Number Of Emails Research Articles

USING COMMUNICATION AND COLLABORATION TOOLS IN VIRTUAL LEARNING ENVIRONMENTS MOODLE FOR MATHEMATICS IN PRIMARY SCHOOL

With the advancement of information and communication technologies, teaching mathematics in a real-life classroom is combined with teaching in a virtual learning environment (VLE). It is important to determine how a primary school teacher can use VLE communication and collaboration tools to teach mathematics primary school students. Participants – 4th grade students ((n = 51). Access to quantitative studies has been chosen for the study. Methods of study: Analysis of scientific literature, testing, descriptive statistics, and inference statistics. Data from the pilot study and the educational experiment were processed using version 23 of the IBM SPSS Statistical Package for Social Sciences. The normality of the variable distribution was tested using the Shapiro-Wilk test. Throughout the research, decisions are taken at a value a = 0.05. Study adhered to the fundamental principles of the European Code of Conduct for Study Ethics. The curator of the education was in contact with the students and their parents by e-mail and using the VLE communication and collaboration tools (messages, forums, feedback). The aim was to find out whether the number of emails and messages sent by the curator affected the students’ learning time in the VLE. The hypothesis of zero Pearson coefficient equality in the population is checked. There was a statistically significant weak relationship between the number of emails sent by the curator of the curriculum, the number of messages for students and the time spent by the student for the lessons of the curriculum. There was a mean relationship in the boy’s group, but there was no statistically significant relationship in girls’ group. There was also a statistically significant weak relationship between e-mails sent by the curriculum curator, the number of messages sent to students and the evaluation of the lessons of the curriculum. There was an average relationship in the boy’s group, but in the girl’s group there was no statistically significant relationship between the emails sent by the tutor, the number of messages to students and the evaluation of the lessons of the curriculum. This confirms the theory of constructivism that VLE is suitable for education because teachers can act as learning facilitators to communicate with each other during learning.

Individual and Work-Related Predictors of Exhaustion in East and West Germany.

Chronic exhaustion is a consequence of detrimental working conditions and demands, as well as inadequate coping techniques, potentially resulting in burnout. Previous research has studied occupational environment and individual factors as predictors of exhaustion. Although these differ between former East and West German states, the regional distinction regarding exhaustion has been neglected. To fill this gap, we used the Copenhagen Burnout Inventory in a representative German sample from 2014 to assess the burnout symptom exhaustion. Estimating ordinary least squares regressions, important burnout predictors were compared between the former East and West German states. Regional differences concerning occupational environments were related to the associations between individual factors, situational aspects of technostress and exhaustion. Associations between individual factors (e.g., female sex, lower working hours, age, partnership status, and household income) and exhaustion were stronger in East Germany, whereas technostress (strain of internet use, number of e-mails during leisure time, and social pressure to be constantly available) was more strongly associated with exhaustion in West Germany. Despite lower financial gratification and a higher social pressure to be constantly available in the East, West Germans were more afflicted by exhaustion. Individual factors and technostress should thus be considered when focusing on job-related mental health issues.

Enhancеd Analysis Approach to Detect Phishing Attacks During COVID-19 Crisis

Abstract Public health responses to the COVID-19 pandemic since March 2020 have led to lockdowns and social distancing in most countries around the world, with a shift from the traditional work environment to virtual one. Employees have been encouraged to work from home where possible to slow down the viral infection. The massive increase in the volume of professional activities executed online has posed a new context for cybercrime, with the increase in the number of emails and phishing websites. Phishing attacks have been broadened and extended through years of pandemics COVID-19. This paper presents a novel approach for detecting phishing Uniform Resource Locators (URLs) applying the Gated Recurrent Unit (GRU), a fast and highly accurate phishing classifier system. Comparative analysis of the GRU classification system indicates better accuracy (98.30%) than other classifier systems.

