Reviewerly/exHarmony huggingface dataset:
TECHNOLOGY IN CLASSICS TEACHING - (B.) Natoli, (S.) Hunt (edd.) Teaching Classics with Technology. Pp. xiv + 246, figs, ills, maps. London and New York: Bloomsbury Academic, 2019. Paper, £24.99, US$34.95 (Cased, £75, US$100). ISBN: 978-1-350-11093-9 (978-1-350-08625-8 hbk).

TECHNOLOGY IN CLASSICS TEACHING - (B.) Natoli, (S.) Hunt (edd.) Teaching Classics with Technology. Pp. xiv + 246, figs, ills, maps. London and New York: Bloomsbury Academic, 2019. Paper, £24.99, US100). ISBN: 978-1-350-11093-9 (978-1-350-08625-8 hbk). - Volume 72 Issue 2
Imprint: Geomechanics and Tunneling 3/2022

Geomechanics and TunnellingVolume 15, Issue 3 p. 331-331 ImprintFree Access Imprint: Geomechanics and Tunneling 3/2022 First published: 03 June 2022 https://doi.org/10.1002/geot.202270307AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume15, Issue3June 2022Pages 331-331 RelatedInformation
Bringing Digital Exhibitions to Life: Simplify User Guidance through the Concept of Aura and white plane

The translation of exhibitions into digital space has become increasingly important in recent years. Further intensified by the COVID pandemic, many museums are looking for alternative solutions to make museum visits possible. In this way, they can continue to fulfil their role as an institution for the communication and presentation of cultural heritage as well as the transfer of knowledge. In an exhibition, the focus is on the exhibit with its inherent knowledge. The curators of the Office for Academic Heritage, Scientific and Art Collections of the TU Dresden, are keen to present the exhibitions that have already been held and those that are planned in an expanded setting. A virtual counterpart to the real exhibition space is to be created, which can also be filled independently of current exhibitions. As part of a course at the Faculty of Computer Science at TU Dresden, a concept for a virtual reality web application with an explorative, immersive character was developed. With the concepts of white plane and aura, the students created an open museum space that focuses on the exhibits and the knowledge transfer.
Developing a comprehensive, adaptive system for large scale x-ray images

Inspection of commerce entering the country is currently an onerous, custom and extremely labor-intensive process. The imaging of commerce with 2D x-rays aids the ability to interdict certain items entering the country, reducing risk and increasing national security. We use a variety of ML techniques together to develop automated threat recognition (ATR) algorithms to assist this process. The challenge is to develop a system that incorporates several approaches simultaneously and ensemble results to improve overall performance. We employ several algorithmic techniques to solve the problem. Generally, we have synthetic data generation techniques that can rapidly spin up datasets that are then employed to train ML models. GANs are used to refine the synthetic data to resemble reality more faithfully; thresholding objectively improves top line S/N; semi-supervised methods are used to handle data sparsity and leverage any available unlabeled stream of commerce (SOC) data. Suites of object detectors infer in parallel using common techniques and results are then ensembled using a novel graph-based method. Similarity and change detection along with topological data analysis may leverage historical data to investigate anomalies. This paper is an overview of our approach, generating synthetic data and attempting to unite these ML methods to provide the highest performance for ATR of 2D x-ray data.
Methods of Measuring Temperature and Pressure on Virtual Laboratory Stands

The format of distance learning for students is increasingly being included in the educational life of teachers and university students. One of the urgent tasks of such training is to translate the process of performing laboratory work on real experimental installations into an online format. One of the most promising options for conducting remote laboratory work is the creation of simulation models of real installations - virtual stands with varying degrees of detailing of the physical processes taking place in them. This article discusses some of the advantages and disadvantages of using virtual benches over their physical counterparts. The features of modeling and some methodological solutions for creating virtual stands in the LabView program are considered. The description and appearance of virtual stands for performing two laboratory works in the discipline "Experimental research methods" are given. In a virtual stand to learn temperature measurement techniques, students can calibrate a thermocouple and calibrate electronic and mercury thermometers with a platinum resistance thermometer. On a virtual stand for teaching gauge pressure measurement methods, students can test the spring-loaded gauge and MIDA gauge, and then draw conclusions about the metrological characteristics of the instruments. The prototypes of the developed virtual stands are real laboratory installations where classes are held with students. At the moment, the creation of virtual stands is considered the most successful and inexpensive way to conduct laboratory work in distance learning. Despite the fact that this method is relatively simple, the implementation of laboratory work on its basis requires a serious study and understanding of the physical processes of the studied phenomena.
Study on reference-based FASTQ genome sequences compression

