Reviewerly/exHarmony huggingface dataset:
Strategies for the Near Term

This chapter focuses on developing a practical and accurate assessment of the current information management situation. The chapter explains how to formulate and conduct an information audit that is business-relevant, credible, and trustworthy. The chapter also considers how to document and communicate the audit results to the business.
Preparing Data for Analysis

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.
Economic Evaluation of Placer Gold Along River Indus From Ghazi to Kund, Khyber Pakhtunkhwa, Pakistan: Implications for Commercial Scale Pilot Plant

A detailed study was conducted on Indus river in order to evaluate the economic potential. Samples werecollected for geochemical studies from both stream sediments (SS) and heavy mineral concentrates (HMC) along Indusriver from Ghazi, Hund, Beka, Alladher and Kund in Khyber Pakhtunkhwa province. All the samples were analyzed forgold (Au), silver (Ag) and base metals in order to get information about geochemical associations. Panning and sluicemethods were applied for the collection of these samples and extraction of visible gold. Results show that HMC havehigh Au contents, having maximum value of 44.15 g/t and 39.15 g/t in Kund and Beka areas respectively with anaverage value of 15.18 g/ton and 11.37 g/ton while the SS have average amount of Au as 0.8 g/t. In both these mediahigher concentration of gold was found in HMC. On the basis of results from both sampling media, the placer golddeposits in Kund, Alladher and Beka are considered highly economical for the commercial exploration of placer gold.Overall, the HMC derived from silt, sand, gravels and cobbles along Indus river indicated potential for placer gold thatcan be utilized for extraction of gold at commercial scale.
Performance Analysis of Multi Scale Applications on Cloud Systems

Cloud Computing is the most adoptable technology in use recently where bigger and complex applications are deployed and used on cloud server. Multi scaled applications are such applications which have multiple attributes (data size, number of requests, number of concurrent users etc.) that can cause to poor performance of its application service. For better performance, it needs to be measured, analyzed and optimized using tools, strategies or algorithms. The multi scale application’s performance is measured at end user level, network level and data center level. In this paper, the focus is measuring the performance of multi scale applications in terms of response time and throughput using CloudAnalyst simulator. Multiple scenarioslike varying data size,varying number of concurrent users and varying number of requests are simulated for multiscale application and tested.The results obtained shown that response time and throughput of application gets reflected mostly by Data Size, number of requests per user and number of concurrent users. It is also observed that the most significant factor is data size along with huge volume of concurrent users, impacts the response time of multi scale application.Hench this research recommends that multi scale data I.e. data type and data size plays vital role in cloud based multi scale application’s performance measurement.
A two-qudit operation on a 256-dimensional Hilbert space

By encoding two 16-dimensional qudits in the time and frequency degrees of freedom of a heralded single photon, we realize a deterministic photonic two-qudit SUM gate operating on a 256-dimensional Hilbert space.
Getting to Know Your Data

An R Companion for the Third Edition of The Fundamentals of Political Science Research offers students a chance to delve into the world of R using real political data sets and statistical analysis techniques directly from Paul M. Kellstedt and Guy D. Whitten's best-selling textbook. Built in parallel with the main text, this workbook teaches students to apply the techniques they learn in each chapter by reproducing the analyses and results from each lesson using R. Students will also learn to create all of the tables and figures found in the textbook, leading to an even greater mastery of the core material. This accessible, informative, and engaging companion walks through the use of R step-by-step, using command lines and screenshots to demonstrate proper use of the software. With the help of these guides, students will become comfortable creating, editing, and using data sets in R to produce original statistical analyses for evaluating causal claims. End-of-chapter exercises encourage this innovation by asking students to formulate and evaluate their own hypotheses.
Report of the Death of the Catalog Is Greatly Exaggerated: The E-Journal Access Journey at the University of Tennessee

Kay Johnson and Maribeth Manoff described the various ways in which the University of Tennessee Libraries provide e-journal access to its patrons. The early history of e-journal cataloging at UTL was given followed by the methods currently used. Notes, fields, and subfields used in the bibliographic records, and the E-Journal Wizard, which was developed by UTL personnel, were explained in detail. Johnson and Manoff gave an excellent description of how article aggregated and title aggregated databases are handled via Hooks-to-Holdings. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: &lt;docdelivery@haworthpress.com&gt; Website: &lt;http://www.HaworthPress.com&gt;]
Hybrid and Decentralized Privacy Preservation using D-Anonymity and T-Closeness in Social Network

