Reviewerly/exHarmony huggingface dataset:
Performance Evaluation of Active Queue Management in Fat Tree Architecture on Data Center Network

In the age of the rapid growth of Internet technology, people are connecting to the0020network continuously. Request is made in seconds, resulting in congestion in the data center network. This makes the researcher tried to make a breakthrough in order to reduce the network latency. One of many proposals is the use of the active queue management (AQM). Active queue management focuses on dropping the network packets inside a buffer to reduce network congestion. This method is capable to dropping the packets according to probabilistic manner. In this paper, we evaluate different AQM algorithms to the Data Center Network (DCN) using fat tree architecture. We conducted some experiments using NS-3 to evaluate the network performance of different AQM algorithms. The simulation is done using a research based tool for computer network design, NS- software on Ubuntu Operating Systems. NetAnim, the visualization and monitoring tool for network is used for the evaluation. Throughput, packet drop, and delay are measured and compared. Best throughput is gained when ARED AQM is used which is 498.5 kpbs. It is 37 kbps higher than NLRED and 59 kbps higher than those of RED. In terms of packet drop, the ARED shows the lowest packet drop of 2230 packet drop. ARED also has the lowest delay, 0.132 second, which is slightly different from NLRED with 0.133 second delay, whereas RED's delay is 0.177 second.
Contributions to Directional Statistics Based Clustering Methods

Author(s): Wainwright, Brian | Advisor(s): Jammalamadaka, Sreenivasa R | Abstract: Statistical tools like the finite mixture models and model-based clustering have been used extensively in many fields such as natural language processing and genomic research to inves- tigate everything from copyright infringement to unraveling the mysteries of the evolutionary process. In model-based clustering, the samples are assumed to be realizations of a mixture distribution consisting of one or more mixture components, and the model attempts to discern what this original model is, given the observed data. In our investigation we explore directional distributions on the circle, the sphere, and the hypersphere, where the component distributions are themselves respectively the von Mises distributions in 2-dimensions, the von Mises-Fisher distributions in 3-dimensions, and ?-dimensional von Mises-Fisher distributions for large ?. In each case, the observations lie on the circle, the unit-sphere, or the hypersphere ??−1 embedded in R?, due to the inherent structure of the data, or by normalizing the curves. We look specifically at clustering curves around the unit circle ?1, treating them first as mixture distributions, and in an alternate approach, as functional data that can be explored via their Fourier coefficients. We also investigate clustering high-dimensional, extremely sparse textual data, by looking at twitter data from the day of the 2016 United States presidential election as document vectors on the unit hypersphere. Finally, we introduce and discuss a broad family of spherical distributions that we call the “Generalized Fisher-Bingham family, and present details of a software package that we developed to simulate and visualize members of this family.
The Art of Elasticity and Scalability of Modern Cloud Computing World for Automation

This paper provides the clients with more valuable guidelines to choose the appropriate cloud computing models based on elasticity and autoscaling features of cloud-based on business & information technology’s (IT) good proven patterns, best practices and along with my research results. It also highlights which cloud solution or platform fits for the organizations, especially for automating the business processes, to reduce the human interventions, and to minimize errors. It also explains why do we need to move from the existing on-premise computer systems into the cloud-based environments, Moreover describes various types of cloud environments currently available, and the advantages of cloud migration and compares the practical results of on-premise vs cloud computing environment. These articulated features of elasticity and scalability benefits motivated me to create this presentation. In fact the test and experimental results proved us to adopt the hybrid cloud model with flexible elasticity and auto-scaling features for organizations to be more cost-effective and would aid for successful operations.
The Effect of Knowledge Management Systems on Measuring Success Indicators for Saudi Arabia 2030

Vision 2030 is designed to place the Kingdom of Saudi Arabia (KSA) as a trading and financial hub in the Middle East. Ninety-six strategic objectives are framed for Vision 2010. Whilst these objectives are very inspiring, challenges are seen in integrating them under a single unifying framework. Unless the diverse objectives are integrated, knowledge and learning of team members are brought on a common platform to measure the success indicators, achieving the vision would be difficult. Objective of the paper is to develop a KM model that will help to measure the success indicators of Vision 2030. A literature review helped to understand the barriers, processes, and methodology of KM frameworks. The findings indicate that Vision 2030 is wide in scope with 96 loosely connected strategic objectives. An overarching framework that links all these objectives and places them on a common platform is not evident. These inputs were used to design the KM Vision 2030 model that links all the objectives and helps to gather metrics from the objectives, and measure the success of the project. Some of the metrics that can be considered are linking objectives, milestone achievement, adhering to schedule and budget, economic and social impact on people and businesses, progress in positioning KSA as the leader of Middle East, and others. Some of these measures are qualitative, whilst others are quantitative, implying that a multimodal data collection and analysis method is needed. The model suggests institution of Knowledge Champions, Communities of Practice, big data analytics, knowledge assets development and sharing, and brings all the objectives on a transparent and usable platform. A pilot study in the form of a semi-structured interview and survey was administered to five experts in the field of KM and IT systems. Their findings indicate that big data analytics can play a major role in decision-making and in measuring the project success. The findings also speak of the need to connect the strategic objectives. Recommendations are made to refine the model.
AANMF: Attribute-Aware Attentional Neural Matrix Factorization

