Web Page Access Research Articles

Effectiveness of Ant Colony Optimization for Weighted Page Rank Algorithm in Web Access

In general the web is growing very rapidly and data generation is also vast and high. Search Engines play an eminent role in retrieving data from web. The user searching for a topic in a web and it retrieves more than hundreds of searchresults as websites. Among the all websites it is difficult for the user to access all the web pages to find relevant information. Weighted Page rank algorithms play a dominant role to make navigation easier to the user. The popularity of a web page depends on the number of its in links and out links and each webpage gets a proportional page rank value. This algorithm considers only link structure not thecontent of the page, so it returns lesssignificant pages to the user query. To overcome the above issues the study focuses on Ant Colony optimization. This study proposes application of ant colony algorithm for modified weighted page rank algorithm. The ACO concept will discovery of redundant components, use clustering based on the structure similarity or web behavior for user and similar WebPages matching. User and webpage similarity matching using Ant colony Optimization based clustering will leads to better access of the webpage in less time and required webpage.

Guidelines and deployment of accessibility-aware framework approach

PurposeThe purpose of this research is to facilitate the full potential of the web for the people with disabilities. People with disabilities may fail to make full use of the potentials offered by the web even if they have the right hardware (computer and assistive technologies) as well as access to the internet because of the lack of accessibility.Design/methodology/approachThis research outlines the guidelines that provide the foundation for building an accessibility-aware framework approach, where people with disabilities can access most of the electronic contents based on their disability levels.FindingsThe framework helps web engineers in developing accessible web pages for all types of users. Disability profile examples (blindness, low vision, deafness and hard of hearing) were taken to determine the performance of the framework approach.Research limitations/implicationsThe validation and testing was carried out on the Sultan Qaboos University website. The framework approach could be further validated by performing the tests on various other public and private websites.Practical implicationsThe guidelines can be used as a road map to overcome accessibility challenges during any web application development life cycle. A proper testing and evaluation is carried out on the framework to test its usability.Social implicationsAlthough people with disabilities are perhaps the segment of society which are expected to gain the most from these technologies, they are facing barriers to access the contents of the web because of the way it is presented. This proposed framework could assist all the people with the disability of blindness and hearing impairment to have a better experience with the internet, making the technology more beneficial and usable to them. In the future, this approach can be extended for the people with other disabilities.Originality/valueThis research provides a pioneering concept for accessibility-aware framework approach. This approach could be utilized for developing accessible web applications and electronic services for people with disabilities. The proposed framework can be used as a road map to overcome accessibility challenges during any web application development life cycle.

Wireless Smart Sensor Network System Using SmartBridge Sensor Nodes for Structural Health Monitoring of Existing Concrete Bridges

There are over 8000 bridges in the Philippines today according to the Department of Public Works and Highways (DPWH). Currently, visual inspection is the most common practice in monitoring the structural integrity of bridges. However, visual inspections have proven to be insufficient in determining the actual health or condition of a bridge. Structural Health Monitoring (SHM) aims to give, in real-time, a diagnosis of the actual condition of the bridge. In this study, SmartBridge Sensor Nodes were installed on an existing concrete bridge with American Association of State Highway and Transportation Officials (AASHTO) Type IV Girders to gather vibration of the elements of the bridge. Also, standards on the effective installation of SmartBridge Sensor Nodes, such as location and orientation was determined. Acceleration readings from the sensor were then uploaded to a server, wherein they are monitored against certain thresholds, from which, the health of the bridge will be derived. Final output will be a portal or webpage wherein the information, health, and acceleration readings of the bridge will be available for viewing. With levels of access set for different types of users, the main users will have access to download data and reports. Data transmission and webpage access are available online, making the SHM system wireless.

