Reviewerly/exHarmony huggingface dataset:
Motivating Blockchain Stakeholders: An Examination of Miner Ownership and Its Determinants Over Time

In this paper, we examine a model of ownership - an important yet underexplored governance phenomenon of blockchain platforms - and explore its dynamic long-run and short-run determinants over time. We particularly focus on the ownership of miners given the critical roles of these blockchain actors in ensuring the blockchain operations and security. Building on the psychological ownership theory, we suggest that miner ownership represents the extent to which miners invest time, effort, and energy to advance the cause of the blockchain. We test our model with on-chain weekly data of seven proof-of-work permissionless blockchains from 07/08/2017 to 27/09/2021 using a panel autoregressive distributed lag (ARDL) approach. We find that, in the long run, miner ownership reacts primarily to market and network-related factors; such that there is a positive impact of transaction volume, price, and number of active addresses but a negative impact of price volatility on miner ownership. In the short run, we find that changes in miner ownership are primarily driven by changes in price. Notably, in both short-run and long-run analysis, mining and energy-related factors appear to be less important to predict miner ownership. Our study also offers novel and empirical insights into the dynamics of blockchain governance.
Short Essay Series - Deconstructing Bias in AI Systems: Is Data Volume the Solution?

Deconstructing Bias in AI Systems: Is Data Volume the Solution?" by Albert Tan Sin Hon delves into the critical issue of bias in Artificial Intelligence, challenging the common notion that increasing data volume can rectify these biases. Tan explores the multifaceted nature of AI biases, including data, algorithmic, and human biases, and how they intersect with social categories like race, gender, and class. He argues for a comprehensive approach to address AI biases, encompassing diversified data sets, ethical guidelines, legal frameworks, and third-party audits. This essay emphasizes that tackling AI bias is not just a technical issue but a profound ethical and social challenge, requiring a collective effort to ensure AI's fair and equitable application in society.
A Multiparty Commutative Hashing Protocol Based on the Discrete Logarithm Problem

Let X and Y be two sets and suppose that a set of participants P={P_1,P_2,...,P_n} would like to calculate the keyed hash value of some message m known to a single participant in P called the data owner. Also, suppose that each participant P_i knows a secret value x_i. In this paper, we will propose a protocol that enables the participants in this setup to calculate the value y=H(m,x_1,x_2,...,x_n)$ of a hash function H:X^{n+1}->Y such that: - The function H is a one-way function.- Participants in P\{P_i} cannot obtain x_i. - Participants other than the data owner cannot obtain m. - The hash value y=H(m,x_1,x_2,...,x_n) remains the same regardless the order of the secret x_i values.
arXiv.org An Innovation in Research Communication

Scholarly communication is a process that has remained unchanged for centuries. As a system, it provides mechanisms to verify knowledge and information. However, its shortcomings include, prohibitive cost, lack of transparency and delays. ArXiv is an innovative service anchored in information and communication technologies to ameliorate some of the shortcomings of the scholarly communication system. The service was created by Paul Ginsparg at Los Alamos Laboratory in 1991, and has succeeded in revolutionizing the scholarly communication system, providing a faster, cheaper, and more transparent option. This chapter traces the development of the service, its functions, drawbacks, and future direction.
ASSESSMENT OF THE LEVEL OF DIGITAL MATURITY OF THE SPHERE OF CULTURE: CLASSIFICATION OF REGIONS OF RUSSIA

The purpose of the article is to analyze the features and trends in the development of digital infrastructure in the cultural sector, as well as assess the level of digital maturity in this area in the regions. The data was analyzed and the dynamics of digital processes in the field of culture for 2013-2021 were determined for 80 constituent entities of the Russian Federation. Using indicators of the share of public libraries with Internet access; museums that have a website on the Internet in the total number of museums; theaters with a website on the Internet, in the total number of theaters; of the volume of the electronic catalog available on the Internet, for each region, the Digitalization Index of the Cultural Sphere was calculated and the rating of Russian regions for 2021 was presented. The results showed that the level of digital maturity of the cultural sphere varies significantly across regions, and inequality in the level of digital development in this area also persists. Leading regions that have achieved high results in digital development, as well as lagging territories, have been identified. The classification obtained during the study allows for a more targeted implementation of cultural policy in the regions of Russia.
DE AEROPORTOS, AVIÕES E NUVENS: LEITURA PÚBLICA EM BIBLIOTECAS PLURIFUNCIONAIS DE PORTUGAL E DO BRASIL

