Reviewerly/exHarmony huggingface dataset:
Pre-processing of Leukemic Blood Cell Images Using Image Processing Techniques

Application of digital image processing on medical images could greatly help the doctors to identify the disease in an early phase before it starts spreading. In this research work, the pre-processing steps needed to find out the leukemic blood cells have been discussed and the resultant images are given at the end of each pre-processing step. The major aim of this research work is to detect the malignant leukemia at the earliest, so that it could improve the chances of survival of the patients. The quality of the images have been improved by using pre-processing methods such as DWT, KSVD, and HKSVD.
Utilizing Hyperledger-Based Private Blockchain to Secure E-Passport Management

A passport is a travel document that confirms the holder’s identity and nationality to travel internationally. E-passports are biometric passports with an electronic chip inserted around them and offer rigorous verification through documentation that tangibly marks the passport holder. Information security is a big concern around the world and the biometric security approaches used in the e-passport like RFID chips have various security threats. In this paper, we propose Hyperledger as a solution, which is an open-source private blockchain with robust security compared to the public blockchain. Validation of transactions in a Hyperledger-based private blockchain is fundamentally different from most blockchain development frameworks to minimize the number of checks that a transaction should have, allowing for faster and more efficient transactions, without compromising any of the security aspects. We have secured the confidential passport information and biometric data using this private ledger and InterPlanetary File System (IPFS), both of which have several security mechanisms like access control features, non-modifiable data and immutable historian records.
Feature Extraction and Selection with Hyperparameter Optimization for Mitosis Detection in Breast Histopathology Images

This paper attempted to detect mitotic nuclei by extracting different features from nuclei patches in the histopathology Images. We extracted features at multiple levels such as pixel, global, and local to find the best combination of features required for efficient mitosis analysis. We then passed an optimal subset of features to three different classifiers by applying the hyperparameter optimization technique. We observed the highest accuracy of 87.4 with a feature combination of the histogram of oriented gradients (HOG), oriented FAST and rotated BRIEF (ORB), center surround extremas (Censure), corner peaks, edge extract, and grayscale pixel value using tree-based pipeline optimization tool (TOPT) as the hyperparameter optimizer with support vector machine (SVM).
Learning Fables: Third Grade Literary Reading Lesson

The article presents a possible version of the methodology for studying fables as a genre of literary work in the third grade. Such teaching methods and techniques are disclosed as the analysis of literary models, "SMS messages", work with an explanatory dictionary, comparison of several literary texts. The significance of the formation of expressive reading skills in third-graders on the basis of their joint activities in pairs is discussed. Particular attention is paid to the description of individual studies of students, conducted on the basis of works of art.
Semantic Analysis of Moving Objects in Video Sequences

On the subject of using moving object analysis to find a specific item or replace a lost object in video sequences, numerous studies and papers have been written. To accurately describe each meaning and track down the behaviors of moving objects is a difficult task for semantic analysis investigations. In order to describe a clear text, some machine learning algorithms have looked at the proper interpretation of scenes or video clips. In order to translate visual patterns and characteristics into visual words, the paper makes use of dense and sparse optical flow methods. This study’s goal is to more easily evaluate moving objects utilizing the Gaussian Mixture Model (GMM) and baseline methods (Lagrange et al. 2017). A lot of moving pieces in the video sequence are synced together for tracking and mapping poses. Additionally, this study's goal is to use two datasets to evaluate the proposed model on people and other moving objects (videodataset.org and HumanEva). The findings should be displayed along with the diagnosis of the moving object and its synchronization with video sequences after looking at the map or tracking an object. Personalized Depth Tracker and GMM Procedures are supplied for the paper. In order to convey the emotional states of the moving objects, the paper first identifies, diagnoses, and then describes them. The emotional states are reflected in people's cheerful or sad faces, or in objects like cars and bicycles that move quickly or slowly. The proposed model's goals were developed using a machine learning technique that integrates the validity of obtaining the necessary moving components with the realism of the delivered results. Because it is an easy-to-use and very effective platform, the project was carried out on the MATLAB and Python versions 3.7 platforms.
Offline Marker-Less Augmented Reality Application for Exploring Threatened Historical Places

