Reviewerly/exHarmony huggingface dataset:
LibGuides: Old Beacon Express: Using Beacon Express

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Effects of miners’ location on blocks selection in blockchain

Blockchain is a distributed ledger technology for recording transactions. To guarantee the immutability of the blocks, miners need a lot of computational resources for generating blocks (mining). Since mining is conducted distributedly by many miners, chain forks can occur in the blockchain. In this paper, we investigate the effects of miners’ locations, the size of the mining pool (MP), and the network structure on the selection rate of blocks generated by the MP when chain forks occur through simulations.
New Improvement of Malware-Attack Scenarios Modeling

It is important to state that, from the intrusion detection point of view, the number of steps that appears in a certain session of an attack process is arbitrary. Indeed, in order to prevent detection, attackers can proceed slowly, following different steps, in many days, or even in many weeks. The main objective of this study is to learn how to shape the progression of an attack process in time. We propose a stochastic model based on Markov chains. The basic assumption of our model consists of evaluating malware valid attack scenarios. The algorithm we have proposed shows that we will be able to identify an attack scenario while the attack process is not yet complete which will help IDS to improve the detection rate of malware attacks.
A prototype for incremental learning finite factored planning domains from continuous perceptions and some case studies

This master project takes place within the research activity carried on by the Fondazione Bruno Kessler (FBK) in Trento, in Data and Knowledge Management unit (DKM), with Luciano Serafini as internal tutor, and Paolo Traverso as external tutor. The project focuses on automated learning of planning domains. Automated learning and planning often leverages on an abstract representation of the world called planning domains. A planning domain is described by a set of states that correspond to possible configurations of the environment, a set of actions, and a state-transition function between states, which describes the effects of actions on the environment. Planning domain models are used by agents to develop their strategies on how to act in a given environment in order to achieve their goals. The construction of these models is normally entrusted to the engineer who manually programs the agent. This work, however, requires human intervention for each new environment, while it would be desirable for an autonomous agent to be able to build a model of the environment autonomously, even if it is in an unknown environment. The aim of the research carried out by the DKM unit is to use automatic methods to learn these models by carrying out actions, and observing their effects on the environment. The specific objectives of this master thesis are to: (1) acquire specific knowledge in the field of automatic learning and planning; (2) acquire specific knowledge in the context of learning planning models; (3) extend the method developed in the research activity in FBK on states variables that are described by a set of variables taking values overdomains; (4) deal with the problem of learning entirely thestate-transition function; (5) extend the ALP algorithm with a prediction part to predict the effects of the actions; (6) complete the state-transition function; (7) implement the algorithm with all the new parts, provide examples, and test this extension in some simulators previously created; (8) validate and analyse the results, and measure the goodness of the model.
모바일 SNS 기반 e-탄뎀 활동의 중국어 학습 효과와 상호작용 분석

This study examined the effect of Chinese learning using e-tandem activity based on mobile SNS on Chinese learning overall for Korean learners learning Chinese in Korea. In addition, Korean learners who had to learn Chinese as a foreign language examined the interactions with native speakers. Also, this paper attempts to summarize some examples of communication strategies used.The results of this study demonstrate that mobile-based e-tandem activity is a universal tool for current learners of various ages, especially mobile. In addition, it can be seen that it can be relatively effective when combined with Chinese learning. However, it can be seen that the environment for learning Chinese must be properly designed so that the e-tandem activity can be used as a more effective tool for the learner''s individual characteristics. In addition, the application plan should be specifically designed and applied to effectively improve the language skills of learners.
Fairy Tale Form Spoken to Written in the Perspective of Readingless Teenager

Fairy tales are imaginary stories that are not bound by place and time told for generations.This research aims to describe of teenager aged 13-15 years in Magelang on the elements of plot, character, style, and theme fairy tale "Burung-burung Memilih Raja" and the affecting factors that influence their response to this fairy tale.It is a method of concurrent embed model combination.The research subjects are the grade VIII students in one learning group of the four schools in Magelang.The data source is the fairy tale entitled "Burung-burung Memilih Raja" retold by Nukila Amal, the result of the response to this fairy tale, and the factors that influence the responses.The research data was obtained through questionnaires.The data were analyzed quantitatively and qualitatively.The results show that in one side, the fairy tale "Burung-burung Memilih Raja" got the positive responses from the readers.But, in the other hand there are contradictions to these results.Internal factors consist of limited literary reading experience and limited experience of hearing or watching fairy tales.External factors consist of motivation from parents to read literature, the influence of friends who are not accustomed to read literature, and the influence of television and social media.
QuMANET- changes in Mobile ad-hoc network with quantum bits for reliability