A network Poisson model for weighted directed networks with covariates

The edges in networks are not only binary, either present or absent, but also take weighted values in many scenarios (e.g., the number of emails between two users). The covariate-p 0 model has been proposed to model binary directed networks with the degree heterogeneity and covariates. However, it may cause information loss when it is applied in weighted networks. In this paper, we propose to use the Poisson distribution to model weighted directed networks, which admits the sparsity of networks, the degree heterogeneity and the homophily caused by covariates of nodes. We call it the network Poisson model. The model contains a density parameter μ, a 2n-dimensional node parameter and a fixed dimensional regression coefficient of covariates. Since the number of parameters increases with n, asymptotic theory is non standard. When the number n of nodes goes to infinity, we establish the -errors for the maximum likelihood estimators (MLEs), and which are for and for up to an additional factor. We also obtain the asymptotic normality of the MLE. Numerical studies and a data analysis demonstrate our theoretical findings.

Review of a paediatric inflammatory bowel disease service during the pandemic and the impact of the CNS role.

Inflammatory bowel disease (IBD) is a chronic relapsing and remitting condition. The COVID-19 pandemic has severely disrupted provision of medical care across the world. IBD clinical nurse specialists (CNSs) played a pivotal role in the care of children with IBD during the pandemic national lockdown and in the recovery phase. This article aims to look at the impact of COVID-19 on the paediatric IBD service in one children's hospital and the effect on the IBD CNSs' workload. A retrospective review of clinical notes and the service's IBD database from January 2019 to September 2020. There was a significant increase in the number of email and telephone contacts to the IBD CNS team during lockdown. There was an increase in virtual clinics, and an increase in new IBD patients coming to the service, but a reduction in the number of face-to-face consultant clinics. COVID-19 has disrupted medical services to children with IBD and led to a reduction in face-to-face activities but has also led to a significant increase in virtual activities. CNSs have taken up a wider role to cover patient care during a time of both medical and nursing redeployment.

Elastic language in academic emails: Communication between a PhD applicant and potential supervisors

ABSTRACT This paper examines how and why elastic language (EL) is used in email communication between a PhD applicant and potential supervisors. It addresses the factors that are involved in EL use when the genre is the same but speech acts differ, which fills a gap in existing research. Based on a corpus of student–supervisor email correspondence, the forms (elastic quantifiers, intensifiers, possibility indicators, subjectivizers and general stretchers) and functions of EL (mitigation and providing the right amount of information) are investigated. A significant statistical difference in the distribution of the five forms of EL between two types of emails (follow-up emails vs. decline emails) is revealed: follow-up emails are more elastic than decline emails. These two types of emails also have distinct rank order and item-level differences. Four factors affecting the frequency of occurrence of EL are identified: the content of the reply, the number of emails exchanged, the possibility that subsequent emails will be exchanged and the level of rapport established through the emails. The findings are important because understanding how EL is used will enable us to contribute to effective communication in academic discourse and beyond.

Email Consultations Between Patients and Doctors in Primary Care: Content Analysis.

BackgroundIncreasingly, consultations in health care settings are conducted remotely using a range of communication technologies. Email allows for 2-way text-based communication, occurring asynchronously. Studies have explored the content and nature of email consultations to understand the use, structure, and function of email consultations. Most previous content analyses of email consultations in primary care settings have been conducted in North America, and these have shown that concerns and assumptions about how email consultations work have not been realized. There has not been a UK-based content analysis of email consultations.ObjectiveThis study aims to explore and delineate the content of consultations conducted via email in English general practice by conducting a content analysis of email consultations between general practitioners (GPs) and patients.MethodsWe conducted a content analysis of anonymized email consultations between GPs and patients in 2 general practices in the United Kingdom. We examined the descriptive elements of the correspondence to ascertain when the emails were sent, the number of emails in an email consultation, and the nature of the content. We used a normative approach to analyze the content of the email consultations to explore the use and function of email consultation.ResultsWe obtained 100 email consultations from 85 patients, which totaled 262 individual emails. Most email users were older than 40 years, and over half of the users were male. The email consultations were mostly short and completed in a few days. Emails were mostly sent and received during the day. The emails were mostly clinical in content rather than administrative and covered a wide range of clinical presentations. There were 3 key themes to the use and function of the email consultations: the role of the GP and email consultation, the transactional nature of an email consultation, and the operationalization of an email consultation.ConclusionsMost cases where emails are used to have a consultation with a patient in general practice have a shorter consultation, are clinical in nature, and are resolved quickly. GPs approach email consultations using key elements similar to that of the face-to-face consultation; however, using email consultations has the potential to alter the role of the GP, leading them to engage in more administrative tasks than usual. Email consultations were not a replacement for face-to-face consultations.

