Reviewerly/exHarmony huggingface dataset:
REDUKSI MISPREPSI PULMONARY EMBOLISM (PE) PADA CT-SCAN ANGIOGRAFI PULMONARY

Background: Pulmonary Embolism (PE) is the third highest cause of death in cardiovascular. Right ventricular failure usually occurs within the first few hours, leading to the occurrence of right ventricular dysfunction (RVD). Computed tomography pulmonary angiography (CTPA) is an imaging technique that is the gold standard in evaluating patients with suspected PE because of their high sensitivity and specificity. The presentation of Pulmonary CTA images in PE needs to be interpreted correctly so that there is no loss of diagnosis by radiologists and cardiologists. This article aims to find out how to minimize the presence of mispreseption in findings of PE cases using CT-Scan modalities with the CT Pulmonary Angiography protocol.&#x0D; Methods: The type of research in this mini research is qualitative research with an experimental approach with measurements on the pulmonary arteries that have emboli, which are aimed at knowing the type and evaluating existing parameters to reduce misdiagnosis in PE patients.&#x0D; Results: The results of identifying the type of emboli using ROI (Region Of Interestand) measurements of the right and left ventricles can be seen that the patient has acute pulmonary embolism. Precise parameter settings play a role in producing informative diagnostic images of Pulmonary CTA.&#x0D; Conclusion: To obtain informative diagnostic images in cases of pulmonary embolism, it is necessary to pay attention in optimizing the procedures and parameters of pulmonary Angiography CT so that there is no misdiagnosis in patients.
LibGuides: Library Orientation: Books

The purpose of this guide is to introduce you to services and resources available at your Library.
LibGuides: Streaming Video Resources: Documentary

This guide will provide students, faculty, and staff with a number of streaming platforms available through the University of Illinois Libraries, as well as free streaming resources. This page provides information about streaming documentaries.
Human Action Recognition using Prominent Camera

Human action recognition has undoubtedly been under research for a long time. The reason being its vast applications such as visual surveillance, security, video retrieval, human interaction with machine/robot in the entertainment sector, content-based video compression, and many more. Multiple cameras are used to overcome human action recognition challenges such as occlusion and variation in viewpoint. The use of multiple cameras overloads the system with a large amount of data, thus a good recognition rate is achieved with cost (in terms of both computation and data) as the overhead. In this research, we propose a methodology to improve the action recognition rate by using a single camera from multiple camera environments. We applied a modified bag-of-visual-words based action recognition method with the Radial Basis Function-Support Vector Machine (RBF-SVM) as a classifier. Our experiment on a standard and publicly available dataset with multiple cameras shows an improved recognition rate compared to other state-of-the-art methods.
LibGuides: Your Guide to OU Libraries: Start Your Research

New to OU? Never used OU Libraries before? This guide will introduce you to must-have resources and services to help get you started. Use the catalog, access databases and journals, find books, and track your sources.
The GlobalWordNet Formats: Updates for 2020

The Global Wordnet Formats have been introduced to enable wordnets to have a common representation that can be integrated through the Global WordNet Grid. As a result of their adoption, a number of shortcomings of the format were identified, and in this paper we describe the extensions to the formats that address these issues. These include: ordering of senses, dependencies between wordnets, pronunciation, syntactic modelling, relations, sense keys, metadata and RDF support. Furthermore, we provide some perspectives on how these changes help in the integration of wordnets.
Towards a Linking between WordNet and Wikidata.

WordNet is the most widely used lexical resource for English, while Wikidata is one of the largest knowledge graphs of entity and concepts available. While, there is a clear difference in the focus of these two resources, there is also a significant overlap and as such a complete linking of these resources would have many uses. We propose the development of such a linking, first by means of the hapax legomenon links and secondly by the use of natural language processing techniques. We show that these can be done with high accuracy but that human validation is still necessary. This has resulted in over 9,000 links being added between these two resources.
Key Blockchain Use Cases

Blockchain is an emerging technology that can radically improve transactions security at banking, supply chain, and other transaction networks. It's estimated that Blockchain will generate $3.1 trillion in new business value by 2030. Essentially, it provides the basis for a dynamic distributed ledger that can be applied to save time when recording transactions between parties, remove costs associated with intermediaries, and reduce risks of fraud and tampering. This book explores the fundamentals and applications of Blockchain technology. Readers will learn about the decentralized peer-to-peer network, distributed ledger, and the trust model that defines Blockchain technology. They will also be introduced to the basic components of Blockchain (transaction, block, block header, and the chain), its operations (hashing, verification, validation, and consensus model), underlying algorithms, and essentials of trust (hard fork and soft fork). Private and public Blockchain networks similar to Bitcoin and Ethereum will be introduced, as will concepts of Smart Contracts, Proof of Work and Proof of Stack, and cryptocurrency including Facebook's Libra will be elucidated. Also, the book will address the relationship between Blockchain technology, Internet of Things (IoT), Artificial Intelligence (AI), Cybersecurity, Digital Transformation and Quantum Computing. Readers will understand the inner workings and applications of this disruptive technology and its potential impact on all aspects of the business world and society. A look at the future trends of Blockchain Technology will be presented in the book.
Dongeng sebagai Media Pembelajaran Bahasa dan Sastra Indonesia di SD/MI

