Reviewerly/exHarmony huggingface dataset:
Balance of Public Medical and Health Services and Reform of Medical Institutions Based on 5G Sensor Technology

Since its reform and opening in 1978, China’s economy has grown rapidly and human life and physical well-being have improved significantly. The public health care system is an imperative guarantee of people’s life and physical health. It is necessary to establish a reasonable planning, a reasonable division of labor, and an efficient medical service system to improve the overall efficiency of health care services and ensure the physical health of the people. The balance of public health care services plays a very important role. It plays a very important role in safeguarding people’s basic right to health, regulating social fairness and justice, promoting the sustainable development of medical and health services, and building a harmonious society. Based on 5G sensor technology, this paper combines relevant research on sensor technology at home and abroad and comprehensively uses related theories such as sensing principles and health care services to discuss the internal operation mechanism of China’s public health care service system. It conducts experiments to compare health care services with 5G sensor technology with existing health care service systems. It compares its bed occupancy rates, hospital admissions and discharges, outpatient and emergency department volumes, and average inpatient costs. It studies the impact of 5G sensor technology on public health care services. The experimental results show that after adopting 5G sensor technology, the average bed utilization rate in the H hospital is 88.71%. The total number of hospitalizations was 9.845 million, and the total number of discharges was 8.668 million. The total number of outpatient visits was 44.259 million, and the total emergency department was 7.694 million. The per capita cost of inpatients in H hospital is 15,840 yuan, and the per capita cost of inpatients in W center is 9,661.75 yuan.
One-dimension orientation method of caster and kingpin inclination of vehicle wheel alignment

Caster and KPI are two important parameters of the wheel alignment for the stability and safety of vehicle. The previous work for the measurement of the wheel caster and KPI focuses on the 2D-target-based test. We propose an accurate 1D-target-based measurement for the caster and KPI of vehicle wheel. The invariance of kingpin position in suspension during the alignment is analyzed. The sub-pixel extraction with the high accuracy is improved for the center position of concentric circles on the 1D target. Then, the caster and KPI are initially orientated by the 1D-1D-2D-3D kingpin measurement model, which relates the 1D center positions of 1D target and the wheel kingpin. Furthermore, the optimization function of the caster and KPI is constructed by the real angle benchmarks, which define caster and KPI, respectively. The measurement method is verified by the simulation, moreover, experimentally proved by two angles of the verification instrument.
Innovative Technologies in Education: National Foresight

The development and implementation of new methods in scientific and educational processes should take into account a full-scale assessment of current needs in education / science and identify the most accordant and effective ways to respond to modern demands. The research is aimed at solving problems related to the formation of current priority areas of innovation in higher education. This involved the use of modern Foresight analysis methodology, which includes methods: horizon scanning, scientometric methods, expert groups and patent analysis. Identified global innovative trends in education, which are mainly related to the use of ICT and the introduction of new teaching methods: blended learning, augmented reality, non-standard teaching methods, artificial intelligence, e-Learning technology, learning applications, learning management system, digital transformation of education, financial literacy and entrepreneurship education, lifelong learning, horizontal learning, technology-friendly learning environment, corporate learning technology, smart learning, Big data, robotics, gamification and Blockchain. Based on scientometric analysis of the latest educational developments of the global publication database Web of Science, the Top 5 current global innovative areas in higher education are established: artificial intelligence, digital transformation of education, lifelong learning, gamification and robotic technologies. The analysis of the results of the first stage of the National Foresight revealed the needs of the national education system in innovations and showed that the proposals received from expert scientists mostly correspond to current global trends in higher education. The second stage of the national foresight allowed to identify thematic groups that are most in demand in the market of educational services (received the highest rating), including: «Educational standards and technologies of vocational training», «Psychological support of the educational process», «Inclusive education» and «Cultural and educational area, improving the quality of education using cultural heritage and political experience of society», «Digital transformation of education», «Artificial Intelligence», «e-Learning Technologies», «Horizontal Learning», «Communication between education and science».
Fitting Non-Parametric Mixture of Regressions: Introducing an EM-Type Algorithm to Address the Label-Switching Problem

