Reviewerly/exHarmony huggingface dataset:
Teacher Professional Identity and Perfomer Identity: Where Does the Stage Cease and the Class Begin?

The focus of the article is on the process of becoming a teacher. Many researchers have concluded that this process is of profound, complex, ever-evolving nature, during which teachers attempt to define their role and their entity. Identity itself brings out another problem of identification with the subject. Thus, more and more studies have been exploring professional teacher identities in different fields regarding the interaction between subject and teacher identities. The aspects of professional identity development among teachers of stage performers from the specific field of artistic education have been chosen for the research due to the lack of scientific research worldwide so far. The arts school case study of professional identity among teachers of stage performers from the development point of view has showed that the professional identity development of teachers among stage performers of an arts school is of a wide scope and possesses its own features. In the course of first socialization, the performer identity is perceived, while the teacher role is selected during the second socialization. No identity conflict has been observed between performer and teacher identities, they help maintain the mission of an artist. Everyday pedagogical practice, knowledge and skills by means of reflection and conversation contribute the understanding of what a teacher role is. Creativity and openness are essential for interaction with the milieu.
Fast Development of ASR in African Languages using Self Supervised Speech Representation Learning

This paper describes the results of an informal collaboration launched during the African Master of Machine Intelligence (AMMI) in June 2020. After a series of lectures and labs on speech data collection using mobile applications and on self-supervised representation learning from speech, a small group of students and the lecturer continued working on automatic speech recognition (ASR) project for three languages: Wolof, Ga, and Somali. This paper describes how data was collected and ASR systems developed with a small amount (1h) of transcribed speech as training data. In these low resource conditions, pre-training a model on large amounts of raw speech was fundamental for the efficiency of ASR systems developed.
Code- Switching as a Language Teaching Strategy Based on the Grammar- Translation Method for Comprehension Enhancement

This study aimed to determine the effectiveness of code-switching as a language strategy anchored on the grammar-translation method for comprehension enhancement to the grade seven junior high school students at Tanauan School of Craftsmanship and Home Industries, Tanauan, Leyte.It lasted for four (4) weeks from February 12 to March 12, 2019 using the 60 grade 7 students enrolled during the school year 2018-2019.The 60 students comprised the four sections belonging in the heterogeneous group and were then divided into comparable groups of 15 students per section: the control group and experimental group.The control group was exposed to the English-only-policy method while the experimental group was exposed to the code-switching strategy taught by the English teachers.To find the effectiveness of the codeswitching strategy, the true-experimental design was used, employing the pre-test and post-test scheme.Since the experiment aimed to investigate the effectiveness of code-switching, in comparison with the English-only-policy approach, there was a need to measure achievement through fifty (50) item pre-test and post-test.Mean ratings of the students in both groups in the achievement test were analyzed.The findings showed that the achievement of the control and experimental group was the same in the pre-test; teaching capitalization was satisfactory, teaching punctuation, grammar and sentence structure was fairly satisfactory, and teaching word usage was satisfactory.The computed t-values were all not significant.The performance of both groups in the evaluations was very satisfactory but the experimental group showed a better performance than the control group.The results of the post-test of the control group were teaching capitalization was very satisfactory; teaching punctuation was very good; teaching grammar, teaching sentence structure and teaching word usage were very satisfactory; and the combination was very satisfactory.In the experimental group: teaching capitalization, teaching punctuation and teaching grammar were outstanding; teaching sentence structure and teaching word usage were very satisfactory; and the combination was outstanding.The computed t-values in teaching word usage was not significant, teaching capitalization, punctuation, grammar, and sentence structure were significant, while the combination was also significant at 0.05 level of significance.The performance of both groups in the pre-and post-tests along the five language competencies tested is found to be "significant".
Project E.N.T.A.B.L.A.D.O: A Basis for Promoting the Drug Abuse Prevention Advocacy And Practices

