Reviewerly/exHarmony huggingface dataset:
Exploring Liability for Cryptoeconomic Consensus - A Law and Economics Approach

Cryptoeconomic systems, such as cryptocurrencies and decentralized autonomous organizations, rely on consensus at several levels. Their protocols and the open source code implementing them are often the results of consensus among several participants. The systems are updated according to consensus mechanisms set in their protocols. This consensus is sometimes reliant on consensus among another set of participants in other cryptoeconomic systems, such as oracles feeding a cryptoeconomic system with external information. The outcomes of consensus may be illegitimate or harmful, which raises the question of liability. There is a heated debate around such liability – both as a matter of law and policy. Some call for stricter regulation in terms of harsher liabilities, while others argue for more of a light-touch approach, shielding participants from liability in the name of promoting “responsible innovation.” Some even argue for cryptoeconomic systems to be left to themselves and their own architecture-based self-regulation not subject to national laws. However, when cryptoeconomic consensus results in undesirable outcomes, remedies are often searched for in the law, both in public enforcement and private litigation. This paper utilizes law and economics to explore the merits of legalist approaches to liability for cryptoeconomic consensus, normative policy guidance for such liability, and institutional implications for such liability.
Five-Year Web Analytics of the Official Public Information Website of Pangasinan State University from 2017 to 2022

The Pangasinan State University website was redesigned last 2016 and continuously being improve up to the present. The purpose of this study is to understand and interpret the web analytics of the website which contribute to a better decision making in writing personalized content. This more than 5 year data focuses on the acquisition and behavior of audiences on the institutional website of Pangasinan State University which can be accessed at psu.edu.ph. The data scope is from January 1, 2017 to September 30, 2022 where the year of the website was redesigned to meet to ongoing innovations. The methodology of the study includes the installation of Analytical code which tracks the audience from the website which generates reports and to monitor the performance of the website for future reference. The study shows the behavior of visitors and other information that could help the information officer of the University to provide personalized content for the year.
Beyond the Surface Web: How Criminals Are Utilising the Internet to Commit Crimes

The internet has revolutionised society and plays a key role in users lives. The rapid advances in technology means that now more than ever, users have the right to anonymity online, a service which is greatly invaluable to some, however, is leading to illicit behavior in others. Security threats and the distribution of illegal materials and substances continue to take place online, with a combination of legal loopholes and advancing anonymity subsequently leading to slow investigatory processes. This research considers how criminals are using services to their advantage and remaining largely undetected by the criminal justice system. This research also considers how ethically the criminal justice system works when dealing with its investigations with recommendations for the future. The growing use of cryptocurrencies are also considered with its security advantages for users but how the virtually anonymous features are enticing for criminal activity. This research considers whether digital forensics is keeping up with demand within the criminal justice system and whether new services with the standardisation and collaboration of governments is required to aid further investigations.
Remote Leadership: A (Re)qualification of School Leaders in Portugal

The COVID-19 pandemic brought about new challenges to schools’ organization leaderships and to school leaders. This study, of qualitative nature, aims at understanding the impact occurred in the area of school management, in pandemic times, from the leaders’ perspective, in Portugal. The investigation question is: what prevailed during the remote school management of the leader's team amidst the COVID-19 pandemic time? The sample is a video, with 2 min and 47 s, done by the Leader of a Cluster of Schools, in the North of Portugal, within the context of activities related to affection, promoted by the group of Schools’ Libraries, entitled “Month of Affections”, when COVID-19 lockdown was mandatory. The content analysis was done using the webQDA® software. All ethical rules were accounted for. The main results are: (i) adaptation and remote management; (ii) challenges to leadership and (iii) vision for the future. It was concluded that, due to the mandatory social distance, the Leader chose for an active and creative virtual presence (re)qualifying his leadership. The concept of this remote leadership kept the organizational balance, leading his co-workers to achieve the defined objectives. The remote leadership will have to be a dialogical field in the Public Policies of the Ministry of Education and Science in Portugal.
Cyber Range Technical Federation: Case Flagship 1 Exercise

