Browsing Model Research Articles

A comparison between field measurements of vapour concentrations of plant protection products and predictions by the BROWSE model

A database of field measurements of air concentrations of pesticide active ingredients has previously been compiled by CropLife Europe with an aim to revise the default air concentration values and assumptions applied in assessing vapour exposure in the risk assessment of bystanders and residents. The BROWSE model, released in 2014, which is a regulatory risk assessment model that includes the exposure of residents and bystanders has a component relating to post-application vapour inhalation. Predictions of concentration deduced from exposures obtained using the BROWSE model were compared with field measurements of 24-h and 7-day average concentrations. The methodology for obtaining concentration estimates from the BROWSE model is described, and the criteria for including field studies in the comparison are given. The field data were adjusted to account for differences between the field experiment and the BROWSE scenario using factors derived from a separate plume dispersion model. This showed that BROWSE provides a satisfactory level of conservatism in determining potential exposures of residents and bystanders to vapour and could be a reliable alternative to replace the current EFSA approach for predicting vapour inhalation exposures for pesticides where no compound-specific data are available.

EavesDrop

Interactive Live streaming is the process of transferring real-time data over the internet. The data can be of type audio, video or any common data type. Interactive live streaming is an important feature of applications and platforms in which the actions of the audience affect the content of the communication. Simultaneously, Podcasting is one of the types of contents that people are attracted to. The idea of podcasting includes recording the audio or video file and uploading it to a platform where people can access it. Now, with the thought of mixing these two, the idea of an interactive podcast was born. We analyze that low delay is a restriction for Web Interactive Streaming. Interactive communication over the internet with the restrictions of real-time boundaries requires a framework that will allow the development of the proposed project. Real Time Communication (RTC) has wide-industry uses. RTC is the standard and it also increases the browsing model which allows access to live streaming systems which consist of social media, television, chatting applications, as well as the communication media. Users are allowed to read comments, write comments, record the sessions/audio/video, and edit audio/videowhich is done within a Cloud Infrastructure which also provides services of quality. The development of the application is the most important part where using different technologies a system can stream audio and video data over the internet, handle a number of users who can make audio rooms to discuss a topic among themselves, where several people can hear them, and they also have a chance to add value to the conversation with their inputs.

How Am I Doing?: Evaluating Conversational Search Systems Offline

As conversational agents like Siri and Alexa gain in popularity and use, conversation is becoming a more and more important mode of interaction for search. Conversational search shares some features with traditional search, but differs in some important respects: conversational search systems are less likely to return ranked lists of results (a SERP), more likely to involve iterated interactions, and more likely to feature longer, well-formed user queries in the form of natural language questions. Because of these differences, traditional methods for search evaluation (such as the Cranfield paradigm) do not translate easily to conversational search. In this work, we propose a framework for offline evaluation of conversational search, which includes a methodology for creating test collections with relevance judgments, an evaluation measure based on a user interaction model, and an approach to collecting user interaction data to train the model. The framework is based on the idea of “subtopics”, often used to model novelty and diversity in search and recommendation, and the user model is similar to the geometric browsing model introduced by RBP and used in ERR. As far as we know, this is the first work to combine these ideas into a comprehensive framework for offline evaluation of conversational search.

Product sequencing and pricing under cascade browse model

We study the assortment optimization problem under the newly proposed cascade browse model. We propose a constant approximate solution to this problem. As a byproduct, we propose the first fully polynomial-time approximation scheme (FPTAS) for the classic assortment optimization problem subject to one capacity constraint and one cardinality constraint. We also studied a joint pricing and sequencing problem under the above model and develop a constant approximate solution to this problem.

