Reviewerly/exHarmony huggingface dataset:
Postcondition-preserving fusion of postorder tree transformations

Tree transformations are common in applications such as program rewriting in compilers. Using a series of simple transformations to build a more complex system can make the resulting software easier to understand, maintain, and reason about. Fusion strategies for combining such successive tree transformations promote this modularity, whilst mitigating the performance impact from increased numbers of tree traversals. However, it is important to ensure that fused transformations still perform their intended tasks. Existing approaches to fusing tree transformations tend to take an informal approach to soundness, or be too restrictive to consider the kind of transformations needed in a compiler. We use postconditions to define a more useful formal notion of successful fusion, namely postcondition-preserving fusion. We also present criteria that are sufficient to ensure postcondition-preservation and facilitate modular reasoning about the success of fusion.
Breaking the Curse of Visual Analytics: Accommodating Virtual Reality in the Visualization Pipeline

Previous research has exposed the discrepancy between the subject of analysis (real world) and the actual data on which the analysis is performed (data world) as a critical weak spot in visual analysis pipelines. In this paper, we demonstrate how Virtual Reality (VR) can help to verify the correspondence of both worlds in the context of Information Visualization (InfoVis) and Visual Analytics (VA). Immersion allows the analyst to dive into the data world and collate it to familiar real-world scenarios. If the data world lacks crucial dimensions, then these are also missing in created virtual environments, which may draw the analyst’s attention to inconsistencies between the database and the subject of analysis. When situating VR in a generic visualization pipeline, we can confirm its basic equality compared to other mediums as well as possible benefits. To overcome the guarded stance of VR in InfoVis and VA, we present a structured analysis of arguments, exhibiting the circumstances that make VR a viable medium for visualizations. As a further contribution, we discuss how VR can aid in minimizing the gap between the data world and the real world and present a use case that demonstrates two solution approaches. Finally, we report on initial expert feedback attesting the applicability of our approach in a real-world scenario for crime scene investigation.
Outlier Detection for Transformer's Oil Chromatographic Data Based on Metric Learning and the Weighted Local Outlier Factor

Detecting the outliers for transformer's oil chromatographic data is very important for analyzing and monitoring the status of a transformer. However, the existing methods are usually developed for some specific situations and may not perform well in many cases. In this paper, we proposed an outlier detection method based on metric learning and weighted local outlier factor (WLOF). We firstly considered the data as points in the high dimensional space and learning a Mahalanobis matrix according to a training set. And then we used WLOF to assign the degree of being an outlier for every point. Metric learning can make a regularization and reduce the correlation between different components of a vector. And WLOF method can detect the outliers accurately even there are many duplicate data points. Results on the real data set showed that the proposed method performs well in outlier detection even the different components of a vector are not similar in scale and have strong correlations.
Optimal Design of Mechanical Press Mechanism for Experiment Teaching

A novel toggle type of mechanical press mechanism for experiment teaching was optimized. The kinematic model of the mechanical press was established by the complex vector method. By doing so, expressions of the displacement, velocity, and acceleration of a slider were deduced. According to the kinematic model, the optimization model of the mechanism was obtained by the genetic algorithm for minimizing the top speed and velocity fluctuation during the operating stroke. The working velocity of the press was low and uniform. Compared with the original data, the maximum displacement, stretch angle, quick return characteristic, and maximum acceleration have been improved after optimization, which proves that the design requirements have been achieved.
Caveats in Eliciting Mobile App Requirements

Factors such as app stores or platform choices heavily affect functional and non-functional mobile app requirements. We surveyed 45 companies and interviewed ten experts to explore how factors that impact mobile app requirements are understood by requirements engineers in the mobile app industry. We observed a lack of knowledge in several areas. For instance, we observed that all practitioners were aware of data privacy concerns, however, they did not know that certain third-party libraries, usage aggregators, or advertising libraries also occasionally leak sensitive user data. Similarly, certain functional requirements may not be implementable in the absence of a third-party library that is either banned from an app store for policy violations or lacks features, for instance, missing desired features in ARKit library for iOS made practitioners turn to Android. We conclude that requirements engineers should have adequate technical experience with mobile app development as well as sufficient knowledge in areas such as privacy, security and law, in order to make informed decisions during requirements elicitation.
Robust Mahalanobis Metric Learning via Geometric Approximation Algorithms

