Reviewerly/exHarmony huggingface dataset:
Representation of Dense Volume Datasets Using Pointerless Sparse Voxel Octrees With Variable and Fixed-Length Encoding

The paper deals with the problematics of the dense volume datasets representation, in which voxels are formed as multi-bit scalar values, and is oriented to the use of hierarchical data structures, not only as the medium for encoding and storing of volume datasets, but also for their lossless compression. The main contribution of the paper is in the design of the hierarchical data structure, that allows carving out of subtrees, that are homogenously filled not only by the symbol 0 or symbol 1, but any binary representation of voxel value from defined set of values. Designed data structure provides the possibility of fixed-length and also variable-length (Huffman) encoding of voxel values in leaf node level of the data structure and also in the non-leaf nodes. Results of tests, performed on medical volume datasets that were obtained by various non-invasive imaging techniques, including Computed Tomography and Magnetic Resonance Imaging, along with conclusions that were made, based on the test results, take place in the second part of the paper.
A Study on English Learning Style of High School Students Based on Their English Proficiency

The purpose of this study was to analyze the dimensions of English learning style of students with high English proficiency. To this end, discriminant analysis was conducted to investigate the variables of their English learning style, which played an important role in identifying the students with high English proficiency. Based on Kolb’s (2007) Learning Style Inventory (LSI), a function discriminating the high level students was extracted, whose variables discriminated them with 76.1% accuracy. On their English learning style, the students wanted to grasp the teacher''s expectations accurately, designed and practiced self-directed learning, and attempted to be recognized by teachers and colleagues for their learning. Given these characteristics, a teacher needed to present explicit learning objectives and intention to students so that the students could actively participate in class. In addition, it was necessary to create comfortable conditions that students could fully demonstrate their self-directed learning capabilities in class, and to improve learning efficiency by continuously providing positive feedback to students throughout the class. (Jeonbuk National University)
The Students’ Perception Of Edmodo For English Learning

E-learning is used for information and communication technologies to enable access to online learning/teaching resources (Arkorful & Abaido, 2014). Edmodo, as e-learning-based media, could be used as an alternative platform to help the student as a tool in learning. This research was aimed at finding the students’ perception of Edmodo. Perception is how someone interprets something based on their senses (Linday & Norman, 1997). It is necessary to know how students’ perceptions know how great and successful it is and to know students’ views.  In this research, the researcher used a descriptive-quantitative approach. The samples were eighty-seven students of the eleventh grade at MAN 2 Model Banjarmasin. The researcher used a questionnaire and interview as the instruments. Edmodo is an optional media for teaching, but students still need face-to-face learning. The results showed that most students chose neither agree nor disagree with the statements, which means it does not cause any significant effect.
Unified approach to data-driven quantum error mitigation

Achieving near-term quantum advantage will require effective methods for mitigating hardware noise. Data-driven approaches to error mitigation are promising, with popular examples including zero-noise extrapolation (ZNE) and Clifford data regression (CDR). Here we propose a novel, scalable error mitigation method that conceptually unifies ZNE and CDR. Our approach, called variable-noise Clifford data regression (vnCDR), significantly outperforms these individual methods in numerical benchmarks. vnCDR generates training data first via near-Clifford circuits (which are classically simulable) and second by varying the noise levels in these circuits. We employ a noise model obtained from IBM's Ourense quantum computer to benchmark our method. For the problem of estimating the energy of an 8-qubit Ising model system, vnCDR improves the absolute energy error by a factor of 33 over the unmitigated results and by factors 20 and 1.8 over ZNE and CDR, respectively. For the problem of correcting observables from random quantum circuits with 64 qubits, vnCDR improves the error by factors of 2.7 and 1.5 over ZNE and CDR, respectively.
Learning Long-Term Style-Preserving Blind Video Temporal Consistency

When trying to independently apply image-trained algorithms to successive frames in videos, noxious flickering tends to appear. State-of-the-art post-processing techniques that aim at fostering temporal consistency, generate other temporal artifacts and visually alter the style of videos. We propose a postprocessing model, agnostic to the transformation applied to videos (e.g. style transfer, image manipulation using GANs, etc.), in the form of a recurrent neural network. Our model is trained using a Ping Pong procedure and its corresponding loss, recently introduced for GAN video generation, as well as a novel style preserving perceptual loss. The former improves long-term temporal consistency learning, while the latter fosters style preservation. We evaluate our model on the DAVIS and this http URL datasets and show that our approach offers state-of-the-art results concerning flicker removal, and better keeps the overall style of the videos than previous approaches.
Expert System of Diagnosis of Human Dental Diseases Using The Naïve Bayes Method: Expert System of Diagnosis of Human Dental Diseases Using The Naïve Bayes Method

