A framework for managing uncertain inputs: An axiomization of rewarding

The success postulate in belief revision ensures that new evidence (input) is always trusted. However, admitting uncertain input has been questioned by many researchers. Darwiche and Pearl argued that strengths of evidence should be introduced to determine the outcome of belief change, and provided a preliminary definition towards this thought. In this paper, we start with Darwiche and Pearl’s idea aiming to develop a framework that can capture the influence of the strengths of inputs with some rational assumptions. To achieve this, we first define epistemic states to represent beliefs attached with strength, and then present a set of postulates to describe the change process on epistemic states that is determined by the strengths of input and establish representation theorems to characterize these postulates. As a result, we obtain a unique rewarding operator which is proved to be a merging operator that is in line with many other works. We also investigate existing postulates on belief merging and compare them with our postulates. In addition, we show that from an epistemic state, a corresponding ordinal conditional function by Spohn can be derived and the result of combining two epistemic states is thus reduced to the result of combining two corresponding ordinal conditional functions proposed by Laverny and Lang. Furthermore, when reduced to the belief revision situation, we prove that our results induce all the Darwiche and Pearl’s postulates as well as the Recalcitrance postulate and the Independence postulate.

Low-cost digital signature architecture suitable for radio frequency identification tags

Continuing achievements in hardware technology are bringing ubiquitous computing closer to reality. The notion of a connected, interactive and autonomous environment is common to all sensor networks, biosystems and radio frequency identification (RFID) devices, and the emergence of significant deployments and sophisticated applications can be expected. However, as more information is collected and transmitted, security issues will become vital for such a fully connected environment. In this study the authors consider adding security features to low-cost devices such as RFID tags. In particular, the authors consider the implementation of a digital signature architecture that can be used for device authentication, to prevent tag cloning, and for data authentication to prevent transmission forgery. The scheme is built around the signature variant of the cryptoGPS identification scheme and the SHA-1 hash function. When implemented on 130 nm CMOS the full design uses 7494 gates and consumes 4.72 mu W of power, making it smaller and more power efficient than previous low-cost digital signature designs. The study also presents a low-cost SHA-1 hardware architecture which is the smallest standardised hash function design to date.

Multimodal Biometric Human Recognition for Perceptual Human-Computer Interaction

In this paper, a novel video-based multimodal biometric verification scheme using the subspace-based low-level feature fusion of face and speech is developed for specific speaker recognition for perceptual human--computer interaction (HCI). In the proposed scheme, human face is tracked and face pose is estimated to weight the detected facelike regions in successive frames, where ill-posed faces and false-positive detections are assigned with lower credit to enhance the accuracy. In the audio modality, mel-frequency cepstral coefficients are extracted for voice-based biometric verification. In the fusion step, features from both modalities are projected into nonlinear Laplacian Eigenmap subspace for multimodal speaker recognition and combined at low level. The proposed approach is tested on the video database of ten human subjects, and the results show that the proposed scheme can attain better accuracy in comparison with the conventional multimodal fusion using latent semantic analysis as well as the single-modality verifications. The experiment on MATLAB shows the potential of the proposed scheme to attain the real-time performance for perceptual HCI applications.

Palmprint Recognition Based on Subspace Analysis of Gabor Filter Bank

This paper introduces a new technique for palmprint recognition based on Fisher Linear Discriminant Analysis (FLDA) and Gabor filter bank. This method involves convolving a palmprint image with a bank of Gabor filters at different scales and rotations for robust palmprint features extraction. Once these features are extracted, FLDA is applied for dimensionality reduction and class separability. Since the palmprint features are derived from the principal lines, wrinkles and texture along the palm area. One should carefully consider this fact when selecting the appropriate palm region for the feature extraction process in order to enhance recognition accuracy. To address this problem, an improved region of interest (ROI) extraction algorithm is introduced. This algorithm allows for an efficient extraction of the whole palm area by ignoring all the undesirable parts, such as the fingers and background. Experiments have shown that the proposed method yields attractive performances as evidenced by an Equal Error Rate (EER) of 0.03%.

Kinematic modeling of Exechon parallel kinematic machine

The studies on PKMs have attracted a great attention to robotics community. By deploying a parallel kinematic structure, a parallel kinematic machine (PKM) is expected to possess the advantages of heavier working load, higher speed, and higher precision. Hundreds of new PKMs have been proposed. However, due to the considerable gaps between the desired and actual performances, the majorities of the developed PKMs were the prototypes in research laboratories and only a few of them have been practically applied for various applications; among the successful PKMs, the Exechon machine tool is recently developed. The Exechon adopts unique over-constrained structure, and it has been improved based on the success of the Tricept parallel kinematic machine. Note that the quantifiable theoretical studies have yet been conducted to validate its superior performances, and its kinematic model is not publically available. In this paper, the kinematic characteristics of this new machine tool is investigated, the concise models of forward and inverse kinematics have been developed. These models can be used to evaluate the performances of an existing Exechon machine tool and to optimize new structures of an Exechon machine to accomplish some specific tasks.

Robust face recognition with partial occlusion, illumination variation and limited training data by optimal feature selection

This study investigates face recognition with partial occlusion, illumination variation and their combination, assuming no prior information about the mismatch, and limited training data for each person. The authors extend their previous posterior union model (PUM) to give a new method capable of dealing with all these problems. PUM is an approach for selecting the optimal local image features for recognition to improve robustness to partial occlusion. The extension is in two stages. First, authors extend PUM from a probability-based formulation to a similarity-based formulation, so that it operates with as little as one single training sample to offer robustness to partial occlusion. Second, they extend this new formulation to make it robust to illumination variation, and to combined illumination variation and partial occlusion, by a novel combination of multicondition relighting and optimal feature selection. To evaluate the new methods, a number of databases with various simulated and realistic occlusion/illumination mismatches have been used. The results have demonstrated the improved robustness of the new methods.

