Reviewerly/exHarmony huggingface dataset:
<i>Library Services for Online Patrons: A Manual for Facilitating Access, Learning, and Engagement</i>. Edited by Joelle E. Pitts, Laura Bonella, Jason M. Coleman, and Adam Wathen. Santa Barbara, CA: Libraries Unlimited, 2020. Pp. vi+200. $55.00 (paper). ISBN 978-1-4408-5952-6.

Previous article No AccessReviewLibrary Services for Online Patrons: A Manual for Facilitating Access, Learning, and Engagement. Edited by Joelle E. Pitts, Laura Bonella, Jason M. Coleman, and Adam Wathen. Santa Barbara, CA: Libraries Unlimited, 2020. Pp. vi+200. $55.00 (paper). ISBN 978-1-4408-5952-6.Alice KalinowskiAlice KalinowskiStanford Graduate School of Business Library Search for more articles by this author PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by The Library Quarterly Volume 90, Number 3July 2020 Article DOIhttps://doi.org/10.1086/708966 Views: 110Total views on this site For permission to reuse, please contact [email protected]PDF download Crossref reports no articles citing this article.
Interspecies Communication: An Introduction and a Provocation

Both an introduction to PUBLIC #59 and a rumination on the difficulty of interspecies communication, this essay argues for art and interspecies communication as means of building mental and emotional qualities useful for re-imagining culture in a time of rapid environmental change, embedding a self-reflexive example in the text.
GPH Algorithm: Improved CBC improved BIFID cipher Symmetric Key Algorithm 

Cryptography is art of illusion within which the sender encodes the message employing a key and sends it over the line. The receiver on the opposite facet of the channel decodes the message back and victimization the key tries to get back the initial message. In case the key throughout the communication is same on each side then it's referred to as radial key cryptography and if is termed as uneven key cryptography. There have been completely different secret writing techniques used for the plain text called as block & stream cipher. The modes for encryption are ECB, CBC, OFB & CFB. In this paper we propose a symmetric key algorithm using CBC mode of encryption with high complexity
Efektivitas Eksistensi Poster-Poster K3 di Gedung F Fakultas Kedokteran Universitas Sebelas Maret Sebagai Peningkat Budaya Literasi Mahasiswa K3 2019

This study aims to explain effectiveness the existence of safety posters at F building, Faculty of Medicine Sebelas Maret University of increasing literature culture Health and Safety Enviroment Student. Literature culture is a such a soft skill, especially on writting and reading. That skill is so important for HSE ( Health and Safety Environment ) Employees in the work environment soon. The Writer realized that Literature culture is very important, considering that, in Indonesia, literature culture was totally low. The writer used descriptive qualitative methods in this research. So we interviewed 8 people of Health and Safety Environment student about effectiveness the existence of posters in F building, Faculty of Medicine Sebelas Maret University of increasing literature culture.
Image data hiding scheme based on spline interpolation and OPAP

In this paper we propose an image steganography method based on the spline interpolation. Firstly, digital images are often transmitted over the Internet which would arouse little suspicion. Secondly, the high correlation between pixels provides rich space for data embedding; in addition, optimal pixel adjustment procedure (OPAP) is employed to minimise the error between the input image and the output image in order to ameliorate the fidelity of the proposed steganography method. We propose image steganography methods in spatial domain by using a nearest neighbour, bilinear and bicubic spline interpolation technique, which can embed a large amount of secret data into images with imperceptible modification. The interpolation error, which is measured by distance between the maximum value and the predicted value, is used to embed the secret data. The experimental results show that the proposed schemes provide a larger payload and a good image quality.
Looking For Novelty in Search-based Software Product Line Testing

This paper show how the novelty search (NS) algorithm can be used for similarity-based software product line testing
administrasi layanan khusus

this article describe about administration of special services. special service administration is one part of the administration in the school
An Asynchronous and Low-Power True Random Number Generator Using STT-MTJ

