the digital age has h...
fBERT: A Neural Transformer for Identifying Offensive Content

Transformer-based models such as BERT, XLNET, and XLM-R have achieved state-of-the-art performance across various NLP tasks including the identification of offensive language and hate speech, an important problem in social media. In this paper, we present fBERT, a BERT model retrained on SOLID, the largest English offensive language identification corpus available with over 1.4 million offensive instances. We evaluate fBERT’s performance on identifying offensive content on multiple English datasets and we test several thresholds for selecting instances from SOLID. The fBERT model will be made freely available to the community.
Administrasi Sekolah: Tinjauan Administrasi Keuangan, Perlengkapan, Hubungan Sekolah dengan Masyarakat

Financial administration, equipment, school relations with the community are carried out in an effort to improve the quality of education in schools. The method used in writing this paper is qualitative by using a literature study, namely by finding and analyzing journals or reading sources related to the papers discussed. In implementing educational supervision, financial administration, completeness and relations between schools and the community must be considered. In addition, improving the relationship between the scope of the school and the relationship between the community also needs to be improved in order to form supervision in the world of education based on improving the quality of education in schools. In the supervision of education, it is necessary to have a model or strategy that is useful to increase the scope of the study. In this case, financial administration, equipment, school relations with the community are carried out in an effort to improve the quality of education in schools.
Hyperspectral imaging system for evaluating the stress field in digital photoelasticity

A limitation for developing real-time stress evaluation in digital photoelas- ticity relies on the multiple acquisitions required and complicated algorithms for fringe demodulation. This paper proposes a hyper-spectral imaging system as a solution of such drawbacks.
Impacto de la inteligencia emocional en la práctica profesional del primer semestre del 2021

During the situation unleashed by the arrival of Covid-19, humanity has had to adapt its life to the new biosecurity measures. One of the biggest changes has been the transition from presence-based modality to a remote environment. In this research, these relationships mediated by platforms were investigated in depth in the Social Communication practitioners of the first semester of 2021 in order to know if these changes had an impact on the Emotional Intelligence of the students.In favor of achieving the above, a theoretical compilation was made on the main competences that affect this topic. In order to compare and contrast opinions, an interview was carried out with the coordinator of the degree internship and a survey of 21 students who were part of the study population.Once the information collected in the aforementioned instruments had been analyzed, a series of recommendations were drawn up to the university and organizations to properly guide and accompany students in this new stage of their lives (remote modality).
TEACHERS SELF-DEVELOPMENT AS A CRITERION FOR INCREASING PROFESSIONAL COMPETENCE

This article examines the skill of teachers' self-development as a criterion for increasing professional competence. The article also examines the psychological qualities of a successful teacher, professional competencies that contribute to the achievement of results in pedagogical activities, the sociopsychological aspects of self-development of future teachers, the social activity of the teacher and the ability to effectively organize the educational process.
LibGuides: A LibGuide for ECE's: Statistics

Are you in the Early Childhood Education program at Algonquin College? Check out this guide for information to help you with your program!
EFL TEACHER'S STRATEGIES IN TEACHING SPEAKING AT MTS N 4 NGANJUK

ABSTRACTNihayah, Ullya I.P.N. Student Registered Number.17203163130.EFL Teacher’s Strategies in Teaching Speaking at MTs Negeri 4 Nganjuk. Sarjana Thesis.English education Department.Faculty of Tarbiah and Teacher Training. State Islamic Institute (IAIN) of Tulungagung. Advisor. Dr. Nurul Chojimah, M.Pd. Keywords: EFL Teacher, Strategies, Teaching Speaking Speaking is one of the elementof communication”. It shows that one of effective skills of doing communication is speaking. Besides, speaking is one of the important skills that must be mastered by all English students. In mastering speaking skill, there is some elements that influence it. One of element is teacher’s strategies. Students will master this skill also because of EFL Teacher’s teaching process. Based on that statement, EFL Teachers also must have strategies to develop their students’ speaking. That is why, studying how EFL Teacher strategies in teaching speaking was interesting. The formulation of the research problem were: 1) what are strategies used by the EFLteacher in teaching speaking at MTS N 4 Nganjuk? 2) how are the students responses to the teacher strategies implemented in teaching speaking at MTS N 4 Nganjuk? The purposes of this research were: 1) to describe the strategies which are used by EFL teacher in teaching speaking at MTS N 4 Nganjuk, 2) to describe the students’ responses toward the strategies which are used by English Teacher. The research method: 1) the research design of this study was descriptive design with qualitative approach, 2) data source of the research was EFL teachers as the subject, students as informant and related documentation, 3) the method of collecting data was observation and interview, 4) technique of verification was triangulation methodologically and triangulation sources, 5) technique of data analysis was technical data anlysis and general data analysis. The result of this research showed that the strategies in teaching speaking are conversation and discussion strategy. This strategies used to increase and develop students in expressing their opinion and consideration. Besides, this strategy also used to develop their self confident in speaking. The students’ responses indicate that they are interestingand this strategies is usefulto support their speaking mastery. But there are some students that doesn’t interest with the strategy because they doesn’t like group work and they feel difficult in select correct word.
ANALYSIS OF VALIDITY AND RELIABILITY OF ONLINE GAME ADDICTION SCALE

Online game addiction is a form of individual activity that is done repeatedly and always focuses on playing online games and has a negative impact on users. Therefore, it is necessary to develop an online game addiction scale to measure the level of addiction to online games. This study uses a quantitative approach with product moment correlation analysis using validity test with Cronbach alpha analysis assisted by SPSS 22 application. The results of the analysis concluded thatfrom 42 items, 26 items were declared valid with a reliability coefficient of 0.837 which was categorized as high reliability. From these results, it can be concluded that the scale of online game addiction is considered feasible and can be used by school counselors to measure online game addiction.
Point-of-Interest Type Prediction using Text and Images.

Point-of-interest (POI) type prediction is the task of inferring the type of a place from where a social media post was shared. Inferring a POI’s type is useful for studies in computational social science including sociolinguistics, geosemiotics, and cultural geography, and has applications in geosocial networking technologies such as recommendation and visualization systems. Prior efforts in POI type prediction focus solely on text, without taking visual information into account. However in reality, the variety of modalities, as well as their semiotic relationships with one another, shape communication and interactions in social media. This paper presents a study on POI type prediction using multimodal information from text and images available at posting time. For that purpose, we enrich a currently available data set for POI type prediction with the images that accompany the text messages. Our proposed method extracts relevant information from each modality to effectively capture interactions between text and image achieving a macro F1 of 47.21 across 8 categories significantly outperforming the state-of-the-art method for POI type prediction based on text-only methods. Finally, we provide a detailed analysis to shed light on cross-modal interactions and the limitations of our best performing model.