Matrix Factorization (MF) is one of the most intuitive and effective methods in the Recommendation System domain. It projects sparse (user, item) interactions into dense feature products which endues strong generality to the MF model. To leverage this interaction, recent works use auxiliary information of users and items. Despite effectiveness, irrationality still exists among these methods, since almost all of them simply add the feature of auxiliary information in dense latent space to the feature of the user or item. In this work, we propose a novel model named AANMF, short for Attribute-aware Attentional Neural Matrix Factorization. AANMF combines two main parts, namely, neural-network-based factorization architecture for modeling inner product and attention-mechanism-based attribute processing cell for attribute handling. Extensive experiments on two real-world data sets demonstrate the robust and stronger performance of our model. Notably, we show that our model can deal with the attributes of user or item more reasonably. Our implementation of AANMF is publicly available at https://github.com/Holy-Shine/AANMF.
ANALISIS ATTITUDE MAHASISWA HOSPITALITY SEKOLAH TINGGI PARIWISATA MATARAM TERHADAP IMPLEMENTASI COMPUTER-ASSISTED LANGUAGE LEARNING

The aim of this study is to investigate the attitudes of students of hospitality major in STP Mataram towards Computer-assisted Language Learning. This study specifically examines how students' attitudes at the Mataram Tourism College towards the implementation of Computer-assisted Language Learning in learning English and the factors underlying their attitudes. The subjects in this study were Diploma students. The sample of this study were students of the Mataram Tourism College in Academic year 2018/2019 of Diploma Hospitality program on fourth semester. A quantitative approach using statistical analysis that will measure the results of the questionnaire instrument and a descriptive qualitative approach for observation and interviews. The data were analyzed using statistical calculation methods with the help of the SPSS program. In general, based on statistical analysis of data shows that respondents tend to show a positive attitude towards the use of CALL in foreign language learning
Dive into Deep Learning for Natural Language Processing

Deep learning has become the dominant approach to NLP problems, especially when applied on large scale corpora. Recent progress on unsupervised pre-training techniques such as BERT, ELMo, GPT-2, and language modeling in general, when applied on large corpora, is shown to be effective in improving a wide variety of downstream tasks. These techniques push the limits of available hardware, requiring specialized frameworks optimized for GPU, ASIC, and distributed cloud-based training.A few complexities pose challenges to scale these models and algorithms effectively. Compared to other areas where deep learning is applied, these NLP models contain a variety of moving parts: text normalization and tokenization, word representation at subword-level and word-level, variable-length models such as RNN and attention, and sequential decoder based on beam search, among others.In this hands-on tutorial, we take a closer look at the challenges from these complexities and see how with proper tooling with Apache MXNet and GluonNLP, we can overcome these challenges and achieve state-of-the-art results for real-world problems. GluonNLP is a powerful new toolkit that combines MXNet’s speed, the flexibility of Gluon, and an extensive new library automating the most laborious aspects of deep learning for NLP.
Breast Cancer Classification Using Discrete Wavelet Transformation and Deep Learning

Background: One of the most prevalent diseases these days is breast cancer which is common amongst women. This sickness has been increasing to an alarming rate due to the lack of accurate diagnoses. Early and accurate detection is one of the safest ways to cure a breast cancer patient. Objectives: The objective of this study was to provide a more effective way to accurately classify a cancer sample; whether is benign or malignant. Methods: The classification model is based on the data collected from the UCI machine learning repository acquired from the Wisconsin hospital called Wisconsin Breast Cancer Data (WBCD). In this study, we preprocessed the dataset using Discrete Wavelet Transform (DWT) and then tested the efficiency of Deep Learning (DL) for breast cancer classification. The model was developed using a feed-forward neural network and the result was compared with the observed values. Results: The result of the experiment proved the effectiveness of the proposed classification technique. The new technique accomplished 98.90% accuracy for classifying breast cancer. Conclusions: The result from the experiment shows the importance of data preprocessing and the efficiency of the neural network over other classification algorithms.
Quality Metadata and The National Climate Assessment

