Adaptive Web Research Articles

Neuroimaging, Genetics, and Clinical Data Sharing in Python Using the CubicWeb Framework.

In neurosciences or psychiatry, the emergence of large multi-center population imaging studies raises numerous technological challenges. From distributed data collection, across different institutions and countries, to final data publication service, one must handle the massive, heterogeneous, and complex data from genetics, imaging, demographics, or clinical scores. These data must be both efficiently obtained and downloadable. We present a Python solution, based on the CubicWeb open-source semantic framework, aimed at building population imaging study repositories. In addition, we focus on the tools developed around this framework to overcome the challenges associated with data sharing and collaborative requirements. We describe a set of three highly adaptive web services that transform the CubicWeb framework into a (1) multi-center upload platform, (2) collaborative quality assessment platform, and (3) publication platform endowed with massive-download capabilities. Two major European projects, IMAGEN and EU-AIMS, are currently supported by the described framework. We also present a Python package that enables end users to remotely query neuroimaging, genetics, and clinical data from scripts.

Estrategias de diseño web para dispositivos móviles

Este artículo presenta una revisión de la literatura referente al diseño web, específicamente a diseño web para dispositivos móviles. El objetivo de la revisión es identificar y analizar las principales estrategias y metodologías para el diseño en dispositivos con pantallas de tamaño pequeño. Tres estrategias aparecen consistentemente en la literatura revisada, a saber: Diseño responsivo, diseño adaptativo, y sitio móvil independiente. El análisis de estas estrategias pretende proveer un claro entendimiento de sus ventajas y desventajas, en términos de costos y experiencia de usuario.

An Adaptive Educational Web Application for Engineering Students

Motivated by the success of student-centered language-learning tools and data-driven platforms commonly found in popular commercial and entertainment platforms, we present a new adaptive educational web platform for engineering students. The presented adaptive education platform ( ADEPT ) focuses on personalizing learning in large college classes by enabling proactive and continuous student engagement. In this paper, we present the principles, implementation strategies, and initial results obtained by working with an early version of ADEPT in a required sophomore-level circuits course at Purdue University. Initial results underline the potential of this web tool to identify the challenging concepts for students as well as prepare instructors to modify the way concepts are presented to the students. In addition, ADEPT helps to reveal the student engagement habits and studying patterns that may not be easily identifiable through other means, such as self-reporting.

Adaptive streaming of complex Web 3D scenes based on the MPEG-DASH standard

Modern Web 3D technologies allow us to display complex interactive 3D content, including models, textures, sounds and animations, using any HTML-enabled web browser. Thus, due to the device-independent nature of HTML5, the same content might have to be displayed on a wide range of different devices and environments. This means that the display of Web 3D content is faced with the same Quality of Experience (QoE) issues as other multimedia types, concerning bandwidth, computational capabilities of the end device, and content quality. In this paper, we present a framework for adaptive streaming of interactive Web 3D scenes to web clients using the MPEG-DASH standard. We offer an analysis of how the standard’s Media Presentation Description schema can be used to describe adaptive Web 3D scenes for streaming, and explore the types of metrics that can be used to maximize the user’s QoE. Then, we present a prototype client we have developed, and demonstrate how the 3D streaming process can take place over such a client. Finally, we discuss how the client framework can be used to design adaptive streaming policies that correspond to real-world scenarios.

A Testing Framework of Adaptive Web Application Based on Multi-agent Collaboration

With the increase of the Web applications, efficient and reliable test has become a practical necessary to improve the reliability of Web applications. Due to the dynamic and uncertain characteristics of Web applications, traditional testing methods are hard to make good performance. Agent could be adapted in the distributed environment which are intelligent and initiative. An adaptive Web application testing framework based on Multi-Agent collaboration theory (ATFBMA) is proposed in this paper. ATFBMA satisfies the dynamics and uncertainties of the adaptive Web application testing. Meanwhile, layered and role-divided Multi-Agent architecture is constructed. Agents are divided into different roles depending on the responsibilities and capabilities. The architecture supports the test requirements of function and structure, and improves test efficiency through the division and distribution of test tasks. A user management system is used to verify the practicality and intelligence of ATFBMAC.

