Query: Indoor positioning of mobile devices with agile iBeacon deployment

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A New Method for Yielding a Database of Location Fingerprints in WLAN <=SEP=> Location fingerprinting in wireless LAN (WLAN) positioning has received much attention recently. One of the key issues of this technique is generating the database of ‘fingerprints’. The conventional method does not utilise the spatial correlation of measurements sampled at adjacent reference points (RPs), and the ‘training’ process is not an easy task. A new method based on kriging is presented in this paper. An experiment shows that the new method can not only achieve more accurate estimation, but can also greatly reduce the workload and save training time. This can make the fingerprinting technique more flexible and easier to implement. Binghao Li, Yufei Wang, Andrew Dempster, Chris Rizos are with the School of Surveying and Spatial Information System, University of New South Wales, Sydney, Australia Hyung Keun Lee is with the School of Avionics and Telecommunication, Hankuk Aviation University, Kyunggi-do, Korea

Hybrid algorithm for indoor positioning using wireless LAN <=SEP=> Locating an indoor mobile station based on a wireless communication infrastructure, has practical applications. The most widely employed methods today use an RF propagation loss (PL) model or location fingerprinting (LF). The PL method is known to perform poorly compared to LF. But LF requires an extensive training dataset and cannot adapt well to configuration changes or receiver breakdown. In this paper, we develop a hybrid method that combines the strength of these two methods. It first formulates the RF PL in a nonlinear, censored regression model and adjusts the regression function to the observed signal strength in the fingerprint dataset. In the absence of a training dataset, the hybrid method coincides with the PL method, and, as the spatial granularity of the training dataset increases, the result of the algorithm approaches the result of the LF method. It balances the flexibility and accuracy of the two traditional methods, makes intelligent use of missing values, produces error bounds, and can be made dynamic. We evaluate the performance of the algorithm by applying it to a real site and observe satisfactory positioning accuracy.

Introduction to Algorithms <=SEP=> problems To understand the class of polynomial-time solvable proble ms, we must first have a formal notion of what a “problem” is. We define anbstract problemQ to be a binary relation on a set I of probleminstancesand a setS of problemsolutions. For example, an instance for SHORTEST-PATH is a triple consi sting of a graph and two vertices. A solution is a sequence of vertices in the g raph, with perhaps the empty sequence denoting that no path exists. The problem SHORTEST-PATH itself is the relation that associates each instance of a gra ph and two vertices with a shortest path in the graph that connects the two vertices. S ince shortest paths are not necessarily unique, a given problem instance may have mo r than one solution. This formulation of an abstract problem is more general than is required for our purposes. As we saw above, the theory of NP-completeness res tricts attention to decision problems : those having a yes/no solution. In this case, we can view an abstract decision problem as a function that maps the instan ce setI to the solution set {0, 1}. For example, a decision problem related to SHORTEST-PATH i s the problem PATH that we saw earlier. If i = 〈G,u, v,k〉 is an instance of the decision problem PATH, then PATH(i ) = 1 (yes) if a shortest path fromu to v has at mostk edges, and PATH (i ) = 0 (no) otherwise. Many abstract problems are not decision problems, but rather optimization problems , in which some value must be minimized or maximized. As we saw above, however, it is usual ly a simple matter to recast an optimization problem as a decision problem that is no harder. 1See Hopcroft and Ullman [156] or Lewis and Papadimitriou [20 4] for a thorough treatment of the Turing-machine model. 34.1 Polynomial time 973

RADAR: An In-Building RF-Based User Location and Tracking System <=SEP=> The proliferation of mobile computing devices and local-area wireless networks has fostered a growing interest in location-aware systems and services. In this paper we present RADAR, a radio-frequency (RF) based system for locating and tracking users inside buildings. RADAR operates by recording and processing signal strength information at multiple base stations positioned to provide overlapping coverage in the area of interest. It combines empirical measurements with signal propagation modeling to determine user location and thereby enable locationaware services and applications. We present experimental results that demonstrate the ability of RADAR to estimate user location with a high degree of accuracy.

WLAN location determination via clustering and probability distributions <=SEP=> We present a WLAN location determination technique, the Joint Clustering technique, that uses: (1) signal strength probability distributions to address the noisy wireless channel, and (2) clustering of locations to reduce the computational cost of searching the radio map. The Joint Clustering technique reduces computational cost by more than an order of magnitude, compared to the current state of the art techniques, allowing non-centralized implementation on mobile clients. Results from 802.11-equipped iPAQ implementations show that the new technique gives user location to within 7 feet with over 90% accuracy.