&lt;div&gt;The Spin Transfer Torque Magnetic Tunnel Junction&lt;/div&gt;&lt;div&gt;(STT-MTJ) is an emerging memory technology whose interesting&lt;/div&gt;&lt;div&gt;stochastic behavior might benefit security applications. In this&lt;/div&gt;&lt;div&gt;paper, we leverage this stochastic behavior to construct a true&lt;/div&gt;&lt;div&gt;random number generator (TRNG), the basic module in the&lt;/div&gt;&lt;div&gt;process of encryption key generation. Our proposed TRNG&lt;/div&gt;&lt;div&gt;operates asynchronously and thus can use small and fast STT&lt;/div&gt;&lt;div&gt;MTJ devices. As such, it can be embedded in low-power and&lt;/div&gt;&lt;div&gt;low-frequency devices without loss of entropy. We evaluate&lt;/div&gt;&lt;div&gt;the proposed TRNG using a numerical simulation, solving the&lt;/div&gt;&lt;div&gt;Landau–Lifshitz–Gilbert (LLG) equation system of the STTMTJ&lt;/div&gt;&lt;div&gt;devices. Design considerations, attack analysis, and process&lt;/div&gt;&lt;div&gt;variation are discussed and evaluated. The evaluation shows that&lt;/div&gt;&lt;div&gt;our solution is robust to process variation, achieving a Shannonentropy&lt;/div&gt;&lt;div&gt;generating rate between 99.7Mbps and 127.8Mbps for&lt;/div&gt;&lt;div&gt;90% of the instances.&lt;/div&gt;
BIG DATA: A NEW FIELD OF ACTION FOR LIBRARIANS BIG DATA: UM NOVO CAMPO DE ATUACAO PARA BIBLIOTECARIOS

In the so-called information society, data are produced in high volumes and become the main raw material of the economic context. In this scenario, Big Data seeks to address the need to extract value from this data. The development of hardware and software capable of storing and processing high amounts of data quickly made it possible to cross-examine and analyze them, transforming unstructured data into useful information. Thus, Big Data can provide a new field of action for information science professionals. The present study observes, through a review of the existing literature and the bibliographical research of exploratory and qualitative scope, the concepts of Big Data, its tools of analysis and the search to delimit the profile of the professional of the area, identifying the positions created in the labor market and attributions. By linking the skills of Big Data professionals and librarians, the paper presents the application of Big Data as a new opportunity for action for librarians who wish to be trained in the field of data analysis. Na chamada sociedade da informação, os dados são produzidos em elevados volumes e se tornam a principal matéria-prima do contexto econômico. Nesse cenário, o Big Data busca suprir a necessidade de extrair valor desses dados. O desenvolvimento de hardwares e softwares capazes de armazenar e processar altas quantidades de dados com rapidez, tornou possível o cruzamento dos mesmos e sua análise, transformando dados não-estruturados em informações úteis. Assim, o Big Data pode propiciar um novo campo de atuação para os profissionais de Ciência da Informação. O presente trabalho observa, através de revisão da literatura existente e da pesquisa bibliográfica de escopo exploratório e qualitativo, as conceituações de Big Data, suas ferramentas de análise e busca delimitar o perfil do profissional da área, identificando os cargos criados no mercado de trabalho e suas atribuições. Ao relacionar as competências dos profissionais de Big Data e dos bibliotecários, o trabalho apresenta a aplicação de Big Data como uma nova oportunidade de atuação para os bibliotecários que desejem se capacitar no campo de análise de dados.
A study of production and consumption of information graphics in Indian regional newspapers

This work involved collecting the infographic data for the month of December 2017 from the Delhi editions of top four most-read Hindi newspapers and top four most-read English newspapers in India. This data is organised newspaper-wise, and date-wise with certain parameters of judgement like the content it is depicting, the location of the news in the newspaper, its treatment, and the area it covers on a page. We propose a tentative data model for a systematic collection of the otherwise unusable infographic data, in a database, ready for analysing and deriving insights. This model can be used to gather similar data from other regional languages (Bangla, Tamil, Malayalam, etc.) newspapers printed in India.
Automatic Sentiment Analysis Model Creation using Multi Kernel Improved Extreme Learning Machine

Recent research activities related to opinion mining, sentiment analysis and emotion detection from natural language texts are all under the umbrella of affective computation. There is now a huge amount of textual information on social media (for example, forums, blogs, and social media) about consumers' ideas about buying products and service experiences. Sentiment analysis or opinion mining is part of an investigation that analyzes people's thoughts and feelings from written text available online. In this paper, this work present a comprehensive experiment to evaluate the effectiveness of psychological and linguistic features in emotion classification. In this scheme, we used five broad categories of LIWC (namely, psychological processes, linguistic processes, punctuation, spoken categories and personal concerns) as feature sets. Five types of LIWCs and their group combinations were considered in the experimental analysis. To understand the predictive performance of various aspects of the engineering scheme, five controlled learning algorithms (namely, Naïve Bayes, support vector machines, Extreme Learning Machine, Kernel Extreme Learning Machine, Multi Kernel Extreme Learning Machine) and proposed Multi Kernel Improved Extreme Learning Machine (MKIELM) are used. Experimental results show that the ensemble feature sets provides a higher predictive effect than the individual set..
The bibliographical guide of publications on the topic «Library activities in ecological education (1984–2019)» – RNPLS&amp;T’s e-publication