Faunal acquisition, maintenance, and consumption: how the Teotihuacanos got their meat

The compilation of the last 40 years of zooarchaeological exploration at Teotihuacan, Mexico, provides a unique opportunity to create more nuanced models of New World vertebrate consumption that did not focus on domesticated animals (dog and turkey). Any single model of ancient food systems fails to represent how varied ecological and social contexts led to a complex web of adaptations, and here, it is argued that Teotihuacan’s arid, highland, and urban environment contributed to a distinct faunal acquisition strategy. Intra-site variation and diverse degrees of animal procurement and management were practiced throughout the site. For example, the low proportion of deer compared to the abundant evidence of rabbit/hare consumption suggests small-scale animal management and breeding programs in the residential complexes supplemented with opportunistic garden hunting and meat purchased through a market economy. Such foodstuffs would have been both more predictable and readily made available to organize large feasting events, a possibility that is strengthened by evidence of extraordinarily high abundances of rabbits in ceremonial contexts.

OPCOMITS: Developing an adaptive and intelligent web based educational system based on concept map model

ABSTRACTConcept map model is a method that creates domain model by identifying the relationship between concepts in course contents. This study presents an adaptive intelligent web based learning system called OPCOMITS (Object Oriented Programming Tutor using Concept Map Model). OPCOMITS has a free domain model which can be regulated by an expert for any course. It uses concept map model to regulate the topic hierarchy, to measure the student's knowledge about a topic and to stimulate learning. By employing a concept map model, it structures the course and provides an environment in which the lecturer can arrange the chapters, topics, concepts and the prerequisite relationships between the concepts. Thus, it offers an adaptive and effective learning environment by measuring the level of student's knowledge about a topic, offering reinforcing feedback, diagnosing students' weaknesses and directing them to related chapter topic in the domain for revisions. To evaluate the effectiveness of the proposed approach an experiment has been conducted on Computer Programming department in Object Oriented Programming course. From the experimental results, it is found that OPCOMITS has contributed to the academic success of students using it and students have exhibited much better learning than those who have used a conventional e‐learning system. © 2016 Wiley Periodicals, Inc. Comput Appl Eng Educ 24:676–691, 2016; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.21740

A Review on Adaptive Web Caching Technique

A Review on Adaptive Web Caching Technique

Spatially-balanced adaptive web sampling

The paper deals with sampling from a finite population that is distributed over space and has a highly uneven spatial distribution. It suggests a sampling design that allocates a portion of the sample units that are well spread over the population and sequentially selects the remaining units in sub-areas that appear to be of more interest according to the study variable values observed during the survey. In order to estimate the population mean while using this sampling design, a computationally intense estimator, obtained via the Rao–Blackwell approach, is proposed and a resampling method is used that makes the inference computationally feasible. The whole sampling strategy is evaluated through several Monte Carlo experiments.

Methodologies for Model-Driven Development of Adaptive Web Applications: An Analytical Survey

Due to the rapid expansion of web applications, the information and services provided on the web have proliferated, leading to ever-increasing complexity. This has not only resulted in the utmost significance of information quality and accuracy on the web, but has also necessitated that access to information be improved. Hence, adaptive web systems have emerged, which focus on adapting web content, presentation, and navigation to meet the needs of the users according to their individual circumstances and preferences. In this field, focus has gradually shifted from creation of new adaptive techniques to solving the problems of analysis and design of adaptive applications; in other words, it has become important to handle the dynamism of the runtime environment and the complexity involved in developing these applications. Model-Driven Engineering (MDE) is considered a promising approach for overcoming these problems, mainly due to its modeling features: Models are created at different levels of abstraction (thus enhancing complexity management), and the process can potentially be automated through the use of transformation rules. We provide a review of several prominent methodologies that utilize MDE for developing adaptive web applications, and propose a criteria-based evaluation approach that highlights their strengths and weaknesses. Evaluation results can be used for comparing and selecting methodologies for use in web development projects; they can also be used for constructing a new methodology that exploits the strengths and addresses the shortcomings of existing methodologies.

An Efficient Agglomerative Clustering Algorithm for Web Navigation Pattern Identification

Web log mining is analysis of web log files with web page sequences. Discovering user access patterns from web access are necessary for building adaptive web servers, to improve e-commerce, to carry out cross-marketing, for web personalization, to predict web access sequence etc. In this paper, a new agglomerative clustering technique is proposed to identify users with similar interest, and to determine the motivation for visiting a website. Using this approach, web usage mining is done through different stages namely data cleaning, preprocessing, pattern discovery and pattern analysis. Results are given to explain how this approach produces tight usage clusters than the existing web usage mining techniques. Rather than traditional distance based clustering, the similarity measure is considered during clustering process in order to reduce computational complexity. This paper also deals with the problem of assessing the quality of user session clusters and cluster validity is measured by using statistical test, which measures the distances of clusters distributions to infer their dissimilarity and distinguish level. Using such statistical measures, it is proved that cluster accuracy is improved to the extent of 0.83, over existing k-means clustering with validity measure 0.26, FCM (Fuzzy C Means) clustering with validity measure 0.56. Rough set based clustering with validity measure 0.54 Generation of dense clusters is essential for finding interesting patterns needed for further mining and analysis.

