Reviewerly/exHarmony huggingface dataset:
PRAGMATICS OF LANGUAGE AND VALUES IN THE PUBLIC SPHERE: TOWARDS AN EXPANSIVE PRAGMATIC APPROACH TO THE USED DISCOURSE

This research aims at analysing the pragmatic prominent discourse in the public sphere, the digital sphere in particular, that reflects special changes in the society. The meant discourse has not been investigated adequately and sufficiently namely the social, the political and the digital virtual discourses which bear an effective semantic and pragmatic power on the public space and at the same time incorporate strong transformations in the values patterns. This study utilizes a pragmatic approach, since the pragmatics is a study of using language in communication, and works on analysing daily discourses using a journalistic editorial. So, what are the changes reflected by this discourse? And what are the values represented and expressed by the prevailing discourses in the public sphere?
Adversarial for Good? How the Adversarial ML Community's Values Impede Socially Beneficial Uses of Attacks

Attacks from adversarial machine learning (ML) have the potential to be used good: they can be used to run counter to the existing power structures within ML, creating breathing space for those who would otherwise be the targets of surveillance and control. But most research on adversarial ML has not engaged in developing tools for resistance against ML systems. Why? In this paper, we review the broader impact statements that adversarial ML researchers wrote as part of their NeurIPS 2020 papers and assess the assumptions that authors have about the goals of their work. We also collect information about how authors view their work's impact more generally. We find that most adversarial ML researchers at NeurIPS hold two fundamental assumptions that will make it difficult for them to consider socially beneficial uses of attacks: (1) it is desirable to make systems robust, independent of context, and (2) attackers of systems are normatively bad and defenders of systems are normatively good. That is, despite their expressed and supposed neutrality, most adversarial ML researchers believe that the goal of their work is to secure systems, making it difficult to conceptualize and build tools for disrupting the status quo.
Supplemental Material: Ferric iron triggers greenalite formation in simulated Archean seawater

A complete description of the experimental methods, analytical techniques, and supporting data and information regarding mineral identifications.&lt;br&gt;
Aspect Based Sentiment Analysis of Restaurant Reviews using Ensemble Algorithms

Digital information is continuously generated from various sources such as social media, and user reviews for services. Analysing of these reviews to extract user opinions is critical for developing customer satisfaction. In particular, restaurant services may be improved with customer feedback if the user opinions or sentiments are inferred from user reviews. The development of automated software systems for evaluating customer reviews is ongoing. This research work proposes an ensemble machine learning approach on the basis of the lexicon method and machine learning classifiers and the performance of the new model is evaluated on the basis of accuracy.  The Nave Bayes (NB), Decision Tree, and Support Vector Machine (SVM) are used to create an ensemble Classifier. The article presents a comparative assessment of the efficacy of ensemble methods for sentiment analysis. The restaurant review dataset is used to demonstrate the feasibility and benefits of the proposed approach.  The work focuses on not only the overall opinions but also aspect-based opinions, including Food, Service, Ambience, Quality and Price. The analysis is followed by a wide range of comparative experiments demonstrating the efficacy of ensemble technology for sentiment analysis. Finally, some detailed discussion and conclusions are drawn concerning the effectiveness of ensemble technology.
Curricular SincNet: Towards Robust Deep Speaker Recognition by Emphasizing Hard Samples in Latent Space

Deep learning models have become an increasingly preferred option for biometric recognition systems, such as speaker recognition. SincNet, a deep neural network architecture, gained popularity in speaker recognition tasks due to its parameterized sinc functions that allow it to work directly on the speech signal. The original SincNet architecture uses the softmax loss, which may not be the most suitable choice for recognition-based tasks. Such loss functions do not impose inter-class margins nor differentiate between easy and hard training samples. Curriculum learning, particularly those leveraging angular margin-based losses, has proven very successful in other biometric applications such as face recognition. The advantage of such a curriculum learning-based techniques is that it will impose inter-class margins as well as taking to account easy and hard samples. In this paper, we propose Curricular SincNet (CL-SincNet), an improved SincNet model where we use a curricular loss function to train the SincNet architecture. The proposed model is evaluated on multiple datasets using intra-dataset and inter-dataset evaluation protocols. In both settings, the model performs competitively with other previously published work. In the case of inter-dataset testing, it achieves the best overall results with a reduction of 4\% error rate compare to SincNet and other published work.
The Value of Humanism in Andrea Hirata's Novel “Orang-Orang Biasa”

