Reviewerly/exHarmony huggingface dataset:
Active learning to measure opinion and violence in French newspapers

News articles analysis may be oversimplified when restricted to detecting classes of interest already benefiting from trustworthy labeled datasets, like political affiliation or fakeness. Behind an apparent neutrality, an editorial slant may be embodied by favoring one-sided interviews, avoiding topics or choosing oriented illustrations. These challenges, seen as machine learning problems, would require a tedious annotation task. We introduce ReALMS, an active learning framework capable of quickly elaborating models which detect arbitrary classes in multi-modal text and image documents. Evidence of this capability is given by a case study on French news outlets: the detection of subjectivity, demonstrations and violence.
A Corpus-Based Study of Austen’s Novel Pride & Prejudice using Cirrus Tool

Previewing approach develops reader's cognition and presents an epigrammatic digital understanding of the text. The visual representations of knowing a word cloud produces an everlasting impact on the memory slate of the reader. The study aims at constructing an interactive cirrus word cloud preview based on statistical data that will help the readers to preview the extracted major themes and important characters in Jane Austen's novel Pride & The study addresses the main research question: How does Cirrus tool reveal significant characters and themes of Austen's novel Pride & Prejudice? A mixed method approach was applied to find out the significant characters and themes in Pride & Prejudice. The findings reflect that Cirrus tool can quickly extract 59 words from the novel, the most frequent 59 words/themes were found in Voyant Tools from the complex text. The corpus of the text of the novel “Pride & Prejudice” represented the main characters and the themes.
STUDENTS’ PERCEPTION ON EFL SPEAKING SKILLS

The aim of this research was to investigate what are students’ perception on EFL speaking skills. This research was conducted in one of Senior High Schools in Garut, in which consisted of six students of eleventh grade students in the data interview as participants. This research used qualitative method. In this research, the data were collected from structured interview. As the results, the first, the researcher founded that all of the participants think that speaking is important to learn. It can be seen from the students’ answered in interview. They are stated that speaking is important to learn because speaking used for interaction and communication in our life. The second, the teachers’ way in teaching speaking can influenced the students’ speaking skill. The students stated that if the teacher’s way in teaching speaking is well, it can make the students more active and interested in learning speaking, and it becomes a main factor for the students can understand or not. The last, the researcher founded that what are the students’ difficulties in learning speaking. The students have difficulties in learning speaking skill because they have poor vocabulary and poor pronunciation.
Factors motivating academic teachers to improve their teaching skills – pilot studies

The purpose of this paper is to develop hypotheses regarding the factors shaping the internal motivation of academic teachers to improve their teaching skills.Teaching methods and forms of communication have become the main research context.Design/methodology/approach: The studies were based on the review of literature on motivation theory and pilot surveys.The pilot analysis was based on data visualization methods and factor analysis.Findings: The use of modern communication methods might be correlated to age, and the use of modern teaching methods to gender.The teaching methods and forms of communication with students are influenced by factors related to the need to acquire knowledge and peer pressure.Originality/value The paper stresses an important aspect of the work of an academic teacher which is didactic work, which is not often taken into account in scientific research.The paper attempts to examine the factors that shape the teacher's motivation to improve their working methods in this regard.
STRATEGI ORKESTRASI PLATFORM BISNIS PENDIDIKAN ERA NEW NORMAL

Online-based education such as e-learning is very useful in today's new normal era. There are several international educational platforms, including those used in this study, namely Coursera, eDX and Future Learn. The purpose of this study was to explore the orchestration strategy of the normal new era education platform business organizers. This study used a qualitative approach was carried out through documentation studies method. This study indicates that the online education business platform implements an orchestration strategy with several different business partner networks. The orchestration strategy is implemented as an integral part of the business model. Through the analysis of The Business Model Canvas, this study finds that the online education business platform has the following business models: 1. Customer Segments, targeting the target group of people; 2. Value Proposition, prioritizing the value offered; 3. Channels, using channels to provide means of communication and information; 4. Customer Relationship, a good relationship with customers; 5. Revenue Streams, a source of income in business; 6. Key resource, in the form of assets of the company; 7. Key Activities, a series of activities; 8. Key Partners, a network of relationships; 9. Cost Structure, all costs incurred to operate the business. Keywords: e-learning, education platform, online course, business model canvas, orchestration
Development of Storybook to Improve Early Children's Reading Ability

