title: Simulation and visualisation in medical diagnosis: perspectives and computational requirements.

abstract: A color television pickup system and device comprising three sets of strip electrodes capable of being energized to establish voltage patterns on the photoelectric surface of the device. When the surface is scanned by an electron beam, indexing signals are generated that depend on the voltage of the electrodes. This voltage is changed at the end of each scanning line interval. Optical strip filters aligned with the sets of electrodes in sets of fundamental color components color-separate light from the object being televised, and the signals generated by the photoelectric surface can be related to the light colors by the index signals. The output signals are selectively filtered, delayed, and combined to separate image signals from indexing signals, to produce luminance and chrominance signals, and to separate signals for each color.


title: Fuzzy adaptive genetic algorithm for multi-objective assembly line balancing problems

abstract: This paper aims at multi-objective straight and U-shaped assembly line balancing problems with the fuzzy task processing times. The problems are referred to herein as f-SALBP and f-SULBP and the objectives that are considered to be satisfied are: (a) minimizing the numbers of stations, (b) maximizing the fuzzy line efficiency, (c) minimizing the fuzzy idleness percentage, and (d) minimizing the fuzzy smoothness index. In fact, the f-SALBP and f-SULBP are SALBP and SULBP generalization in fuzzy circumstance, respectively. Initially, the two problems are formulated and due to the uncertainty, variability and imprecision that often occurred in real-world production systems, the processing time of tasks are supposed as triangular fuzzy numbers. Then, to solve the problem, a hybrid multi-objective genetic algorithm is proposed. A One-Fifth Success Rule (OFSR) is deployed for the selection and mutation operators to improve the genetic algorithm's performance. The results in the genetic algorithm are being controlled in convergence and diversity simultaneously by means of controlling the selective pressure (SP) and mutation rate. Likewise, a fuzzy controller to SP is employed for the OFSR toward a better implementation of the genetic algorithm. In addition, the Taguchi design of experiments is used for parameter control and calibration. Finally, the numerical examples are presented to compare the performance of the proposed method with the existing ones. The results show significantly better performance for the proposed algorithm.


title: Modularity from fluctuations in random graphs and complex networks

abstract: Statistical, mathematical, and model-based analysis of complex networks have recently uncovered interesting unifying patterns in networks from seemingly unrelated disciplines [1-5]. In spite of these advances, many properties of complex networks remain elusive, a prominent one being modularity [6,7]. For example, it is a matter of common experience that social networks have communities of highly interconnected nodes that are poorly connected to nodes in other communities. Such modular structures have been reported not only in social networks [6-8], but also in biochemical networks [9], food webs [10], and the Internet [11]. It is widely believed that the modular structure of complex networks plays a critical role in their functionality [9]. There is therefore a clear need to develop algorithms to identify modules accurately [6,7,11-13]. ::: ::: More fundamentally, the mechanisms by which modularity emerges in complex networks are not well understood. In biological networks—both biochemical and ecological—researchers have suggested that modularity increases robustness, flexibility, and stability [9,10]. Similarly, in engineered networks, it has been suggested that modularity is effective to achieve adaptability in rapidly changing environments [14]. It may therefore seem that evolutionary pressures make networks modular, implying that any successful model of complex networks should take into account external factors that enhance modularity. Recently, however, Sole and Fernandez have pointed out that models without any external pressure are able to give rise to modular networks [15]. ::: ::: In this paper, we show that Erdos-Renyi (ER) random graphs, in which any pair of nodes is connected with probability p [16], have a high modularity. We show numerically and analytically that this high modularity is due to fluctuations in the establishment of links, which are magnified by the large number of ways in which a network can be partitioned into modules. Furthermore, we show that one obtains similar results when considering scale-free networks [2]. We conclude by discussing how these results should be taken into consideration to define statistically significant modularity in complex networks. ::: ::: ::: Following the first quantitative definition of modularity [7,12], several groups have proposed heuristic algorithms to detect modules in complex networks. For a given partition of the nodes of a network into modules, the modularity ℳ of this partition is defined as [7] ::: ::: ::: ℳ≡Σs=1r[lsL−(ds2L)2], ::: ::: (1) ::: ::: ::: where r is the number of modules, L is the number of links in the network, ls is the number of links between nodes in module s, and ds is the sum of the degrees of the nodes in module s. This definition of modularity implies that ℳ≤1 and that ℳ=0 for a random partition of the nodes [7]. We define the modularity M of a network as the largest modularity of all possible partitions of the network M =max{ℳ}. ::: ::: ::: ::: The problem of finding the modularity of a network with S nodes is therefore analogous to the standard statistical mechanics problem of finding the ground-state energy of the Hamiltonian ℋ=−Lℳ. Specifically, one can map the network into a spin system by defining the variables si ∈{1,2,…,S} as the module to which node i belongs and the couplings Jij as being 1 if nodes i and j are connected in the network and 0 otherwise. Then, from Eq. (1), one can demonstrate that ::: ::: ::: ℋ=−Σi,jSJij2δsisj+Σi,j,k,lS[JijJkl16L(δsisjsksl+2δsisjsk+δsisk)]. ::: ::: (2) ::: ::: ::: This Hamiltonian corresponds to an S-state Potts model with both ferromagnetic and anti-ferromagnetic terms, and two-, three-, and four-spin interactions. Therefore, it seems difficult to apply methods used in problems that are similar but formally simpler, like the graph coloring problem [17]. Rather, we propose here a heuristic estimation of the modularity for a number of interesting graph models, namely low-dimensional regular lattices, ER random graphs [16] and scale-free networks [2].


title: Understanding usability in mobile commerce

abstract: Ramifications for wireless design: 'e' ≠ 'm'.


title: High-speed pattern projection for three-dimensional shape measurement using laser speckles

abstract: We propose a high-speed projection system that is able to project statistical speckle patterns at a rate of 500Hz. Its purpose is to generate structured light for a real-time photogrammetry stereo vision setup. As conventional digital light projector (DLP) projection setups are limited in their maximum projection rate to 250Hz for gray-value patterns, stripe projection systems are usually applied for real-time three-dimensional (3D) measurements. However, these techniques can only be used on steady surfaces as phase unwrapping has to be done. In contrast, the proposed setup is able to measure the shape of multiple spatially separated objects at once. We compare the speckle setup with a system using a DLP projector and with other fast 3D shape measurement setups, like the widely used stripe projection methods, qualitatively and quantitatively.


Automated Fact-Checking of Claims in Argumentative Parliamentary Debates


title: Kinematics and constraint analysis of tractor-trailer mobile robot

abstract: Tractor-trailer mobile robot is a complicated system composed of a tractor and multiple trailers. Its path planning is complicated accordingly. The kinematics of the system is analyzed in this paper on the base of band-path concept. The transient parameters in the dynamic motion presented in this paper make the collision avoidance and path seeking easier. It also provides a kinematics model for the simulation.


title: Double-ridged Horn Antenna with Sinusoidal Ridge Profile

abstract: FDTD numerical study compared to the results of measurement is reported for double-ridged horn antenna with sinusoidal profile of the ridge. Different transitions from coaxial to double-ridged waveguide were considered on the preliminary step of the study. Next, a suitable configuration for feeding the ridges of antenna was chosen. The sinusoidal ridge taper is described in the next part of the paper. Finally, the simulations results of complete antenna are presented. Theoretical characteristics of reflection and antenna patterns are compared to the results of measurements showing acceptable accordance.


title: Ferroelectric thin films for micro-sensors and actuators: a review

abstract: This paper reviews deposition, integration, and device fabrication of ferroelectric PbZrxTi1-xO3 (PZT) films for applications in microelectromechanical systems. As examples, a piezoelectric ultrasonic micromotor and pyroelectric infrared detector array are presented. A summary of the published data on the piezoelectric properties of PZT thin films is given. The figures of merit for various applications are discussed. Some considerations and results on operation, reliability, and depolarization of PZT thin films are presented.


title: Deep Discrete Flow

abstract: Motivated by the success of deep learning techniques in matching problems, we present a method for learning context-aware features for solving optical flow using discrete optimization. Towards this goal, we present an efficient way of training a context network with a large receptive field size on top of a local network using dilated convolutions on patches. We perform feature matching by comparing each pixel in the reference image to every pixel in the target image, utilizing fast GPU matrix multiplication. The matching cost volume from the network’s output forms the data term for discrete MAP inference in a pairwise Markov random field. We provide an extensive empirical investigation of network architectures and model parameters. At the time of submission, our method ranks second on the challenging MPI Sintel test set.


title: Current Methods for Detecting Antibodies against Erythropoietin and Other Recombinant Proteins

abstract: Recombinant DNA technology has revolutionized the production and use of a number of therapeutic proteins, including cytokines and cellular growth factors. These proteins have similar or identical biologic activities as their natural counterparts and are particularly useful for treating patients who


title: A Service-Oriented Grid Computing Platform and Its Framework

abstract: Grid computing provides a robust paradigm to aggregate disparate resources in a secure and controlled environment. Grid architectures require an underpinning Quality of Service (QoS) support in order to manage complex data and computation intensive applications. However, QoS guarantees in the Grid context have not been given the attention they merit. In order to enhance the functionality offered by computational Grids, we overlay the Grid framework with an advanced QoS architecture, called G-QoSM. The G-QoSM framework provides a new service-oriented QoS management model that leverages the Open Grid Service Architecture (OGSA) and has a number of interesting features: (1) Grid service discovery based on QoS attributes, (2) policy-based admission control for advance reservation support, and (3) Grid service execution with QoS constraints. This paper discusses the different components of the G-QoSM framework, in the context of OGSA architectures.