Modern cyber domain is an extremely complex field to master. There are numerous capricious dependencies between networked systems and data. In cyber security, technology has a major role, but the knowledge and skills of the individuals combined with the incident response processes of the organisations are even more important assets. Those assets foster the cyber resilience of the organisation. The most effective ways to uphold these urgent assets are training and exercising. Cyber security exercises in particular have proven their efficiency in improving cyber security skillsets. During the cyber security exercises, it is possible to train cyber defence and incident response manoeuvres in stressful and hectic situations of being under cyber attack or intrusion. To achieve the capability to organise technical cyber security exercises with real attacks and real malware, technical training infrastructure mimicking real networks and systems is required. Such infrastructures are universally called cyber ranges or cyber arenas. Globally, cyber security exercises have become more common during the last decade, and there are several cyber ranges with diverse capabilities. Pooling and sharing the capabilities of cyber ranges raises the requirement to establish a cyber range technical federation. In this paper, a state-of-the-art implementation of the cyber range technical federation is introduced. In addition, the implementation demonstrated and evaluated during the Flagship 1 on-line cyber security exercise is discussed.
An Integrative Machine Learning Framework for Classifying SEER Breast Cancer

Background: Breast cancer is the commonest type of cancer in women worldwide and the leading cause of mortality for females. Despite the fact that many breast cancer patients have no family members who have also had the disease. Women who have it are more at risk than those who don't.Objective: The aim of this research is to classify the death status of breast cancer patients using the Surveillance, Epidemiology, and End Results (SEER) dataset. Due to its capacity to handle enormous data sets systematically, machine learning has been widely employed in biomedical research to answer diverse classification difficulties. Pre-processing data enables its visualization and analysis for use in making important decisions.Methodoloogy: This research presents a feasible machine learning-based approach for categorizing datasets related to breast cancer. Moreover, a two-step feature selection method based on Variance Threshold and Principal Component Analysis (PCA) was employed to select the features from the SEER breast cancer dataset. After selecting the features, the classification of the breast cancer dataset is carried out using Supervised and Ensemble learning techniques such as Ada Boosting (AB), Xtreme Gradient Boosting (XGB), and Gradient Boosting (GB), as well as binary classification techniques such as Naive Bayes (NB) and Decision Tree (DT).Results: In this study, it is observed that the Decision Tree algorithm showed better results than other algorithms used in this analysis (AB, XGB, GB & NB). The accuracy of DT for both train-test split and cross validation achieved as 98%.Conclusion: Utilizing the train-test split and k-fold cross-validation approaches, the performance of various machine learning algorithms is examined. The Decision Tree algorithm outperforms other supervised and ensemble learning approaches, according to the experimental data.
Promoting Environmental Sustainability in Africa: Evidence from Governance Synergy

The present study complements the extant literature by assessing how environmental sustainability can be promoted by means of policies that entail the simultaneous implementation of six governance dynamics, notably, political governance (political stability/ no violence and ‘voice & accountability’), economic governance (government effectiveness and regulatory quality) and institutional governance (corruption-control and the rule of law). The study focuses on 44 African countries for the period 2000 to 2020 and the empirical evidence is based on the generalized method of moments (GMM). The findings show that while the individual governance indicators positively influence carbon dioxide (CO2) emissions, the combined or composite governance indicator has a negative effect on CO2 emissions. Moreover, urbanization, economic growth, trade and foreign investment promote CO2 emissions while information and communication technology in terms of mobile phone subscriptions and internet penetration have the opposite effect. Policy implications are discussed.
The Synergy between Governance and Trade Openness in Promoting Female Economic Inclusion in Sub-Saharan Africa

The debate on the need for Sub-Saharan African (SSA) countries to increase female participation in the economic sector has intensified the coming into force of the African Continental Free Trade Area (AfCFTA) and good governance. This study investigates the joint effects of governance (comprising of political, economic and institutional governance) and trade openness on female economic participation in SSA. The study employs panel data of 42 countries in SSA for the period 1996-2020. The empirical strategy is the dynamic System Generalized Method of Moments (SGMM) estimation technique. The findings reveal that the single effect of trade openness on female economic participation is necessary but not sufficient. Hence, complementing trade openness with good governance further enhances female economic participation in SSA. In general, the joint effect of trade openness and good governance should be a concern for policymakers to promote female economic inclusion.
Data Integration for the Evaluation of Cancer Evolution in Mexico through Data Visualization

