Reviewerly/exHarmony huggingface dataset:
Application of usability testing for analyzing the quality of 'Keluarga' pharmacy system in Pekanbaru

Family Pharmacy is a line of business that sells medicines in the city of Pekanbaru. Drug sales at these pharmacies are carried out offline by directly coming to the pharmacy and online through the Family Pharmacy application which can be downloaded via the google play store. However, the facilities offered by the Family Pharmacy application have not been able to provide user satisfaction, so that it has not fulfilled the initial goal of making the application, namely being able to increase drug sales and obtain a high level of satisfaction. Therefore, the author took the opportunity to conduct research in order to determine the quality of the application using the usability testing method. The analysis of the Family Pharmacy application aims to find out the shortcomings of the application that has been built, both in terms of learnability, efficiency, memorability, error, and satisfaction. The results obtained that the family pharmacy application has good quality according to users with 72.5% learnability, 74.2% efficiency, 74.4% memorability, 70.1% errors, and 71.4% satisfaction. However, the weakness of the Family Pharmacy application is that the majority of Family Pharmacy customers do not know about the Family Pharmacy application.
Development of E-Book Teaching Materials about the Four Days Battle in Surakarta August 7-10, 1949 as a Source of Local History Learning for History Education Students

An e-Book is a book that is displayed in digital form that can be used as a support for the learning process. This development aims to develop a digital book (e-Book) about the Four-Days Battle in Surakarta August 7-10, 1949 as a source of local history learning for students of the history education study program. This study uses the Research and Development (R&D) method in its research procedures and uses the ADDIE development procedure (Analysis, Design, Development, Implementation, Evaluation) as the stage of developing teaching materials. This product involves two media validators, two material validators, lecturers, and students of history education at the Veteran Bangun Nusantara University. The results of this development show that the e-Book based on the Four-Days Battle in Surakarta is proven to be valid and feasible based on the assessment of media and material factors from experts. Meanwhile, the results of assessments from small, large, and broad groups also show the effectiveness of the product based on the analysis. needs.
Breast Cancer Diagnosis using Machine Learning Approach

Breast cancer is the second most common cancer in women after skin cancer. When cancer care is delayed or inaccessible, there is a lower chance of survival, greater problems associated with treatment and higher costs of care. Early diagnosis improves cancer outcomes and leads to a better prognosis. In third world countries like Nigeria, where state-of-the art breast cancer diagnostic machines and the experts are grossly insufficient, alternative approaches to early diagnosis of breast cancer must be evolved. These preliminary data obtained from images of suspected cases of breast cancer are transformed in profiles of breast diseases, which are used by the local physicians in charge of breast disease patients. Each new case can then be compared by the local treating physician with the profile of all preceded cases with the same diagnosis. Three supervised learning models; Logistic Regression. Random Forest Classifier, and K-Nearest Neighbors were used to train the cancer dataset, and Random Forest Classifier outperformed with accuracy of 96% and an almost perfect sensitivity/Recall index. The dataset could not capture the demographic effects of the breast cancer images on the diagnosis, which now opens up new research areas in this study of breast cancer.
Libraries work with disabled children

The article deals with the issues of information-library services for disabled childrens, as well as the forms and methods of work of libraries with this category of users
Stochastic Block Model Reveals Maps of In Applied Mathematics Studies Using VOS Viewer

Bibliometric analysis is the mapping of research research trends by processing metadata from Google Scolar. The aim is to find out research trends in applied mathematics. The research was conducted on April 30, 2021 through searching the Google Scholar database with the keywords applied mathematics with the publication name journal and the maximum number of results is 500 journals as a sample. Metadata retrieval using the Publish or Perish (POP) application version 7.31. The PoP data were then analyzed descriptively based on the publication year, publisher name, researcher productivity, and journal ranking. To get an accurate map of research developments, PoP data is exported to Exel CSV and Result as RIS file formats. The CSV data was created in a pivot table and the RIS data was analyzed using the VOSViewer (VV) application. The results of the research show that the number of publications of research results in the years 2005-2021 has fluctuated and is mostly published in Elsevier. The most prolific foreign researcher in publishing research results is Biher Bist with 14 articles. The VV visualization shows that the map of the development of applied mathematics research is divided into 5 clusters. Cluster 1 consists of 27 topics, cluster 2 consists of 15 topics, cluster 3 consists of 10 topics, cluster 4 consists of 7 topics, and cluster 5 consists of 3 topics with the most research covering mathematics, paper, problem, solution, system, university, department, science.
LibGuides: ICT LibGuide: Referencing

