Reviewerly/exHarmony huggingface dataset:
Fundraising in the Field of Education: the curriculum of the discipline – 011 Educational, pedagogical sciences

The curriculum of the discipline “Fundraising in the Field of Education” is compiled in accordance with the educational and scientific program of training the third level of higher education in the field of knowledge 01 “Education/Pedagogy” in the specialty 011 Eeducational, Pedagogical Sciences”. The purpose of the academic discipline “Fundraising in the Field of Education” is: to form a system of knowledge among educational applicants on the theory and practice of the process of attracting resources for the implementation of the project; to determine trends in fundraising activities; to form the methodology of fundraising activities and the necessary provision; highlight the specifics of the functioning of funds and grant programs; form a project budget. The study of this discipline provides for familiarizing graduate students with the modern features of attracting grant funding in accordance with modern trends in international fundraising activities.
A Brief Analysis on Video Compression and Deduplication Models Using Video Steganography with Optimised Feature Extraction Techniques for Integrity Preservation

Increased Internet use has brought about a greater focus on security in recent years. The daily rate of data exchange is increasing as Internet usage grows. Hackers might potentially compromise the daily flow of information. Videos feature a wide variety of sceneries and objects, some of which are static, some of which are constantly moving, some of which are sparsely populated, and some of which undergo complex, non-repetitive motions. The Dynamic Texture (DT) in particular presents a number of difficult challenges due to its constantly shifting appearance and motion. With cloud computing, users have unprecedented flexibility in terms of video data storage, sharing, and accessibility. It has also contributed to the explosive growth of digital data. In order to keep up with this speedy expansion, video deduplication has become a major strategy for Cloud Storage Providers (CSPs) by enabling them to efficiently delete duplicate data from their storage facilities. This research proposes a new compression plot that can safely deduplicate videos stored in the cloud. To efficiently transmit and store digital video files over a network and on computer discs, video compression techniques are used to solve the problem of reducing and deleting superfluous video data. Video steganography, in which information is concealed within video frames, is used in this research. The video compression and deduplication techniques and feature extraction techniques for video steganography for integrity preservation are analysed in this research.
Human Activity Recognition Using CNN-Attention-Based LSTM Neural Network

In the past years, understanding human behavior and classification of human actions and intentions by researching human activity recognition (HAR) using traditional pattern recognition has made great progress. In this paper, a novel approach is proposed based on convolutional neural network (CNN) and attention-based long short-term memory (attentıon LSTM) architecture. Human activity recognition (HAR) or recognizing human behavior is one of the challenging tasks due to human tendencies as the activities are not only complex but also multitasking. This deep learning-based long short-term memory network using convolutional neural networks (CNN-attentıon LSTM) architecture predicts the activities performed by humans and improves the accuracy by reducing the complexity of raw data and also by removing unnecessarily complex data. The convolutional layers act as a feature extractor, where they learn hierarchical representations of the image by applying multiple filters to the input image and passing the resulting feature maps through multiple activation functions. These learned features are then used as input to another classifier, such as a attention LSTM networks, to make the final prediction. On the internal UCF50 dataset, the proposed model achieves an 84.43% accuracy. The outcomes demonstrate that the suggested model is more robust and capable of activity detection than some of the results that have been reported.
Organizational and Project-based Research Activity: the curriculum of the discipline for higher education applicants of the degree of Doctor of Philosophy in the specialty "011 Educational, pedagogical sciences"

The curriculum of the discipline “Organizational and Project-based Research Activity” is compiled in accordance with the educational and scientific program of training of the third level of higher education in the field of knowledge 01 “Education/Pedagogy” for specialty 011 “Educational, Pedagogical Sciences”. The aim of the discipline “Organizational and Project-based Research Activity” is to form systemic comprehension of peculiarities of organizing and financing academic, sector-specific, university and corporative sectors of science in Ukraine and abroad among students.
ANALYSIS OF TRENDS IN HIGHER EDUCATION IN DIGITAL TRANSFORMATION

The article is devoted to changes in organizational and economic relations in a higher educational institution, occurring under the influence of the digital transformation of society. Based on the analysis of trends in the development of higher education in the context of the digital transformation of society, the goal is to create a predictive vision of educational processes and develop recommendations for its development. Based on the analysis of trends in the digital transformation of society and the individual himself, the trends towards the creation of information and didactic complexes as the main tool for the formation of student competencies in new conditions are shown, which will entail changes in the concept of managing higher education. Actual changes in a person and society lead to a transformation in the quality of transmitted knowledge and competencies, methods and tools of training, and, consequently, to qualitative changes in the higher education itself.
Availability Aware Online Virtual Network Function Backup in Edge Environments

