Intelligent indexing of crime scene photographs

The Scene of Crime Information System's automatic image-indexing prototype goes beyond extracting keywords and syntactic relations from captions. The semantic information it gathers gives investigators an intuitive, accurate way to search a database of cases for specific photographic evidence. Intelligent, automatic indexing and retrieval of crime scene photographs is one of the main functions of SOCIS, our research prototype developed within the Scene of Crime Information System project. The prototype, now in its final development and evaluation phase, applies advanced natural language processing techniques to text-based image indexing and retrieval to tackle crime investigation needs effectively and efficiently

Double-Exchange Ferromagnetism and Orbital-Fluctuation-Induced Superconductivity in Cubic Uranium Compounds

A double-exchange mechanism for the emergence of ferromagnetism in cubic uranium compounds is proposed on the basis of a $j$-$j$ coupling scheme. The idea is {\it orbital-dependent duality} of $5f$ electrons concerning itinerant $\Gamma_8^-$ and localized $\Gamma_7^-$ states in the cubic structure. Since orbital degree of freedom is still active in the ferromagnetic phase, orbital-related quantum critical phenomenon is expected to appear. In fact, odd-parity p-wave pairing compatible with ferromagnetism is found in the vicinity of an orbital ordered phase. Furthermore, even-parity d-wave pairing with significant odd-frequency components is obtained. A possibility to observe such exotic superconductivity in manganites is also discussed briefly.Comment: 4 pages, 4 figures. To appear in J. Phys. Soc. Jp

System Level Trade Study of Hybrid Parallel Propulsion Architectures on Future Regional and Thin Haul Turboprop Aircraft

Presented at the AIAA SCITECH 2023 ForumThis paper evaluates the potential benefits of applying hybrid parallel propulsion architectures to future turboprop aircraft that are expected to enter into service in 2030. Two baseline aircraft models are established by infusing viable 2030 airframe and engine technologies on state-of-the-art 19-passenger and 50-passenger aircraft models. Two parametric parallel hybrid architectures are proposed and applied on both size classes: Architecture 1 has two propellers, each driven by an engine and an electric motor in parallel, and allows in-flight recharging; Architecture 2 has four propellers, each driven by either an engine or an electric motor, and allows parallel operation during the cruise. A design space exploration is conducted on the powertrain design variables and the electric component key performance parameters. A constrained optimization implies that Architecture 1 and 2 can achieve fuel savings of about 2.6% and 6.6%, respectively, given 2030 electric component technology assumptions. Electric taxi consistently results in fuel saving when battery technology is beyond the projected 2030 level. Preliminary sensitivity studies show that the performance of Architecture 2 is more sensitive to the battery technology compared to Architecture 1 due to its extensive use of battery energy during the cruise.NATIONAL INSTITUTE OF AEROSPACE, GR0001018

Evidence for sparse synergies in grasping actions

Converging evidence shows that hand-actions are controlled at the level of synergies and not single muscles. One intriguing aspect of synergy-based action-representation is that it may be intrinsically sparse and the same synergies can be shared across several distinct types of hand-actions. Here, adopting a normative angle, we consider three hypotheses for hand-action optimal-control: sparse-combination hypothesis (SC) – sparsity in the mapping between synergies and actions - i.e., actions implemented using a sparse combination of synergies; sparse-elements hypothesis (SE) – sparsity in synergy representation – i.e., the mapping between degrees-of-freedom (DoF) and synergies is sparse; double-sparsity hypothesis (DS) – a novel view combining both SC and SE – i.e., both the mapping between DoF and synergies and between synergies and actions are sparse, each action implementing a sparse combination of synergies (as in SC), each using a limited set of DoFs (as in SE). We evaluate these hypotheses using hand kinematic data from six human subjects performing nine different types of reach-to-grasp actions. Our results support DS, suggesting that the best action representation is based on a relatively large set of synergies, each involving a reduced number of degrees-of-freedom, and that distinct sets of synergies may be involved in distinct tasks

Construction of microscopic model for f-electron systems on the basis of j-j coupling scheme

