Reviewerly/exHarmony huggingface dataset:
Technique for Optimization of Association Rule Mining by Utilizing Genetic Algorithm

Background: Due to advancement in usage of Internet and pattern discovery from huge amount of data flowing through internet, personal information of an individual or organization can be traced. Hence, to protect the private information is becoming extremely crucial, which can be achieved through privacy preserving data mining. Objective: The main objective to preserve the privacy of data and to maintain the balance between privacy and accuracy by applying privacy preserving technique and optimization respectively. Methodology: The generation of class association rule is done by utilizing associative classification technique namely class based association due to its simplicity which serves the purpose of classifying the data. Furthermore, privacy of the data should be maintained and hence privacy preserved class association rules are produced by applying privacy preserved technique namely anonymization. Hence, optimization technique specifically genetic algorithm as well as neural network has been applied to maximize the accuracy. Results: (Four various real datasets has been utilized for different experimentation). : Implemented Classification Based on Association (CBA) algorithm of Associative Classification technique and it provides virtuous accuracy as compared to other techniques by setting the support as 0.2 and confidence at 0.6. : Privacy preserving techniques namely k-anonymization was implemented to preserve the privacy but it has been observed that as privacy (k-level) increases, accuracy (percentage) decreases due to data transformation. Conclusion: (Hence, optimization technique namely Genetic Algorithm (GA) and Neural Network (NN) has been implemented to increase the accuracy (probably 7-8%). Furthermore, on comparison of GA and NN considering the time parameter, GA outperforms well.
Prosodie del Congedo – Analisi fonetica comparativa di dodici letture della prosopopea di Giorgio Caproni

The reading of poetry is one of the most overlooked aspects of Italian studies in Criticism and Linguistics. This experimental research arises from Beccaria’s studies [2] and explores the musical apparatus of a poetic composition through methods of instrumental Phonetics. The study focuses on the prosody of Congedo del viaggiatore cerimonioso read by Giorgio Caproni. The approaches are qualitative and quantitative: from the analysis of the author’s reading, the observation has been extended to other eleven voices, different at a professional and diachronic level (contemporary poets, radio speakers and actors). Listening represents the start of the research, combined with the observation of oscillograms and spectrograms and their annotation using Praat. However, the sound data is always related to the textual data, by identifying the main trends in melody and prosodic segmentation. The study, in addition to highlighting considerable speech variation, reveals aspects of Italian poetry that have always been neglected and are now available, thanks to a quantitative method. The work wants to be also a starting point for “VIP - Voices of Italian Poets”, a project dedicated to original and contemporary readings of of Twentieth Century Italian poems, accompanied by linguistic annotations at different levels.
A Study on the Characters of the Disciples of Confucius

The current study offers a systematic and comprehensive review of the discourse of Confucius with his disciples in LunYu(論語) and ShiJi(史記). We hope to discover and realize the characters of disciples of Confucius and attain an accurate translations of LunYu(論語)<BR>and exact concepts of Confucius" educational messages and enlightenments. The study first pays attention to the sentence "Virtuous conduct(德行): Yanyuan(顔淵), Minziqian(閔子騫), Ranboniu(冉伯牛), Zhonggong(仲弓). speech(言語): Zaiwo(宰我), Zigong(子貢). political affairs(政事): Ranyou(冉有), Jilu(季路). literary capability(文學): Ziyou(子游), Zixia(子夏)" in LunYu(論語). The study focuses on the front six disciples of that sentence. <BR> In the four outstanding achievers on virtuous conduct, it is very difficult to fine out the specific virtuous conducts of Ranboniu(冉伯牛) as he appears only one time in LunYu(論語). Yanyuan(顔淵) was eager to learn and showed excellent capacity for steady practice of venevolent<ren(仁)>. Minziqian(閔子騫) was a very famous devoted son, the man of integrity and principles, and the possessor of capability enough to say worthy wisdoms whenever they are applicable.. Although Zhonggong(仲弓) was a poor speaker, he demonstrated excellent leadership for governing the state.<BR> In the two outstanding achievers on speech, we could obtain the enlightenment that fluency must be supported by virtuous conducts from the faults and failures of Zaiwo(宰我). In the case of Zigong(子貢), we found that Confucius consistently encouraged him to devote to a higher stage rather than boast his fluency in the discourse with Zigong(子貢).<BR> Finally, "individual upbringing" - the unique educational method of Confucius"- was mainly found in the discourse with the disciples such as Yanyuan(顔淵) and Zhonggong(仲弓) who asked the same questions, but Confucius replied with different answers according to the characters of two disciples which were familiar with Confucius. The other distinguished examples of "individual upbringing" were also found in the discourse of Confucius and Zigong(子貢), where Confucius often controlled Zigong"s fluency with the emphasis on the consistent practice of virtuous conducts.
Bursty Topic Detection Based on Bursty Term Detection and Filtration