Learning Mahalanobis metric spaces is an important problem that has found numerous applications. Several algorithms have been designed for this problem, including Information Theoretic Metric Learning (ITML) [Davis et al. 2007] and Large Margin Nearest Neighbor (LMNN) classification [Weinberger and Saul 2009]. We study the problem of learning a Mahalanobis metric space in the presence of adversarial label noise. To that end, we consider a formulation of Mahalanobis metric learning as an optimization problem, where the objective is to minimize the number of violated similarity/dissimilarity constraints. We show that for any fixed ambient dimension, there exists a fully polynomial-time approximation scheme (FPTAS) with nearly-linear running time. This result is obtained using tools from the theory of linear programming in low dimensions. As a consequence, we obtain a fully-parallelizable algorithm that recovers a nearly-optimal metric space, even when a small fraction of the labels is corrupted adversarially. We also discuss improvements of the algorithm in practice, and present experimental results on real-world, synthetic, and poisoned data sets.
Security Issues Due to Vulnerabilities in the Virtual Machine of Cloud Computing

The virtual machine is a medium for provisioning cloud resources to customers. Cloud customers are accountable for configuration and security of the applications and the operating system running on virtual machines. The responsibilities of cloud customers include inbound and outbound traffic flow, access control, security configuration and practices. This work analyzes the vulnerabilities inside the virtual machine and security threats engendered due to it. Some of the security threats on a virtual machine are demonstrated with practical implementation on Amazon Web Service (AWS) as a cloud service provider. This paper also discusses general defense mechanisms for these security threats in a virtual machine.
A collaborative method for identification and prioritization of data sources in MDRE

Requirements engineering (RE) literature acknowledges the importance of stakeholder identification early in the software engineering activities. However, literature overlooks the challenge of ident ...
Recognizing Handwritten Mathematical Expressions as LaTex Sequences Using a Multiscale Robust Neural Network

In this paper, a robust multiscale neural network is proposed to recognize handwritten mathematical expressions and output LaTeX sequences, which can effectively and correctly focus on where each step of output should be concerned and has a positive effect on analyzing the two-dimensional structure of handwritten mathematical expressions and identifying different mathematical symbols in a long expression. With the addition of visualization, the model's recognition process is shown in detail. In addition, our model achieved 49.459% and 46.062% ExpRate on the public CROHME 2014 and CROHME 2016 datasets. The present model results suggest that the state-of-the-art model has better robustness, fewer errors, and higher accuracy.
JAVANESE GRADED READING BOOKS FOR ELEMENTARY SCHOOL STUDENTS

This research was intended to develop graded readers (graded reading books) in the Javanese language for elementary school students. To develop the products, this work usedthe R&amp;D model by Borg and Gall, in which the main procedure was composed of product analysis, product development, expert validation, trials, and product revision. The subjects of this research were the elementary school students and the teachers of Bantul Regency, Sleman Regency, the City of Yogyakarta; experts in the Javanese language;experts in teaching and learning; and experts inteaching and learning media. The sample respondents were obtained through purposive sampling and the data were collected through questionnaires, observations, and interviews. The data were analyzed qualitatively and quantitatively. The products were validated by experts in learning contents, experts in teaching and learning, and experts in teaching and learning media. The result shows that they rated the products very good. The results of questionnaires distributed amongthe teachers and students show that these products carry positive impact on student learning.It can be concluded that the graded reading books are highly recommended for learning activitiesin elementary schools that offer Javanese.
Fast and linear-time string matching algorithms based on the distances of $q$-gram occurrences

Given a text $T$ of length $n$ and a pattern $P$ of length $m$, the string matching problem is a task to find all occurrences of $P$ in $T$. In this study, we propose an algorithm that solves this problem in $O((n + m)q)$ time considering the distance between two adjacent occurrences of the same $q$-gram contained in $P$. We also propose a theoretical improvement of it which runs in $O(n + m)$ time, though it is not necessarily faster in practice. We compare the execution times of our and existing algorithms on various kinds of real and artificial datasets such as an English text, a genome sequence and a Fibonacci string. The experimental results show that our algorithm is as fast as the state-of-the-art algorithms in many cases, particularly when a pattern frequently appears in a text.
Hirschfield, E - Biographical entry - Index to the AMA archive

Hirschfield, E - Biographical entry - Index to the AMA archive - NAME is a biographical, bibliographical and archival database of SUBJECT with links to related articles and images. ADD MORE DESCRIPTION AS REQUIRED
BLENDED LEARNING APPROACH IN TEACHING WRITING RECOUNT TEXT

