Reviewerly/exHarmony huggingface dataset:
Book Review - Cloud Computing Design Patterns

Cloud Computing Design Patterns is written by Thomas Erl, Robert Cope, and Amin Naserpour, and published by Prentice Hall, © 2015, 978-0-13-385856-3, and is 591 pages long. The "Objective of This Book" section sets a lofty goal to catalog design patterns for cloud computing, targeting IT professionals who are involved in architecting, building, maintaining, evolving cloud-based solutions and environments. Since that fits squarely in the middle of my "day job", I was really excited to get my hands on this book.
Guides: Investing: Library Resources

Investing can be an intimidating topic. This guide will provide resources for researching and determining the best investments for your money.
Plaintext aware encryption in the standard model under the linear Diffie-Hellman knowledge assumption

In this paper, we consider the problem of constructing new plaintext aware encryption in the standard model. A new hybrid asymmetric encryption scheme is presented using a new key encapsulation method and a data encapsulation method. To prove the presented asymmetric encryption scheme is simulatable, we put forward some new sufficient conditions for judging a group to be simulatable. By introducing a new assumption called linear Diffie-Hellman knowledge assumption, we prove the proposed hybrid asymmetric encryption scheme is PA2.
A Hybrid Image Watermarking Methodology Based on BP-RBF Neural Network Model and Sift Transform Function

The content of the integrity of digital image needs copyright protection; the process of copyright protection used the methods of digital watermarking techniques. The strength and robustness of watermarking algorithms faced a problem of geometrical attacks. In this paper proposed novel algorithms for digital image watermarking using BP neural networks using features transform. The SIFT transform function is a core feature transform function of a digital image, and the BP neural network is multi-layer neural network models. The BP neural network generates the pattern for the embedding. The BP neural network and RBF neural network cascaded and generates dynamic patterns for embedding. The processing of RBF neural network models is very efficient due to a single layer network. The proposed algorithms implemented in MATLAB software and perform well know image dataset for the processing of image watermarking. For the validation of algorithms measure some standard parameters in concern of quality measure peak to signal-noise ratio. In concern of security strength measure number of correlations of a pixel, and in terms of complexity measure time of encoding and decoding of watermarking algorithms.
Steganographic approach to enhance the data security in public cloud

Steganography is the claim to fame of disguising how correspondence is happening, by hiding information in other information. As picture encryption is a quickly creating innovation in the field of picture preparing, it can be portrayed as the strategy for encoding messages and data especially to such an extent that it can be gotten to ensured elements as it were. The paper manages an overview which deals about delineation enigma, along with its applications as well as techniques. It moreover endeavours so that it can recognise the essentials of a respectable enigma figuring as well as swiftly considers the steganography procedures that are better suitable for specific applications. Information transmission crosswise over systems is a typical practice according to the advancement of internet and sight and sound advances that develops exponentially today. The paper displayed about the mystery sharing of message by concealing it in a picture utilising the most ordinarily utilised least significant bit (LSB) method. Here, steganography went for concealing the information imperceptibly inside any media (picture, sound and video) so it ought to be unnoticeable to the unintended individual and in this manner accomplishing secured applications.
Christian Education For Communal Living Society

In recent years, young people have been favouring the ‘single life’. This means that the idea of ‘living together’ is collapsing in our society. The present state of affairs in Korea mirrors these modern trends. In fact, the ‘single life’ is another aspect of a selfish individualism.BR Individualism is rooted in the principle of ‘enlightenment’. The spirit of ‘enlightenment’ is liberty, self-control, and rationality. It has been understood that these are accomplished through reason. But liberty means that the subjective has control over the objective in modern society. Therefore, Individualism is not only a psychological problem but a sociological and ecological problem in human society as well. These problems are related to the teaching ministry of the church and Christian education. Therefore, this study is to explore prospect and tasks of Christian education through critical reflection on these problems.BR The aims of Christian education orientates around “The kingdom of God”. I use the term “society of communal living” instead of “kingdom of God.” This concept reflects the social conditions and assumptions that have been accepted by Christian teaching as the very sphere in which the Christian life is to be lived.BR The biblical understanding of communal living is an alternative community that is not realized by instrumental reason in modern times but according to a law of life written in ‘Creation narrative’ in Genesis(Gen 1:1~2:4). It is biblical reason which is different from instrumental reason. It is defined by the statement that “living for others” is “living for self.” “Living for others” can be fulfilled through the gradual and systematic educational programmes.
GraphiX: A Fast Human-Computer Interaction Symmetric Multiprocessing Parallel Scientific Visualization Tool1