The Relationship Between Web Content and Web Accessibility at Universities

This research assesses whether universities from varied cultures rank significantly different with respect to the quality of their web contents and with regard to their web accessibility (WA) level. Moreover, this article tests whether universities, which make stronger efforts to improve the quality of their web contents, also take into account WA issues to ease the access to such contents. We use a database containing 399 universities from 16 countries. Main results suggest that universities in Anglo-Saxon countries pay more attention to WA issues and that those in Germanic countries rank significantly higher with regard to web quality contents. On a global basis, there is a significant relationship between the level of accessibility at university webpages and the quality of the web contents. However, if countries are grouped, results are different. While in Germanic, Nordic, and Anglo-Saxon countries, there is no relation between the level of accessibility of university webpages and the quality of the web contents, in Latin countries, this relation is direct and significant.

Screenshot-based color compatibility assessment and transfer for Web pages

Colors play particularly important roles in both designing and accessing Web pages. A well-designed color scheme improves the visual aesthetic of Web pages and facilitates user interactions. As far as we know, existing studies on color compatibility assessment and enhancement focus on images, and the assessment and enhancement for Web colors are rare. In order to aid Web designers evaluate and choose colors, this paper investigates color compatibility assessment for Web pages and applies this assessment to Web color editing based on Web screenshots rather than source codes. This study consists of four parts. First, the roles of color design in Web pages are discussed and a screenshot-based approach is proposed for the analysis of Web page regions. Second, a new method for extracting the color theme of a Web page is proposed. Then, we construct an assessment model that attributes scores to the color compatibility of Web pages through transfer learning. Third, we examine Web color transfer and combine it with the learned compatibility assessment model to create a new application that recommends colors for Web design. Lastly, the evaluation results suggest that the constructed compatibility assessment model and the proposed color transfer technique are effective and are superior over conventional methods. User studies suggest that our color recommendation application can generate new Web page screenshots that have higher color compatibility scores in comparison with those of the original pages.

Quality of information addressing treatment options for women with breast cancer on NCI cancer center websites.

135 Background: The internet is increasingly utilized by cancer patients for information that may influence treatment decisions. National Cancer Institute (NCI)-designated cancer center websites and nationally recognized cancer research agencies are trusted sources of information, however little data exists regarding the quality of information on these sites. We evaluated the quality and accessibility of breast cancer treatment information on cancer center websites addressing therapeutic options. Methods: Websites of all NCI cancer centers, the NCI, and Susan G. Komen were reviewed. Quality was measured using 33 questions from three validated Breast Cancer Decision Quality Instruments (DQI). Two blinded reviewers determined if websites provided information to answer each question. Number of clicks to reach the breast-specific webpage, evaluation time, and Spanish and mobile accessibility were recorded. Kappa coefficient was used to measure inter-observer variability. Correlation between evaluation time and questions answered was measured using Pearson coefficient. Results: Of the 63 cancer center websites evaluated, 94% had breast cancer webpages reached in a median of 2 clicks. Average evaluation time was 11 minutes. 24% were Spanish accessible. 59% were mobile friendly. No site provided information that addressed all questions. The most informative cancer center site addressed 76% of questions. On average, 21% of questions were addressed per site. 16% of sites did not have sufficient information to answer any question. In comparison, the NCI and Komen sites covered higher proportions of questions than cancer center sites (85 and 88%). Inter-observer variability was fair to moderate (avg. Kappa 0.37). Evaluation time strongly correlated with number of questions answered (r = 0.75). Conclusions: NCI cancer center websites provided informative feedback for breast cancer patients across an average 21% of key knowledge points in a validated DQI. This information is less accessible to Spanish speaking patients and patients using mobile devices. Website improvements represent an opportunity to enhance knowledge that may improve shared decision making for women with breast cancer.

An Approach To Webpage Prediction Method Using Variable Order Markov Model In Recommendation Systems

With the continuous increase of web applications and services, web usage data have been overloaded and handling that dynamic web information is very challenging task. Personalized web recommender systems are evolving to provide better and tailored experiences for online users than ever before. The personalization technique is carried out for the each individual user by considering their interests and search behavior stored in the web server access logs. Recently a variety of recommendation systems to predict user future request has been proposed, but the quality of these system results only low prediction accuracy. Hence this paper presents a new framework for effective recommendation system to reduce the searching time of the user and to reach the user’s future intention (request) webpage with the improved prediction accuracy by integrating fuzzy cmeans clustering and variable order markov model recommendation system. Experimental setups are carried out initially by applying preprocessing technique on the web log followed by fuzzy c-means clustering process to identify the similarity patterns. Finally web page recommendation is performed using variable order markov model to predict the user’s next web page access by reducing the search time and better prediction accuracy.