As the cost of genome sequencing decreases, the large amount of genomic data generated brings the storage problem of this massive data. We still have a lot of work to do in the field of specialized data compression of FASTQ files. This paper aims to explore a reference-based lossless compression algorithm for genome sequences in FASTQ format. We propose a compression scheme based on longest matching by using FMD-index to support exact match searching. At the same time, the reverse complementary sequence is used and the insertion, deletion and replacement operations are described effectively to further improve the compression ratio. In comparison with the experimental results of five compressors on seven sets of genome data, the proposed algorithm significantly improves the FASTQ file compression ratios, and is competitive in running time.
Exploring Extended Reality Multi-Robot Ground Control Stations

This paper presents work-in-progress research exploring the use of extended reality headsets to overcome the intrinsic limitations of conventional, screen-based ground control stations. Specifically, we discuss an extended reality ground control station prototype developed to explore how the strengths of these immersive technologies can be leveraged to improve 3D information visualization, workspace scalability, natural interaction methods, and system mobility for multi-robot ground control stations.
Ethics and the Future of Artificial Intelligence in Auditing

Firms are investing millions of dollars in artificial intelligence systems, sparking the growing interest in emerging technology ethics research. This chapter examines fundamental questions that accounting information systems researchers should consider when exploring technology ethics research. Reflecting on prior research, we discuss what is meant by ethics in the first place, how artificial intelligence implementation in accounting creates an ethical dilemma, and for whom. Given the growing number of publications considering the ethical implications of emerging technology, this chapter probes whether the highlighted ethical issues are also prevalent in non-accounting settings and whether accounting researchers have the comparative advantage to resolve the dilemma over a specialist in ethics.
Mixture Density Hyperspherical Generative Adversarial Networks

The Generative Adversarial Networks (GANs) are deep generative models that can generate realistic samples, but they are difficult to train in practice due to the problem of mode collapse, where the generator only repeatedly generates one mode in samples during the learning process, or only generates a small number of modes after reaching the Nash equilibrium during the adversarial training. In order to solve this issue while making the generator contains promising generation ability, we propose a mixture density hyperspherical generative model namely MDH-GAN that combines variational autoencoder (VAE) and generative adversarial network. Unlike most of the GAN-based generative models that consider a Gaussian prior, MDH-GAN adopts the von Mises-Fisher (vMF) prior defined on a unit hypersphere. Our model combines VAE with GAN by integrating the encoder of VAE with GAN to form a jointly training framework. Therefore, the generator of our model can learn data distribution with a hyperspherical latent structure, leading to an improved generative ability of the generator. Moreover, a vMF mixture model is deployed in the discriminator to form a hypersphere space to avoid mode collapse of the model. In our experiments, by calculating the Fréchet Inception distance (FID) between the generated images and real ones, we prove that MDH-GAN has a better ability to generate high-quality images with high diversity.
Hubungan Antara Pengalaman Belajar Dengan Partisipasi Belajar Di Lembaga Kursus Bahasa Jepang Natsuka Gakkou Kota Padang

This research is motivated by the low learning participation of students at the Natsuka Gakkou Japanese Language Course Institute in Padang City caused by low learning experiences. The objectives of this study are (1) to describe the learning experiences of students at the Natsuka Gakkou Japanese Language Course Institute, Padang City. (2) describes the learning participation of students at the Natsuka Gakkou Japanese Language Course Institute, Padang City. (3) describes the relationship between the learning experience and the participation of students at the Natsuka Gakkou Japanese Language Course Institute, Padang City. This research is a quantitative research with the type of correlational research which aims to examine the correlation between the independent and dependent variables. The population in this study were 28 students. The sampling technique used in this study was cluster random sampling. The sample in this study was 21 students or the sample in this study was 75%. techniques in data collection using written statements (questionnaires) and data collection tools in the form of a list of statements. The data analysis technique uses the percentage formula and data processing uses the Sperman Rho formula. The results of this study indicate that: (1) the learning experience of students at the Natsuka Gakkou Japanese Language Course Institute in Padang City is categorized as low. (2) learning participation at the Natsuka Gakkou Japanese Language Course Institute in Padang City is categorized as low. (3) there is a significant relationship between learning experience and participation in learning at the Natsuka Gakkou Japanese Language Course Institute, Padang City.It is hoped that further researchers will be able to examine new variables so that they can complete the variables in existing research.
Collocated sensors bias estimation in autonomous driving