Scientific visualization tools are essential for the understanding of physical simulation, as it gives a visualization aspect of the simulated phenomena. In the past years, data produced by simulations join the big-data trend. To maintain a reasonable reaction time of the user’s commands, many scientific tools tend to introduce parallelism schemes to their software. As the number of cores in any given architecture increases, the need for software to utilize the architecture is inevitable. Thus, GraphiX – a scientific visualization tool parallelized in a shared-memory fashion via OpenMP version 4.5 was created. We chose Gnuplot as the graphical utility for GraphiX due to its speed as it is written in C. GraphiX parallelism scheme’s work-balance is nearly perfect and scales well both in terms of memory and amount of cores. We achieved a maximum of 560% speedup with 16 cores while visualizing approx 3 million cells.
Extracting and searching news articles in web portal news pages

Recently, a large amount of news articles is being created online, and news articles are important resources for understanding social phenomena and trends. Accordingly, a web portal service provides a 'portal news page' that classifies news articles published from various news sources into sections and provides each news article with a certain structure. Therefore, by analysing portal news pages, it is possible to automatically extract information about news articles. In this paper, we introduce a prototype that extracts and searches key information of news articles for analysis. Specifically, we describe: 1) a crawler that collects, analyses and parses news articles; 2) an Elasticsearch server that indexes and searches news information; and 3) a front-end application that provides a search user interface. These systems are expected to provide the foundation for news analytics and forecasting services.
USING KWL (KNOW-WANT TO KNOW-LEARNED) STRATEGY IN IMPROVING STUDENTS’ READING COMPREHENSION

This experimental study aimed to investigate the effects of the use of KWL (Know-Want to Know-Learned) strategy in teaching reading comprehension. The population of this study was 120 students, while the samples consisted of 60 English department students enrolled in the second semester. The sample was divided into two groups; the experimental group (EG) and the control group (CG). The sample was chosen through random sampling technique. The instruments used in collecting the data were test and questionnaire. The data were analyzed through non-parametric statistical in SPSS 20. The result of Wilcoxon test was 0.00 lower than 5%. The findings reveal that there was significant difference in reading comprehension achievement between EG and CG. The mean score of the post-test for the EG was 9.92, while the mean score for post-test of CG was 7.91. Hence, it can be concluded that the alternative hypothesis was accepted and the null hypothesis was rejected. Consequently, the use of KWL strategy has proven a significance improvement in the students’ reading comprehension. Some implications are derived for both students and teachers.
Evolving Fitness Landscapes with Complementary Fitness Functions

Given an optimization problem, local search algorithms may fail to reach optimal solutions when faced to difficult and unsuitable fitness landscapes. Climbing based optimization is sensitive to unexpected distribution of local optima. In this paper, we aim at modifying the initial fitness landscape of a problem in order to better fit climbing requirements. We propose thus a fitness landscape generation framework based on an evolutionary process. Preliminary experiments are presented as a proof of concept.
Attending Knowledge Facts with BERT-like Models in Question-Answering: Disappointing Results and Some Explanations

Since the first appearance of BERT, pretrained BERT inspired models (XLNet, Roberta, ...) have delivered state-of-the-art results in a large number of Natural Language Processing tasks. This includes question-answering where previous models performed relatively poorly particularly on datasets with a limited amount of data. In this paper we perform experiments with BERT on two such datasets that are OpenBookQA and ARC. Our aim is to understand why, in our experiments, using BERT sentence representations inside an attention mechanism on a set of facts tends to give poor results. We demonstrate that in some cases, the sentence representations proposed by BERT are limited in terms of semantic and that BERT often answers the questions in a meaningless way.
Through the eyes of a robot

Network Effect is a glorious, pulpy, action-packed book about a Murderbot, and it raises fascinating questions you will think about long after you have finished it, says Sally Adee
Seçili Kripto Paralarda Kümeleme Analizi

Money has a very important place in our daily lives. To date, many different types of money have been used. The coins commonly used throughout the world in the present century are mostly the products of a central model. Since 2009, the cryptocurrencies built with blockchain technology, which has a distributed architecture, have taken their place in the financial sector. There are many doubts about these relatively new currencies. Cryptocurrency clustering is one of the methods that can be used in forecasting studies on cryptocurrencies. In the light of this information, it is the aim of the study to give investors an idea by revealing their similarity levels in terms of price changes of selected cryptocurrencies. In this study; cryptocurrencies are clustered according to 1-hour, 24-hour and 7-day exchange data of cryptocurrency prices that have reached market value a certain size (which constitutes the top 25 in terms of market value). There are 6 levels in the clustering. According to the lowest level result, the most similar cryptocurrencies were Ontology with NEO. It is a remarkable result that the ATOM currency does not enter the same cluster with any currency at the lower levels.
Användarcentrerad utveckling av navigationssystem i ambulanssjukvården

