Reviewerly/exHarmony huggingface dataset:
Learning dynamical systems using a novel multiple-output Gaussian process model

The Gaussian process (GP) has been widely used to learn the dynamical system from training data. Current methods ignore the dependencies among the multiple dimensions of the system function and model each dimension of the system function using an independent single-output GP. This paper proposes a novel multiple-output Gaussian process model to learn the dynamical system. We assume that ordinary differential equations (ODEs) with unknown physical parameters are available as prior information. The system function is modeled by a GP with the mean function given by the one-step integration of ODEs. By this way, all dimensions of the system function are correlated because they share the same unknown physical parameters. This correlation allows the flow of information between multiple dimensions of the system function which in turn will lead to an improved model. With the existing models as baselines, we show the benefits of the proposed model by simulations.
Ultrasonic-Based Two-Factor Authentication System for Web Applications

Authentication is the first step to access a resource, so it is of vital importance in a system. Many two-factor systems currently fail to address attacks such as eavesdropping or man-in-the-middle attacks. This paper presents a secure two-factor authentication method using sound. The proposed system authenticates a user without any physical contact at no additional cost of hardware by leveraging existing mobile phone technology. This idea is an extension of mobile connectivity-based audio communication in near-ultrasonic spectrum which is inaudible to the human ear.
Traffic Sign Detection in Complex Environment based on Multi-Scale Feature Enhancement and Group Attention

Since traffic light detection is essential for autonomous driving, it is studied intensively. However, traffic sign detection is difficult, especially in a complex environment. The traffic signs should be located first. Their unique features should be extracted next and fed into the classifier subsequently. In this paper, we adopt the current mainstream deep neural network-based object detection method for traffic sign detection. In our work, add specific environmental noise features to the dataset. A lightweight network, YOLOv4-Tiny, is chosen as the baseline network, and a multi-scale feature fusion module is designed to improve the performance of the network model. A lightweight group attention module is also designed. Experiments are carried out using the GTSDB dataset and the result shows the proposed model outperforms the other models in terms of precision and mAP.
Research on Interactive Picking Method of 3D Model Graphics Based on BVH and Qt

Abstract In the front and rear graphics operations of finite element analysis software, traditional methods use ray picking and callback functions to complete the graphics picking interaction, which is inefficient and inflexible, which affects the software user experience. The method in this paper adopts the ray picking algorithm based on the BVH structure and the signal-slot data communication mechanism of Qt to realize multi-threaded concurrent communication, supports efficient and free interactions such as single-point picking of 3D models and rectangular frame selection, and improves the interaction friendliness and friendliness of the finite element analysis system. User operation efficiency.
Named Entity Recognition of Zhuang Language Based on the Feature of Initial Letter in Word

Named entity recognition is an important task and basis for the intelligent information processing and knowledge representation learning of the Zhuang Language. A BilSTM-CNN-CRF network model combining the uppercase and lowercase characters of words is proposed to be applied to the named entity recognition task of the Zhuang language, which lacks corpus for named entity labeling. Firstly, word2vec is used to train in unmarked Zhuang text to get the word vector of the Zhuang language. Then convolutional neural network is used to extract the character features of Zhuang words, and the character feature vector is obtained. The above two vectors were connected with the initial case feature vectors, which are randomly generated, and then the connected vectors were input into a BilSTM-CNN-CRF model for training; thus, the end-to-end named entity recognition model of Zhuang language was constructed. Experimental results show that, without relying on artificial features and external dictionaries, the proposed method in this study is superior to contrastive models by achieving an 80.37% F1 value in the named entity recognition task, which leads to the realization of automated named entity recognition of Zhuang language.
The future of work and employment. AdrianWilkinson and MichaelBarry (Eds.). Northampton, MA: Edward Elgar Publishing, 2021, 264 pages, $35 softcover