Due to the mobility, service discovery and service selection in Mobile Ad hoc Network (MANET), the routing protocol of MANET must adapt to the rapid changes of the network structure, and ensure that the services will be available to the users as quickly as possible.This paper proposes a kind of new quantum based MANET with the help of which service discovery will be fast enough that the user will not get a break in connection and swap over multiple services very fast with the help of quantum bits.By embedding MANET with quantum computing bits, it can effectively reduce the time for service selection, improve the delivery rate of data packets, and reduce the time delay of switching between services.The goal of this work is to shed light on the challenges and the open problems of the Quantum bits dealing with MANET design.To this aim, we first introduce some basic knowledge of Quantum mechanics, MANET needed to understand the differences between a MANET and the design we are thinking quantum MANET.Then, we introduce quantum bits as the key strategy for service swapping without physically transferring the particle that stores the quantum information.Finally, we will introduce the challenges that can be faced while transferring data over quantum bits.
Creation of an Electronic Textbook for University Students

The need for e-learning in modern Russia is caused by the rapid development of informatization, digitalization, information and communication technologies, the creation of a global environment for mutual integration of cultures and disciplines, as well as the formation of open continuous education, which is the basis of a post-industrial (information) society. These processes stimulate an active search for creative educational practices that meet the requirements of the information society. A modern specialist must have a certain amount of knowledge that will allow him to learn constantly, improve his skills and abilities, self-develop and self-actualize in order to keep up with the time of changes in the information society. In the framework of the modern educational paradigm, the student is considered as a subject of knowledge, not an object of pedagogical influence. In the early – mid-2010s, this is actively promoted by electronic learning (e-learning, EL), which should be used in various educational organizations. E-learning allows integrating into the world scientific community, becoming subjects of interaction between cultures, including the exchange of spiritual values. Implementation of EL is one of the key tasks in the context of modernization of national education. The term “electronic learning” is translated into Russian in various ways. The most popular options are: “distance learning/education”, “mobile learning”, and “virtual learning”. The European Commission interprets “e-learning” as “using new multimedia and Internet technologies to improve the quality of learning by improving access to resources and services, as well as remote knowledge sharing and collaboration”. In this study, the concept of “e-learning” will correspond to the phrase “electronic learning”. This is an educational process based on interactive electronic means of storing and providing information: the Internet, corporate networks, and CDs.
Object-based Illumination Estimation with Rendering-aware Neural Networks

We present a scheme for fast environment light estimation from the RGBD appearance of individual objects and their local image areas. Conventional inverse rendering is too computationally demanding for real-time applications, and the performance of purely learning-based techniques may be limited by the meager input data available from individual objects. To address these issues, we propose an approach that takes advantage of physical principles from inverse rendering to constrain the solution, while also utilizing neural networks to expedite the more computationally expensive portions of its processing, to increase robustness to noisy input data as well as to improve temporal and spatial stability. This results in a rendering-aware system that estimates the local illumination distribution at an object with high accuracy and in real time. With the estimated lighting, virtual objects can be rendered in AR scenarios with shading that is consistent to the real scene, leading to improved realism.
Optimal N-gram Subset Extraction for Accelerating Evaluation Using Genetic Algorithm

One of the standard methods of processing natural language in computational linguistics is to apply the ngram model. An n-gram model extracts unigrams, bigrams, trigrams, etc. from texts which are treated as features for various tasks such as feature selection in classification. One of the significant drawbacks of the n-gram model is that the number of n-grams generated can scale exponentially with the size of processing text. This results in complex processing, thus making the n-gram model infeasible on systems with limited computational resources. Here, we discuss a novel strategy to select an optimal subset of n-grams using a genetic algorithm. The subset so generated will be able to perform classification with similar accuracy to the original set and in significantly lower time. The method also leads to reduced memory & computational requirements, thus making it feasible for lowerend systems. The proposed algorithm named OSE produces significant performance gains and is seen as a pre-processing step, which opens up a whole new dimension for algorithms that may appear infeasible on a large corpus.
Suggestions on Discrimination and Training for Occupational Responsibility of Preschool Teachers

