Reviewerly/exHarmony huggingface dataset:
The Units

Written by a team of experienced teachers of Spanish, this textbook is designed to lead the adult beginner to a comprehensive knowledge of Spanish, giving balanced attention to the four key language skills (speaking, listening, reading and writing). It puts language learning into its real-life context, by incorporating authentic materials such as newspaper articles, poems and songs. It contains a learner and a teacher guide and is intended to complement study both inside and outside the classroom, by providing pair and group activities, as well as materials for independent learning. It also includes helpful reference features, such as a guide to grammatical terms, verb tables, vocabulary lists and a pronunciation guide. This extensively updated second edition features extra exercises to support the acquisition of good pronunciation, and is accompanied by a web companion that hosts expansion exercises, activities, solutions and useful links for each unit, as well transcripts, and access to brand new recordings of all the audio examples found in the book.
Pronunciation

Written by a team of experienced teachers of Spanish, this textbook is designed to lead the adult beginner to a comprehensive knowledge of Spanish, giving balanced attention to the four key language skills (speaking, listening, reading and writing). It puts language learning into its real-life context, by incorporating authentic materials such as newspaper articles, poems and songs. It contains a learner and a teacher guide and is intended to complement study both inside and outside the classroom, by providing pair and group activities, as well as materials for independent learning. It also includes helpful reference features, such as a guide to grammatical terms, verb tables, vocabulary lists and a pronunciation guide. This extensively updated second edition features extra exercises to support the acquisition of good pronunciation, and is accompanied by a web companion that hosts expansion exercises, activities, solutions and useful links for each unit, as well transcripts, and access to brand new recordings of all the audio examples found in the book.
Perceptron

This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This final volume, Learning, builds on the foundational topics established in volume I to provide a thorough introduction to learning methods, addressing techniques such as least-squares methods, regularization, online learning, kernel methods, feedforward and recurrent neural networks, meta-learning, and adversarial attacks. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including complete solutions for instructors), 280 figures, 100 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Foundations and Inference, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, data and inference.
Reconstruction of solar radiation in Tokyo since 1720 based on historical weather records

The impact of climate change on human society has been a significant issue in historical studies and is also vital for future adaptation to climate change. To understand climate change and its devastating impacts on societies in the past, before the start of meteorological observations, the spatial patterns of climate variation must be reconstructed with a higher temporal resolution than those provided by the annual data. Japan has a large volume of records, including those related to daily weather conditions (e.g., "fine", "cloudy", and "rainy"), from the 17th to 19th century.This study has developed a method for estimating solar radiation using daily weather descriptions recorded. Using this method and the daily weather records in historical diaries of Tokyo, Japan, we reconstructed solar radiation fluctuations for the period 1720&amp;#8211;1912, pertaining to the Little Ice Age. We compared our estimations with the observed sunshine duration records of the Japan Meteorological Agency to validate our findings. This method is effective in reconstructing solar radiation for all seasons and allows for the reconstruction of historical climate fluctuations with higher temporal resolution compared with that reconstructed using other methods or proxy data often used previously. In addition, solar radiation is a fundamental factor for not only the energy balance of the Earth but also the hydrological cycle and agricultural productivity.Here, we created a long-time series of solar radiation for the period 1720&amp;#8211;2022 in Tokyo, thereby providing insights into low and high solar radiation for this practical 300-year period. Furthermore, the reconstruction of historical solar radiation fluctuations could enable the exploration of the correlation between climate variations and social changes.
Towards an interoperable digital ecosystem in Earth System Science research

Earth System Science (ESS) relies on the availability of data from varying resources and ranging over different disciplines. Hence, data sources are rich and diverse, including observatories, satellites, measuring campaigns, model simulations, case studies, laboratory experiments as well as citizen science etc. At the same time, practices of professional research data management (RDM) are differing significantly among various disciplines. There are many well-known challenges in enabling a free flow of data in the sense of the FAIR criteria. Such are data quality assurance, unique digital identifiers, access to and integration of data repositories, just to mention a few.&amp;#160;The Helmholtz DataHub Earth&amp;Environment is addressing digitalization in ESS by developing a federated data infrastructure. Existing RDM practices at seven centers of the Helmholtz Association working together in a joint research program within the Research Field Earth and Environment (RF E&amp;E) are harmonized and integrated in a comprehensive way. The vision is to establish a digital research ecosystem fostering digitalization in geosciences and environmental sciences. Hereby, issues of common metadata standards, digital object identifiers for samples, instruments and datasets, defined role models for data sharing certainly play a central role. The various data generating infrastructures are registered digitally in order to collect metadata as early as possible and enrich them along the flow of the research cycle. Joint RDM bridging several institutions relies on professional practices of distributed software development. Apart from operating cross-center software development teams, the solutions rely on concepts of modular software design. For example, a generic framework has been developed to allow for quick development of tools for domain specific data exploration in a distributed manner. Other tools incorporate automated quality control in data streams. Software is being developed following guiding principles of open and reusable research software development.A suite of views is being provided, allowing for varying user perspectives, monitoring data flows from sensor to archive, or publishing data in quality assured repositories. Furthermore, high-level data products are being provided for stakeholders and knowledge transfer (for examples see https://datahub.erde-und-umwelt.de). Furthermore, tools for integrated data analysis, e.g. using AI approaches for marine litter detection can be implemented on top of the existing software stack.Of course, this initiative does not exist in isolation. It is part of a long-term strategy being embedded within national (e.g. NFDI) and international (e.g. EOSC, RDA) initiatives.
A lightweight secure retrieval model applied to intranet

