Reviewerly/exHarmony huggingface dataset:
Retracted: The Effect of Introducing Infographic Pattern on Developing Cognitive Understanding by Using AI Technology for University Students during the COVID-19 Pandemic

[This retracts the article DOI: 10.1155/2021/7197224.].
Retracted: Application of Laparoscopy in Comprehensive Staging Operation of Ovarian Cancer Based on Electronic Medical Blockchain Technology

[This retracts the article DOI: 10.1155/2021/6649640.].
Perceptions of EFL students on e-book based extensive reading at a tertiary level

Printed reading texts have been transformed drastically which allows readers to read books in an electronic format flexibly. Reading e-books extensively has received much attention globally thanks to their advantages such as portability, convenience and affordability. Likewise, the popularity of extensive reading programs has increased dramatically. Correspondingly, the number of publications related to e-books and extensive reading has risen tremendously which has urged the researcher to combine both in a single study. In this respect, the current study was conducted to pinpoint the perceptions of students who joined an e-book based extensive reading program at TISHK International University within 2022-2023 Academic Year in Erbil, Iraq. 50 freshman students were chosen by adopting convenience sampling method, and the data were collected via an extensive questionnaire, a survey and interview. The data collection process which included the instruments of a mixed methods design within 11 weeks through SPSS 23 and NVivo revealed that e-book based extensive reading improved students’ performance, increased their motivation, facilitated overcoming language learning anxiety and changed overall attitudes towards learning English with reading e-books extensively. The findings of this study can have some implications for researchers who are planning to conduct an e-book-based ER instruction at their institutions.
Retracted: Comparison of the Meta-Active Machine Learning Model Applied to Biological Data-Driven Experiments with Other Models

[This retracts the article DOI: 10.1155/2021/8014850.].
Retracted: Image Retrieval Using Different Distance Methods and Color Difference Histogram Descriptor for Human Healthcare

[This retracts the article DOI: 10.1155/2022/9523009.].
Retracted: Design of an Interactive Two-Way Telemedicine Service System for Smart Home Care for the Elderly

[This retracts the article DOI: 10.1155/2021/6632865.].
Retracted: Visual Information Features and Machine Learning for Wushu Arts Tracking

[This retracts the article DOI: 10.1155/2021/6713062.].
The Effects of Thematic Progression in Improving Coherence and Cohesion in EFL Writing

From general observations, the writing produced by EFL students is rather difficult for native English speakers to follow due to its lack of coherence and cohesion. This problem is believed to be minimized by applying Thematic progression theory. This action research was conducted with the purpose to measure to what extent the use of thematic progression could improve coherence and cohesion in writing. Moreover, it also fulfills two sub-tasks which are identifying common theme-rheme problems and clarifying students&amp;rsquo; difficulties when applying thematic progression in writing. To reach the answers, the action research was carried out with six-week execution and 20 participants, using both quantitative data (namely numbers of theme-rheme problems and coherence/cohesion scores) and qualitative data (students&amp;rsquo; journals). The findings showed that by learning thematic progression, students&amp;rsquo; coherence and cohesion band scores could be upgraded by approximately one band. Besides, inappropriate textual theme and empty theme were found to be the main theme-rheme problems. In addition, the shortage of ideas and inflexibility in using grammatical structure were discovered to be hurdles for students to employ the theory in their writing.
Retracted: Analysis on Health Information Acquisition of Social Network Users by Opinion Mining: Case Analysis Based on the Discussion on COVID-19 Vaccinations

[This retracts the article DOI: 10.1155/2021/2122095.].
Retracted: Martial Arts Routine Training Method Based on Artificial Intelligence and Big Data of Lactate Measurement

[This retracts the article DOI: 10.1155/2021/5522899.].
Retracted: Study on Collision Detection and Force Feedback Algorithm in Virtual Surgery

[This retracts the article DOI: 10.1155/2021/6611196.].
Retracted: Determinants of the Intention to Use Smart Healthcare Devices: A Framework and Public Policy Implications

[This retracts the article DOI: 10.1155/2021/4345604.].
Retracted: Home Interactive Elderly Care Two-Way Video Healthcare System Design

[This retracts the article DOI: 10.1155/2021/6693617.].
Introduction of digital technologies in education - Concepts and experiences