Sensors are prone to biases which can lead to inaccurate associations and hence poor results in target tracking. The sensors used on autonomous vehicles (AV) are placed together or very close (practically collocated) which makes the bias estimation challenging. This work considers the bias estimation for two collocated synchronized sensors with slowly varying additive biases. The biases’ observability condition is met when the two sensors’ biases are Ornstein-Uhlenbeck stochastic processes with different time constants. The proposed bias estimation is independent of state estimation and bias models are identified based on sample autocorrelations. With bias-compensated observations, the fused measurement can be obtained using the Maximum Likelihood fusion technique. In experiments, two collocated lidars (different manufacturer models) are tested in real time. It is shown that the uncertainties of biases are significantly reduced by the estimation algorithm presented. The observation error reduction is up to 77% with bias-compensated measurement fusion and the bias uncertainty (root mean square error) has reduction up to 45% after fusion compared to the single lidar scenario.
Automatic Brain Tumor Segmentation on Pre-operative MRI using Region Growing Algorithm

The major issue in radiation oncology application is to detect and segment the mixed necrotic tumor tissue. Detecting and segmenting these tissues along with the neighboring vessels are a challenging issue. The normal and the abnormal tissues are used to identify the overlapping of the margins in each tissue by means of an MRI image. Various automatic seed finding methodologies have been proposed but all those suffer from various issues such as the absence of tumor or the presence of any white or gray part. However, the general purpose methods are not effective for segmenting the complex MRI image structures. Generally for the segmentation of brain tumor, region-based active contour models were employed, but the edges are not sharpen in those models, and hence, the accurate results are not obtained due to the over segmentation and under segmentation. This happens due to the initial stage of the tumors and hence is a need for a method to detect the tumor and segment it. Hence, an effective method for detecting the tumor based on MRI texture and automatic segmentation using region growing method is proposed. These approaches were employed to separate the irregular tissues from regular tissues to detect the area and to identify whether it is involved or non-involved which greatly assist the surgeon to identify the affected areas accurately. The proposed work incorporates the texture analysis and region growing algorithm which is investigated on MRI brain images to identify the boundaries of tumor in 2D MRI images.
Inversion of the Radon V-transform with a power-law weight on the plane

A formula for inverting an integral transformation on one family of polylines on the plane is obtained. It generalizes the known formulas to the case of a weighted power function.
Improved Instrument Approach Stability Analysis for Helicopters Using Data Fusion and Analytics

Approach and landing are among the most challenging and dangerous tasks required of helicopter pilots. Helicopter accident statistics suggest that the majority of helicopter accidents occur during the approach and landing phases of flight. Unstabilized approaches are a leading cause of these accidents due to the increased potential for loss of control, loss of situational awareness, or controlled flight into terrain. In the present work, routine flight data records obtained as part of a voluntary helicopter flight data monitoring program are used to identify, analyze, and evaluate the stability of instrument approach events. A data fusion process is developed that enables detection of the approach phase, identification of an associated instrument approach procedure, analysis of approach stability, and knowledge discovery through data mining. The process identified 385 instrument approach events in a set of 7063 operational helicopter flight data records. Manual analysis of these events reveals some common errors, including crossing the final approach fix far below the assigned altitude and violating the minimum altitude requirement during initial and intermediate approach legs and course reversal maneuvers. Data mining algorithms are tested and found to be capable of automatically identifying atypical or unstable approach events.
Patient Monitoring System using Internet of Things (IOT)

Observing your cherished ones turns into a troublesome undertaking in your current life. Monitoring the patient's well-being status at home is a troublesome errand. Particularly old, matured patients ought to be occasionally observed, and their friends and family should be educated about their well-being status now and again while at work. Along these lines, we propose an inventive framework that robotized this assignment easily. Our framework advances a savvy patient well-being global positioning framework that utilizes Sensors to follow patient wellbeing and uses the web to illuminate their friends and family on the off chance regarding any issues. Our framework involves temperature as well as heartbeat detecting to monitor patient wellbeing. The sensors are associated with a microcontroller to follow the status which is thusly interacted to an LCD show as well as a Wi- Fi association with send data on wellbeing. Assuming the framework distinguishes any unexpected changes in the patient's pulse or internal heat level, patient development of the framework naturally sends data to the client about the patient's status over IoT and shows subtleties of the heartbeat and temperature of the patient live over the web. Accordingly, IoT based patient wellbeing global positioning framework really utilizes the web to screen patient wellbeing details and save lives on time.
Research on the problems and Countermeasures of informatization course construction