In universities or enterprises that need to establish an intranet to ensure local data security and privacy, intranet users can store their data on the intranet storage server to realize data backup, data confidentiality, dynamic storage space and other services. However, ensuring the integrity and security of data is a concern for most users. Thus, some users encrypt their data and store them in an intranet storage server. In this case, some useful functions (retrieval, sharing, etc.) will be affected. Additionally, increasing users not only pay attention to the security of data but also focus on protecting their data usage habits, such as the protection of retrieval information. To this end, in this study, we propose an intranet service-oriented secure retrieval model by designing a specific indexing method and introducing a semi-trusted server to manage and update the index files, which realizes the protection of retrieval information and the sharing of encrypted data. This model is designed to prevent snooping by intranet server administrators unauthorized users on storing data and retrieving information. In the proposed model, two encryption algorithms the cyphertext policy attribute-based encryption (CP-ABE) and public-key encryption with keyword search (PEKS) algorithms—were used to protect the retrieval information, and the advantages and disadvantages of the two algorithms were discussed. Finally, we performed a complete code implementation of the proposed model. The experimental results show that the proposed model is fast and effective, making it a candidate for use in intranet storage privacy protection. Notably, the proposed retrieval model has been tried by several government-affiliated institutions in Xuzhou city and has received good feedback.
Hate Speech, Subject Agency and Performativity of Bodies

Hate speech is any form of expression that vilifies and discriminates against individuals or groups based on their identity, including race, ethnicity, national origin, gender, sexual orientation, religion, and more. However, hate speech is not merely an emotional expression; it can often be intertwined with fake news and logical reasoning that appears convincing. This article explores Judith Butler's theories on hate speech, how she resists it, and how to draw a good life out of a bad life. Firstly, it examines the limitations of the traditional dichotomy between reason and emotion and how it relates to issues such as hate speech, fake news, and post-truth. Secondly, it analyzes hate speech as either an illocutionary or perlocutionary speech act, and reviews legal cases related to hate speech in the USA through Judith Butler's Excitable Speech(1997). Thirdly, it explores Butler's analysis of Freud's work in The Force Of Nonviolence(2020), including his ideas about the importance of emotional ties and communities of feeling, and how he aimed to overcome blind fury in his later years. The article also discusses how Butler supplements Freud's unfinished research and extends his ideas beyond their original limits. Finally, the implications of these attempts for Korean society, which is currently grappling with the problem of hate speech, are examined in the last section.
Enhancement of Ecoliteracy for Language Learners Using Song Lyrics

This study explores song lyrics to use in language teaching to enhance students’ ecoliteracy while developing their language competency. Today’s language teaching goes beyond language proficiency but capability to address such emerging issues in society as ecological crises. Inclusion of authentic teaching materials like song lyrics may motive learners to be proficient as well as ecoliterate. The method used in this research include data selection, i.e., song lyrics from KePal-SPI, Navicula, and Burgerkill that can be utilized in ELT; data analysis consisting of paraphrasing, speculating, and interpreting of the song lyrics; and evaluating their thematic and linguistic appropriateness for classroom use. The results show that, first, the five song lyrics reveal ecological problems like deforestation and biodiversity loss that the singing artists lament and call for preventive actions. Secondly, song lyrics may offer imaginative use of language that can enable learners to think critically and creatively, hence useful language teaching materials.
Toward Enriched Decoding of Mandarin Spontaneousspeech

