Web-based Users Research Articles

A comparison of Lab- and Web-based elicited imitation: Insights from explicit-implicit L2 grammar knowledge and L2 proficiency

Abstract Elicited imitation (EI) tasks are a practical tool for measuring second language (L2) knowledge and skills. In this study, we implemented a web-based EI task that measures English morphosyntactic knowledge and compared its measurement properties to a traditional laboratory-based EI. A cohort of 149 L2 English learners engaged in the web-based EI task, and 151 participants completed a traditional lab-based EI counterpart. Correlation analyses revealed a significant, comparable relationship between English proficiency and the two EI versions, with the ungrammatical items showing less consistency that neither improved nor harmed the overall EI effectiveness. Factor analyses corroborated the validity of web-programmed EI, with both EI versions relating similarly to time-pressured, implicit knowledge and untimed, explicit knowledge measures. Our results suggest the potential for utilizing web-based EI to substitute lab-based tasks, enabling larger-scale, more diverse sampling. We end with implications for future web-based EI task users and include a coding guideline for customized web-based EI use.

Profiles of Web-based Portal Users with Inflammatory Bowel Disease.

Web-based portals can enhance communication between patients and providers to support IBD self-management and improve care. We aimed to identify portal use patterns of patients with inflammatory bowel disease (IBD) to inform future web portal-based interventions and portal design. Patients with IBD receiving care at the University of Michigan between 2012 and 2021 were identified. Meta-data from electronic logs of each patient's most recent year of portal use were abstracted. Portal engagement was characterized in terms of intensity (ie, frequency of use); comprehensiveness (ie, number of portal functions used); and duration (ie, quarters per year of portal use). We used k-means clustering, a machine-learning technique, to identify groupings of portal users defined in terms of engagement features. We found 5605 patients with IBD who had accessed their portal account at least once. The average age was 41.2 years (SD 16.7), 3035 (54.2%) were female, and 2214 (39.5%) received immune-targeted therapies. We identified 3 patterns of portal engagement: (1) low intensity users (29.5%); (2) moderate intensity, comprehensive, and sustained users (63.3%); and (3) high intensity, comprehensive, sustained users (7.2%). Patients with more intense, comprehensive, and sustained use of the portal were older, female, with more comorbidities, and were more likely to receive immune-targeted therapies. Understanding distinct patterns of portal use can inform portal-based interventions and portal design. Patient portals may be particularly helpful in delivering assistance to those with comorbidities and those receiving immune-targeted therapies-many of whom demonstrate more intense, comprehensive, and sustained portal use.

An Investigation of Factors Influencing the Postponement of the Use of Distributed Research Networks in South Korea: Web-Based Users' Survey Study.

Distributed research networks (DRNs) offer researchers the advantage of using various big data sets that are difficult to access and use. In addition, since the data are not physically exposed to the outside, it is possible to conduct research using medical data safely without data exposure. However, researchers still have difficulties and are concerned about using DRNs. Few studies involving DRNs have been conducted from the user's viewpoint. Therefore, it is necessary to look at DRNs from the researcher's point of view and find ways to facilitate the active use of DRNs. This study aimed to identify the factors that made researchers hesitate to use DRNs and to derive a method to facilitate active DRN use. We conducted a web-based survey of people working in the medical fields, such as hospitals and universities. We used 131 respondents' data from a survey from December 6 to 17, 2021. We conducted multiple regression analyses to determine the factors affecting the postponement of using DRNs. In addition, 2 independent sample t tests were conducted to analyze the difference between the 2 groups according to the following factors: organization, gender, experience with DRNs, length of the research career, position, and age. Performance risk (t5=2.725, P=.007) and workload from DRNs (t5=3.543, P=.001) were significantly associated with users' postponement of DRN use. Researchers working at hospitals were found to feel more burdened by DRN use than researchers working at universities (t129=1.975, P=.05). It was also found that women perceived a higher privacy risk of DRNs than men (t129=-2.303, P=.02) and that those who had experience using DRNs delayed their use less than those without experience (t129=-4.215, P<.001). It is necessary to simplify the research and approval processes to reduce the performance risk and workload of research using DRNs. To optimize the process, DRN providers should develop a way to improve users' experiences. More user-friendly functionalities should be developed from the researcher's point of view. It is necessary to continuously promote effective functionalities for DRNs to reduce concerns about privacy risks. This study identified the concerns of DRN users in terms of DRN use and suggested ways to actively use DRNs. The derived results can be reflected in planning and developing DRNs. Our research will be helpful to prepare an activation plan for DRNs.