The work presents the results of a study based on a bibliographic revision concerning the potential of public reading mediated by libraries in the critical and creative reading formation of users in order to contribute to the formation of cultural identity and the exercise of citizenship. Libraries meet specific socio-cultural development objectives in the territories where they are located, meaning they can and should dialogue with the contextual needs for transformation of the respective realities, often marked by deprivation of access to knowledge, which results in illiteracy and low levels of education. Access to information provides the opportunity to build knowledge, produce science, technology and innovation through the power of public Reading, promoted mainly through the democratization of access to books. Historians such as Alberto Manguel (1997), Frédéric Bardier (2018), Cristian Brayner (2018) and Irene Valejo (2022) encourage us to look at the millennial history of resistance of libraries in order to engage in the struggle for the maintenance of these cultural spaces for public reading, as well as the redefinition of their use through plurifunctionality.
Environmental Factors and the Performance of PV Panels: An Experimental Investigation

With the increase in demand for renewable energy, photovoltaic (PV) panels have emerged as a major alternative for harvesting solar energy. However, the efficiency and performance of PV panels are inextricably related to environmental conditions. This study examined the effect of ambient variables on the performance of photovoltaic (PV) panels. Through controlled tests, the researchers investigated critical environmental parameters such as sun irradiance, temperature, wind speed, humidity, and dust deposition. Modern sensors and data-gathering methods were used to monitor how these variables affected PV panel output. Statistical tools were used to determine the relationship between environmental factors and PV panel efficiency. The findings showed a clear relationship between environmental variables and PV panel performance. Solar irradiance was recognized as a major indicator for energy generation, while temperature had complex implications on current output. Wind speed, relative humidity, and dust deposition were discovered to have discernible detrimental effects on panel performance. This study adds to the increasing knowledge about PV systems by highlighting the complex links between ambient conditions and panel efficiency. The findings highlight the importance of site-specific considerations in building and running PV installations to ensure optimal energy output and system longevity. The article's results have practical consequences for both the solar energy sector and researchers, leading to the development of ways to improve PV panel performance and contribute to the sustainable energy landscape.
Data Portability Revisited: Toward the Human-Centric, AI-Driven Data Ecosystems of Tomorrow

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Can new technologies replace the experience that cultural heritage sites and museums essentially offer?

When visiting cultural heritage sites and museums, we rely on our senses in perceiving the world around us, especially architectural and artistic sensations. Even though empirical foundation can often be deceitful, it represents the stimulus we form a response to and what ultimately becomes our memory of the space. With our whole world being constantly digitalised, especially during the COVID-19 pandemic, our personal and work relationships mostly became linked to technology. The aim of this paper is to question new technologies' use (Virtual Reality, Augmented Reality, Natural Interaction, Metaverse), values and dangers recently underlined in the public discourse, as well as whether heritage sites and their users thrive in virtual surroundings at all. Using the Stimulus-Organism-Response model, this paper investigates whether the past still has a future in the traditional, formal sense. The main question is: What is the cultural significance of heritage in a virtual world and is digital heritage possible, or is this an oxymoron? The conclusion suggests that new technologies' use should be carefully and moderately carried out and limited to several situations.
Performance analysis of REST API technologies using Spring and Express.js examples

The purpose of this article is a comparative analysis of two technologies for building applications in REST architecture. A Java-based development framework - Spring, and a framework designed for JavaScript language and Node environment - Express.js were analyzed. The test application was designed and implemented in both studied technologies. Using the Apache JMeter tool, HTTP request processing times were measured by operating on simple text data. The experiment was based on 5 scenarios repeated for a different number of users in the range of 10 to 100, with a constant number of executed requests to the server. The analysis conducted showed that the application implemented in Express.js handles HTTP requests up to 249% more efficiently than its counterpart in Spring.
Comparative Analysis of Selected Game Engines

This article presents a comparative analysis of two popular graphic engines, namely Unity and Unreal Engine 5. The objective of the study was to gather insights into the performance and quality of applications developed using these engines. The research involved creating two games, followed by conducting performance tests and collecting user feedback on the quality and performance of these games. The results indicated that the application developed in Unity exhibited superior performance, while the application developed in Unreal Engine 5 received higher user ratings in terms of visual aspects.
Implementation of a set of condition for pedagogical support of the existential choice of a member of a group of different ages at the place of residence (based on the materials of a pilot studi)

