Reviewerly/exHarmony huggingface dataset:
A Strategic Study on Improving the Professional Core Quality of Primary and Secondary School English teachers

This paper first introduces the system structure of English teachers' professional core literacy, and then analyzes the importance of improving professional core literacy. To meet the needs of improving the core literacy of English teachers, this paper puts forward a variety of strategies, including extensive reading of professional data, collective discussion by teachers, optimization of teaching methods according to the situation of students, construction of a multi-faceted English teaching evaluation system and integration of teaching and research on the core literacy of English teachers. It is hoped that these strategies can contribute to the reform and development of English education and help English teachers to continuously improve their professional core qualities.
Robust IMM Filtering Approach with Adaptive Estimation of Measurement Loss Probability for Surface Target Tracking

A suitable jump Markov system (JMS) filtering approach provides an efficient technique for tracking surface targets. In complex surface target tracking situations, due to the joint influences of lost measurements with an unknown probability and heavy-tailed measurement noise (HTMN), the estimation accuracy of conventional interacting multiple model (IMM) methods may be seriously degraded. Aiming to address the filtering issues in JMSs with HTMNs and random measurement losses, this paper presents an IMM filtering approach with the adaptive estimation of unknown measurement loss probability. In this study, we assumed that the measurement noises obey student’s t-distributions and then proposed Bernoulli random variables (BRVs) to characterize the random measurement loss. Notably, by converting the two likelihood functions from the weighted sum form to exponential multiplication, we established hierarchical Gaussian state space models to directly utilize the variational inference method. The system state vectors, unknown distribution parameters, BRVs, and unknown measurement loss probabilities were estimated simultaneously according to the variational Bayesian inference in the IMM framework. The results of maneuvering target tracking simulations verified that the presented filtering approach demonstrated superior estimation accuracy compared to existing IMM filters.
Prediksi Jumlah Mahasiswa Baru Fti Usn Kolaka Menggunakan Metode Single Exponential Smoothing

The FTI student admission target every year is often not achieved. This happened because of the change in FTI's location, from USN Kolaka which was in Kolaka to USN Kolaka which was in Tanggetada. In addition, there are also other causes in terms of the large number of students who do not graduate on time, causing an unbalanced ratio of lecturers and students. This will reduce the assessment at the time of accreditation. Predictions are made to assist FTI in planning and making decisions to determine priorities for how many prospective students will be accepted each year. The observational data used are data on the number of new FTI students for the 2013-2021 academic year (9 periods) for the Information Systems study program and the 2018-2021 academic year (4 periods) for the Computer Science study program. Data processing is carried out using the Single Exponential Smoothing Method and MAPE (Mean Absolute Percent Error) accuracy testing. The results of testing this method are that for the information systems study program the predicted results obtained in the 2022/2023 academic year are 141 people, and the smallest value of MAPE = 26.67% which shows the ability of the forecasting model to be quite good (Reasonable). Meanwhile, for the computer science study program, the prediction results obtained in the 2022/2023 academic year were 116 people, and the smallest value of MAPE = 18.52%, which indicates a good forecasting model ability.
Understand the intersection of disability harassment and free speech

Disability harassment is a common problem on college campuses. However, colleges and universities sometimes have difficulty identifying and addressing such harassment, especially when it involves speech.
Artificial Intelligence in Evidence-based Medicine: Challenges and Opportunities

Evidence-based Medicine (EBM) is facing a new challenge in applying Artificial Intelligence (AI) for better services. Here the fundamental question is: can AI be used as a human intelligence amplifier to make better evidence-based medical decisions? This argument can only be answered if AI-supported decisions are compared and contrasted with those of human experts, and if the implementation of AI-enabled Evidence-Based Medicine (AiEBM) can be explained or justified using the available evidence and experience. In this paper, we propose AiEBM as a human-centered approach to be integrated into processes of healthcare systems, thereby increasing the credibility of the clinical decision support systems. We provide insights into the applicability of AI and its challenges and opportunities in EBM. The AaaS (AI as a Service) and high-order reasoning facilitated by machine learning and AI for medical decisions will be discussed.
Features of reforming the systems of sculpture teaching at art universities and non-art universities in modern China

