Reviewerly/exHarmony huggingface dataset:
A hybrid approach to perform test case prioritisation and reduction for software product line testing

Software Product Line (SPL) is a popular research area in software engineering which deals with many products generated simultaneously. There is a requirement for a tool or framework that can test all the products. SPL implies Test Case Prioritisation (TCP) and Test Case Reduction (TCR) techniques to alleviate the problem of testing. This paper proposes a hybrid approach which combines K-Means and Principal Component Analysis (PCA) approaches to perform SPL testing. The experimental results show that the hybrid approach-based order provides better results than the random, similarity, ICPL algorithm-based order using APFD metric. Our proposed approach reduces the test cases to the minimum amount and is also used to perform efficient SPL testing that not only improves the effectiveness and efficiency of fault detection but also improves the effectiveness of Test Suite Reduction (TSR).
In margine al <i>Lazzaretto Vecchio di Venezia. Le scritture epigrafiche</i> di Francesca Malagnini

The article is focused on some recent textual and linguistic acquisitions contained in the volume by Francesca Malagnini, Il Lazzaretto Vecchio di Venezia. Le scritture epigrafiche (Venice: Marcianum Press, 2018). In particular, the edited epigraphic writings in Latin and in vernacular are resumed and commented with reference to their different functions. In this context, the importance of the texts that convey the language of use emerges as a fundamental item for the reconstruction of the history of Italian.
Spreading Activation: A Fast Calculation Method for Text Centroids

Centroid terms are single, descriptive words that semantically and topically characterise text documents and thus can act as their very compact representation in automated text processing tasks that strongly rely on the semantic similarity of texts. Algorithms to classify and cluster them make use of this information. In this book, the novel, brain- and physicsinspired concept of centroid terms is introduced and deeply discussed. Furthermore, their unique properties and practical usage in major natural language processing and text mining tasks are covered. In this regard, a new graph-based method for their fast calculation is presented as well. In contrast to methods relying on the bag-of-words model, the derived centroid distance measure can uncover
Section Articles PERENCANAAN ULANG SISTEM DRAINASE BERWAWASAN LINGKUNGAN DI KAWASAN RW 08 KELURAHAN SUKUN KECAMATAN SUKUN KOTA MALANG JAWA TIMUR

Road drainage is needed to prevent inundation. Inundation occurs due to the construction of drainage channels that are not in accordance with the discharege of rainwater runoff so that the water overflows and there is a puddle on the road. The purpose of this thesis is to design an environmentally drainage canal, evaluate the hydraulic aspects of the drainage buildings, calculate construction costs, and plan scheduling. The data needed are topographic maps, rainfall data from the 3 closest stations: Dau, Wagir, and Tajinan in 2009 until 2018, and the price of the Malang City work principal in 2018. The data is processed using the Gumbel I method, suitability test with Chi method –Square and Smirnov-Kolmogorov by a period of 5 years, rain intensity with the Mononobe method and design flood discharge with the rational method. The calculation results the design rainfall is 108.579 mm/day; discharge channel varies from 0.006 m3/s until 1.516 m3/s; environmentally drainage using infiltration wells with dimensions of 0.6 meters with a depth of 3 meters, and obtained infiltration well discharge 0.0233 m3/s; channel dimensions of 1 m x 1.1 m with freeboard 0.2 m.
Evolving deep forest with automatic feature extraction for image classification using genetic programming

© Springer Nature Switzerland AG 2020. Deep forest is an alternative to deep neural networks to use multiple layers of random forests without back-propagation for solving various problems. In this study, we propose a genetic programming-based approach to automatically and simultaneously evolving effective structures of deep forest connections and extracting informative features for image classification. First, in the new approach we define two types of modules: forest modules and feature extraction modules. Second, an encoding strategy is developed to integrate forest modules and feature extraction modules into a tree and the search strategy is introduced to search for the best solution. With these designs, the proposed approach can automatically extract image features and find forests with effective structures simultaneously for image classification. The parameters in the forest can be dynamically determined during the learning process of the new approach. The results show that the new approach can achieve better performance on the datasets having a small number of training instances and competitive performance on the datasets having a large number of training instances. The analysis of evolved solutions shows that the proposed approach uses a smaller number of random forests over the deep forest method.
Campus Computing 2019 Survey

The Department ChairVolume 31, Issue 2 p. 26-27 Articles Campus Computing 2019 Survey First published: 29 September 2020 https://doi.org/10.1002/dch.30353Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume31, Issue2Fall 2020Pages 26-27 RelatedInformation
Per una «poetica della totalità-mondo»

