Reviewerly/exHarmony huggingface dataset:
A Single Criteria Ranking Technique for Schools Based on Results of Common Examination Using Clustering and Congenital Weights

In this paper, an innovative clustering-based ranking technique is presented to rank the schools for a common examination. Particularly, the inputs to the problem are a set of schools, and a corresponding set of marks of the students appeared in the common examination. The expected output is the order of these schools on the basis of the marks of students. Note that the number of students participating from each school varies apart from various ranges of marks obtained by its students. Hence, ranking these schools is not straightforward as it is for the students who can be easily ranked by the marks only. An intuitive idea is to rank schools based on the average mark over all the students of each school. However, this will suppress the impact of the volume of students, and likely to consist of several ties. Also, it may discourage higher participation in the entrance and/or scholarship examinations where the school performance is also measured, especially barring the moderately meritorious students. Thus, a solution is adequate only if it additionally addresses the volume of students although the mark is the lone criterion to resolve the issues in an intuitive approach. The proposed ranking technique categorizes the students into disjoint groups generated through a cluster of marks. Then, the schools are ranked on scores that are computed based on the distribution of volumes and marks of the students in various groups. The ranking of schools for an undertaken case study shows that the ordering is adequate.
Reversible Data Hiding Associated with Digital Halftoning That Allows Printing with Special Color Ink by Using Single Color Layer

We propose an efficient framework of reversible data hiding to preserve compatibility between normal printing and printing with a special color ink by using a single common image. The special color layer is converted to a binary image by digital halftoning and losslessly compressed using JBIG2. Then, the compressed information of the binarized special color layer is reversibly embedded into the general color layer without significant distortion. Our experimental results show the availability of the proposed method in terms of the marked image quality.
LibGuides: Alcorn Digital Learning Lab: Mission

Welcome to the website for the Alcorn Digital Learning Lab housed in the Corriher Linn Black Library at Catawba College.
Research Guides: CIS 252 - Database Security: Keywords and Subject Headings

A guide for CIS 252 students working on database security papers. How to use Google Scholar and Academic Search Complete to research database security.
LibGuides: Library Events: Spring 2021 Library Orientation

Want to know what is going on at the Library? Check out all of our past and upcoming events here! Weren't able to join us for our Orientation? No problem! See the video presentation here!
Implementation of Rehabilitation Exercise Posture Determination System Based on CNN Using EMG and Acceleration Sensors

A number of musculoskeletal disorders occur worldwide in occupations that perform physically demanding tasks. In order to treat musculoskeletal disorders, rehabilitation must be performed, but it is not easy to correctly perform rehabilitation exercise by the patient at home where they spend a long time. Therefore, for effective rehabilitation exercise, a rehabilitation exercise posture determination system using body information of patients is required. In this paper, we implemented rehabilitation exercise posture determination system based on CNN using EMG and acceleration sensors. The implemented system measures data during rehabilitation exercise, performs pre-processing, and inputs it into the trained CNN model to determine the exercise posture. In order to evaluate performance of the implemented system, actual measurement data was input CNN model 50 times each to confirm the accuracy of posture determination. As a result of the experiment, the accuracy of 98.6% was confirmed.
The Defender vs. the Censor: CDA Analysis of 2017 Russian Web-Source Ban in Ukraine

With the new challenges of the digital world associated with disinformation, data breaches, and cybercrimes (Cadwalladr & Graham-Harrison, 2018; Connolly et al., 2016; Shipley & Bowker, 201 ...
Volatility Scenario of Bitcoin: The restraining role as a store of value and a unit of account

Bitcoin and other cryptocurrencies are subject to unusual price fluctuations that increase the concern of the people and institutions to transact with it and to invest in it. The daily price volatility in the case of Bitcoin scales even up to 50 per cent in some days. Studies on market efficiency, volatility, demand drivers and so on of Bitcoin are done on considerable scale to bring out pertinent information about its different behavioural dimensions. However, its acceptance and use are limited primarily on account of the volatility and the political risks associated to it. This paper pioneers in the assessment of the temporal sequence and magnitude of volatility of Bitcoin by analysing 2018 daily price data. The study found that the coin shows unusually high daily price changes of 10 per cent or more only on 70 days (3.47%) out of the 2017 daily returns computed from the price data. Noticeably, the number of days with positive returns in the 70 days is 31 as against the 39 days with losses. These unusual daily price changes of 3 to 4 times out of 100 found in the study are the cause of volatility concern spreading around Bitcoin. There are six instances of more than 100 days gap between the two unusual price changes in the 70 cases. No significant correlation is found between the unusual daily returns and the corresponding volume of trade on these days. The unusual daily volatility of Bitcoin occurring once in a while may dampen its role as a store of value and a unit of account.
Gems and nuggets: multicultural education for young children