Teeth are important in the process of breaking down food, but many people do not pay attention to dental health. Unfortunately, most people especially in Indonesia are unconscious and don't really care about the dental health they experience. The main factor is the pattern of consumption of sweet foods and the high cost of consultation with the dentist. Therefore an expert system is needed which is expected to be a solution to diagnose dental disease. The present study applies the Naive Bayes method because it is based on looking at the probabilities that exist in dental disease data through several perceived symptoms. The diagnosis process is carried out by inputting symptoms of the disease then the probability value of each class is calculated then the final result is the disease class that has the highest probability. The test results in this study involved testing data that were able to produce an accuracy of 93% so that the system could be applied to dental disease
Insegnare gli usi dell’italiano istituzionale per la comunicazione pubblica

The Italian university system is organised in three cycles, according to the Bologna’s Process Structure. There are currently 57 Laurea (1st degree) courses in Scienze della Comunicazione (Communication Sciences), and 24 Laurea magistrale (2nd degree) courses in Scienze della comunicazione pubblica, d'impresa e pubblicita (Public and Corporate Communication, Advertising). A Laurea magistrale (2nd degree) in Public and Corporate Communication, Advertising or its equivalent is a requirement for anyone applying for Public Relations (PR) officer positions in the Italian Public Administration. Such jobs entail a full command of a new language variety, Institutional Italian, and yet only 24 out of 4 communication degrees include linguistics or language modules about this specific focus as part of their course structure. The aim of this article is to show why Institutional Italian should be included in the study plan of any future Public Administration (PA) communicator, and it does so by drawing on the experience of teaching two modules at the University of Salerno, Italiano istituzionale (laurea in Scienze della Comunicazione) and Comunicazione pubblica e linguaggi istituzionali (laurea magistrale in Corporate Communication and Media). It outlines the main features of Institutional Italian and it describes how it has been affected by digital innovation and transformation, by the impact of traditional and new media, and by an increased public awareness of plain language as a means of making communication more accessible. Furthermore, it shows that Institutional Italian works on different levels – syntactical, morphosyntactical, lexical, terminological, textual – which serve different pragmatic purposes for different PA communication tasks. Finally, the article provides practical examples on how Institutional Italian can be taught successfully.
Multi-Label Classification Neural Networks with Hard Logical Constraints.

Multi-label classification (MC) is a standard machine learning problem in which a data point can be associated with a set of classes. A more challenging scenario is given by hierarchical multi-label classification (HMC) problems, in which every prediction must satisfy a given set of hard constraints expressing subclass relationships between classes. In this paper, we propose C-HMCNN(h), a novel approach for solving HMC problems, which, given a network h for the underlying MC problem, exploits the hierarchy information in order to produce predictions coherent with the constraints and to improve performance. Furthermore, we extend the logic used to express HMC constraints in order to be able to specify more complex relations among the classes and propose a new model CCN(h), which extends C-HMCNN(h) and is again able to satisfy and exploit the constraints to improve performance. We conduct an extensive experimental analysis showing the superior performance of both C-HMCNN(h) and CCN(h) when compared to state-of-the-art models in both the HMC and the general MC setting with hard logical constraints.
현대중국어 완전문에 대한 소고

This paper discussed a complete sentence and sentence-completing elements in modern Chinese. A complete sentence is the sentence that can be used independently without the help of another language environment. In order for the sentence to become a complete sentence, various sentence-completing elements are involved. Since the sentence-completing elements corresponding to individual sentences may be different, a theory is needed to explain them in an integrated manner.In the text, we discussed some theories like information theory, time anchoring principle, grounding theory, boundary theory. Each of the pros and cons exists, but what is now most widely accepted is the boundary theory. The boundary theory bifurcates nouns, verbs, adjectives and events as being bounded and unbound through the criteria of ''boundaryness''. And according to the boundary theory, there is a tendency to match bounded ones with bounded ones, unbounded ones with unbounded ones.The boundary theory can explain much of the complete sentence by the simple criterion of ''boundaryness''. But as 陆俭明(2014) points out, there are problems that have not yet been solved. Further research is also required on other boundary factors, such as adverb, modal verb, as presented in this paper. This paper raised the possibility of hierarchy between boundary elements through instances. When multiple boundary elements exist in a sentence, the hierarchy can resolve conflicts between them. Thus, the hierarchical problem of boundary element is also a task that the boundary theory should improve in the future.
Approximating LCS in linear time: beating the [MATH HERE] barrier

