Reviewerly/exHarmony huggingface dataset:
Feature and Label Association Based on Granulation Entropy for Deep Neural Networks

Pooling layers help reduce redundancy and the number of parameters before building a multilayered neural network that performs the remaining processing operations. Usually, pooling operators in deep learning models use an explicit topological organization, which is not always possible to obtain on multi-label data. In a previous paper, we proposed a pooling architecture based on association to deal with this issue. The association was defined by means of Pearson's correlation. However, features must exhibit a certain degree of correlation with each other, which might not hold in all situations. In this paper, we propose a new method that replaces the correlation measure with another one that computes the entropy in the information granules that are generated from two features or labels. Numerical simulations have shown that our proposal is superior in those datasets with low correlation. This means that it induces a significant reduction in the number of parameters of neural networks, without affecting their accuracy.
Learning Analytics and Spelling Acquisition in German – The Path to Individualization in Learning

This paper shows how Learning Analytic Methods are combined with German orthography in the IDeRBlog-project ( www.iderblog.eu ). After a short introduction to the core of the platform – the intelligent dictionary – we focus on the presentation and evaluation of a new training format. The aim of this format is, that pupils can train misspelled words individually in a motivating and didactic meaningful setting. As a usability test was run with twenty one third graders, we are able to present the results of this evaluation.
Towards Robust Classification with Deep Generative Forests

Decision Trees and Random Forests are among the most widely used machine learning models, and often achieve state-of-the-art performance in tabular, domain-agnostic datasets. Nonetheless, being primarily discriminative models they lack principled methods to manipulate the uncertainty of predictions. In this paper, we exploit Generative Forests (GeFs), a recent class of deep probabilistic models that addresses these issues by extending Random Forests to generative models representing the full joint distribution over the feature space. We demonstrate that GeFs are uncertainty-aware classifiers, capable of measuring the robustness of each prediction as well as detecting out-of-distribution samples.
Monitoring and control skills of heads of science department and academic performance in sciences in public secondary schools in Nandi county Kenya

This paper looks at the monitoring and control skills of Heads of Department (HODs) of science and its influence on academic performance by students in Kenya Certificate of Secondary Education Subjects. The HODs have been mandated to provide instructional guidance through regular monitoring, assessment and evaluation of science teaching subjects in their secondary schools. However, recent performances in science subjects (Biology, Chemistry and Physics) in KCSE in public secondary schools in Nandi County have been below average. Therefore, the objective of this paper was to determine the influence of science HODs monitoring and control skills towards academic performance of students in science subject. The study used mixed method research methodology which combined qualitative and quantitative data. The area of study was all public secondary schools in Nandi County. Target population consisted of 231 HODs of science, 231 principals and 693 science subject teachers. The study adopted a mixed method research design. A sample size of 23 principals, 128 HODS of science and 247 science teachers were selected through stratified random sampling technique. Data was collected using questionnaires (for HODs and teachers) and interview guide (for principals). The reliability values for HODs was 0.795 and science teachers 0.775 which were above the threshold of R=0.7. Analysis of data was performed using quantitative and qualitative methods. Results of the analysis revealed that HODs organising regular departmental meetings to review performance and take corrective action where possible was the main monitoring and control used. On the average, the study discovered that HODs of science planed with science teachers evaluation and assessment activities in their schools (M=3.38 and SD=1.25). The paper concludes that there existed a significant positive influence (p&lt;0.05) between HODs of Science monitoring and control skills and academic performance of students in science subjects in selected public secondary schools in Nandi County, Kenya. It was recommended that Teachers Service Commission needs to improve staffing levels in public secondary schools especially in science subjects to in order provide ample time for HODs to do their regular monitoring and control activities of science subjects’ curriculum implementation in classrooms and among their departmental teachers.&#x0D; Keywords: Science, Monitoring, Control, Performance and Assessment
Understanding Adversarial Examples from the Mutual Influence of Images and Perturbations

A wide variety of works have explored the reason for the existence of adversarial examples, but there is no consensus on the explanation. We propose to treat the DNN logits as a vector for feature representation, and exploit them to analyze the mutual influence of two independent inputs based on the Pearson correlation coefficient (PCC). We utilize this vector representation to understand adversarial examples by disentangling the clean images and adversarial perturbations, and analyze their influence on each other. Our results suggest a new perspective towards the relationship between images and universal perturbations: Universal perturbations contain dominant features, and images behave like noise to them. This feature perspective leads to a new method for generating targeted universal adversarial perturbations using random source images. We are the first to achieve the challenging task of a targeted universal attack without utilizing original training data. Our approach using a proxy dataset achieves comparable performance to the state-of-the-art baselines which utilize the original training dataset.
A study on solutions of cross-ledger intercommunication : Classification, analysis and comparison of crosschain projects