Bursty topic spreads very quickly and generate huge influence in Weibo. Therefore, bursty topic detection is one of the hot spots of topic detection and tracking. Most of the existing bursty topic detection methods do not consider the basic weight of the bursty term and the filtration of the invalid bursty term. In this paper, we propose a bursty topic detection method BTDF based on calculation of bursty term value and recognition of pseudo bursty term. The proposed BTDF uses topic models and clustering methods to get general topics, and identifies sudden topics from general topics by judging whether topic keywords contain bursty terms. In BTDF, we extract the bursty term by using the basic weight and bursty weight of the term and filter the pseudo bursty terms by analyzing the novelty of the terms. The experiments conducted on Weibo data show that the proposed method achieves better performance in bursty topic detection.
Introduction to Spark

As this book is about Spark, it makes perfect sense to start the first chapter by looking into some of Spark’s history and its different components. This introductory chapter is divided into three sections. In the first, I go over the evolution of data and how it got as far as it has, in terms of size. I’ll touch on three key aspects of data. In the second section, I delve into the internals of Spark and go over the details of its different components, including its architecture and modus operandi. The third and final section of this chapter focuses on how to use Spark in a cloud environment.
Surrounding-Based Attention Networks for Aspect-Level Sentiment Classification

Aspect-level sentiment classification aims to identify the polarity of a target word in a sentence. Studies on sentiment classification have found that a target’s surrounding words have great impacts and global attention to the target. However, existing neural-network-based models either depend on expensive phrase-level annotation or do not fully exploit the association of the context words to the target. In this paper, we propose to model the influences of the target’s surrounding words via two unidirectional long short-term memory neural networks, and introduce a target-based attention mechanism to discover the underlying relationship between the target and the context words. Empirical results on the SemEval 2014 Datasets show that our approach outperforms many competitive sentiment classification baseline methods. Detailed analysis demonstrates the effectiveness of the proposed surrounding-based long-short memory neural networks and the target-based attention mechanism.
Using distribution analysis for parameter selection in repstream

One of the most significant challenges in data clustering is the evolution of the data distributions over time. Many clustering algorithms have been introduced to deal specifically with streaming data, but common amongst them is that they require users to set input parameters. These inform the algorithm about the criteria under which data points may be clustered together. Setting the initial parameters for a clustering algorithm is itself a non-trivial task, but the evolution of the data distribution over time could mean even optimally set parameters could become non-optimal as the stream evolves. In this paper we extend the RepStream algorithm, a combination graph and density-based clustering algorithm, in a way which allows the primary input parameter, the $ K $ value, to be automatically adjusted over time. We introduce a feature called the edge distribution score which we compute for data in memory, as well as introducing an incremental method for adjusting the $ K $ parameter over time based on this score. We evaluate our methods against RepStream itself, and other contemporary stream clustering algorithms, and show how our method of automatically adjusting the $ K $ value over time leads to higher quality clustering output even when the initial parameters are set poorly.
Experimental Analyses of Chinese Tone 3 and Reconsideration of Teaching Contents

The purpose of this study is to analyze the contents of tone3 in textbooks for native speakers and foreign learners and to compare the characteristics of the three characters defined in the textbooks and the actual features of the three characters recorded in the textbooks through phonetic analysis. In case of pronouncing singly, the tone curve is low and smooth. Most of the tone is not more than 1-2 degree. In other words, the stable characteristic of the three is in "low" rather than "rising". When the tone3 is located in the front syllable, most syllables are pronounced as "21" or "32", as described in the textbook. When the tone3 is located at the end of the back syllable or sentence, similar to the result of (1), but a little more various numerical values due to the intonation of the sentence, the characteristics of the low elliptical tone are unchanged, which was also different from the description of the textbook. If you give up the characteristic of "rising", students can distinguish it from "tone2. According to the results of the above analysis and the discrimination characteristics of the tone3 revealed in the previous study, the characteristics of the tone3 defined by many textbooks do not accurately reflect the pronunciation of the actual Chinese speaker, and the tone curve depicting the tone3 , The textbook contents have to review, and the teacher should exclude the "rising" characteristic to be emphasized.
Transforming Forensics Digital: What works in digital forensics? (Effectiveness of digital forensics techniques)