title: Brand management to protect brand equity: A conceptual model

abstract: Corporate and product brands are increasingly accepted as valuable intangible assets of organisations, evidence of which is apparent in the reported financial value that strong brands fetch when traded in the mergers and acquisitions markets. However, while much attention is paid to conceptualising brand equity, less is paid to how brands should be managed and delivered in order to create and safeguard brand equity. In this article we develop a conceptual model of corporate brand management for creating and safeguarding brand equity. We argue that while legal protection of the brand is important, by itself it is insufficient to protect brand equity in the long term. We suggest that brand management ought to play an important role in safeguarding brand equity and propose a three-stage conceptual model for building and sustaining brand equity comprising: (1) adopting a brand- orientation mindset, (2) developing internal branding capabilities, and (3) consistent delivery of the brand. We put forward propositions, which, taken together, form a theory of brand management for building and safeguarding brand equity. We illustrate the theory using 14 cases of award-winning service companies. Their use serves as a demonstration of how our model applies to brand management practice.


title: Experimental Analysis of a UAV-Based Wireless Power Transfer Localization System

abstract: Sensors deployed in remote locations provide unprecedented amounts of data, but powering these sensors over long periods remains a challenge. In this paper, we develop and present a UAV-based wireless power transfer system. We discuss design considerations and present our system that allows a UAV to fly to remote locations to charge hard to access sensors. We analyze the impact of different materials on the wireless power transfer system. Since GPS does not provide sufficient accuracy, we develop and experimentally characterize a relative localization algorithm based on sensing the magnetic field of the power transfer system and optical flow that allows the UAV to localize the sensor with an average error of 15 cm to enable the transfer of on average 4.2 W. These results overcome some of the practical challenges associated with wirelessly charging sensors with a UAV and show that UAVs with wireless power transfer systems can greatly extend the life of remotely deployed sensors.


title: Strain rate and anisotropy effects on the tensile failure characteristics of human skin.

abstract: Abstract The anisotropic failure characteristics of human skin are relatively unknown at strain rates typical in impact biomechanics. This study reports the results of an experimental protocol to quantify the effect of dynamic strain rates and the effect of sample orientation with respect to the Langer lines. Uniaxial tensile tests were carried out at three strain rates (0.06 s −1 , 53 s −1 , and 167 s −1 ) on 33 test samples excised from the back of a fresh cadaver. The mean ultimate tensile stress , mean elastic modulus and mean strain energy increased with increasing strain rates. While the stretch ratio at ultimate tensile stress was not affected by the strain rate, it was influenced by the orientation of the samples (parallel and perpendicular to the Langer lines. The orientation of the sample also had a strong influence on the ultimate tensile stress, with a mean value of 28.0±5.7 MPa for parallel samples, and 15.6±5.2 MPa for perpendicular samples, and on the elastic modulus, with corresponding mean values of 160.8 MPa±53.2 MPa and 70.6 MPa±59.5 MPa. The study also pointed out the difficulties in controlling the effective applied strain rate in dynamic characterization of soft tissue and the resulting abnormal stress–strain relationships. Finally, data collected in this study can be used to develop constitutive models where high loading rates are of primary interest.


title: Control of pneumatic artificial muscle for bicep configuration using IBC

abstract: This paper presents a control algorithm for pneumatic artificial muscles on bicep configuration. Due to the characteristics such as lower power to weight ratios, high strength and lightweight and easiness of employment, pneumatic artificial muscles have become more attractive actuators for robotics applications. The dynamics equations for bicep configuration were derived with the help of single muscle analysis. Nonlinear dynamic equation was linearized in order to derive the state space model. To obtain the desired tracking performance, inversion based control (IBC) concept was employed. Results show the effectiveness of the proposed methodology.


title: What is the Range of Surface Reconstructions from a

abstract: We propose a generalized equation to represent a continuum of surface reconstruction solutions of a given non-integrable gradient field. We show that common approaches such as Poisson solver and Frankot-Chellappa algorithm are special cases of this generalized equation. For a N x N pixel grid, the subspace of all integrable gradient fields is of dimension N 2 - 1. Our framework can be applied to derive a range of meaningful surface reconstructions from this high dimensional space. The key observation is that the range of solutions is related to the degree of anisotropy in applying weights to the gradients in the integration process. While common approaches use isotropic weights, we show that by using a progression of spatially varying anisotropic weights, we can achieve significant improvement in reconstructions. We propose (a) α-surfaces using binary weights, where the parameter a allows trade off between smoothness and robustness, (b) M-estimators and edge preserving regularization using continuous weights and (c) Diffusion using affine transformation of gradients. We provide results on photometric stereo, compare with previous approaches and show that anisotropic treatment discounts noise while recovering salient features in reconstructions.


title: Analyzing the drivers of end-of-life tire management using interpretive structural modeling (ISM)

abstract: Due to industrialization and globalization, automotive sectors in both professional and societal applications have increased manufacturing and have resulted in higher production of virgin tires. These hikes in virgin tire production subsequently results in more end-of-life (EOL) tires, as well as lower quality, shorter tire lifespan, and a restricted availability of new model tires. Many developed nations have started to address EOL tire management issues through various strategies and codes of conduct, but because the environment is a global concern shared both by developed and developing nations, this study examines the issue of EOL tire management in India, a highly populated developing country. This paper proposes a framework to analyze the motivating factors of EOL tire management; it is validated in the Indian scenario with the assistance of a multi-criteria decision-making (MCDM) approach. Existing literatures are limited to the study of recycling and remanufacturing techniques. This study also provides the interrelationship between drivers and their respective influence with sound managerial implications. Finally, the paper concludes with the most influential driver of EOL tire management among all common drivers. We examine its limitations, and we shed light on the prospects of greater sustainability in EOL tire management in the future.


title: Realtime Edge-Based Visual Odometry for a Monocular Camera

abstract: In this work we present a novel algorithm for realtime visual odometry for a monocular camera. The main idea is to develop an approach between classical feature-based visual odometry systems and modern direct dense/semi-dense methods, trying to benefit from the best attributes of both. Similar to feature-based systems, we extract information from the images, instead of working with raw image intensities as direct methods. In particular, the information extracted are the edges present in the image, while the rest of the algorithm is designed to take advantage of the structural information provided when pixels are treated as edges. Edge extraction is an efficient and higly parallelizable operation. The edge depth information extracted is dense enough to allow acceptable surface fitting, similar to modern semi-dense methods. This is a valuable attribute that feature-based odometry lacks. Experimental results show that the proposed method has similar drift than state of the art feature-based and direct methods, and is a simple algorithm that runs at realtime and can be parallelized. Finally, we have also developed an inertial aided version that successfully stabilizes an unmanned air vehicle in complex indoor environments using only a frontal camera, while running the complete solution in the embedded hardware on board the vehicle.


title: BumbleBee: a refactoring environment for spreadsheet formulas

abstract: Spreadsheets are widely used in industry. It is estimated that end-user programmers outnumber regular programmers by a factor of 5. However, spreadsheets are error-prone: several reports exist of companies that have lost big sums of money due to spreadsheet errors. In previous work, spreadsheet smells have proven to be the cause of some of these errors. To that end, we have developed a tool that can apply refactorings to spreadsheet formulas, implementing our previous work on spreadsheet refactoring, which showed that spreadsheet formula smells are very common and that refactorings for them are widely applicable and that refactoring them with a tool is both quicker and less error-prone. Our new tool Bumblebee is able to execute refactorings originating from both these papers, by means of an extensible syntax, and can furthermore apply refactorings on entire groups of formulas, thus improving upon the existing tool RefBook. Finally, BumbleBee can also execute transformations other than refactorings.


title: Pixel Modeling Using Histograms Based on Fuzzy Partitions for Dynamic Background Subtraction

abstract: We propose a novel pixel-modeling approach for background subtraction using histograms based on strong uniform fuzzy partitions. In the proposed method, the temporal distribution of pixel values is represented by a histogram based on a triangular partition. The threshold for background segmentation is set adaptively according to the shape of the histogram. Histogram accumulation is controlled adaptively by a fuzzy controller under a supervised learning framework. Benefiting from the adaptive scheme, with no parameter tuning, the proposed algorithm functions well across a wide spectrum of challenging environments. The performance of the proposed method is evaluated against more than 20 state-of-the-art methods in complex outdoor environments, particularly in those consisting of highly dynamic backgrounds and camouflaged foregrounds. Experimental results confirm that the proposed method performs effectively in terms of both the true positive rate and the noise suppression ability. Further, it outperforms other state-of-the-art methods by a significant margin.