People who abuse drugs can die or get addicted to them without realizing it. Temptation is hard to deny. People may think they are cool if they are into it but truth is, they are not. Instead, they can harm themselves. Using drugs is one of the huge problems in society. Meanwhile, schools are known as the center for the development of every learner and through education, prevention of this malady is expected with coordination with the community. This study then aimed to perform a counterbalancing act in molding a safe and well-informed decision making in a normative culture that can be used by all members of society, most especially the learners. In addition, it sought to promote a project that will showcase activities and trainings of Barkada Kontra Droga (BKD) in Natalia Velasquez Ramos Memorial Integrated School, District III-Alangilan in the Division of Batangas City, Batangas, Region IV-A CALABARZON which will contribute as model illustration to different schools to boost drug education, prevention and awareness and to sustain various services in the Barkadaadopted concepts by maximizing the drug abuse prevention advocacy given by the DepEd from various memorandum and orders. This research used the descriptive method of research with a researcher-made questionnaire as the main data gathering instrument and supplemented with an interview. Frequency, percentage, rank, and weighted mean were used as statistical tools in data analysis. Thirty selected junior and senior high school teachers served as the respondents of the study. Findings revealed that there were more activities needed to improve and to strengthen the awareness on drug addiction among learners and also increase community involvement to keep a fully drug-free atmosphere.
Using “Pepper"s ghost” video installation - Centered on “SIGHT”

Phantom imaging technology originated from Pepper’s Ghost, which uses optical principles to produce virtual images through projection, similar to virtual images produced through holographic projection. In today"s era of rapid development, especially the popularization and application of digital technology. As the most modern imaging technology today, the phantom imaging system uses information-based centralized methods to cooperate with the intuitive and centralized interactive expression of information, which will make various management tasks more rigorous and effective, and services more convenient and efficient. It has been widely used in various fields of many country"s national economic production. This study starts from an experiment using 45° holographic phantom imaging technology through the work SIGHT, studies its technical principles, production, and discusses the application of such technology in cultural industries.
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL

Training autonomous agents able to generalize to multiple tasks is a key target of Deep Reinforcement Learning (DRL) research. In parallel to improving DRL algorithms themselves, Automatic Curriculum Learning (ACL) study how teacher algorithms can train DRL agents more efficiently by adapting task selection to their evolving abilities. While multiple standard benchmarks exist to compare DRL agents, there is currently no such thing for ACL algorithms. Thus, comparing existing approaches is difficult, as too many experimental parameters differ from paper to paper. In this work, we identify several key challenges faced by ACL algorithms. Based on these, we present TeachMyAgent (TA), a benchmark of current ACL algorithms leveraging procedural task generation. It includes 1) challenge-specific unit-tests using variants of a procedural Box2D bipedal walker environment, and 2) a new procedural Parkour environment combining most ACL challenges, making it ideal for global performance assessment. We then use TeachMyAgent to conduct a comparative study of representative existing approaches, showcasing the competitiveness of some ACL algorithms that do not use expert knowledge. We also show that the Parkour environment remains an open problem. We open-source our environments, all studied ACL algorithms (collected from open-source code or re-implemented), and DRL students in a Python package available at https://github.com/flowersteam/TeachMyAgent.
Discovering an Algorithm Actually Learning Restricted Single Occurrence Regular Expression with Interleaving

A recent paper proposed an algorithm iSOIRE, which combines single-occurrence automaton (SOA) and maximum independent set (MIS) to learn a subclass single-occurrence regular expressions with interleaving (SOIREs) and claims the learnt expression is SOIRE, which has unrestricted usage for interleaving. However, in reality, the learnt expression still has many restrictions for using interleaving, even does for Kleene-star or interation, i.e, the learnt expression is not an SOIRE, we prove that by examples. In this paper, for the algorithm iSOIRE, we first give the basic notions, then provide analyses about incorrectness, finally present the correct result learnt by iSOIRE. Our theoretical analyses demonstrate that the result derived by iSOIRE belongs to a subclass of SOIREs.
2D filter design for coding artifacts reduction using structural similarity as a metric

This paper describes a method of designing a 2D post filter for reducing coding artifacts caused by lossy image compression. Though Mean Squared Error (MSE) has been typically used in such filter design, it is not necessarily a good quality measure in terms of consistency with subjective perception. In this paper, we employ a more reliable quality measure called Structural SIMilarity (SSIM), and derive filter coefficients that can maximize the SSIM score for each image.
Search Contact Information of Scams in Classifieds of Marketplace

The article describes an approach to determining whether an ad for sale or provision of services contains contact information: phone numbers, email addresses, website links, social media IDs etc.
Comparison of performance prediction models using logistic and ensemble algorithms in KLPGA

The logistic classification model is the most important and widely used representative algorithm in machine learning. The reason is that it is possible to interpret the results compared to other models. On the other hand, XGBoost of the decision tree class has the disadvantage of not being able to interpret the results like a black box or an excellent algorithm that has won several data learning contests such as Kaggle. Will have. The general approach to predictive models of machine learning has no significant difference from statistics or data mining, but its purpose is not interpretation of the model, but focuses on prediction, such as accuracy, so the most suitable method appears differently for each data. In order to overcome these shortcomings, each prediction model tries to interpret the model through function selection or contribution. The purpose of this study is to compare the logistic regression model most commonly used in classification models with the random forest and boosting models using unbalanced sports data to compare how predictive performance and functional importance of the model are different.
A Survey of Cascading Style Sheets Complexity Metrics

