Deception detection through automatic, unobtrusive analysis of nonverbal behavior

Every day, hundreds of thousands of people pass through airport security checkpoints, border crossing stations, or other security screening measures. Security professionals must sift through countless interactions and ferret out high-risk individuals who represent a danger to other citizens. During each interaction, the security professional must decide whether the individual is being forthright or deceptive. This task is difficult because of the limits of human vigilance and perception and the small percentage of individuals who actually harbor hostile intent. Our research initiative is based on a behavioral approach to deception detection. We attempted to build an automated system that can infer deception or truthfulness from a set of features extracted from head and hands movements in a video. A validated and reliable behaviorally based deception analysis system could potentially have great impacts in augmenting humans' abilities to assess credibility. An automated, unobtrusive system identifies behavioral patterns that indicate deception from nonverbal behavioral cues and classifies deception and truth more accurately than many humans.     

An Integrated Approach for the Estimation of Mobile Subscriber Geolocation

The continuous growth of wireless services market, fuels the need for precise location dependent services, leading researchers from academia and industry to reassess existing geolocation methods regarding accuracy and availability of position estimation. The proposed method for mobile subscriber geolocation utilizes key concepts from estimation theory and specifically the Kalman filter algorithm to determine an optimal estimate on the actual system state (which primarily includes location, velocity) based on the observations acquired by employing network- or terminal-based techniques, which are briefly presented and assessed thereafter. Given the proven limitations of individual techniques, the alternative strategies for fusion of data are outlined, the details of the operation of a fusion scheme based on the Kalman filter are discussed and the impact of the proposed work over conventional methodologies is quantified.     

Tesile toughness of microcellular foams of polystyrene,styrene-acrylonitrile copolymer,and polycarbonate,and the effect of dissolved gas on the tensile toughness of the same polymer matrices and microcellular foams

This paper reports on the tensile properties of microcellular foams of three different thermoplastics, since there have been several reports in the literature, but with indefinite conclusions so far, that microbubbles act in a manner similar to rubber particles in toughening thermoplastics. Polystyrene (PS), styreneacrylonitrile copolymer (SAN), and polycarbonate (PC), were selected based on their different intrinsic ductilities. The gas supersaturation technique was used to generate samples with microbubbles. The effect of the presence of microbubbles inside the polymer matrix was separated from the effects of the pressure and thermal history experienced by the samples. Nitrogen gas dissolved into PS, and to a lesser extent into SAN, caused and increase of the tensile toughness, but this increased decayed with time as nitrogen gas diffused out of the samples. Furthermore, microcellularly foamed PS samples showed some limited improvement in terms of tensile toughness after all the nitrogen gas diffused out. SAN and PC showed deterioration of the tensile toughness in the presence of microbubbles.     

Qualitative representation of spatial knowledge in two-dimensional space

Various relation-based systems, concerned with the qualitative representation and processing of spatial knowledge, have been developed in numerous application domains. In this article, we identify the common concepts underlying qualitative spatial knowledge representation, we compare the representational properties of the different systems, and we outline the computational tasks involved in relation-based spatial information processing. We also describesymbolic spatial indexes, relation-based structures that combine several ideas in spatial knowledge representation. A symbolic spatial index is an array that preserves only a set of spatial relations among distinct objects in an image, called the modeling space; the index array discards information, such as shape and size of objects, and irrelevant spatial relations. The construction of a symbolic spatial index from an input image can be thought of as a transformation that keeps only a set of representative points needed to define the relations of the modeling space. By keeping the relative arrangements of the representative points in symbolic spatial indexes and discarding all other points, we maintain enough information to answer queries regarding the spatial relations of the modeling space without the need to access the initial image or an object database. Symbolic spatial indexes can be used to solve problems involving route planning, composition of spatial relations, and update operations.     

