Reviewerly/exHarmony huggingface dataset:
«INVERTED LEARNING AS AN INNOVATIVE FORM OF EDUCATIONAL PROCESS ORGANIZATION»

The article highlights the need for positive changes in education through the use of innovative learning technologies. Analysis of scientific sources shows that this problem is urgent in the education system. Modern findings of equipping teachers with knowledge based on the innovations and child-centered approach are considered. The meaning and the content of flipped learning concept is specified; the own vision of the term is offered in the article. The principles of literary competence formation among high school students with the use of blended learning are substantiated and determined. The methodological aspects of the model application in a modern school are covered as well as its essence, features, advantages, possible difficulties and conditions which ensure the acquisition of literary education. The appropriateness of introducing such training in Ukrainian literature lessons is substantiated. The use of flipped learning at the Ukrainian literature lesson is demonstrated, due to which students acquire moral and ethical values. In the article there are covered methodological aspects of the Flipped Classroom, implementation possibilities of the competence approach in teaching of Ukrainian literature. The educational process is modeled in accordance with the modern requirements of student-oriented approach and task-based approach and Flipped classroom at the lesson of Ukrainian literature. The article proposes an algorithm based on the flipped learning for conducting the 11th grade Ukrainian literature lesson about the life and career of Valerian Pidmohylny. It is noted that the effective acquisition of knowledge occurs due to a combination of traditional and innovative learning, and it also depends on the student’s moral values and the staged use of technological learning. It is justified that the reading experience is based on the ability to analyze, interpret, compare, draw parallels, draw conclusions, use knowledge of literary theory in practice. It is primarily a combination of logical and sensory aspects, modern means of education, remote teaching and online learning, these components allow students to acquire competencies through projects, discussions and other activities. It is proved that the combination of traditional and innovative learning approaches including the virtual and real educational resources contributes to the transformation of literary knowledge into social and reading experience, prepares students for productive activities by turning them into active learners and changing teachers' role from the main source of knowledge to facilitator
Tumor Detection in MRI Brain Images Based on Saliency Computational Modeling

In recent years, the issue of tumor detection for Magnetic Resonance Imaging (MRI) brain images has become a research hotspot in the field of medical imaging, multimedia and pattern recognition. In this paper, we propose a tumor detection method based on saliency modeling for MRI brain images. Firstly, in order to overcome the influence of the skull, we utilize the morphological method to strip the skull of the MRI brain images. Then, we introduce a principal local contrast based saliency-detection method to enhance the foreground regions which facilitates to get the leision region. Finally, the results are further improved by denoising, segmentation and morphological operations. Experiments performed on MRI brain images show that the proposed method is useful and effective.
ECONOMIC HYPERPARAMETER OPTIMIZATION WITH BLENDED SEARCH STRATEGY

We study the problem of using low cost to search for hyperparameter configurations in a large search space with heterogeneous evaluation cost and model quality. We propose a blended search strategy to combine the strengths of global and local search, and prioritize them on the fly with the goal of minimizing the total cost spent in finding good configurations. Our approach demonstrates robust performance for tuning both tree-based models and deep neural networks on a large AutoML benchmark, as well as superior performance in model quality, time, and resource consumption for a production NLP model fine-tuning task.
Cases of Metaphor and Metonymy Convergence and Metaphtonymy Functioning in Advertising Tourist Discourse of Germany

The article aims to determine relationship between metaphor and metonymy. Various approaches to studying these phenomena are considered: contrasting them, defining metonymy as a kind of metaphor, integrating metaphor and metonymy. The functioning specifics of these phenomena in the advertising tourist discourse are demonstrated. Scientific novelty of the work lies in the authors’ approach to analysing the functioning of secondary nomination means from the standpoint of convergence of metaphor and metonymy; the researchers have identified a metaphtonymic blend in the mental model of familiarisation with the outside world, where the metaphoric component is a fundamental one. As a result, metaphtonymic blend is described as a mechanism of emotional influence on a potential client.
Source Rock Evaluation of Some Mesozoic and Paleozoic Rocks, Faghur Basin, Neith Field, North Western Desert, Egypt

