Reviewerly/exHarmony huggingface dataset:
Collaborative Solutions to Better Achieve Sustainable Development Goals

A number of policy initiatives over the last three decades have been striving to limit the impacts of global warming, reverse land degradation, stop the loss of biodiversity, protect finite natural resources, and reduce the risks associated with environmental disasters. They are summarized under the umbrella of the United Nations Agenda 2030 and the Sustainable Development Goals (SDGs), which together aim at building the resilience of people and systems to new environmental and socioeconomic conditions in the future.Beyond political will, achieving these objectives and tracking progress requires science, data and technology: sophisticated observation instruments and networks, coordinated modeling experiments, scientific assessments, global data access infrastructures and analytical capacity to process and translate data into relevant information. While some of these endeavors have benefited from international coordination and funding under the umbrella of the UN 2030 Agenda for Sustainable Development, the Paris Agreement on climate change, the Sendai Framework for Disaster Risk Reduction and other framework agreements, many still rely on uncoordinated national or international projects, resulting in a proliferation of incompatible, short-lived initiatives. Beyond the waste of time and energy, our main concern is that many solo technological initiatives all solve the same simple problems, deferring work on more complex issues.Advances on the hard global problems of our time requires greater collaboration and innovation. We argue that policy instruments should include technological guidelines, for example mandate the use of international standards for analysis ready data formats, metadata, geodatacubes or machine to machine communication protocols, in order to foster interoperability and software reuse. This would strengthen international collaboration on innovative development, and in turn contribute to the deployment of effective, robust and scientifically credible products to support decision-making and local climate action.
Hypergraph (Beta): v0.9.0 released

We just released Hypergraph (Beta) v0.9.0 [https://libscie.org/hypergraph] 🎉 New releases of Hypergraph will from now on occur on the 28th of every month — we will only break that cycle if there are urgent fixes that we need to ship as soon as possible (e.g., security fixes or bug fixes). If you're interested in understanding how we version our releases, check out Semantic Versioning [https://semver.org/]. If you have Hypergraph (Beta) installe
Web 3.0: The future of the decentralized Internet

Web 3.0 technology represents the evolution of a decentralized Internet that is focused on the desires and needs of users. Decentralization plays an important role in transferring power from providers to users, protecting privacy and regaining control over their information and data. With the evolution of the Internet, users would not need the third party to communicate and perform transactions, and users would be protected from the influence and profiteering of a third party. To stay consistent with its principles of transparency, decentralization, invariability of information and availability, Web 3.0 is designed to function on the principle of blockchain technologies. Blockchain technologies provide the effect of transparency, where every change or transaction can be traced in the network chain. Digital signatures, in the form of code, ensure interaction and authorization between users without the influence of a third party. The method of comparability, analysis of content and historical method were applied in this research. The comparability is made on the evolution of the Internet through the stages and impact on users. The comparative method is important for evaluating the efficiency of the Internet and its effect on users. The historical method was used for the chronological research of phenomenon. The analysis method was used in the content analysis of the literature. The subject of this research is the development of Web technologies and a closer explanation of the concept of Web 3.0, its importance and impact on users. The goal of this research is to point out all the advantages and innovations that Web 3.0 could bring to users.
Overview of Assets 2022

The 24th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2022), was held in Athens, Greece between October 23rd to 26th, 2022. ASSETS continues to be the premier computing research conference exploring the design, evaluation, and use of computing and information technologies with and for people with disabilities and older adults. ASSETS 2022 was held in-person for the first time since 2019. Due to the continuing COVID-19 pandemic, a lightweight online component for virtual conference attendees was conducted as well. In order to support both accessibility and inclusivity, and balancing technical infrastructure and time-zone constraints, all presentations were also pre-recorded and captioned to support both virtual and in-person conference attendees. There were additional creative opportunities for hybrid connections and socializing across modalities, including online trivia and roundtable social networking events. We acknowledge that future ASSETS organizing committees will need to make their own decisions about the length and format of the conference, and so the decision to have an in-person with light-weight online component is not a permanent decision. Overall, ASSETS 2022 had 161 in-person and 146 virtual attendees from 38 countries and 6 continents. For the first time, we hosted 5 virtual workshops, with 94 workshop-only attendees.
Discrete Features Enhancement Based Online Anomaly Detection for Satellite Telemetry Series