The operations of emergency medical services have in the past few decades undergone a transformationfrom mainly transporting patients to health facilities to being a key care-giving contributor in the mobilizationof prehospital care. In order for paramedics to fulfill their expanded set of tasks while maintaininggood patient safety concurrently with increasing demands on the emergency medical services, continuousevaluation of the supporting tools that are used in the operations. One such tool is Paratus Navigation,a digital navigation- and communication system that is used in ambulances in 19 of 21 Swedish regions.In this thesis, an iterative user-centered design study was conducted in order to evaluate the usabilityof Paratus Navigation. An expert evaluation based on established design concepts was followed by twosets of usability tests. The usability tests were conducted on two different user groups (experienced andnon-experienced users) according to two different methods (qualitative and quantitative usability testing,respectively) in order to identify usage patterns and usability issues in Paratus Navigation.Collected data from the evaluations laid the foundation to a set of new functions and interface components,illustrated in a continuously updated prototype of Paratus Navigation. Some design choices in theprototype were incentivized by by statistically proven, measured usability, others by qualitative findingsand opinions from both user groups. The evaluation methods applied in this thesis put the users in thecenter, complement each other well, and give an extensive overall evaluation of Paratus Navigation. Futurestudies within the field of usability are recommended to adopt a similar methodology. Findings fromthis thesis can be used by stakeholders within emergency medical services and the private sector fordirect implementation into the existent system or as a preliminary study for a larger study of profitability.
The Use of Class Assertions and Hypernyms to Induce and Disambiguate Word Senses.

With the spread of semantic technologies more and more companies manage their own knowledge graphs (KG), applying them, among other tasks, to text analysis. However, the proprietary KGs are by design domain specific and do not include all the different possible meanings of the words used in a corpus. In order to enable the usage of these KGs for automatic text annotations, we introduce a robust method for discriminating word senses using sense indicators found in the KG: types, synonyms and/or hypernyms. The method uses collocations to induce word senses and to discriminate the sense included in the KG from the other senses, without the need for information about the latter, or the need for manual effort. On the two datasets created specially for this task the method outperforms the baseline and shows accuracy above 80%.
Discover: Fresh Focus: GLBTQ+ Reads for Kids and Teens: Fresh Focus: GLBTQ+ Reads for Kids and Teens

Here is a fabulous list of books that children of all ages can use to educate, advocate, and celebrate! Here is a fabulous list of books that children of all ages can use to educate, advocate, and celebrate!
Graph Construction using the dK-Series Framework

Author(s): Tillman, Balint | Advisor(s): Markopoulou, Athina | Abstract: It is often desirable to generate random graphs that exhibit certain prescribed properties, for example, for simulation or anonymization of real-world graphs. In this dissertation, we adopt and build on the dK-series modeling framework and we make the following three sets of contributions. First, we focus on undirected graphs, and we provide a flexible approach for generating simple undirected graphs with the exact target joint degree matrix (JDM), which we refer to as 2K graphs, in linear time in the number of edges. Our 2K construction algorithm imposes minimal constraints on the graph structure, which allows us to target additional graph properties, namely node attributes (2K+A), clustering (both average clustering, 2.25K, and degree-dependent clustering, 2.5K) and number of connected components (2K+CC). We show that realizability of exact 2.25K, 2.5K and in general dK-series for any d g= 3 is NP-Complete. Second, we also define the problem of directed and directed acyclic 2K graph construction (D2K, DAG2K), we provide necessary and sufficient conditions for realizability, we develop efficient construction algorithms for D2K and solve DAG2K in the special case of level graphs (D2K+L). We evaluate our approach by creating synthetic graphs that target real-world graphs both undirected (such as Facebook) and directed (such as Twitter) and we show that it brings significant benefits, in terms of accuracy and running time, compared to state-of-the-art approaches.Third, we propose a new approach for graph construction with a prescribed local neighborhood structure. To capture that structure, we define the Neighborhood Partition Matrix (NPM): given a node partition, NPM specifies the number of edges from each node to each part of the partition. Our goal is to construct simple graphs that exhibit a given NPM, if that is realizable. NPM can also be thought of as graph embedding, where each dimension corresponds to a part in the partition. This key observation allows us to create graph realizations from these embeddings with guarantees such as degree sequences, degree correlations, etc. The main strength of the NPM approach is its generality: (i) it bridges the gap between classic graph realization (for degree sequences and other structural properties) and graph embeddings; (ii) it allows arbitrary node partitions, thus includes prior models as special cases. We describe the main approach for undirected graphs and we extend it to directed graphs and graphs with non-chords. We evaluate strategies for NPM based on different node partitions and we compare against baselines w.r.t. targeted graph properties and graph embedding tasks, namely, graph reconstruction, link prediction and node classification.
Developing family reading with personalized books from the Mali junaki collection

