Reviewerly/exHarmony huggingface dataset:
COMBINING FUNCTION MODELLING AND REQUIREMENTS MODELLING WITH THE IFM FRAMEWORK

Abstract The transmission of information between requirements modelling and function modelling in the product development process often appears challenging because of multiple used models and different terminology of specific disciplines. The integrated function modelling (IFM) framework is used for functional analysis of technical moderate complex systems and supports cross-disciplinary modelling and communication in the design team. To improve the applicability of this method and its supporting purpose in the modelling process, the authors combined requirements as an additional entity with the existing entities of this method. Furthermore, the extended framework has been used to visualise the procedure with this approach as an example. The outlook provides the potential for further development of the method.
A New Principle Toward Robust Matching in Human-like Stereovision

Visual signals are the upmost important source for robots, vehicles or machines to achieve human-like intelligence. Human beings heavily depend on binocular vision to understand the dynamically changing world. Similarly, intelligent robots or machines must also have the innate capabilities of perceiving knowledge from visual signals. Until today, one of the biggest challenges faced by intelligent robots or machines is the matching in stereovision. In this paper, we present the details of a new principle toward achieving a robust matching solution which leverages on the use and integration of top-down image sampling strategy, hybrid feature extraction, and RCE neural network for incremental learning (i.e., cognition) as well as robust match-maker (i.e., recognition). A preliminary version of the proposed solution has been implemented and tested with data from Maritime RobotX Challenge (www.robotx.org). The contribution of this paper is to attract more research interest and effort toward this new direction which may eventually lead to the development of robust solutions expected by future stereovision systems in intelligent robots, vehicles and machines.
Deliverable D7.1 Architecture Design for a pan-European PID system for Digital Specimens

Persistent Identifier (PID) systems are the foundation for achieving the FAIR Guiding Principles (“findable, accessible, interoperable and reusable”). As FAIR data and connecting different data classes (i.e. specimens, genomics, observations, taxonomy and publications) are essential aspects of the BiCIKL project, we need a PID system at least at the European level to create and maintain identifiers for the digital representation of specimens and samples, called Digital Specimens (DS) (Hardisty et al. 2022). The PID system provides the mechanism to ensure that identifiers are globally unique, persistent and resolvable. This system should also manage associated metadata, facilitate provenance, enable discovery, manage states and the life cycle of the PID, link to other derived data and digital content, and allow content providers to enforce metadata constraints. For the successful provision of a PID system, this design document has been created to guide us during the implementation and operation phases. The document is based on an earlier milestone (MS28) that was used for discussion and evaluation with potential end-users.
Techno-economic analysis of fixed versus sun-tracking solar panels

The potential output of photovoltaic (PV) panels is influenced by several factors, including the direction of solar radiation from the sun toward the panel’s surface. The maximum output of the panels is obtained when the panels are vertical to the sun's rays. In this study, a techno-economic analysis is conducted to examine whether an automatic one-axis sun tracker system is an economically feasible option for installing a large-scale PV park in the Nicosia district in the central part of Cyprus. The performance of a one-axis sun tracker with an installed capacity of 781 kWp is compared to a PV system with a fixed flat structure having the same capacity and larger capacity at 1034 kWp. Output generated by the three PV system options is simulated by three alternative simulation software (SolarGIS, PVSyst, and PVGIS). Financial analysis is performed utilizing simulated PV power output, accounting for electricity feed-in tariff and overall cost of the project. The cash-flow model is run for several scenarios defined by different leverage ratios, including no leverage. Considering the technical parameters of a PV system and solar panel characteristics, such as the degradation effect on solar panel efficiency and solar radiation, we estimate the solar tracking system produces about 20%–30% more energy compared to a fixed structure. We find both technologies are economically viable options, however, a one-axis tracker system performs better financially. LCOE in all scenarios is below the highest acceptable level for solar PV projects in Cyprus which is 103 EUR per MWh. LCOE for a solar tracker PV is 39 EUR per MWh with a 30% leverage ratio and up to 79 EUR per MWh with 85% leverage. LCOE for a sun-tracker is ~20% lower than LCOE for a PV with a fixed axis of comparable size. Despite higher investment costs, the solar tracking PV system performs with a 12% higher equity internal rate of return, and a 9% shorter loan payback period compared to the same installed power of a fixed structure. The Financial analysis is complemented by quantified benefits due to avoided carbon emissions. Accounting for carbon benefits makes a sun-tracker PV system economically a better option over the fixed tracker PV system, resulting in 228,000 EUR more benefits. Overall, the present value of net benefits of a solar-tracker PV amounts to 1.39 mil. EUR and due to high irradiation in Cyprus, the carbon footprint of PV power output represents only 6% of the footprint of generating electricity in thermal power plants. When these benefits are accounted for the sum of NPV and social benefits will turn out to be higher for a one-axis tracker compared to the total social benefits of a fixed tracker of the same size.
Boosting Differential-Linear Cryptanalysis of ChaCha7 with MILP