The non-parametric Gaussian mixture of regressions (NPGMRs) model serves as a flexible approach for the determination of latent heterogeneous regression relationships. This model assumes that the component means, variances and mixing proportions are smooth unknown functions of the covariates where the error distribution of each component is assumed to be Gaussian and hence symmetric. These functions are estimated over a set of grid points using the Expectation-Maximization (EM) algorithm to maximise the local-likelihood functions. However, maximizing each local-likelihood function separately does not guarantee that the local responsibilities and corresponding labels, obtained at the E-step of the EM algorithm, align at each grid point leading to a label-switching problem. This results in non-smooth estimated component regression functions. In this paper, we propose an estimation procedure to account for label switching by tracking the roughness of the estimated component regression functions. We use the local responsibilities to obtain a global estimate of the responsibilities which are then used to maximize each local-likelihood function. The performance of the proposed procedure is demonstrated using a simulation study and through an application using real world data. In the case of well-separated mixture regression components, the procedure gives similar results to competitive methods. However, in the case of poorly separated mixture regression components, the procedure outperforms competitive methods.
Shared knowledge distillation for robust multi‐scale super‐resolution networks

Although developments in deep learning have resulted in considerable perormance enhancements in super-resolution (SR), they have also caused substantial increases in computational costs and memory requirements. Thus, various compression techniques, such as quantisation, pruning, and knowledge distillation (KD), for single SR models have been introduced. However, multiple SR models are required in the real world to robustly reconstruct low-resolution (LR) images of varying input sizes. Because of the limited resources, storing multiple models is impossible for mobile devices and embedded systems. In this letter, we propose a multi-scale SR network using weight-sharing method to effectively eliminate redundant parameters. To train our multi-scale SR network and mitigate SR performance degradation due to knowledge confusion, we divide backpropagation into two stages. Furthermore, we propose a compression framework that distils shared knowledge within a multi-scale SR network. We achieve a compression rate of 94% from storing multiple scales of single SR models, while only compromising 0.3 dB on average in terms of peak signal-to-noise ratio (PSNR).
Debiasing Neural Retrieval via In-batch Balancing Regularization

People frequently interact with information retrieval (IR) systems, however, IR models exhibit biases and discrimination towards various demographics.The in-processing fair ranking methods provide a trade-offs between accuracy and fairness through adding a fairness-related regularization term in the loss function.However, there haven't been intuitive objective functions that depend on the click probability and user engagement to directly optimize towards this.In this work, we propose the In-Batch Balancing Regularization (IBBR) to mitigate the ranking disparity among subgroups.In particular, we develop a differentiable normed Pairwise Ranking Fairness (nPRF) and leverage the T-statistics on top of nPRF over subgroups as a regularization to improve fairness.Empirical results with the BERT-based neural rankers on the MS MARCO Passage Retrieval dataset with the human-annotated nongendered queries benchmark (Rekabsaz and Schedl, 2020) show that our IBBR method with nPRF achieves significantly less bias with minimal degradation in ranking performance compared with the baseline.
A Chatbot Application by using Natural Language Processing and Artificial Intelligence Markup Language

A program which helps in making conversation with the help of textual methods is referred to as chatbot. Chatbot helps in responding to a message quickly and that too without human intervention. Startups are inventing thousands of chatbots in order to provide a better service and keep their customers busy by a kind and simple conversation. It also helps in providing far better services to customers and helps in buying products. It takes an input from the user in the form of keywords, and it matches those keywords in its data-set to give out the corresponding output saved in it. It gives all the possible answers related to user queries. Since, most of the times like during pandemic, we cannot go outside and cannot meet people, it is an interactive way to get to know about how world is dealing with it. Chatbots exploits AI and ML platforms. Chatbots are becoming popular day by day in this modern era, they are being used in business groups and helps in reducing costs and can help in providing one to many communications that means it can handle multiple customers at same time. Chatbots need to be as efficient as possible.
Implicit Body Representation of the Hand Enlarged by Repetitive Peripheral Magnetic Stimulation within the Boundary of a Real Hand

Deafferentation induced by local anesthesia causes a larger perceived area than the real area of the mouth, which, in the perspective of body representation, belongs to implicit body representation. In this study, we applied repetitive peripheral magnetic stimulation (rPMS) on the motor branch of the radial nerve of participants’ non-dominant-side forearm to induce extension movements of wrist and fingers. This intervention was supposed to increase proprioception to the brain and had an enlargement effect on implicit body representation of the hand in our hypothesis. A total of 39 participants were randomly allocated to the real rPMS group (n = 19) or the sham rPMS group (n = 20). Implicit representation of the hand was measured by a simplified paradigm based on the proposal of Longo and Haggard that depicted perceived locations of fingertips and metacarpophalangeal joints of participants’ occluded hand, in which they showed that implicit body representation of the hand was smaller than the real hand. We compare the main effect of real rPMS vs. sham rPMS and its interaction effect with time by setting four timepoints—before stimulation, right after stimulation, 10 min after stimulation and 20 min after stimulation—to demonstrate the possible short-lasting effect. Results showed that real rPMS had a short-lasting enlargement effect on implicit representation of the hand in general, which was significant especially on the ulnar side of fingers. What is more, the enlarged implicit body representation of the hand was still within the boundary of a real hand, which might indicate the identification role of a real body part.
UPAYA MENINGKATKAN KETERAMPILAN MENULIS PANTUN DENGAN MODEL PEMBELAJARAN KONTEKSTUAL PADA PESERTA DIDIK KELAS V SD

