Reviewerly/exHarmony huggingface dataset:
IPTV Video Hardware Encryption Transmission System Analysis

Facing with the relatively large amount of Internet video data, and the requirement for real-time and successive video transmission, the current file encryption and decryption methods have limited performance in IPTV video transmission. Also, IPTV video transmits in clear streams. Based on this, combined with the characteristics of IPTV video, the hardware encryption transmission system is designed from the perspective of hardware encrypted transmission. We are using ECC encryption algorithm upgrades key transmission to improve encryption transmission efficiency and security. The research aims at providing a reference for the encrypted transmission of IPTV video and the improvement of transmission security.
Named Entity Recognition for Social Media Text

This thesis aims to perform named entity recognition for English social media texts. Named Entity Recognition (NER) is applied in many NLP tasks as an important preprocessing procedure. Social medi ...
RESEARCH OF MAIN TRENDS OF MODERN WEB SITES DEVELOPMENT

The article contains the following sections: introduction, research results, conclusions and prospects for further research. In the introduction, a problem regarding the current trends in the development of web pages is considered, an analysis of recent research and publications is carried out, and the purpose of the article is formulated. The second section of the article reflects the main steps that should be followed in the development of web pages, namely: the collection of materials for the development of a web page (technical task), the division of the technical task into components; designing a web page; ; developing Web page (front-end and back-end) components; testing a web page by component; web page placement. The main components of the front-end development are described. \A detailed review of the text editor Sublime Text , as one of the most popular text editors with a wide range of convenient tools for the selection, marking and text code fragments, , is carried out. Since for modern developers a plugin is an integral part of the tools, the article discusses this concept and also describes the most popular plugins for Sublime Text: Package Control, JavaScript &amp; NodeJS Snippets, Emmet, Advanced New File, Git, GitGutter, Sidebar Enhancements , ColorPicker, Placeholders, DocBlockr, SublimeCodeIntel, Minify, Sublime Linter, Color Highlighter. An example of developing an elementary web page is given to demonstrate the use of the described plug-ins, which consists of the following sections: a header; homepage; about us; contacts; basement. The use of the carousel interactive component has been demonstrated. The nuances of using frameworks and their components, such as CSS-Framework and Bootstrap, are considered. As a result of the research, a clear algorithm for the development of an elementary web page has been formed and and methods and means that can be used for this are described. The conclusions are about the prospects for the development of technologies for creating highquality web pages.
Topology, Computation and Data Analysis (Dagstuhl Seminar 19212)

This report documents the program and the outcomes of Dagstuhl Seminar 19212 Topology, Computation and Data Analysis. The seminar brought together researchers with mathematical and computational backgrounds in addressing emerging directions within computational topology for data analysis in practice. This seminar was designed to be a followup event after a very successful Dagstuhl Seminar (17292; July 2017). The list of topics and participants were updated to keep the discussions diverse, refreshing, and engaging. This seminar facilitated close interactions among the attendees with the aim of accelerating the convergence between mathematical and computational thinking in the development of theories and scalable algorithms for data analysis.
Observing the LOD Cloud using Equivalent Set Graphs: the LOD Cloud is mostly flat and sparsely linked

This paper presents an empirical study aiming at understanding the modeling style and the overall semantic structure of Linked Open Data. We observe how classes, properties and individuals are used in practice. We also investigate how hierarchies of concepts are structured, and how much they are linked. In addition to discussing the results, this paper contributes (i) a conceptual framework, including a set of metrics, which generalises over the observable constructs; (ii) an open source implementation that facilitates its application to other Linked Data knowledge graphs.
THE IMPLEMENTATION OF THINK-PAIR-SHARE TECHNIQUE TO INTROVERTED AND EXTROVERTED STUDENTS TO IMPROVE THEIR SPEAKING ABILITY AT THE SECOND GRADE OF SMA SWADHIPA NATAR