In this paper, we present an improved differential-linear cryptanalysis of the ChaCha stream cipher. Our main contributions are new differential-linear distinguishers that we were able to build thanks to the following improvements: a) we considered a larger search space, including 2-bit differences (besides 1-bit differences) for the difference at the beginning of the differential part of the differential-linear trail; b) a better choice of mask between the differential and linear parts; c) a carefully crafted MILP tool that finds linear trails with higher correlation for the linear part. We eventually obtain a new distinguisher for ChaCha reduced to 7 rounds that requires 2166.89 computations, improving the previous record (ASIACRYPT 2022) by a factor of 247. Also, we obtain a distinguisher for ChaCha reduced to 7.5 rounds that requires 2251.4 computations, being the first time of a distinguisher against ChaCha reduced to 7.5 rounds. Using our MILP tool, we also found a 5-round differential-linear distinguisher. When combined with the probabilistic neutral bits (PNB) framework, we obtain a key-recovery attack on ChaCha reduced to 7 rounds with a computational complexity of 2206.8, improving by a factor 214.2 upon the recent result published at EUROCRYPT 2022.
Understanding the Duplex and Its Security

At SAC 2011, Bertoni et al. introduced the keyed duplex construction as a tool to build permutation based authenticated encryption schemes. The construction was generalized to full-state absorption by Mennink et al. (ASIACRYPT 2015). Daemen et al. (ASIACRYPT 2017) generalized it further to cover much more use cases, and proved security of this general construction, and Dobraunig and Mennink (ASIACRYPT 2019) derived a leakage resilience security bound for this construction. Due to its generality, the full-state keyed duplex construction that we know today has plethora applications, but the flip side of the coin is that the general construction is hard to grasp and the corresponding security bounds are very complex. Consequently, the state-of-the-art results on the full-state keyed duplex construction are not used to the fullest. In this work, we revisit the history of the duplex construction, give a comprehensive discussion of its possibilities and limitations, and demonstrate how the two security bounds (of Daemen et al. and Dobraunig and Mennink) can be interpreted in particular applications of the duplex.
Gestalt Principles Governed Fitness Function for Genetic Pythagorean Neutrosophic WASPAS Game Scene Generation

The maintenance of visual appeal and coherence in the procedural game scene generation is still a difficult problem. Traditional procedural game scene generation algorithms produce samples that show a noticeable resemblance to each other. The proposed algorithm allows us to add diverse game object compositions and increase creativity value in that way. Result diversity is formed by the proposed genetic algorithm modification and MCDM method based on the fitness function. Video game immersion is reached by aesthetic game element pattern composition, and one of the solutions for this issue is to apply automated aesthetic modelling of the generated game levels. In this research, the construction of fitness function was extended by the modelling of aesthetic principles, which were reverse-engineered from Gestalt principles. All rules were implemented by construction of a focal function with a square zone for each matrix cell of the single game scene. Five types of Gestalt rules were modelled and combined into a Pythagorean neutrosophic WASPAS method and the final score calculation algorithm was proposed. The proposed approach to generating game scenes strikes a balance between functionality and aesthetics to provide players with an engaging and immersive gaming experience.
Cyber-physical Systems and Artificial Intelligence: The Role of Cyber Security, Machine Learning, Threats and benefits to Modern Economies and Industries

We have seen several applications based on embedded system principles evolve during the last 20 years. However, embedded systems are only useful for standalone, modest-sized applications. The use of artificial intelligence (AI) in cyber-physical systems is now and, in the future, faced with several difficulties. It also looks at how machine learning, the contemporary economy, and business interact with cybersecurity and artificial intelligence. The emphasis of the literature study is on developing a conceptual framework that will enable automation at both the technological and human levels, hence enhancing AI's resilience. Paradigm changes are a reality in contemporary culture. New technologies that provide high-performance computing capabilities that allow the development of intricate artificial intelligence systems are a contributing factor in these shifts. These advancements have made it possible for brand-new cybernetic systems to emerge, in which artificial intelligence models are employed to carry out specific jobs inside the system using continually produced data. On the one hand, cyber systems are being used more and more often in isolated applications. On the other hand, there is still discussion around the simultaneous integration of cyber systems with other cyber systems, the creation of straightforward cognitive structures, and the profound autonomy of interaction with physical systems. Widely open issue that has only been addressed philosophically in select texts.
Business meetings in the metaverse: stakeholder views evolve