This study aims to describe (1) To describe and explain the value of humanism in Andrea Hirata's novel Orang-Orang Biasa and (2) To describe and explain the use of humanism in Andrea Hirata's novel Orang-Orang Biasa as teaching material for analyzing material. novel. The form of this research is descriptive qualitative. The research strategy used in this research is a case study research strategy. The data in this study were analyzed carefully to obtain results in accordance with the research objectives using qualitative description techniques. The data collection procedure that the author did was a technique of reading and then taking notes. Problems related to the analysis of the value of humanism are obtained through reading the whole, carefully, interpreting the elements of humanism, then recording quotations directly or called verbatim. The results of the research are (1) Fitrah (humans are free to choose their own steps), (2) Human Rights (upholding human rights), (3) Fair (not taking sides with anyone) (4) Potential (the ability of every human being).
The Sustainability of Community Library and Literacy Culture

Community library is an institution that aims to improve the culture of literacy. It is held by several member of the society. However, community library faces several problems that hinder development, including regeneration problems in the organizational management. The library is generally located in the house of a resident, so its accessibility is very dependent on the existence of the homeowner. The homeowner is also the manager of the library. Therefore, regeneration in management is very important. The lack of awareness of community members causes the problem in the regeneration. This paper discusses the problem on sustainability of the community library. The data was taken from one of the community library in Bantul Regency, namely Widuri Pandan. The results of observations and interviews indicate that: 1) collaboration is needed with various parties to be able to develop the community, not only through donations, but also collaboration activities; 2) it is necessary to design forms of routine activities that can stimulate public interest in literacy; 3) sustainability in the human resources development faces some obstacles, so that regeneration and formation of the literacy team need to be formed.
PELATIHAN VIDEO PEMBELAJARAN BERBASIS MULTIMEDIA POWTOON DAN MEDIA UJIAN ONLINE GOOGLE FORMS UNTUK PENUNJANG PELAKSANAAN PEMBELAJARAN ONLINE DI SMPN 1 ANJIR PASAR

The Covid-19 pandemic indirectly impacted the transformation of the education system that was once the learning process is still conducted face-to-face, when the pandemic began to be directed into online learning. Community Service aims to help partners, namely SMPN 1 Anjir Pasar who are still having difficulty in utilizing information and communication technology facilities, especially in the online learning process during the Covid-19 pandemic. The priority of partner problems is divided into two parts, namely the first is still a lack of skills in the creation of multimedia-based learning media such as Powtoon so that learning seems monotonous. The second problem is the lack of skills in utilizing Google Forms media as an online test media because it is only limited to using WhatsApp media which of course uses it less efficiently to be used as an online exam medium. With the community service activities to SMPN 1 Anjir Pasar, of course, the hope is to help teachers in understanding and utilizing information and communication technology facilities well and able to use the information technology facilities as a means of supporting media in the implementation of online learning during the Covid-19 pandemic.
Installasi Site Bts Provider Indosat Di Area Sragen

The use of the internet network every day will increase in line with the times. The increasingly advanced internet network technology has become a demand for every provider to improve the quality of services provided to satisfy consumers by improving the quality of existing services and increasing service coverage in areas that are far from the city center that may not be reached by the internet network. Additional service coverage can be done by installing BTS sites (base transmition stations) in areas that are not yet covered by services from a provider. BTS itself functions as a signal receiver sent from the BSC which will then be distributed back to consumers who are within the range of the BTS. Keywords: BTS, internet network, provider
Communities, Computing &amp; the Carolinas

In this talk Tammy will briefly connect participants virtually to the conference site through tracing her own entree into Computer Science as a woman of color in North Carolina, sharing ways community experiences played pivotal roles. More broadly, she will share research insights from her research that illustrate the pivotal role of communities for STEM learning and that point to ways to mobilize communities to support such learning. Lastly, she will share some examples of STEM and computing learning environments that draw upon inherent characteristics of communities to promote life-relevant STEM learning.
A good body is all you need: avoiding catastrophic interference via agent architecture search

In robotics, catastrophic interference continues to restrain policy training across environments. Efforts to combat catastrophic interference to date focus on novel neural architectures or training methods, with a recent emphasis on policies with good initial settings that facilitate training in new environments. However, none of these methods to date have taken into account how the physical architecture of the robot can obstruct or facilitate catastrophic interference, just as the choice of neural architecture can. In previous work we have shown how aspects of a robot's physical structure (specifically, sensor placement) can facilitate policy learning by increasing the fraction of optimal policies for a given physical structure. Here we show for the first time that this proxy measure of catastrophic interference correlates with sample efficiency across several search methods, proving that favorable loss landscapes can be induced by the correct choice of physical structure. We show that such structures can be found via co-optimization -- optimization of a robot's structure and control policy simultaneously -- yielding catastrophic interference resistant robot structures and policies, and that this is more efficient than control policy optimization alone. Finally, we show that such structures exhibit sensor homeostasis across environments and introduce this as the mechanism by which certain robots overcome catastrophic interference.
CYBER SECURITY AWARENESS BY USING SOCIAL MEDIA PLATFORMS AMONG STUDENTS

