Reviewerly/exHarmony huggingface dataset:
Reply to Walker et al.: Rock melting? Oxygen matters

Microbial communities are found throughout the biosphere, from human guts to glaciers, from soil to activated sludge. Understanding the statistical properties of such diverse communities can pave the way to elucidate the common mechanisms ...Multiple ecological forces act together to shape the composition of microbial communities. Phyloecology approaches—which combine phylogenetic relationships between species with community ecology—have the potential to disentangle such forces but are often ...
Impact of COVID-19 on Human Rights

On March 11, 2020, the World Health Organization declared a coronavirus pandemic. The economy stopped, the lives of billions of people changed. As a result of pandemic, a number of constitutional rights have been restricted. Restrictions imposed during the state of emergency affected public life and threatened the implementation of international human rights instruments at the national level. Number of States declared state of emergency to tackle with pandemic. Herewith, a few states refrained from doing so. The foregoing article reviews the impact of COVID-19 on the rights and freedoms protected by the European Convention on Human Rights, relevant state practice of derogating from obligations under the Convention, statistical data and the supervisory role of the European Court of Human Rights (ECtHR) against abuse of the derogation mechanism.
A Hybrid Method with RDTM for Solving the Biological Population Model

In this paper, we establish an analytical solution to the non-linear biological population model using a hybrid method that combines a reduced differential transform method with a resummation method based on Yang transform and a Padé approximant.The proposed method significantly improves the approximate solution series and broadens the convergence field, It is also dependent on a few straightforward steps, and does not depend on a perturbation parameter or produce secular terms.Three examples are given to test the effectiveness, accuracy, and performance of the suggested method.The results and graph demonstrate that the suggested method is successful and more accurate than other methods.In addition, PYRDTM is a useful tool with great potential for solving nonlinear BPM.
Impacts on organizational forms, business models and strategies

This chapter offers an analysis of blockchain's impacts on organizational forms, business models and strategies. It demonstrates how blockchain-led reduction in the cost of verification and the cost of networking can help promote transparency, build trust and reputation, and enhance efficiency in transactions, which can have important implications on the functioning of organizations. In this way, blockchain can disrupt economies and transform societies. In this chapter we also provide detail discussion of decentralized autonomous organizations (DAOs) that are facilitated by smart contracts. For instance, a DAO could own a self-driving car to use as a taxi 24 hours a day. The income generated would be used to pay for its fuel, repairs and insurance. The money that is saved can be used to replace the vehicle at the end car's life. A key focus of the chapter is also on the effects of blockchain and smart contracts on key mechanisms related to the governance of interorganizational relationships that are employed by participating firms. Specifically, this chapter looks at how formal contracts which focus on economic and legal aspects and relational norms and trust, which deal with social aspects are likely to be impacted by blockchain and smart contracts.
Discussion, conclusion, and recommendations

In this final chapter, we integrate the ideas discussed in earlier chapters regarding blockchain's potential to disrupt economies and transform societies. The technology's impact on business models, competitive positions, markets and industries are summarized. We consider the future of blockchain and how the developments in other technologies are likely to affect its potential to work as a trust machine. The chapter also addresses the importance of organizational, interorganizational and cultural changes to benefit from the potential of blockchain. It argues that while some actors may see an opportunity to distort the truth for profitable gains, new technologies such as AI and satellite imagery can change the economics of truth and bring blockchain closer to a truth machine. Recommendations and implications for policymakers are discussed. First, in order to strengthen security, regulators can make it obligatory for firms to deploy blockchain in supply chains of mission critical systems, and have substantial national security and economic benefits. Second, public policy efforts directed at protecting privacy using blockchain should focus on providing training to key stakeholders and increasing investment in this technology. Third, one way to enrich the blockchain ecosystem would be to turn attention to public–private partnerships. Finally, national governments should provide legal clarity and more information for parties to engage in smart contracts that are enforceable. Recommendations are also offered for companies and scholarly research.
Privacy-Preserving Data Mining in Web Domain Using Protected Data Extraction and Presentation Algorithm