Integrating technology such as augmented reality into the tourism industry has led to e-tourism and smart tourism development. In the most recent few years, there has been observed a meteoric rise in the usage of mobile devices that can swiftly retrieve information has been noticed. As a result, Mobile augmented reality applications have proven globally successful in serving different fields like historical site tourism. Despite this, tourism at historical sites in Iraq continues to suffer from different problems, including a decline in popularity as well as a lack of use of modern technologies to document, preserve, and display sites to attract visitors. This paper aims to develop an offline mobile application for exploring Iraq's most important tourism site. Based on the unity3D engine and ARcore SDK, Marker-less augmented reality application was created to display the minaret and the Great Mosque of Samara. The application functionality was tested, and it was found that it works well and has good interactivity and ease of use, and can provide new solutions for tourism of the historical sites in Iraq.
Automated Grocery List Item Add-to-Cart Leveraging Optical Character Recognition with Transformer

The use of automation and smart interfaces in design of web applications involving visual human–computer interaction (HCI) is a critical research area focusing on improving user friendly interactions between various user types. In recent years, we see a tremendous rise in online grocery shopping services. But, these services do not provide expected streamlined user interaction. This paper proposes a novel smart user interface which provides grocery list item add-to-cart functionality with both handwritten as well as printed grocery list image uploaded by the user. To enable this, the paper details experimental use of transformer, a deep learning model with multi-head attention and position embedding for optical character recognition (OCR) enabling the proposed automatic add-to-cart. The experimental use of transformers for proposed automated add-to-cart shows promising results for real-time applications wherein it can be augmented with existing platforms and applications.
User experience and information architecture of the National Digital Library and archives of Iran: a usability investigation and card sorting

Purpose This study aims to evaluate the usability and information architecture of the digital library (DL) website of the National Library and Archives of Iran (NLAI). Design/methodology/approach This applied study used an exploratory mixed method, card sorting. Data were collected by interviewing, observation, usability test and card sorting. By interviewing users about problems of the DL, eight tasks were predefined and users’ problems in the path were identified. Their satisfaction of the tasks and the usability rates were measured via a questionnaire. Card sorting was done to inform on the information organization of the website elements. The study population included all users of the DL of the NLAI in two groups: ten initiator users (public users) and ten expert users (librarians). SPSS was used for analysing the usability test quantitative data. MaxQda was applied for analysing interview-driven qualitative data. Qualitative content analysis, categorization (data organization and grouping) and determining main and secondary codes were applied as well. The sort optimal application was used for analysing card sorting data in the form of similarity matrix and dendrogram. For validating qualitative findings, triangulation was used. The internal reliability of the used questionnaire amounted to a = 0.87 Findings Regarding the assigned tasks, new initiator users by consuming 367.67 s for registering and new expert users by consuming 403 s spent the most time. Task 2 ranked first in being incomplete among 40% of initiator users and Task 3 ranked first by 30% of incompleteness. Expert users had more unsuccessful attempts. Task 5 with the mean rate of 3.35 and Task 8 with the mean rate of 2.25 were the most difficult and the easiest tasks, respectively. Some usability components were rated lower than the moderate point. Only 30% of initiator users and 10% of expert users were satisfied with the website. A total of 12 categories and 452 codes were identified as main problems of the DL. The problems related to a vague perception of concepts and labels with 90 repetitions and digital source display with six repetitions ranked as the first and the last problems in working with the DL, respectively. The sort optimal package produced the card sorting results as a matrix similarity and a dendrogram. Card sorting reflected some changes in organizing information items. Interviews after card sorting emerged some new groups to be included, such as links to other digital libraries, shared databases in the organization and frequently asked questions. Originality/value The library’s website should be designed in a manner so that it can satisfy users with different traits. As the information technologies are increasingly developing, the importance of such a design increases for better service provision and effective competition.
Success Factors in CHM 4.0

The health coach in your pocket, available and accessible everywhere, resource-saving and suitable for everyday use – this could be the recipe for success in corporate health management 4.0 (CHM 4.0). Smart health exercises are not a hurdle in the digital age. But an attractive collection of tools is not enough, because in everyday business life, the conditions such as healthy leadership must also be created so that the digital toolbox is more than just a pretty gadget.
Hate Speech Detection and Analysis Using Machine Learning