The aim of this ICT subject guide is to make your studies pleasant and enrich your access to information resources. Through it, you will have access to general resources and other Open Access resources you may use for your studies.
Quantum Computing and Blockchain: Facts and Myths

Blockchain is an emerging technology that can radically improve transactions security at banking, supply chain, and other transaction networks. It's estimated that Blockchain will generate $3.1 trillion in new business value by 2030. Essentially, it provides the basis for a dynamic distributed ledger that can be applied to save time when recording transactions between parties, remove costs associated with intermediaries, and reduce risks of fraud and tampering. This book explores the fundamentals and applications of Blockchain technology. Readers will learn about the decentralized peer-to-peer network, distributed ledger, and the trust model that defines Blockchain technology. They will also be introduced to the basic components of Blockchain (transaction, block, block header, and the chain), its operations (hashing, verification, validation, and consensus model), underlying algorithms, and essentials of trust (hard fork and soft fork). Private and public Blockchain networks similar to Bitcoin and Ethereum will be introduced, as will concepts of Smart Contracts, Proof of Work and Proof of Stack, and cryptocurrency including Facebook's Libra will be elucidated. Also, the book will address the relationship between Blockchain technology, Internet of Things (IoT), Artificial Intelligence (AI), Cybersecurity, Digital Transformation and Quantum Computing. Readers will understand the inner workings and applications of this disruptive technology and its potential impact on all aspects of the business world and society. A look at the future trends of Blockchain Technology will be presented in the book.
Kinematics analysis of transmission mechanism of electronic jacquard machine based on virtual prototype and vector method

Abstract Aiming at the problem that the electronic transmission mechanism of the electronic jacquard machine is difficult to design, a kinematic analysis of the mechanical transmission mechanism of the electronic jacquard machine is proposed to clarify the kinematic performance of the electronic transmission mechanism. Based on the vector method, the kinematics mathematical model of the mechanical transmission mechanism of the electronic jacquard machine was established, and the matrix of the displacement, velocity and acceleration curve of the pulling blade was obtained. After the parameters are selected, the correctness of the mathematical model is verified through virtual prototype modeling and simulation. Through simulation analysis and verification, it is found that the numerical calculation results of the solution matrix are consistent with the simulation results of the virtual prototype model, and the peak error does not exceed 0.42%, which provides a certain theoretical basis for the study of electronic jacquard transmission mechanism.
Writing Loops and Functions in R

Abstract Learning how to write your own functions can seem like a daunting task, but Chapter 10 demystifies this process and teaches readers how to think about when and why this is an important thing to do. Beginning with simple functions and progressing to complex data simulations, writing functions is useful skill that will greatly expand the horizons of even relatively beginner R users.
The development of students industrial training information system (FBM-STIS) / Norhidayah Mohd Rashid … [et al.]

Student Industrial Training Information System (FBM-STIS) purposely developed for final year students from Faculty of Business and Management (FBM), Puncak Alam Campus who searching for industrial placement that fit with their studied background. It is aim to increase the accuracy and efficiency of the industrial placement process. The manual process required 107 days to complete and due to this long process, its increase the workload of administrative staff, workflow inefficiency and lead to poor record management. Through FBM-STIS, students need to fill up the internship application via online and this is inline with Industrial Revolution 4.0 (IR 4.0) emerged worldwide. This system allowed students to request and check the status of the Application Letter (AL), dan Conformation Letter (CL) online without visiting FBM - Industrial Training Unit (FBM-ITU) counter physically. Hence, FBM-STIS also help internship coordinator to manage and monitor the application process online because of the easy access of the system; FBM-STIS can be accessed anytime and anywhere.
Who said that? Comparing performance of TF-IDF and fastText to identify authorship of short sentences

Authorship identification is often applied to large documents, but less so to short, everyday sentences. The ability of identifying who said a short line could provide help to chatbots or personal assistants. This research compares performance of TF-IDF and fastText when identifying authorship of short sentences, by applying these feature extraction techniques to the television series Friends' transcripts. TF-IDF outperforms fastText in every measurement, but its performance is only marginally better than randomly guessing the original character, reaching an accuracy of 28 percent when making a distinction between 6 characters. Accuracy increases linearly at the same rate for both techniques as the minimum word count per sentence set on the test data increases. TF-IDF's confidence remains constant as this limit is set on either the test or training data, whereas fastText's confidence decreases and increases, respectively. Cross-entropy loss, however, remains constant for fastText and decreases for TF-IDF as the minimum word count set on the test data increases.
Effects of Children’s Exercise Participation Level on Exercise Continuation Intention: Multi-mediated Effects of Emotional Support and Positive Efficacy Well-Being

