Reviewerly/exHarmony huggingface dataset:
THE USE OF LIVEWORKSHEETS (LWS) FOR VOCABULARY LEARNING

In Indonesia, English is considered the first foreign language taught from high school to university. Vocabulary is very important to students, which is why researchers want to know about techniques that can be used to increase students' vocabulary. This study deals with vocabulary teaching techniques and aims to find out if using Liveworksheets can improve English vocabulary of 7th grade students at SMP Negri 5 Tondano school. This study is a quantitative study through pre-experimental design with group pre-test and post-test design with 11 students. The results of this study indicate that students' English vocabulary increased significantly after using Liveworksheets in vocabulary lessons. This is evidenced by the average score of the test before and after the test, i.e., 3.54 before the test and 8.0 after the test. This means that Liveworksheets are effective in increasing the English vocabulary of students from grade VII to SMP Negeri 5 Tondano. Live spreadsheets are easy to use, can be viewed for free via the web, used anytime, anywhere, have the effect of motivating students to learn and are a new teaching method. Use a laptop or smartphone to access Liveworksheets. And new learning techniques can focus students' attention on learning.
Query-answering with text and knowledge graph

Query-answering (QA) is one of the key areas in Artificial Intelligence, where various researches are performed in recent years. Building query-answering system helps the organization of all sectors. Generating automatic responses saves both time and money. We examine the problem of query-answering over knowledge graphs (KG) where various QA approaches focus on simpler queries and do not work very well for complex queries or vice versa. In addition to that, reasoning over KG is also to be handled properly to predict the proper answer to the corresponding query. Models that use SPARQL are good at domain-related queries, but they are unable to handle out-of-domain queries. Combining contextual text representation and semantic graph representation is a challenge. Our area of research is to combine text and KG for open domain query-answering. Adapting the joint representation ensures that the model can perform well in both simple and complex queries. In this chapter, we explain the various works that have been conducted and the challenges that have come along with it.
Analisis Awal Gerak Butiran pada Transport Sedimen Tanah Gambut Jenis Fibrik

Peat beaches are beaches whose land can be easily abraded than beaches with other types of land. This is due to the light density of peat soil so that it can be easily carried away by the flow of sea water. One of the peat beaches in Indonesia whose coastline has changed significantly in recent decades is the peat beach on Bengkalis Island, Riau Province. Peat samples were taken from Tanjung Jati Beach, Perapat Tunggal Village, Bantan District, Bengkalis Island, Bengkalis Regency, Riau Province and then the sample is carried out an initial motion analysis on peat soil sediment transport. The peat sample that is obtained is a type of fibric peat soil. This research is a basic research that aims to determine at what speed the peat soil begins to move by the flow of water so that it can be seen the relationship between flow velocity and particle diameter at the beginning of the particle movement. The analysis was carried out by visual observation during simulation in the laboratory using a modified flume which was then compared with the results of Shields' theoretical calculations. Simulations were also carried out using sand sediment as a comparison. The flume flow velocity is determined from 0.00989 m/s to 0.10112 m/s for peat material, and 0.03973 m/s to 0.18900 m/s for sand material. The velocity is considered to have met the required simulation conditions, starting from the sediment not moving, starting to move, and being carried away by the flow. The results of the analysis carried out show that the peat material begins to move at a lower speed than the sand material. This is due to the specific gravity of the peat material being lighter than the specific gravity of the sand material as a comparison. This research is also expected to be a reference for further research on related topics.&#x0D; Keywords : Peat, Flow Velocity, Initial Particle Motion, Critical Shear Stress, Shields Theory
Analisis Hasil Belajar Matematika Siswa Ditinjau dari Intellegence Quotient

This study aims to describe the relationship between mathematics learning outcomes in terms of intelligence quotient (IQ). The subjects of this study were selected based on test results and predetermined categories. The data collection technique used consisted of two tests, namely a math test to find out learning outcomes and an IQ test to measure students' IQ levels. The results showed that the level of the students' IQ affected the learning outcomes obtained. In addition, the results of the interviews show that there are several factors that become obstacles and are often faced by students in learning, including internal and external factors. Internal factors are feeling lazy, not liking math lessons, lack of understanding of the material, and lack of time to practice working on practice questions. The external factors in this study were the unconducive classroom atmosphere which made it difficult for students to focus, the teacher's delivery was difficult to understand, and the lack of motivation and encouragement from the family, such as the presence of parents in student learning.
HIPU: A Hybrid Intelligent Processing Unit With Fine-Grained ISA for Real-Time Deep Neural Network Inference Applications