Fairy tales or folktale are part of the story of rayat (folklore). Every region in Indonesia has many stories of folklore and fairy tales that contain aspects of culture, education, character and high moral values. In order to safeguard and inherit the value of local wisdom and the value of education to the next generation, fairy tales are very feasible to be used as a medium for learning Indonesian language and literature at the basic education level, especially in Elementary Schools (SD) and Madrasah Ibtidaiyah (MI). This article aims to discuss and explain: (1) The potential for diversity of tales as part of folklore spread in various places is the socio-cultural wealth of the community. (2). Fairy tales can be used as a medium for learning Indonesian language and literature in elementary and MI basic education. (3) Fairy tales can be a means of improving literacy culture among elementary and MI students.
Towards Achieving a Reusability Framework for Service and Cloud Computing: A Visionary Tale

Software reuse has been identified as one of the solutions towards solving the software crisis and achieving productivity since 1969. Since then it has been a popular research topic in software engineering and in industry. There have been significant achievements in terms of approaches to reuse such as code reuse, generative reuse (automatic code generation) design reuse with components, packages, and patterns, knowledge reuse, process reuse, and reuse of best practices. There have been advances in software development tools and environments. However, reuse practices have not been so successful as expected due lack of not-invented-here syndrome and other cultural factors. Since the emergence of service computing and cloud computing, reuse has now more explicit than ever before as a service allows autonomic composition and distribution of services on-the-fly. This leads us to consider developing techniques, methods, frameworks, and tools for reusability framework that can be ubiquitously embedded in the cloud environment. A great welcome to re-birth of service level reuse (reuse of cloud services, web services, and microservices). This visionary talk will also provide key reuse characteristics of traditional approaches such as class, package, and component vs service reuse characteristics such as scalability and elasticity which are the founding factors for achieving service level reuse. This visionary talk will provide a number of techniques, overview of a developed method of the Software Engineering Framework for Service and Cloud Computing (SEF-SCC), a service-oriented reference architecture, and a reusability framework with techniques, design methods, and a visionary tool towards achieving a reusability framework for the future generation of cloud computing systems and applications.
Causal model design and analysis of environmental criteria in the steel industry with fuzzy cognitive mapping approach (FCM)

Environmental pollution is a serious threats to global warming and human health, and most industries, especially the steel industry, are sources of environmental pollution, so reducing and controlling pollution from this industry has become particularly important in recent studies. Therefore, the purpose of this study is to identify the environmental criteria of Yazd steel industry in order to provide a causal model and analyze the relationships between them. In this study, first, by studying the thematic literature using the content analysis approach, the criteria that had a very low number of repetitions were removed from the list and interviewed with steel industry experts to localize and identify more practical criteria and 36 final environmental criteria were selected. A questionnaire was used to collect data and its validity and reliability were confirmed. Finally, a fuzzy cognitive mapping approach has been used to investigate the intensity of relationships and how the criteria affect and model design, and each of the criteria has been analyzed within the framework of this model. Accordingly, the criteria of green marketing, environmental design and environmental performance have the most influentiality, respectively, and the criteria of green marketing, green warehouse and building and environmental performance have the most impressionability in this industry, respectively.
Consulting support for the activities of the methodological service of a pre-school educational institution

The article presents the theoretical basis of consulting in education. The authors have summarized the material that made it possible to identify consulting support as an innovative technology within the framework of the activity of the methodological service of a pre-school educational institution. depending on the subject of the consulting. The main approaches for advising teachers, specialists and leaders of pre-school education in the process of modernizing educational infrastructure are being considered. The factors influencing the development of educational consulting in the DPI are structured and divided into groups. The specificity of the process of implementing consulting support in the activities of the DOW methodological service is described.
Lirica e poesia

It was Leopardi who produced the thesis that «Lyric can be called the height the culmination the summit of poetry», and as such «the summit of human language» and «of the three main genres of poetry, the only one that really remains for the moderns». This primacy of lyric poetry rests in its ability to guard, better than epic and dramatic poetry, the linguistic institution of the world, the truth of being in the world as truth of word (Martin Heidegger). Lyrical expression as feeling and contemplation of oneself and one's being in the world expresses, each time, individually, the universal human, the original proclivity, in the word, in the ego, on the world. Lyric as the summit of poetry is like a summit reached. Like consciousness (in the evolutionary thesis of Julian Jaynes), poetry also has a story that takes place in the lyric phenomenon.
Multi-agent autonomous battle management using deep neuroevolution