Social Support in a Diabetes Online Community: Mixed Methods Content Analysis

Patients with diabetes may experience different needs according to their diabetes stage. These needs may be met via online health communities in which individuals seek health-related information and exchange different types of social support. Understanding the social support categories that may be more important for different diabetes stages may help diabetes online communities (DOCs) provide more tailored support to web-based users. This study aimed to explore and quantify the categorical patterns of social support observed in a DOC, taking into consideration users' different diabetes stages, including prediabetes, type 2 diabetes (T2D), T2D with insulin treatment, and T2D remission. Data were collected from one of the largest DOCs in Europe: Diabetes.co.uk. Drawing on a mixed methods content analysis, a qualitative content analysis was conducted to explore what social support categories could be identified in users' posts. A total of 1841 posts were coded by 5 human annotators according to a modified version of the Social Support Behavior Code, including 7 different social support categories: achievement, congratulations, network support, seeking emotional support, seeking informational support, providing emotional support, and providing informational support. Subsequently, quantitative content analysis was conducted using chi-square post hoc analysis to compare the most prominent social support categories across different stages of diabetes. Seeking informational support (605/1841, 32.86%) and providing informational support (597/1841, 32.42%) were the most frequent categories exchanged among users. The overall distribution of social support categories was significantly different across the diabetes stages (χ218=287.2; P<.001). Users with prediabetes sought more informational support than those in other stages (P<.001), whereas there were no significant differences in categories posted by users with T2D (P>.001). Users with T2D under insulin treatment provided more informational and emotional support (P<.001), and users with T2D in remission exchanged more achievement (P<.001) and network support (P<.001) than those in other stages. This is the first study to highlight what, how, and when different types of social support may be beneficial at different stages of diabetes. Multiple stakeholders may benefit from these findings that may provide novel insights into how these categories can be strategically used and leveraged to support diabetes management.

The IPD-IMGT/HLA Database.

It is 24 years since the IPD-IMGT/HLA Database, http://www.ebi.ac.uk/ipd/imgt/hla/, was first released, providing the HLA community with a searchable repository of highly curated HLA sequences. The database now contains over 35 000 alleles of the human Major Histocompatibility Complex (MHC) named by the WHO Nomenclature Committee for Factors of the HLA System. This complex contains the most polymorphic genes in the human genome and is now considered hyperpolymorphic. The IPD-IMGT/HLA Database provides a stable and user-friendly repository for this information. Uptake of Next Generation Sequencing technology in recent years has driven an increase in the number of alleles and the length of sequences submitted. As the size of the database has grown the traditional methods of accessing and presenting this data have been challenged, in response, we have developed a suite of tools providing an enhanced user experience to our traditional web-based users while creating new programmatic access for our bioinformatics user base. This suite of tools is powered by the IPD-API, an Application Programming Interface (API), providing scalable and flexible access to the database. The IPD-API provides a stable platform for our future development allowing us to meet the future challenges of the HLA field and needs of the community.

Using search trends to analyze web-based users' behavior profiles connected with COVID-19 in mainland China: infodemiology study based on hot words and Baidu Index.

Mainland China, the world's most populous region, experienced a large-scale coronavirus disease 2019 (COVID-19) outbreak in 2020 and 2021, respectively. Existing infodemiology studies have primarily concentrated on the prospective surveillance of confirmed cases or symptoms which met the criterion for investigators; nevertheless, the actual impact regarding COVID-19 on the public and subsequent attitudes of different groups towards the COVID-19 epidemic were neglected. This study aimed to examine the public web-based search trends and behavior patterns related to COVID-19 outbreaks in mainland China by using hot words and Baidu Index (BI). The initial hot words (the high-frequency words on the Internet) and the epidemic data (2019/12/01-2021/11/30) were mined from infodemiology platforms. The final hot words table was established by two-rounds of hot words screening and double-level hot words classification. Temporal distribution and demographic portraits of COVID-19 were queried by search trends service supplied from BI to perform the correlation analysis. Further, we used the parameter estimation to quantitatively forecast the geographical distribution of COVID-19 in the future. The final English-Chinese bilingual table was established including six domains and 32 subordinate hot words. According to the temporal distribution of domains and subordinate hot words in 2020 and 2021, the peaks of searching subordinate hot words and COVID-19 outbreak periods had significant temporal correlation and the subordinate hot words in COVID-19 Related and Territory domains were reliable for COVID-19 surveillance. Gender distribution results showed that Territory domain (the male proportion: 67.69%; standard deviation (SD): 5.88%) and Symptoms/Symptom and Public Health (the female proportion: 57.95%, 56.61%; SD: 0, 9.06%) domains were searched more by male and female groups respectively. The results of age distribution of hot words showed that people aged 20-50 (middle-aged people) had a higher online search intensity, and the group of 20-29, 30-39 years old focused more on Media and Symptoms/Symptom (proportion: 45.43%, 51.66%; SD: 15.37%, 16.59%) domains respectively. Finally, based on frequency rankings of searching hot words and confirmed cases in Mainland China, the epidemic situation of provinces and Chinese administrative divisions were divided into 5 levels of early-warning regions. Central, East and South China regions would be impacted again by the COVID-19 in the future.