A deep neural network (DNN)-based automatic speech recognition (ASR) method for enriched decoding of Mandarin spontaneous speech is proposed. It adopts a two-stage approach to first building a baseline system composed of factored time delay neural networks (TDNN-f) acoustic model (AM), trigram language model (LM), and recurrent neural network language model (RNNLM) to generate a word lattice. It then sequentially incorporates a multi-task Part-of-Speech-RNNLM (POS-RNNLM), a hierarchical prosodic model (HPM), and a reduplication-word LM (RLM) into the decoding process via expanding the word lattice and performing rescoring for improving the recognition performance as well as for enriching the decoding output with syntactic parameters of POS and punctuation (PM), prosodic tags of word-juncture break type and syllable prosodic states, and edited recognition text with reduplication words being eliminated. Experimental results on the Mandarin conversational dialogue corpus (MCDC) showed that SER, CER, and WER of 13.2%, 13.9%, and 19.1% were achieved when incorporating the POS-RNNLM and HPM into the baseline system. They represented relative SER, CER, and WER reductions of 7.7%, 7.9% and 5.0% as comparing with those of the baseline system. Besides, the use of the RLM resulted in additional 3%, 4.6%, and 4.5% relative SER, CER, and WER reductions through eliminating reduplication words.
PENGARUH PENGGUNAAN FERRITE BEAD DAN VARIASI JENIS BUSI TERHADAP TORSI DAN DAYA PADA SEPEDA MOTOR YAMAHA SOUL GT TAHUN 2012

&lt;p&gt;&lt;em&gt;The purpose of this research was to determine: (1) The effect of Ferrite Bead on Torque and Power on the Yamaha Soul GT 2012 motorcycle. (2) the effect of use variations of spark plug type on Torque and Power on the Yamaha Soul GT 2012 motorcycles. (3) The effect of Ferrite Bead and variations of spark plug on Torque and Power on the Yamaha Soul GT 2012 motorcycle. This research is a quantitative type using experimental methods. The data analysis technique used is descriptive analysis. The research was conducted using a DYNOJET tool. The population in this research was the Yamaha Soul GT 2012 motorcycle. From this results of the research, it can be concluded: (1) The use of Ferrite Bead can increase a Torque and Power on Yamaha Soul GT 2012 motorcycle. The results without the use of Ferrite Bead produces a torque of 9,77 N.m at 4502 rpm and power of 7,23 HP at 6107 rpm, while testing using a Ferrite Bead in the middle of the spark plug wire produces a torque of 10,22 N.m at 4660 rpm and power of 7,33 HP at 5438 rpm. There was an increase in torque of 4,61% and an increase of power in 1,38 %. (2) The use of variations of the spark plugs type can increase a torque and power on Yamaha Soul GT 2012 motorcycle. The highest increase in torque and power occurs in the use of Platinum spark plugs. Test result using a Standar spark plug (C7HSA) produce a torque of 9,77 N.m at 4502 rpm and power of 7,23 HP at 6107 rpm, while testing using a Platinum spark plug (CR7HGP) obtained torque of 10,21 N.m at 4650 rpm and power of 7,33 HP at 6209 rpm, and testing using a Iridium spark plug (NGK CR6HIX) obtained torque of 10,04 N.m at 4632 rpm and power of 7,27 HP at 6466 rpm. An increase in torque on the use of platinum spark plugs by 4,5 % and power by 1,38 %. While the increase in torque on the use of iridium spark plugs is 2,76 % and the power is 0,55 %. (3) Interaction of the use of Ferrite Bead and variations of spark plugs type can increase a Torque and Power on Yamaha Soul GT 2012 motorcycle. The test results show the highest Torque and Power namely the use of Ferrite Bead in the middle of spark plugs wire and the use of Platinum spark plugs with a Torque value of 10,38 N.m at 4664 rpm and a power of 7,4 HP at 6294 rpm. There was an increase in torque by 6,24% and an increase in power by 2,4 % from standard conditions.&lt;/em&gt;&lt;/p&gt;
ACADEMIC WORDS IN BUKU BAHASA INGGRIS KELAS XII

Academic Words in Buku Bahasa Inggris Kelas XII. In learning English as a foreign language (EFL), students have to learn vocabulary and its meaning as vocabulary helps them to understand what they hear, to speak in communication, to understand written text and to construct good sentences in writing. In academic field, the words that should be known by the students are academic words. The academic words widely used in academic textbooks and journals named academic word list. Vocabulary Profiler used in this study was a web profiler program developed by Tom Cobb. The profiler is an online program available at www.lextutor.ca/vp. This program helped the researcher to analyze the AWL in a course Buku book Bahasa Inggris kelas XII. The tool counted a total number of words and also the percentage of words appeared: 1000 most frequent words, 2000 most frequent words, academic words, and off list words. The data of the Web Vocabulary Profilers English version 3 described the percentage of AWL in the Buku Bahasa Inggris Kelas XII. For secondary students, course book might be one of the tools to get inputs in term of vocabulary. Asa key component in language class text books have a significant role on language classes. Considering the important role of course book and the necessity of academic vocabulary in a course book, the present study aimed to analyze Academic Words in Buku Bahasa Inggris Kelas XII.
An Improved Imperialist Competitive Algorithm Inspired by Democratic Revolution