Direct dermal and inhalation exposure of bystanders and residents during vine foliar application using sprayer equipment fitted with an anti-drift device: a comparison between measured exposure levels and existing exposure models

Within the European Union (EU) regulatory framework, plant protection products (PPPs) must be evaluated according to Regulation (EC) No 1107/2009. Bystander/resident exposures can be assessed using the current EU harmonised predictive EFSA model; however, the number of experimental data included in this model is rather limited. In the experimental study conducted, direct dermal and inhalation exposures of bystanders/residents caused by the spray drift during vine foliar application using sprayer equipment fitted with an anti-drift device were quantified. The exposure levels measured during the experimental exposure study were compared to those calculated using the BROWSE model, the former German model, and the EFSA model. The measured direct dermal exposure levels of bystanders/residents were found to be lower than the exposure levels calculated with the BROWSE model using the 95th percentiles [experimental study/BROWSE model (%): 3.9% and 2.1%, respectively for adults and children], and using the 75th percentiles (16% and 7.8%, respectively for adults and children), the German model using the 95th percentiles [experimental study/German model (%): 4.0% and 12%, respectively for adults and children], and much lower than those calculated with the EFSA model using the 95th percentiles [experimental study/EFSA model (%): 0.27% and 0.40% for adults and children, respectively] and using the 75th percentiles (0.51% and 0.62%, respectively for adults and children). Exposure levels via the inhalation route represented less than 1.7% of dermal exposures. The results of this experimental exposure study could be used to refine the bystander/resident exposure estimates provided by the EFSA model.

Modeling Terminologies for Reusability in Faceted Systems.

We integrate heterogeneous terminologies into our category-theoretic model of faceted browsing and show that existing terminologies and vocabularies can be reused as facets in a cohesive, interactive system. Commonly found in online search engines and digital libraries, faceted browsing systems depend upon one or more taxonomies which outline the structure and content of the facets available for user interaction. Controlled vocabularies or terminologies are often curated externally and are available as a reusable resource across systems. We demonstrated previously that category theory can abstractly model faceted browsing in a way that supports the development of interfaces capable of reusing and integrating multiple models of faceted browsing. We extend this model by illustrating that terminologies can be reused and integrated as facets across systems with examples from the biomedical domain. Furthermore, we extend our discussion by exploring the requirements and consequences of reusing existing terminologies and demonstrate how categorical operations can create reusable groupings of facets.

Assessing human health risks from pesticide use in conventional and innovative cropping systems with the BROWSE model

BackgroundReducing the risks and impacts of pesticide use on human health and on the environment is one of the objectives of the European Commission Directive 2009/128/EC in the quest for a sustainable use of pesticides. This Directive, developed through European national plans such as Ecophyto plan in France, promotes the introduction of innovative cropping systems relying, for example, on integrated pest management. Risk assessment for human health of the overall pesticide use in these innovative systems is required before the introduction of those systems to avoid that an innovation becomes a new problem. ObjectivesThe objectives of this work were to assess and to compare (1) the human exposure to pesticides used in conventional and innovative cropping systems designed to reduce pesticide needs, and (2) the corresponding risks for human health. MethodsHumans (operator and residents) exposure to pesticides and risks for human health were assessed for each pesticide with the BROWSE model. Then, a method was proposed to represent the overall risk due to all pesticides used in one system. This study considers 3 conventional and 9 associated innovative cropping systems, and 116 plant protection products containing 89 different active substances (i.e. pesticides). ResultsThe modelling results obtained with BROWSE showed that innovative cropping systems such as low input or no herbicide systems would reduce the risk for human health in comparison to the corresponding conventional cropping systems. On the contrary, BROWSE showed that conservation tillage system would lead to unacceptable risks in the conditions of our study, because of a high number of pesticide applications, and especially of some herbicides. For residents, the dermal absorption was the main exposure route while ingestion was found to be negligible. For operators, inhalation was also a predominant route of exposure. In general, human exposure to pesticides and human health risks were found to be correlated to the treatment frequency index TFI (number of registered doses of pesticides used per hectare for one copping season), confirming the relationship between the reduction of pesticide use and the reduction of risks. ConclusionsAssessment with the BROWSE model helped to identify cropping systems with decreased risks from pesticides for human health and to propose some improvements to the cropping systems by identifying the pesticides that led to unacceptable risks.