“I speak and above all write in the presence of all the languages of the world”, is a quote from Poétique du divers by Édouard Glissant, not as a means to plurilingualism but rather a critical view of the concept of language as being closed and homogeneous, by intertwining poetry and politics in order to deconstruct the language-culture-territory triad. Glissant’s poetics of totalité-monde highlights the open and inclusive interplay between places and literary works, aimed at demonstrating the value of all the composite contributions which come together to form cultures. There are already many literary examples in Italian language written inside and outside Italy which demonstrate a failed or at least weakened correspondence between notions seen often as essential, unchanging and a-historic. The example of Luigi Di Ruscio is particularly apt here, as he was a poet and writer who had lived in Oslo for forty years, and had kept writing and publishing in Italian.
A Study on Community Overlapping Detection Algorithms in Social Networks

Community detection is one of the most important research area wherein invention and growth of social networks.Community is a set of members densely connected within a group and sparely connected with the other groups.In social networks, the singular characteristic of communities is multi membership of a node resulting in overlapping communities.Another relevant feature of social networks is the possibility to evolve over time.In recent years, many researchers have worked on various methods that can efficiently unveil overlapped structure on dynamic network.This paper reviews the previous studies done on the problem of overlapping community detection algorithms.Moreover, some approaches for dynamic network that change from time to time are also described.
Emerson, Thoreau, Fuller, and Transcendentalism

Research Article| September 01 2020 Emerson, Thoreau, Fuller, and Transcendentalism Todd H. Richardson Todd H. Richardson University of Texas Permian Basin Search for other works by this author on: This Site Google American Literary Scholarship (2020) 2018 (1): vii–23. https://doi.org/10.1215/00659142-8225354 Cite Icon Cite Share Icon Share Facebook Twitter Email Permissions Search Site Citation Todd H. Richardson; Emerson, Thoreau, Fuller, and Transcendentalism. American Literary Scholarship 1 September 2020; 2018 (1): vii–23. doi: https://doi.org/10.1215/00659142-8225354 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search nav search search input Search input auto suggest search filter Books & JournalsAll JournalsAmerican Literary Scholarship Search Advanced Search The text of this article is only available as a PDF. © 2020 by Duke University Press2020 Article PDF first page preview Close Modal Issue Section: Part I You do not currently have access to this content.
Development of Diaper using Regenerated Carboxylated Cotton Fiber

The article learn and taking place the improvement and portrayal of infant diaper prepared while regenerated cotton fiber of carboxylated. Regenerated carboxylated cotton fiber has been consolidated into the diaper to improve their ingestion limit, liquid strike, centrifuge retention capacity, PH. It is found that the diaper made up of regenerated fiber shows good absorbency when compared to cotton fiber.
Advanced C# Language Features

In this chapter, you’ll deepen your understanding of the C# programming language by examining several more advanced topics. To begin, you’ll learn how to implement and use an indexer method. This C# mechanism enables you to build custom types that provide access to internal subitems using an array-like syntax. After you learn how to build an indexer method, you’ll see how to overload various operators (+, -, <, >, etc.) and how to create custom explicit and implicit conversion routines for your types (and you’ll learn why you might want to do this).
Cryptosystem by a community of devices with limited resources

Rivest-Shamir-Adleman (RSA) is an encryption algorithm with public-key and is the most widely used for secure data transmission. It provides high safety and consists of modular exponential operation on large numbers. We propose an original approach which makes a distributed calculation of RSA encryption by a community of users endowed with low resources equipment. When a user u of the community wants to encrypte a data X, he exploits the resources of his community. For that, we replace the modular exponentiation operation by a set of calculations dependent of each other and which use fewer resources. These calculations are spread over the members of the user's community to help him perform the operation.
Suggestion for manuscript improvement

This manuscript presents the results a very interesting project performed in the current desert region of China.A multi-proxy approach has been applied to reconstruct environments of the past 2.5 Myr.Besides the currently presented proxy records, I am aware that also pollen analysis was initially planned and supposedly also performed.However, no pollen results are shown in the submitted version of the paper.I am wondering why the authors did not include the pollen analysis results, if they are available?These results could be extremely valuable and interesting and may provide a link for correlation with other long-term records, such as those from Lake Baikal or C1
Indexing