title: Beery-Buktenica Developmental Test of Visual-Motor Integration (Beery-VMI): lessons from exploration of cultural variations in visual-motor integration performance of preschoolers

abstract: Background ::: Visual-motor integration (VMI) is important in children's development because it is associated with the performance of many functional skills. Deficits in VMI have been linked to difficulties in academic performance and functional tasks. Clinical assessment experience of occupational therapists in Singapore suggested that there is a potential difference between the VMI performance of Singaporean and American children. Cross-cultural studies also implied that culture has an influence on a child's VMI performance, as it shapes the activities that a child participates in. The purpose of this study was to (1) explore if there was a difference between the VMI performance of Singaporean and American preschoolers, and (2) determine if there were ethnic differences in the VMI performance of Singaporean preschoolers. ::: ::: Methods ::: The Beery-VMI, which was standardized in America, is commonly used by occupational therapists in Singapore to assess the VMI ability of children. We administered the Beery-VMI (fifth edition) full form test (excluding the supplemental tests) to 385 preschoolers (mean age = 63.3 months) from randomly selected schools in Singapore. We compared the scores of Singaporean preschoolers with those of the American standardization norms using the one-sample t-test. Scores of different ethnic groups among the Singapore population were also compared using a one-way anova, followed by the Bonferroni post-hoc test. ::: ::: Results ::: Singaporean preschoolers and the standardization sample of American children performed significantly differently in all age groups (P < 0.05). Among the Singapore population, the scores were also significantly different (P < 0.05) between the (i) Chinese and Malay and (ii) Chinese and Indians ethnic groups. ::: ::: Conclusion ::: Preschoolers from different cultural and ethnic groups had different VMI performance. Certain cultural beliefs and practices may affect VMI performance. Clinicians should exercise caution when using an assessment in communities and cultures outside the ones on which it was standardized.


title: Playing with prejudice: The prevalence and consequences of racial stereotypes in video games.

abstract: A content analysis of top-selling video game magazines (Study 1) and of 149 video game covers (Study 2) demonstrated the commonality of overt racial stereotyping. Both studies revealed that minority females are virtually absent in game representations. Study 1 revealed that, in video game magazines, minority males, underrepresented generally, were more likely to be portrayed as athletes or as aggressive, and less likely to be depicted in military combat or using technology, than White males. Study 2 also showed evidence of the “dangerous” minority male stereotype in video game covers. Again, underrepresented overall, minority males were overrepresented as thugs, using extreme guns, and also as athletes. Study 3, an experiment, exposed players to both violent and nonviolent games with both White and Black characters. Participants were faster at classifying violent stimuli following games with Black characters and at classifying nonviolent stimuli following games with White characters, indicating that image...


title: An Evaluation Framework and Instruction Set Architecture for Ion-Trap Based Quantum Micro-Architectures

abstract: The theoretical study of quantum computation has yielded efficient algorithms for some traditionally hard problems. Correspondingly, experimental work on the underlying physical implementation technology has progressed steadily. However, almost no work has yet been done which explores the architecture design space of large scale quantum computing systems. In this paper, we present a set of tools that enable the quantitative evaluation of architectures for quantum computers. The infrastructure we created comprises a complete compilation and simulation system for computers containing thousands of quantum bits. We begin by compiling complete algorithms into a quantum instruction set. This ISA enables the simple manipulation of quantum state. Another tool we developed automatically transforms quantum software into an equivalent, fault-tolerant version required to operate on real quantum devices. Next, our infrastructure transforms the ISA into a set of low-level micro architecture specific control operations. In the future, these operations can be used to directly control a quantum computer. For now, our simulation framework quickly uses them to determine the reliability of the application for the target micro architecture. Finally, we propose a simple, regular architecture for ion-trap based quantum computers. Using our software infrastructure, we evaluate the design trade offs of this micro architecture.


title: Stay Cool! Understanding Thermal Attacks on Mobile-based User Authentication

abstract: PINs and patterns remain among the most widely used knowledge-based authentication schemes. As thermal cameras become ubiquitous and affordable, we foresee a new form of threat to user privacy on mobile devices. Thermal cameras allow performing thermal attacks, where heat traces, resulting from authentication, can be used to reconstruct passwords. In this work we investigate in details the viability of exploiting thermal imaging to infer PINs and patterns on mobile devices. We present a study (N=18) where we evaluated how properties of PINs and patterns influence their thermal attacks resistance. We found that thermal attacks are indeed viable on mobile devices; overlapping patterns significantly decrease successful thermal attack rate from 100% to 16.67%, while PINs remain vulnerable (>72% success rate) even with duplicate digits. We conclude by recommendations for users and designers of authentication schemes on how to resist thermal attacks.


title: Mitigating IoT security threats with a trusted Network element

abstract: Securing the growing amount of IoT devices is a challenge for both the end-users bringing IoT devices into their homes, as well as the corporates and industries exposing these devices into the Internet as part of their service or operations. The exposure of these devices, often poorly configured and secured, offers malicious actors an easy access to the private information of their users, or potential to utilize the devices in further activities, e.g., attacks on other devices via Distributed Denial of Service. This paper discusses the current security challenges of IoT devices and proposes a solution to secure these devices via a trusted Network Edge Device. NED offloads the security countermeasures of the individual devices into the trusted network elements. The major benefit of this approach is that the system can protect the IoT devices with user-defined policies, which can be applied to all devices regardless of the constraints of computing resources in the IoT tags. Additional benefit is the possibility to manage the countermeasures of multiple IoT devices/gateways at once, via a shared interface, thus largely avoiding the per-device maintenance operations.


title: Evaluation methods and decision theory for classification of streaming data with temporal dependence

abstract: Predictive modeling on data streams plays an important role in modern data analysis, where data arrives continuously and needs to be mined in real time. In the stream setting the data distribution is often evolving over time, and models that update themselves during operation are becoming the state-of-the-art. This paper formalizes a learning and evaluation scheme of such predictive models. We theoretically analyze evaluation of classifiers on streaming data with temporal dependence. Our findings suggest that the commonly accepted data stream classification measures, such as classification accuracy and Kappa statistic, fail to diagnose cases of poor performance when temporal dependence is present, therefore they should not be used as sole performance indicators. Moreover, classification accuracy can be misleading if used as a proxy for evaluating change detectors with datasets that have temporal dependence. We formulate the decision theory for streaming data classification with temporal dependence and develop a new evaluation methodology for data stream classification that takes temporal dependence into account. We propose a combined measure for classification performance, that takes into account temporal dependence, and we recommend using it as the main performance measure in classification of streaming data.


title: Mathematical modeling and vertical flight control of a tilt-wing UAV

abstract: This paper presents a mathematical model and vertical flight control algorithms for a new tilt-wing unmanned aerial vehicle (UAV). The vehicle is capable of vertical take-off and landing (VTOL). Due to its tilt-wing structure, it can also fly horizontally. The mathematical model of the vehicle is obtained using Newton-Euler formulation. A gravity compensated PID controller is designed for altitude control, and three PID controllers are designed for attitude stabilization of the vehicle. Performances of these controllers are found to be quite satisfactory as demonstrated by indoor and outdoor flight experiments.


title: Online sequential extreme learning machine with kernels for nonstationary time series prediction

abstract: In this paper, an online sequential extreme learning machine with kernels (OS-ELMK) has been proposed for nonstationary time series prediction. An online sequential learning algorithm, which can learn samples one-by-one or chunk-by-chunk, is developed for extreme learning machine with kernels. A limited memory prediction strategy based on the proposed OS-ELMK is designed to model the nonstationary time series. Performance comparisons of OS-ELMK with other existing algorithms are presented using artificial and real life nonstationary time series data. The results show that the proposed OS-ELMK produces similar or better accuracies with at least an order-of-magnitude reduction in the learning time.


title: Instance-Based matching of large ontologies using locality-sensitive hashing

abstract: In this paper, we describe a mechanism for ontology alignment using instance based matching of types (or classes). Instance-based matching is known to be a useful technique for matching ontologies that have different names and different structures. A key problem in instance matching of types, however, is scaling the matching algorithm to (a) handle types with a large number of instances, and (b) efficiently match a large number of type pairs. We propose the use of state-of-the art locality-sensitive hashing (LSH) techniques to vastly improve the scalability of instance matching across multiple types. We show the feasibility of our approach with DBpedia and Freebase, two different type systems with hundreds and thousands of types, respectively. We describe how these techniques can be used to estimate containment or equivalence relations between two type systems, and we compare two different LSH techniques for computing instance similarity.


title: SENSE: Sensitivity encoding for fast MRI

abstract: New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementary to Fourier preparation by linear field gradients. Thus, by using multiple receiver coils in parallel scan time in Fourier imaging can be considerably reduced. The problem of image reconstruction from sensitivity encoded data is formulated in a general fashion and solved for arbitrary coil configurations and k-space sampling patterns. Special attention is given to the currently most practical case, namely, sampling a common Cartesian grid with reduced density. For this case the feasibility of the proposed methods was verified both in vitro and in vivo. Scan time was reduced to one-half using a two-coil array in brain imaging. With an array of five coils double-oblique heart images were obtained in one-third of conventional scan time. Magn Reson Med 42:952-962, 1999.


title: Colored Maximum Variance Unfolding

abstract: Maximum variance unfolding (MVU) is an effective heuristic for dimensionality reduction. It produces a low-dimensional representation of the data by maximizing the variance of their embeddings while preserving the local distances of the original data. We show that MVU also optimizes a statistical dependence measure which aims to retain the identity of individual observations under the distance-preserving constraints. This general view allows us to design "colored" variants of MVU, which produce low-dimensional representations for a given task, e.g. subject to class labels or other side information.


title: Turret: A Platform for Automated Attack Finding in Unmodified Distributed System Implementations

abstract: Security and performance are critical goals for distributed systems. The increased design complexity, incomplete expertise of developers, and limited functionality of existing testing tools often result in bugs and vulnerabilities that prevent implementations from achieving their design goals in practice. Many of these bugs, vulnerabilities, and misconfigurations manifest after the code has already been deployed making the debugging process difficult and costly. In this paper, we present Turret, a platform for automatically finding performance attacks in unmodified implementations of distributed systems. Turret does not require the user to provide any information about vulnerabilities and runs the implementation in the same operating system setup as the deployment, with an emulated network. Turret uses a new attack finding algorithm and several optimizations that allow it to find attacks in a matter of minutes. We ran Turret on 5 different distributed system implementations specifically designed to tolerate insider attacks, and found 30 performance attacks, 24 of which were not previously reported to the best of our knowledge.