Implementation of a set of conditions for pedagogical support of the existential choice of a member of a group of different ages at the place of residence (based on the materials of a pilot study) Annotation: In the article, the author considers such concepts as existential choice, pedagogical support, reveals the components of the model of pedagogical support for the existential choice of a participant in the RVO and the conditions for the success of its implementation, developed taking into account the specifics of the interaction of different ages, among which are the following: - realization of the subjective position of the participants of the group of different ages; - the eventfulness of the activities of a detachment of different ages; - creation of situations of overcoming. The results of the study confirm the effectiveness of forms and methods that ensure the implementation of the conditions for pedagogical support of the existential choice of a member of a group of different ages and contribute to the formation of a subject position in children, the ability to overcome difficult life situations, motivation for self-development in the course of reflection of events. The article is intended for leaders of temporary groups of different ages at the place of residence, as well as teachers working with children's associations of different ages in the system of additional and general education.
Features of the development of cognitive interest of younger students through group work at the lessons of literary reading

Based on the results of the author's research, the article identifies the main problems and features of the cognitive interest of younger students, and identifies methods and means of its development. The general significance of cognitive interest in the structure of the educational environment of elementary school is substantiated and the key directions of the teacher's activity in the use of group forms of work in literary reading lessons are formulated.
Spiritual and moral ideas of pedagogy of the outstanding scientist Konstantin Dmitrievich Ushinsky (on the 200th anniversary of birth)

The pedagogical heritage of K.D. Ushinsky is constantly connected with Christian roots, while in his fundamental work "Anthropology of Man" three aspirations of human activity are distinguished - corporal, spiritual and spiritual. The big role K.D. Ushinsky gave to the primary education of the younger generation, publishing special manuals aimed at using folklore and fairy tales.
Patterns of interaction between theoretical, methodological and practical aspects of education in the system of higher education and the subsequent work activity of students

The relevance of the presented study is due to the ongoing changes in the domestic system of higher education, including the forced withdrawal of Russia from the Bologna process, which predetermined new challenges in the development of a practice-oriented approach to learning, which determine the relationship between learning processes in the higher education system and the processes of subsequent work of students. The purpose of the presented research is to identify patterns of interaction between theoretical, methodological and practical aspects of education in the system of higher education and the subsequent work activity of students in the light of modern challenges for the national economy. The scientific novelty of the results obtained lies in identifying the composition of the main patterns of interaction of the listed theoretical, methodological and practical aspects of training in the system of higher education and the subsequent work of students, including: the use of a competency-based approach to learning, the use of interdisciplinary relationships, the implementation of the processes of humanization of the educational environment, the need for universities independently predict the demand for professions. The practical significance of the results obtained lies in the possibility of their use in the formation of a new domestic system for the development of higher education.
Analysis of the ergonomics of interfaces of popular e-marketing tools

This article analyses the ergonomics of the interfaces of selected e-marketing tools. The main aim of the study was to verify whether all the examined tools have a similar user interface quality. The research was conducted using the cogni-tive walkthrough method, a modified LUT list with WUP scores, and a questionnaire for assessing tool usability based on Nielsen heuristics. Three tools designed for Internet monitoring were analysed - Brand24, Mention and Awario. The experiment showed that, in terms of the ergonomics of the solutions, not all tools have a similar interface quality. For two of the analysed tools, similar results and ratings were obtained, while one of them presented a noticeably lower level.
Predicting Geckler Classification from Gram Stained Smears Images for Sputum: Image Classification versus Object Detection

A Geckler classification is a criterion how the image is quality based on the number of buccal squamous epithelial (BSE) cells and leukocytes in the Gram stained smears images per $100 \times $ field for sputum. The Geckler classification then determines which of images is valuable to microscope testing for the Gram stained smears images per $1, 000 \times $ field for sputum. In this paper, we predict the Geckler classes by using two methods, image classification and object detection. For the image classification, we predict the Geckler classes from the training images for every Geckler class, without annotating BSE cells and leukocytes. On the other hand, for the object detection, we detect BSE cells and leukocytes from the training images annotated by them and determine the Geckler class by the number of them. Hence, we compare the experimental results of predicting Geckler classes obtained by the image classification with those by the object detection.
Peningkatan Kemampuan Menulis Kalimat Rumpang Melalui Media Audio Visual Berbasis Digital Kelas III di SD Gelam 1 Candi

