Benchmarking SQL on MapReduce systems using large astronomy databases

In the era of bigdata, with a massive set of digital information of unprecedented volumes being collected and/or produced in several application domains, it becomes more and more difficult to manage and query large data repositories. In the framework of the PetaSky project (http://com.isima.fr/Petasky), we focus on the problem of managing scientific data in the field of cosmology. The data we consider are those of the LSST project (http://www.lsst.org/). The overall size of the database that will be produced is expected to exceed 60 PB (Lsst data challenge handbook, 2012). In order to evaluate the performances of existing SQL On MapReduce data management systems, we conducted extensive experiments by using data and queries from the area of cosmology. The goal of this work is to report on the ability of such systems to support large scale declarative queries. We mainly investigated the impact of data partitioning, indexing and compression on query execution performances.     

Modulo Based Data Placement Algorithm for Energy Consumption Optimization of MapReduce System

With the explosion of data production, the efficiency of data management and analysis has been concerned by both industry and academia. Meanwhile, more and more energy is consumed by the IT infrastructure especially the larger scale distributed systems. In this paper, a novel idea for optimizing the Energy Consumption (EC for short) of MapReduce system is proposed. We argue that a fair data placement is helpful to save energy, and then we propose three goals of data placement, and a modulo based Data Placement Algorithm (DPA for short) which achieves these goals. Afterwards, the correctness of the proposed DPA is proved from both theoretical and experimental perspectives. Three different systems which implement MapReduce model with different DPAs are compared in our experiments. Our algorithm is proved to optimize EC effectively, without introducing the additional costs and delaying data loading. With the help of our DPA, the EC for the WordCount (https://src/examples/org/apache/hadoop/examples/), Sort (https://src/examples/org/apache/hadoop/examples/sort) and MRBench (https://src/examples/org/apache/hadoop/mapred/) can be reduced by 10.9 %, 8.3 % and 17 % respectively, and time consumption is reduced by 7 %, 6.3 % and 7 % respectively.     

VQA: Visual Question Answering

We propose the task of free-form and open-ended Visual Question Answering (VQA). Given an image and a natural language question about the image, the task is to provide an accurate natural language answer. Mirroring real-world scenarios, such as helping the visually impaired, both the questions and answers are open-ended. Visual questions selectively target different areas of an image, including background details and underlying context. As a result, a system that succeeds at VQA typically needs a more detailed understanding of the image and complex reasoning than a system producing generic image captions. Moreover, VQA is amenable to automatic evaluation, since many open-ended answers contain only a few words or a closed set of answers that can be provided in a multiple-choice format. We provide a dataset containing \(\sim \)0.25 M images, \(\sim \)0.76 M questions, and \(\sim \)10 M answers (www.visualqa.org), and discuss the information it provides. Numerous baselines and methods for VQA are provided and compared with human performance. Our VQA demo is available on CloudCV (http://cloudcv.org/vqa).     

An Embedding Based IR Model for Disaster Situations

Twitter (http://twitter.com) is one of the most popular social networking platforms. Twitter users can easily broadcast disaster-specific information, which, if effectively mined, can assist in relief operations. However, the brevity and informal nature of tweets pose a challenge to Information Retrieval (IR) researchers. In this paper, we successfully use word embedding techniques to improve ranking for ad-hoc queries on microblog data. Our experiments with the ‘Social Media for Emergency Relief and Preparedness’ (SMERP) dataset provided at an ECIR 2017 workshop show that these techniques outperform conventional term-matching based IR models. In addition, we show that, for the SMERP task, our word embedding based method is more effective if the embeddings are generated from the disaster specific SMERP data, than when they are trained on the large social media collection provided for the TREC (http://trec.nist.gov/) 2011 Microblog track dataset.     

Automatic initialization of active contours in ultrasound images of breast cancer

Gradient vector flow (GVF) snakes are an efficient method for segmentation of ultrasound images of breast cancer. However, the method produces inaccurate results if the seeds are initialized improperly (far from the true boundaries and close to the false boundaries). Therefore, we propose a novel initialization method designed for GVF-type snakes based on walking particles. At the first step, the algorithm locates the seeds at converging and diverging configurations of the vector field. At the second step, the seeds “explode,” generating a set of random walking particles designed to differentiate between the seeds located inside and outside the object. The method has been tested against five state-of-the-art initialization methods on sixty ultrasound images from a database collected by Thammasat University Hospital of Thailand (http://onlinemedicalimages.com). The ground truth was hand-drawn by leading radiologists of the hospital. The competing methods were: trial snake method (TS), centers of divergence method (CoD), force field segmentation (FFS), Poisson Inverse Gradient Vector Flow (PIG), and quasi-automated initialization (QAI). The numerical tests demonstrated that CoD and FFS failed on the selected test images, whereas the average accuracy of PIG and QAI was 73 and 87%, respectively, versus 97% achieved by the proposed method. Finally, TS has shown a comparable accuracy of about 93%; however, the method is about ten times slower than the proposed exploding seeds. A video demonstration of the algorithm is at http://onlinemedicalimages.com/index.php/en/presentations.     

