bluuebunny/crossref_metadata_2025_split huggingface dataset:
Statics and Dynamics of Description
in S.T. Coleridge’s Poem «The Rime of the Ancient Mariner»
Authors: Zinoveva Irina 
Published: December 2022

The research task is to study the nature of the correlation of the three main parts of speech in the text of the poem by S.T. Coleridge’s «The Rime of the Ancient Mariner», one of the first poetic works of English romanticism. Part-of-speech features are involved in the study, reflecting the nominality and nature of
the description: nouns, verbs and adjectives.
The study uses both directly observed frequencies and indexes reflecting them. The absolute frequency numbers of nouns, verbs, and adjectives recorded in each part have been normalized through dividing by the number of words in
each part, which made it possible to obtain comparable data for parts of the poem that differ significantly in volume.
A number of statistical procedures are used for the analysis: Busemann
coefficients, and the coefficient of variation, chi-square test. Their application made it possible to determine the relationship between statics and dynamics in the text. A power function is used to reflect the frequency distribution of nouns,
which proved to be very successful for this material. It allows us to determine the
degree of nominalization of various parts in the poem.
The results of the study indicate a fairly high stability of Coleridge’s style within the framework of the poem in terms of nominalization and dynamics of description. In addition, the article notes strong prevalence of the dynamic description over the static one.
A Letter as a Fact of Literature: Letters by L.Ya. Ginzburg and V.S. Baevsky
Authors: Dvoenko Yana , Zakroeva Galina 
Published: December 2022

he archives of the literary critic V.S. Baevsky are kept in the fonds of the
Literature Museum of Smolensk State University. The materials of the scholar’s
archive have not been presented to the public yet. Meanwhile, the fonds contain
a collection of more than a thousand letters from addressees from all over the
world, including such outstanding scientists of the twentieth century as B.Ya. Bu-
khshtab, M.L. Gasparov, L.Ya. Ginzburg, Yu.M. Lotman, B.F. Egorov and others.
Correspondence was of particular importance for the philologists of that gener-
ation, as it made it possible to combine life, history and science. Comparison of scientific views, the need for an independent censor and
obtaining an objective assessment of scientific works are included in the topics
reflected in the letters from L.Ya. Ginzburg to V.S. Baevsky. Their correspondence
and memoirs testify to the coincident temporal rhythms and allow us to trace the
scientific thought of the scholars that lived almost the entire twentieth century.
This paper reconstructs the role of a letter as a fact of scientific autobiography.
It shows its transformation from the genre of «human documents» (letters and
diaries) into the genre of «intermediate literature» (memoirs). Thus, the personal
letters of L.Ya. Ginzburg acquire the status of a literary fact, since they represent
a narrative unit in V.S. Bayevsky’s life
Features of the Language Assessment Expression
in B. Akunin’s Cycle of Novels about the Nun Pelagia
Authors: Fomina Yulia 
Published: December 2022

The article is devoted to the study concerning the peculiarities of the expression of linguistic evaluation in a literary text. The subject of the study comprises the evaluation tools used in B. Akunin’s cycle of novels about the nun Pelagia when the
writer creates the image of the main character. The purpose of the analysis regarding the means of expressing evaluation is to identify their role in revealing the author’s idea and in the formation of the hero’s image in the literary work, as well as to determine the individual author’s features of language evaluation.
The study of evaluation as a universal category and its reflection in the language is based on the concepts and methods that have become classical in Russian philology (the works of N.D. Arutyunova, E.M. Wolf, A.A. Ivin, etc.), as well as on the achievements of modern research.
The study has found that language evaluation tools play a significant role in revealing the image of the main character in the cycle of novels by B. Akunin. The paper notes two directions of the formation of axiological meanings in creation of the image of the nun Pelagia: an assessment of the appearance and an
assessment of the heroine’s character. The analysis has showed that the linguistic means of expressing evaluation are used in the context of the situation and the heroine’s role (Polina Andreyevna Lisitsyna, brother Pelagius, nun Pelagia). Most often, lexical means of expressing evaluation are used: adjectives, nouns,
adverbs with an evaluative meaning. The use of forms with diminutive suffixes contributes to the formation of evaluative meanings. As the author’s method of expressing evaluation, there is a violation of the norms of lexical compatibility,
which gives uniqueness to the evaluation tools used.
B. Akunin quite actively uses language assessment in describing the appearance, as well as the character and actions of the nun, while there is a discrepancy between the assessment of the external appearance of Pelagia and her internal qual-
ities, which contributes to the implementation of the author’s idea when he creates the image of the main character represented in the cycle of detective novels.
Determinan Penghindaran Pajak dengan Profitabilitas Sebagai Pemoderasi pada Perusahaan Manufaktur
Authors: Manik James , Darmansyah Darmansyah 
Published: December 2022

