Reviewerly/exHarmony huggingface dataset:
Evaluation scheme of OBE learning output certification based on Blockchain

The content of OBE learning output certification and evaluation work is complex and numerous. It is difficult for the traditional teaching model to record and analyze the full life cycle of data in all aspects, and to achieve effective and credible quality supervision. To this end, we propose a solution that uses a partially decentralized alliance chain, introduces the Certification Engineering Education Committee(CEEC) as a centralized trusted authority, and expands trusted nodes through the PoA consensus mechanism. The life cycle of the data is recorded by the authorization contract, the learning output certification evaluation contract and the evaluation result contract which the data is stored in the Merkle tree. Finally, we build an engineering education learning output chain to conduct simulation experiments on resource consumption and transaction throughput. Experimental results show that this solution can effectively solve the above problems.
ADAW: Age decay accuracy weighted ensemble method for drifting data stream mining

Dynamic environment data generators are very often in real-world that produce data streams. A data source of a dynamic environment generates data streams in which the underlying data distribution changes very frequently with respect to time and hence results in concept drifts. As compared to the stationary environment, learning in the dynamic environment is very difficult due to the presence of concept drifts. Learning in dynamic environment requires evolutionary and adaptive approaches to be accommodated with the learning algorithms. Ensemble methods are commonly used to build classifiers for learning in a dynamic environment. The ensemble methods of learning are generally described at three very crucial aspects, namely, the learning and testing method employed, result integration method and forgetting mechanism for old concepts. In this paper, we propose a novel approach called Age Decay Accuracy Weighted (ADAW) ensemble architecture for learning in concept drifting data streams. The ADAW method assigned weights to the component classifiers based on its accuracy and its remaining life-time in the ensemble is such a way that ensures maximum accuracy. We empirically evaluated ADAW on benchmark artificial drifting data stream generators and real datasets and compared its performance with ten well-known state-of-the-art existing methods. The experimental results show that ADAW outperforms over the existing methods.
Stereo matching of remote sensing images using deep stereo matching

Very high resolution satellite images can be used to generate stereoscopic digital elevation models (DEMs), efficiently and at scale, as exemplified by the upcoming CO3D mission, which aims to produce worldwide DEMs by the end of 2025. In this paper we present a deep learning stereo-vision algorithm, integrated in the Stereo Pipeline for Pushbroom Images (S2P) framework. The proposed stereo matching method applies a Siamese convolutional neural network (CNN) to construct a cost volume. A median filter is applied to every slice in the cost volume to enforce spatial smoothness, and another CNN estimates a confidence map which is used to derive the final disparity map. Simulation results on the IARPA dataset show that the proposed method improves completeness by 4.5%, compared to the state of the art. A qualitative assessment also shows that the proposed method generates DEMs with less noise.
IMAGE RECOGNITION USING MACHINE LEARNING

Image recognition is important side of image processing for machine learning without involving any human support at any step. In this paper we study how image classification is completed using imagery backend. Couple of thousands of images of every, cats and dogs are taken then distributed them into category of test dataset and training dataset for our learning model. The results are obtained using custom neural network with the architecture of Convolution Neural Networks and Keras API.
Report from IDEA—The Immersive Digital Experiences Alliance

The past 12 months saw significant progress in the emerging world of immersive media. We saw myriad developments across all aspects of the immersive media landscape, ranging from new immersive displays announced by Looking Glass Factory, Sony, Avalon Holographics, Dimenco, and others to strides made in light field capture research. All of this brings us closer to widespread access to immersive media that will transform the way we live and work. To prepare for this future, the Immersive Digital Experiences Alliance (IDEA) recently published updated specifications, papers, and presentations during the last year, raising awareness about immersive media and how we will handle it.
Data Curation in Practice: Extract Tabular Data from PDF Files Using a Data Analytics Tool

Data curation is the process of managing data to make it available for reuse and preservation and to allow FAIR (findable, accessible, interoperable, reusable) uses. It is an important part of the research lifecycle as researchers are often either required by funders or generally encouraged to preserve the dataset and make it discoverable and reusable. This has been especially important as the Open Access (OA) policy is being implemented in many institutions across the nation. In facilitating research data discovery and enhancing its easier reuse, an efficient data repository and its data curation play key roles. In this article, we briefly discuss the local institutional repository at Penn State University and the general data curation practices we adopt for the deposited files and datasets, then we focus on a data analytics tool that has recently been applied to extract tabular data from PDF files. This is an enhancement to the existing data curation practices as it adds additional tabular data to deposits with PDF files where tables are often embedded and not easily reused.
Listening Sessions