Cheap talk,cooperation, and trust in global software engineering

In our studies of global software engineering (GSE) teams, we found that informal, non-work-related conversations are positively associated with trust. Seeking to use novel analytical techniques to more carefully investigate this phenomenon, we described these non-work-related conversations by adapting the economics literature concept of “cheap talk,” and studied it using Evolutionary Game Theory (EGT). More specifically, we modified the classic Stag-hunt game and analyzed the dynamics in a fixed population setting (an abstraction of a GSE team). Doing so, we were able to demonstrate how cheap talk over the Internet (e-cheap talk) was powerful enough to facilitate the emergence of trust and improve the probability of cooperation where the punishment for uncooperative behavior is comparable to the cost of the cheap talk. To validate the results of our theoretical approach, we conducted two empirical case studies that analyzed the logged IRC development discussions of Apache Lucene (http://lucene.apache. org/) and Chromium OS (http://www.chromium.org/chromium-os) using both quantitative and qualitative methods. The results provide general support to the theoretical propositions. We discuss our findings and the theoretical and practical implications to GSE collaborations and research.     

A quantitative approach to evaluate Website Archivability using the CLEAR+ method

Website Archivability (WA) is a notion established to capture the core aspects of a website, crucial in diagnosing whether it has the potential to be archived with completeness and accuracy. In this work, aiming at measuring WA, we introduce and elaborate on all aspects of CLEAR+, an extended version of the Credible Live Evaluation Method for Archive Readiness (CLEAR) method. We use a systematic approach to evaluate WA from multiple different perspectives, which we call Website Archivability Facets. We then analyse archiveready.com, a web application we created as the reference implementation of CLEAR+, and discuss the implementation of the evaluation workflow. Finally, we conduct thorough evaluations of all aspects of WA to support the validity, the reliability and the benefits of our method using real-world web data.     

Improving topology optimization intuition through games

This paper describes the educational game, TopOpt Game, which invites the player to solve various optimization challenges. The main purpose of gamifying topology optimization is to create a supplemental educational tool which can be used to introduce concepts of topology optimization to newcomers as well as to train human intuition of topology optimization. The players are challenged to solve the standard minimum compliance problem in 2D by distributing material in a design domain given a number of loads and supports with a material constraint. A statistical analysis of the gameplay data shows that players achieve higher scores the more they play the game. The game is freely available for the iOS platform at Apple’s App Store and at http://www.topopt.dtu.dk/?q=node/909 for Windows and OSX.     

Dynamically pre-trained deep recurrent neural networks using environmental monitoring data for predicting PM<Subscript>2.5</Subscript>

Fine particulate matter (\(\hbox {PM}_{2.5}\)) has a considerable impact on human health, the environment and climate change. It is estimated that with better predictions, US$9 billion can be saved over a 10-year period in the USA (State of the science fact sheet air quality. http://www.noaa.gov/factsheets/new, 2012). Therefore, it is crucial to keep developing models and systems that can accurately predict the concentration of major air pollutants. In this paper, our target is to predict \(\hbox {PM}_{2.5}\) concentration in Japan using environmental monitoring data obtained from physical sensors with improved accuracy over the currently employed prediction models. To do so, we propose a deep recurrent neural network (DRNN) that is enhanced with a novel pre-training method using auto-encoder especially designed for time series prediction. Additionally, sensors selection is performed within DRNN without harming the accuracy of the predictions by taking advantage of the sparsity found in the network. The numerical experiments show that DRNN with our proposed pre-training method is superior than when using a canonical and a state-of-the-art auto-encoder training method when applied to time series prediction. The experiments confirm that when compared against the \(\hbox {PM}_{2.5}\) prediction system VENUS (National Institute for Environmental Studies. Visual Atmospheric Environment Utility System. http://envgis5.nies.go.jp/osenyosoku/, 2014), our technique improves the accuracy of \(\hbox {PM}_{2.5}\) concentration level predictions that are being reported in Japan.     