Various privacy security standards are used in practical applications to decide research issues. The general strategies of privacy preservation are used to process the data security pledge at a lower privacy level. Furthermore, probability and mathematical models are introduced in order to maintain privacy. Privacy-preserving data mining models are used to preserve the privacy of different high-level data characteristics. The main objective of protecting privacy that is based on data release is to obtain a common approach of protecting privacy in different kinds of applications so that the designed algorithm could be implemented in a versatile way. This paper presents protected data extraction and presentation algorithm (PDEPA) that is used for data extraction and presentation with minimized error in classification and computation time, as well as increased privacy. The framework's development is aimed at ensuring that the running environment and applications are privacy compatible. The web-based distributed application's data extraction time and classification error are reduced.
Virtual immunohistochemical (IHC) staining of unlabeled tissue using deep learning (Conference Presentation)

Immunohistochemical (IHC) staining of the human epidermal growth factor receptor 2 (HER2) is routinely performed on breast cancer cases to guide immunotherapies and help predict the prognosis of breast tumors. We present a label-free virtual HER2 staining method enabled by deep learning as an alternative digital staining method. Our blinded, quantitative analysis based on three board-certified breast pathologists revealed that evaluating HER2 scores based on virtually-stained HER2 whole slide images (WSIs) is as accurate as standard IHC-stained WSIs. This virtual HER2 staining can be extended to other IHC biomarkers to significantly improve disease diagnostics and prognostics.
Visualizing Kelingkan Embroidery through the of Malays Styles and Motives

It was reported that in 2002, at least five kelingkan embroiderers were still practicing their craft in the East Malaysian state of Sarawak, and lesser of them were still active in West Malaysia. This situation may cause stagnation in the development of this type of embroidery making, particularly in Malaysia. It may even lead to this art form becoming obsolete in the future. In fact, in the present day, the demand for kelingkan in the market is high. Malaysian fashion designers have also become responsive to the beauty of traditional embroidery to elevate them to the same sphere as exclusive international embellishments. Keywords: Embroidery; Malay Costumes; Styles; Motives eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning &amp; Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7iSI7%20(Special%20Issue).3802
INTELLIGENT APPROACHES TO HATE DETECTION IN TWEETS

The use of microblogging services like Twitter, Facebook, and Tumblr has increased, making interpersonal contact more indirect and trustworthy; people from various educational and cultural backgrounds interact with their views on several facets of life on a daily basis.These have caused interpersonal difficulties.Consequently, the spread of hate speech issues gets really serious.Hate Speech is when someone uses offensive, violent language.Which focuses on a certain group of people with similar interests a person's gender, caste, religion, color, etc. Manually identifying it is quite time-consuming to gather such content from these websites.The proposed model has the capacity to automatic detection of hate content on Twitter.The proposed methodology is based on a bag of words and the TFIDF (term frequency-inverse document frequency) approach.Machine and deep learning classifiers are trained using these features.The accuracy achieved by the convolutional neural network (CNN) is equivalent to 95% in detecting if a particular tweet is hateful or not in experiments on the already-existing Twitter dataset.
ABOUT LEVELS OF EDUCATION QUALITY MANAGEMENT ORGANIZATION

Education management is considered as a type of social management. It is aimed at ensuring the purposefulness and organization of the construction of educational processes in the education system. Quality management of education is aimed at meeting the requirements for the quality of education. This article analyzes the concept of "education quality management", its main characteristics. It is noted that the management of the quality of education, as a system, has levels of management activity. The author proposes reproductive, productive and creative levels of education management. The highlighted levels are correlated with the process of goal-setting, with the choice of methods and forms of organization of management, as well as with the process of correcting and making changes in management activities.
An Analysis of Market Failure aspects in Chinese High School's ｢Ideological and Political｣ Textbooks