The aim of the study is to characterize the current stage of reforming the system of higher art education in China by the example of the system of future sculptors training. The paper discusses the features of future sculptors training at Chinese art universities and non-art universities, as well as the specifics of organizing the process of their training in accordance with the principles of urban sculpture development. The study is novel in that it is the first to reveal the connection of the existing training programs for sculptors in China with the tasks of modern urban planning and urban environment design. As a result of the analysis, it has been determined that at Chinese art universities and non-art universities, a special institutional environment and a system of practical implementation of students’ ideas are being built in accordance with modern conditions. Based on the results obtained, methodological recommendations are proposed for organizing the training of future sculptors by means of design engineering, which can be implemented in the space of Russian specialized universities.
Structural Analysis of Hydrodynamical Interaction of Full-Submerged Archimedes Screws of Rotary-Screw Propulsion Units of Snow and Swamp-Going Amphibious Vehicles with Water Area via Methods of Computer Simulation

The paper considers the problems of estimation and provision of efficiency of rotary-screw propulsion units (RSP) for snow and swamp-going amphibious vehicles. The performance curves of fully submerged Archimedes screws of RSP are presented with parameters typical for snow and swamp-going amphibious vehicles. These parameters were obtained from the results of computer simulation. For a wide range of performance modes, the impact of particular elements of Archimedes screws on the general efficiency of the propulsion unit is analysed. According to the results of analysis of data received, lines of further research will aim to increase the efficiency of RSP when moving afloat.
Linguistically aware evaluation of coreference resolution from the perspective of higher-level applications

Abstract Coreference resolution is an important part of natural language processing used in machine translation, semantic search, and various other information retrieval and understanding systems. One of the challenges in this field is an evaluation of resolution approaches. There are many different metrics proposed, but most of them rely on certain assumptions, like equivalence between different mentions of the same discourse-world entity, and do not account for overrepresentation of certain types of coreferences present in the evaluation data. In this paper, a new coreference evaluation strategy that focuses on linguistic and semantic information is presented that can address some of these shortcomings. Evaluation model was developed in the broader context of developing coreference resolution capabilities for Lithuanian language; therefore, the experiment was also carried out using Lithuanian language resources, but the proposed evaluation strategy is not language-dependent.
Present-day “mise-en-sonore”: hearing our digitally mediated milieu <b>The auditory setting: environmental sounds in film and media arts</b> , by Budhaditya Chattopadhyay, Edinburgh, Edinburgh University Press, 2021, 224 pp., £19.99 (pb); £90.00 (hb); £90.00 (ePub); £90.00 (PDF), ISBN 9781474474399 (pb); 9781474474382 (hb); 9781474474412 (ePub); 9781474474405 (PDF)

Click to increase image sizeClick to decrease image size Additional informationNotes on contributorsNick PoulakisNick Poulakis (PhD in Ethnomusicology and Cultural Anthropology) serves as a staff member of the Ethnomusicology and Cultural Anthropology Laboratory at the Department of Music Studies of the National and Kapodistrian University of Athens, where he teaches film music, ethnographic cinema, and applied ethnomusicology. He is also an adjunct instructor in the Modern Greek Culture Program of the Hellenic Open University. He has been involved in various research and artistic projects and has written several articles and book chapters on ethnomusicological films, video life-stories of migrants, anthropology of film and TV music, media education, and audiovisual literacy. His recent publications in Greek include Musicology and Cinema: Critical Approaches to the Music of Modern Greek Films, Music from Optical Theater and Silent Cinema, and World Musics: Soundscapes, Identities, and Practices.
Empowering boards: How the National Cyber Security Centre Board (United Kingdom) toolkit is transforming cyber security governance

Dear Editor, the article, “The crippling effects of a cyberattack at an academic level 1 trauma centre” [ [1] Tarka M. Blankstein M. Schottel P. The crippling effects of a cyberattack at an academic level 1 trauma center: an orthopedic perspective. Injury. 2023 Apr; 54 (Epub 2023 Feb 10. PMID: 36801172): 1095-1101https://doi.org/10.1016/j.injury.2023.02.022 Abstract Full Text Full Text PDF PubMed Scopus (1) Google Scholar ], in your latest edition, was a traumatic read, unfortunately it is generally felt that the number of cyber-attacks is going to increase as the technology advances. There is a help at hand, which I will summarise.
Geochemical and mineralogical evaluation of Libale iron- rich manganese deposit, North-central Nigeria