Personnel PsychologyVolume 75, Issue 3 p. 765-767 BOOK REVIEWS The future of work and employment. Adrian Wilkinson and Michael Barry (Eds.). Northampton, MA: Edward Elgar Publishing, 2021, 264 pages, $35 softcover Steven Toaddy, Steven Toaddy Department of Psychology and Behavioral Sciences, Louisiana Tech University, Ruston, Louisiana, USASearch for more papers by this author Steven Toaddy, Steven Toaddy Department of Psychology and Behavioral Sciences, Louisiana Tech University, Ruston, Louisiana, USASearch for more papers by this author First published: 10 June 2022 https://doi.org/10.1111/peps.12534Read the full textAboutPDF 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 Volume75, Issue3Autumn (Fall) 2022Pages 765-767 RelatedInformation
Instrumental Software Environment for Teaching Students the Technology of Designing Intelligent Decision Support Systems

The transition to the "Digital economy" requires training of specialists in the field of modern information technologies using artificial intelligence. The National Research University "Moscow Power Engineering Institute" in a department of "Applied Mathematics and Computer Science" in the master's program "Artificial Intelligence" provides training of students in methods and tools for designing intelligent systems, including their most complex representatives – intelligent decision support systems in real time. This paper considers the application of the Decision-making Modeling System developed at the Department of Applied Mathematics and Artificial Intelligence, used by students when performing laboratory classes in the disciplines "Methods and decision support systems" and "Intelligent decision support systems".
Co-mining: a processing-in-memory assisted framework for memory-intensive PoW acceleration

Recently, HBM (High Bandwidth Memory) and PIM (Processing in Memory) integrated technology such as Samsung function-in-memory DRAM opens a new door for memory-intensive PoW acceleration by jointly exploiting GPU, PIM and HBM. In this paper, we for the first time propose a GPU/PIM Co-Mining framework to accelerate memory intensive PoW by fully exploiting HBM-PIM's bandwidth and coordinately scheduling mining tasks in both GPU and PIM. Specifically, we first design a linear programming model to intelligently guide the GPU/PIM task scheduling. An extended finite-state-machine model is designed for the GPU memory controller to switch PIM working mode (compute/memory mode) accordingly. Finally, considering the speed difference between intra-/inter-channel memory accesses, a hybrid memory access method is proposed to minimize inter-channel data movements. We evaluate Co-Mining based on Samsung's HBM2-based function-in-memory architecture. The experimental results show that it can achieve up to 38.5% hashrate improvement compared with the method by directly integrating PIM into PoW acceleration with GPU.
EGYPT

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 59, Issue 4 p. 23830A-23830B Policy and Practice EGYPT First published: 02 June 2022 https://doi.org/10.1111/j.1467-6346.2022.10558.xRead the full textAboutPDF 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. Volume59, Issue4June 2022Pages 23830A-23830B RelatedInformation
Establishing security and trust for object detection and classification with confidential AI

In the context of multi-domain operations (MDO), artificial intelligence (AI) systems support human operators by processing large volumes of electro-optical/infrared (EOIR) sensor data. In this paper, we demonstrate how confidential computing technology, incorporating a hardware-based root of trust, can provide systemic identity verification through mutual attestation, secure the integrity of AI models, and preserve the confidentiality of processed sensor data. Using the example of aircraft detection and classification, we describe how confidential computing can defend against adversarial machine learning (AML) attacks by providing intrinsic security at the tactical edge and within the distributed applications environment that characterizes MDO.
Volatility Behaviour of Bitcoin as a Digital Asset

The objective of this study is to use the South African financial markets (Johannesburg Stock Exchange or JSE and USD/ZAR) as a case study to understand the volatility spillover dynamics of Bitcoin as a digital asset. Methodologically, the study applies the exponential generalized autoregressive conditional heteroskedastic (EGARCH) model, followed by a robustness check by applying the time-varying conditional correlation multivariate GARCH (VCC-MGARCH) model. The study utilizes the data set for the period 2011 to 2019, a period before the COVID‑19 pandemic. The research outcome revealed three interesting observations. First, Bitcoin and the South African stock market are independent of each other. Second, there is a bidirectional shock transmission between Bitcoin and USD/ZAR in the mean returns only, but not variance. Lastly, results confirm the existence of a bidirectional volatility spillover in both the mean and variance between the JSE stock market and the USD/ZAR market. The study outcome should enlighten investors who may want to consider Bitcoin as a diversifier in their investment and portfolio strategies.
Ready, Steady, Go: Playing and Rapidly Designing with IoTgo

