bluuebunny/crossref_metadata_2025 huggingface dataset:
A THEORETICAL ANALYSIS OF A PERCOLATION MODEL
Authors: TANERI SENCER
Published: September 2012

This is an analytical analysis of a previously published research for a percolation simulation. In that research the effect of mutations on adaptability was investigated in a bit-string model of invading species in a random environment. However, analytical analysis was missing which will be the topic here. The Hausdorff dimensions are calculated for the fractals and the conditions on invasion are analyzed analytically by manipulation of partial differential equations. Thus, various conclusions may be reached without having to run long simulations.
BUILT-IN ELECTRIC FIELD EFFECT ON DONOR IMPURITIES IN STRAINED WURTZITE GaN/AlGaN ASYMMETRIC DOUBLE QUANTUM WELLS
Authors: ZHU JUN , BAN SHI LIANG , HA SI HUA
Published: September 2012

The ground state binding energies of donor impurities in strained [0001]-oriented wurtzite GaN / Al x Ga 1-x N asymmetric double quantum wells are investigated using a variational method combined with numerical computation. The built-in electric field due to the spontaneous and strain-induced piezoelectric polarization and the strain modification on material parameters are taken into account. The variations of binding energies versus the width of central barrier, the ratio of two well widths, and the impurity position are presented, respectively. It is found that the built-in electric field causes a mutation of binding energies with increasing the width of central barrier to some value. The results for symmetrical double quantum wells and without the built-in electric field are also discussed for comparison.
CONSTRUCTIONS OF OPTIMAL SUBSYSTEM CODES
Authors: QIAN JIANFA , ZHANG LINA
Published: September 2012

New families of subsystem codes are constructed. Furthermore, these new families of subsystem codes are optimal. Finally, new families of asymmetric subsystem codes which derived from cyclic codes are presented.
OPTICAL CONDUCTANCE OF A TWO-DIMENSIONAL SEMICONDUCTOR IN THE PRESENCE OF RASHBA SPIN-ORBIT COUPLING AND A PERIODIC POTENTIAL
Authors: O'BRIEN T. E. , ZHANG C.
Published: September 2012

We investigate the optical conductivity of a two-dimensional semiconductor with Rashba spin-orbit coupling subject to an external sinusoidal potential. Using Fourier series, we obtain quantitative results on the band structure of this system. The periodic potential can be treated as a perturbation of the Rashba Hamiltonian, with the induced band gap at degeneracy point being linear with the potential strength. The optical conductance displays a number of interesting features, namely the presence of multiple tunable resonances that originate from a k-shift of band extrema.
SEARCH FOR TWO-PHONON OCTUPOLE VIBRATIONAL BANDS IN 88, 89, 92, 93, 94, 96Sr AND 95, 96, 97, 98Zr
Authors: HWANG J. K. , HAMILTON J. H. , RAMAYYA A. V. , BREWER N. T. , WANG E. H. , LUO Y. X. , ZHU S. J.
Published: September 2012

Several new gamma transitions were identified in 94 Sr , 93 Sr , 92 Sr , 96 Zr and 97 Zr from the spontaneous fission of 252 Cf . Excited states in 88, 89, 92, 94, 96 Sr and 95, 96, 97, 98 Zr were reanalyzed and reorganized to propose the new two-phonon octupole vibrational states and bands. The spin and parity of 6+ are assigned to a 4034.5 keV state in 94 Sr and 3576.4 keV state in 98 Zr . These states are proposed as the two-phonon octupole vibrational states along with the 6+ states at 3483.4 keV in 96 Zr , at 3786.0 keV in 92 Sr and 3604.2 keV in 96 Sr . The positive parity bands in 88, 94, 96 Sr and 96, 98 Zr are the first two-phonon octupole vibrational bands based on a 6+ state assigned in spherical nuclei. It is thought that in 94, 96 Sr and 96, 98 Zr a 3- octupole vibrational phonon is weakly coupled to an one-phonon octupole vibrational band to make the two-phonon octupole vibrational band. Also, the high spin states of odd-A95 Zr and 97 Zr are interpreted to be generated by the neutron 2d5/2 hole and neutron 1g7/2 particle, respectively, weakly coupled to one- and two-phonon octupole vibrational bands of 96 Zr . The high spin states of odd-A87 Sr are interpreted to be caused by the neutron 1g9/2 hole weakly coupled to 3- and 5- states of 88 Sr . New one- and two-POV bands in 95, 97 Zr and 87, 89 Sr are proposed, for the first time, in the present work.
COMBINING ADABOOST WITH PREPROCESSING ALGORITHMS FOR EXTRACTING FUZZY RULES FROM LOW QUALITY DATA IN POSSIBLY IMBALANCED PROBLEMS
Authors: PALACIOS ANA , SANCHEZ LUCIANO , COUSO INES
Published: September 2012