The phenomenon of isolated value in each blockchain system has become adistinct issue of the blockchain field. To address this problem, the demandof cross-chain intercommunication came up. In a nar ...
Graph Approach to Quantum Teleportation Dynamics

Quantum teleportation plays a key role in modern quantum technologies. Thus, it is of much interest to generate alternative approaches or representations aimed at allowing us a better understanding of the physics involved in the process from different perspectives. With this purpose, here an approach based on graph theory is introduced and discussed in the context of some applications. Its main goal is to provide a fully symbolic framework for quantum teleportation from a dynamical viewpoint, which makes explicit at each stage of the process how entanglement and information swap among the qubits involved in it. In order to construct this dynamical perspective, it has been necessary to define some auxiliary elements, namely virtual nodes and edges, as well as an additional notation for nodes describing potential states (against nodes accounting for actual states). With these elements, not only the flow of the process can be followed step by step, but they allow us to establish a direct correspondence between this graph-based approach and the usual state vector description. To show the suitability and versatility of this graph-based approach, several particular teleportation examples are examined, which include bipartite, tripartite and tetrapartite maximally entangled states as quantum channels. From the analysis of these cases, a general protocol is discussed in the case of sharing a maximally entangled multi-qubit system.
ANALYSES OF COMPETENCIAS FORMATION AS THE KEY FACTOR FOR SUCCESSFUL EMPLOYMENT OF UNIVERSITY GRADUATES

The article deals with issues related to the problems of identifying competences demanded on the labor market, examines the regional aspects of assessing the importance of competences by employers in Russia and Kazakhstan. The competence demanded by the regional labor market have been analyzed, approaches to the formation of effective methods of interaction between universities and the labor market to improve the quality of education have been grounded. The article concerns the modern scientific approaches to identifying key competences. The paper studies approaches to the development of methodological tools that provide multi-criteria assessment (diagnostics) of the activities of educational institutions. Dynamic changes in the labor market, caused by the development of information technologies, lead to the fact that universities offer educational programs that do not meet the latest trends. The article discusses on of the ways to solve this problem by means of competence centers created on the basis of universities.
COMPARATIVE CHARACTERISTICS OF TEACHING MATHEMATICS IN COLLEGES AND GYMNASIUMS IN GERMANY AND UKRAINE

The article describes the main features, aspects and issues that can be problem for domestic applicants when they like to study at higher education institutions in Germany.The relevance of the issue under the study is proved by the fact that the global market of modern education is one of the most rapidly developing areas of the economy.In some countries, the profit from the export of educational services is so great, that it is one of the main sources of income for these countries.The number of students studying abroad is constantly growing.The main attention in the paper is paid to the fact that in addition to difficulties of psycho-social nature, a new style of life and new surrounding, the young people can encounter more serious difficulties: a mismatch in the level of professional training.The authors emphasize on the necessity to pay attention to the difference between the systems of school education in Ukraine and Germany.So they say that in Ukraine every student must have a complete school education to enter a higher education institution.If applicant graduates from a technical school (college), then he/ she has possibility to enter the second or the third year of studying at the corresponding University.In German the situation is different, its analysis is presented in the paper.There are noted not only main differences in education system as whole, but in the methods of teaching certain courses on example of teaching mathematics.The main focuses are made on the themes that are highlighted in the last school years, and themes of entrance exams at German universities.The analysis allows the authors to argue that preparing for further studying abroad is a complex process, requiring a difficult professional and educational training.
Report of the ALCTS Bibliographic Conceptual Models Interest Group (IG) Forum Meeting, American Library Association Midwinter Meeting, Philadelphia, January 2020

The ALCTS Bibliographic Conceptual Models IG (formerly the FRBR IG), met from 2:30 to 3:30 pm on Sunday, 26 January 2020, at the American Library Association Midwinter Meeting in Philadelphia. The ...
Bottleneck potentials in Markov Random Fields

We consider general discrete Markov Random Fields(MRFs) with additional bottleneck potentials which penalize the maximum (instead of the sum) over local potential value taken by the MRF-assignment. Bottleneck potentials or analogous constructions have been considered in (i) combinatorial optimization (e.g. bottleneck shortest path problem, the minimum bottleneck spanning tree problem, bottleneck function minimization in greedoids), (ii) inverse problems with $L_{\infty}$-norm regularization, and (iii) valued constraint satisfaction on the $(\min,\max)$-pre-semirings. Bottleneck potentials for general discrete MRFs are a natural generalization of the above direction of modeling work to Maximum-A-Posteriori (MAP) inference in MRFs. To this end, we propose MRFs whose objective consists of two parts: terms that factorize according to (i) $(\min,+)$, i.e. potentials as in plain MRFs, and (ii) $(\min,\max)$, i.e. bottleneck potentials. To solve the ensuing inference problem, we propose high-quality relaxations and efficient algorithms for solving them. We empirically show efficacy of our approach on large scale seismic horizon tracking problems.
Consistency Regularization with Generative Adversarial Networks for Semi-Supervised Image Classification.