Hate speech is offensive or threatening speech or writing that manifests bias against a specific group, basically contingent on religion or sexual orientation. Large-scale social media platforms invest significant resources to detect and classify hate messages with so little success automatically. Hate speeches spread via online social media platforms can trigger damage and distress to human beings and cause social disturbance further than cyberspace. Consequently, in recent times, in user-generated social media content, the detection of offensive language has become an escalating issue. Social media platforms produce a massive amount of data, which requires an effective classification model to uncover hate speech. On the internet and social media platforms, it is easy to spread hatred anonymously. This research will study several feature extraction techniques and classification algorithm’s performance to identify hate speech and repulsive terminology efficiently. This research will inspect several feature extraction techniques such as TF-IDF, Doc2Vec and calculate polarity scores in sentiment analysis by applying different classifiers such as support vector machine, random forest, naïve Bayes and logistic regression. Our purpose is to assess classification algorithms and feature extraction techniques to determine whether their contribution to classification models gives better results.
A Single Electron Transistor-Based Floating Point Multiplier Realization at Room Temperature Operation

Floating point numbers provide more range as compared to the fixed point values. The multiplier is one of the main blocks of a processor. For improved performance, there is a need for fast and efficient floating point multipliers. The single electron transistor (SET) is a prominent advanced device structure for achieving high-end computing system. This paper describes the implementation of single precision floating point multiplier using SET (single electron transistor) for better performance. Design and simulation of floating point multiplier have been performed using Cadence Virtuoso. In this paper, we are comparing SET-based floating point multiplier with 16 nm CMOS and then power and delay had been compared. The main objective of this paper is to reduce power consumption and increase the speed or reduce the delay of execution. IEEE 754 standard has been used to represent floating point numbers. Here, floating point multiplier is implemented and verified using the Cadence Virtuoso tool. Thus, SET-based floating point multiplier provides better execution in lowering the power and increasing the speed.
A Philosophy of Cover Songs

Journal Article A Philosophy of Cover Songs Get access P.D MagnusA Philosophy of Cover Songs Open Book Publishers, UK, 2022, xii + 151 pp., free online. Brandon Polite Brandon Polite Department of Philosophy, Knox College, Galesburg, Illinois, USA bpolite@knox.edu https://orcid.org/0000-0001-6985-8839 Search for other works by this author on: Oxford Academic Google Scholar The Journal of Aesthetics and Art Criticism, Volume 81, Issue 1, March 2023, Pages 109–112, https://doi.org/10.1093/jaac/kpac072 Published: 02 December 2022
Construction of a Knowledge Graph-based Medical Question Answer System

Artificial intelligence is widely used in the field of medical question answering. Some existing medical domain knowledge graphs have problems such as few categories of disease entities covered and small coverage of question answering. In this paper, a medical domain knowledge graph containing nearly 10,000 diseases is constructed, and a medical domain question answering system is implemented based on this knowledge graph using the Bert model. Experiment results show that the accuracy and recall of the system reach 0.96 and 0.93 respectively, with an F1 value of 0.945, which can effectively answer users' questions about the diagnosis of symptoms and medication recommendation of vast majority diseases and save medical resources to a certain extent.
Verifiable and Multi-Keyword Searchable Encryption Scheme Based on LSSS

Attribute-based Searchable Encryption (ABSE) schemes allow keyword encryption to be outsourced to cloud servers, and users can securely search for keyword ciphertext documents of interest. However, most existing searchable encryption schemes do not encourage the fine-grained search of users, and attributes are exposed to third parties easily. Moreover, ABSE schemes have high computational costs for resource-constrained clients on the user's client side. To solve the above problems, a verifiable and multi-keyword searchable encryption scheme based on linear secret sharing schemes (LSSS) is presented by us, which enables users to achieve a more efficient and secure fine-grained search of multi-keyword documents. In this scheme, access control is achieved using LSSS technology, and user attribute hiding is accomplished by hash. Furthermore, user authentication and pre-decryption are outsourced to cloud servers without leaking any information, which lessens the client's computational burden. It is demonstrated that the scheme can resist selective plaintext and selective keyword attacks in security models. In addition, the performance evaluation shows that our scheme performs well in real application scenarios.
Produkte: Vakuum in Forschung und Praxis 6/2022

Vakuum in Forschung und PraxisVolume 34, Issue 6 p. 13-14 Magazin Produkte: Vakuum in Forschung und Praxis 6/2022 First published: 13 December 2022 https://doi.org/10.1002/vipr.202270603AboutPDF 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 onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume34, Issue6December 2022Pages 13-14 RelatedInformation
South Africa: Amazon Africa HQ

