Reviewerly/exHarmony huggingface dataset:
Creating a Buzz around Corporate Reputation with Beeswarm Plots

Polecat is a technology company that helps organisations manage their corporate reputation. Typically, our clients want to compare themselves to their competitors, but are uncomfortable with charts that look 'too statistical'. We discuss how we responded to this challenge by designing and testing a beeswarm plot, which will be added to Polecat's application, called RepVault.
GGP Technical Case &amp;amp; E-Needs

This deliverable is designed to evaluate the current technical state of the GGP infrastructure and possible amendments and developments that can help increase its performance as part of its infrastructural development. It outlines a technical evaluation that will be used to adapt the fieldwork and implementation guidelines and enable the initiation of a new round of GGP. This technical evaluation will also help inform planning elsewhere such as the requirements for financing and governance structures within the GGP, as well as the capacity of the GGP to increase its socio-economic and scientific impact.
Physical Security Concepts and Applications

What is “physical security planning?” It is a recognized security process that, if followed, will result in the selection of physical countermeasures based on risk, threat, vulnerability, and consequence. The selected countermeasures should also be justifiable from a cost point of view. In other words, there is a return on investment for the countermeasures implemented which are realized in the prevention of criminal incidents, injury, or death to people, theft of property, and harm to reputation.
Assessment and statistical analysis of global radiation by decomposing it to its direct and diffse components

In this work, hourly measurements of global solar irradiances obtained from a pyranometer and direct normal irradiances obtained from sunshine duration sensor are assessed through an extensive quality control procedure and statistical analysis on the measured and derived solar parameters for a semimountainous location using data from the last fie years (2016-2020). This information and the method suggested concerning the solar energy capture systems and energy efficiency is useful for engineers who can therefore take knowledge of the local radiation levels. Furthermore, the direct horizontal irradiance canbe easily calculated and the diffuse component can be estimated from the difference of global and direct horizontal irradiances. Monthly mean hourly values of the radiation components are also estimated and shown through isolines diagrams. Representative values of global direct and diffuse irradiances for different times of the year and different hour of the day can be easily read from these diagrams. Simultaneously, a similar analysis is carried out over various solar indices estimated on both an hourly and daily basis. The derived solar indices are the clearness index for global, direct, and diffuse radiation as well as the diffuse and direct fractions from global radiation. The interrelationships between the said indices are also examined.Additionally, the BRL (Boland-Ridley-Lauret) diffuse fraction model which is a multiple predictor logistic model was tested and can be used to estimate the diffuse and later the direct radiation component. The model is a function of clearness index (kt), the apparent solar time (AST), the solar altitude (αs), the daily clearness index (KT) and persistence parameter ψ which is an average of both a lag and lead of the clearness index. The outcome of the model shows that it can be used to estimate successfully the diffuse radiation.
The Impact of Blockchain in Smart Government Services

Nowadays, blockchain technology is attracting massive attentions and trigger multiple projects. This research work aim at illustrating and analyzing the technology of blockchain and describe the different uses for it. Moreover, it discuss how technology impact the service sectors in industries by enhancing the quality of their services.
Petri net model for resource scheduling with auto scaling in elastic cloud

Cloud service vendors offer wide range of services in a pay per use paradigm to the customers. The aim of cloud resource management is to speed up the execution of tasks and efficient usage of computing resources. The main benefit of optimal scheduling policy is reduced makespan, energy as well as cost with minimum number of service level agreement (SLA) violations. In market oriented cloud the service vendors offer vivid variety of purchasing options and also dynamic prices to the customers. In order to incorporate these purchase-promotional offers and dynamic prices, this paper proposes a Petri net model for scheduling the workload across physical servers. Here, SLA requirements considered are CPU speed, memory, makespan and bandwidth with fewer virtual machine migrations. The experimental results indicate that the proposed system efficiently performs dynamic provisioning and elasticity in multiple public clouds with auto scaling that reduces makespan, number of SLA violations, penalty cost and maximises the profit.
Machine Learning Supervised Analysis for Enhancing Incident Management Process