Purpose Organizations have started using the metaverse to sell non-fungible tokens, execute engineering processes and conduct business meetings. A condition of creating value by moving business processes to the metaverse is acceptance of this technology. In business-to-business scenarios, internal employees and external partners may have different views on the topic but must agree upon new practices. Understanding common motivations and challenges associated with using the metaverse is crucial to its success. Design/methodology/approach The authors interviewed managers from a pharmaceutical company considering conducting meetings with clients in the metaverse. A series of 23 statements on reasons for (non)-use was generated. Twenty-five individuals (13 employees and 12 clients) then ranked these statements against each other, revealing what would drive or hinder their metaverse use. The authors compared these perspectives to identify common issues. Findings The authors identified four different views. Views 1 and 2 correspond to internal and external participants, while Views 3 and 4 correspond to external ones only. View 1 is skeptical and underlines the role of peers in acceptance. View 2 is a positive perspective centered on usefulness. View 3 is ambivalent and is centered on efforts required to use the metaverse. View 4 reveals a reversed perspective wherein using the metaverse is a low-effort activity. Originality/value This paper proposes a case study probing acceptance of a realistic business use of the metaverse. This paper identifies risks to mitigate and motivations to leverage when proposing metaverse usage in a business-to-business context.
Self-Attention-Based Bi-LSTM Model for Sentiment Analysis on Tweets about Distance Learning in Higher Education

For limiting the COVID-19 spread, countries around the world have implemented prevention measures such as lockdowns, social distancing, and the closers of educational institutions. Therefore, most academic activities are shifted to distance learning. This study proposes a deep learning approach for analyzing people’s sentiments (positive, negative, and neutral) from Twitter regarding distance learning in higher education. We collected and pre-processed 24642 English tweets about distance learning posted between July 20, 2022, and November 06, 2022. Then, a self-attention-based Bi-LSTM model with GloVe word embedding was used for sentiment classification. The proposed model performance was compared to LSTM (Long Short Term Memory), Bi-LSTM (Bidirectional-LSTM), and CNN-Bi-LSTM (Convolutional Neural Network-Bi-LSTM). Our proposed model obtains the best test accuracy of 95% on a stratified 90:10 split ratio. The results reveal generally neutral sentiments about distance learning for higher education, followed by positive sentiments, particularly in psychology and computer science, and negative sentiments in biology and chemistry. According to the obtained results, the proposed approach outperformed the state-of-art methods.
Face Mask Detection Using Haar Cascades Classifier To Reduce The Risk Of Coved-19

The global epidemic causes extensive damage. Several sectors, including tourism and recreation, have been halted. Since these projects require work together in close contact, it increases the danger of infection. To reduce the spread of COVID-19, keep a safe distance from others and always wear protective clothing. In light of this, we have developed COVID Vision, a system that uses Haar cascades as a classifier for a face mask detector. This will reduce reliance on employees while maintaining COVID-19 criteria. COVID Vision can determine if someone is wearing a mask or covering their lips live. According to the findings, the suggested system correctly displays the output result of human face detection within a range of 0.6 to 1.35 metres away, in lighting conditions ranging from medium to normal, and with facial angles falling within a range of ±40°. Face accessories are allowed on targeted photos as long as they don't cover the face. In conclusion, this approach may reduce the cost of real-time identity verification labour.
CyberTEA: a Technical and Economic Approach for Cybersecurity Planning and Investment

It is essential to look at cybersecurity not only as a technical problem but also from economic, societal, and legal perspectives. Companies need to pay more attention to planning and investments in cybersecurity due to different factors, such as budget constraints and complexities involved in the planning and decision-making processes. Also, companies wrongly do not see themselves as the target of a potential cyberattack. Therefore, there is still a need for approaches that support companies, especially Small and Medium-sized Enterprises (SME), during the cybersecurity planning and investment decisions. This PhD thesis addressed cybersecurity planning and investment gaps by proposing the CyberTEA approach. This approach is composed of a five-phase methodology, a framework, and a set of solutions for cybersecurity planning and investment, considering the technical requirements of cybersecurity and its economic dimensions, such as the potential economic impacts of cyberattacks and the cost-benefit of protections available on the market to protect against specific threats. The evaluations and scientific advances of CyberTEA approach was proven valid to support SMEs while also showing the benefits and opportunities for cybersecurity economic approaches.
Reliable and efficient webserver management for task scheduling in edge-cloud platform