The iron-rich manganese deposits of Libale area is located within the basement complex of North-central Nigeria. Mineralogically, the major mineral phases are: goethite (Fe2O3.H2O), spessartine (Mn32+Al2(SiO4)3), hematite (Fe2O3), and quartz (SiO2), while minor mineral phases are orthoclase (Al2O3.K2O.6 SiO2), illite (KAl2Si3AlO10(OH)2), and manganite (Mn2O3.H2O) suggesting a trend of mineral assemblage attributed to the differential mineralization of the iron-manganese deposit that may have been caused by the geochemical tectonic activity during its formation. Geochemically, on average, the Fe2O3, SiO2, Al2O3, CaO, P2O5 content are 34.59 wt.%; 26.30 wt.%; 6.94 wt%, 2.60 wt%, 2.01 wt% correspondently while K2O and TiO2 are less than 1wt%. Suggesting oxide facies type for the deposit. The trace element composition of V (1040 ppm), Cr (100 ppm), Co (833.33 ppm), Cu (1740 ppm), Nb (1280 ppm), W (240 ppm), Ta (320 ppm) and Zr (302 ppm) were relatively high compared to Maro, Muro and Kakun BIFs in North-central Nigeria. Bivariate plot of Fe2O3 Vs. Al2O3, suggest enrichment of Fe2O3 but depleted in SiO2 and Al2O3, which possibly indicates replacement of precursor silica and kaolinite with goethite which are subsequently dehydrated to hematite. Al2O3-SiO2-Fe2O3 ternary diagram indicates Precambrian Banded Iron Formation (BIF) for the Libale iron- rich manganese deposits, this was confirmed by MnO Vs. FeO. Discriminative plots: FeO. SiO2 - (FeO + MnO) - Fe2O3 and Al2O3+ K2O + Na2O Vs. MnO + FeO confirmed mixed facies as the analyzed data plots between silicate facies and magnetic-silicate facies, this is linked to chemical association between Al2O3 and SiO2 for the iron-rich as it confirms a transitional grade of silicate facies to magnetite-silicate facies. SiO2 Vs. Al2O3 plot revealed hydrothermal and diagenetic processes for its deposition. The iron-rich manganese deposit is of low grade iron (Av. Fe=24.19%) characterized by ferruginous manganese (Av. MnO2=23.82%) based on the generalized percentages of element of major interest in assessing quality of iron and manganese ore, therefore, good for cast iron production.
Development of AI·Digital Competency Structure for Art Teachers

디지털 대전환 시대에 맞춰 교수학습방식의 근본적인 변화가 요구되며, 공교육에서도 이에 맞는 노력이 필요하다. AI를 활용한 학습자 맞춤형 교육을 실천하기 위해 교원에게 요구되는 역량은 달라져야 할 필요가 있다. 본 연구의 목적은 미술교과 예비·현직교원 AI·디지털 역량 체계를 개발하는 데 있다. 교원의 AI·디지털 역량, AI·디지털 시대 미술교육의 변화, AI·디지털 시대 미술 교사의 역량과 관련된 문헌을 살펴보고 미술교과 교원의 AI·디지털 역량 체계 구축 방법 등에 대해 논하였다. 미술교과 예비·현직교원 AI·디지털 공통역량 및 행동지표 내용 타당도를 검증하기 위해 전문가 자문을 진행하였고, 전문가 자문 결과를 토대로 수정 방안을 반영하여 미술교과 예비·현직 교원의 AI·디지털 역량을 도출하였다. 마지막으로 본 연구의 정책적 시사점 및 후속 연구를 제안하였다. 본 연구는 미술교과 교원의 AI·디지털 역량 체계를 개발함으로써 미래 사회에 요구되는 미술교과 교원의 역량은 무엇인지 점검하고 탐색하는 데에 그 의의가 있다.The digital transformation requires a fundamental shift in teaching and learning, and public education needs to keep up this transformation. The competencies required for teachers need to change in order to practice learner-customized education using AI. The purpose of this study is to develop an AI-digital competency structure for prospective and current art teachers. After reviewing the literature related to AI-digital competencies of teachers, changes in art education in the AI-digital era, and competencies of art teachers in the AI-digital era, this study discusses how to build an AI-digital competency structure for art teachers. Expert consultation was conducted to validate the content validity of the AI-digital common competencies and behavioral indicators of art teachers, and the AI-digital competencies of art teachers were derived by reflecting the modification plan based on the results of the expert consultation. Lastly, policy implications and follow-up research are suggested. This study aims to examine and explore the competencies of art teachers required in the future society by developing an AI and digital competency structure for art teachers.
Trans-Dimensional Markov Chain Monte Carlo Methods Applied to Geochronology and Thermochronology