Generative Adversarial Networks (GANs) based semi-supervised learning (SSL) approaches are shown to improve classification performance by utilizing a large number of unlabeled samples in conjunction with limited labeled samples. However, their performance still lags behind the state-of-the-art non-GAN based SSL approaches. One main reason we identify is the lack of consistency in class probability predictions on the same image under local perturbations. This problem was addressed in the past in a generic setting using the label consistency regularization, which enforces the class probability predictions for an input image to be unchanged under various semantic-preserving perturbations. In this work, we incorporate the consistency regularization in the vanilla semi-GAN to address this critical limitation. In particular, we present a new composite consistency regularization method which, in spirit, combines two well-known consistency-based techniques -- Mean Teacher and Interpolation Consistency Training. We demonstrate the efficacy of our approach on two SSL image classification benchmark datasets, SVHN and CIFAR-10. Our experiments show that this new composite consistency regularization based semi-GAN significantly improves its performance and achieves new state-of-the-art performance among GAN-based SSL approaches.
Automatic Web Service Composition -- Models, Complexity and Applications

The automatic composition of web services refers to how services can be used in a complex and aggregate manner, to serve a specific and known functionality. Given a list of services described by the input and output parameters, and a request of a similar structure: the initially known and required parameters; a solution can be designed to automatically search for the set of web services that satisfy the request, under certain constraints. We first propose two very efficient algorithms that solve the problem of the automatic composition of the web services as it was formulated in the competitions organized in 2005 and 2008. The algorithms obtain much better results than the rest of the participants with respect to execution time and even composition size. Evaluation consists of running the previous and the proposed solutions on given benchmarks and generated tests. Further, we design two new models to match service's parameters, extending the semantic expressiveness of the 2008 challenge. The initial goal is to resolve some simple and practical use-cases that cannot be expressed in the previous models. We also adhere to modern service description languages, like OpenAPI and especially schema.org. Algorithms for the new models can solve instances of significant size. Addressing a wider and more realistic perspective, we define the online version of the composition problem. In this regard, we consider that web services and compositions requests can be added and removed in real-time, and the system must handle such operations on the fly. It is necessary to maintain the workflows for users who actively run the compositions over time. As for the new semantic models, we propose new algorithms and provide comprehensive evaluation by generating test cases that simulate all corner cases.
SOSNet: Second Order Similarity Regularization for Local Descriptor Learning

Despite the fact that Second Order Similarity (SOS) has been used with significant success in tasks such as graph matching and clustering, it has not been exploited for learning local descriptors. In this work, we explore the potential of SOS in the field of descriptor learning by building upon the intuition that a positive pair of matching points should exhibit similar distances with respect to other points in the embedding space. Thus, we propose a novel regularization term, named Second Order Similarity Regularization (SOSR), that follows this principle. By incorporating SOSR into training, our learned descriptor achieves state-of-the-art performance on several challenging benchmarks containing distinct tasks ranging from local patch retrieval to structure from motion. Furthermore, by designing a von Mises-Fischer distribution based evaluation method, we link the utilization of the descriptor space to the matching performance, thus demonstrating the effectiveness of our proposed SOSR. Extensive experimental results, empirical evidence, and in-depth analysis are provided, indicating that SOSR can significantly boost the matching performance of the learned descriptor.
허사 학습을 통한 한문 독해 수업 사례 연구 - 중학교 1학년을 대상으로 -

The purpose of this study is to prepare for the foundation to resolve the problem with Chinese reading classes at local schools. The 7th grade is when students first start to learn Chinese in the regular school curriculum. Learning sounds and meanings of Chinese characters is already beyond the capacities of these students, and this study analyzed their problem with comprehension of written Chinese to try to suggest a solution to the problem. First, it analyzed units of short sentences and essays relevant to Chinese reading comprehension in the 2015 revised middle school Chinese textbooks. Then, reference data were created by entering Chinese characters information helpful in deciphering sentences in textbooks. After these processes, the learning material was created by selecting empty morphemes-related data and applied to the classes. It was because the interpretation of empty morphemes was assumed to be an important element of Chinese reading comprehension. Understanding of empty morphemes concept using this learning material was added to the existing classes using textbooks. Formative evaluations, surveys, interviews, etc. confirmed that the learning of empty morphemes could contribute to some extent to a change in the students’ perception of Chinese classes, while it didn’t improve students’ Chinese reading comprehension skill in a short period of time. In this sense, the basic knowledge lessons for reading like Chinese grammar rules should not be cramming and memorization oriented.
OBA: An Ontology-Based Framework for Creating REST APIs for Knowledge Graphs.