During the last decades technologies of information and communication technologies made a lot of progress, which increased the quantity and quality of distance education programs and the upcoming blended learning models. However, some basic difficulties in defining meaningful terms instead of buzzwords, often used in the present debate, will be discussed to raise consciousness of the rather vague terminology. The progress of digital technologies offered also a chance for better inclusion of disadvantaged parts of the population. The focus lies on the young generation of school attendants and how technology-oriented programs can provide better inclusion. We put a regional focus on development in Latin America. To highlight some of the issues discussed before, we will present a detailed case study about the Argentinean project “ConectarIgualdad”. We have also added a brief comparison with some other Latin American Initiatives. Summarizing we list considerations for a successful inclusive application of digital technologies in education.&#x0D;
Analisis Efektivitas Penggunaan Teknologi dalam Pendidikan Terhadap Peningkatan Hasil Belajar

This research aims to analyze the effectiveness of technology use in education on improving students' learning outcomes. The research method used is literature review by collecting data from various sources related to the use of technology in education. The results of the study indicate that the use of technology in education can significantly improve students' learning outcomes, especially in developing cognitive skills and critical thinking. In addition, technology can also help improve the efficiency and effectiveness of the learning process. However, the use of technology in education also has challenges and risks that must be well managed. Therefore, the use of technology in education must be carefully selected and integrated to achieve optimal results.
Analisis Penerapan Teknologi dalam Pembelajaran dan Dampaknya terhadap Hasil Belajar

The aim of this research is to analyze the implementation of technology in learning and its impact on student learning outcomes. The method used is a literature study by collecting data from journals and articles related to the implementation of technology in learning. The results show that the use of technology in learning can provide advantages such as increasing the efficiency and effectiveness of learning, facilitating learning skills, and enriching learning content. However, the use of technology also has disadvantages or negative effects such as dependence on technology and potential disruption of concentration. Therefore, the use of technology in learning needs to be managed properly and balanced, as well as developing balanced learning and digital skills for students.
Translating Academic Texts: An Analysis of Translations Solutions

This research aims to investigate the translation strategies employed by translators in translating the abstracts of undergraduate theses. Specifically, the study focuses on the techniques or translation solutions utilized by translators when handling various topics of thesis abstracts, using Pym's (2016) translation solution theory as a framework. The research adopts a descriptive qualitative approach, and data collection is done through documentation, using two forms of thesis abstracts: the original abstract written in Bahasa Indonesia and its translated version. The study reveals the presence of seven types of translation solutions used in the selected abstracts data, namely: copying words, copying structure, perspective change, density change, compensation, cultural correspondence, and text tailoring. Among these types, text tailoring emerged as the most dominant translation solution. This study provides insights into the translation strategies adopted by translators in handling undergraduate thesis abstracts. The findings of this study could be useful for future research on translation and also for improving the quality of translations in academic settings. Keywords: Pym’s translation solution typology, translation errors, thesis abstract
TWOFOLD FACE DETECTION APPROACH IN GENDER CLASSIFICATION USING DEEP LEARNING

Face classification is a challenging task that is crucial to numerous applications. There are many algorithms for classifying gender, but their ability to evaluate their effectiveness regarding scientific data is constrained. Deep learning is popular among researchers in face classification problems. The detection of many faces is complicated and becomes a necessity in real problems. The proposed research aims to examine the effect of twofold face detection approach on the accuracy of gender classification, as well as the effect of using small datasets on accuracy. In this study, we use a small dataset to classify facial images based on their gender. The following phases involve deep learning methods along with the OpenCV library version 3.4.2 which is recommended to serve as a twofold face detection approach. In the experiments conducted, Phase 1 is the designated training phase, and Phase 2 serves as a testing phase. Two different algorithms are used in the testing phase to detect one face in the image (Experiment 1), while the remaining algorithm detects multiple faces in the image (Experiment 2). The FEI dataset is used to evaluate the accuracy of the proposed research, which results in 84% accuracy for Experiment 2 and 74% for Experiment 1, respectively.
WAVELET NEURAL NETWORKS VERSUS WAVELET-BASED NEURAL NETWORKS

This is the first paper in a sequence of studies including also [33] and [34] in which we introduce a new type of neural networks (NNs) -waveletbased neural networks (WBNNs) -and study their properties and potential for applications.We begin this study with a comparison to the currently existing type of wavelet neural networks (WNNs) and show that WBNNs vastly outperform WNNs.One reason for the vast superiority of WBNNs is their advanced hierarchical tree structure based on biorthonormal multiresolution analysis (MRA).Another reason for this is the implementation of our new idea to incorporate the wavelet tree depth into the neural width of the NN.The separation of the roles of wavelet depth and neural depth provides a conceptually and algorithmically simple but very highly efficient methodology for sharp increase in functionality of swarm and deep WBNNs and rapid acceleration of the machine learning process.
A comparison of point-tracking algorithms in ultrasound videos from the upper limb