On fairness and application performance of active queue management in broadband cable networks

We evaluate the performance of modern delay-based active queue management (AQM) algorithms in downstream DOCSIS 3.0 cable environments. Our simulation-based study involves scenarios that include tiered service levels and application workloads that include FTP, HTTP-based adaptive streaming (HAS), VoIP, and web traffic.Our results show that AQM maintains target queuing delays and consequently provides strong isolation between responsive high bandwidth and low bandwidth latency sensitive flows. We also show that lowering target queuing delays exacerbates TCP’s RTT unfairness. Nevertheless, in the scenarios that we studied, observed application performance was not significantly impacted by the specific AQM in use.With the potential large deployment of AQM imminent for DOCSIS 3.0, the analysis presented in this paper provides timely feedback to the community concerning how delay-based AQM can manage bandwidth allocation fairness and application performance in realistic downstream DOCSIS 3.0 cable network systems.

Methods and Techniques of Adaptive Web Accessibility for the Blind and Visually Impaired

Massive volumes of information shared on the web together with linked open data initiatives and exabytes of data generated through social networks frequently disorientates and confuses web users in their everyday interaction. Additionally, web users constitute a highly heterogeneous entities with different needs and requirements. Considering this, user adaptive software systems have been developed as a new application approach to ease the interaction between users and web information with the intent to bridge the gap between such presentation and navigational pitfalls. The user adaptive interaction is especially useful when considering a marginalized group such as blind and visually impaired users. This paper attempts at providing an overview of a state-of-the-art survey concerning adaptive interaction between users and web information space with special emphasis on exploiting methods and techniques for adaptive web accessibility for blind and visually impaired people. Likewise, the exploration of possibilities of new methods and techniques for user adapted interaction for blind and visually impaired is highly required in order to alleviate the accessibility according to Web Content Accessibility Guidelines (WCAG). Recent studies indicate that even when the guidelines are implemented on web information systems, there is little indication that people with disabilities will gain better accessibility. To address these issues, we introduce various visual and auditory approaches to extend such adaptive methods and techniques for blind and visually impaired.

Audio Scenarios Detection Technique

proposed research objective is to add to a framework for programmed recognition of sound. In this framework the real errand is to distinguish any information sound stream investigate it & anticipate the likelihood of diverse sounds show up in it. To create and industrially conveyed an adaptable sound web crawler a flexible sound search engine. The calculation is clamor and contortion safe, computationally productive, and hugely adaptable, equipped for rapidly recognizing a short portion of sound stream caught through a phone microphone in the presence of frontal area voices and other predominant commotion, and through voice codec pressure, out of a database of over accessible tracks. The algorithm utilizes a combinatorial hashed time-recurrence group of stars examination of the sound, yielding ordinary properties, for example, transparency, in which numerous tracks combined may each be distinguished.

A framework for understanding the website preferences of Egyptian online travel consumers

Purpose– The purpose of this paper is to develop a framework for understanding issues affecting Egyptian online travel website preferences.Design/methodology/approach– Grounded theory was selected due to its suitability in generating frameworks from data gathered plus existing theory.Findings– The research describes the development of the electronic cultural adaptation framework (E-CAF), which consists of six theoretical dimensions that allow both researchers and practitioners to comprehend how Egyptian cultural values can affect their online travel shopping behaviour, in particular website design preferences.Research limitations/implications– The construction of the E-CAF is based on research into Egyptian online travel consumers. Development of the E-CAF could be expanded using participants from different cultural groups and other shopping domains.Practical implications– This research will help practitioners to understand how Egyptian cultural values can affect online behaviour and assist in developing strategies for local adaptations of online travel offerings. The framework will also provide web designers with guidelines for gathering and developing requirements from clients to implement culturally adaptive web interfaces for Egyptian consumers.Originality/value– While there are a number of existing cultural frameworks in existence, such as those of Hofstede, Hall, or Schwartz, these frameworks are not based on consumer behaviour, either online or offline, and are, therefore, not optimally suited for use in online marketing strategies or web design for Egyptian consumers. This research overcomes these limitations by providing a framework that recognises how cultural values can impact Egyptian consumer behaviour and provides a platform for further research, as well as online marketing strategies and tactics.