The internet is not a secure place because of limited regulations. The unawareness of users about threats that can face them in cyberspace, can cause the successful execution of such threats. Users should establish a culture of awareness before entering the workforce. Therefore, academic institutions should engage in the process to enhance cyber security awareness (CSA) among students. In order to communicate effectively on CSA, the medium of communication should be familiar to the user and the user has to engage with this medium on a regular basis. Students at a higher academic institution reveal that they engage with social media platforms at least once a week with Facebook and YouTube the most popular. They also use communication media like websites to pursue material about CSA. This study found that there is a lack among students to engage with CSA initiatives that are available. It is suggested that academic institutions can contribute to the awareness of students by providing CSA material on a regular basis to them. Institutions can make use of social media platforms (Facebook and YouTube) and also communication mediums (institutional website and e-mails) to communicate CSA material with the students.
Non-uniform quantization with linear average-case computation time

A new method for binning a set of $n$ data values into a set of m bins for the case where the bins are of different sizes is proposed. The method skips binning using a binary search across the bins all the time. It is proven the method exhibits a linear average-case computation time. The experiments' results show a speedup factor of over four compared to binning by binary search alone for data values with unknown distributions. This result is consistent with the analysis of the method.
Development of Pop-Up Book Learning Media to Improve Understanding of Teaching

Research uses the development of Borg and Gall model development. The product produced in the development of grade 4 pop-up books in elementary schools in Sidoarjo, Indonesia. The results of the development of learning media by the criteria with the results of content expert validation have a 100% validity percentage. Validation from design experts has a 90% validity percentage, Validation results from linguists have a 100% validity percentage, individual results are found 100%, small group trial results are 97.14%, large group trial results are 98.21%. The results of the t-test analysis using SPSS 16 with a significance level of 0.05 indicate the p-value of the t-test statistic is 0.00, which means (&lt;0.05), it can be concluded that there is a significant significance in the pretest mean values ​​and posttest. This shows the pop-up book learning media developed effectively in increasing students' understanding of Class 4 in Sidoarjo, Indonesia.
Malicious URL Prediction Using Machine Learning Techniques

The usage of malicious website is a serious security threat faced by users while surfing data in internet. It is offensive and it belonging to criminal activities. Requirement of safeguard activities to help end-user is much needed. The need of understanding about protocol, uniform resource locator (URL) and other features of webpage are non-negligible. The purpose of this work is to findmalicious webpage from lexical and to resolve uncertainties faced by users. The study upon identifying features of websites is vulnerable and how malicious attack will occur is reported. To maximise the accuracy in prediction, machine learning technique is intruded. In recent years Phishing, botnet and malicious threats are more common in internet world and by disguising URL to trust it as non-offensive one.In concentrating with future concern and providing solution to real time problems faced by end-user the proposed work initiate two different algorithms namely decision tree and logistic regression. A total of 420000 webpages are taken as input data which included both affected and legitimate website. The time taken for prediction and accuracy is calculated in the form of testing data set. Thus logistic regression achieved higher efficiency with accuracy of 97.5% in an effective manner.
Upaya Peningkatan Hasil Belajar Siswa Kelas V Pada Tema 8 Sub Tema 1 Melalui Model Pembelajaran Project Based Learning Di Sekolah Dasar

&lt;p&gt;&lt;em&gt;The Aim of this research is to increase the student's study results on theme 8 sub theme 1 in the fifth grade students of SD Negeri Ragatunjung 04, Paguyangan. Brebes in the academic year 2018/2019. This research uses Project Based Learning model and it is an Action Classroom Research. The subject of the study is the students of SD Negeri Ragatunjung 4 for 26 students in the academic year 2018/2019. The Result of the reasearch is find out the precentages of the completeness that students achieves in the first cycle is 11 students (42,30%) success and 15 (57,70%) still get failed, which the average score 68,5. In the second cycle students succes increase in 24 students (92,30%) and 2 students (7,7%) still failed because they didn't get average score 84 yet. According to the explanation above can be concluded that using Project Based Learning Model is increasing the students study results on theme 8 sub theme 1 on the fifth grade students of SD Negeri Ragatunjung 4, Paguyangan. Brebes in the academic year 2018/2019.&lt;/em&gt;&lt;/p&gt;
Emulating ultrafast dissipative quantum dynamics with deep neural networks