An extension of the Adaboost algorithm for obtaining fuzzy rule-based systems from low quality data is combined with preprocessing algorithms for equalizing imbalanced datasets. With the help of synthetic and real-world problems, it is shown that the performance of the Adaboost algorithm is degraded in presence of a moderate uncertainty in either the input or the output values. It is also established that a preprocessing stage improves the accuracy of the classifier in a wide range of binary classification problems, including those whose imbalance ratio is uncertain.
HANDLING HIGHLY-DIMENSIONAL CLASSIFICATION TASKS WITH HIERARCHICAL GENETIC FUZZY RULE-BASED CLASSIFIERS
Authors: STAVRAKOUDIS DIMITRIS G. , THEOCHARIS JOHN B.
Published: September 2012

Many modern classification tasks are defined in highly-dimensional feature spaces. The derivation of high-performing genetic fuzzy rule-based classification systems (GFRBCSs) in such scenarios is a non-trivial task. This paper presents a framework for increasing the performance of GFRBCSs by creating a hierarchical fuzzy rule-based classifier. The proposed system is constructed through repeated invocations to a base GFRBCS procedure, considering at each step an input space fuzzy partition of a certain granularity. The best performing rules are inserted in the hierarchical rule base and the process is repeated again, considering a thicker granularity. The employed boosting scheme guides the algorithm in creating new rules to treat uncovered or misclassified patterns, thus monotonically increasing the performance of the classifier. Extensive experimental analysis in a number of real-world high-dimensional classification tasks proves the effectiveness of the proposed approach in increasing the performance of the base classifier, maintaining its interpretability to a considerable degree.
HIERARCHICAL-INTERPOLATIVE FUZZY SYSTEM CONSTRUCTION BY GENETIC AND BACTERIAL MEMETIC PROGRAMMING APPROACHES
Authors: BALÁZS KRISZTIÁN , KÓCZY LÁSZLÓ T.
Published: September 2012

In this paper a family of new methods are proposed for constructing hierarchical-interpolative fuzzy rule bases in the frame of a fuzzy rule based supervised machine learning system modeling black box systems defined by input-output pairs. The resulting hierarchical rule base is constructed by using structure building pure evolutionary and memetic techniques, namely, Genetic and Bacterial Programming Algorithms and their memetic variants containing local search steps.

Applying hierarchical-interpolative fuzzy rule bases is a rather efficient way of reducing the complexity of knowledge bases, whereas evolutionary methods (including memetic techniques) ensure a relatively fast convergence in the learning process.

As it is presented in the paper, by applying a newly proposed representation schema these approaches can be combined to form hierarchical-interpolative machine learning systems.
CHECKING ORTHOGONAL TRANSFORMATIONS AND GENETIC ALGORITHMS FOR SELECTION OF FUZZY RULES BASED ON INTERPRETABILITY-ACCURACY CONCEPTS
Authors: REY M. ISABEL , GALENDE MARTA , FUENTE M. J. , SAINZ-PALMERO GREGORIO I.
Published: September 2012

Fuzzy modeling is one of the most known and used techniques in different areas to model the behavior of systems and processes. In most cases, as in data-driven fuzzy modeling, these fuzzy models reach a high performance from the point of view of accuracy, but from other points of view, such as complexity or interpretability, they can present a poor performance.

Several approaches are found in the bibliography to reduce the complexity and improve the interpretability of the fuzzy models. In this paper, a post-processing approach is carried out via rule selection, whose aim is to choose the most relevant rules for working together on the well-known accuracy-interpretability trade-off. The rule relevancy is based on Orthogonal Transformations, such as the SVD-QR rank revealing approach, the P-QR and OLS transformations. Rule selection is carried out using a genetic algorithm that takes into account the information obtained by the Orthogonal Transformations. The main objective is to check the true significance, drawbacks and advantages of the rule selection based on the orthogonal transformations via the rule firing strength matrix.

In order to carry out this aim, a neuro-fuzzy system, FasArt (Fuzzy Adaptive System ART based), and several case studies, data sets from the KEEL Project Repository, are used to tune and check this selection of rules based on orthogonal transformations, genetic selection and accuracy-interpretability trade-off. This neuro-fuzzy system generates Mamdani fuzzy rule based systems (FRBSs), in an approximative way. NSGA-II is the MOEA tool used to tune the proposed rule selection.
GENETIC-FUZZY MINING WITH TAXONOMY
Authors: CHEN CHUN-HAO , HONG TZUNG-PEI , LEE YEONG-CHYI
Published: September 2012