The informatization course construction mainly includes micro lesson production, short video production, course website, flash animation production and other main means. Through the construction practice of the informatization course of international trade practice, this paper finds that there are some problems in the course construction, such as "relying too much on information technology and ignoring professional knowledge", "lack of targeted combing of informatization resources", "lack of targeted combing", etc It also puts forward countermeasures and suggestions from the aspects of "rational use of teaching means", "information resource sharing" and "information curriculum model innovation".
THE IMAGE OF THE CITY INTERPRETED THROUGH BIOSENSORS PATH ANALYSIS AND IDENTIFICATION OF PERCEPTUAL POLES IN THE NARNI CASE STUDY

Abstract. The research aims to interpret the image of the city, according to the conventions defined by Kevin Lynch, obtained from the analysis of the impact of environmental stimuli on the person. The study relates the digital reconstruction of the spaces analysed with the detection of the trend of valence obtained on a statistical sample using an EEG helmet. The monitoring of the degree of attraction or aversion to the stimuli of the surrounding environment is processed through algorithmic procedures to identify along a path the perceptual poles. This path, reported in GIS environment, allows to reconstruct georeferenced maps that interpret the brain data, synchronized with GNSS. The spatial poles thus identified are further investigated using eye-tracker to understand the reasons for the impact of the environment on humans.
Foley performance and sonic implicit interactions

In this chapter, I argue that Foley artists’ ability to express a character’s behaviour through their body movements and sound – in other words, their expertise of “acting through sound” – is what sets them fundamentally apart from other sound professionals. Furthermore, many sounds created by Foley performers are designed to be felt, rather than explicitly heard. These sounds imply, rather than directly express, a behaviour or an intention. Implicit human–computer interaction is a growing area of research that aims to develop seamless interactions between technology and humans. In this chapter, I posit that the study of implicit interactions that use sound to convey information, which I term “sonic implicit interactions”, can strongly benefit from studying, analysing and bringing to the centre of the design process the expertise of Foley performers. Finally, I outline a few examples of how I address this in my research, utilizing methodologies from sound computing, ethnography and design thinking.
Character-level domain name generation algorithm based on ED-GAN

In response to the need to obtain the latest counterfeit domain name samples in time to prevent new counterfeit domain name attacks in high-level security requirement scenarios, this chapter proposes a character-level domain name generation method based on ED-GAN. By combining Encoder of domain names, Decoder of domain name vectors, and Generative Adversarial Network (GAN), an ED-GAN-based domain name generation algorithm is proposed to generate realistic data by learning from real counterfeit domain names and using the generated data for training of detection models to achieve detection and prediction of emerging and potential counterfeit domain names. The generated data is used to train the detection model to detect and predict emerging and potential counterfeit domain names. Finally, the feasibility of the ED-GAN-based character-level domain name generation algorithm and the effectiveness of the generated data are demonstrated through experimental performance comparisons with various classifiers.
The Implications of the Concept and Type of the Artistic model of Curriculum on the Elementary Integrated Curriculu

Purpose: This study explores the implications of artistic model of curriculum for elementary integrated curriculum.&#x0D; Methods: In this study, based on the concept and type of artistic model of curriculum, the concept and development process of elementary integrated curriculum, the implications of artistic model of curriculum are discussed.&#x0D; Results: As a result of the study, the artistic model of curriculum has implications for the integrated curriculum in three aspects: first, the artistic model of curriculum can be applied as a base theory that can have conceptual uniqueness. Second, the role of teachers in the artistic model of curriculum is similar to that of teachers in the integrated curriculum. Third, as the diversity of instruction in the artistic model of curriculum is supplemented by teachers, the diversity and complexity of instruction in the integrated curriculum are supplemented by teachers. In addition, the evaluation of integrated curriculum increases the validity and suitability through the educational criticism of the artistic model of curriculum.&#x0D; Conclusion: I hope this study will be the beginning of exploring the relationship between the artistic model of curriculum and the integrated curriculum.
Time-space Domain Elimination Method of High-Temperature Thermal Disturbance Test Error

Abstract The digital image correlation (DIC) test method has been widely used in structural deformation measurement due to its non-contact and full-field. However, eliminating the effects of temperature-induced thermal disturbance is a primary challenge in high-temperature DIC measurements. In this paper, the measurement error is regarded as the superposition of zero-mean random error and non-zero mean system error, a time-space domain disturbance error elimination method is proposed to eliminate the adverse effects of thermal disturbance. Firstly, the noise images are averaged in the time domain to reduce the DIC matching error caused by zero-mean random noise. Then the noise displacement field is locally weighted quadratically smoothed in the space domain to eliminate the non-zero mean system error. The experimental results show that the proposed method can improve the high-temperature deformation measurement accuracy compared with the single-domain processing method. This paper will provide a new method for improving the measurement accuracy in DIC full-field deformation measurement under a high-temperature environment.