Telemetry data, collected from different on-board sensors and transmitted via a telemetry link, are the only basis for monitoring the health status and failure of on-orbit spacecraft. The capability of anomaly detection for telemetry series should be further enhanced in ground stations. Owing to the advantages of temporal modeling, dynamic threshold generation, online application, and strong interpretability, probabilistic prediction methods have been designed to realize anomaly detection of telemetry data. However, they face the risks of false alarms for isolated normal points and missing alarms for continuous anomalies. In this case, an improved method is proposed to promote the detection ability of probability prediction methods for collective anomalies in the telemetry data. Firstly, effective dynamic thresholds are derived by the modified probabilistic prediction model with better prediction confidence levels. Then, we design a discrete method based on equal-width discretization and statistical analysis. In detail, each prediction error is divided into several intervals corresponding to different abnormal levels. In this way, the quantitative characterization ability for samples is enhanced. Finally, based on Markov chain and majority voting integration, discrete feature enhancement at multi-time scales referring to multi-step and multi-window is implemented to realize temporal modeling of multi-step prediction features. The experiments on simulated datasets and real telemetry data verify its effectiveness and applicability compared to other methods of labeling anomalies.
METHODS OF TASK AND MOTION PLANNING FOR ROBOTS: APPLICATIONS AND LIMITATIONS

Robots are increasingly required to perform more complex tasks, which in turn demand advanced planning algorithms. Task and Motion Planning (TAMP) methods, studied for decades, have made significant progress but still face various challenges. This document provides an overview of TAMP's development, encompassing problem-solving, simulation environments, methods, and remaining limitations. It particularly compares different simulation environments and methods used in various tasks, offering a practical guide and overview for beginners. Task planning is typically seen as planning in discrete spaces, while motion planning deals with continuous spaces. Significant progress has been made in integrating discrete and continuous planning methods to address TAMP problems. A recent survey has focused on TAMP integration, summarizing various methods for solving multimodal motion planning and TAMP problems. It introduces general concepts but primarily focuses on methods that operate in fully observable environments, which are far from real-world applications. Additionally, it demonstrates TAMP problem-solving in a theoretical manner that may not be user-friendly for beginners looking to apply these methods in practice. Therefore, this article aims to provide a practical and broader overview to readers, facilitating an easy entry into the field of TAMP for solving various tasks. Keywords: task and motion planning, simulation environment, learning methods, TAMP.
An Intelligent Attention-Based Transfer Learning Model for Accurate Differentiation of Bone Marrow Stains to Diagnose Hematological Disorder

Bone marrow (BM) is an essential part of the hematopoietic system, which generates all of the body’s blood cells and maintains the body’s overall health and immune system. The classification of bone marrow cells is pivotal in both clinical and research settings because many hematological diseases, such as leukemia, myelodysplastic syndromes, and anemias, are diagnosed based on specific abnormalities in the number, type, or morphology of bone marrow cells. There is a requirement for developing a robust deep-learning algorithm to diagnose bone marrow cells to keep a close check on them. This study proposes a framework for categorizing bone marrow cells into seven classes. In the proposed framework, five transfer learning models—DenseNet121, EfficientNetB5, ResNet50, Xception, and MobileNetV2—are implemented into the bone marrow dataset to classify them into seven classes. The best-performing DenseNet121 model was fine-tuned by adding one batch-normalization layer, one dropout layer, and two dense layers. The proposed fine-tuned DenseNet121 model was optimized using several optimizers, such as AdaGrad, AdaDelta, Adamax, RMSprop, and SGD, along with different batch sizes of 16, 32, 64, and 128. The fine-tuned DenseNet121 model was integrated with an attention mechanism to improve its performance by allowing the model to focus on the most relevant features or regions of the image, which can be particularly beneficial in medical imaging, where certain regions might have critical diagnostic information. The proposed fine-tuned and integrated DenseNet121 achieved the highest accuracy, with a training success rate of 99.97% and a testing success rate of 97.01%. The key hyperparameters, such as batch size, number of epochs, and different optimizers, were all considered for optimizing these pre-trained models to select the best model. This study will help in medical research to effectively classify the BM cells to prevent diseases like leukemia.
CP-ABE access control scheme based on blockchain and supporting data permissions management