Abstract Tracking points in ultrasound (US) videos can be especially useful to characterize tissues in motion. Tracking algorithms that analyze successive video frames, such as variations of Optical Flow and Lucas–Kanade (LK), exploit frame-to-frame temporal information to track regions of interest. In contrast, convolutional neural-network (CNN) models process each video frame independently of neighboring frames. In this paper, we show that frame-to-frame trackers accumulate error over time. We propose three interpolation-like methods to combat error accumulation and show that all three methods reduce tracking errors in frame-to-frame trackers. On the neural-network end, we show that a CNN-based tracker, DeepLabCut (DLC), outperforms all four frame-to-frame trackers when tracking tissues in motion. DLC is more accurate than the frame-to-frame trackers and less sensitive to variations in types of tissue movement. The only caveat found with DLC comes from its non-temporal tracking strategy, leading to jitter between consecutive frames. Overall, when tracking points in videos of moving tissue, we recommend using DLC when prioritizing accuracy and robustness across movements in videos, and using LK with the proposed error-correction methods for small movements when tracking jitter is unacceptable.
A study of conceptual language similarity: comparison and evaluation

An interesting line of research in natural language processing (NLP) aims to incorporate linguistic typology to bridge linguistic diversity and assist the research of low-resource languages. While most works construct linguistic similarity measures based on lexical or typological features, such as word order and verbal inflection, recent work has introduced a novel approach to defining language similarity based on how they represent basic concepts, which is complementary to existing similarity measures. In this work, we study the conceptual similarity in detail and evaluate it extensively on a binary classification task.
An improvement of Random Node Generator for the uniform generation of capacities

Capacity is an important tool in decision-making under risk and uncertainty and multi-criteria decision-making. When learning a capacity-based model, it is important to be able to generate uniformly a capacity. Due to the monotonicity constraints of a capacity, this task reveals to be very difficult. The classical Random Node Generator (RNG) algorithm is a fast-running speed capacity generator, however with poor performance. In this paper, we firstly present an exact algorithm for generating a $n$ elements' general capacity, usable when $n < 5$. Then, we present an improvement of the classical RNG by studying the distribution of the value of each element of a capacity. Furthermore, we divide it into two cases, the first one is the case without any conditions, and the second one is the case when some elements have been generated. Experimental results show that the performance of this improved algorithm is much better than the classical RNG while keeping a very reasonable computation time.
Differentially Private Medians and Interior Points for Non-Pathological Data

We construct differentially private estimators with low sample complexity that estimate the median of an arbitrary distribution over $\mathbb{R}$ satisfying very mild moment conditions. Our result stands in contrast to the surprising negative result of Bun et al. (FOCS 2015) that showed there is no differentially private estimator with any finite sample complexity that returns any non-trivial approximation to the median of an arbitrary distribution.
Evaluating Model Performance in Medical Datasets Over Time

Machine learning (ML) models deployed in healthcare systems must face data drawn from continually evolving environments. However, researchers proposing such models typically evaluate them in a time-agnostic manner, splitting datasets according to patients sampled randomly throughout the entire study time period. This work proposes the Evaluation on Medical Datasets Over Time (EMDOT) framework, which evaluates the performance of a model class across time. Inspired by the concept of backtesting, EMDOT simulates possible training procedures that practitioners might have been able to execute at each point in time and evaluates the resulting models on all future time points. Evaluating both linear and more complex models on six distinct medical data sources (tabular and imaging), we show how depending on the dataset, using all historical data may be ideal in many cases, whereas using a window of the most recent data could be advantageous in others. In datasets where models suffer from sudden degradations in performance, we investigate plausible explanations for these shocks. We release the EMDOT package to help facilitate further works in deployment-oriented evaluation over time.
Pelatihan Penerapan Metode Full Costing Dalam Perhitungan Harga Pokok Penjualan Untuk Penetapan Harga Jual Produk

The calculation and drafting of cost of goods is an important matter. So that the business owner does not experience a loss, the selling price of an item cannot be determined arbitrarily. Many business owners do not know how to determine the selling price because they do not know the concept of calculating the cost of goods sold (COGS) for the resulting products. Cost of Goods Sold (COGS) is the amount of expenditure and expenses that are allowed, either directly or indirectly, to produce goods or services in the conditions and places where the consumer can sell or use the goods. So there are important benefits that business owners must realize that the Cost of Goods Sold (HPP) must be recorded and calculated properly, so that the selling price is correct. The method used was short training and mentoring which was carried out with individual and classical approaches. The results of this service are expected to provide knowledge and insight for business owners so that they can use financial information carefully for decision making and be able to apply bookkeeping in good business management.Keywords: Full Costing, Cost of Goods Sold, Selling Price
ENVIRONMENTAL MONITORING WITH MACHINE LEARNING