Early childhood reading skills are focused on recognizing reading materials such as magazines, daily journals, children's activity books, books of picture, animal series books, and other books that can improve children's early reading skills. This is rarely understood by some PAUD teachers in Indonesia, resulting in misunderstandings in learning activities. This research aims to develop children's story book by themes as an effort to stimulate early childhood reading skills. Another goal is to find out the feasibility of using children's story books by themes as an effort to stimulate early childhood reading skills. The methode of research used is research and development which is modified from the model developed by Borg and Gall. The research development procedure is carried out through six stages, (a) Collect of information (b) compiling product designs (c) product validation developed (d) product design improvements (e) limited product trials and (6) product results of children's story books. This research resulted in 3 children's story books entitled “Ikan Koi Si Penolong”, “Aku membantu Ayah”, and “Belanja bersama Ibu ". Three of books resulting from this development research have gone through the stages of expert validation tests by material experts with a percentage of 92.8%. Meanwhile, the media expert indicator obtained a percentage of 93.7%, which means this book is valid and can be tested on children. Then a trial was conducted by two users, namely the Al-Huda PAUD teacher in Kabupaten Tasikmalaya. The test results obtained the percentage of values of 96.8% and 93.7%, which means that books by themes are appropriate and can be used by teachers to stimulate early childhood reading skills. Keywords: Story books, Early reading, Early childhood
Enhancing Speech Privacy with Slicing

Privacy preservation calls for speech anonymization methods which hide the speaker's identity while minimizing the impact on downstream tasks such as automatic speech recognition (ASR) training or decoding. In the recent VoicePrivacy 2020 Challenge, several anonymization methods have been proposed to transform speech utterances in a way that preserves their verbal and prosodic contents while reducing the accuracy of a speaker verification system. In this paper, we propose to further increase the privacy achieved by such methods by segmenting the utterances into shorter slices. We show that our approach has two major impacts on privacy. First, it reduces the accuracy of speaker verification with respect to unsegmented utterances. Second, it also reduces the amount of personal information that can be extracted from the verbal content, in a way that cannot easily be reversed by an attacker. We also show that it is possible to train an ASR system from anonymized speech slices with negligible impact on the word error rate.
Impact of artificial intelligence on human rights: special reference to COVID-19

The world has changed due to development of artificial intelligence (AI).Due to this emergence of AI although there is no doubt the development has change the history of humankind, but in what way that is the main question.Because AI has all the potentials to threat to Human rights which can worsens with time.This article try to put some light on this issues that how AI could possible effect the human rights
Capturing the Information-seeking of Students Employing a Wearable Camera: Discussions of Application in School Libraries

Utilizing wayfinding, think-aloud protocol (TAP), retrospective think-aloud protocol (RTAP), and a wearable camera, the actions, thoughts and feelings of an autistic college freshman and a neurotypical peer are recorded as they navigate their campus library in search of materials. The library website, virtual maps to resource locations, and library workers served equally as enablers and barriers to both students in their information seeking. This proof of concept study demonstrates that participant viewpoint ethnography is a viable research methodology that could be applied in school libraries for both neurotypical and autistic students.
Generating faces From the Sketch Using GAN

Abstract: In most cases, sketch images simply show basic profile details and do not include facial detail. As a result, precisely generating facial features is difficult. Using the created adversarial network and attributes, we propose an image translation network. A feature extracting network and a down-sampling up-sampling network make up the generator network. There is a generator and a discriminator in GANs. The Generator creates fake data samples (images, audio, etc.) in intended to mislead the Discriminator. On the other hand, the Discriminator attempts to distinguish between the real and fake sample Keywords: Deep Learning, Generative Adversarial Networks, Image Translation, face generation, skip-connection.
A Need Analysis in English Material for XI Grade of Beauty Program

Needs analysis aims to identify what English students should learn. However, there are still many teachers who have not analyzed the material needs of students. The material used by the teacher is too general for students. Students do not get English for specific purposes for particular majors. This results when students find it challenging to communicate with guests in certain areas. This study aims to analyze the English material and analyze the suitability of the English language material based on the ESP principles. This study used the descriptive qualitative method. The study subjects were students of the class XI beauty program—the use of questionnaires and document checklists as data collection instruments. The study results indicate that students need unique English materials and special English skills in the tourism sector, especially in beauty spas. Furthermore, based on the document checklist, the English teaching materials in the beauty program are not by the ESP concept because the data shows that the teaching materials are too general and not close to the student's field. Therefore, students hope that the school can design an ESP program to improve competence in beauty spa activities.
What Are the Potential Factors That Will Affect the Value of Bitcoin in the U.S.?