Data mining is most commonly used in attempts to induce association rules from transaction data. Since transactions in real-world applications usually consist of quantitative values, many fuzzy association-rule mining approaches have been proposed on single- or multiple-concept levels. However, the given membership functions may have a critical influence on the final mining results. In this paper, we propose a multiple-level genetic-fuzzy mining algorithm for mining membership functions and fuzzy association rules using multiple-concept levels. It first encodes the membership functions of each item class (category) into a chromosome according to the given taxonomy. The fitness value of each individual is then evaluated by the summation of large 1-itemsets of each item in different concept levels and the suitability of membership functions in the chromosome. After the GA process terminates, a better set of multiple-level fuzzy association rules can then be expected with a more suitable set of membership functions. Experimental results on a simulation dataset also show the effectiveness of the algorithm.
A NOVEL GENETIC FUZZY MARKUP LANGUAGE AND ITS APPLICATION TO HEALTHY DIET ASSESSMENT
Authors: LEE CHANG-SHING , WANG MEI-HUI , HAGRAS HANI , CHEN ZHI-WEI , LAN SHUN-TENG , HSU CHIN-YUAN , KUO SU-E , KUO HUI-CHING , CHENG HUI-HUA
Published: September 2012

In this paper, we present a novel Genetic Fuzzy Markup Language (GFML)-based genetic fuzzy system, including the genetic learning base, the knowledge base and rule base of FML, the fuzzy inference engine, and the genetic learning mechanism. The GFML is applied to the genetic fuzzy system for dealing with the knowledge base, the rule base, and the genetic learning base of the healthy diet domain, including the ingredients and the contained servings of six food categories of some common food in Taiwan. Moreover, the proposed novel system is able to infer the healthy status of human's daily eating. In the proposed system, the domain experts first define the nutrient facts of the common food to construct the fuzzy food ontology. Meanwhile, the involved Taiwanese students of National University of Tainan (NUTN) record their daily meals for a constant period of time. Then, based on the built fuzzy profile ontology, fuzzy food ontology, and fuzzy personal food ontology, a GFML-based genetic fuzzy system is carried out to infer the possibility of dietary healthy level for one-day meals. The experimental results show that the proposed GFML-based genetic fuzzy system gives good results for the healthy diet assessment.
DAMAGE EVOLUTION SPECTRA FOR SEISMIC ANALYSIS OF HIGH-RISE BUILDINGS
Authors: HO Y. B. , KUANG J. S.
Published: September 2012

Seismic response spectra are amongst one of the most important tools for characterizing earthquake ground motions. In design practice, the response spectra are presented without including any load history, hence the nonlinear analysis of structures based solely on conventional earthquake response spectra is theoretically unsound, particularly for long-period or vertically irregular high-rise buildings. In this paper, a concept of seismic damage evolution is introduced and the method of analysis for characterizing the process of seismic damage to structures under earthquakes is presented. Seismic damage evolution spectra for analysis and design of high-rise buildings are then developed as an effective means of describing and simplifying earthquake ground motions. These spectra are shown to be very useful in selecting the ground motion-time history and, particularly, validating the equivalent static-load analysis and design of high-rise buildings under near-fault pulse-like ground motions. Case studies of the seismic inelastic performance of two vertically irregular, tall buildings are presented considering the seismic damage evolution spectra.
High-quality image deblurring with panchromatic pixels
Authors: Wang Sen , Hou Tingbo , Border John , Qin Hong , Miller Rodney
Published: September 2012

Image deblurring has been a very challenging problem in recent decades. In this article, we propose a high-quality image deblurring method with a novel image prior based on a new imaging system. The imaging system has a newly designed sensor pattern achieved by adding panchromatic (pan) pixels to the conventional Bayer pattern. Since these pan pixels are sensitive to all wavelengths of visible light, they collect a significantly higher proportion of the light striking the sensor. A new demosaicing algorithm is also proposed to restore full-resolution images from pixels on the sensor. The shutter speed of pan pixels is controllable to users. Therefore, we can produce multiple images with different exposures. When long exposure is needed under dim light, we read pan pixels twice in one shot: one with short exposure and the other with long exposure. The long-exposure image is often blurred, while the short-exposure image can be sharp and noisy. The short-exposure image plays an important role in deblurring, since it is sharp and there is no alignment problem for the one-shot image pair. For the algorithmic aspect, our method runs in a two-step maximum-a-posteriori (MAP) fashion under a joint minimization of the blur kernel and the deblurred image. The algorithm exploits a combined image prior with a statistical part and a spatial part, which is powerful in ringing controls. Extensive experiments under various conditions and settings are conducted to demonstrate the performance of our method.
Simple formulas for quasiconformal plane deformations
Authors: Lipman Yaron , Kim Vladimir G. , Funkhouser Thomas A.
Published: September 2012

We introduce a simple formula for 4-point planar warping that produces provably good 2D deformations. In contrast to previous work, the new deformations minimize the
maximum
conformal distortion and spread the distortion equally across the domain. We derive closed-form formulas for computing the 4-point interpolant and analyze its properties. We further explore applications to 2D shape deformations by building local deformation operators that use thin-plate splines to further deform the 4-point interpolant to satisfy certain boundary conditions. Although this modification no longer has any theoretical guarantees, we demonstrate that, practically, these local operators can be used to create compound deformations with fewer control points and smaller worst-case distortions in comparisons to the state-of-the-art.
Theory, analysis and applications of 2D global illumination
Authors: Jarosz Wojciech , Schönefeld Volker , Kobbelt Leif , Jensen Henrik Wann
Published: September 2012

We investigate global illumination in 2D and show how this simplified problem domain leads to practical insights for 3D rendering.