A Knowledge-Augmented Neural Network Model for Implicit Discourse Relation Classification <=SEP=> Identifying discourse relations that are not overtly marked with discourse connectives remains a challenging problem. The absence of explicit clues indicates a need for the combination of world knowledge and weak contextual clues, which can hardly be learned from a small amount of manually annotated data. In this paper, we address this problem by augmenting the input text with external knowledge and context and by adopting a neural network model that can effectively handle the augmented text. Experiments show that external knowledge did improve the classification accuracy. On the other hand, contextual information provided no significant gain for implicit discourse relations while it worked for explicit ones.

Splitting approaches for context-aware recommendation: an empirical study <=SEP=> User and item splitting are well-known approaches to context-aware recommendation. To perform item splitting, multiple copies of an item are created based on the contexts in which it has been rated. User splitting performs a similar treatment with respect to users. The combination of user and item splitting: UI splitting, splits both users and items in the data set to boost context-aware recommendations. In this paper, we perform an empirical comparison of these three context-aware splitting approaches (CASA) on multiple data sets, and we also compare them with other popular context-aware collaborative filtering (CACF) algorithms. To evaluate those algorithms, we propose new evaluation metrics specific to contextual recommendation. The experiments reveal that CASA typically outperform other popular CACF algorithms, but there is no clear winner among the three splitting approaches. However, we do find some underlying patterns or clues for the application of CASA.

SIGN LANGUAGE RECOGNITION: STATE OF THE ART <=SEP=> Sign language is used by deaf and hard hearing people to exchange information between their own community and with other people. Computer recognition of sign language deals from sign gesture acquisition and continues till text/speech generation. Sign gestures can be classified as static and dynamic. However static gesture recognition is simpler than dynamic gesture recognition but both recognition systems are important to the human community. The sign language recognition steps are described in this survey. The data acquisition, data preprocessing and transformation, feature extraction, classification and results obtained are examined. Some future directions for research in this area also suggested.

Cross-modal plasticity: where and how? <=SEP=> Animal studies have shown that sensory deprivation in one modality can have striking effects on the development of the remaining modalities. Although recent studies of deaf and blind humans have also provided convincing behavioural, electrophysiological and neuroimaging evidence of increased capabilities and altered organization of spared modalities, there is still much debate about the identity of the brain systems that are changed and the mechanisms that mediate these changes. Plastic changes across brain systems and related behaviours vary as a function of the timing and the nature of changes in experience. This specificity must be understood in the context of differences in the maturation rates and timing of the associated critical periods, differences in patterns of transiently existing connections, and differences in molecular factors across brain systems.

Transforming Cooling Optimization for Green Data Center via Deep Reinforcement Learning <=SEP=> Cooling system plays a critical role in a modern data center (DC). Developing an optimal control policy for DC cooling system is a challenging task. The prevailing approaches often rely on approximating system models that are built upon the knowledge of mechanical cooling, electrical and thermal management, which is difficult to design and may lead to suboptimal or unstable performances. In this paper, we propose utilizing the large amount of monitoring data in DC to optimize the control policy. To do so, we cast the cooling control policy design into an energy cost minimization problem with temperature constraints, and tap it into the emerging deep reinforcement learning (DRL) framework. Specifically, we propose an end-toend cooling control algorithm (CCA) that is based on the actorcritic framework and an off-policy offline version of the deep deterministic policy gradient (DDPG) algorithm. In the proposed CCA, an evaluation network is trained to predict an energy cost counter penalized by the cooling status of the DC room, and a policy network is trained to predict optimized control settings when gave the current load and weather information. The proposed algorithm is evaluated on the EnergyPlus simulation platform and on a real data trace collected from the National Super Computing Centre (NSCC) of Singapore. Our results show that the proposed CCA can achieve about 11% cooling cost saving on the simulation platform compared with a manually configured baseline control algorithm. In the trace-based study, we propose a de-underestimation validation mechanism as we cannot directly test the algorithm on a real DC. Even though with DUE the results are conservative, we can still achieve about 15% cooling energy saving on the NSCC data trace if we set the inlet temperature threshold at 26.6 degree Celsius.