Although Social Network (SN) knowledge is significant assets for data examination, freeing the data to the general public could reason an invasion of privacy. Privacy insurance is taken a lot of seriously than various data mining duties. The privacy problems are dealt with by several algorithms and strategies in the literature. But, perpetually there exists a trade-off between privacy and data.Our objective in this work is to design and develop a privacy-preserving solution for the social network. We have used K-anonymity and T-closeness algorithm and data anonymization. Further, data anonymization is decentralized by giving control of anonymization to the data owner. The solution is implemented on a dummy social network for testing the effectiveness of the privacy preservation solution proposed by us.
Classification

In this chapter, we will investigate the issue of automatic selection of ensemble components. The presented methodology allows guaranteeing, that a new component will be included into an ensemble only if it significantly improves the performance of the ensemble, not only for a current chunk of data but also for the whole stream. Additionally, the extension of this method dedicated to deal with special types of concept-drift is presented. The introduced modification allows increasing the diversity of the ensemble components. The problem of selection component is an essential issue for every ensemble algorithm [1–8], however, only few of them are not heuristic procedures [9, 10].
Secure and Fast Biometric Verification Scheme for Cloud Storage Systems

Biometric verification of has turned out to be progressively well known as of late. With the improvement of cloud computing, database owners are enthused to outsource the enormous size of biometric information and verification activity to the cloud to dispose of the costly capacity and calculation costs, which anyway carries potential dangers to clients' security. This article presents an proficient and protection saving biometric verification outsourcing plan. In particular, the biometric information is encoded and redistributed to the cloud server. To execute a biometric verification, the database owner encodes the query information and submits it to the cloud. The cloud performs verification tasks over the encoded database and returns the outcome to the database owner. A careful security examination shows the proposed plan is secure regardless of whether aggressors can produce verification demands and intrigue with the cloud. Contrasted and past conventions, trial results demonstrate the proposed plan accomplishes a better presentation in both preparation and verification systems.
Multiclass Analyzer for Movie Sentiments using Machine Learning Techniques

Gigantic volumes of content information are open in web. The fundamental rich assets of sentiments are from discussions, website evaluations, news and blog. Our point is to group the slants of clients focuses at mining the surveys of clients for a motion picture by removing the information naturally and characterize the conclusions into positive or negative sentiments. With the brisk making of Internet applications, incline course of action would have colossal opportunity to help people customized assessment of customer's notions from the web information. Customized feeling mining will benefit to the two clients and sellers.Up to now, it is as yet an entangled assignment with incredible test. Specifically, there is an abundance of content written in regular language accessible online that would turn out to be significantly more helpful to us were we ready to viably total and process it consequently by using the NLP techniques. The comments are pre-processed using NLP techniques like tokenization, stop word removal &amp; stemming.Machine learning algorithms are used in opinion mining for product review data set to train the system based on the rules of the algorithm utilized where it is tested with test data set, both these train &amp; test data sets are labelled unbalanced opinions.
LinProT: the Feasibility of a Multimedia Courseware for Optimization Methods Course

LinProT is an educational courseware for Optimization Methods. LinProT consists of a multimedia package; short video tutorials and scanned pictures QR Code Reader and HP Reveal as Augmented Reality (AR) application. There are three types of modules of Optimization Methods that contain in LinProT courseware, which are notes module, exercises module and tutorial video modules. Users can enjoy new experiences of learning via courseware involving AR application and reduce frustration in learning through boring reading. The objectives in developing LinProT are to produce courseware that allows self-directed learning that meets the needs of students studying Optimization Methods course and to assess its feasibility. This courseware is developed using the ADDIE model that involves five phases; Analysis, Design, Development, Implementation and Evaluation. The researchers tested the feasibility of the courseware to students via questionnaire. LinProT is a new way of learning, promotes interaction, provides experiences, and will improve learning efficiency in terms of time and place.
Creation of a New Generation of Teaching Literature - A Requirement of Modernity

The article is devoted to creation of a new generation of teaching literature, in which the actuality of creation of a new generation of teaching literature, the modern teaching book and its creation as a essential requirement of the modernity, didactic requirements for creation of a new generation of teaching and teaching methodical literature and mechanisms of their creation, criterion and indicators of estimation of quality of teaching and teaching methodical literature, creation of a new generation of teaching literature for newly instituted directions of education
Confidential Health Care Data Exchange Between Multiple Entities in Cloud using Block Chain