title: [Poor school performance: an updated review].

abstract: This study aims to develop a comprehensive review on the issue of poor school performance for professionals in both health and education areas. It discusses current aspects of education, learning and the main conditions involved in underachievement. It also presents updated data on key aspects of neurobiology, epidemiology, etiology, clinical presentation, comorbidities and diagnosis, early intervention and treatment of the major pathologies comprised. It is a comprehensive, non-systematic literature review on learning, school performance, learning disorders (dyslexia, dyscalculia and dysgraphia), attention deficit / hyperactivity disorder (ADHD) and developmental coordination disorder (DCD). Poor school performance is a frequent problem faced by our children, causing serious emotional, social and economic issues. An updated view of the subject facilitates clinical reasoning, accurate diagnosis and appropriate treatment.


title: Density estimation for out-of-range events on personal mobile devices

abstract: Over the years, personal mobile devices have obtained increasing capabilities to concurrently connect to surrounding networks and nearby other devices. Good knowledge on the dynamics in the availability of these heterogeneous entities constitutes essential input for various data communication problems, ranging from the adaptation of applications on mobile devices to multi-homed situations, to the optimization of routing protocols for delay tolerant networks. In this paper, we focus on a method for the prediction in time of the loss in visibility of currently in-range network entities, as observed on a personal mobile device. We are interested in estimating the full probability density function of the time of these out-of-range events, as this allows us to ask arbitrary questions such as: what is the probability of losing connection X in the next Y minutes? To do so, we model the mobility of the user by applying kernel density estimation on previously observed mobility traces collected during a user experiment we ran with 12 participants in a six week period, logging cellular, 802.11 wireless LAN, Bluetooth, and various other events on the participant's mobile device.


title: The SLAM project: debugging system software via static analysis

abstract: The goal of the S LAM project is to check whether or not a program obeys "API usage rules" that specify what it means to be a good client of an API. The S LAM toolkit statically analyzes a C program to determine whether or not it violates given usage rules. The toolkit has two unique aspects: it does not require the programmer to annotate the source program (invariants are inferred); it minimizes noise (false error messages) through a process known as "counterexample-driven refinement". S LAM exploits and extends results from program analysis, model checking and automated deduction. We have successfully applied the S LAM toolkit to Windows XP device drivers, to both validate behavior and find defects in their usage of kernel APIs.


title: The economic effects of the 1918 influenza epidemic. No. 3791. Centre for Economic Policy Research

abstract: The 1918-19 influenza epidemic killed at least 40 million people worldwide and 675,000 people in the United States, far exceeding the combat deaths experienced by the US in the two World Wars, Korea, and Vietnam combined. Besides its extraordinary virulence, the 1918-19 epidemic was also unique in that a disproportionate number of its victims were men and women ages 15 and 44, giving the age profile of mortality a distinct ‘W’ shape rather than the customary ‘U’ shape, and leading to extremely high death rates in the prime working ages. We examine the impact of this exogenous shock on subsequent economic growth using data on US states for the 1919-30 period. Controlling for numerous factors including initial income, density, urbanization, human capital, climate, the sectoral composition of output, geography, and the legacy of slavery, the results indicate a large and robust positive effect of the influenza epidemic on per capita income growth across states during the 1920s.


title: A novel continuum-style robot with multilayer compliant modules

abstract: This paper introduces a novel continuum-style robot that integrates multiple layers of compliant modules. Its essential features lie in that its bending is not based on natural compliance of a continuous backbone element or soft skeletal elements but instead is based on the compliance of each structured planar module. This structure provides several important advantages. First, it demonstrates a large linear bending motion, whilst avoiding joint friction. Second, its contraction and bending motion are decoupled. Third, it possesses ideal back-drivability and a low hysteresis. We further provide an analytical method to study the compliance characteristics of the planar module and derive the statics and kinematics of the robot. The paper provides an overview of experiments validating the design and analysis.


title: The effects of N-acetylcysteine on spermatogenesis and degree of testicular germ cell apoptosis in an experimental model of varicocele in rats

abstract: Introduction ::: The mechanism by which varicocele interferes in spermatogenesis has not been clearly defined. Germ cell apoptosis and oxidative stress appear to be involved in this process and the use of antioxidants has been proposed to counteract upon these effects. The present study evaluated the effects of N-acetylcysteine (NAC) on spermatogenesis and germ cell apoptosis in an experimental model of varicocele in rats.


title: Occupancy grid map-based extended object tracking

abstract: Robust tracking of extended objects plays a major role in research on highly automated driving applications and advanced driver assistance systems. This paper proposes a new approach to estimate the extension of dynamic objects based on object-local occupancy grid maps. This enables estimating free-formed object shapes while being robust against errors coming from, e.g., incorrect segmentation or association. Its benefit is shown based on 4-layer laser scanner sensor data and is evaluated against a ground truth based on a D-GPS system fused with a highly accurate IMU.


title: Using Multi-task and Transfer Learning to Solve Working Memory Tasks

abstract: We propose a new architecture called Memory-Augmented Encoder-Solver (MAES) that enables transfer learning to solve complex working memory tasks adapted from cognitive psychology. It uses dual recurrent neural network controllers, inside the encoder and solver, respectively, that interface with a shared memory module and is completely differentiable. We study different types of encoders in a systematic manner and demonstrate a unique advantage of multi-task learning in obtaining the best possible encoder. We show by extensive experimentation that the trained MAES models achieve task-size generalization, i.e., they are capable of handling sequential inputs 50 times longer than seen during training, with appropriately large memory modules. We demonstrate that the performance achieved by MAES far outperforms existing and well-known models such as the LSTM, NTM and DNC on the entire suite of tasks.


title: Interpreting Adversarial Robustness: A View from Decision Surface in Input Space

abstract: One popular hypothesis of neural network generalization is that the flat local minima of loss surface in parameter space leads to good generalization. However, we demonstrate that loss surface in parameter space has no obvious relationship with generalization, especially under adversarial settings. Through visualizing decision surfaces in both parameter space and input space, we instead show that the geometry property of decision surface in input space correlates well with the adversarial robustness. We then propose an adversarial robustness indicator, which can evaluate a neural network's intrinsic robustness property without testing its accuracy under adversarial attacks. Guided by it, we further propose our robust training method. Without involving adversarial training, our method could enhance network's intrinsic adversarial robustness against various adversarial attacks.


title: Brain-Computer Interfaces for Multimodal Interaction: A Survey and Principles

abstract: For decades, brain–computer interfaces (BCIs) have been used for restoring the communication and mobility of disabled people through applications such as spellers, web browsers, and wheelchair controls. In parallel to advances in computational intelligence and the production of consumer BCI products, BCIs have recently started to be considered as alternative modalities in human–computer interaction (HCI). One of the popular topics in HCI is multimodal interaction (MMI), which deals with combining multiple modalities in order to provide powerful, flexible, adaptable, and natural interfaces. This article discusses the situation of BCI as a modality within MMI research. State-of-the-art, real-time multimodal BCI applications are surveyed in order to demonstrate how BCI can be helpful as a modality in MMI. It is shown that multimodal use of BCIs can improve error handling, task performance, and user experience and that they can broaden the user spectrum. The techniques for employing BCI in MMI are described, and the experimental and technical challenges with some guidelines to overcome these are shown. Issues in input fusion, output fission, integration architectures, and data collection are covered.


title: Customer Base Analysis : Partial Defection of Behaviorally-Loyal Clients in a Non-Contractual FMCG Retail Setting

abstract: Customer relationship management (CRM) enjoys increasing attention as a countermeasure to switching behaviour of customers. Because foregone profits of (partially) defected customers can be significant, an increase of the retention rate can be very profitable. In this paper we focus on the treatment of a companys most behaviourally loyal customers in a non-contractual setting. We build a model in order to predict partial defection by behaviourally loyal clients using three classification techniques: Logistic regression, automatic relevance determination (ARD) Neural Networks and Random Forests. Focusing on partial attrition of high-frequency shoppers who exhibit a regular visit pattern may overcome the problem of unidentifiability of total defection in non-contractual settings. Classification accuracy (PCC) and area under the receiver operating characteristic curve (AUC) are used to evaluate classifier performance on a test/hold-out sample. Using real-life data from an FMCG retailer, we show that future partial defection can be successfully predicted, i.e. exceeding the benchmark hurdle of the null model. There are no significant differences in terms of performance among alternative classification techniques. Similar to direct-marketing applications we find that past behavioural variables, more specifically RFM variables (recency, frequency, and monetary value) are the best predictors of partial customer defection. This set of variables complements demographic variables confirming findings by other authors about its importance in predicting churn behaviour. Moreover, additional variables (listed in decreasing order of importance) such as the length of customer relationship, mode of payment, buying behaviour across categories, usage of promotions and brand purchase behaviour are shown to be moderately useful to incorporate in attrition models. 2004 Elsevier B.V. All rights reserved.


title: Representation Mixing for TTS Synthesis

abstract: Recent character and phoneme-based parametric TTS systems using deep learning have shown strong performance in natural speech generation. However, the choice between character or phoneme input can create serious limitations for practical deployment, as direct control of pronunciation is crucial in certain cases. We demonstrate a simple method for combining multiple types of linguistic information in a single encoder, named representation mixing, enabling flexible choice between character, phoneme, or mixed representations during inference. Experiments and user studies on a public audiobook corpus show the efficacy of our approach.


