Reviewerly/exHarmony huggingface dataset:
Facilitators and barriers to the adoption of mHealth apps for COVID-19 contact tracing: a systematic review of the literature

Background Despite the enormous potential of mobile health (mHealth) apps for COVID-19 contact tracing, the adoption rate in most countries remains low. Thus, the objective of the current study is to identify facilitators and barriers of mHealth apps adoption for COVID-19 contact tracing based on existing studies. Methods We conducted a systematic review of mHealth studies before December 2021 that evaluate facilitators and barriers associated with the adoption of mHealth apps for COVID-19 contact tracing. We assessed the risk of bias for all included studies using the Cochrane tool. We based our narrative synthesis on the facilitators-barriers to the adoption of mHealth framework comprising seven key factors. Results A total of 27 articles were reviewed from 16 countries representing high income countries (France, German, Italy, United Kingdom, United States, Australia, Singapore, Belgium, Republic Ireland, Netherland, Poland, and Japan), middle-income countries (Fiji), and low-middle income countries (India). We identified the main facilitators of mHealth adoption: perceived risks to COVID-19, trust, perceived benefit, social norm, and technology readiness. The main barriers of mHealth adoption were data privacy/security concerns. Among sociodemographic factors, females, lower education, lower-income, and older individual are barriers to adoption in low-middle income countries, while most of those factors were not significantly associated with adoption in a high-income country. Conclusion The findings imply that resolving data privacy/security issues while developing trust, perceived benefits, social norms, and technology preparedness could be effective strategies for increasing adoption intentions and app use among the general public. In low-middle-income countries, addressing digital divide is critical to the app’s adoption. Systematic review registration https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=249500 , identifier RD42021249500 (PROSPERO).
Deterministic Weight Modification-based Extreme Learning Machine for Stock Price Prediction

Background: The prediction of the stock price is considered to be one of the most fascinating and important research and patent topics in the financial sector. Aims: Making more accurate predictions is a difficult and significant task because the financial industry supports investors and the national economy. Objectives: The DWM is used to adjust the connection weights and biases to enhance prediction precision and convergence rate. DWM was proposed as a method to reduce system error by changing the weights of various levels. The methods for predictable changes in weight were provided together with the computational difficulty. Methods: An extreme learning machine (ELM) is a fast-learning method for training a singlehidden layer neural network (SLFN). However, the model's learning process is ineffective or incomplete due to the randomly chosen weights and biases of the input's hidden layers. Hence, this article presents a deterministic weight modification (DWM) based ELM called DWM-ELM for predicting the stock price. Results: The calculated results showed that DWM-ELM had the best predictive performance, with RMSE (root mean square error) of 0.0096, MAE (mean absolute error) of 0.0563, 0.0428, MAPE (mean absolute percentage error) of 1.7045, and DS (Directional Symmetry) of 89.34. conclusion: The experimental results showed that, in comparison to other well-known prediction algorithms, the suggested DWM+ELM prediction model offers better prediction performance. Conclusion: The experimental results showed that, in comparison to other well-known prediction algorithms, the suggested DWM+ELM prediction model offers better prediction performance.
IMPROVING THE METHODOLOGICAL FOUNDATIONS FOR THE DEVELOPMENT&#x0D; OF PROFESSIONAL COMPETENCES OF STUDENTS IN ECONOMIC SPECIALTIES:&#x0D; THE AUTHOR'S APPROACH

The article is devoted to the study of the methodological foundations for the development of professional&#x0D; competencies of students of economic specialties. The essence of these competencies is studied, various approaches to its&#x0D; interpretation are considered, their advantages and disadvantages are identified. An analysis of modern types of&#x0D; professional competencies of economic specialists was carried out, which made it possible to group them into several&#x0D; enlarged groups and determine the possibilities for supplementing them. Based on the results of the study, an author's&#x0D; approach to improving the methodological foundations for the development of professional competencies of students of&#x0D; economic specialties was developed, including the substantiation of the author's interpretation of the term «professional&#x0D; competencies» and expanding the specific composition of these competencies, taking into account the realities of the&#x0D; modern world.
Application of Technology Acceptance Model in Examining Students’ Behavioural Intention to Use Virtual Meeting Technology: A Partial Least Squares Structural Equation Modeling Approach