Semantics Matter: Cheiloschisis Web-Based Information Differs from Cleft Lip

INTRODUCTION: Increased access and availability to a seemingly endless amount of information online has made it quite onerous for both patients and physicians to find pertinent information that is suitable for the readers at all educational levels. As machine-learning algorithms become more advanced, an internet user’s initial search, which initiates these algorithms, has become pivotal. The purpose of this study was to better understand the disparity in the readability of online information in the setting of cleft lips, also known as cheiloschisis. METHODS: Google searches for the terms “Cheiloschisis” and “Cleft Lip” were performed on the same day in February 2022 on a VPN located in San Francisco, California. The top 10 nonsponsored and nonadvertised results were selected and analyzed for Flesch-Kincaid Readability Ease, Flesch-Kincaid Grade Level, Gunning Fog Index, Simple Measure of Gobbledygook (SMOG) Index, Coleman-Liau Index, and Automated Readability Index. The two cohorts were then compared using Student’s t-tests. P<0.05 was considered significant. RESULTS: Scores for cheiloschisis vs cleft lip were significantly different with regard to Flesch-Kincaid Readability Ease (mean: 40.41 and 63.76 respectively, p < 0.01), Flesch-Kincaid Grade Level (mean: 8.57 and 6.13, p < 0.05), Coleman-Liau Index (mean: 17.45 and 12.73, p < 0.01), and Automated Readability Index (mean: 7.17 and 4.98, p < 0.05; Figure). No significant differences were noted between two cohorts in Gunning Fog Score (mean: 8.32 and 7.03, p = 0.17) and SMOG index (mean: 5.73 and 6.11, p = 0.37).FigureCONCLUSION: The terminology used by all web-based users determines the ability of the user to fully comprehend the results which are populated.

KAJIAN TENTANG PERILAKU PENGGUNA E-FAKTUR WEB-BASED MELALUI PENDEKATAN TECHNOLOGY ACCEPTANCE MODEL (TAM)

This study aims to measure the extent to which taxpayers feel helped by the presence of e-faktur web-based, where to measure this the researcher uses perceived usefulness and perceived ease of use as indicators, and this research is expected to provide input for policymakers, in this case the Directorate General of Taxes regarding deficiencies or difficulties faced by taxpayers in using e-faktur web-based. The population used in this study is web-based e-invoice users and the sampling technique used is snowball sampling where the researcher chooses several research colleagues to be able to help distribute questionnaires to other respondents with the criteria determined by the researcher, namely the respondent is a taxpayer who has reported the Periodic Value Added Tax (VAT) SPT using a web-based e-invoice. This study uses a quantitative approach with primary data. The data collected was then processed using SPSS Version 25 with the Multiple Linear Regression method. This study shows the results that perceived usefulness influences on the attitude of taxpayers towards the use of e-faktur web-based, while the perception of convenience does not influence on the attitude of taxpayers towards the use of e-faktur web-based. This research is expected to be an input for policymakers, especially the Directorate General of Taxes, which is currently very aggressively reforming tax administration to provide convenience for taxpayers in fulfilling their tax compliances.

Patterns of Symptom Tracking by Caregivers and Patients With Dementia and Mild Cognitive Impairment: Cross-sectional Study.