Isolating malicious content scripts of browser extensions

In recent years, browser extensions gain great popularity among users, as they significantly enhance functionality and improve the usability of web browsers. Browser extensions can have high privileges to access web page content, thus recent browsers, such as Chrome, controls their capabilities with permissions. However, permission control is not effective to control the behaviours of content scripts injected into web sessions. Once injected into victim web sessions, malicious content scripts can perform all sorts of actions in a web application without user's knowledge. Therefore, content scripts pose serious threats to the confidentiality and integrity of web application data. To address this problem, we propose a mechanism, SessionGuard, which isolates content scripts in an isolated environment, called the shadow DOM. With the shadow DOM, SessionGuard provides content scripts an encrypted view of web application data, and controls their access to the original DOM. We have developed a proof-of-concept prototype in the Google Chrome web browser with little effect on normal browsing experience. Our experiments with real-world browser extensions demonstrate the effectiveness of the SessionGuard in protecting the confidentiality and integrity of web application data against malicious content scripts.

UNIVERSITY WEBSITE ACCESSIBILITY FOR TOTALLY BLIND USERS

Researchers have discovered significant faults in the accessibility of university websites, especially for visually-impaired users. To determine the requirements for totally blind users, this study conducted a comprehensive literature review and accessibility evaluation on 15 Palestinian university websites. The determined factors were used in designing an accessible web page prototype. An online questionnaire was constructed to evaluate the accessibility of the prototype from the blind users’ perspective. From the evaluation of 16 blind participants, it was found that the prototype was highly accessible (mean score 4.19). The regression analysis test was utilised to determine the relationship between the items and the main principles of accessibility. The results show that there are statistically significant differences between these items. In conclusion, the accessibility factors have been indirectly validated.

Consumer attitude towards website advertising formats: a comparative study of banner, pop-up and in-line display advertisements

The purpose of this study is to compare dimensions of consumer attitude towards different formats of web display advertising. Since internet advertising is a rapidly growing industry in transitional economies like Vietnam, there is an emerging call for further study about the effectiveness of advertising on news portal websites, which are usually top accessed web pages. Data were gathered from an online survey of 200 respondents to compare attitudinal forms towards traditional banner ads, in-line ads and pop-up ads. The research applies the attitudinal dimensions of information, irritation and entertainment. Findings indicate a somewhat positive attitude towards traditional banner ads with high informative value and negative attitude towards pop-up ads with irritating attitude. Besides, entertainment is not evaluated as a significant attitudinal form of web advertising.

NEOSURVEY 1: INITIAL RESULTS FROM THE WARM SPITZER EXPLORATION SCIENCE SURVEY OF NEAR-EARTH OBJECT PROPERTIES

ABSTRACT Near-Earth objects (NEOs) are small solar system bodies whose orbits bring them close to the Earth’s orbit. We are carrying out a Warm Spitzer Cycle 11 Exploration Science program entitled NEOSurvey—a fast and efficient flux-limited survey of 597 known NEOs in which we derive a diameter and albedo for each target. The vast majority of our targets are too faint to be observed by NEOWISE, though a small sample has been or will be observed by both observatories, which allows for a cross-check of our mutual results. Our primary goal is to create a large and uniform catalog of NEO properties. We present here the first results from this new program: fluxes and derived diameters and albedos for 80 NEOs, together with a description of the overall program and approach, including several updates to our thermal model. The largest source of error in our diameter and albedo solutions, which derive from our single-band thermal emission measurements, is uncertainty in η, the beaming parameter used in our thermal modeling; for albedos, improvements in solar system absolute magnitudes would also help significantly. All data and derived diameters and albedos from this entire program are being posted on a publicly accessible Web page at nearearthobjects.nau.edu.