Postgraduate instructors’ formative feedback on EFL students’ assignments in email communication: A gender-based study

The present study seeks to delve into the intricacies of feedback strategies adopted by male and female Jordanian EFL postgraduate university instructors when responding to their students’ assignment submissions and inquiries via asynchronous communication mode, namely email communication, to see if there are any significant differences in their use of these strategies due to the gender of the instructors (male vs. female). A corpus of 180 emails was put under investigation (90 sent by male teachers and 90 sent by female instructors). These were analyzed quantitatively using a t-test to capture if there are significant differences in the use of formative feedback strategies between male and female Jordanian EFL instructors. The analysis was couched within a set of frameworks which all provided different types of corrective feedback, namely, Schute (2008) and Narciss and Huth (2004). Subsequently, a qualitative analysis followed in order to show how and why teachers implement a given formative feedback strategy. The findings indicate that female instructors employed more formative feedback strategies in comparison with their male counterparts. The most frequently used strategy among female teachers was direct feedback, the provision of cues and information tutoring, while male teachers made more use of questioning and in a number of emails, they provided no feedback. In light of the findings of the present study, some pedagogical implications might come to the fore.

A Survey of the Implementation and Usage of Electronic Dental Records in Private Dental Practices in Mississippi

Implementation of electronic health records by the Health Information Technology for Economic and Clinical Health has led to the implementation of electronic dental records in dental offices. The study was conducted to determine the state of implementation and usage of electronic dental records by the private general and pediatric dental practices in Mississippi as well as reasons why the dental practices are not moving forward with the advanced technology. A survey consisting of six research questions was emailed via SurveyMonkey to 712 private general and pediatric dental practices in Mississippi with an invitation to participate in the study: 116 responded (16% response rate) and 104 consented to participate (89.66%). The data collection process transpired over a six-week period (September 18 – October 29, 2017). Results of the survey indicated dental practices in Mississippi using electronic dental records were 46.07%, electronic dental records with paper records were 42.70%, and only paper records were 11.24%. Dissemination of the study results among medical and dental practitioners may raise awareness and thus encourage more dentists to embrace EDRs. The response rate was affected by the number of dental practices that chose not to participate or did not open the survey email as well as the number of emails that were undeliverable. A second limitation was the lack of certainty of collecting all email addresses through the collection method. Third, there was no certainty that the person who responded knew the correct answers.

S105. DIGITAL BIOMARKERS FOR THE ASSESSMENT OF COGNITIVE, BEHAVIORAL AND FUNCTIONAL OUTCOMES IN INDIVIDUALS WITH SCHIZOPHRENIA