We first derive a full theory of 2D light transport by introducing 2D analogs to radiometric quantities such as flux and radiance, and deriving a 2D rendering equation. We use our theory to show how to implement algorithms such as Monte Carlo raytracing, path tracing, irradiance caching, and photon mapping in 2D, and demonstrate that these algorithms can be analyzed more easily in this domain while still providing insights for 3D rendering.

We apply our theory to develop several practical improvements to the irradiance caching algorithm. We perform a full second-order analysis of diffuse indirect illumination, first in 2D, and then in 3D by deriving the irradiance Hessian, and show how this leads to increased accuracy and performance for irradiance caching. We propose second-order Taylor expansion from cache points, which results in more accurate irradiance reconstruction. We also introduce a novel error metric to guide cache point placement by analyzing the error produced by irradiance caching. Our error metric naturally supports anisotropic reconstruction and, in our preliminary study, resulted in an order of magnitude less error than the “split-sphere” heuristic when using the same number of cache points.
Containing bogus packet insertion attacks for broadcast authentication in sensor networks
Authors: Xiong Kaiqi , Wang Ronghua , Du Wenliang , Ning Peng
Published: September 2012

Broadcast is a critical communication primitive in wireless sensor networks. The multihop nature of sensor networks makes it necessary for sensor nodes to forward broadcast messages so that the messages can reach an entire network. Authentication of broadcast messages is an important but challenging problem in sensor networks. Public key cryptography (PKC) has been used recently to address this problem. However, PKC-based authentication techniques are susceptible to bogus packet insertion attacks in which attackers keep broadcasting bogus messages and force resource-constrained sensor nodes to forward such messages. Moreover, because it takes time to do signature verifications, it is impractical for each node to authenticate every received message before forwarding it. In this article, we propose a dynamic window scheme to thwart the aforementioned bogus packet insertion attacks which permits sensor nodes to efficiently broadcast messages. Within this scheme, a sensor node has the ability to determine whether or not to verify an incoming message before forwarding the message. We further study the property of this dynamic window scheme and investigate the best strategy for thwarting bogus packet insertion attacks. We propose three strategies for finding the optimal parameters by an improved additive increase multiplicative decrease (AIMD) window updating function so that the proposed dynamic window scheme can achieve the best overall performance with respect to the authentication and forwarding times of messages. Numerical validations show that our proposed scheme performs very well in terms of energy saving and broadcast delays based on three different metrics, including average authentication delays, the percentage of nodes receiving fake messages, and the percentage of nodes forwarding fake messages.
Optimal multiobjective placement of distributed sensors against moving targets
Authors: Wettergren Thomas A. , Costa Russell
Published: September 2012

We consider the optimal deployment of a sparse network of sensors against moving targets, under multiple conflicting objectives of search. The sensor networks of interest consist of sensors which perform independent binary detection on a target, and report detections to a central control authority. A multiobjective optimization framework is developed to find optimal trade-offs as a function of sensor deployment, between the conflicting objectives of maximizing the Probability of Successful Search (

P
SS

) and minimizing the Probability of False Search (

P
FS

), in a bounded search region of interest. The search objectives are functions of unknown sensor locations (represented parametrically by a probability density function), given sensor performance parameters, statistical priors on target behavior, and distributed detection criteria. Numerical examples illustrating the utility of this approach for varying target behaviors are given.
Direct posterior confidence for out-of-vocabulary spoken term detection
Authors: Wang Dong , King Simon , Frankel Joe , Vipperla Ravichander , Evans Nicholas , Troncy Raphaël
Published: September 2012

Spoken term detection (STD) is a key technology for spoken information retrieval. As compared to the conventional speech transcription and keyword spotting, STD is an open-vocabulary task and has to address out-of-vocabulary (OOV) terms. Approaches based on subword units, for example phones, are widely used to solve the OOV issue; however, performance on OOV terms is still substantially inferior to that of in-vocabulary (INV) terms. The performance degradation on OOV terms can be attributed to a multitude of factors. One particular factor we address in this article is the unreliable confidence estimation caused by weak acoustic and language modeling due to the absence of OOV terms in the training corpora. We propose a direct posterior confidence derived from a discriminative model, such as multilayer perceptron (MLP). The new confidence considers a wide-range acoustic context which is usually important for speech recognition and retrieval; moreover, it localizes on detected speech segments and therefore avoids the impact of long-span word context which is usually unreliable for OOV term detection.