A Daily Life Visualization by Representative Web Page Selection and Magazine-Style Layout

Web browsing history is a fruitful life log representing behavior and knowledge of users. Visualization of summarized browsing history can contribute to represent these information. This paper proposes a system to extract representative Web pages from browsing history of users, and arranges them like a newspaper, called HistoryPaper. This system firstly clusters browsed Web pages based on their contents. Then, it calculates priority of Web pages from search terms and rarity of accessed Web pages, and selects the representative page of each cluster. HistoryPaper arranges the representative pages by a layout algorithm following the magazine style applied in many news sites.

A Novel Approach for Web Personalization

present word web is huge storage of information and it will keep increasing with growing of internet technologies. But the human being capability to read, access and understand content does not increase with that tread. Hence it becomes complex to website owners to present proper information to the users. This led to provide personalized web services to users. One of the well-known approaches in providing web personalization is Web Usage Mining. In this paper, our motive of web usage mining is to discover users' access patterns of web pages automatically and quickly from the huge sever access log records, such as frequently visited hyperlinks, frequently accessed web pages and users grouping. Also, we proposed a new method for discovering users' access patterns and recommend it to the user.

Global access to sonar data: Where can it take you?

Scientific echosounders aboard NOAA fishery survey vessels are used to estimate biomass, measure fish school morphology, and characterize habitat. These surveys produce large volumes of data that are stored locally and difficult to access. Data that are easily discoverable and accessible provide valuable information beyond their original collection purpose. NOAA’s National Centers for Environmental Information, in partnership with the National Marine Fisheries Service and the University of Colorado, created a national archive for the stewardship and distribution of water column sonar data. A data access web page allows users to query the metadata and access the raw sonar data. Visualization products allow researchers and the public to understand the quality and content of large volumes of archived data. Such products transform the complex raw data into a digestible image and are highly valuable for a broad audience of varying backgrounds. Concurrently collected oceanographic and bathymetric data are being integrated into the data access page to provide an ecosystem-wide understanding of the area surveyed. Benefits of the archive include global access to an unprecedented nationwide dataset and the increased potential for researchers to address new questions to advance the field of marine ecosystem acoustics.

Enhancing web accessibility by implementing context aware proxy

Purpose Millions of visually impaired people (VIP) in the world still face difficulties browsing the Web and accessing information. This paper aims to present a proxy service that takes advantage of the concept of context-aware to help contextualizing web pages for visually impaired users. Design/methodology/approach The VIP-aware proxy combines five components to utilize the user preferences, adapts the requested web page and reorganizes its content to best match the preferences set by the user. This new scenario will assist VIP in browsing the Web more effectively. Findings A preliminary evaluation of the system resulted in general user satisfaction. Practical implications The VIP-aware proxy will provide users with a clean, accessible web page, save them time when screen readers examine content related to their preferences and save them money when unnecessary content is not downloaded. Originality/value The VIP-aware proxy presented in this paper is the first of its kind targeting VIP.

To Enhance Frequent Closed Pattern Tree using Fuzzy Clustering of Personalized Web-Log in Big Data

In recent time data mining on big data is very tedious task in current scenario because huge data cannot be handling in the memory with different format type of data. In distributed environment web pages access by the user having some patterns, these patterns are merging and finding closed frequent set of web pages. Now do the Fuzzy C-Means clustering of web page access pattern tree. If user need next request page in advance then it search only partial web data not in whole web data. So that this research utilized a personalized weighted recommendation system based on user's interest with less execution time.

Using social media for community consultation and public disclosure in exception from informed consent trials.

