Why Machines Cannot Feel

For a long time, emotions have been ignored in the attempt to model intelligent behavior. However, within the last years, evidence has come from neuroscience that emotions are an important facet of intelligent behavior being involved into cognitive problem solving, decision making, the establishment of social behavior, and even conscious experience. Also in research communities like software agents and robotics, an increasing number of researchers start to believe that computational models of emotions will be needed to design intelligent systems. Nevertheless, modeling emotions in technical terms poses many difficulties and has often been accounted as just not feasible. In this article, there are identified the main problems, which occur when attempting to implement emotions into machines. By pointing out these problems, it is aimed to avoid repeating mistakes committed when modeling computational models of emotions in order to speed up future development in this area. The identified issues are not derived from abstract reflections about this topic but from the actual attempt to implement emotions into a technical system based on neuroscientific research findings. It is argued that besides focusing on the cognitive aspects of emotions, a consideration of the bodily aspects of emotions—their grounding into a visceral body—is of crucial importance, especially when a system shall be able to learn correlations between environmental objects and events and their “emotional meaning”.     

Nano-texturing of magnetic recording sliders via laser ablation

To increase the storage density of hard disk drives, the flying height of the slider needs to be reduced to <10 nm. This requires super-smooth surfaces of the disk and slider. As the roughness decreases, stiction and adhesion are found to increase substantially leading to failures of the head/disk interface. Texturing the slider surface is a well-known approach to this issue. In this study we investigated laser ablation as a potential process for texturing magnetic recording sliders. It was found that straight laser machining caused unwanted re-deposition of material. These deposits could be significantly reduced by using a chemical etching enhanced laser process.     

Continuous-time quantum Monte Carlo impurity solvers

Continuous-time quantum Monte Carlo impurity solvers are algorithms that sample the partition function of an impurity model using diagrammatic Monte Carlo techniques. The present paper describes codes that implement the interaction expansion algorithm originally developed by Rubtsov, Savkin, and Lichtenstein, as well as the hybridization expansion method developed by Werner, Millis, Troyer, et al. These impurity solvers are part of the ALPS-DMFT application package and are accompanied by an implementation of dynamical mean-field self-consistency equations for (single orbital single site) dynamical mean-field problems with arbitrary densities of states.

Program summary

Program title: dmftCatalogue identifier: AEIL_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIL_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: ALPS LIBRARY LICENSE version 1.1No. of lines in distributed program, including test data, etc.: 899 806No. of bytes in distributed program, including test data, etc.: 32 153 916Distribution format: tar.gzProgramming language: C++Operating system: The ALPS libraries have been tested on the following platforms and compilers:

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  Linux with GNU Compiler Collection (g++ version 3.1 and higher), and Intel C++ Compiler (icc version 7.0 and higher)

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  MacOS X with GNU Compiler (g++ Apple-version 3.1, 3.3 and 4.0)

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  IBM AIX with Visual Age C++ (xlC version 6.0) and GNU (g++ version 3.1 and higher) compilers

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  Compaq Tru64 UNIX with Compq C++ Compiler (cxx)

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  SGI IRIX with MIPSpro C++ Compiler (CC)

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  HP-UX with HP C++ Compiler (aCC)

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  Windows with Cygwin or coLinux platforms and GNU Compiler Collection (g++ version 3.1 and higher)

RAM: 10 MB–1 GBClassification: 7.3External routines: ALPS [1], BLAS/LAPACK, HDF5Nature of problem: (See [2].) Quantum impurity models describe an atom or molecule embedded in a host material with which it can exchange electrons. They are basic to nanoscience as representations of quantum dots and molecular conductors and play an increasingly important role in the theory of “correlated electron” materials as auxiliary problems whose solution gives the “dynamical mean field” approximation to the self-energy and local correlation functions.Solution method: Quantum impurity models require a method of solution which provides access to both high and low energy scales and is effective for wide classes of physically realistic models. The continuous-time quantum Monte Carlo algorithms for which we present implementations here meet this challenge. Continuous-time quantum impurity methods are based on partition function expansions of quantum impurity models that are stochastically sampled to all orders using diagrammatic quantum Monte Carlo techniques. For a review of quantum impurity models and their applications and of continuous-time quantum Monte Carlo methods for impurity models we refer the reader to [2].Additional comments: Use of dmft requires citation of this paper. Use of any ALPS program requires citation of the ALPS [1] paper.Running time: 60 s–8 h per iteration.References:

• [1] 

  A. Albuquerque, F. Alet, P. Corboz, et al., J. Magn. Magn. Mater. 310 (2007) 1187.

• [2] 

  http://arxiv.org/abs/1012.4474, Rev. Mod. Phys., in press.