In this article, we first develop an extensive discussion about the modeling weakness problem associated with OOV terms, and then propose our approach to address this problem based on direct poster confidence. Our experiments carried out on spontaneous and conversational multiparty meeting speech, demonstrate that the proposed technique provides a significant improvement in STD performance as compared to conventional lattice-based confidence, in particular for OOV terms. Furthermore, the new confidence estimation approach is fused with other advanced techniques for OOV treatment, such as stochastic pronunciation modeling and discriminative confidence normalization. This leads to an integrated solution for OOV term detection that results in a large performance improvement.
The nonverbal structure of patient case discussions in multidisciplinary medical team meetings
Authors: Luz Saturnino
Published: September 2012

Meeting analysis has a long theoretical tradition in social psychology, with established practical ramifications in computer science, especially in computer supported cooperative work. More recently, a good deal of research has focused on the issues of indexing and browsing multimedia records of meetings. Most research in this area, however, is still based on data collected in laboratories, under somewhat artificial conditions. This article presents an analysis of the discourse structure and spontaneous interactions at real-life multidisciplinary medical team meetings held as part of the work routine in a major hospital. It is hypothesized that the conversational structure of these meetings, as indicated by sequencing and duration of vocalizations, enables segmentation into individual patient case discussions. The task of segmenting audio-visual records of multidisciplinary medical team meetings is described as a topic segmentation task, and a method for automatic segmentation is proposed. An empirical evaluation based on hand labelled data is presented, which determines the optimal length of vocalization sequences for segmentation, and establishes the competitiveness of the method with approaches based on more complex knowledge sources. The effectiveness of Bayesian classification as a segmentation method, and its applicability to meeting segmentation in other domains are discussed.
Sibyl, a factoid question-answering system for spoken documents
Authors: Comas Pere R. , Turmo Jordi , Màrquez Lluís
Published: September 2012

In this article, we present a factoid question-answering system, Sibyl, specifically tailored for question answering (QA) on spoken-word documents. This work explores, for the first time, which techniques can be robustly adapted from the usual QA on written documents to the more difficult spoken document scenario. More specifically, we study new information retrieval (IR) techniques designed or speech, and utilize several levels of linguistic information for the speech-based QA task. These include named-entity detection with phonetic information, syntactic parsing applied to speech transcripts, and the use of coreference resolution. Sibyl is largely based on supervised machine-learning techniques, with special focus on the answer extraction step, and makes little use of handcrafted knowledge. Consequently, it should be easily adaptable to other domains and languages. Sibyl and all its modules are extensively evaluated on the European Parliament Plenary Sessions English corpus, comparing manual with automatic transcripts obtained by three different automatic speech recognition (ASR) systems that exhibit significantly different word error rates. This data belongs to the CLEF 2009 track for QA on speech transcripts. The main results confirm that syntactic information is very useful for learning to rank question candidates, improving results on both manual and automatic transcripts, unless the ASR quality is very low. At the same time, our experiments on coreference resolution reveal that the state-of-the-art technology is not mature enough to be effectively exploited for QA with spoken documents. Overall, the performance of Sibyl is comparable or better than the state-of-the-art on this corpus, confirming the validity of our approach.
RapidRadio
Authors: Surís Jorge A. , Recio Adolfo , Athanas Peter
Published: September 2012

In this article, the RapidRadio framework for signal classification and receiver deployment is discussed. The framework is a productivity-enhancing tool that reduces the required knowledge base for implementing a receiver on an FPGA-based SDR platform. The ultimate objective of this framework is to identify unknown signals and to build FPGA-based receivers capable of receiving them. RapidRadio divides the process of radio creation into two phases; the analysis phase and radio synthesis phase. The analysis phase guides the user through the process of classifying an unknown signal and determining its modulation scheme and parameters, resulting in a radio receiver model. In the second phase, this model is transformed into a functional receiver in an FPGA-based platform.
Hierarchical Benchmark Circuit Generation for FPGA Architecture Evaluation
Authors: Mark Cindy , Chin Scott Y. L. , Shannon Lesley , Wilton Steven J. E.
Published: September 2012

We describe a stochastic circuit generator that can be used to automatically create benchmark circuits for use in FPGA architecture studies. The circuits consist of a hierarchy of interconnected modules, reflecting the structure of circuits designed using a system-on-chip design flow. Within each level of hierarchy, modules can be connected in a bus, star, or dataflow configuration. Our circuit generator is calibrated based on a careful study of existing system-on-chip circuits. We show that our benchmark circuits lead to more realistic architectural conclusions than circuits generated using previous generators.
RCML
Authors: Reardon Casey , Holland Brian , George Alan D. , Stitt Greg , Lam Herman
Published: September 2012