title: Advances in the Modelling of Motorcycle Dynamics

abstract: Starting from an existing advanced motorcycle dynamics model, which allows simulation of reasonably general motions and stability, modal and response computations for small perturbations from any trim condition, improvements are described. These concern (a) tyre/road contact geometry, (b) tyre shear force and moment descriptions, as functions of load, slip and camber, (c) tyre relax- ation properties, (d) a new analytic treatment of the monoshock rear suspension mechanism with sample results, (e) parameter values describing a contemporary high performance machine and rider, (f) steady-state equilibrium and power checking and (g) steering control. In particular, the "Magic Formula" motorcycle tyre model is utilised and complete sets of parameter values for contemporary tyres are derived by identification methods. The new model is used for steady turning, stability, design parameter sensitivity and response to road forcing calculations. The results show the predictions of the model to be in general agreement with observations of motorcycle behaviour from the field and they suggest that frame flexibility remains an important design and analysis area, despite improvements in frame designs over recent years. Motorcycle rider parameters have significant influences on the behaviour, with results consistent with a commonly held view, that lightweight riders are more likely to suffer oscillation problems than heavyweight ones.


title: Simplicity and probability in causal explanation

abstract: What makes some explanations better than others? This paper explores the roles of simplicity and probability in evaluating competing causal explanations. Four experiments investigate the hypothesis that simpler explanations are judged both better and more likely to be true. In all experiments, simplicity is quantified as the number of causes invoked in an explanation, with fewer causes corresponding to a simpler explanation. Experiment 1 confirms that all else being equal, both simpler and more probable explanations are preferred. Experiments 2 and 3 examine how explanations are evaluated when simplicity and probability compete. The data suggest that simpler explanations are assigned a higher prior probability, with the consequence that disproportionate probabilistic evidence is required before a complex explanation will be favored over a simpler alternative. Moreover, committing to a simple but unlikely explanation can lead to systematic overestimation of the prevalence of the cause invoked in the simple explanation. Finally, Experiment 4 finds that the preference for simpler explanations can be overcome when probability information unambiguously supports a complex explanation over a simpler alternative. Collectively, these findings suggest that simplicity is used as a basis for evaluating explanations and for assigning prior probabilities when unambiguous probability information is absent. More broadly, evaluating explanations may operate as a mechanism for generating estimates of subjective probability.


title: Grid interfaced solar PV based water pumping using brushless DC motor drive

abstract: This paper proposes a solar photovoltaic (PV) fed water pumping system driven by a brushless DC (BLDC) motor. A promising case of interruption in the water pumping due to the intermittency of PV power generation is resolved by using a power grid as an external power backup. The power is drawn from the grid in case the PV array is unable to meet the required power demand, otherwise the PV array is preferably used. A unidirectional power flow control for the same is developed and realized through a power factor corrected (PFC) boost converter. The proposed system and control enable a consumer to get a full volume of water delivery throughout the day and night regardless of the climatic condition. The utilization of motor-pump at best is thus made possible in addition to an enhanced reliability of the pumping system. The power quality standards required at the utility grid are met by the developed control. The MATLAB/Simulink based simulations and the performance analysis are carried out to demonstrate the applicability of the system.


title: High-Performance Hardware Architectures for Galois Counter Mode

abstract: Various high-performance hardware architectures for Galois counter mode (GCM) in conjunction with various advanced encryption standard (AES) circuits and multiplier-adders are proposed. A total of 17 GCM-AES circuits were synthesized by using a 130-nm CMOS standard cell library, and the trade-offs between speed and hardware resources were evaluated. Our flexible architectures achieved a wide variety of performances from compact (2.56 Gbps with 34.5 Kgates) to high speed (62.6 Gbps with 979.3 Kgates). All of our architectures support key sizes of 128, 192, and 256 bits, while only one previous approach does. Even with variable-length key support, our architecture also achieved the highest hardware efficiency (defined as throughput per gate) among the designs using the same generation of process technology.


title: Content based image retrieval using motif cooccurrence matrix

abstract: We present a new technique for content based image retrieval using motif cooccurrence matrix (MCM). The MCM is derived from the motif transformed image. The whole image is divided into 2×2 pixel grids. Each grid is replaced by a scan motif that minimizes the local gradient while traversing the 2×2 grid forming a motif transformed image. The MCM is then defined as a 3D matrix whose (i,j,k) entry denotes the probability of finding a motif i at a distance k from the motif j in the transformed image. Conceptually, the MCM is quite similar to the color cooccurrence matrix (CCM), however, the retrieval using the MCM is better than the CCM since it captures the third order image statistics in the local neighborhood. Experiments confirm that the use of MCM considerably improves the retrieval performance.


title: A topology for three-stage Solid State Transformer

abstract: Solid State Transformer (SST) is a new type of power transformer based on power electronic converters and high frequency transformers. The SST realizes voltage transformation, galvanic isolation, and power quality improvements in a single device. In the literature, a number of topologies have been introduced for the SST. In this work, employing a modular multilevel converter, a new SST topology is introduced which provides not only high-voltage AC (HVAC), low-voltage AC (LVAC) and low-voltage DC (LVDC) ports, but also high-voltage DC (HVDC) port. Besides, the proposed topology is easily scalable to higher voltage levels.


title: Anti-Caching: A New Approach to Database Management System Architecture

abstract: The traditional wisdom for building disk-based relational database management systems (DBMS) is to organize data in heavily-encoded blocks stored on disk, with a main memory block cache. In order to improve performance given high disk latency, these systems use a multi-threaded architecture with dynamic record-level locking that allows multiple transactions to access the database at the same time. Previous research has shown that this results in substantial overhead for on-line transaction processing (OLTP) applications [15]. ::: ::: The next generation DBMSs seek to overcome these limitations with architecture based on main memory resident data. To overcome the restriction that all data fit in main memory, we propose a new technique, called anti-caching, where cold data is moved to disk in a transactionally-safe manner as the database grows in size. Because data initially resides in memory, an anti-caching architecture reverses the traditional storage hierarchy of disk-based systems. Main memory is now the primary storage device. ::: ::: We implemented a prototype of our anti-caching proposal in a high-performance, main memory OLTP DBMS and performed a series of experiments across a range of database sizes, workload skews, and read/write mixes. We compared its performance with an open-source, disk-based DBMS optionally fronted by a distributed main memory cache. Our results show that for higher skewed workloads the anti-caching architecture has a performance advantage over either of the other architectures tested of up to 9× for a data size 8× larger than memory.


title: Characterization and Optimization of Memory-Resident MapReduce on HPC Systems

abstract: MapReduce is a widely accepted framework for addressing big data challenges. Recently, it has also gained broad attention from scientists at the U.S. leadership computing facilities as a promising solution to process gigantic simulation results. However, conventional high-end computing systems are constructed based on the compute-centric paradigm while big data analytics applications prefer a data-centric paradigm such as MapReduce. This work characterizes the performance impact of key differences between compute- and data-centric paradigms and then provides optimizations to enable a dual-purpose HPC system that can efficiently support conventional HPC applications and new data analytics applications. Using a state-of-the-art MapReduce implementation Spark and the Hyperion system at Lawrence Livermore National Laboratory, we have examined the impact of storage architectures, data locality and task scheduling to the memory-resident MapReduce jobs. Based on our characterization and findings of the performance behaviors, we have introduced two optimization techniques, namely Enhanced Load Balancer and Congestion-Aware Task Dispatching, to improve the performance of Spark applications.


title: Simultaneous Localization and Mapping with Stereo Vision

abstract: In the simultaneous localization and mapping (SLAM) problem, a mobile robot must build a map of its environment while simultaneously determining its location within that map. We propose a new algorithm, for visual SLAM (VSLAM), in which the robot's only sensory information is video imagery. Our approach combines stereo vision with a popular sequential Monte Carlo (SMC) algorithm, the Rao-Blackwellised particle filter, to simultaneously explore multiple hypotheses about the robot's six degree-of-freedom trajectory through space and maintain a distinct stochastic map for each of those candidate trajectories. We demonstrate the algorithm's effectiveness in mapping a large outdoor virtual reality environment in the presence of odometry error.


title: A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

abstract: With the continuous increase in complexity and expense of industrial systems, there is less tolerance for performance degradation, productivity decrease, and safety hazards, which greatly necessitates to detect and identify any kinds of potential abnormalities and faults as early as possible and implement real-time fault-tolerant operation for minimizing performance degradation and avoiding dangerous situations. During the last four decades, fruitful results have been reported about fault diagnosis and fault-tolerant control methods and their applications in a variety of engineering systems. The three-part survey paper aims to give a comprehensive review of real-time fault diagnosis and fault-tolerant control, with particular attention on the results reported in the last decade. In this paper, fault diagnosis approaches and their applications are comprehensively reviewed from model- and signal-based perspectives, respectively.


title: Predicting the status of water pumps using data mining approach

abstract: Data mining approach can be used to discover knowledge by analyzing the patterns or correlations among of fields in large databases. Data mining approach was used to find the patterns of the data from Tanzania Ministry of Water. It is used to predict current and future status of water pumps in Tanzania. The data mining method proposed is XGBoost (eXtreme Gradient Boosting). XGBoost implement the concept of Gradient Tree Boosting which designed to be highly fast, accurate, efficient, flexible, and portable. In addition, Recursive Feature Elimination (RFE) is also proposed to select the important features of the data to obtain an accurate model. The best accuracy achieved with using 27 input factors selected by RFE and XGBoost as a learning model. The achieved result show 80.38% in accuracy. The information or knowledge which is discovered from data mining approach can be used by the government to improve the inspection planning, maintenance, and identify which factor that can cause damage to the water pumps to ensure the availability of potable water in Tanzania. Using data mining approach is cost-effective, less time consuming and faster than manual inspection.