Longest common subsequence (LCS) is one of the most fundamental problems in combinatorial optimization. Apart from theoretical importance, LCS has enormous applications in bioinformatics, revision control systems, and data comparison programs1. Although a simple dynamic program computes LCS in quadratic time, it has been recently proven that the problem admits a conditional lower bound and may not be solved in truly subquadratic time [2]. In addition to this, LCS is notoriously hard with respect to approximation algorithms. Apart from a trivial sampling technique that obtains a nx approximation solution in time O(n2-2x) nothing else is known for LCS. This is in sharp contrast to its dual problem edit distance for which several linear time solutions are obtained in the past two decades [4, 5, 9, 10, 16].In this work, we present the first nontrivial algorithm for approximating LCS in linear time. Our main result is a linear time algorithm for the longest common subsequence which has an approximation factor of O(n0.497956). This beats the [MATH HERE] barrier for approximating LCS in linear time.
Affixations and Allomorphs in Verbs and Nouns in a Research Abstract: A Morphemic and Morphophonemic Analysis

This study aims to analyze and describe the morphemic and phonemic structuresof verbs and nouns in a research abstract as source of data. The morphemicstructure analysis focuses on the free-bound morphemic affixations of Englishverbs and nouns while the morphophonemic analysis focuses on the allomorphvariations of the inflectional morphemes in English verbs and nouns. Findings ofthe study reveal that majority of the verbs used in the research abstract haveinflectional type of affixations where a bound morpheme is added to the stem assuffix. These morphemes mark tense and number of verbs. The nouns, on theother hand, generally have derivational affixation that involves appending ofsuffixes to the verb form to derive the noun form. This study affirms that Englishverbs and nouns generally have inflectional suffixes to mark grammaticalcategories such as tense and number. In another note, both of the verbs andnouns with inflectional morphemes undergo phonological modifications in termsof their allomorphic variants. The allomorphs [s], [z] and [iz] of the morpheme{s}are used to mark number in nouns and tense in verbs while the allomorphs [d],[ǝd] and [t] of the morpheme {d} mark the tense in regular verbs with inflectionalmorphemes. The allomorphs in both verbs and nouns involve voicing assimilationand dissimilation as phonological processes. The implications of the findings ofthe study would be that second language learners of English need to familiarizethe morphemic structure of words as they can be very helpful in understandingthe meanings of words. Moreover, they have to familiarize the environmentswhere the allomorphic variants of inflectional morphemes are realized so thatthey would be able to pronounce the words correctly. Such interaction ofmorphology and phonology can cause learning difficulty for second languagelearners of English whose first language, like the Cebuano Visayan, is sounded asspelled and is contrary to English which has allophonic and allomorphic variantsoccurring in words. The analysis can therefore be helpful to teachers inidentifying areas of difficulty in learning a second language.
Running control of ACV corresponding to the radius of curvature of the target trajectory

A kind of an air cushion vehicle (ACV) is known as a hovercraft which carries out a cruise by blowing off the air from the bottom of the body. The ACV has many advantages, such as amphibian vehicle, large payload, and so on. However, the ACV has drawbacks such as its drivability is bad. An improvement of the drivability is effective for the control of the ACV and the disturbance rejection performance of the controller is very significant. In this research we make controller that can run along an arbitrary curve whose shape has not been determined in advance and can changes speed of ACV for each radius of curvature. And we verified usefulness of the proposed controller by running the simulation. Using various sensor and image processing technology we get control value which required for controller. We verified usefulness of the proposed methods by executing control experiments.
Needs Analysis of Simulation-Based Construction Services-Tendering Skill Model

Joining the E-Tendering process for construction services requires technical skill (hard skills) and the ability to operate software (soft skills), especially during E-Tendering. However, Diploma 3 of Civil Engineering Study Program students do not acquire these skills in practice, while the world of work requires them to master these skills. For this reason, a simulation-based construction service E-tendering training model was developed. The needs analysis in this developments initial steps was carried out on 30 students and 8 Business and industrial world (DUDI) who became contract award through E-Tendering within the projects scope at Universitas Negeri Padang. The data analysis technique used a percentage formula, and the data is taken through a questionnaire instrument. The results of the analysis state that of the 15 sub-competencies to carry out E- tendering for construction services, none of the students mastery, on average the students ability is in the low category of 63, while the results of the analysis on the perception of the need to take part in the training area at an average score of 93 with the very needy category. The needs analysis results on the four aspects of ability expected by DUDI obtained an average score of 98 in the very high category. Thus, simulation-based E-tendering training for construction services is feasible.
The 2021 Alonzo Church award for outstanding contributions to logic and computation