As a representation of Cryptocurrency, Bitcoin may have the potential to become a reliable currency due to its characteristics of decentralization and built-in scarcity.The evolution of Bitcoin shows some similarities with gold, that is an inflation hedge with a stable price.The purpose of this study was to determine what factors might affect the value of Bitcoin, which cause it eventually circulate with a stabilized price and become a future gold-like commodity under a macroeconomic scope.This paper conducted a generalized linear regression analysis of the Bitcoin price and gold price on the inflation rate, interest rate, and current account by using RStudio.Based on the United States annual data, this paper found evidence that the U.S. inflation rate, U.S. interest rate, and U.S. current account did not have significant effects on the gold price.However, the Bitcoin price was significantly affected by the U.S. inflation rate and U.S. interest rate.This implied that Bitcoin was not as stable as gold at current stage, but one possible speculation is that Bitcoin has the potential to counter inflation in the future.
Goal-oriented Email Stream Classifier with A Multi-agent System Approach

Now-a-days, email is often one of the most widely used means of communication despite the rise of other communication methods such as instant messaging or communication via social networks.The need to automate the email stream management increases for reasons such as multifolder categorization, and spam email classification.There are solutions based on email content, capable of contemplating elements such as the text subjective nature, adverse effects of concept drift, among others.This paper presents an email stream classifier with a goal-oriented approach to client and server environment.The i* language was the basis for designing the proposed email stream classifier.The email environment was represented with the early requirements model and the proposed classifier with the late requirements model.The classifier was implemented following a multi-agent system approach supported by JADE agent platform and Implementation_JADE pattern.The behavior of agents was taking from an existing classifier.The multi-agent classifier was evaluated using functional, efficacy and performance tests, which compared the existing classifier with the multi-agent approach.The results obtained were satisfactory in all the tests.The performance of multi-agent approach was better than the existing classifier due to the use of multi-threads.
Revealing Developers’ Arguments on Validating the Incidence of Code Smells: A Focus Group Experience

Identifying code smells is considered a subjective task. Unfortunately, current automated detection tools cannot deal with such subjectivity, requiring human validation. Developers tend to follow different, albeit complementary, strategies when validating the identified smells. Intending to find out developers' arguments when validating the incidence of code smells, we conducted a focus group session with developers familiar with identifying code smells. We distributed them among two groups, in which they had to argue about the incidence of a code smell: either accepting or rejecting its presence. Based on their arguments, we compiled a set of general heuristics that developers follow when validating smells. We then used these heuristics for composing validation items. We understand that the set of validation items proposed may support developers in reflecting on the incidence of code smells. However, further studies are needed for reaching a more comprehensive and optimized set. The experience of this study reveals that conducting focus group sessions is helpful to emerge the tacit knowledge of developers when validating code smells.
INDONESIAN GRADUATE STUDENTS’ ATTRIBUTIONAL BELIEFS AND METACOGNITIVE STRATEGIES IN THE ACADEMIC READING COMPREHENSION

The field of students’ beliefs in reading comprehension has become an increasingly significant research issue in the educational context. However, there have been very few studies examining attributional beliefs and metacognitive strategies adopted by EFL graduate students to deal with comprehension skills and reading difficulties. Applying the attribution framework, this study aimed to fill in the gap by investigating students’ attributional beliefs, metacognitive reading strategies, and the correlation between attribution and metacognitive reading strategies. The researchers employed mixed-method research with questionnaires and interviews as the instruments to collect data. The results showed that the majority of students attributed their successes or failures to internal factors (efforts and strategies). Many students claimed that they often experienced reading difficulties during online learning. Lastly, the Pearson correlation showed that there was a strong correlation (r = 0.746) between attributional beliefs and metacognitive reading strategies. This study offers several implications for language learning, in particular, the academic reading comprehension. First, students need to have a higher awareness of attributional beliefs in academic reading. Second, language teachers should support students to develop internal attribution and metacognitive strategies in academic reading.
INFORMATION MODELLING OF ENGINEERING NETWORKS FOR SUSTAINABLE WATER CONSUMPTION

The article based on information modelling considers one of the tasks of developing an automated solution for constructing computational schemes and specification materials for them for water supply and disposal – formation and programming of the calculation module of sustainable water consumption (construction of the computational scheme as a table).
Smart Assistive Activity Recognition Device for Differently Abled People Based on Machine Learning -SAARD

