Reviewerly/exHarmony huggingface dataset:
LEO small satellite QKD downlink performance: QuantSat-PT case study

In this work, we model and simulate the performance of a quantum key distribution (QKD) downlink from a low earth orbit (LEO) small satellite to an optical ground station (OGS), as integral part of the concept and preliminary design phase of the QuantSat-PT mission. By modelling and simulating in detail downlink transmission channel effects, with emphasis on turbulent and atmospheric losses for BB84 and E91 protocols, we find a consistent set of values for the performance envelope that resolves ambiguities of mission experimental data that had been reported previous to this work. We obtain for the 4-state BB84 protocol a sifted key rate and Quantum Bit Error Rate (QBER) of 32.1 kbit/s and $4\%$, respectively, for zenith at 750 km orbit. For the E91 protocol the Clauser, Horne, Shimony and Holt (CHSH) test was performed resulting in a correlation factor of $S \in[-2.63\pm0.02,-1.91\pm0.03]$ for the mission. The consistency of these results with the state of the art simulators and its relevance on experimental satellite based QKD is discussed.
Fingerprinting Robot Movements via Acoustic Side Channel

In this paper, we present an acoustic side channel attack which makes use of smartphone microphones recording a robot in operation to exploit acoustic properties of the sound to fingerprint a robot's movements. In this work we consider the possibility of an insider adversary who is within physical proximity of a robotic system (such as a technician or robot operator), equipped with only their smartphone microphone. Through the acoustic side-channel, we demonstrate that it is indeed possible to fingerprint not only individual robot movements within 3D space, but also patterns of movements which could lead to inferring the purpose of the movements (i.e. surgical procedures which a surgical robot is undertaking) and hence, resulting in potential privacy violations. Upon evaluation, we find that individual robot movements can be fingerprinted with around 75% accuracy, decreasing slightly with more fine-grained movement meta-data such as distance and speed. Furthermore, workflows could be reconstructed with around 62% accuracy as a whole, with more complex movements such as pick-and-place or packing reconstructed with near perfect accuracy. As well as this, in some environments such as surgical settings, audio may be recorded and transmitted over VoIP, such as for education/teaching purposes or in remote telemedicine. The question here is, can the same attack be successful even when VoIP communication is employed, and how does packet loss impact the captured audio and the success of the attack? Using the same characteristics of acoustic sound for plain audio captured by the smartphone, the attack was 90% accurate in fingerprinting VoIP samples on average, 15% higher than the baseline without the VoIP codec employed. This opens up new research questions regarding anonymous communications to protect robotic systems from acoustic side channel attacks via VoIP communication networks.
Tree Methods for Hierarchical Classification in Parallel

We propose methods that enable efficient hierarchical classification in parallel. Our methods transform a batch of classification scores and labels, corresponding to given nodes in a semantic tree, to scores and labels corresponding to all nodes in the ancestral paths going down the tree to every given node, relying only on tensor operations that execute efficiently on hardware accelerators. We implement our methods and test them on current hardware accelerators with a tree incorporating all English-language synsets in WordNet 3.0, spanning 117,659 classes in 20 levels of depth. We transform batches of scores and labels to their respective ancestral paths, incurring negligible computation and consuming only a fixed 0.04GB of memory over the footprint of data.
Selected Cryptocurrency Returns and Capital Gains Tax - Based on the Example of Countries with Varying Degrees of Legal Regulations Concerning Cryptocurrencies

The purpose of the article/hypothesis: The purpose of this article is to present the impact of capital gains tax on the returns of the two most popular cryptocurrencies: BITCOIN and Ethereum Classic (ETC).&#x0D; Methodology: In this study, the rates of return on selected cryptocurrencies were proposed as a variable that may be affected by taxes on capital gains. The article presents a new approach to the analysis of issues related to cryptocurrencies.&#x0D; Results of the research: The results show that for selected countries (Hungary, Italy, Poland, the USA) there is a correlation between the tax rate on capital gains and the return on ETC. In the case of BITCON, however, there is no such a relationship.
Interactive Abstract Interpretation: Reanalyzing Whole Programs for Cheap