Faghur Basin is one of the most important hydrocarbon provinces inthe northern Western Desert of Egypt. Some of the Mesozoic (Alam ElBueib and Khatatba formations) and Paleozoic rocks at this basin wereevaluated as source rocks based on certain parameters including: thequantity, quality and maturation of the contained organic matter.PetroMode 1D software was used for the construction and prediction ofgeological and geochemical models. Results from organic geochemicalanalysis have clarified that the TOC, HI, S1, S2, %Ro and Tmax values ofAlam El Bueib source rock units range from 0.27 to 6.39 wt.%, 34 to114 mg/g, 0.12 to 0.38 mg/g, 0.23 to 4.3 mg/g, 0.58 to 1.07 % and 409to 450 oC, respectively. While for the Khatatba source rock these valuesrange from 0.41 to 30.09 wt.%, 27 to 155 mg/g, 0.1 to 0.53 mg/g, 0.15 to26.41 mg/g, 1.02 to 1.09 %, 363 to 454 oC, respectively. As for thePaleozoic source rock they are ranging from 0.53 to 4.83 wt.%, 52 to136 mg/g, 0.06 to 0.4 mg/g, 0.29 to 6.57 mg/g, 0.97 to 1.1 % and 406 to467 oC, respectively. Such results indicate that the Alam El Bueib sourcerocks are characterized by type (III) kerogen while Khatatba andPaleozoic source rocks are of type (III) kerogen with inputs of kerogentype (II). Burial history analysis indicates that most of these source rocksare mature and reached their maximum temperature at Neogene time.
English Vocabulary Development Among Undergraduates: Social Media

Social networks play a crucial role in fostering second language learning by providing a wide array of resources and facilitate global interaction among youngsters today.Language instructors therefore should consider using these tools into their learning platform to enrich students' language learning experience.Due to the increased popularity of virtual learning platforms, this study aims to inspect the perceptions of university students about the use and roles of social media in learning English vocabulary.The primary method used for this research study is a quantitative research approach which involves a total of 193 undergraduates from different faculties in University Teknologi MARA (UiTM).The data is gathered through questionnaire and analysed by applying descriptive statistical tools.The eventual findings indicated that undergraduates benefited from the numerous functions of social media in learning and developing English vocabulary.They also said that social media can be used as a apt platform by instructors to communicate with students on course-related material and enable them to share educational information in text, images and videos.It is therefore recommended that educators adapt Gen Z's learning preference via interactive social media tools in the learning of vocabulary.
Analytical bounds for dynamic multichannel discrimination

The ability to precisely discriminate multiple quantum channels is fundamental to achieving quantum enhancements in data-readout, target detection, pattern recognition, and more. Optimal discrimination protocols often rely on entanglement shared between an incident probe and a protected idler-mode. While these protocols can be highly advantageous over classical ones, the storage of idler-modes is extremely challenging in practice. In this work, we investigate idler-free block protocols based on the use of multipartite entangled probe states. In particular, we focus on a class of idler-free protocol which uses non-disjoint distributions of multipartite probe states irradiated over multi-channels, known as dynamic discrimination protocols. We derive new, analytical bounds for the average error probability of such protocols in a bosonic Gaussian channel setting, revealing idler-free strategies that display performance close to idler-assistance for powerful, near-term quantum sensing applications.
Application of augmented reality and close range photogrammetry technology for mapping of cultural heritage areas (case study: Ai Renung Site, Sumbawa Regency)

Abstract The Ai Renung site is the first megalithic complex site on Sumbawa that has 8 sarcophagus objects and has been used as an ancient park by the NTB Provincial Cultural Heritage Preservation Hall. Unfortunately, until now it does not have a cultural heritage map that describes the location and condition of the site, so the presentation of spatial information that describes the location is not conveyed to tourists. In this study, an augmented reality application was made from a combination of 3D model visualization and orthophoto maps. Augmented reality application is implemented on an Android device. Application users can see the visualization of the 3D sarcophagus model virtually using an Android device when scanning one of the markers found on the Ai Renung Site Cultural Heritage Map. This study also analyzes 3D models and orthophoto. The results of the control point analysis on orthophoto, the RMSE value of 0.293 m was produced. Based on the CE90 test of the RMSE value, orthophoto can be used as a base map in making Cultural Heritage Zone Maps with a scale of 1: 1000 and entering into order class 3. As for forming a 3-dimensional model, most 3D model objects have RMSE values that are less than 0.5 m. So that it meets the Level of Detail 3 order criteria.
Sustainable Information and Learning Access at a Rural University in Zimbabwe through a Mobile Application