This presentation details how the National Climate Assessment (NCA), by way of compliance with federal mandates for Information Quality (data transparency and accessibility), as a Highly Influential Scientific Assessment (HISA) (reproducible findings), and Foundations for Evidence-Based Policymaking, provides quality metadata for decision and policy-makers, and the general public alike. Details on our tools and processes are explained, along with how the NCA anticipates meeting requirements of open licensing and software documentation in the upcoming 5th National Climate Assessment. This presentation was given in January 2020 at the Earth Science Information Partners (ESIP) Winter Meeting in Bethesda, MD.
Gestão de informação/conhecimento em Ciência da Informação: perspetivas sobre os termos e proposta de aplicação teórico-prática

At the end of the second decade of the twenty-first century, it is generally accepted that Information and Knowledge are strategic and transformative resources of the society.In this context, this study aims to analyse the binomial "Information Management" and "Knowledge Management", within the framework of Information Science (IS) and subsequently proposes the appropriate theoretical and practical application.As methodology, a qualitative approach of exploratory nature was adopted, particularly focusing on the review of the varied literature that has addressed this topic.From the distinction between "tacit knowledge" and "explicit knowledge" established by Michael Polanyi and Tom Wilson, several perspectives on the lexical question (the terms) are emphasized in their close relation to the conceptual aspects they correspond to.The analysis of the scientific production on this subject is also made, emphasizing its application in the respective scientific area of research and in the work that has been developed, helping to clarify what should be the action of the information professional.The results allow us to infer the urgency of an integrated vision of the management of information or the management of explicit knowledge in any organizational context, independent of trends or partial approaches and, therefore, reductionist of the different disciplines or scientific areas.
Pseudonym Pairs: A foundation for proof-of-personhood in the web 3.0 jurisdiction

ABSTRACT: Pseudonym Pairs is a dApp for global proof-of-personhood, through monthly pseudonym events that last 20 minutes, where every single person on Earth is randomly paired together with another person, 1-on-1, to verify that the other is a person, in a pseudo-anonymous context. The events provide NYM tokens, global personhood tokens, untraceable from month to month and disposable, a sort of “temporary access tokens” similar to festival bracelets. The proof-of-personhood is that you are with the same person for the whole event.
ARCLib – development of open source solution for long-term preservation

This short presentation will inform about the Czech ARCLib project. One of the main goals of the project is the development of an open-source solution for a bit-level and logical preservation of digital documents, respecting the national and international standards as well as the needs of all types of libraries in the Czech Republic. The mission of the ARCLib project lies, among others, in creating a solution that will allow institutions to implement all of the OAIS functional modules and entities, considering institutions' information model. The architecture is planned as open and modular and the final product will be able to ingest, validate and store data from a majority of software products used for creating, disseminating and archiving libraries' digital and digitized data in the Czech Republic. The solution is connected to Fedora commons repository and Archivematica, as far as it counts with creation of submission information packages using these software solutions.
Conceptual basis of description for the information security management system architecture

The problems of information security management system development in the organization are considered. Conceptual bases of its architecture description are presented. Basic concepts regarding the information security management system architecture are disclosed through its context. The context of the architecture description is represented by the main elements. These include: parties involved, purpose, information security management system, environment, architecture, architecture descriptions. The parties involved are interested in the system. Such interest is driven by the need to maintain the confidentiality, integrity and accessibility of the organization's information assets. In view of this, the aim is to develop a defined system that is focused on providing information security with acceptable risk. The organization is interpreted as the environment of the functioning of the information security management system. It determines its effects during its life cycle, taking into account the interaction of the system with the environment. The architecture reflects what is significant to the information security management system. Whereas to describe the architecture of a designated system, its description is used. The information security management system architecture is described by an architectural view. It presents architecture from the point of view. This view is characterized by two aspects: a structural representation of the interests of the parties involved; structural representation of architecture features. The architectural representation of the information security management system is reflected by the architecture model. This model describes the features of the designated system architecture, taking into account the interests of the parties involved. Architecture features are reflected by the type of model through which the model is influenced. The relationships between the architectural description elements are shown in the links. Their use makes it possible to represent the attitude of architecture to the interest within its description. Thus, this conceptual description of the information security management system architecture will allow both to develop and justify its development taking into account the interests of the organization and the parties involved.
CONCEPTUAL MODEL OF DIDACTIC SYSTEM OF GRAPHIC-ART PREPARATION FOR FUTURE TEACHERS OF THE FINE ART