An annual award, called the Alonzo Church Award for Outstanding Contributions to Logic and Computation, was established in 2015 by the ACM Special Interest Group for Logic and Computation (SIGLOG), the European Association for Theoretical Computer Science (EATCS), the European Association for Computer Science Logic (EACSL), and the Kurt Gödel Society (KGS). The award is for an outstanding contribution represented by a paper or by a small group of papers published within the past 25 years. This time span allows the lasting impact and depth of the contribution to have been established. The award can be given to an individual, or to a group of individuals who have collaborated on the research. For the rules governing this award, see https://siglog.org/alonzo-church-award/, https://www.eatcs.org/index.php/church-award/, and https://eacsl.org/. The 2020 Alonzo Church Award was given jointly to Ronald Fagin, Phokion G. Kolaitis, Renée J. Miller, Lucian Popa, and Wang Chiew Tan for their ground-breaking work on laying the logical foundations for data exchange. Lists containing this and all previous winners can be found through the links above.
Argumentation, Ideology and Discourse in Evolving Specialized Communication

In the digital age, the transformation process of information into ‘knowledge’ is characterized by hyper-connected communities, where a potentially infinite amount of information is ubiquitously accessible to individuals or community users and is instrumental in the creation of shared knowledge, but also in building consensus across community participants, societal membership and grouping, through the argumentative ideological representation of assumptions, values and practices. This Special Issue of “Lingue e Linguaggi” on the theme Argumentation, Ideology and Discourse in Evolving Specialized Communication explores the interface between these three dimensions and combines an array of perspectives into a distinctly unified volume, offering synchronic, diachronic, comparative, interlinguistic and intercultural approaches over a range of specialized knowledge domains. The volume integrates quantitative and qualitative approaches, making use of Corpus Linguistics, alongside other methods incorporated in theoretical approaches such as Critical Discourse Analysis, Appraisal Theory and Argumentation Theory, focusing on the pragma-linguistic features of different texts and genres, together with their ideological purposes for different audiences in various contexts of use. The collection of essays investigates argumentative styles and patterning along with the discursive socio-construction of ideology in the dynamics of recontextualization, rescripting and remediation which affect the multi-faceted nature of contemporary communication.
New Media Making the Society Inclusive

Inclusivism is an important agenda of all governments across the globe. A big chunk of the population in India is beyond the elms of development and learning. The section includes the marginalized, the differentiated, the differently able and discriminated. The traditional media had a choice of directed communication and hold on who to benefit. New media with its all revolutionized features that are dynamic and evolving have made way in accommodating inclusivism into it. A careful and conscious observation of these features may help bring about sustainable development in an inclusive way. The present research attempts to evaluate these features and comprehensively presents a brief overview of the extent of participation through new media by all. The paper attempts to present the contribution of new media in bringing inclusivism in India and in this process lay an outline of the scope of such use for the betterment of the proportion of the society that had been so far excluded from the mainstream. The research is descriptive in nature and is based on secondary data from the authentic sources to develop findings and conclusion.
IDENTIFIKASI KESULITAN MAHASISWA FAKULTAS BAHASA DAN SENI UNIVERSITAS NEGERI SURABAYA DALAM PENYELESAIAN STUDINYA

The study completion in undergraduate program (S1) requires the completion of thesis writing for students. The flow of thesis preparation at the Faculty of Languages and Arts (FBS), Universitas Negeri Surabaya (Unesa), has followed the Thesis Writing Guidebook issued by FBS Unesa. In the manual, the requirements and procedures for writing a thesis are clearly written. But even so, there are still many students who have not been able to complete their thesis writing on time, which hinders the completion of their studies. Therefore, it is necessary to identify students' difficulties in completing their studies, especially at the thesis writing stage. From the results of the distribution of research instruments in the form of questionnaires, it was concluded that there were five categories of difficulties faced by students, namely: 1) Difficulties in submitting / selecting research titles, 2) Difficulties in the consultation process, 3) Difficulties in data collection and processing, 4) Difficulties in the examination process, and 5) Difficulty in the revision process.
LibGuides: Scholarly Communications: Evaluating Journals

Information on the scholarly publishing process including writing and submitting works, evaluating publications and impact metrics, and copyright.
المراجعة وجودة الترجمة / Revision and translation quality

This study aims to address the concept of revision as a critical measure that falls within the translation process by highlighting its impact on the quality of translation, and this is by adopting a descriptive analytical research approach. The study touched on the various concepts and elements related to the revision and the quality of translation. The study concluded that revision contributes significantly to ensuring the quality of translation. However, revision can negatively affect the quality of translation if it is subjective.
LibGuides: Data Management Plan: Create a DMP

This guide introduces what a research data management plan (DMP) is, its content, the rationale of writing a DMP, and resources on DMP.