With the rapid advancement of edge computing and network function virtualization, it is promising to provide flexible and low-latency network services at the edge. However, due to the vulnerability of edge services and the volatility of edge computing system states, i.e., service request rates, failure rates, and resource prices, it is challenging to minimize the online service cost while providing the availability guarantee. This paper considers the problem of online virtual network function backup under availability constraints (OVBAC) for cost minimization in edge environments. We formulate the problem based on the characteristics of the volatility system states derived from real-world data and show the hardness of the formulated problem. We use an online backup deployment scheme named Drift-Plus-Penalty (DPP) with provable near-optimal performance for the AVBAC problem. In particular, DPP needs to solve an integer programming problem at the beginning of each time slot. We propose a dynamic programming-based algorithm that can optimally solve the problem in pseudo-polynomial time. Extensive real-world data-driven simulations demonstrate that DPP significantly outperforms popular baselines used in practice.
Artificial Intelligence in the Arab World: Intellectual Property Challenges

This research aims to explore the challenges facing intellectual property in the field of artificial intelligence in the Arab world. Artificial intelligence is an advanced technology based on innovation and creativity, so the protection of intellectual property in this area becomes crucial to encourage technological development and innovation in the region.The research addresses a range of intellectual property-related challenges in the field of artificial intelligence in the Arab world, such as the weakness of existing legislation and policies, the difficulty of applying intellectual property rights in an advanced and rapidly changing technological environment, and issues of privacy, security and data control.In light of these challenges, the research provides recommendations to strengthen the protection of intellectual property in the field of artificial intelligence in the Arab world. Among these recommendations, they include enhancing awareness and education on the importance of intellectual property rights, improving legislation and policies related to intellectual property, strengthening international and regional cooperation in the field of intellectual property protection, and supporting research and development in this area.These recommendations aim to promote awareness, legislation and policies related to the protection of intellectual property in the field of artificial intelligence in the Arab world, which promotes technological development and innovation and contributes to enhancing economic sustainability and development in the region.
Evolutionary Multitasking Based on Team Learning Strategy

Multi-factorial optimization (MFO) is a popular optimization mechanism recently, which aims to optimize multiple tasks in a single run. Generally, the multi-factorial optimization algorithm uses the random learning strategy to generate offspring, which leads to an inefficient exploration ability of the algorithm. To address this problem, this paper proposed a simple and effective strategy called team learning strategy (TLS). The proposed learning strategy divided the population into excellent team and ordinary team. Different teams employ different learning strategies. Moreover, nine MFO problems were used to assess the effectiveness of the proposed strategy. The experimental results show that the team learning strategy can improve the performance of the algorithm.
CenterNet-Based Target Detection Method for Remote Sensing Images

With the wide application of remote sensing image detection in military and civil fields, fast and accurate identification of small and dense targets with low imaging quality in remote sensing images becomes the focus and difficulty of remote sensing target detection research based on deep learning techniques. A CenterNet-based target detection method combining attention mechanism is proposed, which utilizes ResNet-50 network for basic feature extraction; an improved channel attention module (ECA-NET) is introduced at the backbone output to weaken the expression of non-concern points while enhancing the information channel of concern points; and adjusts the learning strategy in stages to accelerate the model convergence. Experiments are conducted on remote sensing dataset, and the improved CenterNet algorithm increased 13 percentage points compared with the original, and the detection speed reached 52.61 frames per second. The experimental results show that CenterNet-based target detection method maximizes the remote sensing target representation capability of CenterNet under the condition of maintaining certain computational efficiency, effectively balances the accuracy and speed of remote sensing target detection, and is crucial in practical applications.
Formalising contextual expert knowledge for causal discovery in linked knowledge graphs about transformation processes: application to processing of bio-composites for food packaging

With numerous parameters and criteria to take into account, transformation processes are a challenge to model and reason about. This work can be eased thanks to knowledge graphs, which are a widespread practice for formalising knowledge associated with structured and specialised vocabulary about a given domain. They allow to draw semantic relations between concepts, and thus offer numerous tools for reasoning over complex queries. Yet, some of these queries in transformation processes might rely on an additional layer hard to transcribe: uncertainty. In this article, we present how knowledge graphs and probabilistic models can benefit each other for reasoning over transformation processes and address the necessity of formalising contextual expert knowledge for this combination. We then show how this can be used for (1) reverse engineering approaches and (2) linking knowledge bases, through a detailed example on the process of bio-composites for food packaging.
The Role of Economic Freedom in the Relationship between Foreign Direct Investment and Economic Growth: Evidence from Former Socialist Countries