Neural network algorithms have shown superior performance over conventional algorithms, leading to the designation and deployment of dedicated accelerators in practical scenarios. Coarse-grained accelerators achieve high performance but can support only a limited number of predesigned operators, which cannot cover the flexible operators emerging in modern neural network algorithms. Therefore, fine-grained accelerators, such as instruction set architecture (ISA)-based accelerators, have become a hot research topic due to their sufficient flexibility to cover the unpredefined operators. The main challenges for fine-grained accelerators include the undesired long delays of single-image inference when performing multibatch inference, as well as the difficulty of meeting real-time constraints when processing multiple tasks simultaneously. This article proposes a hybrid intelligent processing unit (HIPU) to address the aforementioned problems. Specifically, we design a novel conversion-free data format, expanding the single-instruction multiple-data (SIMD) instruction set and optimizing the microarchitecture design to improve the performance. We also arrange the inference schedule to guarantee scalability on multicores. The experimental results show that the proposed accelerator maintains high multiply–accumulation (MAC) utilization for all common operators and achieves high performance with 4– <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$7\times $ </tex-math></inline-formula> speedup against NVIDIA RTX2080Ti GPU. Finally, the proposed accelerator is manufactured using TSMC 28-nm technology, achieving 1 GHz for each core, with a peak performance of 13 TOPS.
Curriculum Guided Domain Adaptation in the Dark

Addressing the rising concerns of privacy and security, domain adaptation in the dark aims to adapt a blackbox source trained model to an unlabeled target domain without access to any source data or source model parameters. The need for domain adaptation of black-box predictors becomes even more pronounced to protect intellectual property as deep learning based solutions are becoming increasingly commercialized. Current methods distill noisy predictions on the target data obtained from the source model to the target model, and/or separate clean/noisy target samples before adapting using traditional noisy label learning algorithms. However, these methods do not utilize the easy-to-hard learning nature of the clean/noisy data splits. Also, none of the existing methods are end-to-end, and require a separate fine-tuning stage and an initial warmup stage. In this work, we present Curriculum Adaptation for Black-Box (CABB) which provides a curriculum guided adaptation approach to gradually train the target model, first on target data with high confidence (clean) labels, and later on target data with noisy labels. CABB utilizes Jensen-Shannon divergence as a better criterion for clean-noisy sample separation, compared to the traditional criterion of cross entropy loss. Our method utilizes co-training of a dual-branch network to suppress error accumulation resulting from confirmation bias. The proposed approach is end-to-end trainable and does not require any extra finetuning stage, unlike existing methods. Empirical results on standard domain adaptation datasets show that CABB outperforms existing state-of-the-art black-box DA models and is comparable to white-box domain adaptation models.
AN ANALYSIS OF TEACHERS' STRATEGY IN TEACHING READING COMPREHENSION

This research aimed to determine the strategies used by English teachers in teaching reading comprehension and how they apply these strategies. This research was designed as descriptive qualitative research. The research was conducted at SMAN 02 Muaro Jambi. The participants of this research were three English teachers who taught in the tenth (X) MIPA grade of the school. Due to the COVID-19 pandemic so, each English teachers had two meetings observed by the researcher. The research instrument is an observation and interview. The instrument used is to find out the strategies used and how the English teachers applies the strategies in teaching reading comprehension. The results of the data were analyzed by; checklist observations and field notes. The results showed that the teacher used several strategies in teaching reading comprehension. The strategies are Translation strategy, Scaffolding strategy, and Question and Answer Relationship Strategy. Encourage the use of dictionaries, rereading to assess comprehension, understanding in certain tasks, and asking questions for specific information strategies applied in implementing reading comprehension in the school. This is evidenced by the motivation of students, students’ attention, and the ease of teachers in teaching and learning process
Discussion of ‘The Tax Effort: A Comparison between Sub-Saharan Africa and Benin’

In Benin, top businesspeople not only capture the economy but also the executive, and possibly legislative power. This book develops a comprehensive analysis aimed at identifying and reducing the institutional constraints that impede Benins rapid, sustainable, and inclusive development. The research reveals a chain of causality between four main categories of institutional weaknesses in Benin, namely corruption, inefficiencies in governance, opacity in public decision-making, and excessive informality in the Beninese economy. These institutional weaknesses are traced back to proximate and ultimate causes. The immediate causes include political instability, elite capture of key state functions, weakness of the state, and the possibility of easy but illegal rents. In turn, these causes are linked to deep-rooted underlying factors such as the nature of the political game, essentially neo-patrimonialism with multiple economic and/or political Big Men, but also geographical or ethnic factors. We elaborate on policy reforms aiming at overcoming or circumventing these institutional problems.
Discussion of ‘The Cotton Sector: History of a Capture’