The use of virtual meeting technologies is becoming widespread in the educational field especially due to the outbreak of the Coronavirus Disease (COVID-19) that suddenly traumatized educational institutions activities in many countries across the world. However, despite the numerous advantages of virtual meeting technology, many higher institutions in Nigeria have not embraced the technology even during COVID-19 pandemic due to poor internet connectivity, poor facilities, negative attitudes (non-acceptance) of both teachers and students etc. In this study, partial least squares structural equation modelling (PLS-SEM) based on Davis technology acceptance model (TAM) was used to test the proposed model. The reliability and validity tests of the data collection instrument re-established the suitability of the TAM model in measuring the students’ acceptance of virtual meeting technologies. The research indicated that perceived usefulness as established by TAM was also found to have a significant impact on students’ attitude and behavioral intention to use virtual meeting technology. Similarly, the result has shown that perceived ease of use (PEOU) had a strong effect on perceived usefulness (PU).
Potential Use of Artificial Intelligence in ESL Writing Assessment: A Case Study of IELTS Writing Tasks

This paper investigates the potential use of generative AI in ESL Writing Assessment, particularly in IELTS Writing Tasks. The first part introduces the author’s relationship with generative AI in the educational setting, and why the author chooses this topic. This section also contains information about generative AI like ChatGPT, and the prompts employed to generate the article. The second part is the article created by ChatGPT, which compares the strengths and weaknesses of generative AI in assessing students’ essays. The third part is a critical reflection of how generative AI performs in creating such an academic paper. It can indeed help researchers to write an informative article more efficiently. But it is noticeable that some specific and important information could be missing and the references are likely to be false ones. Educators should be aware of the strengths and weaknesses of generative AI tools to make the most of it.
The Role of Prosocial Behaviour, Personality and General Mental Health in Predicting Emoji Use and Preference

Emojis are prevalent in text-based communication, but the factors that influence our use and preference for emojis remains unclear. This study investigated how emoji use and preference could be explained by three factors; mental health, personality and prosocial behaviour. A questionnaire consisting of five measures was completed by 222 participants and both Pearson correlations and multiple regressions were conducted on the data. The results showed prosocial behaviour significantly related to frequency, attitudes and motivations towards emoji use as well as to positive emoji preference. Agreeableness related to the frequency of emoji use. Extraversion related to both positive and negative emoji preference while conscientiousness and emotional stability significantly related to negative emoji preference only. General mental health significantly related to negative emoji preference. The regressions found all of the factors identified in the correlations predicted emoji use and preference with the exception of extraversion. Further research is needed to explore how the impact of the emotions depicted by emojis on these factors and to investigate how emojis are used by people with specific mental health conditions.
Application progress of virtual reality technology in symptom management of senile mild cognitive impairment

Mild cognitive impairment (MCI) is an intermediate transitional stage between healthy aging and dementia, and is an important problem affecting healthy aging. As a key industry of digital economy, virtual reality technology has a positive impact on the medical field. This paper reviews the concept classification, advantages and application of virtual reality technology in cognition, bad mood, fall and self-care ability of mild cognitive impairment in the elderly, in order to provide reference for clinical practice.
Real-Time Optical Flow Estimation Method Based on Cross-Stage Network

In this paper, a real-time optical flow estimation method based on a cross-stage network is proposed. The proposed model is designed with a network structure with encoders and decoders. The proposed method combines cross-stage network technology with the network structure of FlowNet2 and RAFT to achieve improved parameter number and estimation performance. For real-time optical flow estimation, it is important to maintain performance while reducing the number of parameters in the network. In the proposed method, structural convergence is performed to increase performance while reducing the number of parameters by applying the cross-stage network structure. The proposed model is designed to solve the bottlenecks in model accuracy and complexity by separating feature extraction and flow estimation processes. Flying Chairs, Flying Things 3D, and KITTI datasets were used to evaluate the performance of the proposed model, and the experimental results show superior performance compared to previous traditional methods.
RAPIDTM Based Treatment Algorithms Lead to Faster Activation of Neurointervention Team and Reduce Recanalization Times (P1.3-020)

May 5, 2019April 9, 2019Free AccessRAPIDTM Based Treatment Algorithms Lead to Faster Activation of Neurointervention Team and Reduce Recanalization Times (P1.3-020)Siddhart Mehta, Spozhmy Panezai, Sara Strauss, Briana DeCarvalho, Ashish Kulhari, Amrinder Singh, and Jawad F. KirmaniAuthors Info & AffiliationsApril 9, 2019 issue92 (15_supplement)https://doi.org/10.1212/WNL.92.15_supplement.P1.3-020 Letters to the Editor
Prediction and Visualization of Alzheimer's Disease Using Deep Learning Models

