Shape-based detail-preserving exaggeration of extremely accurate 3D faces

We present an approach to automatically exaggerate the distinctive features of extremely detailed 3D faces. These representations comprise several million triangles and capture skin detail down to the pores. Despite their high level of realism, their size makes visualization difficult and real-time mesh manipulation infeasible. The premise of our methodology is to first remove the detail to obtain low resolution shape information, then perform shape-based exaggeration on a low resolution model and finally reapply the detail onto the exaggeration to recover the original resolution. We also present the results of applying this methodology to a small set of faces.     

Parallel bisecting <Emphasis Type="Italic">k</Emphasis>-means with prediction clustering algorithm

In this paper, we propose a new parallel clustering algorithm, named Parallel Bisecting k-means with Prediction (PBKP), for message-passing multiprocessor systems. Bisecting k-means tends to produce clusters of similar sizes, and according to our experiments, it produces clusters with smaller entropy (i.e., purer clusters) than k-means does. Our PBKP algorithm fully exploits the data-parallelism of the bisecting k-means algorithm, and adopts a prediction step to balance the workloads of multiple processors to achieve a high speedup. We implemented PBKP on a cluster of Linux workstations and analyzed its performance. Our experimental results show that the speedup of PBKP is linear with the number of processors and the number of data points. Moreover, PBKP scales up better than the parallel k-means with respect to the dimension and the desired number of clusters. This research was supported in part by AFRL/Wright Brothers Institute (WBI).     

Managing Role-Based Access Control Policies for Grid Databases in OGSA-DAI Using CAS

In this paper, we present a role-based access control method for accessing databases through the Open Grid Services Architecture – Data Access and Integration (OGSA-DAI) framework. OGSA-DAI is an efficient Grid-enabled middleware implementation of interfaces and services to access and control data sources and sinks. However, in OGSA-DAI, access control causes substantial administration overhead for resource providers in virtual organizations (VOs) because each of them has to manage a role-map file containing authorization information for individual Grid users. To solve this problem, we used the Community Authorization Service (CAS) provided by the Globus Toolkit to support the role-based access control (RBAC) within OGSA-DAI. CAS uses the Security Assertion Markup Language (SAML). Our method shows that CAS can support a wide range of security policies using role-privileges, role hierarchies, and constraints. The resource providers need to maintain only the mapping information from VO roles to local database roles and the local policies in the role-map files, so that the number of entries in the role-map file is reduced dramatically. Also, unnecessary authentication, mapping and connections can be avoided by denying invalid requests at the VO level. Thus, our access control method provides increased manageability for a large number of users and reduces day-to-day administration tasks of the resource providers, while they maintain the ultimate authority over their resources. Performance analysis shows that our method adds very little overhead to the existing security infrastructure of OGSA-DAI.     

LTCC‐based monolithic system‐in‐package (SiP) module for millimeter‐wave applications

A miniature LTCC system‐in‐package (SiP) module has been presented for millimeter‐wave applications. A typical heterodyne 61 GHz transmitter (Tx) has been designed and fabricated in a type of the SiP module as small as 36 × 12 × 0.9 mm³. Five active chips including a mixer, driver amplifier, power amplifier, and two frequency multipliers were mounted on the single LTCC package substrate, in which all passive circuits such as a stripline (SL) BPF, 2 × 2 array patch antenna, surface‐mount technology (SMT) pads, and intermediate frequency (IF) feeding lines have been monolithically embedded by using vertical and planar transitions. The embedded SL BPF shows the center frequency of 60.8 GHz, BW of 4.1%, and insertion loss of 3.74 dB. The gain and 3‐dB beam width of the fabricated 2 × 2 array patch antenna are 7 dBi and 36 degrees, respectively. The assembled LTCC 61 GHz Tx SiP module achieves an output power of 10.2 dBm and an up‐conversion gain of 7.3 dB. Because of the integrated BPF, an isolation level between a local oscillation (LO) and RF signal is below 26.4 dBc and the spurious level is suppressed by lower than 22.4 dBc. By using a 61 GHz receiver (Rx) consisting of off‐the‐shelf modules, wireless communication test was demonstrated by comparing measured IF spectrums at the Tx and Rx part.     