The article reveals the essence of the content of the conceptual model of artistic and graphic preparation of future teachers of the fine arts. Based on a review of scientific studies on this issue are marked new conceptual ideas, pedagogical views of scientists on the theory and practice of art education of students in pedagogical universities. Sub-theoretical construct performs scientific and educational potential of art pedagogy and its component - art didactics. Construct model of didactic conditions of artistic and graphic preparation of future teachers of fine arts in the article is viewed as structural and logical system of artistic and educational interaction between teacher and students.&#x0D; Regarding the nature of cognitive and practical ways of graphic activity of students, the author designed a didactic system that is purposeful on the decision of educational problems of vocational training in the field of graphic arts. Designated article mechanisms of cognitive and creative activity of students in the field of graphic art are due to the basic psycho-pedagogical and didactic regularities of the process of "cognition - teaching – learning - creativity".&#x0D; A priority area in the contemporary socio-economic, spiritual and cultural development of Ukraine, which is part of the European democratic community, is education. Areas of the state policy in the sphere of education are defined by the Constitution of Ukraine Logical-semantic content of the conceptual model of artistic and graphic preparation of future teachers of fine arts combines multiple components in a designated process expedient didactic design with its methodological features.
ELMo embeddings models for seven languages

ELMo language model (https://github.com/allenai/bilm-tf) used to produce contextual word embeddings, trained on large monolingual corpora for 7 languages: Slovenian, Croatian, Finnish, Estonian, Latvian, Lithuanian and Swedish. Each language's model was trained for approximately 10 epochs. Corpora sizes used in training range from over 270 M tokens in Latvian to almost 2 B tokens in Croatian. About 1 million most common tokens were provided as vocabulary during the training for each language model. The model can also infer OOV words, since the neural network input is on the character level.Each model is in its own .tar.gz archive, consisting of two files: pytorch weights (.hdf5) and options (.json). Both are needed for model inference, using allennlp (https://github.com/allenai/allennlp/blob/master/tutorials/how_to/elmo.md) python library.
RANCANG BANGUN E-COMMERCE BERBASIS WEB RESPONSIVE DAN MOBILE ANDROID PADA UMKM AIKORI NATURAL LEATHER BAG SEMARANG SEBAGAI MEDIA PROMOSI DAN INFORMASI

The development of the internet in Indonesia is one factor in improving the economy in Indonesia. UMKM Aikori Natural Leather Bag Semarang is a micro company engaged in the creative industry that produces handicraft items made from cow leather. Since its establishment in 2011, the company has only introduced its leather craft products offline. So many customers find it difficult to get information about the latest product collections from UMKM Aikori Natural Leather Bag Semarang. To overcome this problem a web was created using one of the CMS (Content Management System) namely Wordpress which can expand market share and also facilitate UMKM Aikori Natural Leather Bag Semarang in managing product sales. The purpose of this research is to build online-based sales media using Wordpress content management system so that it can expand market share that cannot be reached by the previous system. The method used in this research is the System Development Life Cycle, namely Waterfall, where there are several stages, namely requirements definition, system and software design, implementation and until testing, system testing, operation and maintenance. The results of this research show that a good web can contain the latest information so that it can be accessed by customers anytime and anywhere.
Readability of Reading Texts in Student’s Handbook at The Ninth Grade of SMP Negeri 1 Telukdalam

Readability is an indicator that used to describe whether a text more or less available to the reader level. This study attempts to find out the appropriateness of the English reading texts in terms of the readability level for the target students. This study is designed by using descriptive qualitative method. The main data used is student’s handbook. The texts were consists of 7 descriptive texts and 1 narrative text and then those data were collected by using documentary technique. In calculating readability level, the researcher employed the Flesch readability formula. The results show that the average readability level of eight reading texts was at level seven grade student by showing the average of the percentage score was 72, 96%. Then, from the eight reading texts were categorized into four levels, namely: there are 2 texts of Easy level, Fairly Easy as many as 3 texts, Standard for 1 texts, and Fairly Difficult for 2 texts. Based on the research results, it can be concluded that those texts were disagree for the target students. Thus, for teachers, English Teacher particularly, should be wise in choosing a textbook as material for teaching students must be match with their capabilities level.