Caracolomobile: affect in computer systems

This essay presents and reflects upon the construction of a few experimental artworks, among them Caracolomobile, that looks for poetic, aesthetic and functional possibilities to bring computer systems to the sensitive universe of human emotions, feelings and expressions. Modern and Contemporary Art have explored such qualities in unfathomable ways and nowadays is turning towards computer systems and their co-related technologies. This universe characterizes and is the focus of these experimental artworks; artworks dealing with entwined subjective and objective qualities, weaving perceptions, sensations and concepts. One of them, Caracolomobile, features an art installation creating a set up for an artificial robot that recognizes humans’ affective states and answers them with movements and sounds. The robot was installed over an artificial mirror lake in an open indigo-blue space surrounded by mirrors. It perceives and discriminates human emotional states and expressions using an interface developed with a non-intrusive neural headset (The neural headset used was developed by Emotiv Systems: http://www.emotiv.com. Accessed 11 August 2011). This artwork raises questions and looks for answers inquiring about the preliminary steps for the creation of artefacts that would conduct one to poetically experiment with affect, emotion, sensations and feelings in computational systems. Other works in progress ask about the poetic possibilities of mixing computational autonomous processes and behavioural robotic procedures (Arkin 1998) to create artificial environments mixed with humans.     

Personalized multimedia content delivery on an interactive table by passive observation of museum visitors

The amount of multimedia data collected in museum databases is growing fast, while the capacity of museums to display information to visitors is acutely limited by physical space. Museums must seek the perfect balance of information given on individual pieces in order to provide sufficient information to aid visitor understanding while maintaining sparse usage of the walls and guaranteeing high appreciation of the exhibit. Moreover, museums often target the interests of average visitors instead of the entire spectrum of different interests each individual visitor might have. Finally, visiting a museum should not be an experience contained in the physical space of the museum but a door opened onto a broader context of related artworks, authors, artistic trends, etc. In this paper we describe the MNEMOSYNE system that attempts to address these issues through a new multimedia museum experience. Based on passive observation, the system builds a profile of the artworks of interest for each visitor. These profiles of interest are then used to drive an interactive table that personalizes multimedia content delivery. The natural user interface on the interactive table uses the visitor’s profile, an ontology of museum content and a recommendation system to personalize exploration of multimedia content. At the end of their visit, the visitor can take home a personalized summary of their visit on a custom mobile application. In this article we describe in detail each component of our approach as well as the first field trials of our prototype system built and deployed at our permanent exhibition space at LeMurate (http://www.lemurate.comune.fi.it/lemurate/) in Florence together with the first results of the evaluation process during the official installation in the National Museum of Bargello (http://www.uffizi.firenze.it/musei/?m=bargello).     

Topology optimization using PETSc: An easy-to-use,fully parallel,open source topology optimization framework

This paper presents a flexible framework for parallel and easy-to-implement topology optimization using the Portable and Extendable Toolkit for Scientific Computing (PETSc). The presented framework is based on a standardized, and freely available library and in the published form it solves the minimum compliance problem on structured grids, using standard FEM and filtering techniques. For completeness a parallel implementation of the Method of Moving Asymptotes is included as well. The capabilities are exemplified by minimum compliance and homogenization problems. In both cases the unprecedented fine discretization reveals new design features, providing novel insight. The code can be downloaded from www.topopt.dtu.dk/PETSc.     

Anonymity interacting with participation on a Q&amp;A site

This article presents a study that investigates how anonymity influences user participation in an online question-and-answer platform [Quora (https://www.quora.com/)]. The study is one step in identifying hypotheses that can be used to address a research and design issue concerning the role of anonymity in online participation, particularly in sensitive situations where people are seeking social support. Based on the literature, we present a model that describes the factors that influence participation. These factors were used when analyzing the answers to questions in the health category on Quora. The results of this study were completed by a survey asking Quora users about their use of the anonymity feature. The main result is that the only significant difference between anonymous and non-anonymous answers is that: with anonymous answers, social appreciation correlated with the answer’s length.     

VizAssist: an interactive user assistant for visual data mining

We study in this work how a user can be guided to find a relevant visualization in the context of visual data mining. We present a state of the art on the user assistance in visual and interactive methods. We propose a user assistant called VizAssist, which aims at improving the existing approaches along three directions: it uses simpler computational models of the visualizations and the visual perception guidelines, in order to facilitate the integration of new visualizations and the definition of a mapping heuristic. VizAssist allows the user to provide feedback in a visual and interactive way, with the aim of improving the data to visualization mapping. This step is performed with an interactive genetic algorithm. Finally, VizAssist aims at proposing a free on-line tool (www.vizassist.fr) that respects the privacy of the user data. This assistant can be viewed as a global interface between the user and some of the many visualizations that are implemented with D3js.     