Reading is of the utmost importance since it helps develop other important linguistic abilities and competences that influence the development of individual’s literacy. The family has a primary role in developing a positive attitude towards reading. It impacts the child's motivation and interest in reading in early childhood. During this period, one of the most important activities is reading out loud to children, which creates an active reading process. Parents are the ones that should introduce books to their children and provide them with quality reading materials. Recently, personalized books have become popular in children's literature. They allow you to alter the name of the main character, its appearance and the book’s content to match the child’s interests. Foreign research show that personalized books have a positive impact on the emotional responses of children and parents and help increase the interest and motivation for reading.The research part of the master's thesis focuses on the impact of “Hooray Heroes” (Mali junaki) personalized books on the development of family reading. In the first part of the empirical research, the results of a quantitative survey were used to explore the user experience of parents, which are already familiar with personalized books, and research whether they feel personalized books influence the child’s interest in reading. The second part of the thesis was a qualitative survey that included three families and researched the way personalized books influence emotional, verbal and non-verbal responses of children while reading. It also explored the opinion of parents and children on personalized books, and whether they feel those books have a positive impact on developing family reading habits and reading motivation.The results of the empirical part show that parents feel more involved in the process of family reading when they are able to actively participate in the creation of personalized books. Moreover, personalized books influence the emotional and verbal responses of children while reading, improve reading motivation and develop family reading habits. The parents participating in the qualitative research confirmed that those were the things that made children more interested in the books: the name of the main character, their graphic image and personalized illustrations. The parents confirmed that personalized books improve reading motivation, contain educational content and encourage reading in a home environment. They believe that children are more concentrated due to personalized elements in the book.
서울시 공공빅데이터 활성화 방안 연구

The purpose of this study is to investigate the current state of public Big Data in Seoul and suggest policy directions for the revitalization of Seoul’s public Big Data. Big Data is perceived as innovation resources under the era of 4th Industrial revolution and Data economy. Especially, public Big Data serves a significant role in terms of universal access for citizens, startup, and enterprise compared with the private sector. Seoul reorganized a substructure of government’s focus on Big Data and established organizations such as Big Data Campus and Urban Data Science Lab. Although the number of public open Data has increased in Seoul, there exists not much Data with characteristics similar to Big Data, such as volume, velocity, and value. In order to present the direction of Big Data policy in Seoul, we investigate the current status of Big Data Campus and Urban Data Science Lab operated by Seoul City. Considering the results of this study, we have proposed several directions that Seoul can use in establishing big data related strategies.
LibGuides: LSC 596- School Library Media Seminar : Professional Packet

This professional portfolio highlights my work for the culminating seminar and practicum for k-12 Library Media certification in Rhode Island.
Non-linear Causal Inference Using Gaussianity Measures.

We provide theoretical and empirical evidence for a type of asymmetry between causes and effects that is present when these are related via linear models contaminated with additive non-Gaussian noise. Assuming that the causes and the effects have the same distribution, we show that the distribution of the residuals of a linear fit in the anti-causal direction is closer to a Gaussian than the distribution of the residuals in the causal direction. This Gaussianization effect is characterized by reduction of the magnitude of the high-order cumulants and by an increment of the differential entropy of the residuals. The problem of non-linear causal inference is addressed by performing an embedding in an expanded feature space, in which the relation between causes and effects can be assumed to be linear. The effectiveness of a method to discriminate between causes and effects based on this type of asymmetry is illustrated in a variety of experiments using different measures of Gaussianity. The proposed method is shown to be competitive with state-of-the-art techniques for causal inference.
Private Key Recovery on Bitcoin with Duplicated Signatures

In the modern financial sector, interest in providing financial services that employ blockchain technology has increased.Blockchain technology is efficient and can operate without a trusted party to store all transaction information; additionally, it provides transparency and prevents the tampering of transaction information.However, new security threats can occur because blockchain technology shares all the transaction information.Furthermore, studies have reported that the private keys of users who use the same signature value two or more times can be recovered.Because private keys of blockchain identify users, private key leaks can result in attackers stealing the ownership rights to users' property.Therefore, as more financial services use blockchain technology, actions to counteract the threat of private key recovery must be continually investigated.Private key recovery studies are presented here.Based on these studies, duplicated signatures generated by blockchain users are defined.Additionally, scenarios that generate and use duplicated signatures are applied in an actual bitcoin environment to demonstrate that actual bitcoin users' private keys can be recovered.