Reviewerly/exHarmony huggingface dataset:
APPLICATIONS OF INTERNET OF THINGS (IOT) IN HEALTHCARE: A COMPREHENSIVE SURVEY

In complementing and improving current healthcare systems, comprehensive research has been devoted to the exploration of different technologies such as information technology (IT). In particular, the Internet of Things (IoT) has been widely used to connect available medical services and provide elderly and chronically ill patients with a secure, productive and smart healthcare service. The goal of this paper is to summarize the IoT applications in the healthcare industry and to identify the trend of intelligentization and future research directions in this area. The development of IoT in healthcare systems has been studied from the perspectives of enabling technologies and methodologies, IoT-enabled smart devices and systems, and various IoT applications in the healthcare industries, based on a systematic literature review and the discussion of the researchers' achievements. Finally, the challenges and prospects of the development of IoT based healthcare systems are discussed in detail.
Social Group Recommendation With Several Algorithms

Group recommendation (GR) has become a trending topic in online social network ambience. The emotion and behaviour recommendation online is a familiar topic in SM (Social media) mining. As nowadays focus on online social NW developed a lot group recommendation acts as a hotspot for accessing. At present, many deep-learning-based approaches are leveraged to locate preferences of groups for elements. That, too predicting peculiar consecutive elements are targeted, in which groups are interested.  The accused survey projects a correlation model which in turn consist of elements to handle the concern is been discussed. The primary element is noted according to the user preference and their substantial needs. All the habits of the clients are noted and their behaviours are recorded. Then, a semi-supervised learning is proved to be easy than supervised models conceive. The approach further use a two graph based theory in further discussion. Many privileged system process amenities with small user groups. These groups are not measured in terms of classification accuracy. Equally the recommendations are pre-processed in terms of speed and measurability. In this survey paper a proposed new framework to accomplish the goal of exploring the group interests are composed. The connections between group users are discussed.  In order to enhance the group recommendation many methods were used an effective model. Social Group Recommendation (SGR) scheme with TrAdaBoost (Boosting for transfer learning) are recommended to raise the performance of group recommendation in online.  A unique aggregation performance of integration recommending media list is discussed. The recommender systems all interest subgroups as the final group recommendation results are given.
Rationally Inattentive Utility Maximization for Interpretable Deep Image Classification

Are deep convolutional neural networks (CNNs) for image classification explainable by utility maximization with information acquisition costs? We demonstrate that deep CNNs behave equivalently (in terms of necessary and sufficient conditions) to rationally inattentive utility maximizers, a generative model used extensively in economics for human decision making. Our claim is based by extensive experiments on 200 deep CNNs from 5 popular architectures. The parameters of our interpretable model are computed efficiently via convex feasibility algorithms. As an application, we show that our economics-based interpretable model can predict the classification performance of deep CNNs trained with arbitrary parameters with accuracy exceeding 94% . This eliminates the need to re-train the deep CNNs for image classification. The theoretical foundation of our approach lies in Bayesian revealed preference studied in micro-economics. All our results are on GitHub and completely reproducible.
Algorithms for a minimum sum of squares clustering

Cluster analysis aims at solving the following very general problem: given a set of entities, find subsets (also called clusters) which are homogeneous and well separated. Homogeneity means that similar entities should belong to the same cluster. Separation means that dissimilar entities should belong to different clusters. This concept can be expressed mathematically in many ways.
What is a Generator

This week, we implemented a classifier in our first lab-session of the Natural Language Processing course that I currently take at LiU. To pass the course, we actually have to write a lot of Python code, and as we – the PhD students from the Institute for Analytical Sociology – do not have any formal education in programming and computer science, it is proving hard to receive good results. One question my colleague had during the week was: “What is a generator?” Here’s the answer I gave her. (Probably a better one, because I had a few days to think about it.)
Universal quantum state preparation via revised greedy algorithm.