The bibliographical guide of publications on the topic «Library activities in ecological education (1984–2019)» prepared by RNPLS&amp;T’s Group of Ecology and Sustainable Projects is presented. The guide comprises two sections: professional publications of 1984–2019 and libraries’ digital resources in ecology. The guide will be of interest to researchers studying this aspect of library activities. The guide reflects indirectly the characteristic features of ecological movement and education in the country and their dynamics during the mentioned period.
Analysis of Representative Values in Clustering using the CURE Algorithm

The collection of data that everyone has on earth has a fully agreed upon value of knowledge. Analysis of a collection of data that can accommodate a long processing time, for this we need an algorithm that can provide a comparison of the acceleration of the analysis process. One process of data analysis is clustering, which is a process of grouping large amounts of data so that it is easy to understand. One of the algorithms in the clustering process is CURE (Clustering Using Representative) where CURE random sample-based data bases partition the data using representative points called representative points. Sample-based process will provide better processing time acceleration because it will only be done on the data collection, not the whole data. This representative point determines the processing time of the testing carried out in the input. Values, representative values, and shrinkage values will provide a faster settlement process for the values inputted according to the correct conditions.
Implications of Short Message Service (Text Messaging) on English Languge Writing and Learning Among Secondary School Students: A Case Study of Some Selected Secondary Schools in Olorunda Local Government Area of Osun State, Nigeria

The study investigated commonly used abbreviated words among the sampled population. It also determined the difference between those that abbreviated words and those that did not abbreviated words. The study revealed the list of abbreviated words in the study. And also ascertained which gender abbreviated words most. These were with a view to provide information on the implications of SMS language on English Language writing and learning of the students. The study adopted quantitative survey research design. The population for the study Comprised 83 senior secondary school students in Olorunda Local Government, Osun State. The sample size comprised 100 respondents, selected using multistage sampling technique. One Local Government Area (LGA) was selected from thirty Local Governments in the state using simple random sampling technique. From the LGA, four senior secondary school was selected using simple random sampling technique and from each school, 25 students were selected from senior secondary school II using simple random sampling technique. The students were taught for forty minutes on how to write a letter devoid of using abbreviated words and after the lesson, the students were asked to write a letter to their father informing him about social amenities in your school. Those letters were collected, marked and converted to data for this study. Data collected was analyzed using simple percentages. Those letter were collected, marked and converted to data for this study. The result showed commonly used abbreviated words by the respondents such as, pls (please) 9 times by 9 students, u (you) 26 times by 10 students , and fyn (fine) 5 times and so on. The result also revealed 51 students (representing 61.4%) did not abbreviated words in the letter writing and 32 students (representing 38.6%) abbreviated words in the letter. The result showed that female gender was the gender that abbreviated words most in the letter with 49% and male with 35%. Lastly, the result also revealed percentage of students that used abbreviated words 38.6% of the students used abbreviated words while 61.4% of the 100% total population did not used abbreviated words The study concluded that use of abbreviated words did not have effect on English language learning and writing among secondary school students in Olorunda Local Government, Osun State.
A conceptual information sharing framework to improve supply chain security collaboration

Modern supply chains are critical in terms of efficiency, economic activities and commercial impact, particularly in case of security incidents. Inland terminals, commercial ports and dry ports constitute key gateways for the transportation flows in these modern supply chains and are require enhanced security procedures. This paper develops a framework that facilitates the sharing of information among various supply chain stakeholders, which is expected to improve the security level from a value chain perspective. In this context, we propose the upgrade of the current security strategies utilising existing processes, equipment in order to minimise time and cost currently needed but more importantly improving the level of security in the supply chain. A conceptual rule and role-based data fusion framework is developed enabling the seamless and timely exchange of messages. The proposed data fusion framework has a simple architecture that supports quick integration to either network-based, distributed systems or conventional stand-alone systems and adheres to common data fusion principles. The proposed framework considers different components (e.g., sensors, algorithms and fusing procedures) in an equipment agnostic approach so as to enable easy access and easy usage of security information.
Prediction of Crowd in Three Levels: a Foot Step to Anomalies Prevention

Crowd is a huge number of people meet jointly in a disorganized or unmanageable way. Crowd in any atmosphere may leads to suspicious events. Nobody can predict the crowd and some anomalies might happen in the presence of crowd. So prevention of crowd well in advance is the only remedy to tackle the situation. Advance crowd detection is an important subfield in video surveillance. Prior detection or prevention of crowd has so much of importance while we are considering the present scenarios all over the world. So now-days, an automatic crowd prevention technique is needed for all the countries to protect their land, provide safety for their citizens and law enforcement. Crowd prevention system using manual operators are weak due to many physiological and non-physiological factors but it will provide better performance than automatic system in case of decision making. Many models have been developed so far to detect the crowd automatically. Our system aims to predict the crowd well in advance in three levels and so the automatic system or the operator will get enough time to respond or take a decision. To detect the formation of crowd well in advance, all the human objects in a frame was identified by Gaussian mixture model and object classification, shadow was eliminated and crowd was predicted using the object rectangle model and center vertical line model. The pixel distance between the each rectangles and center line is used to predict the formation of crowd. This paper also gives some suggestions to crowd modelling.
Introduction To GENERAL LINGUISTICS