Non-Orthogonal Multiple Access Based Integrated Terrestrial-Satellite Networks <=SEP=> In this paper, we investigate the downlink transmission of a non-orthogonal multiple access (NOMA)-based integrated terrestrial-satellite network, in which the NOMA-based terrestrial networks and the satellite cooperatively provide coverage for ground users while reusing the entire bandwidth. For both terrestrial networks and the satellite network, multi-antennas are equipped and beamforming techniques are utilized to serve multiple users simultaneously. A channel quality-based scheme is proposed to select users for the satellite, and we then formulate the terrestrial user pairing as a max–min problem to maximize the minimum channel correlation between users in one NOMA group. Since the terrestrial networks and the satellite network will cause interference to each other, we first investigate the capacity performance of the terrestrial networks and the satellite networks separately, which can be decomposed into the designing of beamforming vectors and the power allocation schemes. Then, a joint iteration algorithm is proposed to maximize the total system capacity, where we introduce the interference temperature limit for the satellite since the satellite can cause interference to all base station users. Finally, numerical results are provided to evaluate the user paring scheme as well as the total system performance, in comparison with some other proposed algorithms and existing algorithms.

Handling class imbalance in customer churn prediction <=SEP=> 0957-4174/$ see front matter 2008 Elsevier Ltd. A doi:10.1016/j.eswa.2008.05.027 * Corresponding author. Tel.: +32 9 264 89 80; fax: E-mail address: dirk.vandenpoel@UGent.be (D. Va URL: http://www.crm.UGent.be (D. Van den Poel). Customer churn is often a rare event in service industries, but of great interest and great value. Until recently, however, class imbalance has not received much attention in the context of data mining [Weiss, G. M. (2004). Mining with rarity: A unifying framework. SIGKDD Explorations, 6 (1), 7–19]. In this study, we investigate how we can better handle class imbalance in churn prediction. Using more appropriate evaluation metrics (AUC, lift), we investigated the increase in performance of sampling (both random and advanced under-sampling) and two specific modelling techniques (gradient boosting and weighted random forests) compared to some standard modelling techniques. AUC and lift prove to be good evaluation metrics. AUC does not depend on a threshold, and is therefore a better overall evaluation metric compared to accuracy. Lift is very much related to accuracy, but has the advantage of being well used in marketing practice [Ling, C., & Li, C. (1998). Data mining for direct marketing problems and solutions. In Proceedings of the fourth international conference on knowledge discovery and data mining (KDD-98). New York, NY: AAAI Press]. Results show that under-sampling can lead to improved prediction accuracy, especially when evaluated with AUC. Unlike Ling and Li [Ling, C., & Li, C. (1998). Data mining for direct marketing problems and solutions. In Proceedings of the fourth international conference on knowledge discovery and data mining (KDD98). New York, NY: AAAI Press], we find that there is no need to under-sample so that there are as many churners in your training set as non churners. Results show no increase in predictive performance when using the advanced sampling technique CUBE in this study. This is in line with findings of Japkowicz [Japkowicz, N. (2000). The class imbalance problem: significance and strategies. In Proceedings of the 2000 international conference on artificial intelligence (IC-AI’2000): Special track on inductive learning, Las Vegas, Nevada], who noted that using sophisticated sampling techniques did not give any clear advantage. Weighted random forests, as a cost-sensitive learner, performs significantly better compared to random forests, and is therefore advised. It should, however always be compared to logistic regression. Boosting is a very robust classifier, but never outperforms any other technique. 2008 Elsevier Ltd. All rights reserved.

Distributed Denial of Service: Taxonomies of Attacks, Tools, and Countermeasures <=SEP=> Distributed Denial of Service (DDoS) attacks have become a large problem for users of computer systems connected to the Internet. DDoS attackers hijack secondary victim systems using them to wage a coordinated large-scale attack against primary victim systems. As new countermeasures are developed to prevent or mitigate DDoS attacks, attackers are constantly developing new methods to circumvent these new countermeasures. In this paper, we describe DDoS attack models and propose taxonomies to characterize the scope of DDoS attacks, the characteristics of the software attack tools used, and the countermeasures available. These taxonomies illustrate similarities and patterns in different DDoS attacks and tools, to assist in the development of more generalized solutions to countering DDoS attacks, including new derivative attacks.