BackgroundAn individual’s mental health is best captured by considering the overall associations of biological, behavioral, and social functions that comprise the framework of individual experience. As such, accessing data on various health indicators concurrently can influence prediction of disease progression or change in response to treatment. Data generated passively by smartphones to measure human behavior has generated significant research interest and has increasingly been utilized in psychiatric disorders. In schizophrenia, passive and continuous assessment of how an individual uses their mobile device may give rise to clinically useful markers that can be used to improve treatment processes, adapt treatment choices, identify early risk for relapse to initiate clinical intervention, and develop new clinical models. A promising approach is to leverage current advances in mobile technology, data analytics and machine learning to enable automated and fast phenotyping of digital data. . In this context, the workflow for phenotyping (passive data collection → data storage and curation → trait extraction → machine learning/classification → models/apps for decision support) has to be carefully designed and efficiently executed to minimize resource usage and maximize utility. Digital phenotyping can be used in conjunction with standard care to reduce time to recognition and acknowledgement that worsening of a symptom needs to be addressed, to reduce time to receiving appropriate level of care, to increase ability to analyze and collect data from a variety of sources to improve mental health needs assessment and delivery of services, and to advance outcome measurement through comparison of passive and active data sets.AimThe aim of this pilot study is to test whether a smartphone digital phenotyping application can help detect early signs of treatment failure or response in individuals with chronic schizophrenia after discharge from hospital.Methods17 individuals with DSM-5 schizophrenia were provided with a smartphone and digital phenotyping app, MindStrong Health app, following discharge from an inpatient psychiatric facility. The participants were followed for 6 months with monthly rater administered evaluations assessing neurocognition (Brief Assessment of Cognition in Schizophrenia (BACS)), symptomatology (PANSS; CGI-S/I), quality of life (SF-36), healthcare utilization, alcohol/drug use, level of clinical insight and depression (Calgary Depression Rating Scale, CDSS). Digital phenotyping data included gestures (swipes, taps, other), orientation (the way the phone is pointing), acceleration (sudden movements of the phone), keystroke patterns with characters encoded, number of calls made, number of emails sent, number of text messages sent, and location information from the GPS. Predictive models were built using multiple machine learning techniques - random forest plots, linear regression and gradient boosting, to predict the target scores based on phone usage patterns.ResultsOf the 17 enrolled participants, 10 provided analyzable data (i.e., had at least 22 target days with data). There was a gradual reduction of passive data generation due to either non-use of the smart phone or due to non-recharging of the device. The mean PANSS score was 80.12 (14.56). BACS scores corresponding to motor speed (token motor task), verbal fluency (category instances, letter fluency), and attention and processing speed (symbol coding) were found to be highly correlated with a composite digital phenotyping marker while scores on the PANSS or CDSS were not.DiscussionThe study provides a basis for using smartphone-base mobile apps to use as an augmentation within clinical practice to gather further information on patients outside the clinic setting, focusing on their behavior in the ‘real world.’ In particular, the cognitive data derived from the digital device correlated well with rater administered traditional cognitive ratings. Collecting digital data can provide a much needed window into the lives of patients in between normally scheduled visits, while minimizing costs and inconvenience to the patient. Studies with larger sample sizes are required to assess relationships with relapse, rehospitalizations and treatment failure.

A framework for sentiment analysis in Arabic text

<p>Over the last decade there has been an increase in number of E-mails or comments to a company via social media sites, to satisfy their customers, the company must take in to consideration these messages and comments and know whether the customers are satisfied with what the company offers or not. Several techniques have been proposed to analyze the sentiment of the comment writer. Dealing with the Arabic language is faced with many challenges, such as it is a morphologically rich language and how to return the word to its original root. In this paper the challenges of dealing with the Arabic language were reviewed and a framework was also established to analyze the comments in Arabic and classify it into positive, negative or neutral sentiment. The framework was trained and tested and then the con-clusions were drawn based on its work.</p>

¿Qué hacer con el correo electrónico en la empresa?

The number of e-mails sent daily in a corporation is growing increasingly and the lack of its control is risky for the business. In order to avoid problems, a variety of strategies of preservation or removal can be applied. Technological solutions are not enough to solve the problems, so it is necessary to start an e-mail retention policy which points out the goals of the organization, applies the right technology and raises awareness about the steps to follow to manage e-mails among the employees.

