Reviewerly/exHarmony huggingface dataset:
Approaches to Classification of Modern Musical-Screen Forms

The purpose of the article is to identify the most appropriate features of the systematization of musical-screen forms to create a flexible system for their classification. The methodology of research is based on a complex of general scientific methods of analysis and synthesis, analogy, comparison and synthesis, systematization, using interdisciplinary (musicological and film studies) approach. The scientific novelty is manifested in finding characteristic features and factors of musical-screen forms, according to which several variants of their classification are offered. The systematization of screen creations with a dominant musical component allows us to look at already known representatives with a new perspective in the process of further scientific exploration. In addition, the classification will promote the introduction into the scientific circulation of the latest forms created by the increasing technology of life. Conclusions. Accumulation of a sufficient number of similar features of individual elements prompts the scientist to propose a classification system that would fit all the existing objects into one. By comparing the "classical" musical-screen forms with the newest ones and organizing them on common terms, we thus assert the right to exist and to research scientifically the newest forms (video album, music blog, video art, musical series, musical almanacs, etc.). The developed systematization will allow in the future to clearly define the place of forms, which are not yet demonstrable at the moment, that forms, which will be generated as new phenomena in the media space. The classification process helps, firstly, to identify the uniqueness of each of the forms and, secondly, to determine its place in the screen arts system.
The Effectiveness of Memrise Application toward Students' Adjective Mastery

This research was conducted because it was discovered that students had difficulty learning vocabulary, especially adjectives, and it was set against the background of several student problems. For instance, utilizing continuous paper-based learning to teach vocabulary resulted in boredom and could demotivate students. Dealing with that, one alternative solution was provided to the problem by implementing the memrise media to be tested in the learning process toteach adjectives. The research objective was to know the effectiveness of using memrise towards students' adjective mastery. Thus, this research used a quasi-experimental design and chose two classes by using cluster random sampling as the sample. The research instrument was tests, the results of which were analyzed using an independent sample t-test. The hypothesis testing results revealed that a significant value of 0.025 was obtained with a significance of α = 0.05. Thus, there was effectiveness in using memrise application toward students' adjective mastery. Furthermore, the N-Gain score for the control class was 0.46, while for the experimental class was 0.58. Therefore, it could be stated that the memrise can be used and is effective as learning mediafor adjectives mastery for seventh grade students of SMP N 3 Pringsewu
The Impact of E-Learning on Student Interest during the Covid-19 Pandemic

E-learning is an alternative method of learning that can be applied during the Covid-19 pandemic. One advantage of online learning (e-learning) is that students will get more sources of reading/references. E-learning encourages students to learn actively and autonomously during online classes. Students accept many assignments, and there are many limitations in the online learning process. When a student experiences monotony in the teaching and learning process, it will result in a setback in learning outcomes; even students become no longer interested in attending lectures. Few students feel bored with online learning; this impacts student enthusiasm in learning which tends to decline compared to direct learning. The aim of this study is to obtain information about the description of student interest in learning during the pandemic, and to find out whether online learning is affected during the Covid-19 pandemic, student interest at Widya Mandala Surabaya Catholic University (WMSCU) Madiun City Campus. This research uses an exposed facto quantitative research approach. The research population of WMSCU Madiun City Campus students who took online learning in the even semester of 2021/2022 amounted to 661. The research sample consisted of 192 people who were determined based on the Isaac and Michael table with a confidence level of 10%. The instrument of data collection was questionnaire. Data analysis method was simple linear regression. The results showed that student interest in learning during the pandemic was 1% in the low category, 35% in the moderately high category, and 64% in the high category. The hypothesis “E-learning has a strong positive effect on student interest in WMSCU Campus Madiun City” is accepted because of the value of Sig. &lt; 0.05. The results of this study indicate that the impact of e-learning on student interest in learning at WMSCU Madiun City Campus is 42.9%.
Reduction of Turbidity, Color Intensity and COD of Jumputan Wastewater with Electrocogulation Method