To put static program analysis at the fingertips of the software developer, we propose a framework for interactive abstract interpretation. While providing sound analysis results, abstract interpretation in general can be quite costly. To achieve quick response times, we incrementalize the analysis infrastructure, including postprocessing, without necessitating any modifications to the analysis specifications themselves. We rely on the local generic fixpoint engine TD, which dynamically tracks dependencies, while exploring the unknowns contributing to answering an initial query. Lazy invalidation is employed for analysis results affected by program change. Dedicated improvements support the incremental analysis of concurrency deficiencies such as data-races. The framework has been implemented for multithreaded C within the static analyzer Goblint, using MagpieBridge to relay findings to IDEs. We evaluate our implementation w.r.t. the yard sticks of response time and consistency: formerly proven invariants should be retained - when they are not affected by the change. The results indicate that with our approach, a reanalysis after small changes only takes a fraction of from-scratch analysis time, while most of the precision is retained. We also provide examples of program development highlighting the usability of the overall approach.
Mandarin Singing Voice Synthesis with Denoising Diffusion Probabilistic Wasserstein GAN

Singing voice synthesis (SVS) is the computer production of a human-like singing voice from given musical scores. To accomplish end-to-end SVS effectively and efficiently, this work adopts the acoustic model-neural vocoder architecture established for high-quality speech and singing voice synthesis. Specifically, this work aims to pursue a higher level of expressiveness in synthesized voices by combining the diffusion denoising probabilistic model (DDPM) and \emph{Wasserstein} generative adversarial network (WGAN) to construct the backbone of the acoustic model. On top of the proposed acoustic model, a HiFi-GAN neural vocoder is adopted with integrated fine-tuning to ensure optimal synthesis quality for the resulting end-to-end SVS system. This end-to-end system was evaluated with the multi-singer Mpop600 Mandarin singing voice dataset. In the experiments, the proposed system exhibits improvements over previous landmark counterparts in terms of musical expressiveness and high-frequency acoustic details. Moreover, the adversarial acoustic model converged stably without the need to enforce reconstruction objectives, indicating the convergence stability of the proposed DDPM and WGAN combined architecture over alternative GAN-based SVS systems.
Learning Representations by Humans, for Humans

When machine predictors can achieve higher performance than the human decision-makers they support, improving the performance of human decision-makers is often conflated with improving machine accuracy. Here we propose a framework to directly support human decision-making, in which the role of machines is to reframe problems rather than to prescribe actions through prediction. Inspired by the success of representation learning in improving performance of machine predictors, our framework learns human-facing representations optimized for human performance. This "Mind Composed with Machine" framework incorporates a human decision-making model directly into the representation learning paradigm and is trained with a novel human-in-the-loop training procedure. We empirically demonstrate the successful application of the framework to various tasks and representational forms.
Generation and Splitting of the Compound Words in Nepali Text

In Nepali language, compound word formation is mostly associated with inflection, derivation, and postposition attachment. Inflection occurs due to suffixation, whereas derivation is driven by both prefixation and suffixation. The compound word generated by the rules may produce lots of out-of-vocabulary words due to limited lexical resources and numerous exceptions. Hence, the machine learning approach can help to generate valid compounds and split them into valid morphemes that can be further used as a resource for spelling suggestions, information retrieval, and machine translation. In this research, a method to generate valid compounds from the corresponding compound splits (head word and prefix/suffix/ postpositions) is suggested. A BiLSTM based deep learning approach was used to generate and split the valid compound words. Publicly available Nepali Brihat Shabdakosh data from Nepal Academy and scraped news data were used for the experimentation. The obtained results were found to be outstanding compared to the rule-based approach applied to a similar job.
STUDENTS’ PERCEPTION ON THE USE OF NHK CHANNEL IN LEARNING VOCABULARY

This research aims at investigating the perception of the third-grade students on learning vocabulary through NHK channel at Madrasah Aliyah Masembo Maros. The method of this research was quantitative descriptive method. The population was all the students of the third grade in Madrasah Aliyah Ainus Syamsy Masembo Maros that consisted of 50 students. The samples were selected purposively, that were those who already watched NHK channel that consisted of 14 students. The data were collected through questionnaires. The data were analyzed by looking for the means score and intervals to classify them. The result indicated that there was a positive perception of watching NHK channel on students’ learning. It was proved by the mean score of total number of all of the questions as 56,6 which was classified as very high. Therefore, it is concluded that learning vocabulary through NHK Channel has good response from third grade students of Madrasah Aliyah Ainus Syamsy Masembo Maros or in the other words the use of media as learning tool such as NHK channel can help students in learning vocabulary
Millennial students’ metalinguistic knowledge on headlines Using Grammaticality Judgment Test

