Reviewerly/exHarmony huggingface dataset:
Sentiment and Sentence Similarity as Predictors of Integrated and Independent L2 Writing Performance

This study aimed to utilize sentiment and sentence similarity analyses, two Natural Language Processing techniques, to see if and how well they could predict L2 Writing Performance in integrated and independent task conditions. The data sources were an integrated L2 writing corpus of 185 literary analysis essays and an independent L2 writing corpus of 500 argumentative essays, both of which were compiled in higher education contexts. Both essay groups were scored between 0 and 100. Two Python libraries, TextBlob and SpaCy, were used to generate sentiment and sentence similarity data. Using sentiment (polarity and subjectivity) and sentence similarity variables, regression models were built and 95% prediction intervals were compared for integrated and independent corpora. The results showed that integrated L2 writing performance could be predicted by subjectivity and sentence similarity. However, only subjectivity predicted independent L2 writing performance. The prediction interval of subjectivity for independent writing model was found to be narrower than the same interval for integrated writing. The results show that the sentiment and sentence similarity analysis algorithms can be used to generate complementary data to improve more complex multivariate L2 writing performance prediction models.
Tindakan Rasional pada Gaya Kepemimpinan Direktur Perpustakaan Universitas Islam Indonesia

Rational action style of the director of Library is able to give a positive impact on library director's autocratic leadership style in managing the Library optimally in order to reach the success of the goals of Indonesian Islamic university Library.Leadership is the ability in effecting and giving motivation to certain community to the way of reaching the better common goals.This research uses qualitative research method and uses field research that has the nature of qualitative research.The result shows that the rational instrumental action of the director of Library can give a positive impact on library director's autocratic leadership style, the director is able to give motivations through strict rules to work better, which makes the workers be carefully in working to reach the target expected by the director.This attitude of workers toward their director of Library is due to a good library organization.The work orientation and target of director of library focuses on the output of the organizational performance of the Indonesian Islamic University Library organization.
Problems on learning thinking aloud for reading via Zoom app in emergency remote learning class

This research attempted to obtain information on the problems of learning think-aloud for reading in an emergency remote learning class utilizing Zoom video conference application as the means of communication. While think-aloud is well-known method for improving students' reading strategy usage management, there are still problems encountered during class, especially if it is learnt via Zoom video conference application. The research participants were nine D3 program students of AMIKOM Purwokerto University PSDKU Yogyakarta who took Reading IV class. Data collection procedure included literary research, observation, questionnaire, and group interview. There were seven problems discovered: (1) Students were too shy to talk, (2) Students did not have or know proper vocabulary to verbalize their thoughts. (3). Students understood the text but had nothing to say. (4) Easy text did not invoke observable understanding processes in the studentsâ€™ minds. (5) Students neither understood the text nor knew what to say. (6) Time-consuming. (7) Internet disconnection. Simple solutions to those problems were also presented.
An Assessment of the Best Practices in the Implementation of Data Centers (A case of Zambia)

The purpose of this study was to assess the best practices in the implementation of the data centres in Zambia. For this reason, a total of 120 respondents were randomly selected from various institutions to participate in the study. The results shows that the impact of new hardware technologies on the infrastructure of the data center facility in Zambia will result in speedy access to data. The results also shows that the location of the Data Centre can be a critical design considerations and best practices in the site selection and design of data center in Zambia. It was observed that availability of power and also security can be a critical design considerations and best practices in the site selection and design of data center in Zambia. In addition, the study showed that human capital is the most common cost elements associated with different levels of data center reliability and fault tolerance in Zambia among others. Based on these recognitions, the following recommendations were made: that deliberate measures should be put in place to acquire new hardware technologies for the data center facility in Zambia to ensure speedy access to data. It was further recommended that in trying to design new data centers, the selection of the location should be a critical consideration. Furthermore, it was revealed that the management of data center facility in Zambia should also be organized through capacity building.
Reducing Response Time with Data Farming and Machine Learning

In industry, there are numerous applications for simulation.However, simulation in our area usually takes some time even if a preexisting model just needs to be parameterized; there is still the run time, which will usually take at least a few minutes if not hours.In our current case, a planner wanted to know for a given product mix situation and for an equipment group with specific characteristics how much he can utilize the equipment without violating flow factor targets.A question, which arises several times during a typical workday as new orders are coming in and the situation on the shop floor is continuously changing.Since the user is usually asking the same question just with different parameters we are able to solve the waiting time problem while still giving good decision support.Instead of simulating every scenario at the time the user actually needs these answers, we use data farming to generate a large set of data points that are then used to train a neural network.This neural network then substitutes for the simulation and responds to the user immediately.
Implementation of boosting on the C5.0 algorithm in the health development index data