Reconfigurable computing (RC) is emerging as a promising area for embedded computing, in which complex systems must balance performance, flexibility, cost, and power. The difficulty associated with RC development suggests improved strategic planning and analysis techniques can save significant development time and effort. This article presents a new abstract modeling language and environment, the RC Modeling Language (RCML), to facilitate efficient design space exploration of RC systems at the estimation modeling level, that is, before building a functional implementation. Two integrated analysis tools and case studies, one analytical and one simulative, are presented illustrating relatively accurate automated analysis of systems modeled in RCML.
Architecture Optimization of Application-Specific Implicit Instructions
Authors: Di Biagio Andrea , Agosta Giovanni , Sykora Martino , Silvano Cristina
Published: September 2012

Dynamic configuration of application-specific implicit instructions has been proposed to better exploit the available parallelism at the instruction level in pipelined processors. The support of such implicit instruction issue-requires the pipeline to be extended with a trigger table that describes the instruction implicitly issued as a response to a value written into a triggering register by a triggering instruction (which may be an add or sub instruction). In this article, we explore the design optimization of the trigger table to maximize the number of instructions that can be implicitly issued while keeping the limited size of the trigger table. The concept of implicitly issued instruction has been formally defined by considering the inter-basic block analysis of control and data dependencies. A compilation tool chain has been developed to automatically identify the optimization opportunities, taking into account the constraints imposed by control and data dependencies as well as by architectural limitations. The proposed solutions have been applied to the case of a baseline scalar MIPS processor where, for the selected set of benchmarks (DSPStone and Mibench/automotive), we obtained an average speedup of 17%.
Automatic Segmentation and Recognition in Body Sensor Networks Using a Hidden Markov Model
Authors: Guenterberg Eric , Ghasemzadeh Hassan , Jafari Roozbeh
Published: September 2012

One important application of body sensor networks is action recognition. Action recognition often implicitly requires partitioning sensor data into intervals, then labeling the partitions according to the action that each represents or as a non-action. The temporal partitioning stage is called segmentation, and the labeling is called classification. While many effective methods exist for classification, segmentation remains problematic. We present a technique inspired by continuous speech recognition that combines segmentation and classification using hidden Markov models. This technique is distributed across several sensor nodes. We show the results of this technique and the bandwidth savings over full data transmission.
KNOWME
Authors: Thatte Gautam , Li Ming , Lee Sangwon , Emken Adar , Narayanan Shrikanth , Mitra Urbashi , Spruijt-Metz Donna , Annavaram Murali
Published: September 2012

The use of biometric sensors for monitoring an individual’s health and related behaviors, continuously and in real time, promises to revolutionize healthcare in the near future. In an effort to better understand the complex interplay between one’s medical condition and social, environmental, and metabolic parameters, this article presents the
KNOWME
platform, a complete, end-to-end, body area sensing system that integrates off-the-shelf biometric sensors with a Nokia N95 mobile phone to continuously monitor the metabolic signals of a subject. With a current focus on pediatric obesity, KNOWME employs metabolic signals to monitor and evaluate physical activity. KNOWME development and in-lab deployment studies have revealed three major challenges: (1) the need for robustness to highly varying operating environments due to subject-induced variability, such as mobility or sensor placement; (2) balancing the tension between achieving high fidelity data collection and minimizing network energy consumption; and (3) accurate physical activity detection using a modest number of sensors. The KNOWME platform described herein directly addresses these three challenges. Design robustness is achieved by creating a three-tiered sensor data collection architecture. The system architecture is designed to provide robust, continuous, multichannel data collection and scales without compromising normal mobile device operation. Novel physical activity detection methods which exploit new representations of sensor signals provide accurate and efficient physical activity detection. The physical activity detection method employs personalized training phases and accounts for intersession variability. Finally, exploiting the features of the hardware implementation, a low-complexity sensor sampling algorithm is developed, resulting in significant energy savings without loss of performance.
Application-Focused Energy-Fidelity Scalability for Wireless Motion-Based Health Assessment
Authors: Hanson Mark A. , Powell Harry C. , Barth Adam T. , Lach John
Published: September 2012

Energy-fidelity trade-offs are central to the performance of many technologies, but they are essential in wireless body area sensor networks (BASNs) due to severe energy and processing constraints and the critical nature of certain healthcare applications. On-node signal processing and compression techniques can save energy by greatly reducing the amount of data transmitted over the wireless channel, but lossy techniques, capable of high compression ratios, can incur a reduction in application fidelity. In order to maximize system performance, these trade-offs must be considered at runtime due to the dynamic nature of BASN applications, including sensed data, operating environments, user actuation, etc. BASNs therefore require energy-fidelity scalability, so automated and user-initiated trade-offs can be made dynamically. This article presents a data rate scalability framework within a motion-based health application context which demonstrates the design of efficient and efficacious wireless health systems.
Verification of Safety and Liveness Properties of Metric Transition Systems
Authors: Girard Antoine , Zheng Gang
Published: September 2012