This study investigates the role of economic freedom in attracting foreign direct investment (FDI) and its impact on economic growth in 15 former socialist countries from 2000 to 2021 through the Generalized Method of Moments estimation method. Our findings suggest that higher economic freedom helps countries attract additional foreign investment. Furthermore, we found that a one-unit increase in the economic freedom index increases the real gross domestic product per capita by 0.019%. The findings also reveal that a 1% increase in FDI leads to a 0.585% surge in real income per capita, whereas trade openness surges income by 1.24%. These results reveal that FDI has a positive impact on economic growth, suggesting that FDI is an important factor driving economic development in former socialist countries. This study also provides policy recommendations based on the findings, highlighting the importance of promoting free and healthy competition, transparency, accountability, and investment in education and infrastructure.
Reducing Capital Flight in Africa: Does Regional Financial Integration Matter?

Capital flight continues to be an issue of paramount importance for developing economies, as it deprives them of the funds required for economic takeoff. Hence, this paper aims to analyze the effect of regional financial integration (RFI) on capital flight in Africa. Based on a sample of 23 countries, we specify and estimate an asset demand model of capital flight using a portfolio choice analysis by the system-generalized method of moments for the period 1996-2015. We find two important results. First, the RFI reduces capital flight. This result becomes even more interesting when the quality of governance is considered. Second, structural breaks in the RFI-capital flight relationship explain why the RFI has had a mixed effect on the capital flight over the study period. We recommend that the attractiveness of regional financial services be enhanced concurrently with the standardization of banking and financial regulation in Africa.
PENERAPAN MODEL PROBLEM BASED LEARNING SEBAGAI UPAYA UNTUK MENINGKATKAN KETERAMPILAN MENULIS TEKS EKSPOSISI DI SMP 5 PALU

The study in this pap The background of this research is the lack of students' ability in writing skills, learning to write in schools in particular does not get the dominant attention so that students' ability to write is still very low. Methodologically, teachers are generally less varied in choosing the method used. This study aims to determine the increase in understanding of class VIII students of SMP 5 Palu in writing exposition texts using the Problem Based Learning (PBL) model. This type of research is Classroom Action Research (PTK) which is carried out in two cycles. Each cycle goes through four stages, namely planning, implementing actions, observing and reflecting. The research subjects were students who were active and enrolled in the even semester of the 2022/2023 school year with a total of 19 students. The data collection technique used observation and concept comprehension ability tests to collect the required data and as a benchmark for students' ability to write exposition texts based on minimum completeness criteria. Data analysis techniques using qualitative and quantitative descriptive analysis. The results showed that there was an increase in conceptual understanding from cycle I to cycle II, with the proportion of completeness 58 with an average of 72 in cycle I, to 89 with an average of 84 in cycle II, as well as the application of the Problem Based Learning model can increase students' understanding in write expository text.
Graffiti Identification System Using Low-Cost Sensors

This article introduces the possibility of studying graffiti using a colorimeter developed with Arduino hardware technology according to the Do It Yourself (DIY) philosophy.Through the obtained Red Green Blue (RGB) data it is intended to study and compare the information extracted from each of the graffiti present on different walls.The same color can be found in different parts of a single graffiti, but also in other graffiti that could a priori be of different authorship.Nevertheless, graffiti may be related, and it may be possible to group graffiti artists and "gangs" that work together.The methodology followed for the construction of the colorimeter and its real application in a practical case are described in four case studies.The case studies describe how graffiti were identified and recognized and they provide a comparison of the collected color samples.The results show the added value of the colorimeter in the graffiti recognition process, demonstrating its usefulness on a functional level.Finally, the contributions of this research are outlined, and an analysis is carried out of the changes to be made to the proposed method in the future, for improved graffiti color identification.
An analysis of the connection between the national curriculum in elementary and secondary schools and the learning contents of education for sustainable development (ESD)