A new Design Criteria for Hash-Functions <=SEP=> The most common way of constructing a hash function (e.g., SHA-1) is to iterate a compression function on the input message. The compression function is usually designed from scratch or made out of a block-cipher. In this paper, we introduce a new security notion for hash-functions, stronger than collision-resistance. Under this notion, the arbitrary length hash function H must behave as a random oracle when the fixed-length building block is viewed as an ideal primitive. This enables to eliminate all possible generic attacks against iterative hash-functions. In this paper, we show that the current design principle behind hash functions such as SHA-1 and MD5 — the (strengthened) Merkle-Damg̊ard transformation — does not satisfy this security notion. We provide several constructions that provably satisfy this notion; those new constructions introduce minimal changes to the plain Merkle-Damg̊ard construction and are easily implementable in practice. This paper is a modified version of a paper to appear at Crypto 2005.

community2vec: Vector representations of online communities encode semantic relationships <=SEP=> Vector embeddings of words have been shown to encode meaningful semantic relationships that enable solving of complex analogies. This vector embedding concept has been extended successfully to many different domains and in this paper we both create and visualize vector representations of an unstructured collection of online communities based on user participation. Further, we quantitatively and qualitatively show that these representations allow solving of semantically meaningful community analogies and also other more general types of relationships. These results could help improve community recommendation engines and also serve as a tool for sociological studies of community relatedness.

7th order sub-millimeter wave frequency multiplier based on graphene implemented using a microstrip transition between two rectangular waveguides <=SEP=> In this work, a 7th order sub-millimeter wave frequency multiplier for Terahertz applications is presented. The multiplier is based on a microstrip line with a small gap where a graphene film layer is deposited. The multiplication phenomena is reached via the nonlinear behavior of the graphene film using an input signal provided by the WR28 standard waveguide operating in the Ka frequency band (31 to 40 GHz). A prototype of the multiplier has been manufactured and the behavior of the output power in the 220-280 GHz band versus the input power has been experimentally characterized.

An FPGA Platform for Real-Time Simulation of Spiking Neuronal Networks <=SEP=> In the last years, the idea to dynamically interface biological neurons with artificial ones has become more and more urgent. The reason is essentially due to the design of innovative neuroprostheses where biological cell assemblies of the brain can be substituted by artificial ones. For closed-loop experiments with biological neuronal networks interfaced with in silico modeled networks, several technological challenges need to be faced, from the low-level interfacing between the living tissue and the computational model to the implementation of the latter in a suitable form for real-time processing. Field programmable gate arrays (FPGAs) can improve flexibility when simple neuronal models are required, obtaining good accuracy, real-time performance, and the possibility to create a hybrid system without any custom hardware, just programming the hardware to achieve the required functionality. In this paper, this possibility is explored presenting a modular and efficient FPGA design of an in silico spiking neural network exploiting the Izhikevich model. The proposed system, prototypically implemented on a Xilinx Virtex 6 device, is able to simulate a fully connected network counting up to 1,440 neurons, in real-time, at a sampling rate of 10 kHz, which is reasonable for small to medium scale extra-cellular closed-loop experiments.

Induction of mitochondrial-mediated apoptosis by Morinda citrifolia (Noni) in human cervical cancer cells. <=SEP=> Cervical cancer is the second most common cause of cancer in women and has a high mortality rate. Cisplatin, an antitumor agent, is generally used for its treatment. However, the administration of cisplatin is associated with side effects and intrinsic resistance. Morinda citrifolia (Noni), a natural plant product, has been shown to have anti-cancer properties. In this study, we used Noni, cisplatin, and the two in combination to study their cytotoxic and apoptosis-inducing effects in cervical cancer HeLa and SiHa cell lines. We demonstrate here, that Noni/Cisplatin by themselves and their combination were able to induce apoptosis in both these cell lines. Cisplatin showed slightly higher cell killing as compared to Noni and their combination showed additive effects. The observed apoptosis appeared to be mediated particularly through the up-regulation of p53 and pro-apoptotic Bax proteins, as well as down- regulation of the anti-apoptotic Bcl-2, Bcl-XL proteins and survivin. Augmentation in the activity of caspase-9 and -3 was also observed, suggesting the involvement of the intrinsic mitochondrial pathway of apoptosis for both Noni and Cisplatin in HeLa and SiHa cell lines.