ABSTRACT
This study aims to examine the potential factors represented by likuidity, sales growth and leverage that are suspected to affect Tax avoidance with Profitability as a moderating variable. Some predictor variables which used this study, liquidity, sales growth & leverage. This research was conducted at Manufacturing companies listed on the Indonesia Stock Exchange in 2015-2018. The number of samples was selected by purposive sampling method is 208 samples from 52 companies for four years. The type of data used is secondary data in the form of financial statements of Manufacturing companies. The data analysis technique used is Moderated Regression Analysis. The results showed that the Liquidity have negative effect on Tax avoidance while sales growth and leverage have significance effect on Tax avoidance. The contribution in this study is Profitability as moderating variable, able to moderate the effect of liquidity, sales growth and leverage on tax avoidance, because profitability is a profit owned by taxpayers which of course will have an impact on the amount of tax burden that must be paid by taxpayers which tends to be avoided. by the taxpayer to be paid.

ABSTRAK
Tindakan penghindaran pajak yang diproksikan dengan likuiditas, pertumbuhan penjualan dan leverage, terhadap penghindaran pajak dengan profitabilitas sebagai variabel moderasi. Penelitian ini dilakukan pada manufaktur yang terdaftar di Bursa Efek Indonesia tahun 2015-2018. Jumlah sampel dipilih dengan metode purposive sampling adalah 208 sampel yang berasal dari 52 perusahaan selama empat tahun. Jenis data yang digunakan adalah data sekunder berupa laporan keuangan perusahaan manufaktur. Teknis analisis data yang digunakan yaitu Moderated Regression Analysis. Hasil penelitian menunjukkan bahwa Likuiditas berpengaruh negatif terhadap penghindaran pajak, sedangkan pertumbuhan penjualan dan leverage berpengaruh positif dan signifikan terhadap penghindaran pajak. Kontribusi dalam penelitian ini adalah, bahwa variabel pemoderasi yaitu Profitabilitas mampu memoderasi pengaruh likuiditas, pertumbuhan penjualan dan leverage terhadap penghindaran pajak, karena profitabilitas merupakan laba yang dimiliki oleh wajib pajak yang tentunya akan berdampak terhadap jumlah beban pajak yang harus dibayar oleh wajib pajak yang cenderung dihindari oleh wajib pajak untuk dibayar.
Data-Driven Variable Impedance Control of a Powered Knee-Ankle Prosthesis for Adaptive Speed and Incline Walking
Authors: Best Thomas , Welker Cara , Rouse Elliott , Gregg Robert 
Published: December 2022

<p> © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. </p>
<p><br></p>
<p> DOI (identifier) 10.1109/TRO.2022.3226887 </p>
<p><br></p>
<p>Abstract:</p>
<p>Most impedance-based walking controllers for powered knee-ankle prostheses use a finite state machine with dozens of user-specific parameters that require manual tuning by technical experts. These parameters are only appropriate near the task (e.g. walking speed and incline) at which they were tuned, necessitating many different parameter sets for variable-task walking. In contrast, this paper presents a data-driven, phase-based controller for variable-task walking that uses continuously-variable impedance control during stance and kinematic control during swing to enable biomimetic locomotion. After generating a data-driven model of variable joint impedance with convex optimization, we implement a novel task-invariant phase variable and real-time estimates of speed and incline to enable autonomous task adaptation. Experiments with above-knee amputee participants (N=2) show that our data-driven controller 1) features highly-linear phase estimates and accurate task estimates, 2) produces biomimetic kinematic and kinetic trends as task varies, leading to low errors relative to able-bodied references, and 3) produces biomimetic joint work and cadence trends as task varies. We show that the presented controller meets and often exceeds the performance of a benchmark finite state machine controller for our two participants, without requiring manual impedance tuning. </p>
Source-free Unsupervised Adaptive Segmentation for Knee Joint MRI
Authors: Li Siyue , Zhao Shutian , Hong Jin , Chen Weitian 
Published: December 2022