Immunization Readiness of a Deploying Emergency Medical Team

Introduction:It is a requirement for a World Health Organization verified Emergency Medical Team (EMT) that all members be immunized against common diseases in the deploying region. Most jurisdictions use private suppliers such as travel doctors for immunization services. When a deployment is announced, members are nominated by their jurisdiction under the condition they are fully immunized. It is up to the individual to monitor their immunization status.Aim:To determine how many members nominated for deployment were fully immunized.Methods:Nominated members sent their completed vaccination record to a central location for assessment of their immunization status. The following data were recorded: vaccination status, last-minute booster doses required, and the number of emails sent by the assessor in processing the records. The number of phone calls made and received were not recorded.Results:To complete the skills matrix for a field hospital containing an emergency department and operating theater (an EMT type 2), 61 members were nominated. At the time of assessment, 32 (52%) were fully immunized, requiring no further booster doses (vaccinations or serology tests). Three members were removed from the deployment as they were not fully immunized. Last-minute booster doses were required by 27 (44%) members, with a total of 74 booster doses administered (range 0-5). 19 of the booster doses administered were immunizations required to work in any health facility in Australia. The most common vaccines requiring booster doses were rabies (n=21) and typhoid (n=15). 58 emails were sent over a period of 5 days to 24 members to clarify vaccination status.Discussion:This deployment highlighted a gap in members’ perception of their immunization status, leading to delays in deployment readiness for the team. A new electronic system where vaccine status tracking occurs in real time should address this issue.

Dynamically Managing a Profitable Email Marketing Program

Although email marketing is highly profitable and widely used by marketers, it has received limited attention in the marketing literature. Extant research has focused on either customers’ email responses or the “average” effect of emails on purchases. In this article, the authors use data from a U.S. home improvement retailer to study customers’ email open and purchase behaviors by using a unified hidden Markov and copula framework. Contrary to conventional wisdom, the authors find that email-active customers are not necessarily active in purchases, and vice versa. Furthermore, the number of emails sent by the retailer has a nonlinear effect on both the retailer's short- and long-term profitability. Through a counterfactual study, the authors provide a decision support system to guide retailers in making optimal email contact decisions. This study shows that sending the right number of emails is vital for long-term profitability. For example, sending four (ten) emails instead of the optimal number of seven emails can cause the retailer to lose 32% (16%) of its lifetime profit per customer.

Email Classification Using Behavior and Time Features

The various forms and tremendous number of spam emails have brought great challenges to accurate email classification. In this paper, we present a behavior- and time-feature-based email classification method. Based on email logs, email social networks are built through the extraction of entities and relations from the email records using the MapReduce model. By combining behavior features from social networks and time features from email sending intervals, we adopt a Support Vector Machine based classifier to identify spammers and nonspammers. Compared with the current email classification methods, the advantages of our method are: (1) in addition to the behavior-based features, our method integrates the time feature to facilitate email classification; (2) to efficiently handle the vast number of emails, we employ the MapReduce model to extract the behavior- and time-based features on the email social network. Experiments on real email data of three years show that the proposed method achieves better classification accuracy.

Improvement through/despite Emails

AbstractEmail flooding, deleting emails without reading them – both common parts of our daily workflows. Emails need to motivate their recipients to read them and of course, the number of emails we receive every day play a crucial role. The present paper shall not only describe how the email communication between the members of a research project could be enhanced, but also show how helpful emails are for implementing strategic communication optimisation. By involving the project members as probands in a study based on AMASA (Research project “Accessing Medicines in Africa and South Asia”) emails for developing a restructuring of the internal communication, the process of communication optimisation was accepted by the project members and the strategic superiour aims could be met.