Pay-per-tracking: A collaborative masking model for web browsing

Web tracking is the key enabling technology of modern online advertising and, at the same time, the source of serious privacy concerns. In recent years, we have witnessed the emergence of a variety of technologies whose main goal is to address these concerns. However, ad blockers and anti-trackers eliminate all forms of tracking and advertising and therefore fail to reconcile user privacy and the current Internet business model.In this paper, we propose a new tracking paradigm that aims at returning control to users over tracking and advertising, and allowing them to participate in the monetization of their browsing data. The proposed paradigm breaks with the current barter model of exchanging privacy for services and, at the same time, it may preserve the Internet economic model where content is paid from advertisement revenue. We have designed a system architecture that implements this model in practice, and optimizes the exchange of privacy for money. Our ultimate aim is to strike a better balance between user privacy and the economic model that sustains the Web, and thus overcome the deadlock caused by the ad blocking wars. Experimental results with real browsing data demonstrate the suitability and feasibility of our approach.

The BROWSE model for predicting exposures of residents and bystanders to agricultural use of pesticides: Comparison with experimental data and other exposure models

A new suite of models has been developed for assessing the exposure of bystanders, residents, operators and workers to pesticides used in agricultural applications. The aim of these ‘BROWSE’ models was to improve regulatory exposure assessment by including recent data, and changes in current knowledge and application practice. The new models for bystander and resident exposure focused on spray drift from boom and orchard sprayers, and vapour emissions from treated crops. The structure of the resident and bystander models is reported elsewhere, together with a description and discussion of model inputs. This paper describes model outputs, model validation where experimental data are available, a sensitivity analysis for some model components and compares predictions with other European regulatory models, including the recently developed European Food Safety Authority (EFSA) calculator. Because BROWSE models can simulate a range of scenarios, there is a wide range of possible outputs. When using recommended default inputs, the resident and bystander models predict higher exposures than existing regulatory models. This is because the model incorporates more exposure routes and defaults are based on a reasonable worst case scenario. However, the probabilistic nature of the BROWSE models results in lower predicted exposures than the new EFSA calculator. Validation of sections of the model suggests that it is not overly conservative. Sensitivity analysis of the vapour exposure component showed that the interaction between temperature and vapour pressure, which is not taken account of in other models, can result in lower exposures for higher vapour pressures in warmer climates.

The BROWSE model for predicting exposures of residents and bystanders to agricultural use of plant protection products: An overview

New models have been developed, with the aim of improving the estimate of exposure of residents and bystanders to agricultural pesticides for regulatory purposes. These are part of a larger suite of models also covering operators and workers. The population that is modelled for residents and bystanders relates to people (both adults and children) who have no association with the application (i.e. not occupational exposure) but are adjacent to the treated area during and/or after the application process. The scenarios that the models aim to describe are based on consideration of both best practice and of real practice, as shown in surveys and from expert knowledge obtained in stakeholder consultations. The work has focused on three causes of exposure identified as having potential for improvement: boom sprayers, orchard sprayers and vapour emissions. An overview of the models is given, and a description of model input values and proposed defaults. The main causes of uncertainty in the models are also discussed. There are a number of benefits of the BROWSE model over current models of bystander and resident exposure, which includes the incorporation of mitigation measures for reducing exposure and the use of probabilistic modelling to avoid an over-conservative approach. It is expected that the levels of exposure that the BROWSE model predicts will, in some cases, be higher than those predicted by the current UK regulatory model. This is largely because the modelled scenarios have been updated to account for current practice and current scientific knowledge.

Species- and site-specific impacts of an invasive herbivore on tree survival in mixed forests.

Invasive herbivores are often managed to limit their negative impact on plant populations, but herbivore density – plant damage relationships are notoriously spatially and temporally variable. Site and species characteristics (both plant and herbivore) must be considered when assessing the potential for herbivore damage, making it difficult to set thresholds for efficient management. Using the invasive brushtail possum Trichosurus vulpecula in New Zealand as a case study, we parameterized a generic model to predict annual probability of browse‐induced mortality of five tree species at 12 sites. We compared predicted and observed tree mortality for each species + site combination to establish herbivore abundance – tree mortality thresholds for each site on a single and combined tree species basis. Model results indicated it is likely that possum browse was the primary cause of all tree mortality at nine of the 12 species‐site combinations, allowing us to estimate site‐specific thresholds below which possum population numbers should be reduced and maintained to keep tree mortality under a predetermined level, for example 0.5% per year. The browse model can be used to set site‐ and species‐specific management action thresholds, and can be adapted easily for other plant or herbivore species. Results for multiple plant or herbivore species at a single site can be combined to create conservative, site‐wide management strategies, and used to: determine which sites will be affected most by changes in herbivore abundance; quantify thresholds for herbivore management; and justify expenditure on herbivore control.