Applying Machine Learning to Text Segmentation for Information Retrieval <=SEP=> We propose a self-supervised word segmentation technique for text segmentation in Chinese information retrieval. This method combines the advantages of traditional dictionary based, character based and mutual information based approaches, while overcoming many of their shortcomings. Experiments on TREC data show this method is promising. Our method is completely language independent and unsupervised, which provides a promising avenue for constructing accurate multi-lingual or cross-lingual information retrieval systems that are flexible and adaptive. We find that although the segmentation accuracy of self-supervised segmentation is not as high as some other segmentation methods, it is enough to give good retrieval performance. It is commonly believed that word segmentation accuracy is monotonically related to retrieval performance in Chinese information retrieval. However, for Chinese, we find that the relationship between segmentation and retrieval performance is in fact nonmonotonic; that is, at around 70% word segmentation accuracy an over-segmentation phenomenon begins to occur which leads to a reduction in information retrieval performance. We demonstrate this effect by presenting an empirical investigation of information retrieval on Chinese TREC data, using a wide variety of word segmentation algorithms with word segmentation accuracies ranging from 44% to 95%, including 70% word segmentation accuracy from our self-supervised word-segmentation approach. It appears that the main reason for the drop in retrieval performance is that correct compounds and collocations are preserved by accurate segmenters, while they are broken up by less accurate (but reasonable) segmenters, to a surprising advantage. This suggests that words themselves might be too broad a notion to conveniently capture the general semantic meaning of Chinese text. Our research suggests machine learning techniques can play an important role in building adaptable information retrieval systems and different evaluation standards for word segmentation should be given to different applications.

Kirigami skins make a simple soft actuator crawl <=SEP=> Bioinspired soft machines made of highly deformable materials are enabling a variety of innovative applications, yet their locomotion typically requires several actuators that are independently activated. We harnessed kirigami principles to significantly enhance the crawling capability of a soft actuator. We designed highly stretchable kirigami surfaces in which mechanical instabilities induce a transformation from flat sheets to 3D-textured surfaces akin to the scaled skin of snakes. First, we showed that this transformation was accompanied by a dramatic change in the frictional properties of the surfaces. Then, we demonstrated that, when wrapped around an extending soft actuator, the buckling-induced directional frictional properties of these surfaces enabled the system to efficiently crawl.

Learning Hand-Eye Coordination for Robotic Grasping with Large-Scale Data Collection <=SEP=> We describe a learning-based approach to hand-eye coordination for robotic grasping from monocular images. To learn hand-eye coordination for grasping, we trained a large convolutional neural network to predict the probability that task-space motion of the gripper will result in successful grasps, using only monocular camera images and independently of camera calibration or the current robot pose. This requires the network to observe the spatial relationship between the gripper and objects in the scene, thus learning hand-eye coordination. We then use this network to servo the gripper in real time to achieve successful grasps. To train our network, we collected over 800,000 grasp attempts over the course of two months, using between 6 and 14 robotic manipulators at any given time, with differences in camera placement and hardware. Our experimental evaluation demonstrates that our method achieves effective real-time control, can successfully grasp novel objects, and corrects mistakes by continuous servoing.

A PRINCIPAL AXIS TRANSFORMATION FOR NON-HERMITIAN MATRICES CARL ECKART AND GALE YOUNG The availability of the principal axis transformation for hermitian <=SEP=> each two nonparallel elements of G cross each other. Obviously the conclusions of the theorem do not hold. The following example will show that the condition that no two elements of the collection G shall have a complementary domain in common is also necessary. In the cartesian plane let M be a circle of radius 1 and center at the origin, and iVa circle of radius 1 and center at the point (5, 5). Let d be a collection which contains each continuum which is the sum of M and a horizontal straight line interval of length 10 whose left-hand end point is on the circle M and which contains no point within M. Let G2 be a collection which contains each continuum which is the sum of N and a vertical straight line interval of length 10 whose upper end point is on the circle N and which contains no point within N. Let G = Gi+G2 . No element of G crosses any other element of G, but uncountably many have a complementary domain in common with some other element of the collection. However, it is evident that no countable subcollection of G covers the set of points each of which is common to two continua of the collection G. I t is not known whether or not the condition that each element of G shall separate some complementary domain of every other one can be omitted.