Preparation of quantum state lies at the heart of quantum information processing. The greedy algorithm provides a potential method to effectively prepare quantum states. However, the standard greedy algorithm, in general, cannot take the global maxima and instead becomes stuck on a local maxima. Based on the standard greedy algorithm, in this paper we propose a revised version to design dynamic pulses to realize universal quantum state preparation, i.e., preparing any arbitrary state from another arbitrary one. As applications, we implement this scheme to the universal preparation of single- and two-qubit state in the context of semiconductor quantum dots and superconducting circuits. Evaluation results show that our scheme outperforms the alternative numerical optimizations with higher preparation quality while possesses the comparable high efficiency. Compared with the emerging machine learning, it shows a better accessibility and does not require any training. Moreover, the numerical results show that the pulse sequences generated by our scheme are robust against various errors and noises. Our scheme opens a new avenue of optimization in few-level system and limited action space quantum control problems.
Performance Evaluation of Blockchains in the Internet of Things

The idea of blockchains technology (BT) in the internet of things (IoT) is to allow the physical things to trust in the transactions held within the IoT network. The BT is a distributed, decentralized, publicly shared its digital ledger and secured technology to eternally record the transactions across the shared database. The BT in IoT can be called Trust Machine to eliminate the intermediates and enables the physical things to trust with each other. This research evaluates the performance of BT in IoT. The simulated results are tested and can be used in the sustainable development of the integration of BT and IoT.
Legendre Wavelet Method for a Class of Fourth-Order Boundary Value Problems

In this paper we apply an approximate method based on Galerkin approach with Legendre wavelets basis, on a class of fourth order boundary value problems. The approach reduces the main equation to a system of linear algebraic equations that could be solved numerically. The operational matrix of the method is obtained, and the convergence of the method is proved. we approximate the solution and its higher order derivatives, for some special examples and compare the results with some other numerical methods. The results show the effectiveness of the proposed method.
The professional choreographic education: current state and development trends

The aim of the article is to highlight the features of the development of choreographic education at the beginning of the XXI century on the example of educational institutions of Great Britain and the United States, which train students in "Choreography" specialties. Methods: analysis, synthesis, induction, deduction, observation, description, tabular and graphical representation, comparison, systematization, questionnaire survey, hypothesis, abstraction and generalization. It was established that the development of choreographic education in the beginning of the XXI century is characterized by an annual increase in the number of students being trained as choreographers, choreographic education support by the universities, positive changes after the introduction of support measures for the development of choreographic education, increase in the level of encouragement for students to study the profession of choreographer, usage of modern ICT.
Sentiment Base Emotions Classification of Celebrity Tweets by Using R Language

Twitter is considered as one of the most effective microblogging site(s) developed mainly to express the views and thoughts of its users. Twitter users follow their favourite personalities, i.e., celebrities, and use to tweet/retweet, frequently, without knowing the emotions behind the made tweet. This research focuses on learning the emotions behind the tweets using R language by formulating it as an emotion classification problem. We applied twitter scraper data scraping technique to collect the dataset from the twitter accounts for our analysis. By using the proposed scheme, we estimate the emotions (whether the person was happy, sad, anxious, joyous, angry, surprised or feared) behind the tweet. We believe that our scheme would help users understand more the personality insights from the tweets. Sentiment R Package of R programming language is used to find out the personality insight than the positive, negative and neutral emoticon combined to find out the accurate results. If the user has more negative tweets we can say that he is happy and joys or if the negative tweets are more than positive tweets we can quickly evaluate that the personality is sad, angry, anxious or feared. The main contribution of this paper is to identify the emotions and the trend of the characters or twitter users.
Integration of Artificial Intelligence Tool (Ai-Chatbot) into Teaching and Learning: A Panacea for Improving Universities` Educational and Administrative Duties in South-South, Nigeria

Recent innovations in the field of Artificial intelligence (AI) has led to diverse influx of newer technologies, such as expert systems, intelligence tutoring systems (ITS) and conversation technologies among others. Conversational technologies such as AI-chatbot is capable of sharing and reducing the multiple-task which the 21st century school administrators and lecturers are saddled with. Since this hectic tasks; instructional delivery of contents, assessment and grading of students learning outcome, career guardian/counseling services are enormous. It is on this premise that the present study is necessitated, to investigate the integration of AI-chatbot into teaching and learning: A panacea for improving educational and administrative duties among universities in South-South geopolitical zone, Nigeria. The study adopted a descriptive survey research design. Three objectives with corresponding research questions guided the study. Three hypotheses were also tested at 0.05 alpha significant levels. The population of the study is 252,000 public universities students in South-South (Delta state, Edo State and Bayelsa). The sample size used was 399 respondents (274 students, 67 lecturers and 58 admin staffs) in the state and federal universities in the states. The instrument used for data collection was AICHATBOTSQ (AI-chatbot structured questionnaire) consisting of 20 items. Data gathered were analyzed using mean, standard deviation and analysis of variance (ANOVA). The study found that there is no significant difference in the mean rating of respondents on the need for AI-chatbot in teaching and learning as well as performing administrative tasks among universities in South-South; there is little availability of AI-chatbot technology in handling universities` administrative duties; and, the findings shows that poor internet facilities, instabilities in governance, inadequate funding, poor electricity supply among others are factors inhibiting implementation of AI-chatbot towards administrative duties among universities in South-South, Nigeria. Therefore, this study recommends full integration of artificial intelligence tool (AI-chatbot) into teaching and learning as a means for improving universities` educational and administrative duties in in south-south, Nigeria. Also, federal government should provide internet services for proper integration of AI-chatbot into education in universities in South-South geopolitical zone and Nigeria in general.
Determinants and Implications for Creativity Education in Korea: Policy Tools, Street-level Administration, and Implementation Conditions

