Optical-transmission characteristics of optical-fiber cables and installed optical-fiber cable networks for WDM systems

Many cables containing 1.3-/spl mu/m zero-dispersion single-mode (SM) optical fibers are installed in trunk and access networks. Recently, there have been a number of studies on wavelength-division-multiplexing (WDM) systems designed to increase transmission capacity and flexibility. If we can construct WDM systems using SM optical-fiber cable networks designed to transmit using wavelengths in the 1.3-/spl mu/m window (O-band), this will prove very effective in reducing construction costs. It is therefore important to examine the wavelength dependence of the transmission characteristics of SM optical-fiber cables and networks that have already been installed and in which several optical fibers are joined. In this paper, we describe the measured optical characteristics of SM optical-fiber cables and installed optical-fiber cable networks at various wavelengths. The optical characteristics were stable in the 1.46 to 1.625-/spl mu/m wavelength range and we confirmed that the installed SM optical-fiber cable networks could be used for WDM system applications.     

Chernoff bounds on pairwise error probabilities of space-time codes

We derive Chernoff bounds on pairwise error probabilities of coherent and noncoherent space-time signaling schemes. First, general Chernoff bound expressions are derived for a correlated Ricean fading channel and correlated additive Gaussian noise. Then, we specialize the obtained results to the cases of space-time-separable noise, white noise, and uncorrelated fading. We derive approximate Chernoff bounds for high and low signal-to-noise ratios (SNRs) and propose optimal signaling schemes. We also compute the optimal number of transmitter antennas for noncoherent signaling with unitary mutually orthogonal space-time codes.     

Self-reflective segmentation of human bodily motions using recurrent neural networks

For realizing a naturalistic collaboration between the human and the robot, we have to establish the intention sharing from the series of motion data that are observed and exchanged between the human and the machine. In a word, this is a problem to detect "meanings" out of the digitized data stream. In this paper, we propose a novel approach based on semiosis, and present a method of interpreting bodily motions using recurrent neural networks called Elman networks. We made some experiments using the raw data acquired while a human performs a simple task of fetching objects by stretching and folding his/her arm, and demonstrate that the network can learn invariant features of the generalized motion concepts, classify the motion by referring to self-organized memory structure, and understand a task structure of the observed human bodily motion. These capabilities are essential for machine intelligence to establishing the human-robot shared autonomy, a new style of human-machine collaboration proposed in the area of robotics.     

Control of polishing of diamond films using microactuation and an atmospheric pressure plasma

In this work, the diamond deposited by hot filament chemical vapor deposition (CVD) is polished using an atmospheric pressure plasma. In order to position the film relative to the plasma, a microactuator system is designed using a stack of domed piezoelectric actuators. A dynamic model based on the physical system is developed and the model parameters are measured experimentally. A system based on laser triangulation is used to measure the position of the diamond film relative to the plasma. Control techniques are used to reduce the oscillations during actuation and to eliminate the steady state positioning error. With the application of feedback control, the overshoot is reduced to 2% and the settling time is reduced to 0.3 s. A preliminary set of experiments is performed to relate process parameters to the final surface roughness of the diamond film. The parameters studied include the film's time of exposure to the plasma, the height of the film relative to the plasma, and the distance from the film to the center of the plasma. It is found that the optimum exposure time is 15 min and the reduction of surface roughness is greatest when the distance between the film and the plasma is at a minimum. The best results are obtained when the top of the film is even in elevation with the tip of the top electrode. The diamond film is translated laterally along the plasma. When feedback control is not used, there is no change in the surface roughness. With feedback control implemented, the surface roughness of the diamond film is reduced by 33%.     

Minimax estimation of deterministic parameters in linear models with a random model matrix

We consider the problem of estimating an unknown deterministic parameter vector in a linear model with a random model matrix, with known second-order statistics. We first seek the linear estimator that minimizes the worst-case mean-squared error (MSE) across all parameter vectors whose (possibly weighted) norm is bounded above. We show that the minimax MSE estimator can be found by solving a semidefinite programming problem and develop necessary and sufficient optimality conditions on the minimax MSE estimator. Using these conditions, we derive closed-form expressions for the minimax MSE estimator in some special cases. We then demonstrate, through examples, that the minimax MSE estimator can improve the performance over both a Baysian approach and a least-squares method. We then consider the case in which the norm of the parameter vector is also bounded below. Since the minimax MSE approach cannot account for a nonzero lower bound, we consider, in this case, a minimax regret method in which we seek the estimator that minimizes the worst-case difference between the MSE attainable using a linear estimator that does not know the parameter vector, and the optimal MSE attained using a linear estimator that knows the parameter vector. For analytical tractability, we restrict our attention to the scalar case and develop a closed-form expression for the minimax regret estimator.     