title: Prevalence of Problematic Video Gaming among Ontario Adolescents

abstract: Video game playing has become a very popular activity among adolescents. Its impact on the mental health and well-being of players is just beginning to be explored. This paper reports on the prevalence of problematic gaming in a representative sample of 2,832 Ontario students in grades 7 to 12. The survey included questions about the school grade, family and school related problems, frequency of video game playing and video game related problems as measured by the Problem Video Game Playing scale (PVP). Most of the students (85 %) reported playing video games in the past year and 18.3 % reported playing video games daily. Slightly less then 1 in 10 of the students (9.4 %) endorsed 5 or more of the PVP items (males 15.1 %; females 3.1 %). Further research is required to delineate the concept of excessive video game playing, its relation to other addictions, and the impact on adolescents’ psychosocial functioning.


title: Variation in verbal fluency: A latent variable analysis of clustering, switching, and overall performance

abstract: Verbal fluency tasks have long been used to assess and estimate group and individual differences in executive functioning in both cognitive and neuropsychological research domains. Despite their ubiquity, however, the specific component processes important for success in these tasks have remained elusive. The current work sought to reveal these various components and their respective roles in determining performance in fluency tasks using latent variable analysis. Two types of verbal fluency (semantic and letter) were compared along with several cognitive constructs of interest (working memory capacity, inhibition, vocabulary size, and processing speed) in order to determine which constructs are necessary for performance in these tasks. The results are discussed within the context of a two-stage cyclical search process in which participants first search for higher order categories and then search for specific items within these categories.


title: Delta-Bench: Differential Benchmark for Static Analysis Security Testing Tools

abstract: Background: Static analysis security testing (SAST) tools may be evaluated using synthetic micro benchmarks and benchmarks based on real-world software. Aims: The aim of this study is to address the limitations of the existing SAST tool benchmarks: lack of vulnerability realism, uncertain ground truth, and large amount of findings not related to analyzed vulnerability. Method: We propose Delta-Bench - a novel approach for the automatic construction of benchmarks for SAST tools based on differencing vulnerable and fixed versions in Free and Open Source (FOSS) repositories. To test our approach, we used 7 state of the art SAST tools against 70 revisions of four major versions of Apache Tomcat spanning 62 distinct Common Vulnerabilities and Exposures (CVE) fixes and vulnerable files totalling over 100K lines of code as the source of ground truth vulnerabilities. Results: Our experiment allows us to draw interesting conclusions (e.g., tools perform differently due to the selected benchmark). Conclusions: Delta-Bench allows SAST tools to be automatically evaluated on the real-world historical vulnerabilities using only the findings that a tool produced for the analyzed vulnerability.


title: A Statistical Transfer Learning Perspective for Modeling Shape Deviations in Additive Manufacturing

abstract: Quality control of additive manufacturing applications is required to improve the shape fidelity of the products, which relies on increasing the predictive performance of statistical deviation models for any new shape. Building a single comprehensive model for a wide range of shapes is a very challenging problem, since the error generating mechanism of additive manufacturing applications is usually of high complexity, the amount of training data is usually limited, and the connection among different shapes is unknown. In this study, a novel shape deviation modeling scheme is proposed. In this scheme, the dimensional error of the product is modeled in a parameter-based transfer learning approach. In particular, the shape deviation is decomposed into two components: the shape-independent error and the shape-specific error. The shape-independent error is described by a statistical model that incorporates the engineering knowledge. Guidelines to investigate modeling of the shape-specific error are also given.


title: Software Defined Networks in Wireless Sensor Architectures

abstract: Nowadays, different protocols coexist in Internet that provides services to users. Unfortunately, control decisions and distributed management make it hard to control networks. These problems result in an inefficient and unpredictable network behaviour. Software Defined Networks (SDN) is a new concept of network architecture. It intends to be more flexible and to simplify the management in networks with respect to traditional architectures. Each of these aspects are possible because of the separation of control plane (controller) and data plane (switches) in network devices. OpenFlow is the most common protocol for SDN networks that provides the communication between control and data planes. Moreover, the advantage of decoupling control and data planes enables a quick evolution of protocols and also its deployment without replacing data plane switches. In this survey, we review the SDN technology and the OpenFlow protocol and their related works. Specifically, we describe some technologies as Wireless Sensor Networks and Wireless Cellular Networks and how SDN can be included within them in order to solve their challenges. We classify different solutions for each technology attending to the problem that is being fixed.


title: Social Media Usage for Patients and Healthcare Consumers: A Literature Review

abstract: The evolution of Internet from static Web “publishing” to the highly participative, and data-driven, innovations of Web 2.0 has been influencing how people search for health-related information. This review included studies indexed in the PubMed electronic database that focused on social media analysis, examining relationships between participants (patients and healthcare consumers) through social media usage. The obtained results showed that previous research regarding social media’s impact on patients and healthcare consumers aimed at a combination of platforms, but there is a penury of information about niche topics or its usage for retrieving medical information. Nevertheless, social media proved to be to be a promising tool in research mainly for recruitment purposes. The review has outlined that eHealth literacy is an attribute for populations that are female and relatively young and educated. Blogs share personal experiences, YouTube contains unregulated, high- and low-quality information that can mislead individuals, Facebook contains more marketing than health-related information, while Wikipedia is recommended for providing high-quality information. Despite healthcare practitioners’ and healthcare public institutions’ reluctance about the use of social media, this review demonstrates the usefulness of social media for patients and healthcare consumers in retrieving health-related information based on content availability and usage implications, and highlights gaps in knowledge that further research needs to fill.


title: A Broadband Omnidirectional Circularly Polarized Antenna

abstract: A broadband circularly polarized (CP) antenna is developed with an omnidirectional radiation pattern in the horizontal plane. Four broadband CP rectangular loop elements are employed for broadband omnidirectional CP radiation. The four rectangular loop elements are first printed on a flexible thin dielectric substrate and then rolled into a hollow cylinder. A conducting cylinder is introduced inside the hollow cylinder for achieving desired omnidirectional CP performance. A feeding network consisting of four broadband baluns and an impedance matching circuit is designed to feed the four rectangular loop elements. The omnidirectional CP antenna has a circular cross section with diameter of $0.38 \lambda_{0}$ . Experimental results show that the omnidirectional CP antenna has bandwidths of 41% (1.65–2.5 GHz) for ${\hbox {axial\ ratio}} dB and 45% (1.58–2.5 GHz) for ${{\hbox {return\ loss}} > 10}$ dB. The gain variation in the omnidirectional plane is less than 1 dB for the frequency range from 1.65 to 2.5 GHz. Good agreement is obtained between simulated and measured results.


title: Calcium hydroxylapatite associated soft tissue necrosis: A case report and treatment guideline

abstract: Summary We present an uncommon case of nasal alar and facial necrosis following calcium hydroxylapatite filler injection performed elsewhere without direct physician supervision. The patient developed severe full-thickness necrosis of cheek and nasal alar skin 24 h after injections into the melolabial folds. Management prior to referral included oral antibiotics, prednisone taper, and referral to a dermatologist (day 3) who prescribed valacyclovir for a presumptive herpes zoster reactivation induced by the injection. Referral to our institution was made on day 11, and after herpetic outbreak was ruled out by a negative Tzanck smear, debridement with aggressive local wound care was initiated. After re-epithelialization and the fashioning of a custom intranasal stent to prevent vestibular stenosis, pulsed dye laser therapy was performed for wound modification. The patient healed with an acceptable cosmetic outcome. This report underscores the importance of facial vasculature anatomy, injection techniques, and identification of adverse events when using fillers. A current treatment paradigm for such events is also presented.


title: Deletion of 8q24 in an adult with mild dysmorphic features, developmental delay, and ketotic hypoglycemia.

abstract: We present a 56-year-old female with a history of carbohydrate intolerance and ketotic hypoglycemia, dysmorphic features, mild developmental delay, lymphedema, altered pain sensation, and frequent fractures, who was found to have a heterozygous 8.09 Mb deletion of chromosome 8q24.11q24.13 containing more than 39 genes, as well as a duplication of 20q11.23 containing one gene. The deleted region overlaps that of two previously reported patients, who share a subset of clinical characteristics with the patient described here. Some of this patient's clinical features are consistent with the loss of genes in the deleted region. The diagnostic work-up of this patient clearly demonstrates the evolution of genetic testing techniques.


title: Non-obtrusive electrocardiogram system for the Smart Rollator

abstract: The objective of the Smart Rollator project is to enable health care monitoring through embedding electronic sensing systems. This paper examines adding an ECG system to a rollator, designed specifically to interface with two gel-less electrodes. The focus is to develop a circuit with minimal filtering of the signal, just sufficient to extract valuable ECG information reliably using digital processing techniques. A prototype system is built and evaluated, its performance compared to a conventional three-electrode ECG amplifier. Preliminary results demonstrate that the proposed circuit can be used for the Smart Rollator application.