The Transforming Forensics Digital project commissioned this Rapid Evidence Assessment (REA) to answer the following research question: What works in digital forensics? (Effectiveness of digital forensics techniques) The review of the evidence serves multiple goals. First, it explores what are the existing digital forensic techniques in use by practitioners? It was carried out rapidly in order to provide the Digital project and the wider Transforming Forensics programme with the necessary information about the effectiveness of digital forensics techniques that are in use by practitioners. Second, it provides a taxonomy of digital forensics techniques. Third, it identifies research challenges, gaps, and opportunities to assist the ongoing the Digital project to understand where the future investment may be most effectively targeted to improve digital service provision. This review thus generates valuable methodological lessons for similar exercises going forward. The review examines academic articles and evaluation published in English between 2014 and 2019. It adopts a systematic approach to the literature search and quality assessment to maximise transparency, replicability and the potential to update.
How to influence physics education for information society

The national project IT academy has an ambitious goal in attraction of young population towards IT and science career. For each science subject, mathematics and informatics new lessons ideas with complete teachers support are developed, piloted and share with project partners. After learning the chosen topic, the verifiers have the opportunity to evaluate the methodology and formulate recommendations for its author. Teacher training courses oriented on IBSE with help of ICT, self-assessment and scientific skills development are involved into TEP in Slovakia, based on evaluated methodology. The networking within IT companies, schools an local partners is generated as an tool for real cooperation. Also wide range of informal educational activities, like science camps, competitions, of school activities, are supported by the project. We hope, all over Slovakia impact, can influence science education at lower and upper secondary level.
A locally adaptive edge preserving filter for denoising of low dose CT using multi-level fuzzy reasoning concept

To reduce the radiation exposure, low dose CT (LDCT) imaging has been particularly used in modern medical practice. The fundamental difficulty for LDCT lies in its heavy noise pollution in the projection data which leads to the deterioration of the image quality and diagnostic accuracy. In this study, a novel two-stage locally adaptive edge preserving filter based on multi-level fuzzy reasoning (LAEPMLFR) concept is proposed as an image space denoising method for LDCT images. The first stage of structured pixel region employs multi-level fuzzy reasoning to handle uncertainty present in the local information introduced by noise. The second stage employs a Gaussian filter to smooth both structured and non-structured pixel region in order to retain the low frequency information of the noisy image. Comparing with traditional denoising methods, the proposed method demonstrated noticeable improvement on noise reduction while maintaining the image contrast and edge details of LDCT images.
LibGuides: MHIKNET: Current Awareness

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A Method for High Resolution Satellite Image Compression using Type-1 and Type-2 Fuzzy Sets

High-resolution satellite images are voluminous in size. Their storage after collection occupies large memory space. This problem can be resolved by storing such images by reducing their size. Image compression techniques available in literature somehow provide a solution for it. But, still such techniques cannot be applied in large voluminous size of images as in the case of high resolution satellite images due to some domain specific problems. Therefore, this study introduces a new method for compressing these images. The proposed method is designed based on type-1 and type-2 fuzzy sets. The proposed method is initially verified with benchmark datasets. Finally, it is validated by compressing high resolution satellite images. Experimental results include comparison study and statistical analysis signify the efficiency of the proposed method over existing well-known techniques of the image compression.
Workshop: Keyword Discovery: Visualizing Your Topic in Research, Thesis and Dissertation Development

Aim/Purpose: Participants will learn various digital tools to assist them in the discovery of appropriate keywords for their own research and writings as well as in teaching. Background: Experiences teaching undergraduates and graduate students information literacy and retrieval have identified several areas where students have problems in searching databases because of misconceptions as to what they should be using as keywords. Methodology: The use of visual tools to identify keywords. Contribution: The visualization software demonstrated and used in the workshop can enhance the literature review portion of any research project. Recommendations for Practitioners: With the vast expansion of the amount of information available via the Web, it is time to go back to a more considered approach to keywords (as in the past when searching a database could cost hundreds of dollars) rather than just the first words that might occur. Recommendations for Researchers: In addition to using these techniques in your own research, teaching them to research assistants and students and not assume that everyone knows how to use keywords. Impact on Society: These same approaches can be used in continuing education or by independent scholars. Future Research: We plan to demonstrate at the conclusion of the workshop visual tools that can take it another step and help in organizing sources.
Spatially adaptive metrics for diffeomorphic image matching in LDDMM