We consider verification problems for transition systems enriched with a metric structure. We believe that these metric transition systems are particularly suitable for the analysis of cyber-physical systems in which metrics can be naturally defined on the numerical variables of the embedded software and on the continuous states of the physical environment. We consider verification of bounded and unbounded safety properties, as well as bounded liveness properties. The transition systems we consider are nondeterministic, finitely branching, and with a finite set of initial states. Therefore, bounded safety/liveness properties can always be verified by exhaustive exploration of the system trajectories. However, this approach may be intractable in practice, as the number of trajectories usually grows exponentially with respect to the considered bound. Furthermore, since the system we consider can have an infinite set of states, exhaustive exploration cannot be used for unbounded safety verification. For bounded safety properties, we propose an algorithm which combines exploration of the system trajectories and state space reduction using merging based on a bisimulation metric. The main novelty compared to an algorithm presented recently by Lerda et al. [2008] consists in introducing a tuning parameter that improves the performance drastically. We also establish a procedure that allows us to prove unbounded safety from the result of the bounded safety algorithm via a refinement step. We then adapt the algorithm to handle bounded liveness verification. Finally, the effectiveness of the approach is demonstrated by applying it to the analysis of implementations of an embedded control loop.
A taxonomy and survey of SCTP research
Authors: Budzisz Łukasz , Garcia Johan , Brunstrom Anna , Ferrús Ramon
Published: September 2012

The Stream Control Transmission Protocol (SCTP) is a relatively recent general-purpose transport layer protocol for IP networks that has been introduced as a complement to the well-established TCP and UDP transport protocols. Although initially conceived for the transport of PSTN signaling messages over IP networks, the introduction of key features in SCTP, such as multihoming and multistreaming, has spurred considerable research interest surrounding SCTP and its applicability to different networking scenarios. This article aims to provide a detailed survey of one of these new features—multihoming—which, as it is shown, is the subject of evaluation in more than half of all published SCTP-related articles. To this end, the article first summarizes and organizes SCTP-related research conducted so far by developing a four-dimensional taxonomy reflecting the (1) protocol feature examined, (2) application area, (3) network environment, and (4) study approach. Over 430 SCTP-related publications have been analyzed and classified according to the proposed taxonomy. As a result, a clear perspective on this research area in the decade since the first protocol standardization in 2000 is given, covering both current and future research trends. On continuation, a detailed survey of the SCTP multihoming feature is provided, examining possible applications of multihoming, such as robustness, handover support, and loadsharing.
A survey of adaptive services to cope with dynamics in wireless self-organizing networks
Authors: Sengul Cigdem , Viana Aline Carneiro , Ziviani Artur
Published: September 2012

In this article, we consider different types of wireless networks that benefit from and, in certain cases, require self-organization. Taking mobile ad hoc, wireless sensor, wireless mesh, and delay-tolerant networks as examples of wireless self-organizing networks (WSONs), we identify that the common challenges these networks face are mainly due to lack of centralized management, device heterogeneity, unreliable wireless communication, mobility, resource constraints, or the need to support different traffic types. In this context, we survey several adaptive services proposed to handle these challenges. In particular, we group the adaptive services as core services and network-level services. By categorizing different types of services that handle adaptation and the types of adaptations, we intend to provide useful design guidelines for achieving self-organizing behavior in network protocols. Finally, we discuss open research problems to encourage the design of novel protocols for WSONs.
A survey of context data distribution for mobile ubiquitous systems
Authors: Bellavista Paolo , Corradi Antonio , Fanelli Mario , Foschini Luca
Published: September 2012

The capacity to gather and timely deliver to the service level any relevant information that can characterize the service-provisioning environment, such as computing resources/capabilities, physical device location, user preferences, and time constraints, usually defined as context-awareness, is widely recognized as a core function for the development of modern ubiquitous and mobile systems. Much work has been done to enable context-awareness and to ease the diffusion of context-aware services; at the same time, several middleware solutions have been designed to transparently implement context management and provisioning in the mobile system. However, to the best of our knowledge, an in-depth analysis of the context data distribution, namely, the function in charge of distributing context data to interested entities, is still missing. Starting from the core assumption that only effective and efficient context data distribution can pave the way to the deployment of truly context-aware services, this article aims at putting together current research efforts to derive an original and holistic view of the existing literature. We present a unified architectural model and a new taxonomy for context data distribution by considering and comparing a large number of solutions. Finally, based on our analysis, we draw some of the research challenges still unsolved and identify some possible directions for future work.
On the stability of interdomain routing
Authors: Cittadini Luca , Battista Giuseppe Di , Rimondini Massimo
Published: September 2012

Most routing protocols guarantee convergence to a stable routing state. That is, in the absence of topology or configuration changes, each router will eventually find a stable route to any destination. However, this is not the case for policy-based routing protocols, for example, the BGP protocol used as a
de facto
standard for interdomain routing.