In Benin, top businesspeople not only capture the economy but also the executive, and possibly legislative power. This book develops a comprehensive analysis aimed at identifying and reducing the institutional constraints that impede Benins rapid, sustainable, and inclusive development. The research reveals a chain of causality between four main categories of institutional weaknesses in Benin, namely corruption, inefficiencies in governance, opacity in public decision-making, and excessive informality in the Beninese economy. These institutional weaknesses are traced back to proximate and ultimate causes. The immediate causes include political instability, elite capture of key state functions, weakness of the state, and the possibility of easy but illegal rents. In turn, these causes are linked to deep-rooted underlying factors such as the nature of the political game, essentially neo-patrimonialism with multiple economic and/or political Big Men, but also geographical or ethnic factors. We elaborate on policy reforms aiming at overcoming or circumventing these institutional problems.
Iterative Causal Forest: A Novel Algorithm for Subgroup Identification

Abstract Precisely and efficiently identifying subgroups with heterogeneous treatment effects (HTEs) in real-world evidence studies remains a challenge. Based on the causal forest (CF) method, we developed an iterative CF (iCF) algorithm to identify HTEs in subgroups defined by important variables. Our method iteratively grows different depths of the CF with important effect modifiers, performs plurality votes to obtain decision trees (subgroup decisions) for a family of CFs with different depths, then finds the cross-validated subgroup decision that best predicts the treatment effect as a final subgroup decision. We simulated 12 different scenarios and showed that the iCF outperformed other machine learning methods for interaction/subgroup identification in the majority of scenarios assessed. Using a 20% random sample of fee-for-service Medicare beneficiaries initiating sodium-glucose cotransporter-2 inhibitors (SGLT2i) or glucagon-like peptide-1 receptor agonists (GLP1RA), we implemented the iCF to identify subgroups with HTEs for hospitalized heart failure. Consistent with previous studies suggesting patients with heart failure benefit more from SGLT2i, iCF successfully identified such a subpopulation with HTEs and additive interactions. The iCF is a promising method for identifying subgroups with HTEs in real-world data where the potential for unmeasured confounding can be limited by study design.
English Learning Activities in Heavy Equipment Engineering Study Program at Olat Maras Community Academy

Language learning activities are carried out by language educators so that students acquire appropriate language skills after engaging in a learning experience. The nature of English language learning in the Olat Maras Community Academy Heavy Equipment Engineering Study Program is not only focused on delivering the material contained in the semester learning plan but also paying attention to creative aspects, student enthusiasm, and paying attention to the needs of students humanely and democratically. The lack of learning experience for students in general is not only triggered by the difficulty of the content of the subject matter that cannot be understood by students, but also driven by the teaching approach to a learning activity that creates little learning experience for students during learning. The type of research used is qualitative. The instrument of this research is observation and direct interview. Data analysis techniques consist of data reduction, data presentation, and conclusions. The results of data analysis show that creating a learning atmosphere full of student activity must involve cognitive, affective, and psychographic students, such as inviting students to listen, practice, argue, and use learning media sourced from students' own ideas in following their study program.
Tingkat Literasi Digital dan Pengaruhnya terhadap Keterampilan Abad-21 Mahasiswa ditinjau dari Perspektif Gender

The 21st century is known for its rapid technological developments, one of which is the development of digital technology. This digital technology has penetrated various fields, including education. This research aims examine the level of digital literacy and its influence on students' 21st century skills from a gender perspective. This research method is a quantitative method. The research population is active students of the Tadris Physics study program who are currently attending lectures in the first to fourth years. The research sample consisted of 38 students (19 male students and 19 female students), selected using the quota sampling technique. Data collection in this research was carried out using questionnaires and interviews. The research instruments are 2 main questionnaires that can gather information about students' digital literacy levels and students' achievement of 21st century skills. Data analysis was conducted by calculating the average score for students' digital literacy and 21st century skills based on gender. Furthermore, an analysis of the relationship between digital literacy and students' 21st century skills will also be carried out. The relationship between the two variables was analyzed using a simple regression test. The results of data analysis show that the level of digital literacy and 21st century abilities of students is in the “good” category. However, for both variables there are no significant differences between male and female students with the significance values ​​of the difference test results for digital literacy and 21st century skills being 0.125 and 0.747 respectively (both greater than 0.05). Furthermore, the results of the regression analysis revealed a statiscally significant positive influence of digital literacy on students' 21st century skills, with an F-value of 20.145 and a significance level of 0.000 &lt; 0.05.
The Effect of Watching Rugrats Movie on Students' Writing Ability