The integration of Internet of Things (IoT) technology in everyday life has significantly improved convenience, particularly through the provision of various services and the monitoring of patients' vital signs. However, as IoT devices collect sensitive user information and transmit it to remote servers, privacy and security concerns have become a major issue. Therefore, there is an urgent need for data access control and data security sharing in IoT environments. To address these challenges, this study proposes a CP-ABE access control scheme based on blockchain technology and Supporting Data Permissions Management. The scheme supports data access control and management, using plaintext partitioning and data access control policies to manage data access effectively. Access control processes are executed through smart contracts, and data units are hashed and uploaded to the blockchain for secure storage. Homomorphic encryption technology is also utilized for outsourcing encryption, while proxy private key technology is used for outsourcing decryption. In conclusion, this scheme effectively resolves data access control and tampering issues in IoT environments, and has high practical value and application prospects.
Innovation in Labor Education for College Students in the Era of Artificial Intelligence

In today's world, artificial intelligence (AI) is a crucial direction in global technological development, permeating various sectors of society and even replacing manual labor in certain fields, significantly enhancing societal productivity. Simultaneously, people's reliance on AI is increasing, leading to a shift in the labor paradigm and a gradual weakening of labor consciousness. College students are high-quality talents cultivated by the party and the state, and their labor consciousness not only determines their own development but is also crucial for societal progress, especially in the face of significant challenges posed by the development of AI on their employment prospects. Therefore, innovating the way labor education is provided to college students to enhance their labor consciousness, skills, and quality, and fostering innovative development in labor education practices for college students is essential to help them adapt to the evolving era, lead societal development, and achieve comprehensive personal development.
Macroeconomic Factors Affecting Commercial Banks’ Credit to Small And Medium-Sized Enterprises in Kenya.

Bank credit to the SMEs in Kenya remains relatively low by international standards, and by holding other factors constant, there is potential for credit growth. However, several factors come into play with regard to the proportion of credit to the SME sector. From this background, the current study will seek to examine the determinants of bank credit to the SME sector in Kenya. The financial intermediation theory, financial liberalization theory and credit risk theory provided the theoretical justification of the study. This study adopted a causal research design to focus on establishing the causal relationships between the dependent and independent variables. Quantitative secondary data was adopted in this study and collected using a data collection instrument. Monthly time series data for the period 2008 to 2021 retrieved from the Central Bank of Kenya reports, Kenya National Bureau of Statistics, and World Bank reports was used. The study used both descriptive and inferential methods to analyze data. The findings from this study support the intuition from empirical evidence and theoretical framework that credit in commercial banks is determined by macroeconomic factors. This means that commercial credit in Kenya are determined by GDP, Inflation, interest rates &amp; Exchange rates when all working simultaneously.
Professional Deficits of Teachers in the Formation of Functional Literacy of Students and Ways to Overcome Them

The article is devoted to one of the important problems of the modern education system – improving the quality of education in the field of formation and assessment of functional literacy of students. Particular attention is paid to the study of professional competencies of teachers in the field of formation of functional literacy of students; ways of effective methodological support of the teacher in overcoming the existing professional deficits in order to improve the quality of education, including through the system of additional vocational education, are proposed.
Principles of Open Scholarly Infrastructure evaluation (2022)

Since 2020, twelve organizations signed on to the Principles of Open Scholarly Infrastructure [https://openscholarlyinfrastructure.org/] (POSI). It‘s not a meagre list of organizations either: CrossRef, ROR, Europe PMC, and many more. Today, Liberate Science joins the POSI posse (their words [https://openscholarlyinfrastructure.org/posse/]) with our initial evaluation of ResearchEquals.
Perancangan Sistem Informasi Penggajian Karyawan pada Jasa Outsourching di PT. Shield On Service Cabang Bandung

Shield on Service in the employee salary management process is still not optimal, because it still uses the Ms Application. Excel. So it is necessary to make a more optimal computerized payroll system which is expected to provide accurate, efficient and effective employee payroll data. The aim of this research is to make it easier for users to process employee payroll and minimize errors in the process. In designing this information system, the Microsoft Visual Studio programming language is used. The waterfall method is used to develop systems, starting from planning tools to implementing flowmaps, ERD and DFD. The results of this employee payroll application can simplify the calculation of employee salaries and save time in searching and matching employee information, thereby reducing errors in the employee payroll system.
An Overview of Computer Operating Systems and Emerging Trends

