Reviewerly/exHarmony huggingface dataset:
Towards Holistic Regulation of ‘Online Hate Speech’

India, as with other jurisdictions, has been struggling to deal with the issue of how to regulate hate speech in the online ecosystem. Regulatory responses have usually seen demands for either new criminal laws to be implemented or for intermediaries to ‘do more’ to make the online ecosystem safer. In this context, this paper provides an overview of regulatory interventions that have been proposed to deal with the issue of online hate speech in India, and argues that attempts to find a ‘silver bullet’ solution are unlikely to bear fruit. The focus on either creating new criminal offences or casting substantive policing obligations on intermediaries may lead to inequitable results and unintended consequences. These could negatively affect the very groups these interventions aim to protect. The issue of regulating online hate speech is complex. Therefore, we suggest that regulatory interventions must take into account the range of modalities available, including other legal alternatives and alternatives to 'law-based methods', that are explored in the paper; and focus on process improvements.
File Fragmentation to Improve Security in Cloud Using Graph Topology Grid Algorithm: A Survey

Cloud computing is an emerging patterning that provides computing, communication and storage resources-as-service over a network. In existing system, data stored in a cloud is unsafe due to the eaves dropping and hacking process. To overcome the drawbacks of earlier approaches, Division and Replication of Data in the Cloud for Optimal Performance and Security (DROPS) methodology is used. The node selection is ensured by means of Graph Topology Grid Algorithm and also data is encrypted here for security. In this process, the common data are divided into multiple nodes and replicate the fragmented data over the cloud nodes. Each data is stored in a different node as fragments in individual locations. In case of any attackers attack a node, no meaningful information will expose to them. The controlled replication of the file fragments is ensured and each of the fragments is replicated only once for the purpose of improved security and minimal retrieval time. In this survey, various relevant approaches were studied and analyzed. Furthermore the DROPS with Graph Topology Grid Algorithm give the better way of security in cloud environment over the earlier approaches.
Sentiment Analysis about Smart Phones Using Twitter Corpus by Deep Learning Approach

Micro blogging websites are nothing but social media website to which user makes quick and frequent posts. Twitter is one of the well-known micro blog sites which offer the space for person which can read and put up messages that are 148 characters in duration. Twitter messages also are referred to as Tweets. And will use these tweets as raw facts. Then use a way that automatically extracts tweets into advantageous, bad or neutral sentiments. By the usage of the sentiment evaluation the consumer can recognize the feedback about the product or services before make a purchase. The organization can use sentiment evaluation to know the opinion of clients about their products, so can examine customer pleasure and in line with that they could improve their product. Now-a-days social networking sites are at the growth, so massive amount of data is generated. Millions of human beings are sharing their views each day on micro blogging sites, since it includes short and simple expressions. In this thesis, able to discuss approximately a paradigm to extract the sentiment from a famous micro running a blog carrier, Twitter, wherein customers submit their opinions for the whole thing. And can use the deep mastering algorithm to categories the twitters which incorporates Convolutional Neural Networks. The experimental end result is presented to demonstrate the use and effectiveness of the proposed system.
VERBAL AND NON-VERBAL SIGNS IN FACIAL WASH ADVERTISEMENTS: A SEMIOTIC ANALYSIS

This study involves the discovery of verbal and non-verbal signs, which also describe the meaning of verbal and non-verbal signs found in the facial wash commercial advertisements. The data were taken from three printed facial wash advertisements. The data source has been taken from the internet. This study used the semiotic hypothesis provided by Saussure (1983: 65) to find out the verbal and non-verbal signs and the theoretical meaning provided by Barthes (1977) to find out the meaning of verbal and non-verbal signs in the facial wash ads. The analysis used a descriptive qualitative approach to analyze the results. As a result, the three facial wash ads show verbal and nonverbal signs that enable the company to market its product. In the verbal signs of the advertising, most of them contain denotative meaning and non-verbal signs which is in part, contain connotative meaning in certain advertisements. Two advertisements used a female as a model; one advertisement used a male as a model. This means that advertisers seek to gain public attention through the use of pretty females, popular figures and natural extracts or ingredients.
Con(fuse)ing and Re(fusing) Barriers

In "Con(fuse)ing and Re(fusing) Barriers", we activate the practice of coalescing to discuss and propose trans* and neuroqueer ways of refusing access barriers and normative expectations. Drawing from trans* feminism, crip technoscience, embodied experiences and our arts-design practice as MELT, we attend to ritual making as a crip and trans* site of resistance. Rituals are activated throughout the text as practices that reduce access barriers, change habits, slow things down, or enact community rites of passage. We refuse (as in: fuse again) and confuse (as in: reconsider assumptions) separability, and trace how materials unfold in our arts-design experiments: concrete and errors become soft, rituals disorder normative space, and cosmic rays embrace neuroqueer understandings of computing. This text is an invitation to share and embrace rituals and refusal as interrelated modes that can make space for other worlds.
Hybrid nowcasting for solar power plants using satellite-data and Numerical Weather Predictions for (Deep) Machine Learning methods