Audio engineering students usually develop technical listening skills through autonomous study and practice, by listening to recordings and through ear training programs. Audio educational programs typically emphasize the importance of doing or practical training, for example, recording sessions with fellow students and student musicians. Listening sessions conjointly build critical listening, critical thinking, and communication skills. Listening sessions that offer opportunities to experience differing understandings, offer opportunities to explore how perspectives and recordings are similar in some ways and unique in others. Professionals are able to find words for what is audible; and they are also able to describe hypothetical listening experiences, experiences that a production might bring about if certain decisions and actions are taken. Listening sessions gently, socially pressure students to communicate about what they hear and think. However, assuming the listening session is extracurricular, unlike an exam, students retain control over how and how much they participate.
Weaknesses of Translation Result Using Google Translate

Google Translate has been widely used worldwide in more than 90 languages, and it becomes the most popular translation tool since then.Many people rely on this tool because they want easy and fast way to translating their text.But, like many tools created by human beings it has its own flaws.This descriptive qualitative research aims to analyze the weaknesses of translating result using Google Translate.The result of this study showed that even though this translation tool may solve people's problem in translating text, the translation result still needs revision because the result of translated text using Google Translate was too wordy and incomprehensible.The tool applied literal translation and often ignore the context contain in the text.Translation activity is not only altering the source language to the receptor language beyond that the translation result should be acceptable, understandable, readable, and natural.
Jagged pupils give away computer-generated faces

The pupils of faces in computer-generated deepfake videos or images have more jagged edges and are less symmetrical than those in real human eyes
Screwed: Anxiety and the Digital Ends of Anticipation

This essay discusses anxiety as the paradigmatic malady of the present and its correlation with the rise of always-on computing. Discussing anxiety as “an expectation emotion,” the essay notes the ways in which always-on computing has outsourced futurity to opaque computational processes. This essay asserts that the latter fuels the former. However, all is not lost. Through the analyses of three online texts—an artist’s clock, a meme, and a YouTube video—the essay argues for a view of this situation that recognizes the pleasurable and resolutely social dimensions of anxiety. Discussion of these texts elucidates the dynamics of anxiety in always-on computing and challenges the assumption of anxiety as an individual problem.
Recurrent motion in vision

In this thesis, Recurrent Motion in Vision, we explore the concept of recurrent motion patterns in video. The thesis, consisting of two parts, begins with a study on the origin of periodic motion which results in its categorization into fundamental cases. The chapters that follow introduce novel solutions for estimating repetition in real-world videos by means of counting. In the second part, we investigate recurrent motion in physical scenes for learning intrinsic object properties.
CBD industry meets sports: Indy 500 to feature landmark sponsorship deal

While the CBD industry has grown rapidly in recent years, it has remained a taboo subject in the sports world.
Hacia la democratización del aprendizaje de máquinas

Machine Learning is a field of Artificial Intelligence that has gained recent interest in all areas of the industry, motivated primarily by the accelerated growth of computer capabilities and data availability. However, one of the main difficulties for its application is the need for experts who know the internal details of the multiple models that can be used. In this context, a new field of study has emerged, AutoML (Automated Machine Learning), which facilitates the use of these techniques by experts from other domains. This paper presents an introduction to the field of AutoML, a brief comparison between existing tools, and a concrete proposal of a technology —AutoGOAL, own authorship— which has been designed to solve machine learning problems of various kinds. Our proposal is competitive with state-of-the-art tools in classic machine learning problems, and it can be seamlessly deployed in more complex domains, such as natural language processing.
Speech – Talk to Your Application

In the previous chapter, we saw how text models can be used to build enriched text and to build smart search applications from unstructured data. In this chapter, we will add a capability to our cognitive computing toolkit – how to understand the request from a user and process these requests via speech. To extend this skillset, you will see how you can take user input via speech, create custom input events, and interact with your user.
Physical culture in the formation of technological competence of a student in the new conditions

The analysis of the problems of modern training of a specialist in a technical university is carried out. The necessity in shaping the capability to overcome problems (tasks) in the conditions of changes is determined. The organizational and methodological conditions for the formation of technological competence of a student as a professionally important quality of a specialist are identified, and a method for its formation is proposed. The possibility of improving the quality of professional education in the new conditions of remote training of students by means of «Physical Culture and Sports» discipline is determined. The stages of self-training of a student in physical education, which is a key element in the formation of technological competence of a future specialist, are presented.
Adaptive Governance for the Internet of Things: Coping With Emerging Security Risks