The purpose of this research is to improve the skill of writing rhymes. The subjects in this study were educators and fifth grade students of SD Negeri 01 Pasangkayu. The teaching methods and methods tend to be conventional and traditional, thus making the students' ability to write poems lacking. Contextual learning model is one of the efforts used to improve the ability to write rhymes. This classroom action research (CAR) was carried out in two cycles. Starting with the identification of problems that exist in the classroom by taking pre-cycle actions. The stage of each cycle begins with planning in the form of compiling learning steps through the application of contextual models. The results showed that the application of the contextual model had improved the students' skills in writing rhymes. The skills of educators in this study have been declared complete. The skills of students in learning have increased from cycle one and cycle two, in cycle one educators achieved a good category with a success percentage of 77% and in cycle II increased by 96% with a very good category. The activities of students have reached the indicators of success and are declared complete. The activity of students in learning has increased, in cycle one it reaches a good category. In the aspect of student attention, it was 85%, in the second cycle it increased by 95%. In the aspect of the learning situation of students in the first cycle of m80%, and in the second cycle of 85%. The children's poetry writing skills have reached the indicators of success and were declared complete. Classical learning completeness in the pre-cycle is only 35%, and in the first cycle it increases by 80%, and in the second cycle the increase reaches 100%. This research is proven to be able to improve the quality of learning which includes the skills of educators, student activities and the results of rhyme writing skills.
Antibunched single-photon/photon-pair emission with coupled Jaynes-Cummings model

Herein, we propose a coupled Jaynes-Cummings model for the preparation of strong antibunched single photons and antibunched correlated photon pairs. Using the effective Hamiltonian method, we obtained the expression for the correlation function and then presented the optimal conditions for conventional/unconventional photon blockade. The results showed that on one hand, an intersection point exists between conventional photon blockade and unconventional photon blockade and that the performance of the single photon at the intersection point is better. On the other hand, under the condition of unconventional photon blockade, the photons produced by each Jaynes-Cummings system are strongly correlated with each other.
Analysis of influence of Jinxiu handicraft immersive experience on purchase action in AIDMA model -- based on SPSS21 and AMOS23 software

In order to promote the protection, inheritance, innovation and development of shanxi folk intangible cultural heritage and solve the back-end marketing problems, questionnaire survey and field investigation were used to understand the marketing problems of Shanxi Embroidery handicrafts, combined with AIDMA model analysis. This paper attempts to construct a quaternity immersive experience model of "museum + guide + experience store + sales store". SPSS21 and AMOS23 software are used to demonstrate the questionnaire data, and the final empirical results are obtained. The results show that the immersive experience model has a significant positive effect on consumers' purchasing actions, and has varying degrees of influence on attracting attention, arousing interest, generating demand and desire, and forming memory, especially on attracting attention. The results show that the immersive experience is suitable for the marketing of Shanxi Jin embroidery handicrafts, and this model provides a new idea for the marketing of shanxi intangible cultural heritage-related cultural and creative products.
EFFECTS OF TEAMWORK ON EMPLOYEE PERFORMANCE: A CASE STUDY OF THE HOTEL SECTOR IN CAN THO CITY, VIETNAM

Potential effects of the teamwork and employee performance have been identified in the literature and viewed as as one of the most concerns in a branch of the human resource management (HRM). The study aims to examine effects of the teamwork on employee performance basing upon a survey from 120 employees working for 2 to 5 star-ranked hotels in Can Tho city. The widely-used methods for the qualitative data analysis including the Exploratory Factor Analysis (EFA) and regression analysis were applied. The empirical results show that the employee performance is positively and directly related with four elements, relevant to the postulated theory. It is also worth noting that two out of these four factors - Recognition and reward and Team trust – are enough of the statistical significance which may explain in the relation with the employee performance at hotels. In conclusion, some main findings and limitations of the study are pointed out.
The use of LMS Moodle to Improve Reading Comprehension Skill for the 10th Grade Students