The public health development index is a collection of health indicators that can be easily and directly measured to describe health problems down to the district/city level. The last calculation of the public health development index in Indonesia was carried out in 2018 with the result that not all districts/cities are in a high condition. This research was conducted to classify districts/cities that have a high and low public health development index using the boosted C5.0 algorithm. The results showed that the accuracy of the model increased with the increase in the number of iterations and was constant at the 60th iteration. Error training was also smaller and constant at the 10th iteration. The final accuracy, sensitivity and specificity were obtained respectively 97.09, 96.72, and 97.62.
An Intelligent Realtime Traffic Control Based on Vehicle Density

These days traffic congestion is becoming a serious problem. Roads and streets are getting over crowded, mainly in large cities leading to long vehicle queue, long hour of traffic on daily basis. This can evoke the day-to-day travellers to violate or break the traffic rules which can sometimes lead to accidents. Controlling and managing traffic system is the most demanding work in present days and the tradition traffic system cannot manage it efficiently. Nowadays worldwide in many big cities Intelligent system is been used for traffic surveillance and controlling. Therefore, we proposed a traffic control and management system which will detect the movement of vehicles, identify, track and count the numbers of vehicles in the lane by analysing a real-time live video feed form the camera with the help of computer vision and after detecting, classifying and counting the numbers of vehicle on a specific lane it will control traffic light according to the set threshold value, threshold value will be based on two criteria one is the density count of the lane and other is priority of that lane. This is done by using OpenCV and (YOLOV3) You Only Look Once real-time object detection algorithm based on CNN (Convolutional Neural Network).
Female Saudi University Students’ Perceptions of Online Education Amid COVID-19 Pandemic

The outbreak of the COVID-19 pandemic has wreaked havoc and caused world-wide disruptions to daily activities, including education. Numerous mitigation measures were taken to slow down the rapid spread of this pandemic. The situation, subsequently, entailed utilizing technology to ensure the continuation of the educational process. The abrupt shift to online education presented significant challenges to teachers and learners alike. Uncovering students’ perceptions of their online education experience will help address and deal with these challenges. This study attempted to explore the perceptions of Saudi female undergraduate students of their online education experience amid the COVID-19 pandemic. The total of 241 female students at the College of Languages and Translation at King Saud University in Riyadh answered a multi-item online survey. The results revealed that many of the respondents were happy with their online learning experience, enjoyed learning online and looked forward to their online classes. However, when asked to compare online learning to brick-and-mortar classes, more than half of the participants stated that they prefer traditional, face-to-face learning. The results of this study also revealed that the significant problems students faced in online education related to staying motivated, technical issues and the absence of face-to-face interaction. Despite the many challenges they face when learning online, the most cited advantage for online education mentioned by the participants is that it is more convenient. The results also indicated that this education mode seemed to suit shy students more, as they stated that they participate and ask questions more in online classes.
The Important Role of Extensive Reading Strategy in Indonesian EFL Learning Contexts

Abstract&#x0D; &#x0D; Academic literacy is one of the paramount global competencies that should be mastered by worldwide university academicians including Indonesian EFL learners. To fully fulfill this holistic educational objectivity, extensive reading plays a key role in fostering overarching Indonesian EFL learners’ target language proficiency due to the inducement of pleasurable, continual, and stress-free L2 reading learning dynamics proffered by this student-centered learning approach. Furthermore, the researcher attempted to delve more profoundly regarding the important role of extensive reading strategy in Indonesian EFL learning contexts. This present qualitative study harnessed a document analysis approach to yield renewable insights for Indonesian EFL experts, practitioners, researchers, and educators concerning the influential impacts potentially promoted by extensive reading strategy implementations. The research results indicated that the inducement of contextual and continual extensive reading activities had successfully improved EFL learners’ L2 reading interest and competencies. Future researchers are advocated to conduct a more exhaustive document analysis on the contrary beliefs and perilous effects generated by extensive reading approach to better impart more appropriate extensive reading programs applicable for Indonesian EFL learners’ reading needs, interests, and levels. &#x0D; &#x0D; Keywords: document analysis, extensive reading strategy, Indonesian EFL learning contexts
Building, Encoding, and Annotating a Corpus of Parliamentary Debates in TEI XML: A Cross-Linguistic Account