The occupational responsibility of preschool teachers is an important measurement for their occupational level, and an indivisible unity composed of responsibility cognition, responsibility emotion and responsibility behaviors.Strengthening the rational research on preschool teachers' occupational responsibility, clarifying the range of their occupational responsibility cognition, arousing the correct and positive emotion of occupational responsibility, and paying attention to their occupational responsibility behaviors, etc. are conducive to training their occupational responsibility.
On the relationship between (secure) multi-party computation and (secure) federated learning

The contribution of this short note, contains the following two parts: in the first part, we are able to show that the federate learning (FL) procedure presented by Kairouz et al. \cite{Kairouz1901}, is a random processing. Namely, an $m$-ary functionality for the FL procedure can be defined in the context of multi-party computation (MPC); Furthermore, an instance of FL protocol along Kairouz et al.'s definition can be viewed as an implementation of the defined $m$-ary functionality. As such, an instance of FL procedure is also an instance of MPC protocol. In short, FL is a subset of MPC. To privately computing the defined FL (m-ary) functionality, various techniques such as homomorphic encryption (HE), secure multi-party computation (SMPC) and differential privacy (DP) have been deployed. In the second part, we are able to show that if the underlying FL instance privately computes the defined $m$-ary functionality in the simulation-based framework, then the simulation-based FL solution is also an instance of SMPC. Consequently, SFL is a subset of SMPC.
Automatic extraction of cell nuclei using dilated convolutional network

Pathological examination has been done manually by visual inspection of hematoxylin and eosin (H&amp;E)-stained images. However, this process is labor intensive, prone to large variations, and lacking reproducibility in the diagnosis of a tumor. We aim to develop an automatic workflow to extract different cell nuclei found in cancerous tumors portrayed in digital renderings of the H&amp;E-stained images. For a given image, we propose a semantic pixel-wise segmentation technique using dilated convolutions. The architecture of our dilated convolutional network (DCN) is based on SegNet, a deep convolutional encoder-decoder architecture. For the encoder, all the max pooling layers in the SegNet are removed and the convolutional layers are replaced by dilated convolution layers with increased dilation factors to preserve image resolution. For the decoder, all max unpooling layers are removed and the convolutional layers are replaced by dilated convolution layers with decreased dilation factors to remove gridding artifacts. We show that dilated convolutions are superior in extracting information from textured images. We test our DCN network on both synthetic data sets and a public available data set of H&amp;E-stained images and achieve better results than the state of the art.
Does competence of central bank governors influence financial stability

This study investigates whether the competence of central bank governors affect the stability of the financial system they are responsible for. Using publicly available information about central bank governors from 2000 to 2016 together with data on financial stability and the macro-economy, the findings reveal that central bank governors’ competence promotes financial stability, depending on how competence is measured. Specifically, the findings reveal that the financial system is more stable when the central bank governor is older and male. The financial system is also stable during the tenure of a central bank governor that has a combination of cognitive ability, social capital and technical competence in economics. The gender analyses reveal that the financial system is also stable during the tenure of a female central bank governor that has high social capital or high cognitive abilities while the financial system is relatively less stable during the tenure of a male central bank governor that has high social capital or high cognitive abilities. Comparing developed countries to developing and transition countries, the findings reveal that the financial system of developed countries is more stable during the tenure of a central bank governor that has high cognitive ability, social capital and technical competence in economics while the financial system of developing and transition countries is less stable during the tenure of a central bank governor that has high cognitive ability, social capital and technical competence in economics. Also, there is evidence that the financial system of developing and transition countries is more stable during the tenure of a central bank governor that has knowledge in disciplines other than economics. The findings are consistent with the view that certain characteristics of central bankers shape their beliefs, preferences and choice of policy, which in turn, are consequential for policy outcomes during their tenure.
LibGuides: Reading Ladders & Text Suggestions: Home