The success of a policy depends on whether policy tool is appropriately chosen and how they work well to effective policy implementation in complex policy environments. However, only a handful of empirical studies attempt to test the effects of policy tools. This study uses a hierarchical regression analysis with data from both administrative data and survey data gathered from 167 lower secondary school teachers in Korea to examine the effect of key policy tools. The results are as followings: for grant, subject classroom facility grant has statistically significant positive relationships with CE, whereas CE Model School grant does not; for regulation, textbook regulation has statistically significant positive relationships with CE, whereas fewer subjects per a semester regulation does not.
Can the Subaltern Speak?

This paper presents AI-controlled robotic masks intended to empower women and allow them to communicate with one another. These are inspired by the historical masks worn by the Bandari women from southern Iran. Legend has it that these masks were developed during Portuguese colonial rule as a way of protecting the wearer from the gaze of slave masters looking for attractive women. In this project two robotic masks seemingly begin to develop their own language to communicate with each other, blinking their eyelashes in rapid succession using AI-generated Morse code. This project draws upon a Facebook experiment where two AI bots apparently began to develop their own language. It also draws upon an incident when an American soldier used his eyes to blink and spell out the word "TORTURE" using Morse code during his captivity in Vietnam, as well as stories of women using code to report domestic abuse during the COVID-19 lockdown. The aim is to sow anxiety within the patriarchal system where the "wink" of the sexual predator is subverted into a language to protect women from the advances of a predator. The project bridges AI, interactive design, and critical thinking (Figure 1).
INVESTIGATION OF A NEW DIGITAL PICTURE ENCRYPTION ALGORITHM: A STATE OF THE ART SURVEY

A new image encryption scheme using a 144-bit secret key is introduced in this paper. The image is divided into blocks and subsequently into colour components in the scheme replacement process. By conducting bitwise operations, each colour component is changed based on the secret key as well as a few most essential bits of its previous and next colour component. Three rounds are taken to complete the process of substitution. A feedback mechanism is also implemented to make the cypher more stable by changing the secret key used after each block is encrypted. In addition, the resulting image is partitioned into several dynamic sub-images based on the key. Each sub-image uses a created magic square matrix to move through the scrambling process where sub-image pixels are reshuffled within themselves. For the scrambling process, five rounds are taken. The proposed system is straightforward, quick and sensitive to the secret key. Popular attacks such as linear and differential cryptanalysis are infeasible due to the high order of substitution and permutation. The experimental results indicate that the encryption approach proposed is effective and has strong security characteristics.
VBridge: Connecting the Dots Between Features, Explanations, and Data for Healthcare Models.

Machine learning (ML) is increasingly applied to Electronic Health Records (EHRs) to solve clinical prediction tasks. Although many ML models perform promisingly, issues with model transparency and interpretability limit their adoption in clinical practice. Directly using existing explainable ML techniques in clinical settings can be challenging. Through literature surveys and collaborations with six clinicians with an average of 17 years of clinical experience, we identified three key challenges, including clinicians' unfamiliarity with ML features, lack of contextual information, and the need for cohort-level evidence. Following an iterative design process, we further designed and developed VBridge, a visual analytics tool that seamlessly incorporates ML explanations into clinicians' decision-making workflow. The system includes a novel hierarchical display of contribution-based feature explanations and enriched interactions that connect the dots between ML features, explanations, and data. We demonstrated the effectiveness of VBridge through two case studies and expert interviews with four clinicians, showing that visually associating model explanations with patients' situational records can help clinicians better interpret and use model predictions when making clinician decisions. We further derived a list of design implications for developing future explainable ML tools to support clinical decision-making.
Social media (FB) : NDA Fragrance / Nur Hashimah Sharani