This paper introduces an integrative and comprehensive method for the linguistic annotation of parliamentary discourse. Initially conceived as documentation for a specific and small-scale research project, the annotation scheme takes into account national specificities and is geared to proposing an annotation scheme that is both highly standardized and adaptable to other research contexts. In this paper we present a specific application of the Text Encoding Initiative (TEI) framework applied to a subset of official transcripts of plenary proceedings in three parliamentary cultures. The TEI annotation scheme proposed here has two main applications: first, it serves as a basis for encoding parliamentary corpora by providing a systematic way of annotating both elements within the text (e.g., turns, incidents, and interruptions) and the metadata associated with it (e.g., variables pertaining to the speaker or the speech event); second, it provides a cross-linguistic empirical basis for further annotation projects.
THE EFFECT OF BOARD GAME TO INCREASE ENGLISH VOCABULARY MASTERY: SYSTEMATIC REVIEW

The aims of this study were: (1) to find out the effect of board game to increase English vocabulary mastery and (2) to find out which level of education can apply board game by collecting several sources related to the use of board game in learning English. This study used systematic review method. To collect the data, this study used documentations. The data in this study were 10 sources which consisted of 4 theses and 6 articles. In analyzing the data, this study used descriptive analysis. The results presented the significance differences before and after getting the treatment by using board game. It can be seen from the post-test scores that presented better than the pre-test scores. Therefore, board game is effective to increase students’ vocabulary mastery. Moreover, it can be applied in all levels of education.
LEST WE FORGET: INHUMANITY THREATS IN TEACHING IN THE NEW ERA

Since the prolonged pandemic, teaching language will never be the same even in the New Normal when less strict social distancing measures apply. The sudden shift from offline and/or blended learning to full online learning has brought about diverse pedagogical implications. On the one hand, unlike in traditional teaching and learning, one positive outcome in online learning is the enhancement of social engagement, autonomy, and digital compassion. On the other hand, ignorance, over-indulgence, and cold-heartedness are among the drawbacks of technology-mediated teaching. Drawing from personal experiences and relevant studies, this article highlights the threats of inhumanity when the power of technology takes over life skills that language learners need to acquire. At the core of the recommendation made herein is an open heart in this nearly closed world – a small fraction of Pope Francis’ newest encyclical letter Fratelli Tutti on fraternity and social friendship. The four core values suggested include critical thinking, ethical reasoning, interpersonal connectivity, and compassion.
Psybersecurity: A New Emerging Topic and Research Area within Human Security, Part 1

With the rise of technology in every facet of daily life, the increased conveniences come with multiple security risks. When imagining cybersecurity, the focus is generally on the protection of personal information, and the technology that stores this information. However, cyber-attacks can come in multiple forms. The term psybersecurity refers to the subject of securing the mental health, including protection of the human psychological wellbeing from the psychiatric consequences of technology usage, and studying the mental health attack surface plus vectors within the field of human security [1, 6]. With 1,473 reported cybersecurity breaches and over 164.68 million sensitive records exposed in the United States alone [2], the aftermath of these attacks extends beyond the technical repercussions.
Simulation-guided Beam Search for Neural Combinatorial Optimization

Neural approaches for combinatorial optimization (CO) equip a learning mechanism to discover powerful heuristics for solving complex real-world problems. While neural approaches capable of high-quality solutions in a single shot are emerging, state-of-the-art approaches are often unable to take full advantage of the solving time available to them. In contrast, hand-crafted heuristics perform highly effective search well and exploit the computation time given to them, but contain heuristics that are difficult to adapt to a dataset being solved. With the goal of providing a powerful search procedure to neural CO approaches, we propose simulation-guided beam search (SGBS), which examines candidate solutions within a fixed-width tree search that both a neural net-learned policy and a simulation (rollout) identify as promising. We further hybridize SGBS with efficient active search (EAS), where SGBS enhances the quality of solutions backpropagated in EAS, and EAS improves the quality of the policy used in SGBS. We evaluate our methods on well-known CO benchmarks and show that SGBS significantly improves the quality of the solutions found under reasonable runtime assumptions.
ConvGeN: Convex space learning improves deep-generative oversampling for tabular imbalanced classification on smaller datasets