BackgroundIndividuals with dementia and mild cognitive impairment (MCI) experience a wide variety of symptoms and challenges that trouble them. To address this heterogeneity, numerous standardized tests are used for diagnosis and prognosis. myGoalNav Dementia is a web-based tool that allows individuals with impairments and their caregivers to identify and track outcomes of greatest importance to them, which may be a less arbitrary and more sensitive way of capturing meaningful change.ObjectiveWe aim to explore the most frequent and important symptoms and challenges reported by caregivers and people with dementia and MCI and how this varies according to disease severity.MethodsThis cross-sectional study involved 3909 web-based myGoalNav users (mostly caregivers of people with dementia or MCI) who completed symptom profiles between 2006 and 2019. To make a symptom profile, users selected their most personally meaningful or troublesome dementia-related symptoms to track over time. Users were also asked to rank their chosen symptoms from least to most important, which we called the symptom potency. As the stage of disease for these web-based users was unknown, we applied a supervised staging algorithm, previously trained on clinician-derived data, to classify each profile into 1 of 4 stages: MCI and mild, moderate, and severe dementia. Across these stages, we compared symptom tracking frequency, symptom potency, and the relationship between frequency and potency.ResultsApplying the staging algorithm to the 3909 user profiles resulted in 917 (23.46%) MCI, 1596 (40.83%) mild dementia, 514 (13.15%) moderate dementia, and 882 (22.56%) severe dementia profiles. We found that the most frequent symptoms in MCI and mild dementia profiles were similar and comprised early hallmarks of dementia (eg, recent memory and language difficulty). As the stage increased to moderate and severe, the most frequent symptoms were characteristic of loss of independent function (eg, incontinence) and behavioral problems (eg, aggression). The most potent symptoms were similar between stages and generally reflected disruptions in everyday life (eg, problems with hobbies or games, travel, and looking after grandchildren). Symptom frequency was negatively correlated with potency at all stages, and the strength of this relationship increased with increasing disease severity.ConclusionsOur results emphasize the importance of patient-centricity in MCI and dementia studies and illustrate the valuable real-world evidence that can be collected with digital tools. Here, the most frequent symptoms across the stages reflected our understanding of the typical disease progression. However, the symptoms that were ranked as most personally important by users were generally among the least frequently selected. Through individualization, patient-centered instruments such as myGoalNav can complement standardized measures by capturing these infrequent but potent outcomes.

The effectiveness of web-based technology platforms in facilitating construction project collaboration: a qualitative analysis of 1,152 user reviews

The construction industry accounts for 9% of global GDP. Efforts at addressing construction’s inherent inefficiencies have over the last decade increasingly involved the deployment of web-based collaborative tools. Consequently, much research has been devoted to assessing these platforms; including interoperability, workflow management and technological limits. What has not been considered to date are the views of web-based tool users themselves as to the functionality, potency and usability of the various platforms available on the market. Currently, there are 5,300,000 documented users of web-based collaborative tools. If web-based collaboration is to be further enhanced, the views of users must be known. This study explores this dimension. Financeonline’s top six tools were considered: CoCostruct, PlanGrid, Autodesk BIM 360, Procore, e-builder and Aconex. Around 200 reviews for each tool were collected from ‘Business Software Reviews from Software Advice,’ resulting in a total dataset of 1,152 complete reviews. Text-mining analysis was applied to this dataset, using RapidMiner Studio 7.5. Thirty key terms with a frequency of over 100 occurrences were retrieved; terms such as software, manage, inform, support, easy use, function, track and friendly. These constitute the subject of the reviews. These terms were then analyzed for sentiment qualifiers; either positive or negative. A total of 804 sentiments were positive, 322 negative and 26 neutral. This study thus highlights that while 70% of user reviews of web-based collaborative tools are positive, there remains much room for improvement. Areas for improvement are also indicated by this study.

Home-based telerehabilitation: A review of remote therapy frameworks

Remote therapy frameworks play the main role in home-based telerehabilitation. These remote therapies are exergames that help in the physical and cognitive rehabilitation of the patient. The objective of this review is to present the frameworks of home-based therapies using exergames and to identify the points that can be improved in the development of future systems. To carry out this research, the criteria of the PRISMA were adopted. Literature searches were conducted up to April 2021 in the Web of Sicence, Pubmed, Cochrane, Embase and Scopus databases. The search query was: (("game*" OR "exergame*") AND ("rehabilitation") AND ("remote" OR "telerehabilitation" OR "telemedicine")). We have selected a total of fourteen studies. We found five types of frameworks: Client-Server, Web-Based, Layers, Cloud Based and Multi users. We identified that it may be advantageous to mix the features of these frameworks to have a cheaper home-based system and prevent the patient from having to purchase more powerful computers. In addition, there are some challenges that need to be studied that will also help reduce costs for the patient: 1) Reduce the need for high processing of exergames on the patient's computer; 2) Prevent the patient from having to purchase expensive external devices for motion tracking.