The complex continuous optimization problem has a wide variety of practical applications in a range of areas. Swarm intelligence algorithms are promising approaches in solving this kind of problems. However, the optimal solution of this problems requires a balance between diversification and convergence. Considering this requirement, an improved imperialist competition algorithm inspired by the democratic revolution (ICA-IDR) is proposed tentatively. In ICA-IDR, a variable revolution mechanism allows some colonies to develop into sovereignties. The sovereignty is a new evolution entity dedicated to exploration. Two random walk operators, Gaussian walk and Levy flight, are applied to construct the search behavior of sovereignties and to enhance the convergence performance of empire members, respectively. Moreover, sovereignties utilize the information of potential areas obtained exploration to help the trapped empires leave the local optimum. By interactively utilizing the exploration and exploitation capabilities of different entities, the search for the optimal solution is implemented. 30 benchmark functions from the CEC2017 test set have been used to test the ability to solve CEC2017 of the ICA-IDR against 2 modern ICA-based algorithms. These experimental results show the competitiveness and optimize performance of proposed ICA-IDR.
A heterogeneous remote-sensing image matching method based on graph neural networks

To solve the difficulty in matching heterogeneous remote sensing images due to differences in imaging mode, time phase, resolution, etc., a matching method based on graph neural network is proposed. First, the feature point locations are encoded using multilayer perceptron combined with feature descriptors. The new feature vector is then aggregated through the graph neural network to aggregate contextual features and finally, the Sinkhorn algorithm is used to find matching points and eliminate mismatching points between images. The algorithm in this study is tested with multiple sets of heterogeneous remote sensing images and compared with some advanced algorithms. The results show that the algorithm has strong adaptability and provides a good algorithm for robust matching of heterogeneous and different remote sensing images.
Graphs in pattern recognition: successes, shortcomings, and perspectives

Graphs in pattern recognition have been studied since the late seventies with alternating events of successes and failures. Far from wanting to propose a unique survey on the subject, we aim to present the areas in which graphs have been shown to be effective and to illustrate the problems still open in this research domain, with a focus on recent developments moving in the direction of deep learning. This work intends to arouse the interest of neophytes to this interesting domain that is the representation of the world through graphs.
Vision-based toddler physical activity recognition using deep learning

Human activity recognition (HAR) is a system for understanding human movements and behaviour. It has been applied in many fields such as video surveillance, behaviour analysis, and human-computer interaction. The stateof- the-art studies on HAR generally focus their attention on public dataset which mostly consist of adults as their subjects. Research on HAR for children especially toddlers is important to facilitate their surveillance by monitoring their activities automatically. Since toddlers possess different anatomical proportions than adults, their unusual movements can be a challenge to infer. In this paper, a vision-based deep learning HAR system for toddlers was developed based on skeleton features. Videos of toddlers&apos; activities in a day-care were obtained through different public sources. 2D skeleton data were then extracted from every frame of these videos using a pre-trained deep learning network. These skeleton data were trained on LSTM and fully connected network to infer the toddler&apos;s activities. Results showed that this proposed framework managed to achieve 75% accuracies for three toddlers&apos; activities which are jumping, sitting, and standing.
Development of a real time wearable system for monitoring sprint running performance

The main goal of this project is to create a system for tracking 100-meter sprint performance. An athlete&apos;s performance is monitored by a system called a performance monitoring system (PMS). It was challenging for earlier generations to evaluate an athlete&apos;s accomplishments on their own. Athletes can track their performance using the performance monitoring system in ways including total steps, total time, time utilised for each step, and distance used for each step. This prototype consists of two pieces of hardware. One of the pieces of hardware is placed on the shoe of the athlete, with the connection of a FSR sensor and GPS module. The FSR sensor is used to measure the time and the total step, while the GPS module is used to measure the distance used for each step. The data from the FSR sensor and GPS module was sent to an XBEE for real-time display on a laptop. A different outcome will follow from the difference in running behaviour. The accuracy of step detection yielded results that showed 90% of steps were detected at moderate speeds and 93% at high speeds. At low speed and high speed, the time detection accuracy for each step was 96.77% and 92.22%, respectively.