Data is commonly stored in tabular format. Several fields of research are prone to small imbalanced tabular data. Supervised Machine Learning on such data is often difficult due to class imbalance. Synthetic data generation, i.e., oversampling, is a common remedy used to improve classifier performance. State-of-the-art linear interpolation approaches, such as LoRAS and ProWRAS can be used to generate synthetic samples from the convex space of the minority class to improve classifier performance in such cases. Deep generative networks are common deep learning approaches for synthetic sample generation, widely used for synthetic image generation. However, their scope on synthetic tabular data generation in the context of imbalanced classification is not adequately explored. In this article, we show that existing deep generative models perform poorly compared to linear interpolation based approaches for imbalanced classification problems on smaller tabular datasets. To overcome this, we propose a deep generative model, ConvGeN that combines the idea of convex space learning with deep generative models. ConvGeN learns the coefficients for the convex combinations of the minority class samples, such that the synthetic data is distinct enough from the majority class. Our benchmarking experiments demonstrate that our proposed model ConvGeN improves imbalanced classification on such small datasets, as compared to existing deep generative models, while being at-par with the existing linear interpolation approaches. Moreover, we discuss how our model can be used for synthetic tabular data generation in general, even outside the scope of data imbalance and thus, improves the overall applicability of convex space learning.
EFEKTIVITAS PENGGUNAAN LKPD BERBASIS REFUTATION TEXT DALAM MEREMEDIASI MISKONSEPSI SISWA PADA MATERI SENYAWA HIDROKARBON

This aims of this research is to determine whither there is a significant difference at of achievement between students before and after learning using refutation text based worksheet ant to effectiveness refutation text based worksheet on reducing misconceptions on topic hydrocarbon. The form of research used was pre-experimental with a one-group pretest-posttest research design. Samples were taken from class XI MIPA 4 which consisting of twenty nine students through purposive sampling technique. Data were collected using multiple choice diagnostic test with three alternative answers and three alternative reasons consisting of 15 questions. Acoarding to analusis, there is a differences in achievement between students were tested using the Wilcoxon test and an Pvalue who less the 0,000 which meant there was a significant difference. Acoarding to propotions test the effectiveness score 0,61 which was as category medium. Acoarding to analysis, there was a decrease in the percentage of students' concept errors by 47.4%. Conclude there is a significant different of achievement before and after remediation with medium effectiveness. Keywords: Effectiveness, Hydrocarbon Compounds, LKPD, Misconception, Refutation Text, Remediation
DEVELOPING AUDIO MEDIA FOR TEACHING LISTENING

This research was aimed to develop the investigation of English audio media for teaching listening to the seventh grade students. In this case, the product is an audio media, students’ book and the teacher’s book.The researcher applied Research and Development (R &amp; D) design. In this research the potential problem and solution were obtained by analyzing the policy study, doing the observation, the interview, and the questionnaire. The result of finding potential problem and solution is that the listening practice is very rare to do and the teachers do not use the audio media yet.The result of the design and development showed that the Audio Media for Teaching Listening was valid, the average of the three material validators is 93% and the three media validators is 84%. The result of product trial showed that the model was effective. The research was carried out in VII A class of SMP N 2 Sutojayan, Blitar.The class consisted of 32 students involved in the need analysis and try out using one group pre and post test experimental design method. The result of pre- test (57.13) while the post test was(83.06). the result shows the increase of the students’ result. In paired samplet- test, t- count was -21.351 with sig 0.050. The implementation of validation and try out was in the final product, all steps of learning and exercise was based onTask Based Language Teaching (TBLT) approach that had three steps namelyPre- Task, Whilst- Task, and Post- Task. The Audio Media supported with the teacher’s book and students’ book.The product gave a significant effect to the students’ listening skill. It was valid and could be used as the media in teaching and learning process.The “Active Listening” Audio Media enhanced the students’ listening skill.
Digital-based SME Innovation Development Strategy: Marketing, Entrepreneurship Insight and Knowledge Management

The success factor for the knowledge sharing from a management point of view, RBV views that substantially the success factor for knowledge sharing is fully held by business leaders. Leaders are seen as the main driving force for business organizations, because all policies and work procedures that a leader will implement in the organization will shape perceptions, culture and will also affect future organizational activities. Support from all parties is needed, not only the role of the leader but also the cooperation and involvement of employees. Refer to the resume of 20 recent Scopus indexed publications. Mapping the literature in this study provides several clues and propositions which can be clearly seen in this paper.