Visual Descriptors for Dense Tensor Fields in Computational Turbulent Combustion: A Case Study <=SEP=> Simulation and modeling of turbulent flow, and of turbulent reacting flow in particular, involve solving for and analyzing time-dependent and spatially dense tensor quantities, such as turbulent stress tensors. The interactive visual exploration of these tensor quantities can effectively steer the computational modeling of combustion systems. In this article, the authors analyze the challenges in dense symmetric-tensor visualization as applied to turbulent combustion calculation; most notable among these challenges are the dataset size and density. They analyze, together with domain experts, the feasibility of using several established tensor visualization techniques in this application domain. They further examine and propose visual descriptors for volume rendering of the data. Of these novel descriptors, one is a density-gradient descriptor which results in Schlieren-style images, and another one is a classification descriptor inspired by machine-learning techniques. The result is a hybrid visual analysis tool to be utilized in the debugging, benchmarking and verification of models and solutions in turbulent combustion. The authors demonstrate this analysis tool on two example configurations, report feedback from combustion researchers, and summarize the design lessons learned. c © 2016 Society for Imaging Science and Technology. [DOI: 10.2352/J.ImagingSci.Technol.2016.60.1.010404] INTRODUCTION Computational simulation of turbulent combustion for gas turbine design has become increasingly important in the last two decades, due in part to environmental concerns and regulations on toxic emissions. Such modern gas turbine designs feature a variety of mixing fuel compositions and possible flow configurations,1,2 which make non-computational simulations difficult. The focus of the computational research effort in this direction is on the development of computational tools for the modeling and prediction of turbulent combustion flows. Received June 30, 2015; accepted for publication Nov. 4, 2015; published online Dec. 10, 2015. Associate Editor: Song Zhang. 1062-3701/2016/60(1)/010404/11/$25.00 Tensor quantities are common features in these turbulent combustion models. In particular, stress and strain tensors are often correlated to turbulent quantities—which appear unclosed in the mathematical formulation and thus need to be modeled as part of the computational simulation. Visual identification of the characteristics of such tensor quantities can bring significant insights into the computational modeling process. However, these computational tensor fields are very large and spatially dense—a good example of the Big Data revolution across sciences and engineering. Figure 1 shows an example turbulent combustion configuration, featuring a grid size of 106 and 6× 106 particles (shown as spheres); this dataset should be considered in contrast to traditional tensor datasets, which feature grid sizes in the 102 range. At such large scales, typical glyph encodings become cluttered and illegible. Furthermore, combustion experts seldom have an intuitive understanding of the tensor quantities. In this respect, froma tensor visualization perspective, workingwith these datasets poses an array of challenges. Are traditional tensor and flow representations useful in this context? Does increasing the level of complexity or expressiveness of such representations help or hinder? Is interaction speed more important than the benefits gained from complex descriptors? In this article, we address a specific application design problem. In the process of exploring the design space, we also investigate some of the larger visualization questions above, through the opportunity of a case study in the computational-combustion domain. In thiswork,motivated by an ongoing collaborationwith domain experts,3 we investigate the challenges associated with the exploratory visualization of tensor quantities in turbulent combustion simulations. We first provide a characterization of the problem domain, including a data analysis. Through a case study involving five senior combustion researchers, we then iteratively explore the space of tensor visual encodings. We implement and evaluate several J. Imaging Sci. Technol. 010404-1 Jan.-Feb. 2016 Marai et al.: Visual descriptors for dense tensor fields in computational turbulent combustion: a case study Figure 1. One timestep in an example turbulent combustion configuration. The grid size is 106. In this image, 6× 106 particles are shown as spheres. This dataset should be contrasted to traditional tensor datasets, which feature sparse grids in the 102 range. At this scale, typical glyph encodings become cluttered. approaches advocated by the visualization community in an interactive prototype, and we contrast these approaches with the best-of-breed visualization practices in the target domain. Based on domain expert feedback, we then focus our efforts on identifying effective visual descriptors for volume rendering of the combustion tensor data. Our contributions include a novel density-gradient descriptor and the adaptation of a machine-learning classification technique. Next, we evaluate the visual descriptors on two computational-combustion datasets of particular interest, and we show the importance of the proposed approach for debugging the numerical simulation of complex configurations. In an effort to better bridge the gap between the combustion and tensor visualization communities, we describe these tensor field datasets. Last but not least, we contribute a summary of design lessons learned from the study and from the application design process. To the best of our knowledge, this is the first formal, exploratory case study of tensor visualization techniques in the context of very large, high-density turbulent combustion flow. TENSORS IN TURBULENT COMBUSTION MODELING Turbulent Combustion Modeling. A sufficiently accurate, flexible and reliable model can be used for an in silico combustor rig test as a much cheaper alternative to the reallife rig tests employed in combustor design and optimization. In order to achieve such amodel, themethodology should be well tested and proven with lab-scale configurations. Multiple numerical approaches exist for the generation of such computational models of combustion, most notably Direct numerical simulation (DNS), Reynolds-averaged Navier–Stokes (RANS) and Large eddy simulation (LES). DNS, RANS and LES have complementary strengths. However, allmodels begin by describing the compressible reacting flow via a set of partial differential equations (PDEs) that represent the conservation of mass, momentum and energy. These PDEs are a fully coupled set of multi-dimensional non-linear equations and can be posed in a variety of forms depending on the flow conditions (compressibility, scale, flow regime, etc.).4 In this article, we exemplify the visualization of stress/strain tensors, and therefore restrict the presentation to the pertinent subset of these PDEs, namely the momentum transport equation. Stress, Strain and Turbulent Stress Tensors. A tensor is an extension of the concept of a scalar and a vector to higher orders. For example, while a stress vector is the force acting on a given unit surface, a stress tensor is defined as the components of stress vectors acting on each coordinate surface; thus, stress can be described by a symmetric second-order tensor (a matrix). The velocity stress and strain tensor fields aremanifested in the transport of fluid momentum, which is a vector quantity governed by the following conservation equation:

Tooth survival following non-surgical root canal treatment: a systematic review of the literature. <=SEP=> AIMS
To investigate (i) the effect of study characteristics on reported tooth survival after root canal treatment (RCTx) and (ii) the effect of clinical factors on the proportion of root filled teeth surviving after RCTx.


METHODOLOGY
Longitudinal human clinical studies investigating tooth survival after RCTx which were published up to the end of 2007 were identified electronically (MEDLINE and Cochrane database 1966-2007 December, week 4). In addition, four journals (Dental Traumatology, International Endodontic Journal, Journal of Endodontics, Oral Surgery Oral Medicine Oral Pathology Oral Radiology & Endodontics), bibliographies of all relevant articles and review articles were hand searched. Two reviewers (Y-LN, KG) assessed and selected the studies based on specified inclusion criteria and extracted the data onto a pre-designed proforma, independently. The criteria were as follows: (i) clinical study on RCTx; (ii) stratified analysis of primary and secondary RCTx available; (iii) sample size given and larger than 10; (iv) at least 6-month postoperative review; (v) success based on survival of tooth; and (vi) proportion of teeth surviving after treatment given or could be calculated from the raw data. Three strands of evidence or analyses were used to triangulate a consensus view. The reported findings from individual studies, including those excluded for quantitative analysis, were utilized for the intuitive synthesis, which constituted the first strand of evidence. Secondly, the pooled weighted proportion of teeth surviving and thirdly the combined effects of potential prognostic factors were estimated using the fixed and random effects meta-analyses on studies fulfilling all the inclusion criteria.


RESULTS
Of the 31 articles identified, 14 studies published between 1993 and 2007 were included. The majority of studies were retrospective (n = 10) and only four prospective. The pooled percentages of reported tooth survival over 2-3, 4-5 and 8-10 years following RCTx were 86% (95% CI: 75%, 98%), 93% (95% CI: 92%, 94%) and 87% (95% CI: 82%, 92%), respectively. Substantial differences in study characteristics were found to hinder effective direct comparison of findings. Evidence for the effect of prognostic factors on tooth survival was weak. Based on the data available for meta-analyses, four conditions were found to significantly improve tooth survival. In descending order of influence, the conditions increasing observed proportion of survival were as follows: (i) a crown restoration after RCTx; (ii) tooth having both mesial and distal proximal contacts; (iii) tooth not functioning as an abutment for removable or fixed prosthesis; and (iv) tooth type or specifically non-molar teeth. Statistical heterogeneity was substantial in some cases but its source could not be investigated because of insufficient available information.


CONCLUSIONS
The pooled proportion of teeth surviving over 2-10 years following RCTx ranged between 86% and 93%. Four factors (listed above) were identified as significant prognostic factors with concurrence between all three strands of evidence.

100 top-cited scientific papers in limb prosthetics <=SEP=> Research has tremendously contributed to the developments in both practical and fundamental aspects of limb prosthetics. These advancements are reflected in scientific articles, particularly in the most cited papers. This article aimed to identify the 100 top-cited articles in the field of limb prosthetics and to investigate their main characteristics. Articles related to the field of limb prosthetics and published in the Web of Knowledge database of the Institute for Scientific Information (ISI) from the period of 1980 to 2012. The 100 most cited articles in limb prosthetics were selected based on the citation index report. All types of articles except for proceedings and letters were included in the study. The study design and level of evidence were determined using Sackett's initial rules of evidence. The level of evidence was categorized either as a systematic review or meta-analysis, randomized controlled trial, cohort study, case-control study, case series, expert opinion, or design and development. The top cited articles in prosthetics were published from 1980 to 2012 with a citation range of 11 to 90 times since publication. The mean citation rate was 24.43 (SD 16.7) times. Eighty-four percent of the articles were original publications and were most commonly prospective (76%) and case series studies (67%) that used human subjects (96%) providing level 4 evidence. Among the various fields, rehabilitation (47%), orthopedics (29%), and sport sciences (28%) were the most common fields of study. The study established that studies conducted in North America and were written in English had the highest citations. Top cited articles primarily dealt with lower limb prosthetics, specifically, on transtibial and transradial prosthetic limbs. Majority of the articles were experimental studies.