&amp;lt;p&amp;gt;With the expanding penetration of renewable energy in the energy sector, we observe an ever-increasing need for more accurate weather and production forecasts. They are needed by several energy players: plant owners, system operators, service providers (balancing service providers, energy traders). For the energy market needs, in different countries we can already find almost real-time trading markets; in a likely future scenario, the day-ahead market will disappear in favour of 5-15 minutes ahead market. This trend luckily matches the system operators need of predicting in the very short term the energy fed into the grid, to effectively cope with voltage and congestions problems and manage the ancillary services. Overall, the scenario indicates a compelling need for advanced forecasting techniques.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;This article discusses a hybrid solar nowcasting system, predicting energy production from +15 minutes to 3 hours ahead, with a time granularity of 15 minutes. The system combines observed data (especially from satellite) and Numerical Weather Predictions to nowcast data in two steps: the first step is the nowcast of global horizontal irradiance and direct normal irradiance; they are then fed into the following system to predict the energy production. Thus, we disentangle the problem, and we can improve in parallel the two subsystems.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The weather nowcast model core is a Deep Learning method especially suited for time series problems (Long Short Term Memory Network - LSTM). It has been tested over different sites corresponding to different satellite spatial resolution, weather conditions and climate regions. The results are compared with different benchmarks such as the persistence model, smart persistence model and ground truth (where available), obtaining typical annual MAE results over the 15-&amp;gt;3 hours between 10 and 80 W/m2. Other metrics (MBE, RMSE, and the forecast score) are calculated to get a deeper view of the results meaning. We also compared results without the availability of NWP (computationally expensive) or ground sensors (not always available in real-time) to understand the benefits of processing those data.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The power production system (fed with the output of the previous model) is a combination of different techniques: Decision trees, KNN, and NN. The performance is typical of 3-6% annual NMAE, depending on the site. We compare the results with the persistence benchmark and we calculate other metrics such as MBE, NRMSE and to get a deeper understanding of the results.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The two-steps model is finally compared with a one-step model only, where just satellite data are fed into a model predicting the power, to compare pros, cons and performance.&amp;lt;/p&amp;gt;
Implementasi Pengolahan Citra Untuk Identifikasi Daun Tanaman Obat Menggunakan Levenberg-Marquardt Backpropagation

Digital Image processing implementation can be applied to identify medicinal leaves, because it can help the elderly and people with color-blindness in identifying medicinal leave to be consumed and in avoiding reading errors, since some leaves have similar shape and color . In this discussion, the feature-extractions are using color and shape features, and using Levenberg-Marquardt for pattern recognition algorithm. The success of this medicinal plant identification system resulted in fairly good accuracy. The backpropagation network architecture used two hidden layers with 10 and 5 neurons. Data training is using 60 training leaf images with 15 images each of 5 types: green betel leaf, red betel, soursop, castor and aloe vera. Then, offline testing is using 20 test images for each of 4 images from 5 types with the accuracy of 85%. Meanwhile the online (realtime) test is using 20 times for each leaf types so the accuracy is 88%.
Effectiveness of Pre-Teaching Vocabulary through Modified Orthography to Support Sight Word Acquisition on Esl Pupils

This study investigates the effectiveness of pre-teaching vocabulary through modified orthography to support sight word acquisition on ESL pupils.Participants include two hundred thirty pupils from Year 1 up to Year 4 in Temiang National School.An experimental plan was utilized.Pupils from each year were split into two groups: experimental group which consists of 114 pupils and control group which consists of 116 pupils.The lesson content for both groups is the same but it varies by the year which they are in.Teachers of the experimental group pre-teach vocabulary before the topic and revise every lesson.Findings of this study reveal that were significant improvement in pupil's performance, where pupils have already known the proper vocabulary before the topic hence their participation has increased in listening and speaking lesson.The findings also show that the experimental group outperformed the control group in reading and writing lessons.
Technology and Education: A Deterministic and Instrumentalist Philosophical Approach

