Abstract

Toggle navigation CCSD. HAL: HAL; HALSHS; TEL; MédiHAL; Liste des portails; AURéHAL; API; Data; Documentation. Episciences.org: Episciences.org; Revues; Documentation. Sciencesconf.org; Support. Connexion: Connexion; Connexion avec ORCID; se connecter avec Fédération; Créer un compte; Mot de passe oublié ? Login oublié ? fr; en. HAL - hal.archives-ouvertes.fr. Accueil; Déposer; Consulter: par thème arXiv; Par type de document; Les derniers dépôts; par année de publication; par laboratoire; —————; HAL; TEL; INSPIRE-HEP; ArXiv; CDS - CERN. Rechercher. in2p3-01577700, version 1. Structure, energetics, and dynamics of smectite clay hydration: Molecular dynamics investigations of hectorite” (oral). Christin P. Morrow A. Ozgur Yazaydin 1 Marimuthu Krishnan Geoffrey M. Bowers Andrey G. Kalinichev 2 R. James Kirkpatrick Détails. 1 Department of Chemistry. 2 SUBATECH - Laboratoire

Abstract

Legal judgements are complex in nature and contain cita-tions to other judgements. Research efforts are going on to develop meth-ods for efficient search of relevant legal information by extending the pop-ular approaches used in information retrieval and web searching research areas. In the literature, it was shown that it is possible to find similarjudgements by exploiting citations or links. In this paper, an approachh as been has been proposed using the notion of “paragraph-link” to im-prove the efficiency of link-based similarity method. The experiments on real-world data set and user evaluation study show the encouraging results.

Abstract

This paper presents a novel answer summarization approach for community Question Answering services (cQAs) to address the problem of “incomplete answer”, i.e., missing valuable information from the “best answer” of a complex multi-sentence question, which can be obtained from other answers to the same question. Our method automatically generate a novel and non-redundant summary from cQA answers using structured determinantal point processes (SDPP). Experimental evaluation on sample dataset from Yahoo Answers shows significant improvement over baseline approaches.

Abstract

The ever increasing data on world wide web calls for the use of vertical search engines. Sandhan is one such search engine which offers search in tourism and health genres in more than 10 different Indian languages. In this work we build a URL based genre identification module for Sandhan. A direct impact of this work is on building focused crawlers to gather Indian language content. We conduct experiments on tourism and health web pages in Hindi language. We experiment with three approaches-list based, naive Bayes and incremental naive Bayes. We evaluate our approaches against another web page classification algorithm built on the parsed text of manually labeled web pages. We find that incremental naive Bayes approach outperforms the other two. While doing our experiments we work with different features like words, n-grams and all grams. Using n-gram features we achieve classification accuracies of 0.858 and 0.873 for tourism and health genres respectively.

Abstract

Content discovery is fast becoming the preferred tool for user engagement on the web. Discovery allows users to get educated and entertained about their topics of interest. StumbleUpon is the largest personalized content discovery engine on the Web, delivering more than 1 billion personalized recommendations per month. As a recommendation system one of the primary metrics we track is whether the user returns (retention) to use the product after their initial experience (session) with StumbleUpon

Abstract

The availability of increasingly richer applications is providing surprisingly wide range of functionalities and new use cases on mobile devices. Even tough mobile devices are becoming increasingly more powerful, the resource utilization of richer application can overwhelm resources on these devices. At the same time, ubiquitous connectivity of mobile devices also opens up the possibility of leveraging cloud resources. Seamless and flexible path to mobile cloud computing requires recognizing opportunities where the application execution on cloud instead of mobile device. In this paper we propose a cloud aware scheduler for application offloading from mobile devices to clouds. We used learning based algorithm for predicting the gain attainable using performance monitoring and high level features. We evaluated prototype of our system on various workloads and under various conditions.

Abstract

Resource management in modern data centers has become a challenging task due to the tremendous growth of data centers. In large virtual data centers, performance of applications is highly dependent on the communication bandwidth available among virtual machines. Traditional algorithms either do not consider network I/O details of the applications or are computationally intensive. We address the problem of identifying the virtual machine clusters based on the network traffic and placing them intelligently in order to improve the application performance and optimize the network usage in large data center. We propose a greedy consolidation algorithm that ensures the number of migrations is small and the placement decisions are fast, which makes it practical for large data centers. We evaluated our approach on real world traces from private and academic data centers, using simulation and compared the existing algorithms on various parameters like scheduling time, performance improvement and number of migrations. We observed a ~70% savings of the interconnect bandwidth and overall ~60% improvements in the applications performances. Also, these improvements were produced within a fraction of scheduling time and number of migrations.

Abstract

Thermal comfort in building results from a complex set of physical conditions, occupant sensations and preferences as well as occupants behaviour therefore thermally comfortable environment leads to better energy efficiency in buildings. A field study was carried out at five star rated (Certified by Bureau of Energy Efficiency, BEE) air conditioned office building (day time occupancy) located at Jaipur, composite climate of India. The purpose of conducting this study was to evaluate the existing thermal environmental conditions and then to propose the required thermal comfort conditions and determine energy saving potential considering adaptive thermostat control strategy. Questionnaire was developed for conducting the field survey including objective and subjective information as per class˗ II protocol of field measurements. Statistical analysis of occupant responses and recorded environmental variables was performed to determine the required comfortable temperature in the building and this temperature was used as thermostat set point of the air conditioner. The office building was modelled using eQUEST simulation program and calibrated with measured annual energy consumption. Result revealed that majority of the occupants felt thermally comfortable at proposed room temperature of 27.5oC as against the existing practice of maintaining 20-22oC at which most of the occuapants were complaining overcooling and discomfort. Proposed set point temperature of air conditioner also resulted in building energy saving of about 7.86%.

Abstract

Field study of thermal comfort was conducted in six naturally ventilated hostel buildings of composite climate considering Class-II protocol of field measurement during summer 2011. Total 429 survey samples of same age group (average 19.6 years) were collected including objective and subjective measurements. Statistical analysis of student's responses and measured thermal environment variables was performed to determine existing indoor environmental conditions and priority of using behavioural controls. Thermal comfort indices were also calculated and compared to the student's perceptions. Neutral temperature was found to be 30.15 °C through regression analysis, with an average clothing of 0.41 Clo (min. 0.19 Clo, max 0.82 Clo). Results have shown a wide bandwidth of neutral temperatures (25.9–33.8 °C) for the hostel buildings which is higher than national/international standards of thermal comfort …

Abstract

In this paper, we show that certain phrases although not present in a given question/query, play a very important role in answering the question. Exploring the role of such phrases in answering questions not only reduces the dependency on matching question phrases for extracting answers, but also improves the quality of the extracted answers. Here matching question phrases means phrases which co-occur in given question and candidate answers. To achieve the above discussed goal, we introduce a bigram-based word graph model populated with semantic and topical relatedness of terms in the given document. Next, we apply an improved version of ranking with a prior-based approach, which ranks all words in the candidate document with respect to a set of root words (ie non-stopwords present in the question and in the candidate document). As a result, terms logically related to the root words are scored higher than terms that are not related to the root words. Experimental results show that our devised system performs better than state-of-the-art for the task of answering Why-questions.