Novel Modified Fuzzy Possibilistic C Means (FPCM) for Web Log Mining by Removing Global Noise and Web Robots

Nowadays, internet is a useful source of information in everyone’s daily activity. Hence, this made a huge development of world wide web in its quantity of interchange and its size and difficulty of websites. Web Usage Mining WUM is one of the main applications of data mining, artificial intelligence and so on to the web data and forecast the user’s visiting behaviors and obtains their interests by investigating the samples. SinceWUM directly involves in large range of applications, such as, e-commerce, e-learning, Web analytics, information retrieval etc. Web log data is one of the major sources which contain all the information regarding the users visited links, browsing patterns, time spent on a particular page or link and this information can be used in several applications like adaptive web sites, modified services, customer summary, pre-fetching, generate attractive web sites etc. There are varieties of problems related with the existing web usage mining approaches. Existing web usage mining algorithms suffer from difficulty of practical applicability. So, a novel research is very much necessary for the accurate prediction of future performance of web users with rapid execution time. The main aim of this paper to remove the noise and web robots by novel approach and provide faster and easier data processing and it also helps in saving time and it resource. In this paper, a novel pre-processing technique is proposed by removing local and global noise and web robots. Anonymous Microsoft Web Dataset and MSNBC.com Anonymous Web Dataset are used for evaluating the proposed preprocessing technique. An Effective Web User Analysis and Clustering are analyzed using Modified Fuzzy Possibilistic C Means (FPCM). Then results are evaluated using Hit Rate and Execution time.

Visualize and Semantic Structure in Web Navigate Communication

 Abstract—When facing the overabundant of semantic web information, in this paper, the researcher proposes the hierarchical classification and visualizing RIA (Rich Internet Application) navigation system: Concept Map (CM) + Semantic Structure (SS) + the Knowledge on Demand (KOD) service. The aim of the Multimedia processing and empirical applications testing, was to investigating the utility and usability of this visualizing navigation strategy in web communication design, into whether it enables the user to retrieve and construct their personal knowledge or not. Furthermore, based on the segment markets theory in the Marketing model , to propose a User Interface (UI) This research is based on the Information Architecture design in Human Computer Interface (HCI) theory; and the Interactive; Sensorial design in User Interface (UI) theory, to explore the utility and usability of the CM + SS + KOD navigation system in the adaptive Web learning environment. Moreover, in the adoption of Knowledge Space Theory, Dietrich Albert (1997) (1) and Michael D. (2010) (2) points out: the knowledge space provides a formal model for representing students' knowledge and describing the structure of domain knowledge. In this researcher's opinion, the Concept Map (CM); Semantic Structure (SS) and Knowledge on Demand (KOD) navigation system, integrated the multimedia metadata with a self-navigating format. This adaptive navigation method not only enhances the information communication process, but also fosters the user's cognition construction.

Home Automation with a low-cost AVR-based Board

Smart Home technology is greatly on the rise. Many manufacturers offer central control units and various actuators and sensors that make it possible to control home appliances remotely via the Internet or smartphones. Unfortunately, such producers mainly use proprietary communication protocols by which the user is bounded to a specific company and therefore the price increases. In general, accessories from different manufacturers cannot be mixed. In this contribution, a solution is presented in which a commercially available €20 evaluation board with the processor ATMega32 serves as the main controller. The provided firmware has been replaced by a web server communicating with the client via REST interface. Two client versions were created: An adaptive web client that makes it possible to determine the actual response using JavaScript and a specific web client for controlling a gas boiler.

Model-driven development of adaptive web service processes with aspects and rules

Modern software systems are frequently required to be adaptive in order to cope with constant changes. Unfortunately, service-oriented systems built with WS-BPEL are still too rigid. In this paper, we propose a novel model-driven approach to supporting the development of dynamically adaptive WS-BPEL based systems. We model the system functionality with two distinct but highly correlated parts: a stable part called the base model describing the flow logic aspect and a volatile part called the variable model describing the decision logic aspect. We develop an aspect-oriented method to weave the base model and the variable model together so that runtime changes can be applied to the variable model without affecting the base model. A model-driven platform has been implemented to support the development of adaptive WS-BPEL processes. In-lab experiments show that our approach has low performance overhead. A real-life case study also validates the applicability of our approach.

A Comparative Study of Performance of Adaptive Web Sampling and General Inverse Adaptive Sampling in Estimating Olive Production in Iran

A Comparative Study of Performance of Adaptive Web Sampling and General Inverse Adaptive Sampling in Estimating Olive Production in Iran