This two-part book arose from the concerns of early years educators about Reconciliation and Intercultural education. In response to their concerns, preservice educators from the University of Southern Queensland created the resources included in Gems and Nuggets, published openly on USQ's Pressbooks site. Part 1 is called Reconciliation and it includes resources for helping educators and young children engage with the Reconciliation process. Part 2 is called Intercultural education and it offers teaching ideas and strategies for supporting culturally diverse learners. Each chapter highlights the importance of respecting, valuing and celebrating cultural diversity and the book, as a whole, offers a treasure chest of our preservice teachers' gems of wisdom and nuggets of resources to support and promote Reconciliation and Intercultural Education in the early childhood context.
WHAT IS THE SIGNIFICANCE OF CONDUCTING DIDACTIC GAMES IN TEACHING ATOMIC PHYSICS COURSES IN HIGHER EDUCATION

This article discusses the importance of the use of didactic games, which can be used in atomic physics lessons in higher education.
Library: Using the EBSCO Mobile App: Using the App

Make progress on your research anytime, anywhere with EBSCO’s mobile app! This guide shows you how to find, install and start using the free EBSCO mobile app.
TECHNOLOGICAL ADVANCEMENT AND CHILD-FRIENDLY EDUCATION IN NIGERIA: A POST-COVID REVIEW

Over the years, education has been a source of sustainable development in many countries in the world. Unfortunately, even though it is a potent weapon for measuring a country's development, it has suffered setbacks resulting in poor quality education. Quality Education is a significant prerequisite for developing every country's one of the United Nations' sustainable development goals. According to the United Nations, every child is entitled to quality and accessible education equipped with skills useful for their future development. For a child to enjoy quality education regarding the United Nations Sustainable Development Goals, technology is necessary. Technology in education has helped solve many problems, making life-learning processes enjoyable and exciting for every child to learn. The adoption of technology in education comes with many advantages embedded in improving communication and research. However, some challenges have affected easy access to learning, which has led to low participation in educational activities. This study embraces the Modernization theory, which talks about the description and explanation of transformation processes from a simple traditional society to a more complex modern society in all spheres of life. Hence, this paper seeks to examine the challenges and impacts of technological advancement in education in Nigeria.
The concept of “neo” and the novels of G. Rodenbach: between romanticism and symbolism

Various forms of transition in literature and art of the turn of 19th and 20th centuries havent been explored enough. The use of the concept of neo allows to clarify the ideas of neo-romanticism that have developed in modern science. The article analyzes the novel heritage of the Belgian writer Rodenbach as a transitional phenomenon that brings together the writer's tetralogy with romanticism, Parnassus and symbolist French poetry; as well as phenomenon that organically includes Belgian literature in the European space of intertextuality. It is proved that addressing the problems of art, the artist-creator, the beautiful soul, connects Rodenbach with the traditions of Yens romanticism, at a new stage of development of literature generates a transformation of the myth of romanticism. The ideal of art is not subject to devaluation, but the artist, who lives in society, always fails. Indulging in earthly passion, coming into conflict with society and himself, he doesnt keep faith in his beliefs. Real life creates illusions and self-deception, leading the character to disaster. Rodenbach uses a romantic model of mythologization, saturating it with symbolic allusions and signs, on the eve of modernism creates a neo-romantic novel synthesis.
LibGuides: Missouri A&OER Symposium: Sponsors

All the information attendees need for the March 2021 Missouri Affordable & Open Educational Resources Symposium.
18 Commonsense Reasoning

One of the deepest problems in cognitive science is understanding how commonsense reasoning works. It has received a great deal of attention in AI (e.g., Davis, 1990; Mueller, 2014) but surprisingly little in other areas of cognitive science. We reason about the everyday physical, social, and mental worlds rapidly, with reasonable accuracy, across a breathtakingly broad range of situations. Just think about cooking for a moment. Cooking requires making plans and predictions about the physical world, using causal reasoning and perception. Where can I set this bowl down on a crowded countertop? Could I add another cup of water to its contents? Is it safe to go check something in the next room while the soup is cooking? The picture I have painted so far argues that qualitative representations are central in such reasoning. The ontologies developed by qualitative dynamics provide the causal theories that enable us to reason about the processes and events that will happen as a consequence of our actions over situations framed in part by qualitative spatial representations derived via perception. Much of this reasoning, I have argued, occurs via within-domain analogical reasoning over qualitative representations. Experience thus plays a central role in common sense. Some first-principles reasoning does occur: a situation might require us to combine influences in novel ways, for example, or to reason about situations for which we have no close analog. Some things are better thought through than experienced—for example, what happens if a running blender falls into the sink or someone tries cooking a hard-boiled egg in a microwave oven?
Strategic evaluation of deep neural networks in board games