NDA Fragrance is a business that carries out online business for fragrance products. Fragrance products consist of Inspired Perfume, Body Mist and Body Butter. This business is created to provide an opportunity to all customers who love quality fragrances and want to have them at affordable prices. Apart from selling products to consumers, NDA Fragrance also provides useful info and tips to fragrance customers. Retaining NDA Fragrance's customers is a very strong suit for this business and so we have strategies in place to ensure that our customers remain happy with our products and services. This can be achieved if we employ the best customer service executives who are adept at handling orders, promptly attending to complaints and inquiries. We also intend to provide a listening ear to our clients for feedbacks that will help make the company progress. In addition to reinforcing strategies for maintaining customer loyalty towards NDA Fragrance, expanding and exploring ways to promote this online product and services business in social media is important. Skills and ways to know how to attract customers are important. Start by giving teaser a customer to give the customer a sense of excitement to know which product to sell. Next, the skills to make soft sell to give you an idea of exactly what the product is going to sell in the right way. Last but not least, hard-sell-making skills to customers to attract customers continue to buy promoted products. NDA Fragrance can further enhance this entrepreneurial knowledge to further develop this business in the near future.
Scammers posing as IRS use credible emails to threaten victims

Scammers impersonating the Internal Revenue Service are perfecting the art of fraud, according to a new report.
Subject & Research Guides: Open Data Sets and Visualization Resources: Other Data Sets

Locate and use open source numeric, statistical, geospatial, and qualitative data sets by topic. Explore data visualization methods, techniques, and resources to help discover patterns in the data that may not be clear from statistics alone.
Emergent Design Challenges for Embedded Systems and Paths Forward: Mixed-criticality, Energy, Reliability and Security Perspectives: Special Session Paper

Modern embedded systems need to cater for several needs depending upon the application domain in which they are deployed. For example, mixed-critically needs to be considered for real-time and safety-critical systems and energy for battery-operated systems. At the same time, many of these systems demand for their reliability and security as well. With electronic systems being used for increasingly varying type of applications, novel challenges have emerged. For example, with the use of embedded systems in increasingly complex applications that execute tasks with varying priorities, mixed-criticality systems present unique challenges to designing reliable systems. The large design space involved in implementing cross-layer reliability in heterogeneous systems, particularly for mixed-critical systems, poses new research problems. Further, malicious security attacks on these systems pose additional extraordinary challenges in the system design. In this paper, we cover both the industry and academia perspectives of the challenges posed by these emergent aspects of system design towards designing highperformance, energy-efficient, reliable and/or secure embedded systems. We also provide our views on paths forward.
Analysis of Advance with English Coursebook (Yilin Oxford Edition)

Teaching materials are the concrete embodiment of the course targets and contents. It is also the main medium for teachers and students to carry out teaching activities. Good language teaching materials should be used by learners at different levels in different ways. They also provide an opportunity for teachers to form or create their unique teaching styles. Therefore, the analysis of English teaching materials is particularly important. First, this article introduces the writing purposes which match the requirements of the General English Curriculum Standards and then analyzes the contents of Advance with English in listening, speaking, reading, and writing. The third part discusses the limitations of Advance with English in respect to its practical use.
Attitude toward Business and Business Intention of ABM andSTEM Students of Senior High School of Divine WordColleges in Ilocos Region, Philippines: The Role of Education

The purpose of this study was to determine the level of attitude of ABM and STEM students toward business and their business intention and to find out if there is a difference of attitude toward business and business intention of both strands (ABM and STEM). To establish the theories of the study, the literature was reviewed. The study used descriptive correlational research design and to gather the data, the validated questionnaires were used. The population of the study was grade XII ABM and STEM students of the Divine Word Colleges in the Ilocos Region. The study found that their attitude toward business and their business intention is high and based on Pearson r correlation, it was found that there is a significant correlation between attitude toward business and business intention and therefore, the hypothesis is accepted. However, based on the F-test which measures the difference between the attitude of ABM and STEM students’ attitude toward business and their business intention, the study found that there is no significant difference between both strands when it comes to their attitude toward business and their business intention.