Amid the proliferation of online news portals, there is a felt need for a reinvestigation of the millennial students’ metalinguistic knowledge (MK) on the technicality of the headlines. Couched within Relevance Theory, including the interlarding theories of Communicative Competence and Monitor Hypothesis, this study investigated 80 students’ technical knowledge on selected 35 headlines vis-à-vis the students’ academic disciplines and exposure to the headlines/news articles. The study employed a Grammaticality Judgment Test (GJT) by Schütze (1996) following Noam Chomsky’s competence/performance distinction. The results showed the dearth of the students’ knowledge on the technical rules of the headlines, which only fared around 70.66% accuracy. Likewise, the results showed that those who were never exposed to the headlines had a significantly lower mean score as compared to those with exposure to the headlines. Poor cognizance of the semantics-syntax of the headlines statistically cuts across eight academic disciplines and exposure to news articles. Overall, the students’ understanding of the headlines seems to be shaped by their explicit knowledge and grammaticality judgment about the technicalities of the headlines. By and large, such results may be an indication of the students’ experiences of semantic ambiguities of the headlines. We put forth the dire need for the re-introduction of ‘Journalism’ course across educational levels in a language classroom given today’s rapid pervasiveness and breadth of digitalism. Students’ lack of MK on the technicality of the headlines can impinge on their understanding of the semantics and the actual story-level depictions of the news.
The First 500 Mistakes You Will Make While Streaming on Twitch.tv

Three librarians at the Mitchell Park branch of the Palo Alto City Library detail two years of lessons learned while streming a virtual event series on Twitch.tv for the first time. This series, titled Teach a Librarian How to Play Videogames, began at the start of the COVID-19 pandemic. We hope this article will inspire you to try something new with your library events, and encourage readers to learn from these mistakes and build off our success.
Developing local culture-based EFL reading materials for the 21st-century learning

The material specification is one aspect of teaching English at a vocational high school. Materials should be well-prepared to facilitate and promote students’ comprehension of concepts. This study aimed to develop instructional reading materials for Palembang – Tourism-Destination that are valid, practical, and potentially effective for students enrolled in a Travel Agent Study Program at one vocational school in Palembang, South Sumatera Province, Indonesia. The product was developed to meet the students’ needs. This research was a developmental study, with research phases including design, evaluation, and revision phases. Questionnaires, interviews, and reading comprehension tests were used to collect data. The data were analyzed quantitatively and qualitatively. A formative evaluation was conducted to determine the product’s validity, practicality, and potential impact. Experts evaluated the content, media, and instructional design for validity. The results indicated that the established product was extremely valid, scored an average of 3.65 for all evaluated elements. Practicality was rated highly in one-to-one and small-group evaluations, with average scores of 3.55 and 3.35. The results of the field test showed that the established texts had a high potential for impact, as 79.16 percent of students earned the required passing grade. As a result, it is reasonable to assume that the established product can be used in the classroom as the product for reading.
Tertiary Institute Result Computation System

The dome of any enterprise is its data and information.Acquiring complete, accurate, and easy retried tertiary institute computed results has fashioned catastrophe experience in almost all the tertiary institutions of the state.Thus, the demand for an intelligent result repository system with high computation capability is an urgent need of the tertiary institutes.This brings into light the importance of information technology and its efficiency where data durability and accuracy are optima.This research aims to develop an Automated Result Computing System (ARCS) through Knowledgebase Competitive Intelligence (KCI) solution; using strong storage flexible sensitive technique to achieve realtime processing that achieved efficiency in tertiary institute results computation, and data handling for durability.The software was developed and implemented on the Windows platform using object-oriented design and analyses technique, Visual Basic6 programming language enterprise edition, and Microsoft access for backend database with MySQL quarry language.The test data was obtained from Architecture Department, KenuleWiwa Polytechnic, Bori.The pragmatic evaluation of the system confirm; that the system speeds up tertiary institute semester results computation, offer accurate result, and provided uncomplicated access to results for both lecturers, students, as well as exam and records staff.The system achieved the designed aim.Therefore, the system is recommended for use in any tertiary institute with adjustable course parameters.
Image resolution enhancement via sparse interpolation on wavelet domain

The image processing algorithms collectively known as super-resolution (SR) have proven effective in producing high-quality imagery from low-resolution (LR) images. This paper focuses on a novel image resolution enhancement method employing the wavelet domain techniques. In order to preserve more edge information, additional edge extraction step is proposed employing high-frequency (HF) sub-band images - low-high (LH), high-low (HL), and high-high (HH) - via the Discrete Wavelet Transform (DWT). In the designed procedure, the LR image is used in the sparse interpolation for the resolution-enhancement obtaining low-low (LL) sub- band. Additionally, all sub-bands (LL, LH, HL and HH) are performed via the Lanczos interpolation. Finally, the estimated sub-band images are used to form the new high-resolution (HR) image using the inverse DWT (IDWT). Experimental results on real data sets have confirmed the effectiveness of the proposed framework in terms of objective criteria as well as in subjective perception.
Motivation of the hate speech perpetrator from the Polish and Greek perspective