This study aims to determine the effect of digital based audiovisual media in writing missing sentence for students SD Negeri 1 Gelam Kecamatan Candi Kabupaten Sidoarjo. As for the variable in this study is the audio-visual media as the independent variable, while student learning outcomes as the dependent variable. Data analysis in this study is by using descriptive data analysis techniques; and inferential statistical analysis. The results showed that the learning outcomes before using digital-based audio-visual media showed an average of 60,80; then the average student learning outcomes after using audio-visual media is 79,20. This shows the value of students has increased the average value of 18.40. And the effect of using audio-visual media is very influential. If viewed from the percentage of students' completeness can be categorized into “Very Influential” when compared to before using audio-visual media.
Integrating a Neural Network Library in Embedded Federated Learning

Federated learning has become a popular collaborative machine learning approach in which clients use their local data for training. This results in bandwidth savings since the training data does not have to be transferred to a central node, and also protects the privacy of these data. However, doing federated learning in tiny Internet of Things (IoT) devices is challenging due to the resource constraints of the devices and lack of experimental tools. In this paper, we develop a federated learning implementation that allows training of different machine learning models on embedded IoT devices. Our starting point is a library of neural network models which we have developed. We analyze the metadata to describe these models, design the interaction process between clients and server of a federated learning network, and implement the software. We validate the system by conducting experiments with our implementation deployed on real embedded boards. We observe in a non-IID experiment the capacity of federated learning to provide a trained model whose capacities go beyond those that the node could train by itself. Being heterogeneous data distribution a realistic scenario in distributed IoT devices, we believe that our implementation can be useful for the community as a tool to explore the training of neural networks on microcontrollers with the support of federated learning.
The New Frontier of Cybersecurity: Emerging Threats and Innovations

In today's digitally interconnected world, cybersecurity threats have reached unprecedented levels, presenting a pressing concern for individuals, organizations, and governments. This study employs a qualitative research approach to comprehensively examine the diverse threats of cybersecurity and their impacts across various sectors. Four primary categories of threats are identified and analyzed, encompassing malware attacks, social engineering attacks, network vulnerabilities, and data breaches. The research delves into the consequences of these threats on individuals, organizations, and society at large. The findings reveal a range of key emerging threats in cybersecurity, including advanced persistent threats, ransomware attacks, Internet of Things (IoT) vulnerabilities, and social engineering exploits. Consequently, it is evident that emerging cybersecurity threats pose substantial risks to both organizations and individuals. The sophistication and diversity of these emerging threats necessitate a multi-layered approach to cybersecurity. This approach should include robust security measures, comprehensive employee training, and regular security audits. The implications of these emerging threats are extensive, with potential consequences such as financial loss, reputational damage, and compromised personal information. This study emphasizes the importance of implementing effective measures to mitigate these threats. It highlights the significance of using strong passwords, encryption methods, and regularly updating software to bolster cyber defenses.
Optimized aspect and self-attention aware LSTM for target-based semantic analysis (OAS-LSTM-TSA)

Purpose Aspect-based sentiment analysis (ASA) is a task of sentiment analysis that requires predicting aspect sentiment polarity for a given sentence. Many traditional techniques use graph-based mechanisms, which reduce prediction accuracy and introduce large amounts of noise. The other problem with graph-based mechanisms is that for some context words, the feelings change depending on the aspect, and therefore it is impossible to draw conclusions on their own. ASA is challenging because a given sentence can reveal complicated feelings about multiple aspects. Design/methodology/approach This research proposed an optimized attention-based DL model known as optimized aspect and self-attention aware long short-term memory for target-based semantic analysis (OAS-LSTM-TSA). The proposed model goes through three phases: preprocessing, aspect extraction and classification. Aspect extraction is done using a double-layered convolutional neural network (DL-CNN). The optimized aspect and self-attention embedded LSTM (OAS-LSTM) is used to classify aspect sentiment into three classes: positive, neutral and negative. Findings To detect and classify sentiment polarity of the aspect using the optimized aspect and self-attention embedded LSTM (OAS-LSTM) model. The results of the proposed method revealed that it achieves a high accuracy of 95.3 per cent for the restaurant dataset and 96.7 per cent for the laptop dataset. Originality/value The novelty of the research work is the addition of two effective attention layers in the network model, loss function reduction and accuracy enhancement, using a recent efficient optimization algorithm. The loss function in OAS-LSTM is minimized using the adaptive pelican optimization algorithm, thus increasing the accuracy rate. The performance of the proposed method is validated on four real-time datasets, Rest14, Lap14, Rest15 and Rest16, for various performance metrics.