Penelitian ini dilakukan untuk mengetahui apakah ada peningkatan yang signifikan dari kemampuan berbicara siswa introvert dan ekstrovert dalam memberikan pendapat setelah penerapan teknik Think-Pair-Share dan untuk melihat sikap siswa introvert dan ekstrovert terhadap implementasi teknik Think-Pair-Share . Penelitian ini dilakukan di SMA Swadhipa Natar dan menggunakan satu kelas eksperimen, yaitu XI IS 3 yang terdiri dari 17 siswa. Data diperoleh melalui pre-test dan post-test yang kemudian dianalisis dengan menggunakan Paired Sample T-test . Setelah penerapan teknik, hasilnya menunjukkan bahwa kemampuan berbicara siswa introvert dan ekstrovert dalam memberikan pendapat meningkat secara signifikan karena nilai signifikansi lebih rendah dari 0,05. Selain itu, tanggapan siswa dalam penerapan teknik TPS juga positif. Dapat disimpulkan bahwa teknik Think-Pair-Share membantu siswa introvert dan ekstrover t dalam meningkatkan kemampuan berbicara mereka. This research was carried out to find out whether there was a significant improvement of introverted and extroverted students’ speaking ability in giving an opinion after the implementation of Think-Pair-Share technique and to investigate the attitude of introverted and extroverted students towards the implementation of the technique. This research was conducted in SMA Swadhipa Natar and employed one experimental class, which was XI IS 3 consisting of 17 students. The data were obtained through a pre-test and a post-test in which the results were analyzed by using Paired Sample T-test. After the implementation of the technique, the result indicated that both introverted and extroverted students’ speaking ability in giving opinion significantly improved because the significance value was lower than 0.05. In addition, students' attitudes to the implementation of TPS technique were also positive. In brief, it can be concluded that Think-Pair-Share technique helps the introverted and extroverted students to improve their speaking ability. Keywords: Think-Pair-Share, personality, speaking ability, giving an opinion.
Using Neural Networks to Schedule Automated Testing in an Agile Environment

Agile methodologies highly recommend the use of automated testing to ensure the quality of the software delivered to the customer. As a software project grows, however, the number of automated tests also grows. It is often the case that the automated tests start taking hours to execute. It would be beneficial that tests which have a high probability of failing be moved to the head of the test execution queue so that failures could be identified early in the test run. In this manner, programmers could begin remedial action on source classes where the test programs failed prior to the entire test run finishing executing. Prior research by the author used Weka and J48 algorithm in order to prioritize the execution of tests. The research in this paper compares the use of J48 and a multi-layer perceptron.
Ensembles of Neural Morphological Inflection Models.

We investigate different ensemble learning techniques for neural morphological inflection using bidirectional LSTM encoder-decoder models with attention. We experiment with weighted and unweighted majority voting and bagging. We find that all investigated ensemble methods lead to improved accuracy over a baseline of a single model. However, contrary to expectation based on earlier work by Najafi et al. (2018) and Silfverberg et al. (2017), weighting does not deliver clear benefits. Bagging was found to underperform plain voting ensembles in general.
Securing Informative Fuzzy Association Rules using Bayesian Network

In business association rules being considered as important assets, play a vital role in its productivity and growth.Different business partnership share association rules in order to explore the capabilities to make effective decision for enhancement of business and core capabilities.The fuzzy association rule mining approach emerged out of the necessity to mine quantitative data regularly present in database.An association rule is sensitive when it violates few rules and regulation for sharing particular nature of information to third world.Like classical association rules, there is a need for some privacy measures to be taken for retaining the standards and importance of fuzzy association rules.Privacy preservation is used for valuable information extraction and minimizing the risk of sensitive information disclosure.Our proposed model mainly focuses to secure the sensitive information revealing association rules.In our model, sensitive fuzzy association rules are secured by identifying sensitive fuzzy item to perturb fuzzified dataset.The resulting transformed FARs are analyzed to conclude/calculate the accuracy level of our model in context of newly generated fuzzy association rules, hidden rules and lost rules.Extensive experiments are carried out in order to demonstrate the results of our proposed model.Privacy preservation of maximum number of sensitive FARs by keeping minimum perturbation highlights the significance of our model.
Design of Electromagnetic Signal Generator Based on Field Programmable Gate Array