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 59, Issue 10 p. 24072B-24072B Industries South Africa: Amazon Africa HQ First published: 13 December 2022 https://doi.org/10.1111/j.1467-6346.2022.10853.xRead 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 onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume59, Issue10December 2022Pages 24072B-24072B RelatedInformation
Problematic of Implementing Asesmen Nasional in Elementary School

This study aims to analyze the problems of Asesmen Nasional in elementary schools. The type of research used in this study is qualitative descriptive research. This study uses analytical techniques from Miles, and explains Huberman which consists of Data Collection; Data Reduction; Data View; and drawing conclusions/verifications. The results showed that: (1) Problems first arise in schools when the distribution or announcement of the names of students who must take literacy and numeracy tests is submitted to the school. (2) The second problem is that students when the AKM numeracy literacy test is carried out, learning is still running with the fifty-fifty model (50-50), (3) The last problem that arises is when the implementation of taking the test in the Computer Laboratory. Furthermore, the design of solutions when implementing the Asesmen Nasional of fifth grader, including: (1) the efforts made by the next teacher are to provide literacy and numeracy materials in the form of books and questions that have been given when students are of fourth grader. (2) Regarding students' difficulties with literacy questions whose reading is too long and understanding numeracy questions that require a high level of thinking, the teacher provides guidance as long as the students conduct trials and do the practice questions. (3) The next effort made by the teacher is to provide literacy and numeracy materials in the form of books and questions that have been given when students as fourth grader. (3) Furthermore, the last problem that arises in schools is the occurrence of an error system and having to re-login. This can be anticipated with the teacher's instructions to record the results of the answers that have been done.
Combining Augmented and Virtual Reality Experiences for Immersive Fire Drills

We propose an application that combines the benefits of augmented reality (AR) and virtual reality (VR) experiences for realistic and effective fire response training. Our analysis of recent literature reveals that there are different advantages to AR versus VR applications, and combining these experiences can generate new compound benefits in fire drills. In this study, a high-level training environment is automatically generated using three-dimensional object recognition technology, and the physical training tools are linked to the VR environment to improve immersion and training effectiveness. The combined advanced AR and VR experience demonstrates the potential use of this method in various industries.
It’s Me: VR-based Journaling for Improved Cognitive Self-Regulation

Journaling is a well-known evidence-based strategy for practicing better self-regulation and self-awareness in daily life. It is also an effective way for reducing the effects of negative emotions like anxiety and depression. We explore the combination of virtual reality (VR) and a body-tracking mirror as a cognitive activity in the form of VR journaling. VR-based journaling aims to build cognitive reappraisal, self-reflection, and autonomic emotion regulation in a sustainable way. The user performs in front of the mirror, using body-tracking to help them keep a daily journal. Considering that looking into the mirror is already a daily habit for most people, it does not require the users to form a new habit when trying to do journaling. Furthermore, it activates creativity by encouraging the user to use their body language as a story-telling tool.
Kyd’s influence on early Shakespeare

Pervez Rizvi has developed an electronic corpus of 527 plays dated between 1552 and 1657, titled Collocations and N-Grams. Users can download summary spreadsheets for play pairs sharing n-grams (contiguous word sequences). The spreadsheets rank plays in the electronic corpus according to all n-gram matches, as well as unique n-gram matches (i.e. occurring only in two plays in the corpus), and takes account of composite word counts. Rizvi’s results are fully automated and enable scholars to check for every phrasal repetition (including lemmas), as well as all collocations (discontinuous word sequences), shared between texts. Searches of these lemmatised texts – drawn from Mueller’s corpus and the Folger Shakespeare Editions website – allow a wider range of matches to be discovered than by searches using the unlemmatised forms of words. Utilising Rizvi’s corpus, this chapter further explores Shakespeare’s early verbal indebtedness to plays that have been attributed to Kyd. The study utilises quantitative measures to demonstrate the influence of Kyd’s phraseology on plays such as Henry VI Part Three, The Taming of the Shrew, and Richard III beyond reasonable doubt. The chapter proceeds to examine the influence of Kyd’s dramaturgy on Shakespeare’s early plays, including such elements identified by Brian Vickers as vengeful women and foreboding dreams, as well as dramatic structure and staging. The chapter then demonstrates that Shakespeare elaborated on Kyd’s dramatic devices, and that close study of the plays themselves reveals that, in doing so, he recycled aspects of Kyd’s idiom.