     

Two‐Level Grids for Ray Tracing on GPUs

We investigate the use of two‐level nested grids as acceleration structure for ray tracing of dynamic scenes. We propose a massively parallel, sort‐based construction algorithm and show that the two‐level grid is one of the structures that is fastest to construct on modern graphics processors. The structure handles non‐uniform primitive distributions more robustly than the uniform grid and its traversal performance is comparable to those of other high quality acceleration structures used for dynamic scenes. We propose a cost model to determine the grid resolution and improve SIMD utilization during ray‐triangle intersection by employing a hybrid packetization strategy. The build times and ray traversal acceleration provide overall rendering performance superior to previous approaches for real time rendering of animated scenes on GPUs.     

Fully-adaptive algorithms for long-lived renaming

Long-lived renaming allows processes to repeatedly get distinct names from a small name space and release these names. This paper presents two long-lived renaming algorithms in which the name a process gets is bounded above by the number of processes currently occupying a name or performing one of these operations. The first algorithm is asynchronous, uses LL/SC objects, and has step complexity that is linear in the number of processes, c, currently getting or releasing a name. The second is synchronous, uses registers and counters, and has step complexity that is polylogarithmic in c. Both tolerate any number of process crashes.     

Precision,Local Search and Unimodal Functions

We investigate the effects of precision on the efficiency of various local search algorithms on 1-D unimodal functions. We present a (1+1)-EA with adaptive step size which finds the optimum in O(log n) steps, where n is the number of points used. We then consider binary (base-2) and reflected Gray code representations with single bit mutations. The standard binary method does not guarantee locating the optimum, whereas using the reflected Gray code does so in Θ((log n)²) steps. A(1+1)-EA with a fixed mutation probability distribution is then presented which also runs in O((log n)²). Moreover, a recent result shows that this is optimal (up to some constant scaling factor), in that there exist unimodal functions for which a lower bound of Ω((log n)²) holds regardless of the choice of mutation distribution. For continuous multimodal functions, the algorithm also locates the global optimum in O((log n)²). Finally, we show that it is not possible for a black box algorithm to efficiently optimise unimodal functions for two or more dimensions (in terms of the precision used).     

PIN OLEDs — Improved structures and materials to enhance device lifetime

Abstract— Currently, three issues are identified that decide upon the commercial success of organic light‐emitting diodes (OLEDs), both in display and lighting applications: power efficiency, lifetime, and price competitiveness. PIN OLEDs are widely seen as the preferred way to maximize power efficiency. Here, it is reported that this concept also delivers the world longest lifetimes. For a highly efficient deep‐red PIN OLED, a half‐lifetime of 25,000 hours for a starting brightness of 10,000 cd/m² and a minimal voltage increase over lifetime is reported. This value corresponds to more than 1 × 10⁶ hours at 1000 cd/m² using an exponent of n = 1.7, which was measured by driving the OLEDs at different starting luminances. Because there is no initial luminance drop, these PIN OLEDs also exhibit a very high 80% lifetime (>300,000 hours at 1000 cd/m²). New record lifetime values for blue and green will be reported as well. Additionally, further topics that have impact on the production yield and cost such as the newly developed air‐stable organic n‐doping material NDN‐26 and top‐emitting structures will be discussed.     

What is the optimal architecture for visual information routing?

Analyzing the design of networks for visual information routing is an underconstrained problem due to insufficient anatomical and physiological data. We propose here optimality criteria for the design of routing networks. For a very general architecture, we derive the number of routing layers and the fanout that minimize the required neural circuitry. The optimal fanout l is independent of network size, while the number k of layers scales logarithmically (with a prefactor below 1), with the number n of visual resolution units to be routed independently. The results are found to agree with data of the primate visual system.     

Engineering better wheelchairs to enhance community participation.

With about 2.2 million Americans currently using wheeled mobility devices, wheelchairs are frequently provided to people with impaired mobility to provide accessibility to the community. Individuals with spinal cord injuries, arthritis, balance disorders, and other conditions or diseases are typical users of wheelchairs. However, secondary injuries and wheelchair-related accidents are risks introduced by wheelchairs. Research is underway to advance wheelchair design to prevent or accommodate secondary injuries related to propulsion and transfer biomechanics, while improving safe, functional performance and accessibility to the community. This paper summarizes research and development underway aimed at enhancing safety and optimizing wheelchair design.