Using the direct digital frequency synthesis (DDS) technology, an electromagnetic (EM) signal generator was designed with the field programmable gate array (FPGA) chip as the carrier. The EM signal generator is capable of generating sinusoidal signals with adjustable frequency and amplitude. The system circuit has the advantage of being low-cost, simple and reliable. The function simulation results and the oscilloscope test results show that the signal generator has strong flexibility and stability and meets the design requirements.
Quality and Testing

Quality refers to the degree to which software does what it’s supposed to do, and is built in a way that is structurally sound. Testing refers to checking and giving feedback on software quality. Testing can assess functional quality: does it do what it’s supposed to do and not do things it shouldn’t? Testing can also assess structural quality: is it reliable, secure, maintainable, performant, and appropriately sized?
Monetary Policy and Cryptocurrencies: Much Noise for Nothing?

At the beginning of 2017, there were more than 500 digital currencies (DC) for a total market value of $ 16.8 billion or € 16 billion, the Bitcoin, launched in early 2009, representing alone about 85% of the market. In comparison, euro banknotes and coins in circulation at the end of 2016 amounted to EUR 1 150 billion, 72 times more, for the single currency in fiduciary form. However, some authors have suggested that increased use of DCs could, at some point and under certain circumstances, have profound consequences for the financial system and the conduct and effectiveness of monetary policy (Raskin and Yermack, 2016; Bordo and Levin, 2017). Under the same hypothesis that the consequences of monetary policy can only be significant if the use of DC was widespread, this article offers a more nuanced view. The first part recalls the main characteristics of DCs. The third part looks at Consequences and adjustments of monetary policy from widespread use of digital currencies. In this part, we describe scenarios of widespread use of DCs and their consequences for monetary policy. The fourth part concludes.
Chinese Classics as Liberal Arts Education in era of Fourth Industrial Revolution

교양 한문교과는 4차 산업혁명에 대비한 융합학문이 되어 미래사회에 필요한 과목이라는 인식을 심어주어야 한다. 미래사회는 기계로 대체가 불가능한 “인간만의 능력”을 필요로 한다. 그러나 “인간만의 능력” 배양은 기술의 영역도 아니고 인공지능이 할 수 있는 일이 아니다. 한문 교육은 동양 고전을 통해 미래사회를 대비한 통찰력을 제공해 줄 수 있고 그 기반도 마련해줄 수 있다. 기존의 한문교육은 유교 관련 고문의 학습을 통한 전통사회의 문화와 예절 등의 전수에 치우져 있었다. 이러한 이유로 학생들은 한문 교과에 대한 흥미를 잃었다. 한문을 미래사회에서도 통용되는 매력적인 학문으로 만들기 위해서는 유교 경전 기반의 인성교육 위주의 텍스트 이외에 현대사회의 다양한 문제를 다루는 텍스트가 필요하다. 그 대안으로는 非儒家 텍스트 중 道家와 미래사회를 연관한 내용이나 현대사회의 갈등을 해소할 수 있는 내용 등이 있다. 또한 능동적인 수업을 위하여 상반되는 주장을 통한 토론 유도 방법이 있다. 예시로는 사랑에 대한 유가와 묵가의 견해 차이, 노동에 대한 맹자와 묵자의 견해 차이 등을 제시할 수 있다. 한문 교과가 나아갈 길은 한문텍스트를 통해 미래로 가는 길을 보여주는 것이다. 미래 사회와 관련된 지혜, 미래사회의 생존 방법을 안내해주는 수업을 진행해야 경쟁력이 있다.The Chinese Classics, should be included as a Liberal Arts course in convergence study for the fourth industrial revolution to establish that it is a necessary subject for future society. Future societies need human capabilities that cannot be replaced by machines. However, the cultivation of human capabilities cannot be achieved by technology or artificial intelligence. Classical Chinese language education can provide insights for future society through Oriental classics, creating a foundation for these capabilities. The existing Classical Chinese language education is centered on the culture and manners of traditional society through the teachings of Confucianism. Thus, students have lost interest in Classical Chinese language. In order to make Classical Chinese language an attractive subject that can be useful for future society, texts dealing with the problems of modern society are necessary along with texts focusing on personality education based on Confucian scriptures. Some alternatives include Daoism and future society in non-Confucian texts, as well as resolving conflicts in modern society. There are ways of eliciting debate in classes by posing conflicting arguments, for example, Confucianism for love, differences in Mohists, differences between Mencius and Mozi opinions on labor. Classical Chinese language classes can show the way to the future through Classical Chinese texts. These classes can be productive only when they impart wisdom on future society and survival.
A Temporal Module for Logical Frameworks.