<p>Knee osteoarthritis is a prevalent disease worldwide. The automatic segmentation of knee tissues in magnetic resonance (MR) images has important clinical utility in assessing knee osteoarthritis. Deep learning- based methods show great potential in this application, but they often require a large amount of labeled training data, which is challenging and expensive to acquire. Unsupervised domain adaptation that transfers the learned knowledge from a source labeled dataset to a target unlabeled dataset can be used to address this problem. However, in medical scenarios, domain adaption techniques are often limited by access to the source data due to concerns about patient privacy. In this work, we proposed a novel and effective source-free unsupervised domain adaptation method for knee joint multi-tissue segmentation that does not require a source dataset. The proposed framework is split into two stages. In the first stage, matching batch normalization statistics guides the first segmentation network to realize model adaptation and is combined with augmented entropy minimization to obtain pseudo segmentation labels for the target MR images. The pseudo labels generated by the first segmentation network are then refined using a voting strategy to supervise the training of the models in the second stage. In the second stage, uncertainty-aware cross pseudo supervision is used to further boost the performance of the desired segmentation network, which comprises an encoder and a primary decoder. Our experiments demonstrated that the proposed method outperforms the current state-of-the-art source-free unsupervised domain adaptation techniques for segmenting knee tissues in MR images. Our study also demonstrated that the proposed approach is effective in reverse-directional adaptation. </p>
Chance-Constrained Rollover-Free Manipulation Planning with Uncertain Payload Mass
Authors: Song Jiazhi , Petraki Antoine , DeHart Brandon , Sharf Inna 
Published: December 2022

<p>This paper presents a chance-constrained rollover-free manipulation planning method for robotic arms under payload mass uncertainty. The corresponding motion planning problem is stated as a chance-constrained nonlinear optimal control problem (NOCP) subject to kinematics and rollover stability constraints. The latter takes the form of a chance constraint that ensures a certain probability of the robot maintaining dynamic rollover stability in the presence of payload mass uncertainty. To achieve efficient solutions to the NOCP, a novel geometric bound for the stability region is derived. The novel bound is then utilized to modify the rollover-stability constraint. To showcase its benefit, comparisons between the proposed bound of probabilistic rollover stability measure and the naive noise model are provided through statistical analysis. The formulation's practicality is demonstrated through experiments with a Kinova Jaco 2 arm mounted on a free-to-roll platform. Results demonstrate greater robustness of the robot's motion plan to mass uncertainty and computational efficiency of the trajectory generation. </p>
Rate-Splitting Multiple Access-based Cognitive Radio Network With ipSIC and CEEs
Authors: Gao Xuesong , Li Xingwang , Han Congzheng , Zeng Ming , Liu Hongwu , Mumtaz Shahid , Nallanathan Arumugam 
Published: December 2022

<p> In this paper, we study the outage and ergodic rate performance of a rate-splitting multiple access (RSMA)-based cognitive radio (CR) system, where the secondary transmitter aims to communicate with two RSMA users. Imperfect successive interference cancellation (ipSIC) and channel estimation errors (CEEs) are considered in the proposed analysis. Analytical expressions for the outage probability (OP) and the ergodic rate (ER) are calculated. For a deeper understanding, the asymptotic behavior of OP and ER at high signal-to-noise ratio (SNR) regimes are carried out. Illustrative simulation results are presented and reveal that: i) The OP decreases and the ER gradually increases with the increase of SNR, and eventually approaching a constant; ii) ipSIC and CEEs have a negative impact on the considered system; iii) The outage and ergodic rate performance of RSMA-based CR network outperforms CRNOMA network due to flexible power allocation between common and private messages; iv) The OP first decreases and then increases with the power allocated to the common message, and there exists an optimal power allocation factor to ensure the reliable performance. </p>
Are Classifiers Trained on Synthetic Data Reliable? An XAI Study
Authors: IQBAL ASIF , Sikdar Biplab 
Published: December 2022