Data in the cloud is leading to the more interest for cyber attackers. These days’ attackers are concentrating more on Health care data. Through data mining performed on health care data Industries are making Business out of it. These changes are affecting the treatment process for many people so careful data processing is required. Breaking these data security leads to many consequences for health care organizations. After braking security computation of private data can be performed. By data storing and running of computation on a sensitive data can be possible by decentralization through peer to peer network. Instead of using the centralized architecture by decentralization the attacks can be reduced. Different security algorithms have been considered. For decentralization we are using block chain technology. Privacy, security and integrity can be achieved by this block chain technology. Many solutions have been discussed to assure the privacy and security for Health care organizations somehow failed to address this problem. Many cryptographic functions can be used for attaining privacy of data. Pseudonymity is the main concept we can use to preserve the health care means preserving data by disclosing true identity legally.
SPICA: a Methodology for Reviewing and Analysing Fault Localisation Techniques

The International Conference on Software Maintenance and Evolution is the premier international forum for researchers and practitioners from academia, industry, and government to present, discuss, and debate the most recent ideas, experiences, and challenges in software maintenance and evolution.
Hybrid deep-learning based reduced order models for the coupled fluid-structure dynamics of physics-based digital twins

Machine Learning (ML) and Digital Twins (DT) are at the heart of today’s different industries, ranging from advanced manufacturing to biomedical systems to resilient ecosystems, civil infrastructures, smart cities, and healthcare. They have become indispensable for solving complex problems in science, engineering, and technology development. The purpose of the MMLDT-CSET 2021 conference is to facilitate the transition of ML and DT from fundamental research to mainstream fields and technologies through advanced data science, mechanistic methods, and computational technologies. This 3-day conference features technical tracks of emerging ML-DT fields and applications, special public lectures, short courses, and demonstrations. The conference will be held in a hybrid format, featuring both on-site and virtual sessions.
The influence of lexical characteristics and talker accent on the recognition of English words by speakers of Korean

A number of recent studies have examined whether English-language learners (ELLs) and native speakers of English (NS) show the same effects of lexical (word frequency [WF] and phonological neighborhood density [PND]) and indexical (speaker accent) factors on word recognition accuracy and speed. The motivation behind this work is to understand how different types of linguistic knowledge emerge over the course of learning an L2. Two recent studies, Imai et al. (2005) and Yoneyama and Munson (2017) used nearly identical methods and stimuli with two groups of ELLs: those whose first language (L1) was Spanish (Imai et al.) and those whose L1 was Japanese (Yoneyama and Munson), and found very different effects of PND on word-recognition accuracy. In this project, we use the methods reported by Imai et al. and stimuli on a third group of ELLs, those who L1 was Korean. In a preliminary report on this project (Choi et al., 2018), we found evidence that the Korean L1 ELLs performed more similarly to the Japanese L1 ELLs in Yoneyama and Munson. However, these conclusions were based on data from a small group of relatively high-proficiency ELLs. In the current study, we report the results of a larger group of ELLs, including lower-proficiency individuals.
Preface from the editors

It is our truly pleasure to present the 2017 BASIC proceeding. The conference was successfully organized by Faculty of Mathematics and Natural Sciences, Universitas Indonesia in collaboration with Commission for Basic Science-Indonesian Academy of Sciences (KIPD-AIPI) on 18–19 August 2017. The event provides a network for academics and researchers from the fields of mathematics and natural sciences to share their ideas and experiences, update themselves with the latest developments on basic and applied research, also encourage collaboration between researchers or institutions that can enhance the synergy of basic research with applied research to advances in science and technology. The 2017 BASIC event conducted in conjunction with the 2nd International Science and Mathematics in Academics Research Talks 2017 (2nd ISMART 2017). The contribution of the keynote and invited speakers at the morning plenary sessions was greatly appreciated. They have made their best efforts to deliver their ideas and share knowledge with the participants. No less than 160 contributors have presented their papers - all of which maintain the high promise suggested by the abstract. This conference proceeding volume consists of rigorously selected papers, which have been accepted, after undergoing a peer-review process, conducted by expertise reviewers. Our in-depth appreciation goes to our colleagues on the international advisory board, and the scientific committee for all efforts in selecting abstracts, papers and sharing their expert networks, to the experts in reviewing the paper and to the editorial teams (substantive, language and technical) in providing camera-ready version to send to the publisher. We are grateful for the efforts of the organizing committee, the support of the steering committee, and the financial support from Universitas Indonesia. Finally, we thank all participants and authors for their contributions. Depok, October 2019 Editors, Djoko Triyono Anny Sulaswaty Ivandini T Anggraningrum
Orders &amp; Contracts