This study aims to analyze the connection between the achievement standards of elementary and secondary school curriculum and the learning contents of education for sustainable development (ESD) in order to lay the groundwork for enhancing ESD in schools, which is limitedly dealt in a few subjects. In order to analyze the connection, a working group was formed with experts from each school subject, and a total of 46 experts participated. The analysis was conducted in two stages; in the first analysis, each expert analyzed individually for each subject, and in the second analysis, experts reviewed and adjusted the results of the first analysis to reach a final agreement. After the analysis by subject was completed, the results were synthesized and analyzed for the learning domains and contents of ESD in elementary and secondary schools, and the final results were presented as a block graph. The results by learning domains are as follows. In the major domain I, which deals with backgrounds of sustainable development and ESD, the achievement standards of social studies, science, and practical subjects (technology and home economics) showed higher connectivity than other subjects. In the major domain II, which deals with the environment and ecological aspects, the achievement standards of elementary school integrated subjects, safe life, social studies, and science showed relatively high connectivity compared to other subjects. In the major domain III, which deals with social and cultural aspects, the achievement standards of elementary school integrated subjects, safe living, social studies, moral studies, practical studies (technology and home economics), and physical education showed relatively high connectivity. In the major domain IV, which deals with the economic aspect, the achievement standards for social studies and practical subjects (technology and home economics) showed relatively high connectivity. These results are expected to help enhance ESD in classes of various school subjects.
DiSSCo Prepare Project: Increasing the Implementation Readiness Levels of the European Research Infrastructure

The Distributed System of Scientific Collections (DiSSCo) is a new world-class Research Infrastructure (RI) for Natural Science Collections. The DiSSCo RI aims to create a new business model for one European collection that digitally unifies all European natural science assets under common access, curation, policies and practices that ensure that all the data is easily Findable, Accessible, Interoperable and Reusable (FAIR principles). DiSSCo represents the largest ever formal agreement between natural history museums, botanic gardens and collection-holding institutions in the world. DiSSCo entered the European Roadmap for Research Infrastructures in 2018 and launched its main preparatory phase project (DiSSCo Prepare) in 2020. DiSSCo Prepare is the primary vehicle through which DiSSCo reaches the overall maturity necessary for its construction and eventual operation. DiSSCo Prepare raises DiSSCo’s implementation readiness level (IRL) across the five dimensions: technical, scientific, data, organisational and financial. Each dimension of implementation readiness is separately addressed by specific Work Packages (WP) with distinct targets, actions and tasks that will deliver DiSSCo’s Construction Masterplan. This comprehensive and integrated Masterplan will be the product of the outputs of all of its content related tasks and will be the project’s final output. It will serve as the blueprint for construction of the DiSSCo RI, including establishing it as a legal entity. DiSSCo Prepare builds on the successful completion of DiSSCo’s design study, ICEDIG and the outcomes of other DiSSCo-linked projects such as SYNTHESYS+ and MOBILISE. This paper is an abridged version of the original DiSSCo Prepare grant proposal. It contains the overarching scientific case for DiSSCo Prepare, alongside a description of our major activities.
Deterioration of the deterrence function against the information criminal

Summary The characteristics of cybercriminal are throwing their repercussions on the function of public deterrence and private deterrence in light of the traditional criminal methods established to treat with classical crimes. In an attempt to overcome these repercussions, it is necessary to diversify the penalties for crimes that occur in the digital environment and to move towards alternative penalties that have been proven effective in reforming and rehabilitating offenders, such as the punishment of community service or wearing an electronic bracelet applied in some countries and other modern methods. As well as working to intensify efforts to spread cyber-ethics starting from the childhood stage by adding cyber-ethics to educational curricula to avoid all forms of computer related crimes; As Teaching computer and internet ethics is an essential step in combating crime. Keywords: Cybercriminal, Public deterrence, Private deterrence, Deterrence obstacles, Rehabilitation
Anomaly Detection in Digital Industry Sensor Data Using Parallel Computing

The article presents the results of case studies on the anomaly discovery in sensor data from various applications of the digital industry. The time series data obtained from the sensors installed on machine parts and metallurgical equipment, and from the temperature sensors in the smart building heating control system are considered. The anomalies discovered in such data indicate an abnormal situation or failures in the technological equipment. In this study, the anomaly is formalized as a range discord, namely a subsequence, the distance from which to its nearest neighbor is not less than the threshold prespecified by an analyst. The nearest neighbor of the given subsequence is a subsequence that does not overlap with this one and has a minimum distance to it. The discord discovery is performed through the parallel algorithm for GPU developed by the author. To visualize the anomalies found, a discord heatmap method and an algorithm for selection the most interesting discords regardless of their lengths are proposed.