Introduction to general is a text book designed and writen to help and provide the language students of University, or those who wish to learn and teach language. The references of this book derived from the writer's experience during teaching linguistics at English Department of Teacher Training and Education of Islamic University of Riau, his papers in seminar, and library references. This book is also intended togive basic information about linguistics and to indicate the development of linguistics research particularly to the students and teacher language. consequently, since this book is far from being perfect, the writer accepts sugesstions and critieisms of leader for futher revisions.
ASIS International: Investigator Certification

The Professional Certified Investigator (PCI) certification, by ASIS International, provides independent confirmation of specialized skills in security investigations, including case evaluation and review of options for case management strategies. It validates the PCI’s ability to collect information through the effective use of surveillance, interviews, and interrogations, and is applicable to a wide range of specialized investigations.
Verifiable Contracting

We investigate the combined use of eIDAS-based electronic identity and Verifiable Credentials for remote onboarding and contracting, and provide a proof-of-concept implementation based on SAML authentication. The main non-trivial value derived from this proposal is a higher degree of assurance in the contract offering phase for the Contracting Service Provider.
Multiple Object Detection in Images using Template Matching

Template matching is an application in computer vision for finding similar objects between the images. Template matching is a key component in image analysis process for mapping similar patterns between images. The detection and matching of objects has gained widespread application in quality control, manufacturing and medical applications. The major challenges in template matching process are occlusion, background noise and non-rigid transformation particularly in medical images. The present work proposes a template matching method based on correlation analysis techniques to detect multiple objects occurrence in an image. The method has been experimented for various real-time applications. In medical images, the proposed method gave an accuracy of 86% in detecting the nodules in lung CT images
Robustious Feature Selection Based Genetic Algorithm (RFS-GA) For Cross Domain Opinion Mining

Day by day the requirement of information for processing the sentiment analysis is getting increased multiple times. For these kind of reasons, feature selection is utilized to detect the opinion among different reviews and comments. Sentiment analysis is becoming like phenomenon due to increase of social media’s popularity. Currently, significant advancements are shown in this research domain, but still multiple challenges are to be solved – i.e., sentiment analysis in cross domains. In this paper rumbustious feature selection based genetic algorithm is proposed to address the problem of analyzing the sentiments in cross domain. It performs classification based optimistic-class and pessimistic-class. The dataset used to this research work includes books, DVDs, gadgets and kitchen appliances. Initially the features selection is performed and opinion mining is performed by Genetic Algorithm. Benchmark performance metrics are selected for measuring the performance of proposed work against existing method. Results depict that the proposed work has better performance than that of the existing work as far as chosen performance metrics.
The Development of Intelligence Walking Stick for Elderly Health Care using IoT

Nowadays, Thailand is stepping into an aging society. This research purposes developing the intelligence walking stick for the elderly in terms of the health care system by applied the IoT devices and biometric sensors in a real-time system. The heart rate, blood pressure, oxygen saturation, and temperature were measured at the finger of the elderly that holding the intelligence walking stick. All data can monitor and display on mobile devices. The intelligence walking stick system was evaluated by twenty users who are five experts and fifteen elderly in Ratchaburi province. As a result of the mean value at 4.88 and 4.85 by experts and elderly, respectively. It could be said that the development of intelligence walking stick by using IoT can help and improve the daily living of the elderly at the highest level.
Frequent Itemset Mining in a Unique Sc an using Transaction Database

In recent year, frequent Itemset Mining (FIM) has occurred as a vital role in data mining tasks. The search of FIM in a transactions data is discovered in this paper, pull out hidden pattern from transactions data. The main two limitation of the Apriori algorithm are undertaken, first, its scans the complete Databases at every passes to compute the supports of every itemset produced and secondly, the user defined responsive to variation of min_sup (minimum supports) thresholds. In this paper, proposed methodology called frequent Itemset Mining in unique Scan (FIMUS), needs a scan only one time of transaction databases to extract frequent itemsets. The generation of a static numbers of candidate Itemset is an exclusive feature, individually from the threshold of min_sup, which reduces the execution time for huge database. The proposed algorithm FIMUS is compared with Apriori algorithm using benchmark database for a dense databases. The experimental result confirms the scalability of FIMUS.