The Internet of Things (IoT) is a disruptive innovation known for its socio-economic potential, but also for generating unprecedented vulnerabilities and threats. As a dynamic sociotechnical system, the IoT comprises well-known cybersecurity risks and endemic uncertainties that arise as IoT adoption increases and the system evolves. We highlight the impact of these challenges by analyzing how insecure IoT devices pose threats to both consumer protection and the Internet’s infrastructure. While recent regulatory responses are starting to target IoT security risks, crucial deficiencies – especially related to the feed- back necessary to keep pace with emerging risks and uncertainties – must be addressed. We propose a model of adaptive regulatory governance that integrates the benefits of centralized risk regulatory frameworks with the operational knowledge and mitigation mechanisms developed by epistemic communities that manage day-to-day Internet security. Rather than focusing on the choice of regulatory instruments, this model builds on the “planned adaptive regulation” literature to highlight the need to systematically plan for a knowledge-sharing interface in regulatory governance design for disruptive technologies, facilitating the feedback necessary to address evolving IoT security risks.
CODE-MIXING IN SPEAKING OF TENTH GRADE STUDENTS AT SMAN 1 METRO ACCADEMIC YEAR 2019/2020

Code-mixing is the use of two different languages in a sentence without changing the topic. The objectives of this research are to find out the types of code-mixing utilized in students speaking and to know the factors of code-mixing mostly occurred in students speaking. Due to covid-19, the researcher collects the data by using Triangulation namely Participant Observation, In-depth Interview and Documentation through Zoom and WhatsApp Application. Furthermore, analytical research is applied to analyze code-mixing in students speaking of tenth grade students at State Senior High School 1 Metro accademic year 2019/2020. Thus, the result shows that there are 23 out of 33 students use code-mixing in their speaking. It is found 45 code-mixing devided into three types including 21 Insertion which characterized by inserting one or more Indonesian vocabularies into an English sentence or utterence, 19 Alternation which characterized by the existence of clause or sentence alternation between Indonesian and English, and 5 Congruent Lexicalization which characterized by the existence of dialect from Indonesian inserted in tenth grade students English Speaking. Meanwhile, it is found that there are 4 factors of code-mixing namely interlocutor or the person whom they are talking to, culture or habit, confidence and lack of vocabulary.
Recent Study on Maturity Model for IT Managed Services

There is a growing trend for Enterprises to engage Managed Service Providers in order to outsource their IT related activities. The basic intention of adopting a managed service is to transfer the responsibility of managing IT assets to the Managed service provider (MSP) for a financial consideration. The delivery capability of an MSP needs to be assessed in a standardized manner, which can be achieved by way of conceiving a Maturity model for the purpose. A study was conducted to develop a Maturity model for Managed Service providers. This model was implemented on a specific environment and the results were documented. The model had to undergo a few iterations and was refined during the implementation. Maturity scores for target rating were finalized after discussions with the customer teams from functional domains.
IMPLEMENTATION OF INTEGRATION MODEL OF EDUCATION QUALITY MANAGEMENT IN THE COMPREHENSIVE COMPLEX

The article researches the concept and necessity of integration and integrative approach in the educational process. It grounds the peculiarities of implementation of integration model in the comprehensive complex under present-day conditions.
Multi -Turn Response Selection with Temporal Gated Graph Convolutional Networks

Multi-turn response selection is an important task in natural language processing, which is designed for developing dialogue agents. Existing models on this task mainly extract semantic features of dialogue contexts and rely heavily on linguistic matching for response selection. However, these previous approaches simply consider contextual features and largely ignore the temporal information among utterances. In this paper, we propose a novel graph-based retrieval model to tackle the above problems. We first construct a temporal graph based on both dialogue contexts and utterance relations, and then leverage the gated graph convolutional networks to aggregate significant information from all neighboring utterances. Preciously, we exploit the proposed graph-based architecture to perform accurate reasoning over multi-turn dialogues, capturing semantic and temporal features simultaneously for selecting the appropriate response. Experimental results have shown that our model can achieve strong performance on multi-turn response selection compared to the baseline models. Additionally, ablation studies validate the effectiveness of different components in our model.
Flexible entanglement-distribution network with an AlGaAs chip for secure communications