When a user queries a table, the user is often interested in only some of its records, such as the records having a specified value of some field. An index is a file that allows the database engine to locate such records quickly, without having to search through the entire table. This chapter considers three common ways to implement an index: static hashing, extendable hashing, and B-trees. It then develops new relational algebra operations that take advantage of indexes.
Micro-learning and Flipped Classroom to Improve Learning Motivation in Psychology Students

This research work shows the combination of micro-learning and flipped classroom to improve motivation in the learning process. The work was applied with 33 students from the professional school of Psychology of the Cognitive Psychology course of the National University of San Antonio Abad del Cusco in Peru. The applied methodology consisted of delivering podcast educational material before the synchronous session class; then, during the session class, they carry out a case study in groups of 4 to 5 students; then, the students created a video of very short time duration to be shared among other students. A questionnaire of 17 questions referring to student’s satisfaction was applied to measure the satisfaction of the 33 participants, and the results show that 83.9% reached the positive evaluations of Agree+Totally Agree.
Monitor and detect suspicious transactions with database forensics and Dempster-Shafer theory of evidence

The digital investigators have now approached databases for investigating the cyber crimes. The illegal financial transactions on the web which goes undetected can now be revealed through database forensics. In response to this, we have proposed a methodology to detect the illegal financial transactions through database audit logs. The aim here is to monitor the database, detect the suspicious transactions and report the risk level of these transactions. Different databases are monitored to extract SQL transactions through their respective audit logs. The SQL transactions obtained are transformed and loaded in a standard XML format which contains financial records along with its metadata. Initially, we process the financial transaction records with rule-based outlier detection algorithm and classifies the transactions as per RBI rules. The suspected transactions obtained as outliers are marked with initial belief values. To verify the uncertainty of the suspected transactions we apply Dempster-Shafer's theory of evidence which combines various evidence of suspected transactions obtained through audit logs. The experiments performed manifest the risk level of suspected transactions.
Efficient Cognitive Skill Based Learning System using Augmented Reality

Augmented Reality provides an interactive experience by imposing virtual objects over real world environment and used in different field in learning, entertainment, or edutainment by developing higher order cognitive and practical learning skills. With the infusion of digital technology, nowadays all the educational institutions adapted the online mode learning environment like smart classroom for content delivery, Webcast Lecture by using AR. AR attracts research attention for its ability to allow students to be immersed in realistic experiences. AR will allow learners too deep about real time and cognitive skill development experiences. Recent scenario in education and academic sectors needs emerging technologies for learning system. In that scenario AR technology will be used to create new type of self-learning and automated application in academic. This technology is used to enhance the teaching and learning for students in effective way and efficient too. Even this technology will attract the students to learn fast and improve the cognitive skill also. This is a new standard, merging features from ubiquitous computing, tangible computing, and social computing. The benefits of this proposed component include inspiring deep and thoughtful education, in real world problems and challenges can be refining the creative problem solving abilities while also as long as exposure/ new perception. This proposed research paper goals to improve present educational system using Augmented Reality.
Differential evolution for filter feature selection based on information theory and feature ranking

© 2017 Elsevier B.V. Feature selection is an essential step in various tasks, where filter feature selection algorithms are increasingly attractive due to their simplicity and fast speed. A common filter is to use mutual information to estimate the relationships between each feature and the class labels (mutual relevancy), and between each pair of features (mutual redundancy). This strategy has gained popularity resulting a variety of criteria based on mutual information. Other well-known strategies are to order each feature based on the nearest neighbor distance as in ReliefF, and based on the between-class variance and the within-class variance as in Fisher Score. However, each strategy comes with its own advantages and disadvantages. This paper proposes a new filter criterion inspired by the concepts of mutual information, ReliefF and Fisher Score. Instead of using mutual redundancy, the proposed criterion tries to choose the highest ranked features determined by ReliefF and Fisher Score while providing the mutual relevance between features and the class labels. Based on the proposed criterion, two new differential evolution (DE) based filter approaches are developed. While the former uses the proposed criterion as a single objective problem in a weighted manner, the latter considers the proposed criterion in a multi-objective design. Moreover, a well known mutual information feature selection approach (MIFS) based on maximum-relevance and minimum-redundancy is also adopted in single-objective and multi-objective DE algorithms for feature selection. The results show that the proposed criterion outperforms MIFS in both single objective and multi-objective DE frameworks. The results also indicate that considering feature selection as a multi-objective problem can generally provide better performance in terms of the feature subset size and the classification accuracy. © This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Opportunities to utilize the potential of Augmented Reality to interact with photographic material in museum and archive collections