Science and Technology have made human life addictive to comfort, yet concurrently there exists an oppressed gathering of individuals who are battling for tracking down a creative way that can make their life easier for them.After concentrating and highlighting the problems faced by the differently abled people like blind and deaf, solving it through a device alone is a very hard task.A ton of exploration has been done on every issue and arrangements have been proposed independently.Objective of the smart assistive device SAARD (Smart Assistive Activity Recognition Device for Differently Abled People) is to recognize activity for differently abled people so; they feel confident and independent by helping them to know objects surrounding them.The Proposed device SAARD help the differently abled people by taking images and give the output in form of audio.Along with that it also detects obstacles and surrounding sound which alert them.
Document Storage Needs Analysis of Medical Record Rack and Spacious Room in Clinical Pertamedika Main Hall

Storage rack is one of the hospital equipment that functions to store medical record documents with the availability of medical record document storage racks in accordance with the storage capacity of medical record documents, there will be no buildup of documents on the floor. This study aims to determine the number of shelves needed for storing medical records of patients at the Pertamedika Pendopo Main Clinic in 2021. This research used a quantitative descriptive method by describing the results of the research and comparing it with the theory then conclude it. The study was conducted in June 2021 at the Pertamedika Pendopo Main Clinic. The population and sample used are storage shelves and all patient medical record documents. The instruments used in data collection include observation and interviews. The results of this study indicate that the number of visits of all patients at the Pertamedika Pendopo Main Clinic in 2020 was 5,197. The number of storage shelves needed at the Pertamedika Pendopo Main Clinic in 2021 amounted to 35 storage shelves with a length of 103 cm and a height of 224 cm. And the amount of space needed to accommodate 35 storage racks with a space between 90 cm and a distance of 150 cm is a room area of 157.59M ^ 2 with a length of 15.3 m and a width of 10.3 m. So that the shelf needed can be fulfilled and can accommodate all the patient's medical record documents systematically and does not complicate the officer in the process of storing and searching the patient's medical record document.
Aplikasi Point of sale Berbasis Website pada Toko Sembako Tegar

The development of the business world always requires us to improve the quality of products and services to consumers. goods purchasing services can be done electronically and can also be done online or in electronic commerce. Not a few entrepreneurs or business owners still manage their business transaction data manually, which of course has a high risk of losing data or making financial calculations wrong. Therefore, this website-based Point of sale application was designed with the aim of reducing these shortcomings and making it easier for entrepreneurs to manage their company's transaction data. This website-based Point of sale application has several advantages such as: facilitating transaction data management, simplifying business financial calculations, a computerized monthly financial recapitulation of the business.
MENINGKATKAN PEMAHAMAN TEKS RECOUNT SISWA KELAS X SMA NEGERI 4 PAMEKASAN MELALUI METODE TALKING STICK

The success of student learning in the classroom is highly dependent on the selection of appropriate learning strategies by the teacher. This study aims to improve the ability of students of class X MIPA-3 SMAN 4 Pamekasan in learning English with recount text material using the talking stick method. This research is a type of classroom action research which consists of two cycles. Each cycle consists of a process of planning, implementing, observing, and reflecting. The research subjects were 36 students. The object of the research is the process and results of learning English in recount text material. Data were collected using observation, documentation, interviews, questionnaires, and tests. The results showed that the students' average score increased from the first cycle of 54.72 to 85.13 in the second cycle. Thus, it can be concluded that the use of the talking stick method has succeeded in increasing students' abilities in recount text material.
A Dynamic Discriminative Canonical Correlation Analysis via Adaptive Weight Scheme

In multi-view learning, massive literature is devoted to exploring the intrinsic structure between cross-views. It is well known that canonical correlation analysis (CCA) is a conventional multi-view learning method, which considers the correlation between two views. However, it fails to utilize class information and is difficult to suit different issues to extract discriminative features. In this paper, we propose a novel cross-view discriminative feature learning method called dynamic discriminative canonical correlation analysis, which captures class information to yield discriminative features. More specifically, we develop an adaptive weight scheme of cross-view within-class and between-class scatters to make full use of distribution class information. In addition, an iterative algorithm with Cauchy inequalities and the Lagrange multiplier is proposed to handle the non-smooth objective function. Our method is applied to face recognition and multi-linguistic text classification tasks. Extensive experimental results reveal that the adaptive weight scheme plays a beneficial role and our method is an effective feature learning.