In this work, we combine an on-chip, telecom, broadband polarization-entangled photon source with industry-grade flexible wavelength management techniques to build a reconfigurable entanglement distribution quantum network over up to 75 km between up to 8 users. As an application, we implement a multi-user QKD protocol (BBM92) over our network.
Energy fluctuations in recorder pipes during transient sound attacks and steady state sound

The evaluation of temporal and spatial fluctuations of energy using compressible fluid analysis is proposed as an effective method to clarify the fundamental mechanism of the self-sustained oscilla-tions in a actual recorder. The main factors of the self-sustained oscillations are investigated in more detail by evaluating not only the steady state of the sound where the flow field and the sound field are completely coupled, but also the characteristics at the attack transient of the sound before the coupling is established. By analyzing the large energy fluctuations that occur just below the edge of the labium in the attack transient, it was shown that this phenomenon may be one of the main causes of the self-sustained oscillations. And the characteristics of the energy fluctuations and sound power generation during the steady state of the sound are discussed. It was also focused on the energy variations in another region that is near the exit of the windway.
Mixing it Up

Mozart’s musical dice game is one example of how musicians and other artists have incorporated aleatoric elements into their work. Jazz improvisation means every performance is different. Cage left space for the environment to make its own music, but Xenakis took a mathematician’s understanding of randomness and created avant-garde compositions that use the orchestra in new ways. Generative techniques use random numbers to provide new music and other kinds of art on demand. Blocked creativity can be freed by deliberate injections of spontaneity.
Determining the new role of accountants, identifying the challenges and weaknesses of blockchain technology using the Technology Acceptance Model

Purpose: This study identifies the new roles of accountants in the adoption of blockchain technology in accounting and financial reporting along with determining the weaknesses of this technology. In this regard, a systematic review of the literature in this field has been done in the Web of Science database from the beginning to 2020. Methods: A total of 40 articles were extracted and the qualitative content analysis technique and 10NVivo software were used to analyze the data. Results:Several key application areas were identified along with the weaknesses and challenges of using blockchain in financial accounting and reporting. After analyzing the qualitative content by adopting a qualitative method and analyzing the content of 11 semi-structured interviews, it has modified the initial theoretical model and identified the factors affecting this technology in financial accounting and reporting. Finally, by collecting and analyzing 35 questionnaires by fuzzy Delphi method, he presented the final model and evaluated the views of experts regarding the determination of new roles of accountants and the identification of weaknesses in the use of this technology. Conclusion:The results of the present study show that the main reason for accepting this new technology is the perceived usefulness as a result of a positive impact on the quality characteristics of information and accountants have new roles and tasks in their field of work. This technology also has weaknesses that should be Pay attention.                Contribution:This research helps to better understand the factors that accountants accept new techniques and their impact on the current intention and application of the system in the field of financial reporting.
Extraction of Ship Images using Deep Learning

Ship Extraction is very important in the marine industry. Extraction of ships is helpful to the fishers to find the other ships nearly around the particular area. Still today the fishers are to find the ships using some traditional methods. But now it became difficult due to environmental changes. So, by using the deep learning techniques like the CNN algorithm the ship extraction can be identified effectively. Generally, the ships are identified as narrow bow and parallel hull edge, etc. Here, the Existing system they have used the Tensor flow, to see the performance of the datasets, using Recall and precision. In the proposed system, we are using CNN deep learning techniques to identify the ships. By finding the ships with the techniques, the time will be saved and the productivity can be increased. The features of the ship image are taken and trained using the neural network algorithm and then the prediction is done by testing the images.
The Application of Cooperative Principle in Learning Spoken English

Language is a communication tool since it is the means by which people communicate their thoughts. English is now a common language that is widely transmitted worldwide. It plays an important role in the world and has to be selected as the first foreign language to be taught in Indonesian schools, where four language skills are taught in an integrated way: listening, speaking, reading, and writing. There is a lack of spoken English ability among students. One of the main concepts guiding the language learning of students and achieving a successful outcome is the Cooperative Theory, which Paul Grice suggested. In order to develop English skills, the English teacher must teach the students by applying this theory, especially in speaking and stimulating the interest of the students.
Improving the Research Competence of Students in Physics (On the Example of Teaching Semiconductor Physics)

The development of the didactic provision of an improved methodology for the formation and objective assessment of the level of preparation for research activities of future physics teachers based on a competency-based approach serves to develop the component nature of future physics teachers. This article provides information about the organization of experimental work on the formation of research competencies of future physics teachers, professional tasks of a research nature of various levels of complexity; mastery of research technology.