Djuptauganet hafa farið fram ur vaentingum a morgum sviðum, þau geta framkallað oflugar og nakvaemar spar um raunvoruleikann. Þetta mun verða oflugt tol i framtiðinni og við munum þurfa aðferðir til að geta rýnt i þessar spar til að styrkja traust okkar a þeim. Þessi ritgerð skoðar hvaða herkaensku aðferðir djuptauganet sem spilar leikinn Breakthrough nýtir ser til að taka akvarðanir. Við utskýrum ferlið að smiða tauganet sem getur nað arangri i borðspilum með þvi einungis að spila gegn sjalfu ser, an inngrips fra monnum. Við utskýrum ferlið að bua til likan til að skoða innri framsetningu tauganets a leikstoðu til að meta hvort tauganetið þekki eða nýtir ser aðferðir sem menn hafa notað til að spila leikinn vel. Þessar aðferðir eru bornar saman til að alykta hver se best og hver tauganetið notar mest. Við sýnum að tauganetið leggur aherslu a aðferðir sem eru taldar bestar fyrir leikinn Breakthrough. Að lokum skoðum við þjalfað tauganet með hop af auðveldum sem og floknum aðferðum til að rýna i hver herkaensku aðferð er mest notuð af tauganetinu.; Deep neural networks have exceeded expectations in many areas where they can generate accurate predictions of the real world. This is going to be a powerful tool for the future, and we require a method of examining them to understand why and how they come to a specific prediction to alleviate trust issues. This paper examines which strategies a deep neural network that plays the game Breakthrough uses to reach its predictions. We explain the process of creating a neural network that can achieve success in playing board games only from playing against itself, without any human input. We outline the process of creating a model to examine the internal representation of the neural network of the game state to evaluate whether it both recognizes and uses strategies applied by humans that play the game. These strategies are compared against each other to infer which is best, and which the neural network uses the most. We show that the neural network emphasizes strategies that are considered the most successful handcrafted strategies for the game Breakthrough.
“This is the first Russian monthly”: Book review: Gotovtseva, A.G. (2018). “This is the most useful for Russian society”: The “Monthly Essays” as a Russian integrative enlightenment project of the mid-18th century. Moscow, YASK Publ.

The review analyzes the monograph of A.G. Gotovtseva “This is the most useful thing for Russian society”: the “Monthly essays” as a Russian integration enlightenment project of the middle of the 18th century”. The review of the presents book examines a universal descriptive way of periodical, as well as the genesis of its internal plot. The review considers the journal’s evolution in the context of the historical and political process of the epoch, the creation of various headings, modification of the original concept of the journal and the composition of authors. The author of the present monograph emphasizes a new view of the role of G.F. Miller as one the major Russian historians of that period in the development of Russian science and journalism in the 18th century.
%%title%% (2019) %%sep%% %%sitename%%

Create and download LoL Mastery Level 7 avatar from this page. We will provide here a program which you can use to make an avatar for your mastery level ...
Mathematical and Economic Foundations of Bitcoin

Blockchain technology has a significant impact in multiple fields. Bitcoin was the first of its applications to rise to widespread attention. Due to its source code being publicly available (open source), it was followed quickly by a number of other cryptocurrencies as developers caught on to the opportunities it presented. The chief innovation introduced by Bitcoin was the ability to pay in a moderately secure fashion without third parties, such as banks.In this work we examine the mathematical and economic foundations upon which cryptocurrencies are built. We include a discussion of some cryptographic tools used in cryptocurrencies, such as hash functions that enable hiding information and committing to specific values; and the elliptic curve digital signature algorithm (ECDSA) used to implement Bitcoin's digital signature scheme.After covering the mathematical background we move on to the cryptocurrencies themselves. Bitcoin offers an immutable bookkeeping system based on blockchain technology, implemented using hash functions. To add transactions to the blockchain, miners calculate suitable hashes by trial and error. In order to change a transaction after it has been written onto the blockchain would require a practically infeasible amount of computation. Bitcoin transactions rely on ECDSA for authorisation. Having discussed the technical implementation of Bitcoin to some level of detail, we move on to describe two other cryptocurrencies, Zcash and Monero. These were developed to address some limitations in Bitcoin, especially when it comes to privacy considerations. We finish with a comparison of the cryptocurrencies introduced previously and a discussion of the relationship between cryptocurrencies and the society at large.
Searching Process Using Boyer Moore Algorithm in Digital Library