Communication Strategies Used to Obtain Clinical Histories Before Remotely Prescribing Antibiotics for Postal Treatment of Uncomplicated Genital Chlamydia: Service Evaluation.

BackgroundWeb-based services for testing of sexually transmitted infections are widely available across the United Kingdom. Remote prescriptions with medications posted home may support prompt treatment; however, the absence of face-to-face contact with clinicians raises clinical safety issues as medical history may not be accurately provided.ObjectiveThis service evaluation aimed to capture the use and explore the safety of 3 remote communication strategies employed within a web-based service offering remote prescriptions of antibiotics, delivered via post, for uncomplicated genital Chlamydia trachomatis. User acceptability and time-from-diagnosis-to-treatment were also obtained.MethodsThree iterations of the service were compared, where medical history was collected via SMS text message, telephone, or a secure web form before a prescription was issued. We contacted users after they were issued a prescription and completed the medical history a second time via telephone, asking when they took their medication and how they felt about the service. The primary safety measure was agreement in information supplied at 2 assessments (ie, clinical and evaluation assessment) on key elements of safe prescribing: allergies, current medications, or contraindicating clinical conditions or symptoms. Agreement in information between clinical and evaluation assessment was summarized as a binary variable. Factors associated with the assessment agreement variable were explored using univariate and multivariate analysis. The secondary evaluation measures were recall of and adherence to instructions for taking medication, time-from-diagnosis-to-treatment, and acceptability of the web-based service.ResultsAll web-based service users, resident in the London Boroughs of Lambeth and Southwark with a positive chlamydia diagnosis, who were eligible for and chose postal treatment between February 15, 2017, and October 24, 2017, were invited to participate in this service evaluation. Of 321 eligible users, 62.0% (199) participated. A total of 27.6% (55/199) users completed the clinical assessment via SMS text message, 40.7% (81/199) users via telephone, and 31.7% (63/199) users via a secure web form. Those who were assessed for prescription via SMS text message were less likely to have an agreement in safe prescribing information than those assessed via telephone (adjusted odds ratio [aOR] 0.22, 95% CI 0.08-0.61; P=.004). We found no statistically significant difference in odds of agreement between the web form and telephone assessment (aOR 0.50, 95% CI 0.17-1.43; P=.20). Median time-to-treatment was 4 days (IQR 3-5.5). In addition, 99.0% (196/199) of users reported understanding remote communication, and 89.9% (178/198) would use the service again.ConclusionsPostal treatment is an acceptable and rapid treatment option for uncomplicated genital chlamydia. Clinical assessment via SMS text message before remote prescription may not be accurate or sufficient. As health care is delivered via the web, strategies that support safe remote prescribing are increasingly important, as is their evaluation, which should be robust and carefully considered.

Update on Fengyun Meteorological Satellite Program and Development

China began to develop its meteorological satellite program since 1969. With 50-years' growing, there are 17 Fengyun (FY) meteorological satellites launched successfully. At present, seven of them are in orbit to provide the operational service, including three polar orbiting meteorological satellites and four geostationary meteorological satellites. Since last COSPAR report, no new Fengyun satellite has been launched. The information of the on-orbit FY-2 series, FY-3 series, and FY-4 series has been updated. FY-3D and FY-2H satellites accomplished the commission test and transitioned into operation in 2018. FY-2E satellite completed its service to decommission in 2019. The web-based users and Direct Broadcasting (DB) users keep growing worldwide to require the Fengyun satellite data and products. A new Mobile Application Service has been launched to Fengyun users based on the cloud technology in 2018. In this report, the international and regional co-operations to facilitate the Fengyun user community have been addressed especially. To strengthen the data service in the Belt and Road countries, the Emergency Support Mechanism of Fengyun satellite (FY_ESM) has been established since 2018. Meanwhile, a Recalibrating 30-years' archived Fengyun satellite data project has been founded since 2018. This project targets to generate the Fundamental Climate Data Record (FCDR) as a space agency response to the Global Climate Observation System (GCOS). At last, the future Fengyun program up to 2025 has been introduced as well.