The US Food and Drug Administration and the Department of Health and Human Services outline regulations allowing an exception from informed consent (EFIC) for research conducted in an emergency setting. Acute care clinical trials using EFIC must include community consultation and public disclosure (CC/PD) activities. We describe our experience using social media to facilitate the CC/PD process in two trauma resuscitation clinical trials. We conducted local CC/PD activities for two multicenter trauma clinical trials, Pragmatic, Randomized Optimal Platelet and Plasma Ratios (PROPPR) and Prehospital Tranexamic Acid Use for Traumatic Brain Injury (ROC-TXA). As part of the CC/PD process, we developed research study advertisements using the social media Web site Facebook. The Facebook advertisements directed users to a regional study Web site that contained trial information. We targeted the advertisements to specific demographic users, in specific geographic areas. We analyzed the data using descriptive statistics. During the study periods, the PROPPR Facebook advertisement was displayed 5,001,520 times (12 displays per target population) with 374 individuals selecting the advertisement. The ROC-TXA Facebook advertisement was displayed 3,806,448 times (8 per target population) with 790 individuals selecting the advertisement. Respondents to both Facebook advertisements were mostly male (52.6%), with the highest proportion between the ages 15 years and 24 years (28.2%). Collectively, 26.9% of individuals that clicked on the Facebook advertisement spent more than 3 minutes on the study Web site (3-49 minutes). Commonly accessed Web pages were "contact us" (PROPPR, 5.5%; ROC-TXA, 7.7%), "study-specific FAQs" (PROPPR, 2.4%; ROC-TXA, 6.7%), and "opt out of research" (PROPPR, 2.5%; ROC-TXA, 3.8%). Of 51 total individuals viewing the opt out of research information (PROPPR, 19; ROC-TXA, 32), time spent on that specific page was modest (PROPPR, 62 seconds; ROC-TXA, 55 seconds), with no individuals requesting to opt out of either study participation. In clinical trauma trials using EFIC, social media may provide a viable option for facilitating the CC/PD process.

Prediction of User Behavior using Web log in Web Usage Mining

usage mining is application of data mining. Web Usage Mining is the automatic discovery of user access pattern from web servers. Web usage mining is consists of preprocessing, pattern discovery, pattern analysis. Web prediction is a classification problem which attempts to predict the most likely web pages that a user may visit depending on the information of the previously visited web pages. In this paper emphasizes is given on the user Behaviour using web log file prediction using web log record, click streams record and user information. Here, two different clustering techniques, namely Fuzzy C-Means Clustering algorithms and Markov model has been investigated to predict the webpage that will be accessed in the future based on the previous action of browsers behavior. But prediction of future request of the user mainly concern with its accuracy and efficiency. The discovered patterns can be used for better web page access prediction.Prediction model are better prediction of next web page the user want to visit. Using web page access prediction, the right advertisement will be placed in the website according to the users' browsing patterns.In Web page prediction, the next action corresponds to predicting the next page to be visited. The previous actions correspond to the previous pages that have already been visited.

Novel Hybrid k-D-Apriori Algorithm for Web Usage Mining

The Web usage mining is a branch of web mining in which by clustering the datasets, frequently accessed patterns can be obtained for betterment of social portals, websites. The divisive analysis is one of the types of hierarchical method of data clustering that is used to separate each dataset from the clustered data depending on previous small clusters. Apriori & k-Apriori are commonly used hierarchical algorithms for web usage mining but they are less efficient for mining dynamic item sets such as twitter dataset. Recently D-Apriori algorithm has been proposed in the literature for mining dynamic dataset to find the frequently accessed web pages from web log database. The disadvantage of D-Apriori is that, it takes more execution time compared to k-Apriori. This research work proposes a new hybrid k-D-Apriori algorithm that reduces the execution time, improves frequent pattern generation, works efficiently with dynamic datasets and gives improved association rule generation as compared to D-Apriori algorithm.

Web navigation prediction using Markov-based models: an experimental study

Navigation prediction on web has gained a lot of importance due to its rapid growth. Web navigation prediction WNP deals with discovering the future pages for a particular website that users/the user may visit based on previously accessed web pages. WNP can be applied effectively in many applications such as web related search, latency reduction, improving website design, location prediction and personalised systems. Markov models and its variations are widely used to represent and analyse the navigational data on web. It can also used to predict user navigation behaviour. Diverse Markov model varies in terms of state-space complexity, prediction accuracy, model accuracy, coverage and failure cases. Research is still in progress for determining the suitability of Markov models for various web applications. Therefore, this paper presents a comparison of existing Markov-based models and its merit lies in the non-trivial conclusions derived by the experiments. Comparison is done in terms of state-space complexity, failure cases, coverage, prediction accuracy and model accuracy.