Hate speech is a crime that is a serious violation of human rights. Themotivation of the perpetrator in the commission of such an offense are certaincharacteristics of the victim of the crime or the victim’s membership in a particular group, in relation to which the perpetrator feels disinclination. Problemswith the laws protecting human rights corresponding with hate speech inPoland and Greece towards various social groups differ when considering themotivation of the perpetrator. The complexity of hate speech and problemswith the definition of it were studied. Moreover, the attention was focused onthe psychological motivation of the perpetrator. The aim of the study was thecomparison of the penalization of hate speech under Polish and Greek law inthe context of the motivation of perpetrator. It was concluded that the act ofhate speech is always dependent on the context under which it was made, andeach such act should be judged on an individual basis. It has been shown thatthe motivations of the perpetrators of hate speech offenses are closely linkedto sociological and political determinants.
Impact of the COVID-19 pandemic on the digitalization and strategic development of German universities

The HIS-Institute of Higher Education Development (HIS-HE) conducted a nationwide survey among Higher Education leaders about the extent to which the push for digitalization at German higher education institutions related to the COVID-19 pandemic has promoted strategic engagement with digitalization and how such experiences have been integrated into concepts for the future of teaching and learning. The findings show that the effects of the pandemic are most evident in the digitalization of teaching formats, while many infrastructural and technical developments had already been initiated before the pandemic and were at most accelerated. When the COVID-19-related developments of digitalization are analyzed with regard to structural characteristics of the HEIs represented in the sample, it becomes apparent that there are no fundamental differences between universities and universities of applied sciences. Only the universities of arts and music are distinguished by the fact that the pandemic-related changes are generally smaller and fewer innovations are to be expected after the pandemic. The range of disciplines of the HEIs also proves to be relevant when comparing HEIs with and without STEM subjects, as the former group shows a significantly greater dynamic of change. Last but not least, differences can also be found with regard to the existence of a digitalization strategy. Universities with a digitalization strategy not only have a head start in terms of experience, since they already offered online teaching or hybrid formats before the pandemic. Rather, they have changed their teaching and examination formats particularly extensively in the course of the pandemic and are planning to a greater extent to use instruments and formats for digital teaching in the future.
David against Goliath: How a University Cloud Succeeds in the Niche of Higher Education – a User Survey

In the discussion about digital sovereignty, an important goal of the EU, there is always the fear that no one would stand a chance against the big giants from the U.S. which dominate the cloud market thanks to early starts, huge resources and network effects. However, the state-funded open source project “sciebo” proves the opposite, at least in the higher education sector. High data protection is a central argument for using a private cloud service at universities, but this alone does not make it competitive. University-specific functions and integrations – for example in the area of digital teaching or research data management – can be a unique selling point, but for a majority of students and employees the basic sync and share functions seem to be sufficient. So how can a university cloud service compete with commercial offers and what can make it successful in the long term? In a cloud landscape dominated by big players like Microsoft, Apple or Google, who move their established services to the cloud and encourage customers to also use their cloud storage with the arguments of a central account and seamless linkage with their other products, this question needs to be addressed to those at the front line: the users. To investigate the above question, we conducted a user survey, taking the university cloud service “sciebo” as an example, which has been in use at numerous higher education institutions in the German state of North Rhine-Westphalia since 2015.
Critical discourse analysis of cultural representations in EFL national commercial textbooks

Mastering grammar and vocabulary in communication are seemingly insufficient for learners to communicate with different societies worldwide. For this rationale, cultures in ELT materials took a pivotal role in equipping learners with intercultural communicative competence (ICC). Hence, the researchers critically analyze two national commercial textbooks commonly used in senior high schools for the tenth and eleventh grades in any area to examine the elements of cultures and their representations. The researchers address this gap by adopting critical discourse analysis (CDA) to get a profound interpretation of data. The textual data was categorized, coded, counted, and finalized by creating a description. The result revealed that these textbooks contained elements of cultures; product (63%, 44%), person (13%, 42%), practice (19 %, 8%), and perspective (5%, 6%) in different proportions. The result also points out that there is an unbalance among culture-related items with 59%, 51% in source cultures, 11% and 26% in target, and 17% and 8% in international, which means target and international cultures are less than source cultures. This research also found universal cultures relating to cultures free in these textbooks with 13% and 18%, respectively. The finding indicated that both textbooks have imbalanced cultures, which means that target and international cultures were under-represented. The researchers suggest that other Southeast Asian, African, and Russian cultures must be considered in the textbooks. Furthermore, this research expects the stakeholders to be more concerned with designing, concerning, and choosing suitable textbooks to equip learners with diverse cultures.