<p>Machine learning (ML) solutions are being applied in many areas of our daily lives, but they often require high-quality, balanced datasets in order to perform well.</p>
<p>However, datasets for real-world problems are often imbalanced, requiring the use of special-purpose ML algorithms or synthetic data to address the class imbalance.</p>
<p>Traditional techniques such as Synthetic Minority Oversampling Technique (SMOTE) and generative models such as Variational Auto Encoders (VAE) and Generative Adversarial Networks (GAN) are commonly used to generate minority class samples. </p>
<p>Evaluating the quality of synthetic samples can be challenging, and researchers often rely on improved classifier performance as justification for their use. </p>
<p>However, simply performing well on a test set is not sufficient to ensure the trustworthiness of a model, and further analysis of model predictions is necessary. </p>
<p>To address this, we trained multiple classifiers on synthetic data generated by various methods and analyzed their predictions using SHAP, an explainable AI technique. </p>
<p>Our in-depth analysis showed that these classifiers used different features for making predictions and placed different levels of importance on commonly used features. Therefore, we conclude that classification models trained on synthetic data must be carefully analyzed by human experts before being deployed in the real world.</p>
Combining Federated Learning and Edge Computing toward Ubiquitous Intelligence: Challenges, Recent Advances, and Future Directions
Authors: Duan Qiang , Huang Jun , Hu Shijing , Deng Ruijun , Lu Zhihui , Yu Shui 
Published: December 2022

<p>Full leverage of the huge volume of data generated on a large number of user devices for providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to developing UI lies in the involvement of the large number of network devices, which contribute their data to collaborative Machine Learning (ML) and provide their computational resources to support the learning process. Federated Learning (FL) is a new ML method that enables data owners to collaborate in model training without exposing private data, which allows user devices to contribute their data to developing UI. Edge computing deploys cloud-like capabilities at the network edge, which enables network devices to offer their computational resources for supporting FL. Therefore, a combination of FL and edge computing may greatly facilitate the development of ubiquitous intelligence. </p>
<p>In this article, we present a comprehensive survey of the recent developments in technologies for combining FL and edge computing with a holistic vision across the fields of FL and edge computing. We conduct our survey from both the perspective of an FL framework deployed in an edge computing environment (<em>FL in Edge</em>) and the perspective of an edge computing system providing a platform for supporting FL (<em>Edge for FL</em>). From the <em>FL in Edge</em> perspective, we first identify the main challenges to FL in edge computing and then survey the representative technical strategies for addressing the challenges. From the <em>Edge for FL</em> perspective, we first analyze the key requirements for edge computing to support FL and then review the recent advances in edge computing technologies that may be exploited to meet the requirements. Then we discuss open problems and identify some possible directions for future research on combining FL and edge computing, with the hope of arousing the research community’s interest in this emerging and exciting interdisciplinary field. </p>
PREPARASI DAN KARAKTERISASI SUBMIKRO PARTIKEL KITOSAN DAN NATRIUM ALGINAT SEBAGAI PEMBAWA CAPTOPRIL DENGAN VARIASI KITOSAN
Authors: Wahyuni Yenni Sri , Melinda Risya , Rasyad Ade Arinia 
Published: December 2022

Telah dilakukan penelitian mengenai submikro partikel kitosan dan natrium alginat sebagai pembawa kaptopril. Penelitian ini bertujuan untuk mengatasi permasalahan permeabilitas dan memperbaiki absorbsi suatu senyawa makromolekul. Preparasi kaptopril menjadi submikro pertikel dengan polimer penjerap kitosan, natrium alginat dan crosslinking CaCl2 dengan metode gelasi ionik dapat memperbaiki masalah permeabilitas kaptopril. Konsentrasi kitosan yang divariasikan terhadap formula F1, F2 dan F3 berturut-turut adalah 0,1%; 0,2% dan 0,3% menghasilkan persen entrapment efficiency (EE) masing-masing sebesar 69,69%; 76,86% dan 79,2%, distribusi partikel (PDI) dan zeta potensial yaitu 232,0 nm; 0,259; -29,1 mV (F1), 333,8 nm; 0,290; +32,4 mV (F2), dan 426,3 nm; 0,321; +55,6 mV (F3). Formula submikro partikel dapat diperoleh pada formula 3 (kitosan 0,3%). Konsentrasi polimer mempunyai pengaruh penting terhadap persen entrapment efficiency (EE), ukuran pertikel, distribusi partikel, dan zeta potensial dari submikro partikel captopril.
HAMBATAN-HAMBATAN YANG DIALAMI MAHASISWA DALAM PEMBELAJARAN DARING SELAMA PANDEMI COVID-19
Authors: Kolivia  , Nazaryo Radja  , Kelik Wachyudi  , Acep Bahrum Kamil  
Published: December 2022