We construct a microscopic model for f-electron systems, composed of f-electron hopping, Coulomb interaction, and crystalline electric field (CEF) terms. In order to clarify the meaning of one f-electron state, here the j-j coupling scheme is considered, since the spin-orbit interaction is generally large in f-electron systems. Thus, the f-electron state at each site is labelled by $\mu$, namely, the z-component of total angular momentum j. By paying due attention to f-orbital symmetry, the hopping amplitudes between f-electron states are expressed using Slater's integrals. The Coulomb interaction terms among the $\mu$-states are written by Slater-Condon or Racah parameters. Finally, the CEF terms are obtained from the table of Hutchings. The constructed Hamiltonian is regarded as an orbital degenerate Hubbard model, since it includes two pseudo-spin and three pseudo-orbital degrees of freedom. For practical purposes, it is further simplified into a couple of two-orbital models by discarding one of the three orbitals. One of those simplified models is here analyzed using the exact diagonalization method to clarify ground-state properties by evaluating several kinds of correlation functions. Especially, the superconducting pair correlation function in orbital degenerate systems is carefully calculated based on the concept of off-diagonal long-range order. We attempt to discuss a possible relation of the present results with experimental observations for recently discovered heavy fermion superconductors CeMIn$_5$ (M=Ir, Co, and Rh), and a comprehensive scenario to understand superconducting and antiferromagnetic tendencies in the so-called ``115'' materials such as CeMIn$_5$, UMGa$_5$, and PuCoGa$_5$ from the microscopic viewpoint.Comment: 16 pages, Revtex, with 6 figures embedded in the text. Submitted to Phys. Rev.

The POETICON corpus: Capturing language use and sensorimotor experience in everyday interaction

Natural language use, acquisition, and understanding takes place usually in multisensory and multimedia communication environments. Therefore, for one to model language in its interaction and integration with sensorimotor experiences, one needs a representative corpus of such interplay. In this paper, we will present the first corpus of language use and sensorimotor experience recordings in everyday human:human interaction, in which spontaneous language communication has been recorded along with corresponding multiview video recordings, recordings of 3D full body kinematics, and 3D tracking of objects in focus. It is a twelve-hour corpus which comprises of six everyday human:human interaction scenes, each one performed 3 times by 4 different English-speaking couples (interaction between a male and a female actor), each couple acting each scene in two settings: a fully naturalistic setting in which 5-camera multi-view video recordings take place, and a high-tech setting, with full body motion capture for both individuals, a 2-camera multiview video recording, and 3D tracking of focus objects. The corpus has been developed within an EU-funded cognitive systems research project, POETICO

The POETICON enacted scenario corpus: A tool for human and computational experiments on action understanding

A good data corpus lies at the heart of progress in both perceptual/cognitive science and in computer vision. While there are a few datasets that deal with simple actions, creating a realistic corpus for complex, long action sequences that contains also human-human interactions has so far not been attempted to our knowledge. Here, we introduce such a corpus for (inter)action understanding that contains six everyday scenarios taking place in a kitchen / living-room setting. Each scenario was acted out several times by different pairs of actors and contains simple object interactions as well as spoken dialogue. In addition, each scenario was first recorded with several HD cameras and also with motion-capturing of the actors and several key objects. Having access to the motion capture data allows not only for kinematic analyses, but also allows for the production of realistic animations where all aspects of the scenario can be fully controlled. We also present results from a first series of perceptual experiments that show how humans are able to infer scenario classes, as well as individual actions and objects from computer animations of everyday situations. These results can serve as a benchmark for future computational approaches that begin to take on complex action understanding

Quality Evaluation of Computational Models for Movie Summarization

Abstract-In this paper we present a movie summarization system and we investigate what composes high quality movie summaries in terms of user experience evaluation. We propose state-of-the-art audio, visual and text techniques for the detection of perceptually salient events from movies. The evaluation of such computational models is usually based on the comparison of the similarity between the system-detected events and some ground-truth data. For this reason, we have developed the MovSum movie database, which includes sensory and semantic saliency annotation as well as cross-media relations, for objective evaluations. The automatically produced movie summaries were qualitatively evaluated, in an extensive human evaluation, in terms of informativeness and enjoyability accomplishing very high ratings up to 80% and 90%, respectively, which verifies the appropriateness of the proposed methods

Understanding Objects and Actions: a VR Experiment

The human capability to interpret actions and to recognize objects is still far ahead of that of any technical system. Thus, a deeper understanding of how humans are able to interpret human (inter)actions lies at the core of building better artificial cognitive systems. Here, we present results from a first series of perceptual experiments that show how humans are able to infer scenario classes, as well as individual actions and objects from computer animations of everyday situations. The animations were created from a unique corpus of real-life recordings made in the European project POETICON using motion-capture technology and advanced VR programming that allowed for full control over all aspects of the finally rendered data