Writing is a language skill which is used as indirect communication and an activity of getting down ideas and feeling. Actually, the process of writing is not easy for students. In writing students have to focus on grammar, words and also control them in making sentences. There is a way to help students to write, that is through watching a movie. Movie is a good media to increase students’ interest and motivation. Therefore, the ability to use media is one of competences that every teacher must have. One example of children movie is Rugrats. The population of this research was 360 students while the sample was 72 students. This research was conducted by using quasi experimental method. The writer used nonequivalent and applied Pre–test and Post-test control group design. Based on the research the result of t-calculated is 1.46 in the level of significance of 0.01 is 2.39 and the level of significance of 0.05 is 1.67. So, t-calculated is lower than t-table. It means that there is no effect of watching Rugrats movie on students’ writing ability.
Composing the Assemblage: Probing Aesthetic and Technical Dimensions of Artistic Creation with Machine Learning

Abstract In this article we address the role of machine learning (ML) in the composition of two new musical works for acoustic instruments and electronics through autoethnographic reflection on the experience. Our study poses the key question of how ML shapes, and is in turn shaped by, the aesthetic commitments characterizing distinctive compositional practices. Further, we ask how artistic research in these practices can be informed by critical themes from humanities scholarship on material engagement and critical data studies. Through these frameworks, we consider in what ways the interaction with ML algorithms as part of the compositional process differs from that with other music technology tools. Rather than focus on narrowly conceived ML algorithms, we take into account the heterogeneous assemblage brought into play: from composers, performers, and listeners to loudspeakers, microphones, and audio descriptors. Our analysis focuses on a deconstructive critique of data as being contingent on the decisions and material conditions involved in the data creation process. It also explores how interaction among the human and nonhuman collaborators in the ML assemblage has significant similarities to—as well as differences from—existing models of material engagement. Tracking the creative process of composing these works, we uncover the aesthetic implications of the many nonlinear collaborative decisions involved in composing the assemblage.
Validating the Formal Specification of the THUNDERS Process

Collaborative work encourages participants to build knowledge through exploration, discussion, negotiation, and debate to generate a better understanding or shared understanding of a concept, problem, or situation within a group. The aim of collaborative work is to find that shared understanding, which is understood as the existing agreement or similarity in the perceptions of the participants on a topic. Considering this, it can be determined that the greater the understanding and cohesion among all team members, the better results will be obtained in the development of the tasks and responsibilities that each of the members must fulfill, generating greater group trust and allowing everyone to move in the same direction. However, such understanding is not easy to build, there is no clarity on how it should be built, and it is simply given as something obvious or to be achieved, without giving it real importance. Trying to address these problems, from the multi-cycle action research methodology, THUNDERS is defined as a process that establishes how to build shared understanding in problem-solving activities. This article shows the conceptual and methodological cycles for its construction, and more in detail the validation cycle, in which was performed: an expert validation of the formal specification of THUNDERS to determine the correctness and completeness of its structure, a quality validation of its process model SPEM 2.0, and an experiment to validate its feasibility and usefulness. As results of these validations, it was obtained that THUNDERS needs to improve the syntactic and semantic elements of its specification and the cognitive load generated by its use. In addition, it was found that is a viable and useful process for the construction of a shared understanding with each of the elements that compose it.
Exploration on the Innovative Talent Training Model for Chinese-Foreign Cooperative Education in Chinese Universities in the Post-epidemic Era

The COVID-19 pandemic has presented the world education system with never-before-seen difficulties, and the Chinese higher education market has also been impacted. To improve student career development and academic performance in Chinese universities, creative talent training and Chinese-foreign cooperation have come to light in this setting. With a focus on the mediating role of teaching quality and the moderating influence of the epidemic scenario, this study intends to evaluate the impact of creative talent training and Chinese-foreign collaboration on student career development and academic performance in the post-epidemic age. Using a stratified random sample technique, a survey of 350 undergraduate students from Chinese universities was carried out to meet this goal. SEM was used to examine the gathered data. The study's conclusions show that creative talent training and Chinese-foreign cooperation significantly improve academic achievement and career growth in students. Additionally, the association between these two variables and student outcomes is somewhat mediated by teaching quality, highlighting the significance of effective instruction for the effectiveness of these tactics. Additionally, the findings reveal that the severity of the epidemic scenario modifies the association between Chinese foreign cooperation and student outcomes, indicating that the success of this method is dependent on the issue's severity. By providing empirical evidence of their impact on student outcomes in the post-epidemic era, highlighting the significance of teaching quality, and recognizing the moderating effect of the epidemic situation, this study contributes to the literature on talent development and international cooperation in higher education.