Cascading style sheets (CSS) is a Web-based style sheet language that is used for the presentation of Web documents. CSS has advanced from CSS1 to CSS3.and extensions to CSS known as CSS pre-processors have also emerged in the last few years. As is the case with regular software, CSS have inherent complexity that keeps on increasing with age which is undesirable, and metrics are needed to measure with the aim of controlling it. Although several Web metrics have been proposed in the literature, the area of stylesheets is still lagging. Findings show that few CSS-related metrics exist, and there is no evidence of proof for their mathematical soundness through the popularly known frameworks such as Briand framework and Weyuker’s properties. In addition, they have not been empirically validated. In order to address this gap, future studies should focus on defining and validating new metrics for CSS and its pre-processors.
Study on the Pricing Mechanism of Deductive Right License Transfer Based on Mechanism Design Theory

The relevant laws and regulations in our country only provide in principle for the license transfer of deductive right. In practice, we often encounter two major problems: First, there is information asymmetry between the original author and the deductive author, and there is a large transaction cost. The second is how to give consideration to the interests of the original author and the deductive author to achieve incentive compatibility. To solve these two problems, build a quantitative model. It has a certain reference value to the practice of deduction right license transfer.
Weakly Complete Semantics Based on Undecidedness Blocking

In this paper we introduce a novel family of semantics called weakly complete semantics. Differently from Dung's complete semantics, weakly complete semantics employs a mechanism called undecidedness blocking by which the label undecided of an attacking argument is not always propagated to an otherwise accepted attacked argument. The new semantics are conflict-free, non-admissible but employing a weaker notion of admissibility; they allow reinstatement and they retain the majority of properties of complete semantics. We show how both weakly complete and Dung's complete semantics can be generated by applying different undecidedness blocking strategies, making undecidedness blocking a unifying mechanism underlying argumentation semantics. The semantics are also an example of ambiguity blocking Dunganian semantics and the first semantics to tackle the problem of self-defeating attacking arguments. In the last part of the paper we compare weakly complete semantics with the recent work of Baumann et al. on weakly admissible semantics. Since the two families of semantics do not coincide, a principle-based analysis of the two approaches is provided. The analysis shows how our semantics satisfy a number of principles satisfied by Dung's complete semantics but not by Baumann et al. semantics, including directionality, abstention, SCC-decomposability and cardinality of extensions, making them a more faithful non-admissible version of Dung' semantics.
Scarcity leads to .... affection

Where in the 90s everyone had a hi-fi stereo sound system to play their favourite records or CDs, now we hardly have any favourite music, let alone a decent installation to play it on. Although we can hear everything ever made through Spotify or iTunes, we usually listen through a speaker on the smartphone or tablet. Gone is both the pleasure in music and the pleasure of building a personal music collection and thus identity. The same goes for books (for example Kobo plus). The presentation of text - fonts, paragraphs, and images - in eBooks cannot be compared to the beautiful formatting of printed books. The easier we communicate textually, the less we read. SMS and WhatsApp are wonderful examples of garbled textual communication. Tis text focusses on why this may be the case.
Formal verification of Zagier's one-sentence proof

We comment on two formal proofs of Fermat's sum of two squares theorem, written using the Mathematical Components libraries of the Coq proof assistant. The first one follows Zagier's celebrated one-sentence proof; the second follows David Christopher's more recent proof relying on partition-theoretic arguments. Both formal proofs rely on a general property of involutions of finite sets, of independent interest. The proof technique consists for the most part of automating recurrent tasks (such as case distinctions and computations on natural numbers) via ad hoc tactics. With the same method, we also provide a formal proof of another classical result on primes of the form $a^2 + 2 b^2$.
Towards data-free gating of heterogeneous pre-trained neural networks

The combination and aggregation of knowledge from multiple neural networks can be commonly seen in the form of mixtures of experts. However, such combinations are usually done using networks trained on the same tasks, with little mention of the combination of heterogeneous pre-trained networks, especially in the data-free regime. This paper proposes multiple data-free methods for the combination of heterogeneous neural networks, ranging from the utilization of simple output logit statistics, to training specialized gating networks. The gating networks decide whether specific inputs belong to specific networks based on the nature of the expert activations generated. The experiments revealed that the gating networks, including the universal gating approach, constituted the most accurate approach, and therefore represent a pragmatic step towards applications with heterogeneous mixtures of experts in a data-free regime. The code for this project is hosted on github at https://github.com/cwkang1998/network-merging.
Steering between outputs of a beamsplitter using Gaussian states of light with excess noise