Next-generation autonomous vehicles will require a level of team coordination that cannot be achieved using traditional Artificial Intelligence (AI) planning algorithms or Machine Learning (ML) algorithms alone. We present a method for controlling teams of military aircraft in air battle applications by using a novel combination of deep neuroevolution with an allocation-based task assignment algorithm. We describe the neuroevolution techniques that enable a deep neural network to evolve an effective policy, including a novel mutation operator that enhances the stability of the evolution process. We also compare this new method to policy gradient Reinforcement Learning (RL) techniques that we have utilized in previous work, and explain why neuroevolution presents several benefits in this particular application domain. The key analytical result is that neuroevolution makes it easier to select long sequences of actions following a consistent pattern, such as a continuous turning maneuver that occurs frequently in air engagements. We additionally describe multiple ways in which this neuroevolution approach can be integrated with allocation algorithms such as the Kuhn- Munkres Hungarian algorithm. We explain why gradient-free methods are particularly amenable to this hybrid approach and open up exciting new algorithmic possibilities. Since neuroevolution requires thousands of training episodes, we also describe an asynchronous parallelization scheme that yields order of magnitude speedup by evaluating multiple individuals from the evolving population simultaneously. Our deep neuroevolution approach out-performs human-programmed AI opponents with a win rate greater than 80% in multi-agent Beyond Visual Range air engagement simulations developed using AFSIM.<sup>&dagger;</sup>
Sistem Informasi Pengarsipan Dokumen SMA N Kerjo

Increasing technological developments can spur human resources to do work by utilizing technology, especially in the administration section as information facilitators who are tasked with updating any archiving information in order to create good service. Archival management at SMA Negeri Kerjo still uses the manual method, where the administration section still writes data on incoming letters, position letters and outgoing letters in the agenda book, and document data such as incoming letters, outgoing letters, and exam questions are still not organized, resulting in lost document data. The purpose of this research is to produce a data management system at SMA Negeri Kerjo from a manual system to a technology-based system.The method used is to use the Waterfall model System Development Life Cycle (SDLC) method. In developing this system, some software is needed, namely the Windows 10 Operating System, MySql, Visual Studio Code, PHP, Javascript, and CodeIgniter Framework and the hardware used is a laptop (Intel Core i5 8250U up to 3.40 GHz, 4GB Memory). The method used is to use the Waterfall model System Development Life Cycle (SDLC) method. In developing this system, some software is needed, namely the Windows 10 Operating System, MySql, Visual Studio Code, PHP, Javascript, and CodeIgniter Framework and the hardware used is a laptop (Intel Core i5 8250U up to 3.40 GHz, 4GB Memory, 1TB SATA HDD 5400RPM). The result of this research is that the system can manage incoming mail, outgoing letters, position letters, and technology-based exam questions by using black-box testing, so as to produce a system that can run according to its functionality.Keywords: Document archives, Codeigniter, PHP, Information Systems
OPINION MINING OF TWITTER DATA USING MACHINE LEARNING

People express their opinions through social media sites like Twitter, Instagram, and Facebook. Tweets can be used to analyze opinions expressed towards various keywords, which can be anything from the names of products, companies or famous people. Consumers can utilize the insights of analyzed opinions and companies that want to monitor the public sentiment of their brands or any other situation where data on public opinions can be useful. Training data is abundantly available and can be obtained through automated means, we’ve obtained our data from twitter. The goal of our project is to implement the most effective algorithms and compare their accuracy. We use machine learning techniques like Max entropy, Naive Bayes, SVM and DCNN (Deep Convolution Neural Network). The data is analyzed for the presence of emoticons and keywords that either signify positive or negative expression towards the query term by Max, NB, and SVM methods. In DCNN, latent contextual semantics relationships and co-occurrence of statistical characteristics are used to obtain word embeddings between the words. Finally, word embedding is combined with n-grams and a polarity score is issued for the tweets. Our research focuses on comparing the accuracy of these algorithms to determine which are the most effective and accurate.
Authenticators and Recovery Codes

In this chapter, I describe how ASP.NET Core Identity supports authenticators for two-factor authentication and how to provide users with recovery codes for emergency access when their second factor isn’t available. Table 21-1 puts these features in context.
Inspiration or infringement