In artificial intelligence, multi agent systems constitute an interesting typology of society modeling, and have in this regard vast fields of application, which extend to the human sciences. Logic is often used to model such kind of systems as it is easier to verify than other approaches, and provides explainability and potential validation. In this paper we define a time module suitable to add time to many logic representations of agents.
Reasoning in Highly Reactive Environments.

The aim of my Ph.D. thesis concerns Reasoning in Highly Reactive Environments. As reasoning in highly reactive environments, we identify the setting in which a knowledge-based agent, with given goals, is deployed in an environment subject to repeated, sudden and possibly unknown changes. This is for instance the typical setting in which, e.g., artificial agents for video-games (the so called bots), cleaning robots, bomb clearing robots, and so on are deployed. In all these settings one can follow the classical approach in which the operations of the agent are distinguished in sensing the environment with proper interface devices, thinking, and then behaving accordingly using proper actuators. In order to operate in an highly reactive environment, an artificial agent needs to be: 1. Responsive -> The agent must be able to react repeatedly and in a reasonable amount of time; 2. Elastic -> The agent must stay reactive also under varying workload; 3. Resilient -> The agent must stay responsive also in case of internal failure or failure of one of the programmed actions in the environment. Nowadays, thanks to new technologies in the field of Artificial Intelligence, it is already technically possible to create AI agents that are able to operate in reactive environments. Nevertheless, several issues stay unsolved, and are subject of ongoing research.
Comparing the Performance of Feature Representations for the Categorization of the Easy-to-Read Variety vs Standard Language

We explore the effectiveness of four feature representations – bag-of-words, word embeddings, principal components and autoencoders – for the binary categorization of the easy-to-read variety vs standard language. Standard language refers to the ordinary language variety used by a population as a whole or by a community, while the “easy-to-read” variety is a simpler (or a simplified) version of the standard language. We test the efficiency of these feature representations on three corpora, which differ in size, class balance, unit of analysis, language and topic. We rely on supervised and unsupervised machine learning algorithms. Results show that bag-of-words is a robust and straightforward feature representation for this task and performs well in many experimental settings. Its performance is equivalent or equal to the performance achieved with principal components and autoencorders, whose preprocessing is however more time-consuming. Word embeddings are less accurate than the other feature representations for this classification task.
Natural Language Generation for Non-Expert Users.

Motivated by the difficulty in presenting computational results, especially when the results are a collection of atoms in a logical language, to users, who are not proficient in computer programming and/or the logical representation of the results, we propose a system for automatic generation of natural language descriptions for applications targeting mainstream users. Differently from many earlier systems with the same aim, the proposed system does not employ templates for the generation task. It assumes that there exist some natural language sentences in the application domain and uses this repository for the natural language description. It does not require, however, a large corpus as it is often required in machine learning approaches. The systems consist of two main components. The first one aims at analyzing the sentences and constructs a Grammatical Framework (GF) for given sentences and is implemented using the Stanford parser and an answer set program. The second component is for sentence construction and relies on GF Library. The paper includes two use cases to demostrate the capability of the system. As the sentence construction is done via GF, the paper includes a use case evaluation showing that the proposed system could also be utilized in addressing a challenge to create an abstract Wikipedia, which is recently discussed in the BlueSky session of the 2018 International Semantic Web Conference.
On the Generation of Equational Dynamic Logics for Weighted Imperative Programs