In recent years, Semantic Web technologies have been increasingly adopted by researchers, industry and public institutions to describe and link data on the Web, create web annotations and consume large knowledge graphs like Wikidata and DBPedia. However, there is still a knowledge gap between ontology engineers, who design, populate and create knowledge graphs; and web developers, who need to understand, access and query these knowledge graphs but are not familiar with ontologies, RDF or SPARQL. In this paper we describe the Ontology-Based APIs framework (OBA), our approach to automatically create REST APIs from ontologies while following RESTful API best practices. Given an ontology (or ontology network) OBA uses standard technologies familiar to web developers (OpenAPI Specification, JSON) and combines them with W3C standards (OWL, JSON-LD frames and SPARQL) to create maintainable APIs with documentation, units tests, automated validation of resources and clients (in Python, Javascript, etc.) for non Semantic Web experts to access the contents of a target knowledge graph. We showcase OBA with three examples that illustrate the capabilities of the framework for different ontologies.
Pandemic, Fundamental Rights and Democracy - The Greek Example

The Coronavirus pandemic is not only a health, economic and social challenge but a major challenge for national constitutions, international law and the EU legal order as well. More precisely, the pandemic is evolving into a comprehensive challenge to the acquis of modernity, i.e. liberal democracy, human rights and the guarantees of the rule of law, the nation state and its sovereignty, the organization of international society and the role of the United Nations and international organizations, regional cooperation, European integration and solidarity, and the degree of economic development and the “western way of life”. Our analysis will be focused on fundamental rights, while also making some necessary references to the function of liberal democracy institutions.
Securing Plan for PS-LTE wide-area maritime communication area

정부는 재난 관련 기관의 유기적 상호소통을 위한 전국 단일의 재난안전통신망(PS-LTE) 구축사업을 진행하고 있다. PS-LTE 기지국 구축은 자가망 방식을 선택하였으나, 비용 등의 이유로 철도망(LTE-R), 해상망(LTE-M), 상용 이동통신망을 상호연동(RAN-Sharing)하는 방식이다. 이 연구는 해상이라는 특수한 지리적 특성으로 재난안전통신망이 광역해상에 이르기까지 발생할 수 있는문제점들을 예측하고, 개선 방안을 찾고자 하였다. LTE-M은 해상에서 최대100km까지 10Mbps의 통신이 가능하지만, 100km를 넘어서는 광역해상에서 사고가 발생했을 경우는 LTE-M으로는 PS-LTE와 상호연동할 수 없다. 따라서이 연구는 광역해상에서 PS-LTE 연동을 위한 선박형 이동기지국에 초점을 두었다. 광역해상에서 선박형 이동기지국으로 운용될 해양경찰 경비함정의 위성통신망(KOSNET) 운용 현황을 조사한 결과, 현장 영상전송 및 각종 업무시스템의 활용으로 이미 할당된 대역폭이 부족한 실태였다. 재난안전통신망을 운용하기 위해서는 많은 예산을 들여 위성대역폭을 증설하는 것이 단기적 과제였다. 그러나 해양경찰 위성통신망으로 운용 중인 무궁화 5A호 위성대역폭 증설에는한계가 있었으며, 결국, 광역해상에서 PS-LTE 연동을 위해서는 차세대 공공복합재난위성이 필요함을 확인하였다. 이 연구가 재난안전통신망 광역해상 통신권 확보를 위한 정책에 반영됨으로써 소중한 국민의 생명과 재산을 보호할 수있기를 기대한다.The government is carrying out a project to establish a single nationwide public safety communication network (PS-LTE) for the organic mutual communication of disaster-related organizations. PS-LTE base stations were chosen by the municipal method, but RAN-Sharing system was selected among the railway network (LTE-R), maritime network (LTE-M), and commercial mobile communication network for cost reasons. This study was intended to predict problems that could arise from the public safety network to the wide-area sea due to the special geographical characteristics of the sea. LTE-M can communicate with 10Mbps up to 100 kilometers from the sea, but LTE-M cannot interconnect PS-LTE in the event of an accident in wide-area waters exceeding 100 kilometers. Therefore, this study focused on ship-type mobile base stations for PS-LTE linkage in wide-area waters. According to a survey of the operation status of the satellite communication network (KOSNET) of Korea Coast Guard patrol ships that will be operated as ship-type mobile base stations in wide-area waters, there was a lack of bandwidth already allocated due to on-site video transmission and the use of various business systems. It was a short-term task to spend a large budget to expand the satellite bandwidth in order to operate the public safety communication network. However, there was a limit to the expansion of the Mugunghwa 5A satellite bandwidth operated by the Korea Coast Guard satellite network, and it was confirmed that the next-generation satellite for public complex disaster was needed to link PS-LTE in wide-area waters. It is hoped that this research will be reflected in policies to secure wide-area maritime communication rights for public safety networks, thereby protecting the lives and property of the people.