Over the past few decades, enormous studies examining the significant contribution of technology adoption and usage in the education industry have emerged.Albeit, miniatures of this literature tend to focus on the outcome of massive (total) dependence of these technologies.To achieve the study objective, the authors engage instrumentalism, and determinism, philosophical approaches to investigate the potential outcome of full dependence of education technology in the pedagogical process in the education industry.Exhuming works of literature on technology adoption and usage in the education industry, and how the two philosophical approaches are being used in the field of philosophy, the conceptual findings reveal that using the instrumentalism approach to identify the potential outcome of educational technologies for the pedagogical process, there are bigger chances of producing a high level of effective and efficient students over traditional education.However, complete technology usage can be a complete disaster for the education industry if education is commercialized to the extent that students view education as a determining substance with lesser value.With this, the authors remark that education management should envision and present education technological adoption and usage as a mediating substance that the students needed to reach greater heights.
Visual Analysis of Research on Precise Funding Fine Chemical in Universities Based on Knowledge Mapping

The article utilizes Citespace software to analyze the existing research literature, uses the method of word frequency analysis to conduct content mining and data processing on the journal literature in the field of precision funding fine chemical industryresearch in colleges and universities, and analyzes the history and research of the precision funding of colleges and universities for students with financial difficulties in recent years. The current situation is expected to provide reference and reference for follow-up researchers, and to provide ideas and suggestions for practically improving the level of university funding.
A Qualitative Analysis of Using Games Learning Programs to Improve Elementary Teachers’ Application of STEM Capabilities

This study used CodeMonkey, an online learning platform through which elementary teachers can learn programming while playing games and experience how to integrate STEM into their courses. The study analyzed and examined their experiences using a qualitative research method. According to the research results, learning programming while playing games can encourage beginners to go all in. There are also complete guidelines on the teaching platform, so beginning learners can quickly become familiar with the interactive model, which stimulates their curiosity and changes the traditional learning method of teaching by teachers and received by students. On the whole, learning programming itself is a rigid subject. At the fundamental stage, learners can be greatly interested in learning it. However, if learners cannot understand the learning goals, the advantages gained from their self-confidence and joy of learning will no longer exist. Among beginners to the novel model of learning programming while playing games, there is no obvious difference in learning effectiveness between male and female students. Learners who actively seek to solve problems during the learning process can achieve better learning efficacy.
Performance Analysis of Dimensionality Reduction Techniques in the Context of Clustering

Data mining is one of the major areas of research. Clustering is one of the main functionalities of datamining. High dimensionality is one of the main issues of clustering and Dimensionality reduction can be used as a solution to this problem. The present work makes a comparative study of dimensionality reduction techniques such as t-distributed stochastic neighbour embedding and probabilistic principal component analysis in the context of clustering. High dimensional data have been reduced to low dimensional data using dimensionality reduction techniques such as t-distributed stochastic neighbour embedding and probabilistic principal component analysis. Cluster analysis has been performed on the high dimensional data as well as the low dimensional data sets obtained through t-distributed stochastic neighbour embedding and Probabilistic principal component analysis with varying number of clusters. Mean squared error; time and space have been considered as parameters for comparison. The results obtained show that time taken to convert the high dimensional data into low dimensional data using probabilistic principal component analysis is higher than the time taken to convert the high dimensional data into low dimensional data using t-distributed stochastic neighbour embedding.The space required by the data set reduced through Probabilistic principal component analysis is less than the storage space required by the data set reduced through t-distributed stochastic neighbour embedding.
A Corpora-based Analysis of I was used to, I got used to, and I became used to

The goal of this paper is to provide an in-depth analysis of the frequency of I was used to, I got used to, and I became used to in the Corpus of Contemporary American English and the British National Corpus. The COCA clearly shows that I was used to may be the most preferable one for Americans, followed by I got used to, and I became used to, in that order. When it comes to the genre frequency of the COCA, it is interesting to note that in the fiction genre, I was used to may be the most commonly used one. The BNC clearly indicates, on the other hand, that I was used to may be the most preferred by British people, followed by I got used to, and I became used to. With respect to the genre frequency of the BNC, it is interesting to note that in the fiction genre, I was used to may be the most widely used. When it comes to the frequency of was used to and nouns, the expression was used to measure is the most preferable one for Americans, followed by was used to people, was used to rate, was used to power, was used to fuel, was used to group, and was used to film. With respect to the frequency of was used to and gerunds, the expression was used to being is the most preferable one for Americans, followed by was used to seeing, was used to having, was used to getting, was used to doing, was used to doing, was used to working, was used to hearing, and was used to going, in that order. Additionally, the COCA shows that got used to life and got used to things are the most preferred ones in America, followed by got used to people, and got used to weapons (got used to walking, got used to violence, got used to name calling), in that order. The COCA also indicates that got used to being is the most preferable one for Americans, followed by got used to seeing, got used to having, got used to hearing, got used to wearing, got used to living, and got used to using (got used to doing). The COCA further shows that became used to seeing is the most preferred by Americans and followed by became used to writing (became used to tying, became used to talking).
Developing Supplementary Speaking Materials For “Bahasa Inggris” Textbook For 1st Grade Pharmacy Students