The simulation of driven dissipative quantum dynamics is often prohibitively computation-intensive, especially when it is calculated for various shapes of the driving field. We engineer a new feature space for representing the field and demonstrate that a deep neural network can be trained to emulate these dynamics by mapping this representation directly to the target observables. We demonstrate that with this approach, the system response can be retrieved many orders of magnitude faster. We verify the validity of our approach using the example of finite transverse Ising model irradiated with few-cycle magnetic pulses interacting with a Markovian environment. We show that our approach is sufficiently generalizable and robust to reproduce responses to pulses outside the training set.
Using Artificial Intelligence to Promote Student-Teacher Interaction Research in and out of Class

Teaching is an interactive process in which students and teachers actively participate. Teachers and studentsinteract, communicate, influence and complement each other, which is the essence of teaching. The classroomatmosphere and the relationship between teachers and students largely determine the degree of students'participation. Learning is not only the transfer and transmission of knowledge from outside to inside, but also theprocess of learners actively constructing their own knowledge and experience, and students are not passiveinformation absorbers. The intelligent classroom constructed by artificial intelligence plays an important role incultivating the comprehensive quality of primary school students. Based on the construction of excellent courses ofartificial intelligence technology and application, this paper puts forward a mixed teaching strategy based onmulti-dimensional in and out of class interactive teaching method, so as to improve teaching effect and enhancestudents' learning enthusiasm.
PSYCHOSEMANTIC INDICATORS OF UNIVERSITY STUDENTS’ LEARNING MOTIVATION

The article analyzes the psychosemantic content and structure of students’ learning motivation as a holistic phenomenon. The structuralsubstantive and procedural characteristics of learning motivation are revealed based on the performed theoretical analysis. The “Unfinished sentences” technique was used to study the psycholinguistic and psychosemantic structure of students’ motivational sphere. This technique allowed us to evaluate expressiveness of the most important factors of students’ mental activities, which have a significant impact on their learning: their motivational orientations, leading motives and ways of their implementation, sources of tension, and styles of relationships with other people. In order to objectify the obtained data and interpret the research results, we used the developed procedure of content analysis, that help us to identify the psychosemantic indicators of students’ learning motivation, we also developed the technology for analysis and interpretation of textual diagnostic information obtained from the students. The performed psychosemantic analysis of the diagnosed textual information revealed in depth the essence of structural-meaningful and procedural characteristics of students’ learning motivation. The results obtained indicate that learning motivation is characterized by a complex structure, one form of which is the structure of internal (as for processes and results) and external (rewards or avoidance) motives. Students’ learning activities have a lot of motives. The main of them, which determine their work, are the following: an activity result (a product created, knowledge learned, etc.); satisfaction with a process; awards for efforts (salary, promotion, recognition); success in an activity; avoidance of failure. The main function of the differences arisen between an attained level and a level of actual goals is to form learning motivation, motivation to achieve the goals.
MENINGKATKAN HASIL BELAJAR SISWA DENGAN MENGGUNAKAN MODEL PEMBELAJARAN TALKING STICK

ABSTRACT Education does not necessarily greatly affect learning outcomes and Closed education: students, educators, materials, models / methods, curriculum, learning facilities and infrastructure. Educators are people who are responsible for the implementation of education targeting students. Student trainees improve their education in three environments, namely the Family Environment, School Environment, and Community Environment. Therefore, those responsible for education are parents, teachers, leaders in the learning, training and community programs. However, so far there is still something found in the learning process carried out. Therefore to solve this problem actions will be chosen using the Talking Stick Model because by using the Talking Stick model, the student acceptance process will be more memorable about making agreements by making good. Students will also be more active and interested in participating in learning because they are directly involved in learning a kensep through stick games by the teacher and students themselves in the classroom.
Secure and Accurate Multi-Keyword Retrieval With Privacy Protection for Multiple Data Owners in Cloud Computing

Cloud computing is a remarkable technology, due to the rapid rise in demand for infinite storage and high-quality retrieval services. Numerous research studies on privacy prob-lems have been conducted using a variety of keyword searches. Cloud storage is encrypted in compliance with the definition of multiple data owners. But most of these systems are vulnerable to threats and test attacks with keywords. Moreover, the top search results can be returned correctly From individual data owners. These inconveniences will obviously result in privacy-sensitive leakage Keywords and inaccurate of search results returned. in this paper, recovery system with various keyword confidentiality data owners that allow the cloud server to scan the cloud over multiple words and then return the relevant files to data customer search results without any keyword leakage. Moreover, we prove rigorous Safety analysis that our system is safe from attacks started by indoor and outdoor assailants. In conclusion, The performance assessment shows that our system has more efficient than the current graded keyword search system.