Dynamic logic is a powerful framework for reasoning about imperative programs. This paper extends previous work [9] on the systematic generation of dynamic logics from the propositional to the equational case, to capture ‘full-fledged’ imperative programs. The generation process is parametric on a structure specifying a notion of ‘weight’ assigned to programs. The paper introduces also a notion of bisimilarity on models of the generated logics, which is shown to entail modal equivalence with respect to the latter.
Performance Evaluation of Block-Based Adaptive Algorithms

Performance of real-time digital signal processing systems is limited by their data computing capability. Therefore, evaluation of different architectures to determine the most efficient one is an important task. An efficient architecture for the implementation of block-based least mean square (LMS) adaptive filter is presented in this paper. In order to achieve lower adaptation delay different methods for optimization are used. Proposed solution is implemented in FPGA technology. Adaptive filters with different orders and block lengths are analyzed. Simulation results indicate that, compared to sample by sample based algorithm, the adaptation delay may be reduced by up to $N$ times, where $N$ is the block size of input data samples.
Conversational AI : Open Domain Question Answering and Commonsense Reasoning.

Our research is focused on making a human-like question answering system which can answer rationally. The distinguishing characteristic of our approach is that it will use automated common sense reasoning to truly understand dialogues, allowing it to converse like a human. Humans often make many assumptions during conversations. We infer facts not told explicitly by using our common sense. Incorporating commonsense knowledge in a question answering system will simply make it more robust.
Mathematics Teachers Attitude Towards The Use Of Multichioce Resource Centre For Instruction In Ogun State

The purpose of the study was to determine the attitude of Mathematics teachers towards the use of Multi- choice Resource Centres in Ogun State. A researcher designed questionnaire was administered to 35 Mathematics teachers in 20 secondary schools. Data obtained were analysed using percentage and mean. The study revealed that Mathematics teachers always use the technology tools provided at the Multi choice resource centre. Mathematics teachers also showed a positive attitude towards the use of the technology tools at the Multi- choice Resource Centres. The study concluded that the attitude of Mathematics teachers towards the use of the Multi- choice Resource Centres in Ogun State helps the usage. The study recommended among others that Multi- choice Resource Centres should be put in place in other schools and continuous training should be organized for the teachers.
Lower Bounds for (Non-monotone) Comparator Circuits.

Comparator circuits are a natural circuit model for studying the concept of bounded fan-out computations, which intuitively corresponds to whether or not a computational model can make copies of intermediate computational steps. Comparator circuits are believed to be weaker than general Boolean circuits, but they can simulate Branching Programs and Boolean formulas. In this paper we prove the first superlinear lower bounds in the general (non-monotone) version of this model for an explicitly defined function. More precisely, we prove that the n-bit Element Distinctness function requires Ω((n/ log n)^(3/2)) size comparator circuits.
Current practice of cytology in the diagnosis of acute leukemias in Madagascar

Introduction - Acute leukemias are clone proliferation of cells blocked at a stage of maturation. These pathologies are frequent in Western countries with an incidence of 2.5 to 3.5 / 100 000 inhabitants/year. Their frequency is about 25.5% in Madagascar. In Madagascar, diagnosis and classification of acute leukemias is cytological because our laboratories haven't immunophenotyping, molecular biology and karyotype. We share through this study our daily practice in front of acute leukemia. Method - We conducted a prospective descriptive study of cases of acute leukemia diagnosed between January and April 2017 at hematological laboratory of Joseph Ravoahangy Andrianavalona Antananarivo hospital (Madagascar) Results - During this period, 16 cases of acute leukemia were diagnosed in our unit. Blood and bone marrow smear cytological study revealed 6 cases (37.5%) of ALL2, 4 cases (25.0%) of AML2, 2 cases (12.5%) of AML3, 2 cases (12.5%) of AML4, 1cas (6.25%) of AML5 and 1 case (6.25%) of ALL1. Conclusion - Cytology is crucial in malignant hemopathies, particularly in low resource countries, although the need for molecular biology and immunophenotyping is well established.