The purpose of this study is to develop supplementary speaking materials for Bahasa Inggris for grade X students of SMK Insan Mulia Yogyakarta and describe the efficacy of the supplementary speaking materials for grade X students of SMK Insan Mulia Yogyakarta. This research belongs to Educational Research and Development (R&amp;D) using a simplified six steps of Borg and Gall’s model (1983). The findings show that the students’ goal of learning English is to communicate with the foreign costumers. Moreover, necessities of students are able to use English in their working field especially pharmacy and it helps students to pass job’s selection besides English is very important because the students are be able to use English in their working field especially pharmacy. more than that, the research finds that the students are lacking of vocabularies and speaking activities in the classroom and The students also lack of English speaking activities in the class because the books only provide reading. More than that, in learning English the students’ wants to learn English with their specific information about pharmacy. Some themes in the textbook were not relevant with the students’ want such as pharmacy, hospital and medicine. The efficacy of the supplementary speaking materials textbook serve the clear instruction and encourage the students in doing activities especially speaking, besides there are various activities in the textbook. This textbook is developed based on the Insan Mulia vocational pharmacy student’s need, lack, and want. Furthermore, the speaking materials as the product of this study provide additional learning resources for students.
LibGuides: Library Equipment Rules of Use: General Borrowing Information

A public guide collecting the various rules and policies that govern the circulation of library equipment, such as laptops, hotspots, and webcams.
WAYANG SANTRI SEBAGAI MODEL DAKWAH ISLAM BERBASIS KEARIFAN LOKAL

This study aims to describe and analyze the model of Islamic da’wah based on local wisdom contained in wayang santri performances. The model of Islamic da’wah is a pattern or approach used in broadcasting Islamic values. Wayang santri is a concept of puppet performances specifically used for the purpose of da'wah. This study uses a qualitative research method with a descriptive approach that describes a model of Islamic da'wah with the resource persons of wayang santri, that include dalang, sinden and music players of wayang santri. This research produced several important points regarding the model of Islamic da’wah based on local wisdom in wayang santri, namely regarding the origin and history of the development of wayang santri, the beauty side contained in wayang santri performances, and Islamic values contained in wayang santri performances
Peningkatan Hasil Belajar PPKn Melalui Strategi Pembelajaran Aktif Tipe Giving Question and Getting Answer Pada Peserta Didik Kelas V Sekolah Dasar

&lt;p&gt;&lt;em&gt;The purpose of this research was to improve student learning outcomes in PPKn grade V elementary schools with &lt;em&gt; active learning strategy type Giving Question and Getting Answer (GQGA) &lt;/em&gt;. The research conducted was a Classroom Action Research (PTK) with three cycles, with each cycle consisting of one meeting. The stages of each cycle are planning, implementing, observing and reflecting. Each meeting is carried out formative test to determine the progress of students. In the first cycle the students who completed after carrying out the formative test were 70% &lt;/em&gt;and a class average 70&lt;em&gt;. In the second cycle students who completed after carrying out the formative test were 82,5% dan &lt;/em&gt;a class average &lt;em&gt;77. In the third cycle students who completed after carrying out formative test were 100% and a class average 81,75. These results indicate that &lt;em&gt;active learning strategy type giving question and getting answer (GQGA) &lt;/em&gt;can improve student learning outcomes, especially grade V PPKn at SD Negeri 04 Serang academic year 2019/2020.&lt;/em&gt;&lt;/p&gt;
E-learning and Ground Reality: Problems and Remedies

Abstract: Learning is integral part of our life. We continuously learn directly or indirectly, knowingly and unknowingly. But, the formal education always demands a systematic way of learning, to bring improvement and modification in our behavior through experiences and training. At this moment the prevalence of e-learning due to Covid-19 is causing too many challenges before all of us. Not only student community but also teacher community comes under serious treat. Then also the effect on student community ultimately more serious as their academic years are delaying and a mental pressure is causing them to take very nuisance decisions. Thus, in this study it is targeted to highlight what kinds of problems are faced by the students belonging to poor and illiterate parents and probable way for its solutions. The study is designed in descriptive analysis based on both primary and secondary data collected from being participant observation and web pages. The findings of the study reveal that the poor condition and illiteracy of the parents are causing as a curse for students. Due to poorness of parents many students even suicide them and many students are going to be drop out and illiterate due to the lack of system as well as lack of knowledge to handle the system. Keywords: E-learning, Ground Reality, Problems and Remedies.