title: Chronic histopathological consequences of fluid-percussion brain injury in rats: effects of post-traumatic hypothermia

abstract: Early outcome measures of experimental traumatic brain injury (TBI) are useful for characterizing the traumatic severity as well as for clarifying the pathomechanisms underlying patterns of neuronal vulnerability. However, it is increasingly apparent that acute outcome measures may not always be accurate predictors of chronic outcome, particularly when assessing the efficacy of potential therapeutic regimens. This study examined the chronic histopathological outcome in rats 8 weeks following fluid-percussive TBI coupled with moderate post-traumatic brain hypothermia, a protocol that provides acute neuronal protection. Animals received a moderate parasagittal percussive head injury (2.01–2.38 atm) or sham procedure followed immediately by 3 h of brain hypothermia (30°C) or normothermia (37°C). Eight weeks following TBI, serial tissue sections were stained with hematoxylin and eosin or immunostained for glial fibrillary acidic protein. Tissue damage, gliosis and immunoreactive astrocytes were observed in the ipsilateral thalamus, hippocampus, and in the neocortex lateral to the injury site. Within the thalamus, focal necrosis was restricted to selective thalamic nuclei. Significant hippocampal cell loss was found in the ipsilateral dentate hilar region of both TBI groups. Quantitative volume measurements revealed significant decreases in cortical, thalamic and hippocampal volume ipsilateral to the impact in both TBI groups. Lateral ventricles were substantially enlarged in the TBI-normothermia group, an effect which was significantly attenuated by post-TBI hypothermia. The attenuation of lateral ventricular dilation by post-traumatic hypothermia is indicative of chronic neuroprotection in this TBI model. These data provide new information concerning the chronic histopathological consequence of experimental TBI and the relevance of this trauma model to chronic human head injury.


title: Are We Ready for Driver-less Vehicles? Security vs. Privacy- A Social Perspective

abstract: At this moment Autonomous cars are probably the biggest and most talked about technology in the Robotics Research Community. In spite of great technological advances over past few years a full edged autonomous car is still far from reality. This article talks about the existing system and discusses the possibility of a Computer Vision enabled driving being superior than the LiDar based system. A detailed overview of privacy violations that might arise from autonomous driving has been discussed in detail both from a technical as well as legal perspective. It has been proved through evidence and arguments that efficient and accurate estimation and efficient solution of the constraint satisfaction problem addressed in the case of autonomous cars are negatively correlated with the preserving the privacy of the user. It is a very difficult trade-off since both are very important aspects and has to be taken into account. The fact that one cannot compromise with the safety issues of the car makes it inevitable to run into serious privacy concerns that might have adverse social and political effects.


title: Google Scholar as a tool for discovering journal articles in library and information science

abstract: Purpose: The purpose of this paper is to measure the coverage of Google Scholar for the Library and Information Science (LIS) journal literature as identified by a list of core LIS journals from a study by Schlogl and Petschnig (2005). Methods: We checked every article from 35 major LIS journals from the years 2004 to 2006 for availability in Google Scholar (GS). We also collected information on the type of availability—i.e., whether a certain article was available as a PDF for a fee, as a free PDF, or as a preprint. Results: We found that only some journals are completely indexed by Google Scholar, that the ratio of versions available depends on the type of publisher, and that availability varies a lot from journal to journal. Google Scholar cannot substitute for abstracting and indexing services in that it does not cover the complete literature of the field. However, it can be used in many cases to easily find available full texts of articles already found using another tool. Originality/value: This study differs from other Google Scholar coverage studies in that it takes into account not only whether an article is indexed in GS at all, but also the type of availability.


title: Anonymization technique through record elimination to preserve privacy of published data

abstract: The term Data Privacy is associated with data collection and dissemination of data. Privacy issues arise in various area such as health care, intellectual property, biological data etc. It is one of the challenging issues when sharing or publishing the data between one to many sources for research purpose and data analysis. Sensitive information of data owners must be protected. There are two kinds of major attacks against privacy namely record linkage and attribute linkage attacks Earlier, researchers have proposed new methods namely k-anonymity, l-dlverslty, t-closeness for data privacy. K-anonymity method preserves the privacy against record linkage attack alone. It fails to address attribute linkage attack. l-diversity method overcomes the drawback of k-anonymity method. But it fails to address identity disclosure attack and attribute disclosure attack in some exceptional cases. t-closeness method preserves the privacy against attribute linkage attack but not identity disclosure attack. But it computational complexity is large. In this paper, the authors propose a new method to preserve the privacy of individuals' sensitive data from record and attribute linkage attacks. In the proposed method, privacy preservation is achieved through generalization of quasi identifier by setting range values and record elimination. The proposed method is implemented and tested with various data sets.


title: User interface design for crowdsourcing systems

abstract: Harnessing human computation through crowdsourcing offers an alternative approach to solving complex problems, especially those that are relatively easy for humans but difficult for computers. Micro-tasking platforms such as Amazon Mechanical Turk have attracted large, on-demand work force of millions of workers as well as hundreds of thousands of job requesters. Achieving high quality results by putting humans in the loop is one of the main goals of these crowdsourcing systems. We study the effects of different user interface designs on the performance of crowdsourcing systems. Our results indicate that user interface design choices have a significant effect on crowdsourced worker performance.


Does the new biology syllabus encourage students to think differently about their biology knowledge


title: iThink: A Game-Based Approach Towards Improving Collaboration and Participation in Requirement Elicitation.

abstract: Abstract Requirements are the heart of Information Systems development because they determine how the system will operate. There- fore, requirements elicitation is a critical activity of the information systems development life cycle. Recognizing the im- portance of collaborative work and the huge difficulty of gathering stakeholders at the same time and place, researches have been proposing web collaborative tools to elicit requirements. In this article we present a game-based collaborative tool called iThink that aims at improving the participation in a requirement elicitation process. iThink takes advantage of the associa- tion between “gamification” concepts and the six hats of thinking method for collecting both new requirements and feedback about existing ones and for presenting the requirement elicitation process in a form of a collaborative game. Two case-studies, involving several stakeholders, are also presented with the purpose of evaluating the effectiveness and acceptance of this tool.


title: Using a Delphi process and the Analytic Hierarchy Process (AHP) to evaluate the complexity of projects

abstract: Research highlights? Describing, defining, and understanding better project complexity and its measures. ? Building up a generic project complexity framework. ? Performing a Delphi study about project complexity factors. ? Building up an AHP-based multi-criteria evaluation of project complexity. ? Exploring the sensitivity of such a measure. Project complexity is ever growing and needs to be understood, analysed and measured better to assist modern project management. The overall ambition of this paper is therefore to define a measure of project complexity in order to assist decision-making, notably when analysing several projects in a portfolio, or when studying different areas of a project. A synthesised literature review on existing complexity measures is firstly proposed in order to highlight their limitations. Then, we identify the multiple aspects of project complexity thanks to the construction and refinement of a project complexity framework thanks to an international Delphi study. We then propose a multi-criteria approach to project complexity evaluation, underlining the benefits of such an approach. In order to solve properly this multi-criteria problem, we first conduct a critical state of the art on multi-criteria methodologies. We then argue for the use of the Analytic Hierarchy Process. In the end, this tool permits to define a relative project complexity measure, which can notably assist decision-making. Complexity scales and subscales are defined in order to highlight the most complex alternatives and their principal sources of complexity within the set of criteria and sub-criteria which exist in the hierarchical structure. Finally, a case study within a start-up firm in the entertainment industry (musicals production) is performed. Conclusions, limitations and perspectives of research are given in the end.


title: Understanding the spatial distribution of crime based on its related variables using geospatial discriminative patterns

abstract: Crime tends to cluster geographically. This has led to the wide usage of hotspot analysis to identify and visualize crime. Accurately identified crime hotspots can greatly benefit the public by creating accurate threat visualizations, more efficiently allocating police resources, and predicting crime. Yet existing mapping methods usually identify hotspots without considering the underlying correlates of crime. In this study, we introduce a spatial data mining framework to study crime hotspots through their related variables. We use Geospatial Discriminative Patterns (GDPatterns) to capture the significant difference between two classes (hotspots and normal areas) in a geo-spatial dataset. Utilizing GDPatterns, we develop a novel model—Hotspot Optimization Tool (HOT)—to improve the identification of crime hotspots. Finally, based on a similarity measure, we group GDPattern clusters and visualize the distribution and characteristics of crime related variables. We evaluate our approach using a real world dataset collected from a northeast city in the United States.


title: Building and evaluating a location-based service recommendation system with a preference adjustment mechanism

abstract: The location-based service (LBS) of mobile communication and the personalization of information recommendation are two important trends in the development of electric commerce. However, many previous researches have only emphasized on one of the two trends. In this paper, we integrate the application of LBS with recommendation technologies to present a location-based service recommendation model (LBSRM) and design a prototype system to simulate and measure the validity of LBSRM. Due to the accumulation and variation of preference, in the recommendation model we conduct an adaptive method including long-term and short-term preference adjustment to enhance the result of recommendation. Research results show, with the assessments of relative index, the rate of recommendation precision could be 85.48%.