&lt;span lang="EN-US"&gt;The development in the field of cloud webserver management for the execution of the workflow and meeting the quality-of-service (QoS) prerequisites in a distributed cloud environment has been a challenging task. Though, internet of things (IoT) of work presented for the scheduling of the workflow in a heterogeneous cloud environment. Moreover, the rapid development in the field of cloud computing like edge-cloud computing creates new methods to schedule the workflow in a heterogenous cloud environment to process different tasks like IoT, event-driven applications, and different network applications. The current methods used for workflow scheduling have failed to provide better trade-offs to meet reliable performance with minimal delay. In this paper, a novel web server resource management framework is presented namely the reliable and efficient webserver management (REWM) framework for the edge-cloud environment. The experiment is conducted on complex bioinformatic workflows; the result shows the significant reduction of cost and energy by the proposed REWM in comparison with standard webserver management methodology.&lt;/span&gt;
Numeracy Literacy in Early Childhood: An Investigation in Arithmetic, Geometry and Patterns in Early Stage

Early childhood education is a coaching effort carried out for children from birth to the age of six by providing educational stimuli in helping their physical and spiritual growth and development with the aim that children have maximum readiness to enter higher education levels. Numerical literacy in early childhood can be used as a tool used in developing thinking skills in children, supporting children in developing various talents or intellectual potentials they have and can be used as a means of cultivating a positive affective side in instilling basic personalityThis study aims to describe a numeracy literacy skills in early childhood students. The research method used is descriptive qualitative. Researchers used purposive sampling to take research subjects, and obtained as many as 28 PAUD students, and from 28 people 3 people were taken to be analyzed in depth related to their numeracy literacy skills. Instruments in this research are observation, test, Interview, and dokumentation. Data analysis techniques in this study include data reduction, data presentation, and conclusions. The results of research that have been done show that numeracy literacy in early childhood aged 5-6 years of arithmetic, geometry and patterns as follows: (1) Be able to name the symbols of numbers 1-20, (2) Have the ability to using number symbols to calculate, (3) Able to match numbers with number symbols and recognize differences based on "more than"; "less than"; and "most”, (4) Able to classify objects based on color, shape and size (3 variations), (5) Have the ability to sort objects by size from smallest to largest or vice versa, (6) Can estimate the next pattern after seeing the shape of more than 3 consecutive patterns (7) Meets errors in writing number symbols due to the accumulation of information received by the brain. This happens because at the same time, the brain receives information in the form of numeric symbols in Arabic and number symbols in general at the same time, (8) Numeracy literacy activities in the pandemic period for early childhood can still be done one of them with learning involving the environment which without eliminating the element of play but still able to facilitate the development of children.
THE EFFECT OF MEDIA GUESSING GAME TOWARDS UNIVERSITY STUDENTS’ WRITING ABILITY ON DESCRIPTIVE TEXT LOCAL TOURISM CONTENT

This study aims to determine the effect of media guessing games on students’ writing ability on the descriptive text about local tourism. The type of research is quasi-experimental. The population in the research is students of University of Prima Indonesia. The samples were taken by cluster random sampling which consists of two classes namely the experimental class and the control class and each class consists of 25. The experimental group was taught by guessing game media while the control group was taught by conventional teaching media in writing descriptive text. The instruments used were test sheets for writing and observation sheets. The techniques used in analyzing the data were descriptive statistical analysis and t-test. The finding of the research explained that guessing game media of local tourism content successfully effect students’ ability in writing descriptive text, especially on local tourism conten
A REVIEW OF THE CULTURAL HERITAGE LINKED OPEN DATA ONTOLOGIES AND MODELS

Abstract. In recent years, there has been a trend towards synergies among cultural heritage institutions, such as GLAM (Galleries, Libraries, Archives &amp;amp; Museums) collaborations in the field of information resource management. These institutions have been actively promoting the construction of digital humanities projects. Such projects primarily target data resource construction and digital humanities services, which are in line with the service functions of GLAM institutions. With the development of networking and digitisation, museums have been making more prominent contributions to knowledge sharing and dissemination.Digital technology has brought about profound changes in the academic research environment. The expansion of traditional research and the emergence of new questions in the digital environment have promoted novel perspectives, thinking, and methods. With the increase in digitisation of cultural heritage, the scale of data has grown rapidly, and the types of data available have been continuously enriched, from knowledge aggregation to knowledge organization and even knowledge transmission. Therefore, it is necessary to examine the tools of digital humanities, which constitute an important means of knowledge production, and to work with traditional GLAM institutions to promote digital thinking and interdisciplinary knowledge integration methods. At the technical level, methods such as knowledge graphs and ontologies are used to construct a multi-layered and systematic knowledge system. This paper presents a review focused on three cultural heritage models, CIDOC CRM, Europeana and the Sampo Model, and reflects on three aspects of the current models: technical framework construction, digital resources, and service systems.