This paper presents the descriptions of the attributes which are composed of an enriched incident management process event log.The degree of accuracy of the models for prediction depends on the usefulness of the log attributes utilized in building such models are and by using a machine learning algorithm approaches to the attributes gives a better comprehension of the background (underlying) process.This paper studies the classification method that applies for deciding which best feature among the features in an enriched event log dataset for the incident management process.The classification method compared to other methods used in related work.The result will state which one algorithm is the highest and the best one to be selected.The selection of an attribute is vital to building or creating a model with completion time prediction capability by determining concept description features to be learned and ways of feature combination.In this paper, a classification method was applied.Depending on the feature-target feature association (correlation), every attribute is separately analyzed.The outcomes indicate that the technique used outperformed human expert's decision making.We conducted predictions over different periods and achieved satisfactory performance in terms of accuracy, whereas, the best performance for classifying is achieved by the Bayes Net algorithm of 85.2760% accuracy.
Recognition times for 62 thousand English words: Data from the English Crowdsourcing Project

We present a new dataset of English word recognition times for a total of 62 thousand words, called the English Crowdsourcing Project. The data were collected via an internet vocabulary test, in which more than one million people participated. The present dataset is limited to native English speakers. Participants were asked to indicate which words they knew. Their response times were registered, although at no point were the participants asked to respond as fast as possible. Still, the response times correlate around .75 with the response times of the English Lexicon Project for the shared words. Also results of virtual experiments indicate that the new response times are a valid addition to the English Lexicon Project. This not only means that we have useful response times for some 35 thousand extra words, but we now also have data on differences in response latencies as a functionof education and age.
Harnessing Enzymatic Activity for Lifesaving Remedies (DOD)

Federal Grants & ContractsVolume 44, Issue 16 p. 4-4 Grant Alerts Harnessing Enzymatic Activity for Lifesaving Remedies (DOD) First published: 14 July 2020 https://doi.org/10.1002/fgc.31188Read 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 onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume44, Issue1616 July 2020Pages 4-4 RelatedInformation
Development of Indonesian Stemming Algorithms through Modification of Grouping, Sequencing and Removing of Affixes Based on Morphophonemic

Text documents stored on the system in an unstructured form, so that the information inside cannot be extracted directly. To be able to extract it, it takes text processing which is first carried out initial processing (preprocessing text) to convert text documents into more structured by selecting words that used as indexes. The smaller the index value, the more text documents are recognized on the system and the information is more easily extracted. The size of the index determined by the number of groups of words formed. To avoid forming many groups of words, then each word is changed to become a basic word first before grouping. The process of changing of affix word into a basic word using certain rules is called stemming. This research aims to produce a new Indonesian stemming algorithm named UG18 Stemmer algorithm, which can reduce or eliminate stemming errors such as over-stemming and under-stemming on existing stemming algorithms including the Enhanced Confix Stripping (ECS) Stemmer algorithm and the New Enhanced Confix Stripping (NECS) stemming algorithm. The method used is the morphophonemic process approach, which sees affixes as bound morphemes that experience phoneme changes, phoneme addition, and phoneme removal. The three processes are mapped, and Finite State Automata was made to obtain new affixed groups, sequences and new deletion methods that form the basis of the development of the UG18 Stemmer algorithm. This algorithm developed not using a list of decapitation rules used in pre-existing algorithms. Decapitation rules replaced with morphophonemic based elimination rules. Based on the evaluation results and testing of the UG18 Stemmer algorithm, it has a lower error rate compared to the results of stemming using NESC Stemmer. The result can be seen from the randomized test of 2500 word using Relevance Judgment validated by Indonesian language experts, from 1.48% over-stemming and 16.69% under-stemming using the NECS stemmer algorithm down to 0.12% overstemming and 0% understemming using the UG18 algorithm stemmer. Also, the UG18 Stemmer algorithm can improve the speed performance process in the information retrieval-based document similarity measurement application of 45.47% compared to using the ECS stemmer algorithm.
E-learning experience in schools and colleges with 1C:Education platform

The article presents the experience of mass organization of distance learning in organizations of secondary general and vocational education in March—May 2020 in connection with the difficult epidemiological situation in Russia. The possibilities of the 1C:Education system for organizing the educational process in a distance format, the peculiarities of organizing distance interaction in schools and colleges are considered, the results of using the system are summarized, examples of the successful use of the system in specific educational organizations are given. Based on the questionnaire survey of users, a number of capabilities of the 1C:Education system have been identified, which are essential for the full-fledged transfer of the educational process from full-time to distance learning. The nature and frequency of the use of electronic educational resources in various general education subjects in schools and colleges are analyzed, the importance of the presence in the distance learning system not only of a digital library of ready-made educational materials, but also of tools for creating author’s content is assessed. On the basis of an impersonal analysis of user actions in the system, a number of problems were identified that teachers and students faced in the process of an emergency transition to distance learning.
Exergaming May Have Unwanted Side Effects