This research is aimed to examine the use of WhatsApp Messenger as blended learning and how it could help the students to improve their ability in writing recount text and to know the student ’s attitude toward using WhatsApp Messenger in writing recount text. Participants were 20 second-year students of State Junior High School 7 Metro. The researcher uses descriptive quantitative and designs the instruments, they are questionnaire and writing test. Data were gathered from a survey conducted on 20 respondents. The pre-post test was conducted to know the improvement of the students’ ability in writing recount text. The result of the research shows that the number of the students who get a score at least 75 is 18 students (90%) and the students’ attitude towards WhatsApp and its convenience/ease of use it are all at the very high level,17 students (85%) were strongly agree . The findings of the study suggested that the use of WhatsApp as blended learning is significant in helping the students writing better. This study implies that the usage of WhatsApp should be encouraged to the students and institutions should provide internet facilities as a top priority in today’s education.
Bounding the expected run-time of nonconvex optimization with early stopping

This work examines the convergence of stochastic gradient-based optimization algorithms that use early stopping based on a validation function. The form of early stopping we consider is that optimization terminates when the norm of the gradient of a validation function falls below a threshold. We derive conditions that guarantee this stopping rule is well-defined, and provide bounds on the expected number of iterations and gradient evaluations needed to meet this criterion. The guarantee accounts for the distance between the training and validation sets, measured with the Wasserstein distance. We develop the approach in the general setting of a first-order optimization algorithm, with possibly biased update directions subject to a geometric drift condition. We then derive bounds on the expected running time for early stopping variants of several algorithms, including stochastic gradient descent (SGD), decentralized SGD (DSGD), and the stochastic variance reduced gradient (SVRG) algorithm. Finally, we consider the generalization properties of the iterate returned by early stopping.
Il Discovery tool è un organismo in crescita

EnglishThis article sums up two years of work selecting, configuring and promoting a discovery tool. Our choices were based on our circumstances and might not be right for every library. However, they led us to a state of things which we find satisfactory, and which we are going to improve further. That is why we wish to share them with colleagues who face the same challenges daily, hoping our experience can be of help. italianoQuesto articolo vuole essere il resoconto della nostra esperienza nella scelta, implementazione, configurazione e promozione di un discovery tool. Le nostre scelte sono basate sulla situazione della nostra biblioteca e potrebbero non adattarsi a tutti; ci hanno pero portati ad un risultato soddisfacente e che abbiamo intenzione di migliorare ulteriormente. Per questo motivo vorremmo condividere il lavoro fatto con altri, nella speranza che qualcuno lo trovi utile.
Visualising Spatial Complexity of Urban Sites

Recent research has linked urban design to artistic practice, and it is suggested that urban design could become refocused if conceived of as an integrative art of place.However, the urban design research methods literature is silent on the topic of artistic practice, and therefore the potential for interpretative, abductive knowledge to emerge from creative visualisation in urban design is under-appreciated.More specifically, regarding evaluation for urban design, complexity theories of cities claim that understanding complexity in particular enhances our ability to organise knowledge in relation to cities, and it is further argued that complexity theory responds to a need for a knowledge leap in planning, design and maintenance of cities, to rise to global urban challenges and crises.In this context, visualising spatial complexity of urban sites through artistic practice is useful to urban design.The specifically spatial complexity of urban sites, (as the spatial component of urban complexity), has not previously been explored, evaluated or visualised for urban design.This paper argues that in creatively visualising spatial complexity, multi-scalar, relational and temporal aspects of the urban built environment can be captured, and this visualisation communicates a unique 'signature' of each urban site.
KISALTMALARIN OTOMATİK ÇEVİRİ YOLUYLA AKTARIMI

The rapid progress of technology has paved the way for a number of innovations in the field of translation as well as in many fields. In the past, most of the translation services of human translators are now performed automatically by machines. However, the accuracy of semantic and content translations of some translations with automatic translation systems is still a matter of debate. Because the lack of interpretation of machines compared to human translators seems to be the most significant deficiency of the automatic translation process. In addition, the proportion of the syntactic and formal similarities and differences between the source language and the target language are among the factors affecting the quality of automatic translation. For example, if an element in the source language does not have an equivalent in the target language or if it has a different format, it may cause incorrect translation in the automatic translation process. Abbreviations can be given as examples for this situation. Because the forms and types of abbreviations can vary according to languages, these differences in translation can lead to difficulties. The aim of this study is to examine the transfer of abbreviations through automatic translation. This is based on the Turkish and French language pairs. In the first part of the study which consists of two chapters, firstly, the types of abbreviations in both languages and the forms of forming abbreviations are briefly mentioned. In the second part, the abbreviations used in the national and international fields were translated from French to Turkish and vice versa on automatic translation systems. In order to determine whether there is a difference in the context of the transmission of abbreviations by automatic translation, translation was performed in two stages. In the first step, the abbreviations in the sentence are translated and then the same abbreviations are translated independently of the sentence. Then, the abbreviation translations performed in both stages are shown in tables and examined comparatively. From this review, determinations and evaluations about the transfer of abbreviations through automatic translation systems are given. As a result, it was found that the translations of the abbreviations on the automatic translation from Turkish to French and vice versa were performed correctly, but in some cases deficiencies occurred. In order to support this, in the last section, the comparison of the names and abbreviations of some international organizations in Turkish and their use in French has been compared.
A NOVEL APPROACH TO THE INFORMATION SECURITY USING RC4 AND LSB TECHNIQUES