The purpose of this research was to increase students' achievement in reading comprehension by implementing the LMS Moodle to the 10th grade students at SMA Petra 4 Sidoarjo in the academic year 2020/2021. Classroom Action Research (CAR) was applied in conducting this study from January to June 2021. Each cycle of CAR consisted of four steps: planning, action, observation, and reflection. The data were gathered through the use of two instruments: observation and test. The results indicated that students made great progress in their ability to comprehend the reading texts. Pre-test mean score was only 72.71, but improved to 79.29 in cycle 1 and 86.57 in cycle 2. The lowest pre-test score was only 65 and improved to 70 to 75 in subsequent cycles. Meanwhile, the highest pre-test score was 82.5, and the highest post-tests scores were 92.5 and 95. In case of the students who passed the tests, while only 9 students (25.71%) passed the pre-test, there were significant improvements in post-tests, with 21 students (60%) passing in post-test cycle 1 and 33 students (94.29%) passing in post-test cycle 2. This research was stopped in cycle 2 due to the fact that the criteria for success were met in a percentage of 94.29%, with 33 students passing the post-test in cycle 2, based on the Minimum Mastery Criteria (KKM) standard of &gt; 76
Pengaruh Penggunaan Media Pembelajaran Quizizz Terhadap Motivasi Belajar Siswa Kelas V

This study aims to find out whether there is an effect of using Quizizz learning media on the learning motivation of fifth grade students at SDN 3 Lemba, Soppeng Regency. This study uses a quantitative research approach with the type of experimental research using a True Experimental Design research design. The results showed that there were differences in students' learning motivation between the experimental class and the control class. Then continued with the N-Gain test, the N-Gain Score for the experimental class was 0.4 in the medium category and the N- Gain Score for the control class was 0,2 is in the low category. It can be concluded that the use of quizizz learning media has a significant effect on the learning motivation of fifth grade students at SDN 3 Lemba, Soppeng Regency
Challenges of applying e-learning facing faculty members in public universities during COVID-19

Introduction. The impact of the Corona pandemic in various countries of the world is still present on most aspects of life, albeit to varying degrees. The higher education sector, including universities and higher education institutions, was not immune from this, there are universities that have faced the challenge of the pandemic by developing innovative ways and solutions to continue academic and research activity in them; such as e-learning, virtual scientific conferences, and working in remote research groups. This study aimed to reveal the e-learning challenges facing faculty members in Jordanian Public Universities during Coronavirus Pandemic from their perspectives. Methods. The study involved 226 faculty members chosen randomly from four Jordanian public universities for the second semester of the academic year 2019/2020. To study the e-learning challenges facing faculty members in universities, a questionnaire was developed and it included sixty-four items divided into seven domains as follows: (the challenges of planning and designing for e-learning), (technical challenges to the use of e-learning techniques), (challenges of e-learning management), (the challenges of scientific research via the Internet), (financial and administrative challenges for e-learning university), (general professional challenges for a faculty member in the domain of e-learning), and (the challenges of evaluating e-learning). Research results. It was revealed that the descending order of challenges as follows: scientific research (mean (M) = 2.78; standard deviation (s) =1.198), challenges of e-learning techniques (M = 2.72; s = 1.120), financial and administrative challenges (M = 2.38; s = 0.841), professional challenges (M = 2.37; s = 0.717, evaluation (M = 2.27; s = 0.082), management (M = 2.27; s = 0.882), planning and design of e-learning (M = 2,26; s = 0.788. The results showed a high percentage of the faculty members attended training to deal with technology. No statistically significant differences were found in challenges due to gender (M = 2.33, s = 0.684), academic rank, and experience (M = 2.47, s = 0.693). The results showed that there were differences attributed to the type of college and in favor of the humanities colleges, and differences attributed to the university, and in favor of Tafila Technical University. Conclusion. The coronavirus crisis has cast a shadow over the education sector. As it prompted universities and educational institutions to close their doors to reduce the chances of its spread. This aroused great concern among those involved in this sector. All this prompted educational institutions to switch to e-learning, as an alternative that has long been talked about and controversy over the necessity of integrating it into the educational process. However, faculty members in universities faced several challenges in the use of e-learning, and the researchers studied these challenges facing them from their point of view and made some recommendations.
A Deep Dive into Blockchain Consensus Algorithms

Blockchain has a great potential to change the way we interact and transact on the Internet. It has features like decentralized systems, security, immutability and transparency. Given that it is a decentralized system and there is no third party involved to verify transactions, security is at risk. Such a system can be highly prone to attacks like double spending and might become vulnerable at times. How is it avoided without having a centralized system? For this system to function at a global scale, a secure algorithm is highly needed. That is where a consensus algorithm comes into play. This chapter discusses various Blockchain consensus algorithms like Proof of Work, Proof of Stake, etc. and gives a brief overview of each.