Purpose: This study verifies that exercise participation significantly mediates exercise continuation in the relationship among emotional support of social support, positive efficacy well-being, and exercise continuation.<BR> Method: For the study, data on a total of 232 students in fifth and sixth grades were collected and used for research by senior elementary school students. The measurement tools used in this study were produced and used for research purposes by social supporters’ level of participation, emotional support, positive efficacy questionnaires, and exercise persistence tests. Results were derived from exploratory factor analysis, reliability analysis, and mediated effect analysis using PRECESS (Hayes, 2013) Macro Model 6 of IBM SPSS 21.<BR> Results: First, children’s level of periodic sports participation had been shown to affect emotional support, positive efficacy well-being, and exercise continuation Intention, while emotional support had been shown to affect efficacy well-being and exercise continuation Intention. Second, positive efficacy well-being was also significantly affecting exercise continuation Intention, and exercise participation level was shown to affect exercise continuation Intention. In addition, emotional support and positive efficacy well-being had been identified as factors affecting exercise continuation Intention.<BR> Conclusion: In conclusion, emotional support and positive efficacy well-being have been confirmed to be partially mediated by exercise participants’ level. And exercise participation levels have a direct influence on exercise continuation Intention and indirect effects on emotional support and positive efficacy well-being.
Study of Interpretability in ML Algorithms for Disease Prognosis

Disease prognosis plays an important role in healthcare. Diagnosing disease at an early stage is crucial to provide treatment to the patient at the earliest in order to save his/her life or to at least reduce the severity of the disease. Application of Machine Learning algorithms is a promising area for the early and accurate diagnosis of chronic diseases. The black-box approach of Machine Learning models has been circumvented by providing different Interpretability methods. The importance of interpretability in health care field especially while taking decisions in life threatening diseases is crucial. Interpretable model increases the confidence of a medical practitioner in taking decisions. This paper gives an insight to the importance of explanations as well as the interpretability methods applied to different machine learning and deep learning models developed in recent years.
Spatiotemporal Texture Reconstruction for Dynamic Objects Using a Single RGB‐D Camera

Abstract This paper presents an effective method for generating a spatiotemporal (time‐varying) texture map for a dynamic object using a single RGB‐D camera. The input of our framework is a 3D template model and an RGB‐D image sequence. Since there are invisible areas of the object at a frame in a single‐camera setup, textures of such areas need to be borrowed from other frames. We formulate the problem as an MRF optimization and define cost functions to reconstruct a plausible spatiotemporal texture for a dynamic object. Experimental results demonstrate that our spatiotemporal textures can reproduce the active appearances of captured objects better than approaches using a single texture map.
Forensic Investigation of Forged Educational Documents

Fake educational documents differ in that they can be completely identical to the original and have all registration data, but at the same time differ in the quality of execution. The purpose of the study is considering fake documents as a source of the restoration of lost originals and the creation of a document that was not previously registered in the database. In the course of the research, two aspects of the production of forged documents were considered - filling in an analogue of a genuine document with distorted data and the creation of a knowingly forged document, which, for various reasons, cannot be entered into the database. The paper summarised methods of fraudulent changes in the original content of documents. It turned out the objects of technical expertise of documents are: cliché impressions of seals; signatures intersecting with seals, blank documents, etc.
LibGuides: A Cure for Boardom: Games for a Larger Group

Board Game Suggestions: All available at the Urbana Free Library. Games that scale up easily for a variety of gatherings, and have quick, learn-as-you-go instructions to jump right into it!
Information Seeking Behavior and Utilization of Social Media for Agricultural Information by Farmers of Prayagraj District of Uttar Pradesh

Social media is becoming very important implement in agriculture to edge people to people due to its capacity to connect with farmers and agribusiness people around the globe over hug geographical distances. At present time there are 2.078 billion social media user in the world. The study was conducting in purposely selected Prayagraj district of Uttar Pradesh of also purposely two selecting blocks two villages from each block. Selected for the study Thus, in all, four villages thirty farmers were selected randomly. Thus, total 120 respondents were selected randomly and interviewed with the help of well semi structured schedule. The statistical tools/technique was used to computing the data and information. Descriptive research design was followed for the analysis. Maximum number respondents communicate through social media and WhatsApp is highly exposed and adopted by the respondents in the study area. Smart phones, computer usage and internet should be promoted among stakeholders (esp. farmers).majority of the respondents information getting through Kisan SMS Portal. The highest utilization level of the respondents about social media programme was WhatsApp with a weighted mean score of 1.58 and it was ranked first, followed by the Kisan SMS Portal a weighted mean score was 1.43 with ranked was second, while YouTube was ranked third and so on.
Quantistica — and style and gender in the superposition of quantic art