Cancer is the third cause of death in Mexico, one of the chronic degenerative diseases that has grown the most throughout the territory. This document describes a system that allows collecting, integrating, and deploying a unified data repository on cancerology in Mexico. Data were obtained from public access sources generated by units specialized in cancer treatment and follow-up. We use data mining techniques for the integration of the data repository. The application developed allows the analysis of the cancer panorama in Mexico. The project involves cleaning processes, integration, selection, and transformation of data in a pre-processing stage, for further analysis and presentation through a graphical interface. The primary objective is to visualize the general behavior and evolution of cancer in Mexico in recent years using data science techniques.
WSC2RCNN: A Deep Learning Actions-based Classifier for Improved Web Service Discovery

Due to the increasing popularity of Web services and their tremendous number, discovery task is shown as the most important and difficult step. The difficulty lies in the limited data provided on them which is, in the most cases, a short textual description. Based on these descriptions, many interesting works have been proposed trying to classify them in an efficient way. In this work, we propose a new approach based on deep learning WSC2RCNN that uses Web services descriptions and actions within these descriptions to improve the classification task, which has given promising results and outperforms state-of-the-art approaches using the same data.
Digital Image Slicing to Strengthen the Security of LSB Technique of Encrypting Text Messages

Among the different forms of social media, textmessages are known to be the most extensivelydisseminated forms of information. This informationcould be private or sensitive in nature, and so need tobe shielded from prying eyes. To conceal textmessages in an electronic photograph, the LeastSignificant Bit (LSB) technique is employed. Themechanism of concealing the message is simpleenough to accomplish the process of concealingprivate information yet, not change the carrierImage. Despite its simplicity and apparent success inhiding things, this approach must be used cautiously.In this study, we will examine a different and simpleto-implement approach to increase the LSB method'slevel of security and blocking any attacker attemptingto spy on the text message or retrieving its content,while maintaining a certain level of LSB method'sefficiency. The suggested solution relies on creating asecret and private key that is difficult to crack inorder to conceal the message. Cutting the digitalImage into blocks generates this key, which comprisesthe block's row and column lengths as well as theblock's image size, which is used to conceal themessage In addition to ensure that the sender andreceiver are both has a compatible technique bywhich the key is used to define the length of eachblock line and column and the block number thatcontains the text message, this will also set aside aportion of the Image to store the key.
Identification of Technical and Technological Factors That Influence Software Development Projects

Nowadays, in spite of the enormous advances and the irruption of agile methods, software development projects have not been able to increase success rates. In the literature, it is possible to find information regarding the main causes of failure in this type of project. Among the main causes identified are mistakes made in project management, insufficient support from top management, low stakeholder commitment, low level of collaboration among team members, and skill development levels of professionals. A key aspect in the execution of a software project is the technical and technological factors that appear as relevant in the literature, but have not been studied in sufficient depth compared to the factors mentioned above. The objective of this work is to identify the technical and technological factors that influence the success of software development projects. In order to identify these factors, a systematic mapping of the literature was carried out. Seventy-seven primary studies were selected and classified according to the defined protocol. The results obtained are quite encouraging since it was possible to identify and categorize a set of technical and technological factors that will allow conducting future research on this topic.
Using Heaps on GPU

Nowadays, searching algorithms are a key component in modern computer science applications. However, traditional approaches of exact search techniques are practicallyan unfeasible solution with the rise of data in high-dimensional databases. The kNN algorithm is frequently used in content based information retrieval systems as it returns similar object sand classifies them. Exhaustive sorting algorithms, such as those based on kNN, can be implemented using a Heap, reducing the computational complexity of the search process. In the present study, we analyze the efficiency of using the Heap data structure on GPUs for solving kNN queries, analyzing the performance of this type of structure as a function of the number of children in the structure. The best results were achieved by increasing the number of children, reaching a speed-up of 1.45x using aternary Heap. The source codes used for the experimentation willbe available to the scientific community in a GitHub repository:https://github.com/ruberhg/GPU-Heaps.
Social Factors Linked to Uncertainty in the Online Educational Context Infirst-Year Engineering Students