The purpose of this study was to determine the effectiveness of the electrocoagulation method in reducing turbidity, color concentration and COD levels on Jumputan wastewater treatment. The electrodes used are aluminum plates as anode and cathode. The variations of the research used were the speed of agitation and the system used (batch and intermittent system). The fixed variable used is a voltage of 3.5 volts, the 2 aluminium electrodes, and 250 ml volume of Jumputan wastewater. The results showed that the maximum turbidity degraded to 99.89% for the batch system at a contact time of 150 minutes with agitation speed of 150 rpm, and 99.97% for intermittent system at a contact time of 60 minutes with agitation speed of 150 rpm. The maximum percentage of color removal reached 58.90% for the batch system at a contact time of 90 minutes with a stirring speed of 50 rpm, and 54.74% for intermittent system at a contact time of 150 minutes with a stirring speed of 150 rpm. The electrocoagulation method could reduce 78.75% of the COD level for the batch system is and 80% for the intermittent system. The intermittent system slightly had more effect on the turbidity, color and COD reduction compared to batch system. Both batch and intermittent system got optimum turbidity and color removal on first 30 minutes of electrocoagulation process. The results prove that electrocoagulation method has been effective as an alternative to reduce COD and turbidity on Jumputan wastewater.
Instagram Post: Modifying the Use of Instagram to Increase Students’ Ability in Writing Cutline Caption

With the rapid advancements in technology, educators have increasingly explored the utilization of social media platforms as educational tools. Among these platforms, Instagram has emerged as a prominent choice due to its widespread popularity. This transformation has seen Instagram being repurposed from a mere entertainment tool to an educational medium, particularly in the domain of language instruction. English teachers, in particular, have embraced this platform to facilitate the teaching of essential language skills such as speaking and writing. This study aims to investigate the effectiveness of using Instagram in enhancing students' proficiency in writing cutline captions. The research subjects consisted of 32 twelfth-grade students from SMAN 1 Jatiagung, South Lampung, Lampung Province. Data collection was carried out through a pretest and posttest writing assessment, and the obtained data were subjected to descriptive quantitative analysis. The findings revealed a notable improvement in students' ability to write cutline captions following the integration of Instagram into the instructional process. These results highlight the potential of Instagram as a valuable tool for fostering students' writing skills, specifically in the context of crafting engaging and concise captions. The implications of this study contribute to the expanding body of literature on technology-mediated language learning and underscore the importance of incorporating social media platforms into educational settings for effective language instruction
Difficulties of Non-English Study Program Students in Carrying Out the Institutional TOEFL Test

This study aims to provide an analysis of TOEFL results and examine the challenges faced by non-English study program students when tackling TOEFL exam questions. The study adopts a descriptive qualitative approach, with a sample size of 30 students selected through purposive sampling from a larger population of 100 students. Data collection involved the administration of TOEFL tests and conducting interviews. The findings indicate that among the different sections of the TOEFL, Listening Comprehension posed the greatest difficulty for the participants, followed by Reading Comprehension and Structure and Written Expression. Based on the conclusions drawn from the data and explanations, it can be inferred that participants encountered the most challenges in the Listening Comprehension section of the TOEFL exam. Specifically, they struggled with long conversations, spoken passages, and short conversations in sequential order. The second most challenging section for students was Structure and Written Expression. Furthermore, the analysis reveals that within the three TOEFL sections, Structure was perceived as more difficult than Written Expression. In contrast, Reading Comprehension appeared to be the easiest section. The findings suggest that identifying difficult words presented the most significant challenge in Reading Comprehension, while identifying topics, explanatory sentences, and references were considered relatively easier. Overall, this study provides valuable insights into the specific difficulties faced by non-English study program students when attempting TOEFL exam questions, highlighting the areas that require further attention and support in their language learning journey
Gradient is All You Need?

In this paper we provide a novel analytical perspective on the theoretical understanding of gradient-based learning algorithms by interpreting consensus-based optimization (CBO), a recently proposed multi-particle derivative-free optimization method, as a stochastic relaxation of gradient descent. Remarkably, we observe that through communication of the particles, CBO exhibits a stochastic gradient descent (SGD)-like behavior despite solely relying on evaluations of the objective function. The fundamental value of such link between CBO and SGD lies in the fact that CBO is provably globally convergent to global minimizers for ample classes of nonsmooth and nonconvex objective functions, hence, on the one side, offering a novel explanation for the success of stochastic relaxations of gradient descent. On the other side, contrary to the conventional wisdom for which zero-order methods ought to be inefficient or not to possess generalization abilities, our results unveil an intrinsic gradient descent nature of such heuristics. This viewpoint furthermore complements previous insights into the working principles of CBO, which describe the dynamics in the mean-field limit through a nonlinear nonlocal partial differential equation that allows to alleviate complexities of the nonconvex function landscape. Our proofs leverage a completely nonsmooth analysis, which combines a novel quantitative version of the Laplace principle (log-sum-exp trick) and the minimizing movement scheme (proximal iteration). In doing so, we furnish useful and precise insights that explain how stochastic perturbations of gradient descent overcome energy barriers and reach deep levels of nonconvex functions. Instructive numerical illustrations support the provided theoretical insights.
Training on Writing Scientific Papers for Teachers at Public Junior High School 3 Batukliang, Central Lombok