Requirements engineering and the creative process in the video game industry <=SEP=> The software engineering process in video game development is not clearly understood, hindering the development of reliable practices and processes for this field. An investigation of factors leading to success or failure in video game development suggests that many failures can be traced to problems with the transition from preproduction to production. Three examples, drawn from real video games, illustrate specific problems: 1) how to transform documentation from its preproduction form to a form that can be used as a basis for production;, 2) how to identify implied information in preproduction documents; and 3) how to apply domain knowledge without hindering the creative process. We identify 3 levels of implication and show that there is a strong correlation between experience and the ability to identify issues at each level. The accumulated evidence clearly identifies the need to extend traditional requirements engineering techniques to support the creative process in video game development.

Heart-Brain Neurodynamics : The Making of Emotions <=SEP=> As pervasive and vital as they are in human experience, emotions have long remained an enigma to science. This monograph explores recent scientific advances that clarify central controversies in the study of emotion, including the relationship between intellect and emotion, and the historical debate on the source of emotional experience. Particular attention is given to the intriguing body of research illuminating the critical role of ascending input from the body to the brain in the generation and perception of emotions. This discussion culminates in the presentation of a systems-oriented model of emotion in which the brain functions as a complex pattern-matching system, continually processing input from both the external and internal environments. From this perspective it is shown that the heart is a key component of the emotional system, thus providing a physiological basis for the long-acknowledged link between the heart and our emotional life.

An integrated conceptual model for information system security risk management supported by enterprise architecture management <=SEP=> Risk management is today a major steering tool for any organisation wanting to deal with information system (IS) security. However, IS security risk management (ISSRM) remains a difficult process to establish and maintain, mainly in a context of multi-regulations with complex and inter-connected IS. We claim that a connection with enterprise architecture management (EAM) contributes to deal with these issues. A first step towards a better integration of both domains is to define an integrated EAM-ISSRM conceptual model. This paper is about the elaboration and validation of this model. To do so, we improve an existing ISSRM domain model, i.e. a conceptual model depicting the domain of ISSRM, with the concepts of EAM. The validation of the EAM-ISSRM integrated model is then performed with the help of a validation group assessing the utility and usability of the model.

A simple regression method for mapping quantitative trait loci in line crosses using flanking markers <=SEP=> The use of flanking marker methods has proved to be a powerful tool for the mapping of quantitative trait loci (QTL) in the segregating generations derived from crosses between inbred lines. Methods to analyse these data, based on maximum-likelihood, have been developed and provide good estimates of QTL effects in some situations. Maximum-likelihood methods are, however, relatively complex and can be computationally slow. In this paper we develop methods for mapping QTL based on multiple regression which can be applied using any general statistical package. We use the example of mapping in an F2 population and show that these regression methods produce very similar results to those obtained using maximum likelihood. The relative simplicity of the regression methods means that models with more than a single QTL can be explored and we give examples of two linked loci and of two interacting loci. Other models, for example with more than two QTL, with environmental fixed effects, with between family variance or for threshold traits, could be fitted in a similar way. The ease, speed of application and generality of regression methods for flanking marker analyses, and the good estimates they obtain, suggest that they should provide the method of choice for the analysis of QTL mapping data from inbred line crosses.

Comparative analysis of big data transfer protocols in an international high-speed network <=SEP=> Large-scale scientific installations generate voluminous amounts of data (or big data) every day. These data often need to be transferred using high-speed links (typically with 10 Gb/s or more link capacity) to researchers located around the globe for storage and analysis. Efficiently transferring big data across countries or continents requires specialized big data transfer protocols. Several big data transfer protocols have been proposed in the literature, however, a comparative analysis of these protocols over a long distance international network is lacking in the literature. We present a comparative performance and fairness study of three open-source big data transfer protocols, namely, GridFTP, FDT, and UDT, using a 10 Gb/s high-speed link between New Zealand and Sweden. We find that there is limited performance difference between GridFTP and FDT. GridFTP is stable in terms of handling file system and TCP socket buffer. UDT has an implementation issue that limits its performance. FDT has issues with small buffer size limiting its performance, however, this problem is overcome by using multiple flows. Our work indicates that faster file systems and larger TCP socket buffers in both the operating system and application are useful in improving data transfer rates.