Factors affecting the quality and reliability of online health information.

BackgroundInternet represents a relevant source of information, but reliability of data that can be obtained by the web is still an unsolved issue. Non-reliable online information may have a relevance, especially in taking decisions related to health problems. Uncertainties on the quality of online health data may have a negative impact on health-related choices of citizens.ObjectiveThis work consisted in a cross-sectional literature review of published papers on online health information. The two main research objectives consisted in the analysis of trends in the use of health web sites and in the quality assessment and reliability levels of web medical sites.MethodsLiterature research was made using four digital reference databases, namely PubMed, British Medical Journal, Biomed, and CINAHL. Entries used were “trustworthy of medical information online,” “survey to evaluate medical information online,” “medical information online,” and “habits of web-based health information users”. Analysis included only papers published in English. The Newcastle Ottawa Scale was used to conduct quality checks of selected works.ResultsLiterature analysis using the above entries resulted in 212 studies. Twenty-four articles in line with study objectives, and user characteristics were selected. People more prone to use the internet for obtaining health information were females, younger people, scholars, and employees. Reliability of different online health sites is an issue taken into account by the majority of people using the internet for obtaining health information and physician assistance could help people to surf more safe health web sites.ConclusionsLimited health information and/or web literacy can cause misunderstandings in evaluating medical data found in the web. An appropriate education plan and evaluation tools could enhance user skills and bring to a more cautious analysis of health information found in the web.

Energy Efficient Resource Management Techniques in Cloud Environment for Web Based Community by Machine Learning: A Survey

Cloud computing is a platform where the services of information technology are delivered by retrieval of resource from the internet through web applications and web tools instead of using direct server. In order to offer better quality of service to the larger number of web-based community users, many companies are adopting cloud computing. A dynamic number of web-based community user are interacting with each other via cloud computing. The number of online users is not just limited to manual counting figure so it is extremely important to manage each and every resource efficiently by minimising the energy consumption. To increase the performance of the system, the concepts of machine learning can be used to solve the challenges occur in cloud computing while managing resources for online communities. In this paper, we discuss the application of machine learning in cloud environment and its effect on web-based community.

Geographic Representativeness of a Web-Based Smoking Cessation Intervention: Reach Equity Analysis.

BackgroundCigarette smoking is the leading cause of preventable death and disease in the United States. Smoking prevalence is higher in rural areas than in metropolitan areas, due partly to differences in access to cessation treatment. With internet use at 89% of all US adults, digital approaches could increase use of cessation treatment and reduce smoking.ObjectiveWe investigated the extent to which smokers from rural areas use a digital cessation resource. We compared the geographic distribution of registered users of a free Web-based smoking cessation program with the geographic distribution of US smokers.MethodsWe mapped user-provided ZIP codes to Rural-Urban Continuum Codes. A total of 59,050 of 118,574 users (49.80%) provided valid ZIP codes from 2013 to 2017. We used US National Survey of Drug Use and Health data from 2013 to 2017 to compare the geographic distribution of our sample of Web-based cessation users with the geographic distribution of US smokers. Reach ratios and 95% confidence intervals quantified the extent to which rural smokers’ representation in the sample was proportionate to their representation in the national smoking population. Reach ratios less than 1 indicate underrepresentation.ResultsSmokers from rural areas were significantly underrepresented in 2013 (reach ratio 0.89, 95% CI 0.87-0.91) and 2014 (reach ratio 0.89, 95% CI 0.86-0.92), proportionally represented in 2015 (reach ratio 1.08, 95% CI 1.02-1.14) and 2016 (reach ratio 1.03, 95% CI 0.94-1.14), and proportionally overrepresented in 2017 (reach ratio 1.16, 95% CI 1.12-1.21). Smokers from Large Metro areas were proportionally represented in 2013 and 2014 but underrepresented in 2015 (reach ratio 0.97, 95% CI 0.94-1.00), 2016 (reach ratio 0.89, 95% CI 0.85-0.94), and 2017 (reach ratio 0.89, 95% CI 0.86-0.91).ConclusionsResults suggest that smokers from rural areas are more than proportionally reached by a long-standing digital cessation intervention. The underrepresentation of smokers from Large Metro areas warrants further study.

Tools4MSP: an open source software package to support Maritime Spatial Planning.