: Trans-dimensional Markov chain Monte Carlo (MCMC) treats the number of model parameters as an unknown, and provides a natural approach to assess models of variable complexity. We demonstrate the application of these methods to geochronology and thermochronology. The first is mixture modelling, physically a finite dimension problem, which aims to extract the number and characteristics of component age distributions from an overall distribution of radiometric age data. We demonstrate the MCMC method with Gaussian and skew-t component distributions, the latter containing the former as a special case, applied to a suit of U-Pb zircon data from a sediment in northern France. When considering the posterior distributions obtained from the MCMC samplers, the asymmetrical skew distribution models imply fewer components than the symmetrical Gaussian distribution models. We present some heuristic criteria based on different ways to look the results and aid in model choice in the mixture modelling problem. The second application is a thermal history model, physically a continuous time-temperature function but here parametrised in terms of a finite number of time temperature nodes. We consider a suite of synthetic data from a vertical profile to demonstrate the variable resolution in models constrained from single and multiple samples. Provided the implicit assumptions made when grouping multiple samples are valid, the multi-sample approach is preferable as we exploit the variable information on the model (thermal history) contained in different samples.
Effects of Dual Task Activity Using Virtual Reality Program on Cognitive Function, Activities of Daily Living, and Fall Prevention in Stroke Patients

연구목적: 본 연구에서는 가상현실 프로그램을 활용한 이중과제 훈련이 뇌졸중 환자의 인지기능과 일상생활활동 및 낙상예방에 미치는 효과를 알아보고자 하였다. 연구방법: 입원 뇌졸중 환자 20명을 대상으로 하였으며, 실험군 10명, 대조군 10명을 무작위로 나누어 연구를 진행하였다. 실험군에게는 Thera-trainer Balo를 사용한 균형 훈련과 함께 주의력, 기억력, 실행기능 등을 향상 시킬 수 있는 이중과제 프로그램과 전통적 작업치료를 제공하였으며, 대조군에게는 전통적인 작업치료를 제공하였다. 중재는 하루 30분, 주 5회 총 4주간 실시하였다. 연구결과: 중재 후 인지기능 평가에서 실험군과 대조군 모두 통계적으로 유의한 향상을 보였으며(p<.05, p<.01), 두 집단 간의 변화량을 살펴본 결과 숫자 바로 따라 외우기와 기호잇기 검사-A 항목에서는 실험군의 변화량이 유의하게 더 큰 것으로 나타났다(p<.05). 일상생활활동과 균형 및 낙상 효능감 평가에서 실험군과 대조군 모두 통계적으로 유의한 향상을 보였으며(p<.01), 두 집단 간의 변화량을 살펴본 결과 실험군의 변화량이 유의하게 더 큰 것으로 나타났다(p<.05, p<.01). 결론: 가상현실 프로그램을 활용한 이중과제 훈련은 인지기능과 일상생활활동 및 낙상예방에 효과적인 것으로 나타났다. 본 연구에서 제시한 프로그램은 추후 뇌졸중 환자의 재활치료에 유용한 중재 방안이 될 수 있을 것으로 기대한다.Objective : The purpose of this study was to investigate the effect of dual task activities using virtual reality programs on cognitive function, activities of daily living and fall prevention in stroke patients. Methods : The study included 20 stroke patients randomly divided into an experimental group of 10 and a control group of 10. The experimental group. The experimental group received a dual-task program using Thera-trainer Balo for balance training, as well as traditional occupational therapy to improve attention, memory, and executive function. The control group received only traditional occupational therapy. The intervention was conducted for 30 minutes per day, 5 days a week, for 4 weeks. Results : The results of the study showed that both the experimental group and control group showed statistically significant improvement in cognitive function assessments (p<.05, p<.01). When examining the changes between the two groups, the experimental group showed significantly greater changes in the DST-DF and TMT-A (p<.05). Both the experimental and control groups showed statistically significant improvement in activities of daily living and balance and fall efficacy assessments (p<.01), and there were significant differences between the two groups (p<.05, p<.01). Conclusion : The dual-task training utilizing the virtual reality program in this study improved the cognitive function, activities of daily living and fall prevention of stroke patients. These results are expected to serve as a useful guideline for therapists who wish to develop rehabilitation programs for stroke patients in the future.
The Evaluation of the Item Classification Criteria for Elderly-Friendly Equipment of the Korea Health Industry Development Institute: Based on the Creation of Intellectual Property Rights by a college