Underdetermined Convolutive Blind Source Separation via Time–Frequency Masking

In this paper, we consider the problem of separation of unknown number of sources from their underdetermined convolutive mixtures via time-frequency (TF) masking. We propose two algorithms, one for the estimation of the masks which are to be applied to the mixture in the TF domain for the separation of signals in the frequency domain, and the other for solving the permutation problem. The algorithm for mask estimation is based on the concept of angles in complex vector space. Unlike the previously reported methods, the algorithm does not require any estimation of the mixing matrix or the source positions for mask estimation. The algorithm clusters the mixture samples in the TF domain based on the Hermitian angle between the sample vector and a reference vector using the well known k -means or fuzzy c -means clustering algorithms. The membership functions so obtained from the clustering algorithms are directly used as the masks. The algorithm for solving the permutation problem clusters the estimated masks by using k-means clustering of small groups of nearby masks with overlap. The effectiveness of the algorithm in separating the sources, including collinear sources, from their underdetermined convolutive mixtures obtained in a real room environment, is demonstrated.     

Conceptual modeling of causal map: Object oriented causal map

This study has been started from question “Is there a methodology that can make causal map comprised of causality as a database by using conceptual modeling method?” In this research, causal map is proposed to represent causal relation by using conceptual modeling method. Therefore, we formalize causality as a cognitive rule to allow us to control changes in the decision making environment. Such causality is embedded in the real world (application domain). And, user (decision maker) use to represent set of causality which decision-makers have retrieved from the set of knowledge or experiences in application domain. Such set of causality that decision-makers possess in their know–how and short (long) term memory are usually formalized by causal map. It is verified for users whether this causal map is helpful in solving their problems. By extending the basis of conceptual modeling theory (ontology theory, classification theory, decomposition theory, and semantic network theory), we introduce a concept of causal entity diagram and address why causal map is needed to analyze a specific domain knowledge for given decision problem solving. Finally, object oriented causal map (O2CM) were employed to verify usefulness of causal map for user (decision maker) in this study.     

Technology application in project-based learning

Project-based learning is a student-centered comprehensive instructional approach where students collectively engage themselves in complex learning tasks. Recent advances in educational technologies have made student-centered learning in a technology rich environment both possible and feasible. This paper will report part of a larger study carried out at a school in the United States of America on the use ofconstructivism and technology in project-based learning. Data collection techniques included those typically associated with qualitative field research. In this paper, the technological infrastructure of the school and how technology is used in one of the project-based learning classes will be provided. Based on this study, some suggestions are also provided on how technology can be used in the context of other countries including in Malaysia.     

Extraction of enhanced evoked potentials using wavelet filtering

In order to remove physiological artefacts and gain the improved evoked potentials, we propose a filtering method using the multi-resolution wavelet transform. The wavelet transform is repeatedly performed until all resolution levels are obtained. It decomposes the measured evoked potentials into scale coefficients corresponding to low frequency components and wavelet coefficients corresponding to high frequency components. In the wavelet domain, artefacts are dispersed mainly at the wavelet coefficients rather than the scaling coefficients. Thus, when the inverse wavelet transform is performed, this method shrinks the wavelet coefficients to reduce artefacts with shrinkage functions. By repeatedly performing the inverse wavelet transform, an evoked potential having the reduced artefacts and background noise is obtained. In this study, quantitative evaluation with simulation data and actual clinical data were conducted. As a result, characteristic peaks of evoked potential could be gained removing background EEG and artefacts using suggested shrinkage function. It was improved more than 0.2–1.6Db compared to the conventional averaging method. Also, the system for measuring and analyzing evoked potentials using DSP is implemented.