The current technological revolution must be harnessed to increase access to information and help communities in developing countries make informed decisions that can improve their standard of life. The purpose of this study was to develop an app that attempts to complement traditional media by improving access to timely and relevant information to enhance teaching and learning in deprived rural contexts. The process was guided by design science research methodology. The paper responds to three questions: the processes considered for effective development of apps in resource-constrained environments; the value of mobile apps in supporting teaching; and how mobile apps transform deprived rural institutions. As part of the design research, the rural-university community was engaged in the construction of an app enabling access to educational information, registration portals, fee balances, and coursework. The findings indicate that the app was useful, easy to learn, and provided utility to its users, which consequently transformed their university life. The paper concludes by arguing that in a deprived learning context, mobile apps have the impetus to bridge the rural-urban dichotomy and recentre rural contexts in a direction for sustainable learning.
Degrees of Laziness in Grounding

The traditional ground-and-solve approach to Answer Set Programming (ASP) suffers from the grounding bottleneck, which makes large-scale problem instances unsolvable. Lazy grounding is an alternative approach that interleaves grounding with solving and thus uses space more efficiently. The limited view on the search space in lazy grounding poses unique challenges, however, and can have adverse effects on solving performance. In this paper we present a novel characterization of degrees of laziness in grounding for ASP, i.e. of compromises between lazily grounding as little as possible and the traditional full grounding upfront. We investigate how these degrees of laziness compare to each other formally as well as, by means of an experimental analysis using a number of benchmarks, in terms of their effects on solving performance. Our contributions are the introduction of a range of novel lazy grounding strategies, a formal account on their relationships and their correctness, and an investigation of their effects on solving performance. Experiments show that our approach performs significantly better than state-of-the-art lazy grounding in many cases.
Evolutionary Robotics Controllers with Proprioception Facilitated by Neural-Network-Based Simulators

Abstract Taking inspiration from the navigation ability of humans, this study investigated a method of providing robotic controllers with a basic sense of position. It incorporated robotic simulators into robotic controllers to provide them with a mechanism to approximate the effects their actions had on the robot. Controllers with and without internal simulators were tested and compared. The proposed controller architecture was shown to outperform the regular controller architecture. However, the longer an internal simulator was executed, the more inaccurate it became. Thus, the performance of controllers with internal simulators reduced over time unless their internal simulator was periodically corrected.
Problems with Physical Simulation in a Virtual Lego-based Assembly Task using Unity3D Engine

Augmented Reality (AR) has potential in the manufacturing and manual assembly industry. However, the effectiveness of AR as an assistive system depends on several factors, one of which is information presentation. A set of guidelines for the effective interface design of Augmented Reality systems for manual assembly have been proposed. To validate the design guidelines, it was decided to use a simulated AR approach using Virtual Reality (VR). To evaluate the simulated AR system, it is necessary to also simulate the manual assembly task. This paper describes the challenges faced when developing the manual assembly task simulation, particularly when simulating physical interactions in VR using the Unity3D engine.
Research on Key Technologies of Hand Function Rehabilitation Training Evaluation System Based on Leap Motion

This paper proposes an immersive training system for patients with hand dysfunction who can perform rehabilitation training independently. The system uses Leap Motion binocular vision sensors to collect human hand information, and uses the improved PCA (Principal Component Analysis) to perform data fusion on the real-time data collected by the sensor to obtain more hands with fewer principal components, and improve the stability and accuracy of the data. Immediately, the use of improved SVM (Support Vector Machine) and KNN (K-Nearest Neighbor Algorithm) for gesture recognition and classification is proposed to enable patients to perform rehabilitation training more effectively. Finally, the effective evaluation results of the rehabilitation effect of patients by the idea of AHP (Analytic Hierarchy Process) are taken as necessary reference factors for doctors to follow up treatment. Various experimental results show that the system has achieved the expected results and has a good application prospect.
Research on the International Development Trend of Big Data and Digital Economy and Its Reference to China

With the wide application and development of big data, digital economy has become the innovation power of global economic growth and has an important impact on the development of global social and economic cooperation. From an international perspective, this paper analyzes the development trend and achievements of the United States, the European Union and important international organizations in the field of digital economy. On this basis, this paper analyzes the current situation and challenges of the development of China's digital economy, and puts forward suggestions and measures to promote the development of China's digital economy in view of the digital gap, value assessment, development mode, talent training.
Automatic Hierarchical Reinforcement Learning for Reusing Service Process Fragments