Effect of a post-paid incentive on response rates to a web-based survey

We randomized half of the sample from two southern California medical centers to a post-paid incentive (n = 1,795) and half to no incentive (n = 1,797) for completing a web-based survey about their experiences with health care. Respondents in the incentive group were given the choice between a $5 cash or Target® e-certificate. The characteristics of respondents in the incentive and control groups was similar on age, education, length of membership in the plan, number of emails sent and visits to the primary care doctor in the 12 months prior to sampling, and their global rating of the doctor; the incentive group had more Asians (8% vs. 5%, χ 2 (1 df) = 7.92, p = 0.005) and fewer Blacks/African Americans (2% vs. 4%, χ 2 (1 df) = 11.0, p =0.001) than the no incentive group. Those randomized to the incentive were significantly more likely to respond to the survey than those in the control group (57% vs. 50%, t (df = 3590) = 4.06, p <0.0001). Item non response rates were similar for those in the incentive and the control groups. Those randomized to the incentive condition who completed the survey were more likely to prefer a cash incentive over the e-certificate (69% of the incentives delivered to web respondents were in the form of cash). The unit cost per incentive was $8.32 for cash and $7.49 for the e-certificate. The results of this experiment indicate that a post-paid incentive can significantly increase the response rate to a web-based survey.

Unsupervised Extraction of Signatures and Roles from Large-Scale Mail Archives

In this paper, we focus on the problem of signature and role extraction from largescale mail archives. Due to the huge scale and great diversity of large-scale mail archives, the extraction methods should not only be able to extract signatures and roles accurately without any training data, but also be general enough to work well with largescale mail archives with different characteristics. To address this problem, we first propose an unsupervised language model based method to identify sig-natures from large numbers of emails, and then present an unsupervised two-stage method to effectively extract roles from the identified signatures. Experimental results on two real-world datasets show that our methods are general and effective for both the signature and role extrac-tion from large-scale mail archives.

Advantages and disadvantages of educational email alerts for family physicians: viewpoint.

BackgroundElectronic knowledge resources constitute an important channel for accredited Continuing Medical Education (CME) activities. However, email usage for educational purposes is controversial. On the one hand, family physicians become aware of new information, confirm what they already know, and obtain reassurance by reading educational email alerts. Email alerts can also encourage physicians to search Web-based resources. On the other hand, technical difficulties and privacy issues are common obstacles.ObjectiveThe purpose of this discussion paper, informed by a literature review and a small qualitative study, was to understand family physicians’ knowledge, attitudes, and behavior in regard to email in general and educational emails in particular, and to explore the advantages and disadvantages of educational email alerts. In addition, we documented participants’ suggestions to improve email alert services for CME.MethodsWe conducted a qualitative descriptive study using the “Knowledge, Attitude, Behavior” model. We conducted semi-structured face-to-face interviews with 15 family physicians. We analyzed the collected data using inductive-deductive thematic qualitative data analysis.ResultsAll 15 participants scanned and prioritized their email, and 13 of them checked their email daily. Participants mentioned (1) advantages of educational email alerts such as saving time, convenience and valid information, and (2) disadvantages such as an overwhelming number of emails and irrelevance. They offered suggestions to improve educational email.ConclusionsThe advantages of email alerts seem to compensate for their disadvantages. Suggestions proposed by family physicians can help to improve educational email alerts.

A NOVEL E-MAIL CLASSIFICATION FRAMEWORK FOR SUPPORTING DECISION MAKERS IN EDUCATIONAL INSTITUTIONS

Abstract Rapid growth of the Internet has led to a proliferation of emails. Nowadays, it is common for an email user to receive tens or even hundreds of emails every day. To organize our emails so that they can be searched and maintained efficiently, we often group them into files. However, reading the emails one by one and filing them by hand is still a tedious process. Moreover, the problem is getting worse as the number of emails and folders keep increasing. Thus, the problem of automatic email classification is important and has gained much attention, especially in recent years. In this paper, we study the problem and focus on building a new proposed system used to classify emails automatically based on VCAD algorithm to help decision makers in educational institutions. Key Words: Email classification; Naive bayes; Support Vector Machines, k-nearest neighbor; Vector Cosine Angle Distance, Euclidean Distance .