Smart things are everywhere: smart watches, smart jewellery, smart art installations. All have in common the capability of sensing with input devices (e.g., buttons), computing, reacting with output devices (e.g., light matrices), and connecting with other smart things. Engaging their end users in their design can be challenging and yet give end users unique empowering opportunities. Toolkits are fundamental for engaging end users and enabling them to design. This paper presents the IoTgo phygital toolkit for smart-thing design with end users who are not experts, e.g., artists and school learners, which results from co-design actions and interventions in the field.
Mapping Motion Direction to Color in Ground-Motion Visualizations—A Tool with Potential Applications in Different Settings

Abstract The increase in seismometer density on a continental scale since the start of the EarthScope project has enabled the community to produce visualizations of the propagating wavefield from local and teleseismic events. Previous work has shown that these animations generate much interest yet have limitations and can be confusing to novices. Here, we present a new type of visualization in which the color, position, and size of the symbols representing each seismometer are time dependent and determined by the instantaneous proportion of motion in the Z, R, and T components. This color-mapping scheme has the advantage of automatically producing different colors for different wave types and results in vibrant animations. The color mapping is based on transforming the value of the envelopes of the filtered velocity traces to red–green–blue values and subsequently boosting the color saturation in the hue–saturation–value color space. Animations in map view and along great-circle paths have been produced and used in a formal classroom setting and have also been shared with the broader public through social media channels. In both formal and informal settings, the animations have succeeded in garnering attention and stimulating discussion.
G<scp>eophysics</scp> Bright Spots

Welcome to the latest installment of Geophysics Bright Spots. There are a number of interesting research articles in the last two issues of Geophysics. Here is a list of what piqued the editors' interests.
Integration of models for linked data in cultural heritage and contributions to the FAIR principles

Incorporating linked data-based models into the process of describing cultural objects is increasingly important for cultural heritage. Communities such as libraries, archives, and museums have developed and adopted models specific to their contexts. Without a trivial solution, choosing models to support more general applications is challenging. This Ph.D. aims to analyze existing solutions and practices in these domains and propose validated solutions for the discovery, access, interoperability, and reuse of cultural objects, following the FAIR principles. Transversal to the base models used, this research intends to adopt solutions that balance the simplicity of the models with the satisfaction of the requirements.
Personalisation of Higher Education

This chapter aims to present the connection between the digital transformation of Higher Education Institutions (HEI) and personalization in relations to students throughout their life-cycle from prospectus to graduation. Personalized communication, the adoption of emerging technologies to support along with personalized learning, are the new focus in many HEI strategies. Digital technologies offer opportunities that facilitate blended, online, and mobile learning. Nonetheless, the implementation of real data-driven personalization is still at its initial stage, therefore relatively little attention is paid to the impact of personalization on the awarding of academic degrees, the value of diplomas and certificates. This chapter presents personalization at various stages of the student's life cycle, from the initial recruitment and on-boarding through the time of acquiring knowledge and qualifications to ideas related to lifelong learning and “student for life”. The opportunities and challenges that personalization creates for the certification process in higher education were also considered.
Face Mask Detection

The corona virus COVID-19 pandemic is causing a global health crisis so the effective protection methods is wearing a face mask in public areas according to the World Health Organization (WHO). The COVID-19 pandemic forced governments across the world to impose lockdowns to prevent virus transmissions. Reports indicate that wearing face masks while at work clearly reduces the risk of transmission. An efficient and economic approach of using AI to create a safe environment in a manufacturing setup. A hybrid model using deep and classical machine learning for face mask detection will be presented. A face mask detection dataset consists of with mask and without mask images , we are going to use OpenCV to do real-time face detection from a live stream via our webcam. We will use the dataset to build a COVID-19 face mask detector with computer vision using Python, OpenCV, and Tensor Flow and Keras. Our goal is to identify whether the person on image/video stream is wearing a face mask or not with the help of computer vision and deep learning.
A Study on xodial rights discourse and welfare intervention through the concept of children and adolescents - Are the rights of children and adolescents the same?-