Home curation versus teenage photography: Photo displays in the family home

In this paper we report an empirical study of the photographic portrayal of family members at home. Adopting a social psychological approach and focusing oil intergenerational power dynamics, our research explores the use of domestic photo displays in family representation. Parents and their teenagers from eight families in the south of England were interviewed at home about their interpretations of both stored and displayed photos within the home. Discussions centred on particular photographs found by the participants to portray self and family in different ways. The findings show that public displays of digital photos are still curated by mothers of the households, but with more difficulty and less control all with analogue photos. In addition, teenagers both contribute and comply with this curation within the home, whilst at the same time developing additional ways of presenting their families and themselves online that are 'unsupervised' by the curator. We highlight the conflict of interest that is at play within teen and parent practices and consider the challenges that this presents for supporting the representation of family through the design of photo display technology. (C) 2009 Elsevier Ltd. All rights reserved.

Building Autonomous Sensitive Artificial Listeners

This paper describes a substantial effort to build a real-time interactive multimodal dialogue system with a focus on emotional and non-verbal interaction capabilities. The work is motivated by the aim to provide technology with competences in perceiving and producing the emotional and non-verbal behaviours required to sustain a conversational dialogue. We present the Sensitive Artificial Listener (SAL) scenario as a setting which seems particularly suited for the study of emotional and non- verbal behaviour, since it requires only very limited verbal understanding on the part of the machine. This scenario allows us to concentrate on non-verbal capabilities without having to address at the same time the challenges of spoken language understanding, task modeling etc. We first report on three prototype versions of the SAL scenario, in which the behaviour of the Sensitive Artificial Listener characters was determined by a human operator. These prototypes served the purpose of verifying the effectiveness of the SAL scenario and allowed us to collect data required for building system components for analysing and synthesising the respective behaviours. We then describe the fully autonomous integrated real-time system we created, which combines incremental analysis of user behaviour, dialogue management, and synthesis of speaker and listener behaviour of a SAL character displayed as a virtual agent. We discuss principles that should underlie the evaluation of SAL-type systems. Since the system is designed for modularity and reuse, and since it is publicly available, the SAL system has potential as a joint research tool in the affective computing research community.

Polyopes lancifolius (Halymeniales, Rhodophyta), a new component of the Japanese marine flora introduced to Europe

Polyopes lancifolius (Harvey) S. Kawaguchi & H.W. Wang has been recorded for the first time in Europe, during the summer or 2008. A small population was discovered in the Gulf of Morbihan (northeast Atlantic, France). This is the first observation of P. lancifolius outside its native range. Vegetative and reproductive morphological features are compared with previous descriptions. rbcL sequences show no divergence from Japanese populations. Imports of Pacific oysters Crassostrea gigas (Thunberg 1793) are likely to be responsible for its accidental introduction into the Gulf of Morbihan, either directly from northwest Pacific regions or indirectly (secondary dispersal) by transfers from another European oyster farming site. The history of previous algal introductions from Japan suggests that if it becomes successfully established at Morbihan, the species is likely to spread to other European coastal areas.

Universal power-law diet partitioning by marine fish and squid with surprising stability–diversity implications

A central question in community ecology is how the number of trophic links relates to community species richness. For simple dynamical food-web models, link density (the ratio of links to species) is bounded from above as the number of species increases; but empirical data suggest that it increases without bounds. We found a new empirical upper bound on link density in large marine communities with emphasis on fish and squid, using novel methods that avoid known sources of bias in traditional approaches. Bounds are expressed in terms of the diet-partitioning function (DPF): the average number of resources contributing more than a fraction f to a consumer's diet, as a function of f. All observed DPF follow a functional form closely related to a power law, with power-law exponents indepen- dent of species richness at the measurement accuracy. Results imply universal upper bounds on link density across the oceans. However, the inherently scale-free nature of power-law diet partitioning suggests that the DPF itself is a better defined characterization of network structure than link density.

The Movebank data model for animal tracking

Studies of animal movement are rapidly increasing as tracking technologies make it possible to collect more data of a larger variety of species. Comparisons of animal movement across sites, times, or species are key to asking questions about animal adaptation, responses to climate and land-use change. Thus, great gains can be made by sharing and exchanging animal tracking data. Here we present an animal movement data model that we use within the Movebank web application to describe tracked animals. The model facilitates data comparisons across a broad range of taxa, study designs, and technologies, and is based on the scientific questions that could be addressed with the data.

Low power field programmable gate array implementation of fast digital signal processing algorithms: characterisation and manipulation of data locality

Dynamic power consumption is very dependent on interconnect, so clever mapping of digital signal processing algorithms to parallelised realisations with data locality is vital. This is a particular problem for fast algorithm implementations where typically, designers will have sacrificed circuit structure for efficiency in software implementation. This study outlines an approach for reducing the dynamic power consumption of a class of fast algorithms by minimising the index space separation; this allows the generation of field programmable gate array (FPGA) implementations with reduced power consumption. It is shown how a 50% reduction in relative index space separation results in a measured power gain of 36 and 37% over a Cooley-Tukey Fast Fourier Transform (FFT)-based solution for both actual power measurements for a Xilinx Virtex-II FPGA implementation and circuit measurements for a Xilinx Virtex-5 implementation. The authors show the generality of the approach by applying it to a number of other fast algorithms namely the discrete cosine, the discrete Hartley and the Walsh-Hadamard transforms.