We have studied the conditions for quantum steering between output modes when squeezed Gaussian light and vacuum mix in a beamsplitter as a function of the amount of squeezing and purity of the incident state. For Gaussian measurements, we find that for sufficiently strong squeezing, steering is possible regardless of the purity of the incident state. Two different types of non-Gaussian measurements were also considered. For one of them, an increase with respect to Gaussian measurements of the set of two-way-steerable states is obtained only for unbalanced beamsplitters.
Toward Neural-Network-Guided Program Synthesis and Verification

We propose a novel framework of program and invariant synthesis called neural network-guided synthesis. We first show that, by suitably designing and training neural networks, we can extract logical formulas over integers from the weights and biases of the trained neural networks. Based on the idea, we have implemented a tool to synthesize formulas from positive/negative examples and implication constraints, and obtained promising experimental results. We also discuss two applications of our synthesis method. One is the use of our tool for qualifier discovery in the framework of ICE-learning-based CHC solving, which can in turn be applied to program verification and inductive invariant synthesis. Another application is to a new program development framework called oracle-based programming, which is a neural-network-guided variation of Solar-Lezama's program synthesis by sketching.
Admissibility Of Electronic Evidence In Criminal Proceedings

This article attempts to analyze the institution of admissibility of evidence, in particular electronic evidence. Some issues of the specifics of such evidence are also considered. As a result, some recommendations were developed to ensure the issue of admissibility of electronic evidence.
The School Marching Band Program

This special chapter offers a short-format version of detailed teaching and organizational strategies directed toward all things marching. The suggestions are designed to be simple, easily implemented, and particularly helpful to directors with somewhat less marching experience. However, experienced marching teachers will also find value from guest contributor Christian Carichner, director of the Iowa State University Cyclone Marching Band. The chapter provides an excellent blueprint for developing a new marching band program, highlighting all steps to successful planning and execution. The discussions provide a detailed look at the marching band in its various forms; the chapter addresses drill design, field shows, competitions, parades and even basic pep band functions. Carichner offers specific suggestions about substitutions and recruiting, music selection, storyboarding, and program components including the battery, the front ensemble, and the drum majors. There is special guidance toward individuals, especially when a single director must assemble the program as a one-person team. The chapter presents numerous quick-fix strategies for sound production, music performance, visual rehearsal processes, commands, uniforms, and more. In this one source, band directors may discover the wide variety of tips, suggestions, and activities leading to success with all elements of the marching band program.
An acoustic sensor network for planetary exploration

This paper investigates the concept of an acoustic sensor network that can monitor a variety of geophysical processes occurring on other planetary bodies. In many cases sound is naturally omnidirectional and travels at known speeds which depend on the composition and density of the atmosphere. The differences in the time of flight of signals received by a distributed microphone network can be used to locate the source of the sound. We suggest this property is ideal for mobile planetary robots and can be used to expand the exploration envelope considerably by directing camera pointing or rover path planning thus extending beyond line-of-sight exploration. Acoustic signatures have been used in a variety of fields (eg. sonar, heavy machinery) to identify and catalog sounds associated with a specific vessels and malfunctioning machinery. Our ears have cataloged hundreds of sounds and we continuously use these sounds both consciously and subconsciously to extract information about our surroundings. This paper investigates the use acoustic measurements on other planetary bodies that could be used to characterize specific environmental parameters such as rain droplet size, wind speed, thunder, or dust devil vortex diameter. The paper identified other important sound sources that are thought to occur on other bodies in our solar system include; booming or singing dunes, waves, rivers, streams, fluidfalls, geysers, hurricanes, tornados, ice flow, volcanoes, planetary quakes, avalanche, rock slides and ice cracking. In addition, this paper focused on issues associated with the development of appropriate sensors for the network including the specification of the sensitivity, frequency response, and directional response of each of the microphones in the network in order to aid in localization of sound sources. We also presented our initial development of the transducers for potential mission targets including Mars and Titan and investigated the use of signal processing techniques including windowing, time frequency plots and correlation techniques to resolve phase differences between sensors in the network to aid in localization. We also identified additional benefits of these sensor networks in that they could used as engineering sensors to diagnose mechanical malfunctions on a rover or lander actuators or mechanisms. We also noted that they could also enhance public outreach by adding sound to videos.