Growth method for size,topology, and geometry optimization of truss structures

The problem of optimally designing the topology of plane trusses has, in most cases, been dealt with as a size problem in which members are eliminated when their size tends to zero. This article presents a novel growth method for the optimal design in a sequential manner of size, geometry, and topology of plane trusses without the need of a ground structure. The method has been applied to single load case problems with stress and size constraints. It works sequentially by adding new joints and members optimally, requiring five basic steps: (1) domain specification, (2) topology and size optimization, (3) geometry optimization, (4) optimality verification, and (5) topology growth. To demonstrate the proposed growth method, three examples were carried out: Michell cantilever, Messerschmidt–Bölkow–Blohm beam, and Michell cantilever with fixed circular boundary. The results obtained with the proposed growth method agree perfectly with the analytical solutions. A Windows XP program, which demonstrates the method, can be downloaded from http://www.upct.es/~deyc/software/tto/.     

Quantum to classical one-way function and its applications in quantum money authentication

In 2013, Farid and Vasiliev [arXiv:1310.4922 [quant-ph]] for the first time proposed a way to construct a protocol for the realisation of “Classical to Quantum” one-way hash function, a derivative of the quantum one-way function as defined by Gottesman and Chuang [Technical Report arXiv:quant-ph/0105032] and used it for constructing quantum digital signatures. We, on the other hand, for the first time, propose the idea of a different kind of one-way function, which is “quantum-classical” in nature, that is, it takes an n-qubit quantum state of a definite kind as its input and produces a classical output. We formally define such a one-way function and propose a way to construct and realise it. The proposed one-way function turns out to be very useful in authenticating a quantum state in any quantum money scheme, and so we can construct many different quantum money schemes based on such a one-way function. Later in the paper, we also give explicit constructions of some interesting quantum money schemes like quantum bitcoins and quantum currency schemes, solely based on the proposed one-way function. The security of such schemes can be explained on the basis of the security of the underlying one-way functions.     

An interactive satisficing approach for multi-objective optimization with uncertain parameters

Uncertain variables are used to describe the phenomenon where uncertainty appears in a complex system. For modeling the multi-objective decision-making problems with uncertain parameters, a class of uncertain optimization is suggested for the decision systems in Liu and Chen (2013), http://orsc.edu.cn/online/131020 which is called the uncertain multi-objective programming. In order to solve the proposed uncertain multi-objective programming, an interactive uncertain satisficing approach involving the decision-maker’s flexible demands is proposed in this paper. It makes an improvement in contrast to the noninteractive methods. Finally, a numerical example about the capital budget problem is given to illustrate the effectiveness of the proposed model and the relevant solving approach.     

Activity recognition system using inbuilt sensors of smart mobile phone and minimizing feature vectors

Mobile phone is becoming a very popular tool due to having various user friendly applications with all flexible options. It is highly popular for its light weight, wearable and comfortable uses. Many extrinsic habitat of human being can be monitored by the help of inbuilt sensors and its application software. This has appealing use for healthcare applications using exploitation of Ambient Intelligence for daily activity monitoring system. Here, a standard dataset of UCI HAR (University of California, Irvine, Human Activity Recognition, http://archive.ics.uci.edu) is used for analysis purpose. Naive Bayes Classifier is used for recognition of runtime activities minimizing dimension of large feature vectors. Threshold based condition box is designed by us and finally these two results are compared with that of another classifier HF-SVM (Hardware Friendly-Support Vector Machine) of previous related work.     

Subdividing Long-Running,Variable-Length Analyses Into Short,Fixed-Length BOINC Workunits

We describe a scheme for subdividing long-running, variable-length analyses into short, fixed-length boinc workunits using phylogenetic analyses as an example. Fixed-length workunits decrease variance in analysis runtime, improve overall system throughput, and make boinc a more useful resource for analyses that require a relatively fast turnaround time, such as the phylogenetic analyses submitted by users of the garli web service at molecularevolution.org. Additionally, we explain why these changes will benefit volunteers who contribute their processing power to boinc projects, such as the Lattice boinc Project (http://boinc.umiacs.umd.edu). Our results, which demonstrate the advantages of relatively short workunits, should be of general interest to anyone who develops and deploys an application on the boinc platform.