Prevailing research trend is to use Web services for data publishing and sharing among organizations, but existing works often fall short of service reuse.Developing efficient solutions to achieve composite services has drawn significant attention in services computing.Services and service process fragments reuse is critical to improve the efficiency of software development and economize on human and material resources, meanwhile Reinforcement Learning (RL) is one commonly used approach in services computing.However, in service composition and service process fragments (SPFs) reusing scenarios, traditional RL methods cannot guarantee good efficiency for large-scale service processes construction problems.In this paper, we present a novel SPF reusing framework that combines automatic Hierarchical Reinforcement Learning (HRL) and extended Cocke-Kasami-Younger (CKY) algorithm.This framework has the ability to reuse any granularity of SPFs.We firstly get action models and trajectories by means of analysis on historical service process fragments.Furthermore, the ''Causal Analysis'' identifies the causal relationships among the actions in a trajectory, i.e. returning a causally annotated trajectory (CAT).Then, we utilize the SPF-Hierarchy algorithm to discover a coherent task hierarchy for each service process fragment.Finally, we map the hierarchy obtained from the previous stage to the HRL-CKY algorithm, which can fulfill the reuse and retrieval of any granularity of SPFs.The effectiveness and robustness of our approach are evaluated through a set of experiments.
Persistent Covering With Latency and Energy Constraints

Most consumer-level low-cost unmanned aerial vehicles (UAVs) have limited battery power and long charging time. Thus, they cannot accomplish some practical tasks such as providing service to cover an area for an extended time, also known as persistent covering. Algorithmic approaches are limited mostly due to the computational complexity and intractability of the problem. Approximation algorithms that assume unlimited energy have been considered to segment a large area into smaller cells that require periodic visits under the latency constraints. In this letter, we explore geometric and topological properties that allow us to significantly reduce the size of the optimization problem. Consequently, the proposed method can efficiently determine the minimum number of UAVs needed and schedule their routes to cover an area persistently. We experimentally demonstrate that the proposed algorithm has better performance than the baseline.
Image Steganography-Based GUI Design to Hide Agricultural Data

Throughout the ages, safely preserving and transmitting data that have extraordinary importance for humanity has increased its importance with rapid advances in computer technology. Steganography stores hidden data within the files, which are unnoticed by third parties, so it provides secure transmission of data to the receiver. In this study, a steganography-based GUI design has been carried out, which ensures that the agricultural data is safely stored and communicated to the other party. We used LSB one-bit, two-bit, three-bit substitution and PVD algorithms with GUI for stages of agricultural data hiding and extracting at cover images. We also provided extra security using the embedded key and shifting operations on the hidden data before hiding data the cover image. In short, we confused the hidden data in the cover image so that malicious people can't understand. In experimental studies, performance analysis was evaluated by comparing various criteria as similarity ratio (Structural Similarity Index Measure, SSIM), stego image quality (Peak Signal-to-Noise Ratio, PSNR) and data hiding capacity (Payload).
Analysis of Improvement Effects for Flight Training Quality

Currently, flight training is not only a technical instruction that teaches maneuvering operations, but has expertise equal to that of general disciplines. Therefore, flight instructors must have academic knowledge and flight skills. As flight instructors are the first teacher in flight training for students who have never experienced actual flight control, the behavior of flight instructors will affect the students’ flight education. Therefore, the influence of flight instructors for students are quite large compared to other educational institutions. In this study, the factors of instructional behavior were determined, and the actual state of instructional behavior of flight instructors were confirmed through students’ survey. Improvements were derived to solve the problems identified in the survey results. For the follow-up analysis, improvements were applied to the flight instructors for 8 months, and then re-question was conducted to the same students who responded to the first questionnaire to find out the difference in results before and after through a paired t-test.
A Multi-view Approach to Preserve Privacy and Utility in Network Trace Anonymization

As network security monitoring grows more sophisticated, there is an increasing need for outsourcing such tasks to third-party analysts. However, organizations are usually reluctant to share their network traces due to privacy concerns over sensitive information, e.g., network and system configuration, which may potentially be exploited for attacks. In cases where data owners are convinced to share their network traces, the data are typically subjected to certain anonymization techniques, e.g., CryptoPAn, which replaces real IP addresses with prefix-preserving pseudonyms. However, most such techniques either are vulnerable to adversaries with prior knowledge about some network flows in the traces or require heavy data sanitization or perturbation, which may result in a significant loss of data utility. In this article, we aim to preserve both privacy and utility through shifting the trade-off from between privacy and utility to between privacy and computational cost. The key idea is for the analysts to generate and analyze multiple anonymized views of the original network traces: Those views are designed to be sufficiently indistinguishable even to adversaries armed with prior knowledge, which preserves the privacy, whereas one of the views will yield true analysis results privately retrieved by the data owner, which preserves the utility. We formally analyze the privacy of our solution and experimentally evaluate it using real network traces provided by a major ISP. The experimental results show that our approach can significantly reduce the level of information leakage (e.g., less than 1% of the information leaked by CryptoPAn) with comparable utility.