Virtual emergency education has been characterized by a lack of contact and directsocial interaction. In first-year students, who experience a process of social integration at the university, this aspect can be linked to a greater perception of uncertainty, complicating their effective integration. The present study sought to evaluate the relationships between variables linked to social integration and the perceived uncertainty during emergency virtual education. For this, a brief instrument was constructed and evaluated to assess the perceived uncertainty in the educational context. An associative-predictive design was used with 459 first-year engineering students to whom a virtual survey was applied to achieve both objectives. The results showed evidence of validity and reliability for the instrument.Inaddition, they showed statistically significant relationships between the different included social integration variables and uncertainty with effect sizes ranging from moderate to small.Based on these results, it is possible to conclude the existence of a relevant link between the social integration of students and the uncertainty perceived during the period of admission to the university. In this way, having social support, feeling that they belong and not being socially isolated can be protective factors against the perception of uncertainty.
Evaluation of Tools to the Fault Localization

Despite the research effort in debugging activity this task is still carried out in the same way since the 60s, when the first symbolic debuggers were introduced and is responsible for a large part of costs in a software project by organizations. A promising approach, called Spectrum-based Fault Localization(SFL), consists of techniques that provide a list of suspicious programelements (eg., statements, blocks, methods and packages)more likely to be faulty. In this study, we compare two SFL toolsthat utilize different metaphors. Jaguar uses a textual metaphor while Code Forest a three-dimensional metaphor. The results ofan evaluation with 119 students using both tools are presented in this article. They were assessed regarding to the effectiveness and efficiency during fault localization. The effectiveness and efficiency were assessed, respectively, by the tool's ability to direct the developer to the faulty method or line and the time spent to locate them. The results show that Jaguar is more effective and efficient than Code Forest; however, the statistical effect size measure is insignificant.
Belonging to Engineering During the First Year in Online Education

Virtual education can have great virtues, but it can also generate unwanted effects due to the lack of social contact and community experience in university students. This article describes the experiences of belonging in 112 students of recent entry to engineering during the period of emergency virtual education in the year 2021. A mixed study was carried out that collected the written reflections of the students regarding the level of belonging experienced, the reasons why they have felt belonging and potential actions to improve belonging to the career they are studying in the emergency virtual education system. A thematic content analysis was carried out to obtain response categories around the questions and the Xi Square test to analyze the emerging contingencies between the categories. The χ2 analysis showed a significant relationship between the experienced belonging and the reasons for this sense of belonging, with a moderate intensity. In addition, a significant relationship was observed between the reasons attributed to membership and the actions proposed to increase it. These relationships showed a moderate-strong intensity. A relationship is concluded between the membership experience, the reasons for membership and possible improvement action.These highlight the importance of face-to-face activity and interpersonal contact, but also the need for articulated pedagogical designs that allow considering the university experience as part of training in virtual scenarios mediated by technologies.
Blockchain Technology

Blockchain is a distributed digital ledger technology that enables individuals and enterprises to store transactions and track assets in a network. Blockchain cannot be corrupted since each node on the network has a copy of the digital ledger. A blockchain network is designed on a decentralized structure, and the nodes on the network maintain it; hence, no governing authority exists. Since central authority does not exist, the information on the nodes cannot be modified without a consensus of the nodes. This feature of blockchain enhances secure transactions and communication on the network. Blockchain technology can be applied in various industrial and technical fields, such as finance, real estate operations, voting, logistics operations, smart contracts, healthcare, and cybersecurity.
Exploring International Research Trends on Technological Pedagogical and Content Knowledge (TPACK)

Objectives This study aims to the international research trend for technology-based teaching content knowledge (TPACK) from a big data bibliographic analysis using the R program.&#x0D; Methods For this research, we extracted 809 SCI and SSCI-level research papers from the Web of Science database and detailed bibliographic information of the papers. We conducted network analysis along with big data analysis of sources, keywords, authors, and references. The overall research was conducted through the steps of data collection, data refinement, and data analysis, and the R program was used for data analysis.&#x0D; Results As a result of this study, most TPACK research articles were published in educational journals specialized in technology education. And researchers from the United States, China, and Europe formed a research network and conducted TPACK research actively. In addition, as the TPACK concept was not established long ago, studies to form the theoretical framework of TPACK and to verify its validity have been mainstream.&#x0D; Conclusions International research on TPACK needs to be conducted more actively in Korea. And also, it is necessary to conduct more research considering various classroom contexts such as gifted, multicultural, and special students and intelligent science labs. In addition, it is required to study the TPACK in a situation where various technology tools are introduced, along with research in subjects other than mathematics and science.