Analysis of left ventricular wall motion based on volumetric deformable models and MRI-SPAMM

We present a new approach for the analysis of the left ventricular shape and motion based on the development of a new class of volumetric deformable models. We estimate the deformation and complex motion of the left ventricle (LV) in terms of a few parameters that are functions and whose values vary locally across the LV. These parameters capture the radial and longitudinal contraction, the axial twisting, and the long-axis deformation. Using Lagrangian dynamics and finite-element theory, we convert these volumetric primitives into dynamic models that deform due to forces exerted by the datapoints. We present experiments where we used magnetic tagging (MRI-SPAMM) to acquire datapoints from the LV during systole. By applying our method to MRI-SPAMM datapoints, we were able to characterize the 3-D shape and motion of the LV both locally and globally, in a clinically useful way. In addition, based on the model parameters we were able to extract quantitative differences between normal and abnormal hearts and visualize them in a way that is useful to physicians.     

Efficient Management of Persistent Knowledge

Although computer speed has steadily increased and memory is getting cheaper, the need for storage managers to deal efficiently with applications that cannot be held into main memory is vital. Dealing with large quantities of clauses implies the use of persistent knowledge and thus, indexing methods are essential to access efficiently the subset of clauses relevant to answering a query. We introduce PerKMan, a storage manager that uses G-trees, and aims at efficient manipulation of large amounts of persistent knowledge. PerKMan may be connected to Prolog systems that offer an external C language interface. As well as the fact that the storage manager allows different arguments of a predicate to share a common index dimension in a novel manner, it indexes rules and facts in the same manner. PerKMan handles compound terms efficiently and its data structures adapt their shape to large dynamic volumes of clauses, no matter what the distribution. The storage manager achieves fast clause retrieval and reasonable use of disk space.     

Effect of Density and Processing Conditions on Oxide Transformations and Mechanical Properties in Cr–Mo-Alloyed PM steels

To improve the mechanical properties and performances of water-atomized powder metallurgy steels, it is necessary to enhance the density. Consolidating water-atomized steel powders via conventional pressing and sintering to a relative density level > 95 pct involves processing challenges. Consolidation of gas-atomized powders to full density by hot isostatic pressing (HIP) is an established process route but utilizing water-atomized powders in HIP involves challenges that result in the formation of prior particle boundaries due to higher oxygen content. In this study, the effect of density and processing conditions on the oxide transformations and mechanical properties from conventional press and sintering, and HIP are evaluated. Hence, water-atomized Cr–Mo-alloyed powder is used and consolidated into different density levels between 6.8 and 7.3 g cm⁻³ by conventional die pressing and sintering. Fully dense material produced through HIP is evaluated not only of mechanical properties but also for microstructural and fractographic analysis. An empirical model based on power law is fitted to the sintered material properties to estimate and predict the properties up to full density at different sintering conditions. A model describing the mechanism of oxide transformation during sintering and HIP is proposed. The challenges when it comes to the HIP of water-atomized powder are addressed and the requirements for successful HIP processing are discussed.

     

An online color naming experiment in Russian using Munsell color samples

Russian color naming was explored in a web‐based experiment. The purpose was 3‐fold: to examine (1) CIELAB coordinates of centroids for 12 Russian basic color terms (BCTs), including 2 Russian terms for “blue”, sinij “dark blue”, and goluboj “light blue”, and compare these with coordinates for the 11 English BCTs obtained in earlier studies; (2) frequent nonBCTs; and (3) gender differences in color naming. Native Russian speakers participated in the experiment using an unconstrained color‐naming method. Each participant named 20 colors, selected from 600 colors densely sampling the Munsell Color Solid. Color names and response times of typing onset were registered. Several deviations between centroids of the Russian and English BCTs were found. The 2 “Russian blues”, as expected, divided the BLUE area along the lightness dimension; their centroids deviated from a centroid of English blue. Further minor departures were found between centroids of Russian and English counterparts of “brown” and “red”. The Russian color inventory confirmed the linguistic refinement of the PURPLE area, with high frequencies of nonBCTs. In addition, Russian speakers revealed elaborated naming strategies and use of a rich inventory of nonBCTs. Elicitation frequencies of the 12 BCTs were comparable for both genders; however, linguistic segmentation of color space, employing a synthetic observer, revealed gender differences in naming colors, with more refined naming of the “warm” colors from females. We conclude that, along with universal perceptual factors, that govern categorical partition of color space, Russian speakers’ color naming reflects language‐specific factors, supporting the weak relativity hypothesis.