Steganography is the art of hiding data within data where it is an encryption technique that can be used along with cryptography as an extra-secure technique to secure data. The security of information can be prospered by using encryption and steganography. In cryptography, at first the original form of data is encrypted into another form and then it is transferred. The proposed system improves the security system by combining these two techniques. In this system, the encrypted data is embedded in a BMP/JPEG image file and intends for data confidentiality, data authentication and data integrity. Data is encrypted with RC4 encryption algorithm and then embedded the encrypted data in the BMP/JPEG image file using LSB steganographic method where the primary goal of this system could be attained.
Big Data Security Issues in Networking

As of now with the advantages of big data in many fields like Business, E-Commerce, Social Media, networking and so on, approach in this paper concentrates on security issues which our future is going to face if they are not encountered today, especially in security of public, private data. Data may be available publicly to all or it may be some confidential known to very few systems or persons. Big data technology makes use of massive datasets being flown through social media websites and many other sources, analyses it and make pro-intelligent decisions i.e., immature output that is not completely accepted it may violate the privacy concern of a company or system or it may be an individual. So it’s our today’s responsibility to maintain data confidentiality and data integrity together so that we will not face such problems in future. We propose some of important, major security issues that will emerge today or tomorrow.
Cataloguing in the digital epoch: B. N. Yeltsin Presidential Library’s experience

The digital cataloguing experience of Presidential Library is discussed. The integrated e-collection comprises digital copies of library materials, archival documents and museum objects, which requires designing methods for describing entries new to library preservation. The Presidential Library’s interdepartmental working group has developed principles and approaches toward integrating presentation and access to the library, archival, and museum resources into the single catalog in accordance with existing international standards. The Presidential Library acts as a methodological center developing special methods for describing diverse information resources. Methodological publications by Presidential Library are considered the logical extension of RUSMARC Application Examples guidance series intended for Russian bibliographizing institutions. The Presidential Library’s work within the framework of the National Standardization Program, National Electronic Library and the union catalog of electronic resources is also discussed. The Library participates in IFLA UNIMARC permanent committees and IFLA Subject Analysis and Access Section. The Presidential Library is an educational center for digital content cataloguing for libraries, and holds training work-shops. It enrolls university graduates in generating the descriptive metadata. The prospective vectors in cataloguing are examined, e. g. designing model description of digital collections and Metadata Encoding and Transmission Standard (METS) implementation.
CLARA: Clinical Report Auto-completion

Generating clinical reports from raw recordings such as X-rays and electroencephalogram (EEG) is an essential and routine task for doctors. However, it is often time-consuming to write accurate and detailed reports. Most existing methods try to generate the whole reports from the raw input with limited success because 1) generated reports often contain errors that need manual review and correction, 2) it does not save time when doctors want to write additional information into the report, and 3) the generated reports are not customized based on individual doctors' preference. We propose {\it CL}inic{\it A}l {\it R}eport {\it A}uto-completion (CLARA), an interactive method that generates reports in a sentence by sentence fashion based on doctors' anchor words and partially completed sentences. CLARA searches for most relevant sentences from existing reports as the template for the current report. The retrieved sentences are sequentially modified by combining with the input feature representations to create the final report. In our experimental evaluation, CLARA achieved 0.393 CIDEr and 0.248 BLEU-4 on X-ray reports and 0.482 CIDEr and 0.491 BLEU-4 for EEG reports for sentence-level generation, which is up to 35% improvement over the best baseline. Also via our qualitative evaluation, CLARA is shown to produce reports which have a significantly higher level of approval by doctors in a user study (3.74 out of 5 for CLARA vs 2.52 out of 5 for the baseline).