This paper presents the Tools4MSP software package, a Python-based Free and Open Source Software (FOSS) for geospatial analysis in support of Maritime Spatial Planning (MSP) and marine environmental management. The suite was initially developed within the ADRIPLAN data portal, that has been recently upgraded into the Tools4MSP Geoplatform (data.tools4msp.eu), an integrated web platform that supports MSP through the application of different tools, e.g., collaborative geospatial modelling of cumulative effects assessment (CEA) and marine use conflict (MUC) analysis. The package can be used as stand-alone library or as collaborative webtool, providing user-friendly interfaces appropriate to decision-makers, regional authorities, academics and MSP stakeholders. An effective MSP-oriented integrated system of web-based software, users and services is proposed. It includes four components: the Tools4MSP Geoplatform for interoperable and collaborative sharing of geospatial datasets and for MSP-oriented analysis, the Tools4MSP package as stand-alone library for advanced geospatial and statistical analysis, the desktop applications to simplify data curation and the third party data repositories for multidisciplinary and multilevel geospatial datasets integration. The paper presents an application example of the Tools4MSP GeoNode plugin and an example of Tools4MSP stand-alone library for CEA in the Adriatic Sea. The Tools4MSP and the developed software have been released as FOSS under the GPL 3 license and are currently under further development.

Two Factor Authentication for Secured Login Using Array Password Engender by Petri net

Abstract In the most recent decades, the amount of web-based users has increased dramatically. However information and network security is a challenging issue for web users and service providers. Different authentication methods have been proposed to secure their data and networks from unauthorized access and for security. The Password cracking has created serious heated discussion and fear in providing security of the information. Exceedingly secured Password generation is consequently has become an exigent task. In this Paper Petri net based 3 × 3 Array Password generations has been proposed. As two factor confirmations it can be executed for web logins. The methodology adopted in this paper is novel and more immune. This paper exemplifies a new proposal of executing the authentications for effectual information Preservation and Network Security.

Effects of System Characteristics on Adopting Web-Based Advanced Traveller Information System: Evidence from Taiwan

This study proposes a behavioural intention model that integrates information quality, response time, and system accessibility into the original technology acceptance model (TAM) to investigate whether system characteristics affect the adoption of Web-based advanced traveller information systems (ATIS). This study empirically tests the proposed model using data collected from an online survey of Web-based advanced traveller information system users. Con­firmatory factor analysis (CFA) was performed to examine the reliability and validity of the measurement model, and structural equation modelling (SEM) was used to evaluate the structural model. The results indicate that three system characteristics had indirect effects on the intention to use through perceived usefulness, perceived ease of use, and attitude toward using. Information quality was the most im­portant system characteristic factor, followed by response time and system accessibility. This study presents implica­tions for practitioners and researchers, and suggests direc­tions for future research.

Staging Dementia From Symptom Profiles on a Care Partner Website

BackgroundThe World Wide Web allows access to patient/care partner perspectives on the lived experience of dementia. We were interested in how symptoms that care partners target for tracking relate to dementia stage, and whether dementia could be staged using only these online profiles of targeted symptoms.ObjectivesTo use clinical data where the dementia stage is known to develop a model that classifies an individual’s stage of dementia based on their symptom profile and to apply this model to classify dementia stages for subjects from a Web-based dataset.MethodsAn Artificial Neural Network (ANN) was used to identify the relationships between the dementia stages and individualized profiles of people with dementia obtained from the 60-item SymptomGuide (SG). The clinic-based training dataset (n=320), with known dementia stages, was used to create an ANN model for classifying stages in Web-based users (n=1930).ResultsThe ANN model was trained in 66% of the 320 Memory Clinic patients, with the remaining 34% used to test its accuracy in classification. Training and testing staging distributions were not significantly different. In the 1930 Web-based profiles, 309 people (16%) were classified as having mild cognitive impairment, 36% as mild dementia, 29% as moderate, and 19% as severe. In both the clinical and Web-based symptom profiles, most symptoms became more common as the stage of dementia worsened (eg, mean 5.6 SD 5.9 symptoms in the MCI group versus 11.9 SD 11.3 in the severe). Overall, Web profiles recorded more symptoms (mean 7.1 SD 8.0) than did clinic ones (mean 5.5 SD 1.8). Even so, symptom profiles were relatively similar between the Web-based and clinical datasets.ConclusionSymptoms targeted for online tracking by care partners of people with dementia can be used to stage dementia. Even so, caution is needed to assure the validity of data collected online as the current staging algorithm should be seen as an initial step.