This training activity aims to improve the competence of teachers at Public Junior High School 3 Batukliang, Central Lombok Regency in the field of writing scientific papers. This activity is carried out in three stages. The stages involved in solving this problem are the preparation stage, the implementation stage, and the evaluation stage. The results of the training showed that the teachers who attended were very enthusiastic about following and observing what was explained by the community service team regarding the models and strategies taught in class to compile them into a scientific work. In addition, the training participants wanted the training activities to be sustainable.
An Application of the Input Hypothesis to the Teaching Design of English Reading Class in Senior High School

Reading as a form of input can provide students with a good foreign language environment, allowing them to improve their vocabulary, master fixed expressions, use grammar rules flexibly and appreciate the beauty of cultural differences without having to leave home.To maximize the benefits of the English reading, this study is expected to explore the distinguished teaching design based on the author’ s own experience in the competition because there is still a long way to go given the fact that nothing is consummate. Krashen’s “input hypothesis” are chosen to be the theoretical basis of the study for its sweeping impact on the area of second language acquisition and foreign language teaching. By clarifying the internal relationship between Krashen’s “input hypothesis” and English reading teaching design, reflecting and summarizing the actual situation of English reading teaching in senior high school, the study tries to put forward the ideal pattern of English reading teaching design in senior high school and gives some inspirations to teachers-college students majoring in English.
The Impact of the Free Fire Online Game on Language Attitudes Elementary School Students

Playing online games has become a habit, including among elementary school students currently. In addition to entertainment, online games are often used as a means of learning. This study aims to determine the impact of free-fire online games on students' language attitudes. This research was designed in a qualitative descriptive form. The research was conducted on students, teachers, and parents of fourth-grade students at SD Negeri 31 Salotellue, Palopo City. Data was collected through observation and interviews. Data analysis was carried out qualitatively by following the Miles and Huberman model. The results of this study indicate that students are active users of free-fire online games using Android devices with a duration of 2-3 hours a day. Students' language attitudes from playing Free Fire online games can be seen using less polite and careful language choices. Changes in students' language attitudes after using the free-fire online game for a long time are indicated by using pejorative language, addiction, emotional changes, interest in learning and lack of interaction. On the other hand, students also get a second language, English, in the form of several vocabulary words used in daily activities.
The solution of MRSLP with the use of heuristicalgorithms

Improving production processes includes not only activities concerning manufacturing itself, but also all the activities that are necessary to achieve the main objectives.One such activity is transport, which, although a source of waste in terms of adding value to the product, is essential to the realization of the production process.Over the years, many methods have been developed to help manage supply and transport in such a way as to reduce it to the minimum necessary.In the paper, the problem of delivering components to a production area using trains and appropriately laid out carriages was described.It is a Milk Run Stop Locations Problem (MRSLP), whose proposed solution is based on the use of heuristic algorithms.Intelligent solutions are getting more and more popular in the industry because of the possible advantages they offer, especially those that include the possibility of finding an optimum local solution in a relatively short time and the prevention of human errors.In this paper, the applicability of three algorithms -Tabu Search, genetic algorithm and simulated annealingwas explored.
Using Game-based Learning in Order to Enhance Decision Making Under Uncertainty

How do people make their decisions? Searching for the answer in the relevant literature, we can find that decisions are based either on rationality or intuition. Rational thinking is mainly observed in situations characterized by certainty (in terms of data or the consequences of decisions), while heuristic intuitive methods are mainly observed in situations of uncertainty. Training for the enhancement of decision making skills usually employs problem-based activities which mainly focus either only on rationality or only on intuition. However, problems in real life cannot always be solved with the contribution of only one way of thinking. In a decision making process often rationality works up to an extent and then intuition will lead to the final decision. For this reason, we designed and developed a game-based learning activity that enhances both rational and intuitive decision making skills. More specifically, we created a decision scenario in a virtual environment in which participants were provided with uncertainty-based information in their decision making process. As they tried to follow a rational decision making process, most of them realized that based on the given information they were confused and they had to decide intuitively at the end. This experiential learning activity was a tickler for the participants to decide under uncertainty and trust their intuition.
Perspectives on Database Rights of Humans and Machines in Electronic Health Records: Focus on South Africa

