Implementing and Running a Workflow Application on Cloud Resources

Scientist need to run applications that are time and resource consuming, but, not all of them, have the requires knowledge to run this applications in a parallel manner, by using grid, cluster or cloud resources. In the past few years many workflow building frameworks were developed in order to help scientist take a better advantage of computing resources, by designing workflows based on their applications and executing them on heterogeneous resources. This paper presents a case study of implementing and running a workflow for an E-bay data retrieval application. The workflow was designed using Askalon framework and executed on the cloud resources. The purpose of this paper is to demonstrate how workflows and cloud resources can be used by scientists in order to achieve speedup for their application without the need of spending large amounts of money on computational resources.Workflow, Cloud Resource

Pedagogical based Learner Model Characteristics

International audienceThe personalisation and adaptation of content creation, distribution and presentation aim to increase learner quality of experience, improve the learning process and increase the learning outcomes. This paper introduces a novel Learner Model that is integrated by the NEWTON project into the NEWTELP learning platform in order to support personalisation and adaptation. The NEWTON's Learner Model includes a multitude of learner characteristics, including pedagogical, disability, affective and multi-sensorial

Weighting Passages Enhances Accuracy

We observe that in curated documents the distribution of the occurrences of salient terms, e.g., terms with a high Inverse Document Frequency, is not uniform, and such terms are primarily concentrated towards the beginning and the end of the document. Exploiting this observation, we propose a novel version of the classical BM25 weighting model, called BM25 Passage (BM25P), which scores query results by computing a linear combination of term statistics in the different portions of the document. We study a multiplicity of partitioning schemes of document content into passages and compute the collection-dependent weights associated with them on the basis of the distribution of occurrences of salient terms in documents. Moreover, we tune BM25P hyperparameters and investigate their impact on ad hoc document retrieval through fully reproducible experiments conducted using four publicly available datasets. Our findings demonstrate that our BM25P weighting model markedly and consistently outperforms BM25 in terms of effectiveness by up to 17.44% in NDCG@5 and 85% in NDCG@1, and up to 21% in MRR

Exploring the meaning behind twitter hashtags through clustering

Abstract. Social networks are generators of large amount of data produced by users, who are not limited with respect to the content of the information they exchange. The data generated can be a good indicator of trends and topic preferences among users. In our paper we focus on analyzing and representing hashtags by the corpus in which they appear. We cluster a large set of hashtags using K-means on map reduce in order to process data in a distributed manner. Our intention is to retrieve connections that might exist between different hashtags and their textual representation, and grasp their semantics through the main topics they occur with

Energy-aware Adaptive Multimedia for Game-based e-learning

Thanks to their motivational potential, video games have started to be increasingly used for e-learning. However, as e-learning gradually shifts towards mobile learning, there is a growing need for innovative techniques to deliver rich learning material such as educational games to resource-constrained devices. In particular, the limited battery capacity of mobile devices stands out as a key issue that can significantly limit players' access to educational games. This paper proposes an Energy-aware Adaptive Multimedia Game-based E-learning (EAMGBL) framework that aims to enable energy-efficient educational games delivery to mobile devices over wireless networks. The framework builds on top of the idea to render the game on the server side and stream a recording of it to the player's device over the Internet. To reduce the mobile device energy consumption and enable the player to play for longer, the proposed framework proposes to adapt both the educational game elements as well as the game's recorded multimedia stream

Caching Historical Embeddings in Conversational Search

Rapid response, namely low latency, is fundamental in search applications; it is particularly so in interactive search sessions, such as those encountered in conversational settings. An observation with a potential to reduce latency asserts that conversational queries exhibit a temporal locality in the lists of documents retrieved. Motivated by this observation, we propose and evaluate a client-side document embedding cache, improving the responsiveness of conversational search systems. By leveraging state-of-the-art dense retrieval models to abstract document and query semantics, we cache the embeddings of documents retrieved for a topic introduced in the conversation, as they are likely relevant to successive queries. Our document embedding cache implements an efficient metric index, answering nearest-neighbor similarity queries by estimating the approximate result sets returned. We demonstrate the efficiency achieved using our cache via reproducible experiments based on TREC CAsT datasets, achieving a hit rate of up to 75% without degrading answer quality. Our achieved high cache hit rates significantly improve the responsiveness of conversational systems while likewise reducing the number of queries managed on the search back-end

User-centered EEG-based multimedia quality assessment

Multimedia users are becoming increasingly quality-aware as the technological advances make ubiquitous the creation and delivery of high-definition multimedia content. While much research work has been conducted on multimedia quality assessment, most of the existing solutions come with their own limitations, with particular solutions being more suitable to assess particular aspects related to user's Quality of Experience (QoE). In this context, there is an increasing need for innovative solutions to assess user's QoE with multimedia services. This paper proposes the QoE-EEG-Analyser that provides a solution to automatically assess and quantify the impact of various factors contributing to user's QoE with multimedia services. The proposed approach makes use of participant's frustration level measured with a consumer-grade EEG system, the Emotiv EPOC. The main advantage of QoE-EEG-Analyser is that it enables continuous assessment of various QoE factors over the entire testing duration, in a non-invasive way, without requiring the user to provide input about his perceived visual quality. Preliminary subjective results have shown that frustration can indicate user's perceived QoE

Correction to: Human migration: the big data perspective

n/

Paclitaxel: Application in Modern Oncology and Nanomedicine-Based Cancer Therapy

Paclitaxel is a broad-spectrum anticancer compound, which was derived mainly from a medicinal plant, in particular, from the bark of the yew tree Taxus brevifolia Nutt. It is a representative of a class of diterpene taxanes, which are nowadays used as the most common chemotherapeutic agent against many forms of cancer. It possesses scientifically proven anticancer activity against, e.g., ovarian, lung, and breast cancers. The application of this compound is difficult because of limited solubility, recrystalization upon dilution, and cosolvent-induced toxicity. In these cases, nanotechnology and nanoparticles provide certain advantages such as increased drug half-life, lowered toxicity, and specific and selective delivery over free drugs. Nanodrugs possess the capability to buildup in the tissue which might be linked to enhanced permeability and retention as well as enhanced antitumour influence possessing minimal toxicity in normal tissues. This article presents information about paclitaxel, its chemical structure, formulations, mechanism of action, and toxicity. Attention is drawn on nanotechnology, the usefulness of nanoparticles containing paclitaxel, its opportunities, and also future perspective. This review article is aimed at summarizing the current state of continuous pharmaceutical development and employment of nanotechnology in the enhancement of the pharmacokinetic and pharmacodynamic features of paclitaxel as a chemotherapeutic agent