This chapter builds on the previous two chapters to summarise and apply what copyright infringement is and what that actually means in relation to your own creative process. This chapter clarifies the difference between taking inspiration and copying; thereby enabling you to understand when it is okay to draw from other’s work and when it would constitute copyright infringement. First it sets the context of inspiration by considering what is creativity. Then it summarises what is and what is not copying for the purpose of copyright infringement, including when someone copies unconsciously - i.e. not on purpose.
TeMoTopic: Temporal Mosaic Visualisation of Topic Distribution, Keywords, and Context

In this paper we present TeMoTopic, a visualization component for temporal exploration of topics in text corpora. TeMoTopic uses the temporal mosaic metaphor to present topics as a timeline of stacked bars along with related keywords for each topic. The visualization serves as an overview of the temporal distribution of topics, along with the keyword contents of the topics, which collectively support detail-on-demand interactions with the source text of the corpora. Through these interactions and the use of keyword highlighting, the content related to each topic and its change over time can be explored.
Digitalizacija nastave u školskom obrazovanju

The paper presents a research on the extent to which the digitalization of teaching has so far helped to achieve better results than before with students and how much it has helped students themselves in learning and mastering school materials. Teachers, although aware of the positive and negative aspects of using digital technology in teaching, still use it sparingly and rely more on older teaching methods. Teachers believe that textbooks are enough for children to master the material and that due to the dynamics of the teaching process itself, it is desirable to occasionally and moderately use digital tools in teaching. They find that often the digital tools themselves distract from the content. For students, on the other hand, the use of technology in teaching creates additional interest, fun and dynamism. They are more motivated when using digital technology in teaching, and they are more independent in researching content that is more accessible to them than ever.
A New Approach for Movie Recommender System using K-means Clustering and PCA

Recommendation systems are refining mechanism to envisagethe ratings for itemsand users, to recommend likes mainly from the big data. Our proposed recommendationsystem gives a mechanism to users to classify with the same interest. This recommendersystem becomes core to recommend the e-commerce and various websites applications basedon similar likes. This central idea of our work is to develop movie recommender system withthe help of clustering using K-means clustering technique and data pre-processing usingPrincipal Component Analysis (PCA). In this proposed work, new recommendationtechnique has been presented using K-means clustering, PCA and sampling with the help ofMovieLens dataset. Our proposed method and its subsequent results have been discussed andcollation with other existing methods using evaluation metrics like Dunn Index, averagesimilarity and computational time has been also explained and prove that our technique isbest among other techniques. The results achieve from the MovieLens dataset is able to provehigh efficiency and accuracy of our proposed work. Our proposed method is able to achievethe MAE of .67, which is better than other methods.
IRNLP_DAIICT@DravidianLangTech-EACL2021:Offensive Language identification in Dravidian Languages using TF-IDF Char N-grams and MuRIL

This paper presents the participation of the IRNLPDAIICT team from Information Retrieval and Natural Language Processing lab at DA-IICT, India in DravidianLangTech-EACL2021 Offensive Language identification in Dravidian Languages. The aim of this shared task is to identify Offensive Language from a code-mixed data-set of YouTube comments. The task is to classify comments into Not Offensive (NO), Offensive Untargetede(OU), Offensive Targeted Individual (OTI), Offensive Targeted Group (OTG), Offensive Targeted Others (OTO), Other Language (OL) for three Dravidian languages: Kannada, Malayalam and Tamil. We use TF-IDF character n-grams and pretrained MuRIL embeddings for text representation and Logistic Regression and Linear SVM for classification. Our best approach achieved Ninth, Third and Eighth with weighted F1 score of 0.64, 0.95 and 0.71in Kannada, Malayalam and Tamil on test dataset respectively.
Research Guides: Finding, Accessing, and Using Online Archives and Special Collections Materials: Home

This resource contains a selection of digitized collections available for research as well as tutorials for how to use archives and special collections for your research.
Culinary Places Recommendation System in Bekasi City Using the Simple Additive Weighting Method

Bekasi city, based on data from the Central Bureau of Statistics (BPS) in 2018, shows the average Economic Growth Rate (LPE) of 5.82% from 2013 to 2016. Based on this growth, Bekasi city has business opportunities, for example culinary business, that has already spread around Bekasi city. The number of culinary places can cause problems when visitors determine culinary places that fit their criteria. Many visitors usually rely on information from relatives in determine culinary places, so this allows a mismatch between the recommendations of relatives and the criteria they want. Based on the problem, one of the proposed solutions needs to be made a method to support decisions that can provide recommendations in determining culinary places for visitors. The method used in determining the recommendation of culinary places is Simple Additive Weighting (SAW). In the process of calculating the method there are alternatives and assessment criteria used, there are several assessment criteria, namely price, number of menus, rating, and distance. The result shows the recommended alternative culinary place is the eighth alternative (A8) since the alternative has the highest preference value of 0.85. Therefore, the proposed system can be integrated in the culinary website to support user in choosing the culinary place.