The term environmental monitoring refers to the practice of keeping tabs on and assessing the state of both natural and built environments. The purpose of environmental monitoring is to gather information that may be utilized to spot patterns, hazards, and improvement avenues. Because they can analyse enormous volumes of data and identify complicated patterns that may not be clearly detectable using conventional methods, machine learning techniques may be particularly successful for environmental monitoring. The lack of a reliable method to gather complete data, and the overall lack of data openness, is the main problem with the status quo. These environmental data are often collected in siloed units, requiring time and money from environmental protection agencies before they can be made public. In this study, we will look at how machine learning may be put to use in environmental surveillance. Two recent cases will be discussed briefly within the framework of our paper before we wrap things up.
EVALUASI KINERJA SALURAN IRIGASI DAN BANGUNAN DISTRIBUSI PADA DAERAH IRIGASI AIR NAKAI BATU ROTO BENGKULU UTARA

This study intends to analyze the dimensions of the channel, subdivision, and tapping infrastructure. The mainstay discharge was analyzed using the Mock method, the analysis of irrigation water needs was based on Irrigation Planning Standard KP-01, and recalculation of the dimensions of the channel, building for, and tapping building based on the existing discharge and the planned discharge in accordance with Irrigation Planning Standard KP- 03. Rainfall data were analyzed using the algebraic average method. The findings indicated that the highest primary discharge, which occurred in November period I, was 9.21 m3/s. The highest amount of clean water needed in the fields per day (NFR) was 7.55 mm, while the maximum amount of water needed for intake per second (DR) was 1.34 l/sec. The bottom width of the channel (b) is 2.26 m according to the findings of recalculating the BNa 1 primary channel's dimensions using the current discharge. Na.2Ki.A secondary channel measured 0.48 meters for channel bottom width (b). The bottom width of the channel (b) was determined to be 0.601 m as a consequence of recalculating the BNa 1 primary channel's dimensions using the intended discharge. Na.2Ki.A secondary channel measured 0.44 meters for channel bottom width (b). The measurements of the width of the buildings door (b) after being recalculated and tapped based on the current discharge are larger than those of the door's existing dimensions. Keywords: Water Discharge, Irrigation Channels Area, Distribution Building
INTERDISCIPLINARY APPROACH TO CURRICULA DEVELOPMENT IN GEOMATICS EDUCATION: ERASMUS+ LBS2ITS PROJECT

Abstract. LBS2ITS is a Curricula Enrichment delivered through the Application of Location Based Services to the Intelligent Transport Systems project funded by the Erasmus+ programme. The main goal of the LBS2ITS project is the development of the new and the modernisation of the existing curricula in four Sri Lankan universities. The project takes an interdisciplinary approach and is currently developing curricula on topics of Location Based Services and Intelligent Transportation Systems from the perspective of disciplines such as geomatics, cartography, transport engineering, urban planning, environmental engineering and computer science. In the paper, we detail our approach to curricula modernisation and development in two phases: teacher training and development. We also provide more details and theoretical backgrounds for the methodologies such as Problem Based Learning, Problem Based e-Learning, and Quality Aassurance in teaching.
A Multimodal Move Analysis of Graphical Abstracts in Medicine and Chemistry

Graphical abstracts (GAs), as other new digital forms of communicating science, have been promoted as tools to escalate the reach of journal articles and move science into unconventional environments such as social media.Despite the rapid and widespread adoption of the GA in various fields, its genre status is still controversial due to its unstable structure and functions.Here, we examine the move structure of 100 GAs published in 2022 in 10 high impact journals in medicine and chemistry.We aim to verify adherence to the Introduction-Methods-Results-Discussion pattern and the role of visual and written resources in move realization.We also discuss selections of multimodal resources that may result from the processes of recontextualization of scientific discourse to audiences other than expert peers.Our findings reveal that move structure varies across fields: in chemistry, only Results are obligatory, while in medicine the obligatory pattern is Methods-Results-Conclusion.Move realization in predominantly multimodal, with visual resources as the key element in the presentation of Methods and Results, while the written mode is characteristic of Conclusion.Acknowledgment of readers other than the peer scientist is evident in three medicine journals whose GAs are not produced by the author of the respective articles, but by graphic designers.