Registering two medical images consists in computing a mapping between the organs of interest they contain. Although this mapping is dense in space, it can only be accurately estimated based on significant intensity variations in the images, which is a sparse information. Using deformation regularization properties that are physiologically meaningful is then one of the keys to estimate pertinent mappings. In the LDDMM framework these regularization properties are directly related to the right-invariant metric which controls the optimal deformation. In this chapter we then present different methodologies related to this degree of freedom. After briefly introducing the LDDMM framework, we present a simple strategy to regularize the mappings at different scales and a more advanced technique to make it possible to estimate a sliding motion at predefined locations. We then propose to switch the paradigm of right-invariant metrics to left-invariant ones, so that spatially adaptive metrics can be used in LDDMM. In the last part, we review different attempts to optimize these spatially adaptive metrics and propose a new evolution of LDDMM that incorporates spatially adaptive metrics.
Cuidados estéticos faciais de mulheres praticantes de exercício físico no município de Armazém-SC

Introduction: It is noticeable in today's society, a great increase in the search for the practicn of physical activities which bring personal satisfaction, as well as the search for aesthetic procedures, not only for the care with the appearance, but also for the benefits brought to the health of the skin. In this way, it is emphasized that the skin plays several important functions for the human body, because it is the largest organ, it has essential functions for health, such as protecting our body from mechanical trauma, regulation of temperature and water content, among others. In parallel, it can be associated with the fact that many women take care of their bodies through the practice of exercises, raising the question of which care and procedures they use for the skin. Goal: The aim of this research was to analyze the facial care and the aesthetic treatments performed by women practicing physical exercise in the city of Armazem-SC. Checking different factors such as the type of skin, which care, cosmetics used and how often, and finally, if they seek specialized treatment. Methodology: The methodology used is characterized by an exploratory research, with data collection and quantitative analysis of the data obtained. A questionnaire containing closed questions regarding facial aesthetic care was applied to 80 women practitioners of physical exercise residing in the city of Armazem-SC. Results: The most found skin was the mixed skin, the most used cosmetic was the sunscreen. Conclusion: Women who exercise do not take care of their face skin as often as they do their boby.
Decentralized collaborative TTP free approach for privacy preservation in location based services

In recent trends, growth of location based services have been increased due to the large usage of cell phones, personal digital assistant and other devices like location based navigation, emergency services, location based social networking, location based advertisement, etc. Users are provided with important information based on location to the service provider that results the compromise with their personal information like user’s identity, location privacy etc. To achieve location privacy of the user, cryptographic technique is one of the best technique which gives assurance. Location based services are classified as Trusted Third Party (TTP) &amp;amp; without Trusted Third Party that uses cryptographic approaches. TTP free is one of the prominent approach in which it uses peer-to-peer model. In this approach, important users mutually connect with each other to form a network to work without the use of any person/server. There are many existing approaches in literature for privacy preserving location based services, but their solutions are at high cost or not supporting scalability. In this paper, our aim is to propose an approach along with algorithms that will help the location based services (LBS) users to provide location privacy with minimum cost and improve scalability.
Using the Shell with InnoDB Cluster

Thus far, we have learned what high availability is and how to set up a basic high availability installation with MySQL Replication. We also learned how to configure Group Replication for even better high availability. However, we learned along the way that the setup and commands to make all this work are specific and require more manual setup and configuration steps than most would want. Fortunately, Oracle has listened to their customers and has been busy working on MySQL high availability by dramatically improving not only the features and capabilities but also the ease of use (or administration). This is where InnoDB Cluster really shines.
Roles of University Libraries in MOOCs

Roles of the libraries become very critical in present era due to rapid changes in technologies and learning patterns of the users. These changes are enforcing to the libraries to play multiple roles in this online and technology driven era in order to provide effective services to the users particularly in higher education sector. Thus, this study aims to examine the roles of the university libraries in massive open online courses (MOOCs) domain. This study may be useful to the library and information science professionals and libraries to get involved in MOOCs activities at the large level.