Network Performance Testing System Integrating Models for Automatic QoE Evaluation of Popular Services: YouTube and Facebook

Smartphones have significantly changed the traffic pattern usage of mobile subscribers. In addition to the classical file sharing and web browsing usage, social networking applications and access to video content are now a significant percentage of the typical user data traffic consumption. As the change in usage pattern affects the performance of mobile networks, operators need methods to estimate how well the network behaves. The metrics to use for the evaluation of the quality of experience (QoE) are only well documented for traditional applications. In this paper a novel QoE system that automatically captures and processes the metrics needed to evaluate two commonly used applications, the social networking application Facebook and the video download application YouTube, is presented. The system uses a test application developed for Android phones, which report the results to a centralized platform capable of processing and presenting the results in different formats. The system has been used to test those two services over 3G/LTE network technologies. In the case of the YouTube services, performance results show a subjective score very similar for the 3G and LTE because of the automatic adaptation of the video coding rate to the network conditions. Testing of the Facebook application has led to the proposal of a new MOS expression that takes into account the content type being posted, which provides more reasonable MOS estimations than the generic web browsing models available in the literature and commonly used to estimate Facebook QoE.

BorreliaBase: a phylogeny-centered browser of Borrelia genomes.

BackgroundThe bacterial genus Borrelia (phylum Spirochaetes) consists of two groups of pathogens represented respectively by B. burgdorferi, the agent of Lyme borreliosis, and B. hermsii, the agent of tick-borne relapsing fever. The number of publicly available Borrelia genomic sequences is growing rapidly with the discovery and sequencing of Borrelia strains worldwide. There is however a lack of dedicated online databases to facilitate comparative analyses of Borrelia genomes.DescriptionWe have developed BorreliaBase, an online database for comparative browsing of Borrelia genomes. The database is currently populated with sequences from 35 genomes of eight Lyme-borreliosis (LB) group Borrelia species and 7 Relapsing-fever (RF) group Borrelia species. Distinct from genome repositories and aggregator databases, BorreliaBase serves manually curated comparative-genomic data including genome-based phylogeny, genome synteny, and sequence alignments of orthologous genes and intergenic spacers.ConclusionsWith a genome phylogeny at its center, BorreliaBase allows online identification of hypervariable lipoprotein genes, potential regulatory elements, and recombination footprints by providing evolution-based expectations of sequence variability at each genomic locus. The phylo-centric design of BorreliaBase (http://borreliabase.org) is a novel model for interactive browsing and comparative analysis of bacterial genomes online.

Content-based and collaborative techniques for tag recommendation: an empirical evaluation

The rapid growth of the so-called Web 2.0 has changed the surfers' behavior. A new democratic vision emerged, in which users can actively contribute to the evolution of the Web by producing new content or enriching the existing one with user generated metadata. In this context the use of tags, keywords freely chosen by users for describing and organizing resources, spread as a model for browsing and retrieving web contents. The success of that collaborative model is justified by two factors: firstly, information is organized in a way that closely reflects the users' mental model; secondly, the absence of a controlled vocabulary reduces the users' learning curve and allows the use of evolving vocabularies. Since tags are handled in a purely syntactical way, annotations provided by users generate a very sparse and noisy tag space that limits the effectiveness for complex tasks. Consequently, tag recommenders, with their ability of providing users with the most suitable tags for the resources to be annotated, recently emerged as a way of speeding up the process of tag convergence. The contribution of this work is a tag recommender system implementing both a collaborative and a content-based recommendation technique. The former exploits the user and community tagging behavior for producing recommendations, while the latter exploits some heuristics to extract tags directly from the textual content of resources. Results of experiments carried out on a dataset gathered from Bibsonomy show that hybrid recommendation strategies can outperform single ones and the way of combining them matters for obtaining more accurate results.