This paper develops an adaptive robust combination of feedback linearization (FL) and sliding mode controller (SMC) based on fuzzy rules and gradient descent laws. The new suggested control algorithm is tested to stabilize a fourth-order under-actuated nonlinear inverted pendulum system. More precisely, the reliable feedback linearization approach and the robust SMC controller are combined to design a stable control effort. In order to enhance the performance of the suggested controller, an adaptation technique as long as fuzzy rules are applied to update the control gains and the boundary layer parameter. Then, a novel evolutionary algorithm termed multi-objective ant lion optimizer (MOALO) is implemented to determine the control coefficients. The analysis and results conducted on the inverted pendulum system demonstrate the desired performance of the proposed control scheme by providing an optimal smooth control input, suitable tracking performance, and proper time responses.
Ontology Formation and Comparison for Syllabus Structure Using NLP

Ontologies are largely responsible for the creation of a framework or taxonomy for a particular domain which represents the shared knowledge, concepts and how these concepts are related with each other. This paper shows the usage of ontology for the comparison of a syllabus structure of universities. This is done with the extraction of the syllabus, creation of ontology for the representing syllabus, then parsing the ontology and applying Natural language processing to remove unwanted information. After getting the appropriate ontologies, a comparative study is made on them. Restrictions are made over the extracted syllabus to the subject “Software Engineering” for convenience. This depicts the collection and management of ontology knowledge and processing it in the right manner to get the desired insights.
A two-stage underwater image enhancement method

Scattering and absorption result in color shift and low visibility of underwater images. To handle the mentioned issues, this paper proposes a two-stage underwater image enhancement method. In the first stage, this paper proposes a piece-wise linear stretching method to remove the color shift. In the second stage, this paper introduce a contrast enhancement method based on local mean value to improve the contrast and detail of the output image, which uses a sliding window to enhance each pixel value by scanning pixel-by-pixel. Experiments on a real-world underwater image enhancement dataset demonstrate that the proposed method outperforms several state-of-the-art methods in qualitative and quantitative.
The Effectiveness of Question and Answer Technique in Teaching Reading Comprehension at SMP Negeri 3 Ratahan

This research was conducted with the purpose to develop students’ reading comprehension of descriptive text through question and answer technique. This study is classified as quantitative through pre-experimental design with one group pre-test and post-test design. The population of this research is the students of SMP Negeri 3 Ratahan. It was limited only to the second year studens. There were 30 students. The data were collected through test. The first test is pre-test, the teacher intends to know the students’ reading comprehension without using question and answer technique. The second test is post-test in which the teacher has used question and answer technique in teaching reading comprehension. The result shows that the scores of the students in post-test are higher then those in pre-test. This is shown by the mean score of pre-test which is 5.5 and mean score of post-test which is 7.8
A Precise Framework for Source-Level Control-Flow Analysis

Welcome to the 21st IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2021)! We hope that you enjoy the conference and that it will inspire you in your future research. Should you require a certificate of participation please contact Alexander Serebrenik, the general chair of SCAM, at a.serebrenik@tue.nl. For questions related to the Morressier virtual platform please contact support@morressier.com.
Introduction to the Minitrack on Software Development for Mobile Devices, Wearables, and the Internet-of-Things

Applications for mobile devices (apps) have facilitated the success of smartphones and tablets.By using apps, the multi-purpose hardware of modern devices can be utilized to the full extent.Despite much progress with regard to development methods, software development kits, and frameworks, app development poses many challenges.This is even truer for novel mobile devices such as wearables and for the hardware that constitutes the Internet-of-Things (IoT).Compatibility, performance, battery-saving, security, and testing are only some of the issues that are mainly driven by the quality of the used software.A satisfying level of this quality in many cases is very hard to achieve.