The interaction of not-so-complex BGP configurations can cause permanent oscillations of routing. Several models and algorithms have been proposed in the literature to study routing oscillations. This article surveys state-of-the-art contributions in this field, with a special emphasis on algorithmic and combinatorial aspects.
Stacking Model-Based Korean Prosodic Phrasing Using Speaker Variability Reduction and Linguistic Feature Engineering
Authors: Lee Jinsik , Lee Sungjin , Lee Jonghoon , Kim Byeongchang , Lee Gary Geunbae
Published: September 2012

This article presents a prosodic phrasing model for a general purpose Korean speech synthesis system. To reflect the factors affecting prosodic phrasing in the model, linguistically motivated machine-learning features were investigated. These features were effectively incorporated using a stacking model. The phrasing performance was also improved through feature engineering. The corpus used in the experiment is a 4,392-sentence corpus (55,015 words with an average of 13 words per sentence). Because the corpus contains speaker-dependent variability and such variability is not appropriately reflected in a general purpose speech synthesis system, a method to reduce such variability is proposed. In addition, the entire set of data used in the experiment is provided to the public for future use in comparative research.
Cross-Language Latent Relational Search between Japanese and English Languages Using a Web Corpus
Authors: Duc Nguyen Tuan , Bollegala Danushka , Ishizuka Mitsuru
Published: September 2012

Latent relational search is a novel entity retrieval paradigm based on the proportional analogy between two entity pairs. Given a latent relational search query {(Japan, Tokyo), (France, ?)}, a latent relational search engine is expected to retrieve and rank the entity “Paris” as the first answer in the result list. A latent relational search engine extracts entities and relations between those entities from a corpus, such as the Web. Moreover, from some supporting sentences in the corpus, (e.g., “Tokyo is the capital of Japan” and “Paris is the capital and biggest city of France”), the search engine must recognize the relational similarity between the two entity pairs. In cross-language latent relational search, the entity pairs as well as the supporting sentences of the first entity pair and of the second entity pair are in different languages. Therefore, the search engine must recognize similar semantic relations across languages. In this article, we study the problem of cross-language latent relational search between Japanese and English using Web data. To perform cross-language latent relational search in high speed, we propose a multi-lingual indexing method for storing entities and lexical patterns that represent the semantic relations extracted from Web corpora. We then propose a hybrid lexical pattern clustering algorithm to capture the semantic similarity between lexical patterns across languages. Using this algorithm, we can precisely measure the relational similarity between entity pairs across languages, thereby achieving high precision in the task of cross-language latent relational search. Experiments show that the proposed method achieves an MRR of 0.605 on Japanese-English cross-language latent relational search query sets and it also achieves a reasonable performance on the INEX Entity Ranking task.
Entangled queries
Authors: Gupta Nitin , Kot Lucja , Roy Sudip , Bender Gabriel , Gehrke Johannes , Koch Christoph
Published: September 2012

Many data-driven social and Web applications involve collaboration and coordination. The vision of
Declarative Data-Driven Coordination
(D3C), proposed in Kot et al. [2010], is to support coordination in the spirit of data management: to make it data-centric and to specify it using convenient declarative languages. This article introduces
entangled queries
, a language that extends SQL by constraints that allow for the coordinated choice of result tuples across queries originating from different users or applications.

It is nontrivial to define a declarative coordination formalism without arriving at the general (NP-complete) Constraint Satisfaction Problem from AI. In this article, we propose an efficiently enforceable syntactic
safety
condition that we argue is at the sweet spot where interesting declarative power meets applicability in large-scale data management systems and applications. The key computational problem of D3C is to match entangled queries to achieve coordination. We present an efficient matching algorithm which statically analyzes query workloads and merges coordinating entangled queries into compound SQL queries. These can be sent to a standard database system and return only coordinated results. We present the overall architecture of an implemented system that contains our evaluation algorithm. We also describe a proof-of-concept Facebook application we have built on top of this system to allow friends to coordinate flight plans. Finally, we evaluate the performance of the matching algorithm experimentally on realistic coordination workloads.
Foster b-trees
Authors: Graefe Goetz , Kimura Hideaki , Kuno Harumi
Published: September 2012

Foster B-trees are a new variant of B-trees that combines advantages of prior B-tree variants optimized for many-core processors and modern memory hierarchies with flash storage and nonvolatile memory. Specific goals include: (i) minimal concurrency control requirements for the data structure, (ii) efficient migration of nodes to new storage locations, and (iii) support for continuous and comprehensive self-testing. Like B
link
-trees, Foster B-trees optimize latching without imposing restrictions or specific designs on transactional locking, for example, key range locking. Like write-optimized B-trees, and unlike B
link
-trees, Foster B-trees enable large writes on RAID and flash devices as well as wear leveling and efficient defragmentation. Finally, they support continuous and inexpensive yet comprehensive verification of all invariants, including all cross-node invariants of the B-tree structure. An implementation and a performance evaluation show that the Foster B-tree supports high concurrency and high update rates without compromising consistency, correctness, or read performance.