The author of the paper is based on the provisions of the “Quantum Art” manifesto, created in 2008 by Roberto Denti, an Italian theorist, architect, artist, computer graphics and designer. In his opinion, the avant-garde styles of the twentieth century, which are based on a spontaneous image of a religious, meditative, psychedelic and narcotic trance seen in an altered state (such as visionary art, abstraction, surrealism, etc.), should be perceived as special cases of quantism, fixing random images of altered consciousness, but the authors are not aware of the causal relationship with the galactic information field, the quantum structure of the Universe, confirmed by the latest discoveries of the world scientific community in the field of cosmogony and quantum mechanics.
A Game Interface to Study Semantic Grounding in Text-Based Models

Can language models learn grounded representations from text distribution alone? This question is both central and recurrent in natural language processing; authors generally agree that grounding requires more than textual distribution. We propose to experimentally test this claim: if any two words have different meanings and yet cannot be distinguished from distribution alone, then grounding is out of the reach of text-based models. To that end, we present early work on an online game for the collection of human judgments on the distributional similarity of word pairs in five languages. We further report early results of our data collection campaign.
Hate Speech in Political Election

It is said that politicians’ hate speech or hate speech in political election tend to cause more serious impact on society. They are more influential to society and there is often an increased tension in political election. In this sense, some insist that strict regulation is needed to address politicians’ hate speech or hate speech in political election. However, we have to pay attention to the fact that on the one hand hate speech regulation is need for politicians, but on the other hand freedom of speech for politicians and free speech in political elections is extremely important. This article tries to sort out this dilemma between regulation and non-regulation for for politician and free speech in political elections. Firstly, incitement to hatred is also applied to polticians but most of them could skillfully evade legal regulation and I am afraid prosecuting politicians leads to political oppression by selectively prosecuting some of the political enemies. Another option is to deal with hate speech by the National Election Commission. This institution plays an important role in tackiling hate speech by informing politicians of the harm of hate speech.
LibGuides: CRJU U361 - Criminal Justice Research Methods: APA 7th Style Examples

This LibGuide is a work in progress designed to assist upper level Criminal Justice students with research
Improved Video Steganography for Secured Communication Using Clustering and Chaotic Mapping

The increased use of technology generates a huge volume of data in the forms of text, audio, video, and images, among others. With the increasedgenerationofdata, the security and protection of data are major concerns since data are transferred via wireless networks. Although many cryptographic algorithms are available for secure data transmission, they are prone to attacks because cipher text can be known prior to the decryption stage. An improved version for enforcing data security in wireless communication is steganography. It is the art of masking information or sensitive data inside an image or video that can be transferred across wireless networks in a secured way. Using deep learning techniques for video processing can aid in steganography, concealing sensitive information within a cover medium. Since convolutional neural networks can process a variety of multimedia formats, it plays a major role in secure wireless communication by encoding sensitive information within a cover medium. In steganography, the intruder is unaware that something is hidden within the carrier medium. Block shuffling using chaotic mapping further improves the security of hidden information. As long as the presence of these cretre mains unknown to the third party or an intruder, the possibility of attacks on the stego-image or stego-video remain slower. This asset adds some extra security to steganography, thereby achieving security in wireless data transmission using deep learning.
A Deep Convolutional Neural Network Approach for Detecting Malignancy of Ovarian Cancer Using Densenet Model

Ovarian malignant development has a helpless perseverance rate since general analysis and improved methods are needed for its underlying revelation. Ovarian danger is the sixth most characteristic infection in ladies, causing 152,000 decrease by and large yearly. To lessen this rate there is a requirement for an early detection of the infection. We plan a deep learning approach for essential recognition of ovarian malignancy utilizing histopathological pictures. Convolutional Neural Network (CNN) is utilized for the process. Feature extraction is finished by utilizing DenseNet-201 model of CNN. Malignant and benign cancer types are classified. In the characterization cycle, the PLCO dataset is utilized with most elevated ac-curacy accomplished is 94.73, exactness is 0.91, review and f1-score is 0.90 and 0.95 separately. Conditional outcomes and assessment of other earlier work explains truly trustworthy execution and the profitability of proposed work.