Lippincott's Bone and Joint Newsletter: May 2021 - Volume 27 - Issue 5 - p 55-56 doi: 10.1097/01.BONEJ.0000749776.55509.7f
Tor and the City: MSA-level Correlates of Interest in Anonymous Web Browsing

In the 21st century, Americans have put more of their lives online, while the U.S. government has expanded its mass surveillance apparatus. Interest in anonymity-granting technologies like the The Onion Router (Tor) has grown substantially as citizens seek to protect their privacy. However, this same technology can be used to engage in illegal activity on the Dark Web. This study examines how interest in the Dark Web, public attention to the 2013 Snowden revelations, and metro area political ideology affect public interest in Tor. We link data from multiple sources including Google Trends, the American Community Survey, the Bureau of Labor Statistics, and the Cooperative Congressional Election Study for the 49 largest U.S. MSAs from 2006-2015 (n=490). Broadly, we find that metro areas with liberal citizen ideology and greater interest in the Dark Web were more likely to search for Tor. When controlling for the level of interest in the Dark Web, the Snowden revelations of 2013 had no significant impact on interest in Tor. These findings tend to suggest that the lure of the Dark Web and left-leaning ideological contexts offer stronger explanations for interest in anonymity-granting technology than the public attention brought to mass surveillance by the Snowden revelations.
Dimension Reduction using Orthogonal Local Preserving Projection in Big data

Big Data is unstructured data that overcome the processing complexity of conventional database systems.The dimensionality reduction approach, which is a fundamental technique for the large-scale dataprocessing, try to maintain the performance of the classifier while reduce the number of required features.The pedestrian data includes a number of features compare to the other data, so pedestrian detection is the complex task.The accuracy of detection and location directly affect the performance of the entire system.Moreover, the pedestrian based approaches mainly suffer from huge training samples and increase the computation complexity.In this paper, an efficient dimensionality reduction model and pedestrian data classification approach has been proposed.The proposed model has three steps Histogram of Oriented Gradients (HOG) descriptor used for feature extraction, Orthogonal Locality Preserving Projection (OLPP) approach for feature dimensionality reduction.Finally, the relevant features are forwarded to the Support Vector Machine (SVM) to classify the pedestrian data and non-pedestrian data.The proposed HOG+OLPP+SVM model performance was measured using evaluation metrics such as precision, accuracy, recall and f-measure.The proposed model used the Penn-Fudan Database and compare to the existing research the proposed model improved approximately 6% of pedestrian data classification accuracy.
PROCEDURE FOR IMPLEMENTATION OF DATA LEAKAGE PREVENTION (DLP) SYSTEM TO COMMERCIAL COMPANY FOR INFORMATION NETWORK USING LARGE DATABASE

The purpose of this work consists in the creation of such a procedure according to which a head or an expert dealing with the information safety in a company could make a decision quickly, whether he has got to install a system for intrusion prevention or not, and also how to substantiate a leadership the necessity The environment constantly develops and changes due to new technologies and the Internet. The products of intrusion detection are tools which help to control threats and voidability in this changing environment. Threats are people or groups which can jeopardize your computer system. It may be an inquisitive teenager, a discontented worker or it may be espionage of a rival company or a foreign government. That is why the implementation of a data protection system against leakage is an urgent necessity for companies in the modern world. &#x0D; The information content obtained for processing increases on a dynamic scale around the world. The information content incoming for processing grows on a dynamic scale all over the world. For the purpose of a quick reaction to any market changes, obtaining competitive advantages, increased production is required quick obtaining, processing and analyzing large data contents. &#x0D; of costs for operation. On this reason, there are defined basic advantages and disadvantages of the installation of the DLP system and there is shown a design examination of an attempt to implement the system in a commercial company.
NONPARAMETRIC METHODS OF AUTHORSHIP ATTRIBUTION IN ENGLISH LITERATURE

The paper describes the results of comparison of two nonparametric methods of authorship identification in English literature. It describes testing methods with and without clustering. A method was also proposed to select the n-grams that would best serve as a marker to identify the author. More than 800 texts of 16 authors were used for testing. The method using the density of the distribution is suitable for identifying authors of both large texts (50000+ characters) and small (10000+ characters) ones. A method that uses p-statistics is only suitable for large texts.
Evaluation (validation and verification)