Objectives This study aims to analyze the trend of market failure by period in the Chinese high school ｢Ideological and Political｣ textbook published from 1983 to 2019 to explore how market failure in China by period is reflected in the textbook.&#x0D; Methods 12 textbooks were collected and analyzed in 1983, 1989, 1998, 2004, 2011, 2016, and 2019 published in line with the revision cycle of the ｢Ideological and Political｣ curriculum in Chinese high schools. The collected data were analyzed based on China's economic development stage and the definition of market failure, and both text and illustration were included.&#x0D; Results As a result of the analysis, the pattern of market failure in the Chinese high school ｢Ideological and Political｣ textbooks appears differently depending on the period. Market failure in the textbooks during the Chinese market economy exploration stage (1978-1991) was monopolization, corruption, inflation, and widening the income gap. Market failure in textbooks during the Initial construction stage of the market economy (1992-2001) is administrative monopoly, Counterfeit Products, mammonism, unfair competition. Market failure in the textbooks during the stage of full-scale and in-depth reform (2002-2012) is corruption, economic instability, administrative monopoly, counterfeit products, distributionism, unfair competition, illegal fundraising and investment, socioeconomic inequality, and environmental issues. Market failure in textbooks in comprehensive deepening of reform (2013~present) is administrative monopoly, unfair competition, monopoly, Socio-economic inequality, environmental issues, urbanization, economic instability and supply-side structural reform.&#x0D; Conclusions In Chinese high school ｢Ideological and Political｣ textbooks, market failure is the basis for the party and the government's involvement in the economic field. Administrative monopoly, which appears only in China, a country in the transition period of the economic system in Chinese textbooks, is also a problem in the market. Since the market has inherent problems such as unfair competition, monopoly, damage to social equity, and widening income gap, it is argued that control and control of the national economy of the country are needed before the market failure of the market. The logic of the Communist Party of China has been consistently reflected since China adopted a socialist market economy system, and in particular, the 2019 textbook shows a strong tendency for state-led economic growth led by the party.
Formation of positive motivation in teaching conservatory students through Enlightening projects

Introduction. The problem of teaching motivation is a key one in psychological and pedagogical science. Positive motivation determines the trajectory of a student’s development throughout the entire educational activity. If students lack cognitive interests, motives to learn, develop, and improve then in the future it is difficult for such young people to become competitive specialists. Theoretical analysis. A comparative analysis of this problem allowed us to formulate the following: today, the teacher faces an important task of forming a positive motivation in teaching modern students in the process of educational activity with the help of new interesting forms of communication. The author of the article offers an experimental experience of creating a new form of interaction between a student and a teacher. An enlightening project is proposed as one of the ways to form a positive motivation for educational activities at the conservatory. Such a practice of cooperation between a teacher and a student does not exclude classical classes as such, but offers another way of creative work. Conclusion. The novelty of this form of interaction is given by the innovative internal component and the methodological foundations on which each enlightening project devoted to a certain topic is based. In creating an enlightening project as a new form of work, the author used the basic principles: the principle of openness, variability, dialogicity, pedagogical support and support.
Optimizing Data Layout for Training Deep Neural Networks

The widespread popularity of deep neural networks (DNNs) has made it an important workload in modern datacenters. Training DNNs is both computation-intensive and memory-intensive. While prior works focus on training parallelization (e.g., data parallelism and model parallelism) and model compression schemes (e.g., pruning and quantization) to reduce the training time, choosing an appropriate data layout for input feature maps also plays an important role and is considered to be orthogonal to parallelization and compression in delivering the overall training performance. However, finding an optimal data layout is non-trivial since the preferred data layout varies depending on different DNN models as well as different pruning schemes that are applied. In this paper, we propose a simple-yet-effective data layout arbitration framework that automatically picks up the beneficial data layout for different DNNs under different pruning schemes. The proposed framework is built upon a formulated cache estimation model. Experimental results indicate that our approach is always able to select the most beneficial data layout and achieves the average training performance improvement with 14.3% and 3.1% compared to uniformly using two popular data layouts.
A Sensitivity Analysis on a MCDM Problem Evaluated by ARAS Method

Multi-Criteria Decision Making, also known as MCDM, is a highly helpful technique for assessing numerous issues and conclusions as well as resolving conflicts in daily life. The choice of any technique, service, or product is fraught with difficulties. The choosing of any useful product, such as a scooter, is an important task that requires careful research into the selection criteria, where MCDM techniques play a significant role. But the results that are coming with different MCDM methods are has to be consistent enough. This particular study associated with the checking or verifying the results that are evaluated by the Additive Ratio Assessment (ARAS) method with AHP weights for each Criterion.
Singular value decomposition model application for e-commerce recommendation system