This LibGuide is meant to serve as a tool for educators looking to recommend texts to their readers in order to help them move from lower to higher reading levels. The texts and categories in this LibGuide are meant to serve high school-aged students.
Peculiarities of using social networks as a source of information in online media

Social networks are a modern communication trend performing various functions in society. One of them is a source of information for the media. The article examines theoretical aspects of usage of social networks in Internet media, content analysis of Internet media materials that use information from social networks, highlights the topics of such materials, ways to use information from social networks, evidence and argumentation of information. In order to achieve this goal, we conducted a study that consisted of several stages. The first is an analysis of theoretical basis. We have studied the research of the Ukrainian and foreign researchers on social networks and the possibilities of using them as a source of information in journalism. After that, a content analysis of materials of all-Ukrainian and regional Internet media was carried out for the presence of links to social networks, in particular text links, screens, photos or videos. Technologically, it looked like this: we introduced a search query for the phrases «social networks», «in the social network», «form social networks» in search engines, filtering the results in the news for April-May 2020. It produced almost 200 results (N = 197). The object of content analysis was information materials placed in the newsfeed, as well as publications placed in the top sections. Next, we analyzed the topic, the argumentation of the materials, the availability of additional comments, links to official sources, resources, and so on. We also singled out those materials whose content seemed questionable, contained emotional headlines, insufficient evidence, manipulation, and so on. The conclusions state that despite the multi-vector use of information from social networks in the Internet media, journalists must adhere to journalistic standards, check the information so as not to spread misinformation. Keywords: Internet media, social networks, information, source.
The interactive e-textbooks in Ukraine: typological problems

The article deals with the problems of term functioning and classification in the field of electronic educational publications (electronic textbooks) in the Ukrainian publishing market. It analyses the main features of the standards in the field of electronic book publishing, as well as basic principles of its creation. The problems of creating electronic textbooks have been highlighted. Prospects for further research and a possibility of terms’ usage from the publishing business have been described. Previously, this term was understood as a device enabling reading, but at present an e-book is a content that requires playback by individual devices. The problems of creating interactive electronic publications, including the lack of skills of publishers and a high cost of software for such publications’ layout have been explored. This issue can be resolved either in concluding agreements with foreign partners,or in creating their own technological platforms. Summarizing our analysis, we can conclude that standards in the field of electronic publications should be updated at least once every five years. Ukraine needs not only well-designed standards, but also a respect for copyright and a protection of intellectual property. A lack of control, unified typological classification and certification of such publications can result in springing up electronic publications of improper quality. Respectively, they can harm users. Sometimes publishers can not clearly identify which electronic product they have made. The problem can be solved only at the national level, with the help of regulations and a creation of a regulative institution. The latter should be responsible for standardization and certification of e-learning publications and their quality characteristics. The prospects for standardization of electronic publications have been determined. Keywords: e-learning edition, e-textbook, interactive textbook, multi media content, standard, typology, problems.
Energy trading systems on blockchain networks

Traditional energy trading system has some weakness in terms of network attack.So blockchain is considered for P2P energy trading systems to evade network attacks.We consider three energy trading systems on blockchain which are centralized energy trading system with one producer, P2P energy trading system with DSO and P2P energy trading system with smart contract.And we compared P2P energy trading systems on running in terms of transaction fees.By using blockchain, users can reduce transaction fees then make more benefi ts.
Considering Fine-Grained and Coarse-Grained Information for Context-Aware Recommendations

Abstract In context-aware recommendation systems, most existing methods encode users’ preferences by mapping item and category information into the same space, which is just a stack of information. The item and category information contained in the interaction behaviours is not fully utilized. Moreover, since users’ preferences for a candidate item are influenced by the changes in temporal and historical behaviours, it is unreasonable to predict correlations between users and candidates by using users’ fixed features. A fine-grained and coarse-grained information based framework proposed in our paper which considers multi-granularity information of users’ historical behaviours. First, a parallel structure is provided to mine users’ preference information under different granularities. Then, self-attention and attention mechanisms are used to capture the dynamic preferences. Experiment results on two publicly available datasets show that our framework outperforms state-of-the-art methods across the calculated evaluation metrics.