연구목적: 본 연구의 목적은 일개 대학에서 창출한 고령친화용품 지식재산권을 중심으로 한국보건산업진흥원 (KHIDI)의 고령친화용품 품목 분류기준을 평가하여 개선하는데 기여하고자 하였다. 연구방법: KHIDI(2017)가 분류한 고령친화용품 품목분류체계의 대분류 및 중분류 기준에 일개 대학에서 지난 6년여 동안 창출했던 특허권 60건을 적용하여 분류체계의 적정성에 대해 분석하였다. 연구결과: KHIDI(2017)의 고령친화용품 품목분류 기준에서 대분류의 품목 범위는 적정하였으나, 일부 중분류의 품목 범위는 확대 또는 개선이 필요한 것으로 나타났다. 결론: 본 연구결과는 국내의 고령친화용품 품목 분류체계를 개선하고 고령친화용품산업을 활성화시키는 기초자료로 활용될 수 있다.Objective : This study aimed to improve the Classification Criteria of Elderly-Friendly Equipment of the Korea Health Industry Development Institute (KHIDI), based on created intellectual property rights for senior-friendly equipment by a college. Methods : The adequacy of the Item Classification was analyzed by applying for 60 patents among intellectual property rights created by one university over the past six years to the large and medium classification criteria of the item classification system classified by the Korea Health Industry Promotion Agency (2017). by the Korea Health Industry Development Institute (2017). Results : In the Korea Health Industry Development Institute (KHIDI)'s Elderly-Friendly Equipment Classification Criteria, the range of items in the major category was appropriate, but the range of items in some middle categories was found to need to be expanded or improved. Conclusion : The results of this study can be used as primary data to improve the domestic elderly-friendly equipment classification system and vitalize the senior product industry.
Calibration-based Steganalysis for Neural Network Steganography

Recent research has shown that neural network models can be used to steal sensitive data or embed malware. Therefore, steganalysis for neural networks is urgently needed. However, existing neural network steganalysis methods do not perform well under small embedding rates. In addition, because of the large number of parameters, the neural network steganography method under a small embedding rate can embed enough information into the model for malicious purposes. To address this problem, this paper proposes a calibration-based steganalysis method, which fine-tunes the original neural network model without implicit constraints to obtain a reference model, then extracts and fuses statistical moments from the parameter distributions of the original model and its reference model, and finally trains a logistic regressor for detection. Extensive experiments show that the proposed method has superior performance in detecting steganographic neural network models under small embedding rates.
Progressive JPEGs in the Wild: Implications for Information Hiding and Forensics

JPEG images stored in progressive mode have become more prevalent recently. An estimated 30% of all JPEG images on the most popular websites use progressive mode. Presumably, this surge is caused by the adoption of MozJPEG, an open-source library designed for web publishers. So far, the optimizations used by MozJPEG have not been considered by the multimedia security community, although they are highly relevant. The goal of this paper is to document these optimizations and make them accessible to the research community. Most notably, we find that Trellis optimization in MozJPEG modifies quantized DCT coefficients in order to improve the rate-distortion tradeoff using a perceptual model based on PSNR-HVS. This may compromise the reliability of known methods in steganography, steganalysis, and image forensics when dealing with images compressed with MozJPEG. We also find that the type and order of scans in progressive mode, which MozJPEG adjusts to the image, offer novel cues that can aid forensic source identification.
Comprehensive Dataset of Synthetic and Manipulated Overhead Imagery for Development and Evaluation of Forensic Tools

We present a first of its kind dataset of overhead imagery for development and evaluation of forensic tools. Our dataset consists of real, fully synthetic and partially manipulated overhead imagery generated from a custom diffusion model trained on two sets of different zoom levels and on two sources of pristine data. We developed our model to support controllable generation of multiple manipulation categories including fully synthetic imagery conditioned on real and generated base maps, and location. We also support partial in-painted imagery with same conditioning options and with several types of manipulated content. The data consist of raw images and ground truth annotations describing the manipulation parameters. We also report benchmark performance on several tasks supported by our dataset including detection of fully and partially manipulated imagery, manipulation localization and classification.