A recommendation system is one of the most important things in today’s technology. It can suggest products that match the user’s preferences. Many fields utilize this system, including e-commerce, using various algorithms. This paper used the matrix factorization-based algorithm, singular value decomposition (SVD), to make a recommendation system based on users’ similarities. Afterward, we implement the model against the ModCloth Amazon dataset. The results imply that the SVD algorithm yields the best accuracy compared to other matrix factorization-based algorithms with root mean square error (RMSE) of 1.055586. Then, we optimized the SVD algorithm by changing the hyperparameters of the algorithm to generate better accuracy and yield a model with an RMSE value of 1.041784.
PKM PELATIHAN DAN PENDAMPINGAN GURU SMP HARAPAN SUNGAILIAT DALAM MENGEMBANGKAN PEMBELAJARAN BERBASIS LMS MOODLE DAN GOOGLE CLASSROOM

Moodle and Classroom are some of the alternative learning media that can be used by teachers in improving the learning process more effectively. However, many teachers still do not understand how to utilize e-learning in learning process. This program aims to improve the ability of teachers to utilize ICT for learning through Moodle and Classroom. The program activity includes the development of Moodle-based e-learning and training for teachers at SMP Harapan Sungailiat. The training results show that teachers’ skills in using the e-learning module are increase. The training questionnaire showed that 98% of the participants were able to use e-learning. The percentage of participants who quite agree that they are skilled at using e-learning is 52%. Meanwhile, 41% agree that they are skilled at using e-learning, and 6% strongly agree that they are skilled at using e-learning.
Peer review declaration

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing Publishing. Type of peer review: Double anonymous Conference submission management system: Morressier Number of submissions received: 88 Number of submissions sent for review: 85 Number of submissions accepted: 24 Acceptance Rate (Submissions Accepted / Submissions Received × 100): 27.3 % Average number of reviews per paper: 2.00 Total number of reviewers involved: 48 Contact person for queries: Name: Catherine Liu Affiliation: International Computing and Engineering Association Email: conf@i-cea.net
RGB photoelastic method based on gradient-square inversion correction

Abstract Automatic photoelastic method focuses on the recognition of stress field. RGB photoelastic method has the advantages of low condition requirements and accurate low-level fringe recognition, but it is easy to be disturbed by image noise, color repetition and other factors, resulting in recognition errors. In this study, the combination of gradient-square inversion and RGB photoelastic technology can not only effectively eliminate the error points introduced by color repetition, but also greatly reduce the scope of look-up table, shorten the calculation time and quickly analyze the stress field. The effectiveness of the proposed RGB photoelastic method based on gradient-square inversion correction is verified by photoelastic experiments.
Incremental Local Linear Fuzzy Classifier in Fisher Space

&lt;p&gt;Optimizing the antecedent part of neurofuzzy system is an active research topic, for which diﬀerent approaches have been developed. However, current approaches typically suﬀer from high computational complexity or lack of ability to extract knowledge from a given set of training data. In this paper, we introduce a novel incremental training algorithm for the class of neurofuzzy systems that are structured based on local linear classiﬁers. Linear discriminant analysis is utilized to transform the data into a space in which linear discriminancy of training samples is maximized. The neurofuzzy classiﬁer is then built in the transformed space, starting from the simplest form (a global linear classiﬁer). If the overall performance of the classiﬁer was not satisfactory, it would be iteratively reﬁned by incorporating additional local classiﬁers. In addition, rule consequent parameters are optimized using a local least square approach. Our reﬁnement strategy is motivated by LOLIMOT, which is a greedy partition algorithm for structure training and has been successfully applied in a number of identiﬁcation problems. The proposed classiﬁer is compared to several benchmark classiﬁers on a number of well-known datasets. The results prove the eﬃcacy of the proposed classiﬁer in achieving high performance while incurring low computational eﬀort.&lt;/p&gt; &lt;p&gt;&lt;br&gt;&lt;/p&gt;
The Network

October 07 2022 The Network Nick Cronbach Nick Cronbach Email: editor@leonardo.info. Search for other works by this author on: This Site Google Scholar Author and Article Information Nick Cronbach The Network Coordinator, Senior Editor Email: editor@leonardo.info. Online Issn: 1530-9282 Print Issn: 0024-094X © ISAST2022ISAST Leonardo 686. https://doi.org/10.1162/leon_a_02289 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn MailTo Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Nick Cronbach; The Network. Leonardo 2022; doi: https://doi.org/10.1162/leon_a_02289 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsLeonardo Search Advanced Search This content is only available as a PDF. © ISAST2022ISAST Article PDF first page preview Close Modal You do not currently have access to this content.