Symptoms of Alzheimer's disease are dullness, memory loss, and an inability to socialize. These symptoms of Alzheimer's disease are caused by the shrinking of the brain, which leads to the death of brain cells and prevents the patient from accessing his or her memories and making normal decisions. Alzheimer's disease affects about 10 percent of people over the age of 65 in the United States. But even with such a large number of patients, scientists still don't know much about Alzheimer's disease. Currently, scientists believe that the dominant causes of Alzheimer's are age and family history. The mainstay of diagnosing Alzheimer's disease is a combination of patient history, neuropsychology, and MRIs, as well as the use of medications to slow down the disease (Alzheimer's disease is not curable at the current state of medical care). However, as the United States and a growing number of countries around the world experience declining fertility rates and aging societies, the number of patients with Alzheimer's disease is beginning to increase. As a result, society's medical resources are becoming overwhelmed by the diagnosis of Alzheimer's disease. Society needs a more efficient way to diagnose Alzheimer's disease. Therefore, some scholars began to try to use AI deep learning to carry out the prediction of Alzheimer's disease. After validation, the network model trained using AI deep learning can now achieve a diagnosis of Alzheimer's disease accuracy better than that of ordinary neurologists. Thus, it can be seen that the direction of AI deep learning is feasible for the future to solve the problem of overloading the social healthcare system with Alzheimer's diagnosis. This paper is based on the FCN model in Development and Validation of an Interpretable Deep Learning Framework for Alzheimer's Disease Classification. We also used the same ANDI dataset as that paper. The model is an FCN and it randomly selects 3000 voxels of size 47x47x47 from each MRI scan for each training session #go back to the FCN section of the paper#. This FCN model is divided into six convolutional blocks. The first four convolutional blocks are 3D Convolutional Layer #explain more about these four convolutional blocks#. The remaining two convolutional blocks act as speedups for model efficiency #explain more about these two convolutional blocks convolutional blocks (speedups for model efficiency)# . After training, the final model that comes out can successfully predict the MRI images. After completing the reconstruction of this model and going through 3000 epochs of training, the model is slightly less accurate #To be completed#. But the model already has the ability to make predictions on MRI images.
Research on Investment Income of Gold and Bitcoin

In financial markets, gold and Bitcoin are common investment assets. Under a fixed commission rate, this paper predicts price changes by referring to financial indicators and established an investment strategy model influenced by known price data. This problem is part of the 2022 U.S. Mathematical Contest in Modeling (MCM) Problem C. Using the Autoregressive Integrated Moving Average (ARIMA) model to predict prices, this paper obtains visualized prediction data sequences, establishes evaluation indicators for bull and bear markets, calculates buying scores, and verifies the accuracy of the investment strategy using a multi-objective dynamic programming model.
Application of the Planning Model in Mathematical Modeling

In recent years, planning models have been deeply loved by participants in mathematical modeling competitions. The basic idea is to determine the decision variable and the target function and solve it, and then use the traditional numerical solution method or the current relatively emerging intelligent optimization algorithm to obtain the optimal solution. Planning models are widely used in many fields such as physics, chemistry, dynamics and optics. This paper discusses the practical application of the model in the last three years, and discusses the application of the model in daily life. It provides reference opinions for the subsequent participants to systematically learn this model.
Information Seeking Anxiety Amongst Postgraduate Students of Punjab Agricultural University, Ludhiana

This paper is envisioned to investigate the Information Seeking Anxiety (ISA) among postgraduate (masters’ and PhD) students of Punjab Agricultural University, Ludhiana. The Information Seeking Anxiety Scale (ISAS) developed by Erfanmanesh, et al., containing 47 statements representing ISA under seven components having Cronbach alpha values reported to be at 0.902, was used as a data collection tool. 108 students participated in the survey. About 70 % respondents experienced mild level of anxiety. The gender-based difference in ISA associated with ‘Computer and the Internet’ was found to be significant at .05 (t= 2,426), females being less anxious. The location of the students did not influence their ISA, and different components of the ISAS were found to be interrelated, affecting the overall anxiety level. Prevalence of low to severe levels of ISA amongst students mandated the need for planning and execution of well-prepared information literacy programmes.
Website-Based Savings and Loans Data Processing Information System at the Office of Cooperatives and UMKM Medan Helvetia District

At the Cooperative Office, currently the process of processing savings and loans data is not optimal because the processing of savings and loans data still uses manual methods. Data processing like this can lead to data loss and insecure data storage. Therefore, the research will create a data processing system with sufficient computerization. So that the report that will be needed can be processed appropriately by the medan helvetia sub-district cooperative. From the problems that have been obtained so that a solution arises from its handling by implementing a web site-based savings and loans information system, so that with the existence of a web site-based information system, this research can
Village Activity Management Information System with Mobile-Responsive User Interface Design and Usability Test