In this chapter we will examine the important phase of Evaluation (validation and verification): in particular we shall see how the device designer needs to understand this phase whilst designing the new device.
The Effect of Using Internet-based Project Work toward Students' Vocabulary Mastery

English is an international language. Everyone is competing to master foreign language, especially English language as a communication tool in this era of globalization. As foreign language, it has many problems faced by Indonesian students, especially learning vocabulary. They are able to understand the teachers’ explanation, but it cannot stand any longer in their mind and especially for junior high school students. Vocabulary is one of the language component that should be learned by students, so they are able to accept the English material well. Therefore, the implementation of teaching media is one of the most important strategies in teaching learning process. The research findings in this research are the scores of vocabulary before and after being taught by using Internet-based Project Work. The results showed that the mean of total scores of students’ vocabulary mastery before being taught using Internet-based Project Work was (72,51). While the mean of total scores of students’ vocabulary mastery after they are taught using Internet-based Project Work was (83,16) . It was proved with the t-test analysis that used by the researcher can be shown the result tcount =(11,641), The value of “t” on the t score table t0,05 =(2.045). Based on the results above, alternative hyphotesis (Ha) states there is significant different score of student’s vocabulary mastery by using Internet-based Project Work is accepted, while the null hyphotesis (Ho) that states there is no significant different score of student’s vocabulary mastery is rejected. Finally, it can be concluded that Internet-based Project Work is effective media in teaching English vocabulary to junior high school, especially for eight grade students of SMPN 1 Durenan.
The Sentiment is in the Details: A Language-agnostic Approach to Dictionary Expansion and Sentence-level Sentiment Analysis in News Media

Determining the sentiment in the individual sentences of a newspaper article in an automated fashion is a major challenge. Manually created sentiment dictionaries often fail to meet the required standards. And while computer-generated dictionaries show promise, they are often limited by the availability of suitable linguistic resources. I propose and test a novel, language-agnostic and resource-efficient way of constructing sentiment dictionaries, based on word embedding models. The dictionaries are constructed and evaluated based on four corpora containing two decades of Danish, Dutch (Flanders and the Netherlands), English, and Norwegian newspaper articles, which are cleaned and parsed using Natural Language Processing. Concurrent validity is evaluated using a dataset of human-coded newspaper sentences, and compared to the performance of Polyglot dictionaries. Predictive validity is tested through two long-standing hypotheses on the negativity bias in political news. Results show that both the concurrent validity and predictive validity is good. The dictionaries outperform their Polyglot counterparts, and are able to detect a negativity bias, which is stronger for tabloids. The method is resource-efficient in terms of manual labor when compared to manually constructed dictionaries, and requires a limited amount of computational power.
State of the Art in Digital Paleography

Digital paleography is an approach used to assist paleographers in deciding the origin of manuscripts.This is done by recording types of writings present in old manuscripts.It uses digital representation of book hands as a tool to support paleographical analyses by human experts.There are six types of manuscripts selected which are Arabic, Chinese, Jawi, Indian, Latin and Roman.These types of manuscripts are discussed through their current contribution in the digital paleography field.The main purpose of this paper is to discuss the current work on digital paleography for selected types of manuscripts.Thus, we identified the approaches and methods used to define the types of handwritings in old
Reliability of Hijacked Journal Detection Based on Scientometrics, Altmetric Tools and Web Informatics: A Case Report Using Google Scholar, Web of Science and Scopus

This short paper presents a case report on detecting hijacked journals. Towards identification of a fake journal website and preventing a hijacked paper, we can use different tools including Google Scholar (an altmetric tool), Web of Science (WoS) and Scopus (both as scientometric databases) to distinguish a fake website from a legal journal website. Our evaluation shows that analysis of a doubtful website for a targeted journal based on Google Scholar is not reliable. In fact, the use of scientometric tools for tracking prior publications of the targeted journal is compulsory. Another result of this case study is that in some uncommon cases, fake websites may sometimes convince a scientometric database in order to be partially indexed along with an abstracting of their hijacked papers while these websites steal identity of the legal journals. Therefore as a results, we should check both of WoS and Scopus for verifying a fake website at the same time to obtain more reliability.
Generating Cross Domain Models using Generative Adversarial Networks

Normally an average human can understand the relationship between different fields and domains easily with limited information exposure. On the other hand even a modern day computer is pretty bad in understanding relationship between different domain