The use of Augmented Reality (AR) as an immersive and interactive engagement tool for art and cultural institutions is increasing. AR, when used in a meaningful way, has shown great potential for discovery-based learning experiences. My research considers the potential of AR for photographic collections in museums and archives by addressing two key questions. How can digital tools like AR serve to enhance our understanding of photographs as both object and image? What are the implications and limitations of this technology when used for this purpose? These questions are explored further in the form of a creative project that builds on how AR can be used to enhance interaction with photographic material in archives. These questions are explored further in the form of a creative project that builds on how AR combined with multimedia storytelling can be used to interact with photographic material in archives.
Multimedia push system based on a wellness slot machine

In an aged society, more than 80% of elders who are still healthy or sub-healthy people with self-care abilities, sociability and the society support system should access mental care which can be effectuated in a play therapy program. Based on electronic games supplemented by a media push system, the wellness slot machine practised in this study is a play therapy platform through which a preventive care service program for recreational effects and health promotion is planned for elders. For necessary information available to elderly participants of wellness slot machines such as ads for community activities and promotional films naturally and constantly, the multimedia push system in this study is designed and practised in a wellness slot machine with which the media content is pushed to the elderly participants actively without excessive manual operations.
Efficient Algorithm for Mining High Utility Item Sets

Efficient introduction of obvious things in savage datasets could be a key test for data mining. Assorted perspective for making high utility models have been held for the instigating years, and this raises different issues, for instance, the age of a more perceivable than common level of contender things for top utility things, and clearly wealth mining capacity to the degree speed and zone. The unessential tree structure that has beginning late been organized, i.e., FP-Tree and UP-Tree, holds information on get-together advancement and itemsets, mining results, and dependably abstains from checking the affirmed data. During this report to get a controlled far up-tree is seen, basically twofold checks the data to get the up-and-comer.
Information for Authors

Traditional face recognition method usually faces the challenge of varying lighting condition. In this paper, we propose an illumination-invariant local binary descriptor learning method for face recognition. Unlike local binary descriptor (LBP) and its variants, which usually utilize the rigid sign function for binarization despite of data distributions. We first determine a dynamic thresholds strategy including the information of illumination variation to extract nonlinear multi-layer contrast features. Specially, Exponential Discriminant Analysis (EDA) is designed to act as preprocessing which can contribute to improve the discriminative ability of the face image by enlarging the margin between different classes relative to the same class. To further improve the recognition performance, we combined our preliminary work, the adaptive fuzzy fusion framework, to integrate the recognition results for multi-scale features spaces. Extensive experiments conducted on four face databases validate the effectiveness of the proposed method for illumination face recognition.
Implementing Blockchain for trade facilitation

In 2018, a survey found that “65 per cent of responding enterprises with over 10,000 employees are considering or actively engaged in Blockchain deployment. This marks a significant rise from 2017, when the corresponding figure was 54 per cent.”
SUNTINGAN DOKUMEN BERBASIS WEB

Web-based document editing is a system for making scientific papers without having to adjust the format of writing scientific papers. Where in this system has provided a framework for entering journal contents. Journal article creation must follow the format already in place in the organization, such as font size, edge size, and so on. Often in writing journals, writers experience difficulties or constraints in the format of writing, so they often experience errors in writing journal articles. For this reason, it is necessary to have a standard web journal writing program, which provides a framework for the format of journal writing. The process carried out in designing this application is by looking at the guidelines for journal manuscript writing, with these guidelines the writer can know how the journal format will be translated into a program script. The purpose of this research is to design a standard web program for editing documents in journals and to assist journal authors / journal authors in making scientific papers online. In this research, the writer made a document editing system for scientific journal writing format using PHP and MySQL in the application system. Where in the system designed the author only includes the entries of each input in the journal framework. In this system all the input that is filled in is stored in a database with different tables. And when the author sees the contents of the journal, the display on the journal contents automatically matches the journal template.
A Deep Neural Network for face Recognition

Face recognition is used to biometric authentication method to analyze the face extract and photographs useful to reputation formation from them, which can be usually called as a characteristic vector this is used to differentiate the organic features. In this paper to detect the suspect by extracting facial features from the captured image of the suspect from CCTV and match it with the pictures stored in the database and also to achieve an accuracy rate of 100 %, negligible loss using deep learning technique. For extracting the facial features, we are using deep learning model known as Convolutional Neural Network (CNN). It is one of the best models to extract features with the highest accuracy rate .