Pandemi Covid-19 telah memberikan perubahan yang signifikan pada proses belajar dan mengajar. Dengan memperhatikan dampak tersebut maka penelitian ini membahas mengenai hambatan-hambatan yang dialami mahasiswa selama pembelajaran daring. Tujuan penelitian ini adalah untuk menginvetigasi kendala yang selama ini ditemukan selama kegiatan pembelajaran berlangsung. Metode yang diguanakan adalah studi pustaka. Pengumpulan data diperoleh dari artikel penelitian sebelumnya, peneliti mencari artikel yang relevan dengan permasalahan yang sedang diteliti. Teknik analisis data yang digunakan adalah dengan reduksi data, display data, dan penarikan verifikasi kesimpulan. Hasil penelitian menunjukan bahwa terdapat tiga hambatan yaitu: 1) sarana prasarana atau fasilitas yang kurang memadai, 2) kesulitan mahasiswa dalam memahami materi, dan 3) keterbatasan kemampuan dosen dalam memanfaatkan teknologi.
CORRELATION BETWEEN VOCABULARY MASTERY AND READING COMPREHENSION OF EIGHTH-GRADE STUDENTS OF SMP TP. 45 DENPASAR
Authors: Wensislaus Sunardi Woga  , Putri Wirastuti I Gusti Agung , Krismayani Ni Wayan 
Published: December 2022

This study aims to clarify the relationship between vocabulary acquisition and reading comprehension. This study is a correlation study. Samples are selected using a random sampling technique and consist of 30 students. To collect the data, the researchers also used two types of tests. Fill in the blanks for the vocabulary proficiency test and the short answer reading comprehension test. In addition, the data collected were analyzed using the SPSS 20.0 program. The results of the paired sample t-test are bilateral significant values ​​from the student's vocabulary and reading comprehension 010. The results showed that the variances of the significance values ​​of the t-test were relatively equal due to the greater significance. From 0.05. The result of calculating the correlation between the student's vocabulary and reading comprehension in reading comprehension was r = 813. From the results, it can be concluded that there is a significant correlation between vocabulary and reading comprehension in the 8th-grade students of SMP TP.45 Denpasar in 2021/2022.
IMPLEMENTASI GERAKAN LITERASI SEKOLAH (GLS) PADA PEMBEJARAN JARAK JAUH DI SD NEGERI 26 PEMECUTAN
Authors: Ni Nyoman Tri Wahyuni  , Putu Suweka Oka Sugiharta  , I Wayan Eka Biasa  
Published: December 2022

Penelitian ini bertujuan untuk mengetahui implementasi Gerakan Literasi Sekolah (GLS) yang dilaksanakan di SD Negeri 26 Pemecutan pada saat pembelajaran jarak jauh dengan menggunakan pendekatan deskriptif kualitatif. Data ini dikumpulkan dengan teknik observasi non partisipan, wawancara tak terstruktur, angket tertutup, dan kuisioner terbuka. Pandemi Covid-19 menyebabkan kegiatan pembelajaran tidak dapat dilaksanakan secara tatap muka, kegiatan pembelajaran dilaksanakan jarak jauh. Demikian pula pelaksanaan Gerakan Literasi Sekolah (GLS) tidak dapat dilaksanakan seperti biasanya. Di SD Negeri 26 Pemecutan sebelumnya dilaksanakan kegiatan literasi dengan kegiatan membaca 15 menit sebelum pembelajaran dimulai serta kunjungan rutin ke perpustakaan seminggu sekali, namun pada pembelajaran jarak juah tidak dapat dilaksanakan kegiatan-kegiatan tersebut. Pada saat pembelajaran jarak jauh Gerakan Literasi Sekolah (GLS) di SD Negeri 12 Pemecutan dilaksanakan dengan berbagai kegiatan seperti literasi di awal pembelajaran, pelatihan membaca nyaring untuk siswa, orang tua, dan guru, guru melakukan apersepsi, sekolah aktif dalam kegiatan festival literasi sekolah serta peserta didik membuat video bercerita. Kegiatan ini diharapakan dapat meningkatkan kemampuan literasi peserta didik meskipun dilaksanakan secara jauk jauh.