This article presents an overview of computer operating systems (OS) and emerging trends. OS is simply defined as an interface between computer hardware and the user. The objective of the study is to investigate the emerging trends of OS and to find out the direction of OS for modern computing systems. To achieve this goal the paper looks at the concepts of OS, its underlying architectures and evolution. The papers also outline the components of the OS provide knowledge on security issues with OS architectures and provide best practices to secure OS. The paper found out that the current trends in OS include IoT OS, Cloud OS, AI-powered OS, Blockchain OS, Hybrid OS and Container OS. The paper compares the strengths and weaknesses of the major OS. The Paper proposes a double-layer security approach where the OS is hardened with security policies and embedding security protocols in the Hardware architecture of the OS. It was discovered that every technology comes with its unique architecture and OS. This makes it worrisome for engineers to crack their brains to develop such a system. The paper further proposes the development of a universal OS for all architectures leaving room for further expansion while mitigating power consumption issues by incorporating green computing technology in the design architecture.
Optimizing Social Media Platforms for Enhanced Distance Learning Support Systems: A Case Study of Universitas Terbuka

The rapid evolution of information and communication technology (ICT) has revolutionized education, particularly in the context of distance learning. Social media has emerged as a crucial component in the educational landscape, offering opportunities for collaboration and interaction. This article explores the optimization of social media platforms to enhance distance learning support systems, focusing on the case of Universitas Terbuka, a renowned institution for Open Distance Learning (ODL) programs. The study employs the UTAUT model to investigate the factors influencing the voluntariness of social media use for distance learning. Through a quantitative research design involving 233 respondents, Structural Equation Modeling (SEM) is used to analyze the relationships between variables. The findings reveal that factors such as effort expectancy, social influence, and facilitating conditions significantly impact students' willingness to use social media for distance learning. These results suggest the importance of fostering social influence and ease of use expectations to enhance the distance learning experience at Universitas Terbuka and similar institutions. Overall, this study underscores the transformative potential of social media in education and its role in shaping the future of learning environments.
Social media and health promotion: evaluation of effectiveness in promoting hypertension self-care in urban contexts of social iniquities

This paper explores the role of social media in promoting self-care for Systemic Arterial Hypertension (SAH) and addressing health inequities, emphasizing its significance in the context of the COVID-19 pandemic. It calls for a focus on social determinants of health and highlights the global impact of Chronic Non-Communicable Diseases (NCDs), with a particular focus on Brazil's healthcare system. The research, a collaboration between the University of Brasília and the research initiative Escola de Pacientes DF (EP-DF), employs Participatory Community Based Research (CBPR) to evaluate the impact of social media on SAH self-care in urban areas with social inequities. The study includes a scoping review of relevant articles, document analysis of SAH patient testimonials, and knowledge translation for community understanding. Results from the scoping review show positive changes in self-care behaviors due to social media interventions, while acknowledging challenges such as low Functional Health Literacy (FHL), age, education, and internet access. In conclusion, the paper highlights social media's potential in improving healthcare accessibility and equity for SAH and NCDs in vulnerable communities.
Consulting: Privacy in open data

The past six months we consulted for the Meta-Research Center on their NWO Open Science Fund project, aimed at detecting privacy violations in datasets.
Specifying the de-facto OS of a production SoC

Verification of any operating system is inevitably relative to a model of the underlying hardware. Within the context of kernel verification, the underlying hardware model usually comprises of architectural correctness of the executing cores, but pays little attention to devices underneath barring the assumption that they are "trusted".
The Advancement of Electronic Gadgets in 21st Century

The 21st Century was full of innovation when it came to the Tech Sector alone, be it the introduction of the Iphone, or the launch of the big conglomerates such as Facebook and Twitter. The 21st Century gave rise to the concepts of the Curved Displays on phones and the Foldable phones. There were numerous problems which were associated with the flat screen displays, and the shortcomings have been overcome by the Curved Displays and the Foldable phones as discussed in the paper. They have revolutionized the Technological market since their launch. Many Conglomerates such as Samsung, Honor, Xiaomi have invested millions of dollars in availing this new technology. However, currently Samsung has the lead over all its Chinese competitors, and with different companies investing in the new technology, the competition is predicted to become more intense. This will surely give customers a huge variety of phones to choose from. However, this technology did not come without its drawbacks. There were multiple issues associated with the Foldable Phones such as the weight associated with the phone when folded, the tensile strength of the Foldable phones is very low, and the User Interface is not something one could get excited about. Similar issues existed with Curved Displays as well, including costly repair costs, and it is harder to get a grip on compared to the Foldable phones due to the thinning of the edges. The paper discusses in depth the shortcomings of all the types of Phones, as well as which would be the best fit for the user, along with the current trend of the users, and what the Future holds for this segment of Technology.