Collaborative hierarchical clustering in the browser for scatter/gather on the web

AbstractScatter/Gather is a powerful browsing model for exploratory information seeking. However, its potential on the web scale has not been demonstrated due to scalability challenges of interactive clustering. We have developed in previous research a two‐stage method to support on‐the‐fly Scatter/Gather, in which an offline module pre‐computes a hierarchical structure to support constant time on‐line interaction. In this work, we focus on the offline hierarchy construction and develop a novel distributed approach to hierarchical agglomerative clustering (HAC). Relying on Javascript that is commonly supported by browsers, the distributed clustering method has the potential to scale with growing traffics of a site. We show in experiments that a moderate increase in the number of parallel processes (in visitors' browsers) leads to a dramatic decrease of clustering time. This demonstrates great potentials in supporting large‐scale Scatter/Gather interactions on the web. We present preliminary analysis of clustering effectiveness and a related Scatter/Gather prototype for web search.

Scatter/Gather browsing of web service QoS data

Many of the current Quality of Service (QoS) based web service selection systems assume that users will formulate QoS queries accurately. However, this may not always be the case. It would be helpful if users could browse through the QoS data of the service repository before they start the searching process. In this way, they could know what the actual QoS value distributions are, so that they could put down reasonable numbers in their QoS queries. The browsing process performed on QoS queries, on the other hand, could help service providers understand the actual QoS demands from users. In this paper, we propose to use the Scatter/Gather model—a well-known browsing model for large document collections, to implement QoS browsing. We modified the original model to make it fit QoS data and implemented a few variations of the model. We tested and compared performance on both synthetic and real QoS datasets, mainly focusing on the ability to handle real time interaction with users while balancing efficiency and accuracy.

Modeling Web Browsing on Mobile Internet

In this letter, we present a Web browsing model for mobile Internet. Instead of relying on simulation data, our approach is based on real data. We set up our model with six parameters including main-object size, embedded object size, number of embedded objects, inter-arrival of embedded objects, reading time and session duration. By using KS-test method, we fit the measurement results to matched statistical distributions. Compared to previous Web studies, our results are new findings.

Small Knowledge Canvas: Software for Managing Fragmental Knowledge

We propose a concept called “Small Knowledge” and a prototype system called “Small Knowledge Canvas” that enables users to collect and utilize fragmental knowledge, “Small Knowledge”. We find pieces of Small Knowledge in our daily life, such as a book that seems interesting, a phrase that might be used in ones writing, or a beautiful place to go. For the first step, though the concept is general, we limit the target for adopting this concept to the Web browsing environment. Small Knowledge can be regarded as an enhanced bookmark with personal context. We also propose a simple browsing model and context extraction algorithm for extracting personal context for Small Knowledge. Finally, we discuss the results of a user experiment of our prototype system.

Modeling Online Browsing and Path Analysis Using Clickstream Data

Clickstream data provide information about the sequence of pages or the path viewed by users as they navigate a website. We show how path information can be categorized and modeled using a dynamic multinomial probit model of Web browsing. We estimate this model using data from a major online bookseller. Our results show that the memory component of the model is crucial in accurately predicting a path. In comparison, traditional multinomial probit and first-order Markov models predict paths poorly. These results suggest that paths may reflect a user's goals, which could be helpful in predicting future movements at a website. One potential application of our model is to predict purchase conversion. We find that after only six viewings purchasers can be predicted with more than 40% accuracy, which is much better than the benchmark 7% purchase conversion prediction rate made without path information. This technique could be used to personalize Web designs and product offerings based upon a user's path.

A summarization system for Chinese news from multiple sources

AbstractThis article proposes a summarization system for multiple documents. It employs not only named entities and other signatures to cluster news from different sources, but also employs punctuation marks, linking elements, and topic chains to identify the meaningful units (MUs). Using nouns and verbs to identify the similar MUs, focusing and browsing models are applied to represent the summarization results. To reduce information loss during summarization, informative words in a document are introduced. For the evaluation, a question answering system (QA system) is proposed to substitute the human assessors. In large‐scale experiments containing 140 questions to 17,877 documents, the results show that those models using informative words outperform pure heuristic voting‐only strategy by news reporters. This model can be easily further applied to summarize multilingual news from multiple sources.