Database right, as a subcategory of copyright law, rewards the creative exploits, labour and skill expended in compiling, arranging and organising a set of information for ease of use. When humans create, the labour and ingenuity exerted in reaching completion is compensated by the law by bestowing exclusive rights of exploitation on creators and their assigns. In the sphere of Electronic Health Record databases, data (which are mainly inputted by clinicians) are obtained from various sources, including clinician deduction, patients and caregivers’ observations and reports, and family-reported or community-reported traits. Using the doctrinal research method and writing primarily from a South African legal standpoint with insights drawn from other countries, the author considers the dynamics of navigating ownership rights in Electronic Health Record databases and the associated challenges when AI is involved. In summary, this paper examines the Electronic Health Record ownership rights of humans and machines, particularly in the South African context.
Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima

Sharpness-Aware Minimization (SAM) is an optimizer that takes a descent step based on the gradient at a perturbation $y_t = x_t + \rho \frac{\nabla f(x_t)}{\lVert \nabla f(x_t) \rVert}$ of the current point $x_t$. Existing studies prove convergence of SAM for smooth functions, but they do so by assuming decaying perturbation size $\rho$ and/or no gradient normalization in $y_t$, which is detached from practice. To address this gap, we study deterministic/stochastic versions of SAM with practical configurations (i.e., constant $\rho$ and gradient normalization in $y_t$) and explore their convergence properties on smooth functions with (non)convexity assumptions. Perhaps surprisingly, in many scenarios, we find out that SAM has limited capability to converge to global minima or stationary points. For smooth strongly convex functions, we show that while deterministic SAM enjoys tight global convergence rates of $\tilde \Theta(\frac{1}{T^2})$, the convergence bound of stochastic SAM suffers an inevitable additive term $O(\rho^2)$, indicating convergence only up to neighborhoods of optima. In fact, such $O(\rho^2)$ factors arise for stochastic SAM in all the settings we consider, and also for deterministic SAM in nonconvex cases; importantly, we prove by examples that such terms are unavoidable. Our results highlight vastly different characteristics of SAM with vs. without decaying perturbation size or gradient normalization, and suggest that the intuitions gained from one version may not apply to the other.
Wasserstein distributional robustness of neural networks

Deep neural networks are known to be vulnerable to adversarial attacks (AA). For an image recognition task, this means that a small perturbation of the original can result in the image being misclassified. Design of such attacks as well as methods of adversarial training against them are subject of intense research. We re-cast the problem using techniques of Wasserstein distributionally robust optimization (DRO) and obtain novel contributions leveraging recent insights from DRO sensitivity analysis. We consider a set of distributional threat models. Unlike the traditional pointwise attacks, which assume a uniform bound on perturbation of each input data point, distributional threat models allow attackers to perturb inputs in a non-uniform way. We link these more general attacks with questions of out-of-sample performance and Knightian uncertainty. To evaluate the distributional robustness of neural networks, we propose a first-order AA algorithm and its multi-step version. Our attack algorithms include Fast Gradient Sign Method (FGSM) and Projected Gradient Descent (PGD) as special cases. Furthermore, we provide a new asymptotic estimate of the adversarial accuracy against distributional threat models. The bound is fast to compute and first-order accurate, offering new insights even for the pointwise AA. It also naturally yields out-of-sample performance guarantees. We conduct numerical experiments on the CIFAR-10 dataset using DNNs on RobustBench to illustrate our theoretical results. Our code is available at https://github.com/JanObloj/W-DRO-Adversarial-Methods.
Underestimating the uncertainty of aggregated results: the case of W-Boson mass

Estimates of uncertainty or variance in experimental means are central to physics. This is especially the case for `world averages' of fundamental physical parameters in particle physics, which aggregate results from a number of experiments to express current knowledge about these parameters and where variance in these world averages reflect uncertainty in that knowledge. The standard aggregation method used to estimate such parameters is a form of hierarchical fixed-effect meta-analysis. This method is inherently unsuitable for estimating these parameters because it ignores sources of random variation between experiments (that is, variation in experimental accuracy, which becomes increasingly important as experimental precision rises). This problem is well-known in the statistical literature, where the typical recommendation is to use random -- rather than fixed-effect techniques. We illustrate this problem by applying random-effect meta-analysis to estimates of the W-Boson mass.