X-ray or UV adjustment of MOS threshold voltage: Analytical and numerical modeling

A model is formulated that describes how radiation-induced charge accumulates in the gate oxide of a MOS structure and how it decays through tunneling and thermal emission. The model is used in a numerical analysis of the x-ray or UV adjustment of threshold voltage in MOS-circuit manufacture. The limits of this process technique are evaluated.     

Using the magneto-optical Kerr effect to study magnetization processes in two-dimensional magnonic crystals based on YIG thin films

The magneto-optical Kerr effect for red (628 nm) and green (532 nm) light is used to study magnetization processes in 2D magnonic crystals obtained by etching pits with the diameter D ≈ 32 μm to a depth of t ≤ 2 μm in a 16.1-μm-thick film of yttrium iron garnet (YIG). Hysteresis loops obtained in the case of the inplane crystal magnetization at 628 nm are characterized by lower saturation fields H _s and higher remanent magnetizations than those obtained at 532 nm, a result that is attributed to different absorption coefficients of the YIG film at these wavelengths. This difference between the magnetization curves reflects the fact that the magnonic-crystal surface probed with the green light makes a greater contribution to the magneto-optical Kerr effect. Therefore, the green light is more sensitive to the demagnetizing fields, which govern magnetization processes in the magnonic crystals.     

Nondegenerate Phase-Locking of a Semiconductor Laser by Sideband Injection

A semiconductor laser rate equation theory is presented that describes sideband injection locking under both weak optical injection and current modulation. By simultaneous optical injection and current modulation, control of both the phase and the frequency of a semiconductor laser is demonstrated. The phase-locked semiconductor laser operates at a different frequency to the optical injection source, with a frequency-difference given by the current modulation frequency. This method can be used to produce broadband sources, such as those producing ultrashort pulses and those required for coherent control, or to create high-frequency electronic oscillator sources with phase control by interference beating     

Holographic sensors for the determination of ionic strength

Holographic sensors for monitoring ionic strength have been fabricated from charged sulphonate and quaternary ammonium monomers, incorporated into thin, polymeric hydrogel films which were transformed into volume holograms. The diffraction wavelength or reflected colour of the holograms was used to characterise their swelling or de-swelling behaviour as a function of ionic strength in various media. The effects of co-monomer structure, buffer composition, ion composition, pH and temperature were evaluated, whilst the reversibility and reproducibility of the sensor was also assessed. An acrylamide-based hologram containing equal molar amounts of negatively and positively charged monomers was shown to be able to quantify ionic strength independent of the identity of the ionic species present in the test solution. The sensor was fully reversible, free of hysteresis and exhibited little response to pH between 3 and 9 and temperature within the range 20-45 °C. The system was successfully used to quantify the ionic strength of milk solutions, which contain a complex mixture of ions and biological components.     

Adaptive agents and multiagent systems

New information systems and recent applications (grid computing, Web Services, and so on) are often distributed, large-scale, open, heterogeneous, and characterized by a dynamic environment. To model these complex systems, researchers have spent much effort during the last few years on multiagent systems. The aim is to model complex distributed systems as a set of (possibly organized) software agents that interact in a common environment. The decomposition of a system into a number of agents lets the system react and adapt better in a changing environment. Moreover, organized structures ("social" structures) can emerge from interactions between agents, which in turn constrain and coordinate the agents' behavior. A multiagent system takes its metaphors of interaction from social systems rather than using the metaphor of the isolated thinker that early artificial intelligence researchers preferred. An important issue when dealing with this increasing complexity is to build adaptive agents and multiagent systems. Agents and multiagent systems must be aware of their own capabilities and of changes to other agents and their environment. To remain effective, agents must be able to adapt their structures and knowledge while they execute.