Reading helps to learn more vocabularies and their usages. People should read books to get knowledge. Nowadays, digital libraries are used to search for various books. If the internet connection is available, digital libraries can be accessed easily via computers, laptops, and mobile phones. Students and readers can search for the desired books from this digital library by typing sub-strings of a book title that matches with parts of the original book title. To be able to make such a searching process effectively, string searching algorithms can be applied. There are many sophisticated and efficient algorithms for string searching. In this paper, a Boyer Moore (BM) string-searching algorithm is applied to search the desired books effectively in the digital library. And then the BM algorithm is presented by comparing it with Horspool’s algorithm to prove the performance efficiency of the BM algorithm for the searching process.
Profit model for admission control and resource scheduling for optimum utilization of resources in cloud computing environment

Globalization has brought many changes in modern business world. Problems of enterprise-oriented software applications like distribution and configuration of resources presents challenge to the traditional software sales model. Cloud computing presents the solution for such problems. With the help of cloud-based model one can earn good return by making the QoS demands of their users (customers) satisfied. In order to fulfill the infrastructure demands (like network, storage, etc.) to their users, service providers have to maintain their own hardware or they lease it from the Iaa S providers. For maintaining their own hardware SaaS providers will have to incur an extra cost, but if taken on lease, zero maintenance cost involved. Moreover, if provider wants to optimize cost and gain customer satisfaction, they will have to satisfy their customers/users by maintaining service level objectives. This paper presents a model for resource allocation in such a way as to minimize cost and maximize profit by satisfying the service level needs of the customers. The model is designed to enable the service providers with an ability to cope with the changing needs of customers, mapping customer requests to infrastructure level parameters and better handling of heterogeneous VMs.
Multisensor drill core logging integrating XRF and SWIR sensors to support machine learning

Summary An innovative computer assisted drill core logging system has been developed based on the integration of a SWIR spectral imaging system and a systematic XRF analytical probe. The system has been trained on mineralisations from the Iberian Pyrite Belt. The use of deep learning algorithms allows to obtain consistent logging results
LibGuides: Instructional - Accessing e-Resources: Privacy

This guide describes how to use OpenAthens, a single sign-on solution for off-campus access to the Booher Library's electronic resources.
MEMORIZATION LEARNING OUTCOMES OF VOCATIONAL HIGHSCHOOL STUDENTS IN LEARNING BASIC PATTERNS

A learning strategy is needed to improve the ability of students. This study aims to determine theBasic Pattern learning outcomes which was taught by memorization learning models of 3Pematangsiantar Vocational High School students. As a population, the instrument used learningoutcomes tests, then analyzed by t test. The results of the analysis showed that learning outcomestaught by conventional learning showed average results (57.03), and learning outcomes were learnedusing a memorization learning model (72.03). Data distribution of learning outcomes by conventionallearning is normally distributed where 0.151 <0.157 and student learning outcomes data bymemorization learning models were normally distributed where 0.079 <0.151 and homogeneousvariance data for f arithmetic 1.71 <f table 1.82. It was concluded that the results of memorizationlearning model were better than conventional learning where the test results showed a value of t -4,761 <ttable 1.67. So it is proven that there is no effect of student learning outcomes taught usingmemorization learning models and students who are taught using conventional learning. This meansthat the use of learning learning memorization models can be used as an alternative learning inschools
Learning Deeply Shared Filter Bases for Efficient ConvNets

Recently, inspired by repetitive block structure of modern ConvNets, such as ResNets, parameter-sharing among repetitive convolution layers has been proposed to reduce the size of parameters. However, naive sharing of convolution filters poses many challenges such as overfitting and vanishing/exploding gradients, resulting in worse performance than non-shared counterpart models. Furthermore, sharing parameters often increases computational complexity due to additional operations for re-parameterization. In this work, we propose an efficient parameter-sharing structure and an effective training mechanism of deeply shared parameters. In the proposed ConvNet architecture, convolution layers are decomposed into a filter basis, that can be shared recursively, and layer-specific parts. We conjecture that a shared filter basis combined with a small amount of layer-specific parameters can retain, or further enhance, the representation power of individual layers, if a proper training method is applied. We show both theoretically and empirically that potential vanishing/exploding gradients problems can be mitigated by enforcing orthogonality to the shared filter bases. Experimental results demonstrate that our scheme effectively reduces redundancy by saving up to 63.8% of parameters while consistently outperforming non-shared counterpart networks even when a filter basis is deeply shared by up to 10 repetitive convolution layers.
Data management in community seed banks. DIVERSIFOOD Innovation factsheet #19

There is a remarkable range of data storage, data organisation and rules for data management in community seed banks. We investigated this diversity in five civil society organisations that are partners of DIVERSIFOOD.