title: Miniature Inverted–Repeat Transposable Elements (MITEs) Have Been Accumulated through Amplification Bursts and Play Important Roles in Gene Expression and Species Diversity in Oryza sativa

abstract: Miniature inverted–repeat transposable elements (MITEs) are predicted to play important roles on genome evolution. We developed a BLASTN-based approach for de novo identification of MITEs and systematically analyzed MITEs in rice genome. The genome of rice cultivar Nipponbare (Oryza sativa ssp. japonica) harbors 178,533 MITE-related sequences classified into 338 families. Pairwise nucleotide diversity and phylogenetic tree analysis indicated that individual MITE families were resulted from one or multiple rounds of amplification bursts. The timing of amplification burst varied considerably between different MITE families or subfamilies. MITEs are associated with 23,623 (58.2%) genes in rice genome. At least 7,887 MITEs are transcribed and more than 3,463 were transcribed with rice genes. The MITE sequences transcribed with rice coding genes form 1,130 pairs of potential natural sense/antisense transcripts. MITEs generate 23.5% (183,837 of 781,885) of all small RNAs identified from rice. Some MITE families generated small RNAs mainly from the terminals, while other families generated small RNAs predominantly from the central region. More than half (51.8%) of the MITE-derived small RNAs were generated exclusively by MITEs located away from genes. Genome-wide analysis showed that genes associated with MITEs have significantly lower expression than genes away from MITEs. Approximately 14.8% of loci with full-length MITEs have presence/absence polymorphism between rice cultivars 93-11 (O. sativa ssp. indica) and Nipponbare. Considering that different sets of genes may be regulated by MITE-derived small RNAs in different genotypes, MITEs provide considerable diversity for O. sativa.


title: Line-Based Structure from Motion for Urban Environments

abstract: We present a novel method for recovering the 3D-line structure of a scene from multiple widely separated views. Traditional optimization-based approaches to line-based structure from motion minimize the error between measured line segments and the projections of corresponding 3D lines. In such a case, 3D lines can be optimized using a minimum of 4 parameters. We show that this number of parameters can be further reduced by introducing additional constraints on the orientations of lines in a 3D scene. In our approach, 2D-lines are automatically detected in images with the assistance of an EM-based vanishing point estimation method which assumes the existence of edges along mutally orthogonal vanishing directions. Each detected line is automatically labeled with the orientation (e.g. vertical, horizontal) of the 3D line which generated the measurement, and it is this additional knowledge that we use to reduce the number of degrees of freedom of 3D lines during optimization. We present 3D reconstruction results for urban scenes based on manually established feature correspondences across images.


title: Planar High-Gain Circularly Polarized Element Antenna for Array Applications

abstract: This paper proposes a planar high-gain circularly polarized element antenna that can be used for array applications. The substrate-integrated waveguide (SIW) cavity is designed to support dual-resonant modes, the ${\bf TE}_{{\bf 120}}$ -like and ${\bf TE}_{{\bf 210}}$ -like modes, for the implementation of circularly polarized radiation performance. Four rectangular radiation slots and a large perturbation, introduced by inserting a metallic via-brick into the SIW cavity, are deployed to achieve a high simulated gain of 10.28 dBi at 6.65 GHz for the proposed element. As a demonstration of an array application, a $4 \times 4$ array antenna is designed using the proposed element with a compact beam-forming network. Experiments are carried out to verify the designed prototypes. The measured peak gains of the designed element and array antennas are 9.6 and 20.1 dBi, respectively, which include the loss from SMA connectors. Good agreement between simulated and measured results is obtained.


title: Improve Uncertainty Estimation for Unknown Classes in Bayesian Neural Networks with Semi-Supervised /One Set Classification

abstract: Although deep neural network (DNN) has achieved many state-of-the-art results, estimating the uncertainty presented in the DNN model and the data is a challenging task. Problems related to uncertainty such as classifying unknown classes (class which does not appear in the training data) data as known class with high confidence, is critically concerned in the safety domain area (e.g, autonomous driving, medical diagnosis). In this paper, we show that applying current Bayesian Neural Network (BNN) techniques alone does not effectively capture the uncertainty. To tackle this problem, we introduce a simple way to improve the BNN by using one class classification (in this paper, we use the term "set classification" instead). We empirically show the result of our method on an experiment which involves three datasets: MNIST, notMNIST and FMNIST.


title: Study of Chronic Wound Image Segmentation: Impact of Tissue Type and Color Data Augmentation

abstract: Chronic wound segmentation is an essential task for evaluating wound and its recovery progress. A physician usually measures a wound area to choose proper treatment according to wound conditions. However, precise measurement needs accurate image-region segmentation. With the advent of deep learning for semantic image segmentation, accuracy of region segmentation is dramatically higher than traditional methods. Unfortunately, semantic segmentation in prior work did not produce satisfactory outputs in wound image segmentation, even with a large training dataset. This work, therefore, rethinks about the challenge and aims at not only improving segmentation accuracy, but also studying the impact of wound tissue types and color on accuracy. Since an end-to-end approach of semantic segmentation in prior work performed relatively poorly, the proposed method employs both image processing and deep learning techniques. The experiments indicated that slough was the most challenging tissue to be segmented. Also, properly increasing color variety of wound images significantly improved segmentation performance. The accuracy of the proposed method was 72%, 40%, and 53% in terms of intersection over union for granulation, necrosis, and slough wound tissue types, respectively. The proposed method outperformed a prior end-to-end approach, even though this method employed particularly simpler neural network models and much smaller number of training images.


title: Articles Building Watson: An Overview of the

abstract: IBM Research undertook a challenge to build a computer system that could compete at the human champion level in real time on the American TV Quiz show, Jeopardy! The extent of the challenge includes fielding a real-time automatic contestant on the show, not merely a laboratory exercise. The Jeopardy! Challenge helped us address requirements that led to the design of the DeepQA architecture and the implementation of Watson. After 3 years of intense research and development by a core team of about 20 researches, Watson is performing at human expert-levels in terms of precision, confidence and speed at the Jeopardy! Quiz show. Our results strongly suggest that DeepQA is an effective and extensible architecture that may be used as a foundation for combining, deploying, evaluating and advancing a wide range of algorithmic techniques to rapidly advance the field of QA.


title: Logical Physical Clocks

abstract: There is a gap between the theory and practice of distributed systems in terms of the use of time. The theory of distributed systems shunned the notion of time, and introduced “causality tracking” as a clean abstraction to reason about concurrency. The practical systems employed physical time (NTP) information but in a best effort manner due to the difficulty of achieving tight clock synchronization. In an effort to bridge this gap and reconcile the theory and practice of distributed systems on the topic of time, we propose a hybrid logical clock, HLC, that combines the best of logical clocks and physical clocks. HLC captures the causality relationship like logical clocks, and enables easy identification of consistent snapshots in distributed systems. Dually, HLC can be used in lieu of physical/NTP clocks since it maintains its logical clock to be always close to the NTP clock. Moreover HLC fits in to 64 bits NTP timestamp format, and is masking tolerant to NTP kinks and uncertainties.We show that HLC has many benefits for wait-free transaction ordering and performing snapshot reads in multiversion globally distributed databases.


The MobiAct Dataset: Recognition of Activities of Daily Living using Smartphones


Sentiment Analysis of a German Twitter-Corpus


title: An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation

abstract: Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight between the camera and the markers, which may be difficult to maintain in actual applications. In contrast, inertial sensing does not require line-of-sight but is subject to drift, which may cause large cumulative errors, especially during the measurement of position. To handle cases where some or all of the markers are occluded, this paper proposes an inertial and optical sensor fusion approach in which the bias of the inertial sensors is estimated when the optical tracker provides full six degree-of-freedom (6-DOF) pose information. As long as the position of at least one marker can be tracked by the optical system, the 3-DOF position can be combined with the orientation estimated from the inertial measurements to recover the full 6-DOF pose information. When all the markers are occluded, the position tracking relies on the inertial sensors that are bias-corrected by the optical tracking system. Experiments are performed with an augmented reality head-mounted display (ARHMD) that integrates an optical tracking system (OTS) and inertial measurement unit (IMU). Experimental results show that under partial occlusion conditions, the root mean square errors (RMSE) of orientation and position are 0.04° and 0.134 mm, and under total occlusion conditions for 1 s, the orientation and position RMSE are 0.022° and 0.22 mm, respectively. Thus, the proposed sensor fusion approach can provide reliable 6-DOF pose under long-term partial occlusion and short-term total occlusion conditions.


title: Developmental Changes in the Effects of pH on Contraction and Ca2+Current in Rabbit Heart☆

abstract: Protons inhibit Ca2+current and contraction in heart muscle. The present study compares the effects of lowering the pH of the bath solution on single-cell contraction, action potential configuration and Ca2+currents between neonatal and adult rabbit hearts. We found that a reduction of extracellular pH from 7.3 to 6.3 decreased cell contraction amplitude to 84.3% of control in isolated neonatal myocytes. A comparable change in extracellular pH resulted in a decrease in cell contraction to 56.2% of control in adult cells. Similarly, tension generation in intact neonatal papillary muscles was less sensitive to a decrease in external pH as compared to papillary muscles from adult animals. In addition, acidosis caused a less pronounced inhibition of Ca2+current in neonatal cells than in adult cells (85±4%v62±4% of control, pH=6.3,P<0.001; 63±5%v32±5% of control, pH=5.8,P<0.001). Thus, the effect of external acidosis on myocardial contractility is commensurate with the effect on trans-sarcolemmal Ca2+current. The membrane potential at which peak Ca2+current occurred was not altered by low pH in neonatal cells, but was shifted toward positive potentials by 17.7 mV in adult myocytes. Further, low external pH solution reduced Ca2+current conductance more in adult cells than in neonatal cells. Moreover, action potential configuration in neonatal cells was altered less by acidosis as compared with adult cells. These findings may help explain the greater resistance of neonatal hearts to extracellular acidosis.


Universal Dependencies and Morphology for Hungarian - and on the Price of Universality


title: Merkle Tree Traversal Revisited

abstract: We propose a new algorithm for computing authentication paths in the Merkle signature scheme. Compared to the best algorithm for this task, our algorithm reduces the worst case running time considerably.