Social rights are active rights followed by the responsibilities of the state and society, and are very important rights for children and adolescents, especially at an important time in the life development process. The age range of children and adolescents is so wide that it is inevitably ineffective in developing social and policy programs suitable for the characteristics of all the ages. Therefore, this study aims to explore the social rights of children and adolescents and seek welfare support measures to guarantee and promote the rights of children and adolescents. As a result of the study, considering the legal age, social awareness, and developmental characteristics of children and adolescents, it can be confirmed that it is desirable to distinguish between children and adolescents and to distinguish welfare support measures accordingly. From the perspective of social rights, while strengthening children's rights to be protected in society, the focus should be placed on the transition of adolescents to the right to be responsible for their autonomous choices. Welfare intervention allowances, educational rights, play rights, and environmental rights related to children and adolescents' social rights should be more applied to children and to adolescents.
Distribution and Abundance of Blood Shells (Anadara granosa) on the Coast of Concong Luar Village Indragiri Hilir Regency

This study was conducted in September 2021, around the coastal of Concong luar village Indragiri Hilir Regency with the aim to find out the abundance, distribution, and morphometrics of blood shell (Anadara granosa). The method used survey methods, in which blood shell sampling and aquatic substrates, as well as measurements of environmental parameters, were conducted in the field and in the laboratory. Determination of sampling location by purposive sampling is based on the character of the environment in the location of the research. Based on the results of research that has been obtained an abundance value at the station 1 = 4,8 Ind/m2, station 2 = 8,7 Ind/m2, and station 3 = 3 Ind/m2. The pattern of blood shell levy in the waters of Concong Luar Village stations 1 and 2 is clustered, while station 3 is evenly distributed. Furthermore, the results of measurement of the width of the highest blood shells are 16 - 30 mm in 70 individuals, followed by size &gt;31 mm of 43 individuals, the lowest measurement result is &lt;15 mm in 27 individuals, and the highest measurement of the length of the blood shells 16 – 30 mm of 77 ind, followed by a size &gt;31 mm of 42 ind, and the lowest measurement result is &lt;15 mm of 29 ind.
Artificial Intelligence and International Economic Law by Shin-yi Peng, Ching-Fu Lin, and Thomas Streinz Cambridge University Press, 2021

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
시몽동의 발명 철학 탐색

Gilbert Simondon is the first philosopher of technology and invention to explain the beginning of the philosophy of technology by shifting the paradigm of thought from substance to relationship, and claiming that technological entities can solve problems through invention because they are invented entities. This study aims to explore the philosophy of invention of Simondon, a French philosopher of technology, and the research results are as follows. First, in Simondon’s philosophy, ‘individuation’ is a key concept that characterizes relational thinking. It is an operation transductive that resolves the problems of inconsistency, incompatibility, tension and conflict inherent in metastable systems through ontotogenesis. Second, the invention concept is a transformation operation that solves problems by creating a new structure by mediating and establishing relationships between things that are difficult to communicate because of incompatible, inconsistent and disparity. Third, technological invention is a process that transcends the individual’s mind, and is achieved through the inventive ‘imagination’ of problemsolving of successive inventors who communicate through existing technological objects. Fourth, an ideal society through invention is a ‘society of individual creators of technological existence’, united through the medium of technological entities, and humans communicate through their inventions. Lastly, in order to overcome the obstacles to the limitless possibilities of inventive imagination and social change, it is necessary to create a foundation for a balanced technology culture by implementing technology literacy education from school education in the dimension of inventive imagination.
An Innovative Model for Secure Environment Using Steganography

Steganography is a form of safety approach through obscurity, and it&#x0027;s the art of hiding the message among sender and the intended recipient. it is used to cover secret messages in various varieties like documents and also digital images, video and audio. it works through hidden information in the sort of way that nobody can suspect. this is the far method to shield sensitive or mystery information from spiteful assault. photo Steganography is the method of hiding the secret message which can be textual content, photograph or video inside stegno image in the way that is not visible to the human eyes. In this paper, we are using steganography technique to hide a secure image, we use virtual environment by using PowerShell tool.
Process Design In Water Treatment: Software Choice Problem

The article describes approach for selection water treatment design software for students at the National Research University "Moscow Power Engineering Institute" (MPEI). The advantages, disadvantages and approaches are described.