The village is a small part of the city that manages and regulates the governance system in a smaller scope. In carrying out its work, the village has structured activities in realizing the results of these activities. Village activities include several parts. Activities are often carried out in the village both related to the village office, employees and activities related to the community. So that village activities can be monitored properly and can also be seen directly by the community, this activity needs to be informed to the community through an information system or website that can be accessed directly by the wider community. The current village activity management system still uses a manual system and is not optimal. This research aims to build a village activity management information system design that is responsive to mobile which can provide information about activities carried out through the village office to the general public who live around the village or in other areas. Activity information will be managed by the village office admin directly so that they can read or follow up on feedback given by the community on village activities that have been, are being or will be taking place. The information system that is built is expected to be able to assist the village office in carrying out existing activities in the village of Klambir Lima Gardens so that it can be carried out to improve the quality of subsequent activities
PERFORMANCE STUDY OF IRRIGATION NETWORK IN RENGGUNG IRRIGUNG AREA, LOMBOK CENTRAL REGENCY

The impact of the decline in irrigation performance is direct and indirect. The direct impact is a decrease in productivity, a decrease in cropping intensity and an increase in farming risk. The indirect impact is the weakening of the farmer's commitment to maintaining the paddy field ecosystem because the poor performance of irrigation makes the land less conducive for farming, especially rice crops. In order to obtain an overview of the condition of the irrigation areas being managed, it is necessary to conduct a study of the irrigation areas, to determine the conditions of irrigation performance and to determine priorities for handling the rehabilitation of irrigation networks and to make policies. DI performance appraisal evaluation results. Renggung is 75.8% where the performance condition of Irrigation Area of Renggung Irrigation is Good Performance.
Expert System Application Design for Diagnosing Damage to The Charger Rectifier Panel with A Website-Based Forward Chaining Method

In the increasingly complex world of work, as technology and information continue to evolve, there is a need for a medium that can leverage information to support business processes or activities in an organization, making them more effective and efficient. PT. Swadaya Engineering, a company operating in the electrical and telecommunications industry located in South Jakarta, is facing a problem of frequent damage reports on rectifier charger panels that are difficult to convey manually through phone calls. This constraint is a hindrance to improving the effectiveness and efficiency of the company, causing customer dissatisfaction due to a lack of information obtained. To address this issue, the author developed an expert system application for diagnosing rectifier charger panel damage based on a website using forward chaining as the application development method. The purpose of designing this application is to improve the effectiveness and efficiency of the company in delivering information on rectifier charger panel damage and increasing customer satisfaction in diagnosing such damage. It is expected that this expert system application will be an effective medium for the company to leverage information and support business processes or activities that are carried out.
Website Design at SDN Cipete Utara 07

The easiest way to introduce information to the public is to use technological developments, currently technology is a part of everyday life. Technology is needed in all fields, one of which is in the field of education, for the information society education is needed to know the condition of education in Indonesia, because education is a very important factor for society to increase intelligence, other factors with the use of technology are the most important. much needed by using technological facilities utilizing both desktop and web-based applications can help human activities. so in the world of education also keep abreast of developments, because of current demands that require society to better understand technological developments, schools need to continue to innovate in improving services and more comprehensive interaction with student guardians in particular and society in general. One of them is by utilizing internet media (school website). Departing from these needs, schools need to have media that can be used as a means of interaction between the school and the community and as a means of school existence in cyberspace, and to introduce schools to the community, schools must also be able to provide facilities that are easily known, one of which is using website. With a website, more information about the school can be provided to the public. In addition, the website also raises the status of the school.
Developing A New Model for Context-Awareness in Ambient Intelligence

Ontologies are a powerful way to model context, thanks to their expressiveness, ability to share knowledge, support for logical inference, and extensibility. While there are many generic ontology that capture and represent general context concepts, such as the SOCAM and CoOL projects, they are not tailored specifically for ambient intelligence and smart homes. This research aims to develop a specific ontology for these domains, building on existing generic ontologies and incorporating logical inference capabilities to assist people with reduced mobility and the elderly in carrying out their daily activities without constant assistance from others.
Evaluation of Higher Order Target Models in Radar And IRST Data Fusion

In general, the motion of maneuvering targets is described by acceleration model, which is a kinematic model, including position derivatives up to the second order. It is found that for tracking highly maneuvering targets, it is necessary to include higher order position derivatives in the model. A model including derivatives of position up to the third order called the jerk model is presented. In this paper, the tracking performance of an extended Kalman filter with the jerk model is evaluated and compared with that of an extended Kalman filter with acceleration model for fusion and tracking of a maneuvering target sensed by IRST and radar.