Intelligent process analytics for CRM

Many organisations use decision models in their processes such as tables or trees to provide decision support to their operational divisions. For example, in fault management, customer contact centre operators usually use a decision model in the form of prescribed interviews. Based on the answers given by customers, the operator navigates through the decision model to reach an assessment of the problem. In order to achieve customer satisfaction and operational excellence, it is very important to constantly monitor the performance of a decision model not only on an overall level, but also on the level of individual decisions. In this paper we present a configurable business process analytics tool, known as the intelligent Universal Service Management System, that constantly monitors decision data and is capable of optimising the decisions based on high-level business objectives. We explain the various features of the software and show how it can be used to optimise decision processes. We also show how we can easily provide a customised version to monitor the performance of provision processes.     

Learning in multiple model adaptive control switch

Including a learning mechanism in SMMAC (switched, multiple-model adaptive control) avoids the need for a priori knowledge of the model set of the plant to control and leads to a significant performance improvement with respect to the sole inclusion of an adaptive control channel in combination with switched fixed local controllers.     

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.     

1/f noise in large-area Hg<Subscript>1−x</Subscript>Cd<Subscript>x</Subscript>Te photodiodes

The 1/f noise in photovoltaic (PV) molecular-beam epitaxy (MBE)-grown Hg_1−xCd_xTe double-layer planar heterostructure (DLPH) large-area detectors is a critical noise component with the potential to limit sensitivity of the cross-track infrared sounder (CrIS) instrument. Therefore, an understanding of the origins and mechanisms of noise currents in these PV detectors is of great importance. Excess low-frequency noise has been measured on a number of 1000-μm-diameter active-area detectors of varying “quality” (i.e., having a wide range of I-V characteristics at 78 K). The 1/f noise was measured as a function of cut-off wavelength under illuminated conditions. For short-wave infrared (SWIR) detectors at 98 K, minimal 1/f noise was measured when the total current was dominated by diffusion with white noise spectral density in the mid-10⁻¹⁵A/Hz^1/2 range. For SWIR detectors dominated by other than diffusion current, the ratio, α, of the noise current in unit bandwidth i_n(f = 1 Hz, V_d = −60 mV, and Δf = 1 Hz) to dark current I_d(V_d = −60 mV) was α_SW-d = i_n/I_d ∼ 1 × 10⁻³. The SWIR detectors measured at 0 mV under illuminated conditions had median α_SW-P = i_n/I_ph ∼ 7 × 10⁻⁶. For mid-wave infrared (MWIR) detectors, α_MW-d = i_n/I_d ∼ 2 × 10⁻⁴, due to tunneling current contributions to the 1/f noise. Measurements on forty-nine 1000-μm-diameter MWIR detectors under illuminated conditions at 98 K and −60 mV bias resulted in α_MW-P = i_n/I_ph = 4.16 ± 1.69 × 10⁻⁶. A significant point to note is that the photo-induced noise spectra are nearly identical at 0 mV and 100 mV reverse bias, with a noise-current-to-photocurrent ratio, α_MW-P, in the mid 10⁻⁶ range. For long-wave infrared (LWIR) detectors measured at 78 K, the ratio, α_LW-d = i_n/I_d ∼ 6 × 10⁻⁶, for the best performers. The majority of the LWIR detectors exhibited α_LW-d on the order of 2 × 10⁻⁵. The photo-induced 1/f noise had α_LW-P = i_n/I_ph ∼ 5 × 10⁻⁶. The value of the noise-current-to-dark-current ratio, α appears to increase with increasing bandgap. It is not clear if this is due to different current mechanisms impacting 1/f noise performance. Measurements on detectors of different bandgaps are needed at temperatures where diffusion current is the dominant current. Excess low-frequency noise measurements made as a function of detector reverse bias indicate 1/f noise may result primarily from the dominant current mechanism at each particular bias. The 1/f noise was not a direct function of the applied bias.     

Evaluation and optimization of package processing and design through solder joint profile prediction

Solder joints are generated using a variety of methods to provide both mechanical and electrical connection for applications such as flip-chip, wafer level packaging, fine pitch, ball-grid array, and chip scale packages. Solder joint shape prediction has been incorporated as a key tool to aid in process development, wafer level and package level design and development, assembly, and reliability enhancement. This work demonstrates the application of an analytical model and the Surface Evolver software in analyzing a variety of solder processing methods and package types. Bump and joint shape prediction was conducted for the design of wafer level bumping, flip-chip assembly, and wafer level packaging. The results from the prediction methodologies are validated with experimentally measured geometries at each level of design.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.     

Synthesis of ZSM‐5 Films and Monoliths with Bimodal Micro/Mesoscopic Structures

A route to synthesize ZSM‐5 crystals with a bimodal micro/mesoscopic pore system has been developed in this study; the successful incorporation of the mesopores within the ZSM‐5 structure was performed using tetrapropylammonium hydroxide (TPAOH)‐impregnated mesoporous materials containing carbon nanotubes in the pores, which were encapsulated in the ZSM‐5 crystals during a solid rearrangement process within the framework. Such mesoporous ZSM‐5 zeolites can be readily obtained as powders, thin films, or monoliths.     

The First Template‐Free Growth of Crystalline Silicon Microtubes

A simple template‐free high‐temperature evaporation method was developed for the growth of crystalline Si microtubes for the first time. As‐grown Si microtubes were characterized using X‐ray diffraction, scanning electron microscopy, transmission electron microscopy, and room‐temperature photoluminescence. The lengths of the Si tubes can reach several hundreds of micrometers; some of them have lengths on the order of millimeters. Each tube has a uniform outer diameter along its entire length, and the typical outer diameter is ≈ 2–3 μm. Most of the tubes have a wall thickness of ≈ 400–500 nm, though a considerable number of them exhibit a very thin wall thickness of ≈ 50 nm. Room‐temperature photoluminescence measurement shows the as‐synthesized Si microtubes have two strong emission peaks centered at ≈ 589 nm and ≈ 617 nm and a weak emission peak centered at ≈ 455 nm. A possible mechanism for the formation of these Si tubes is proposed. We believe that the present discovery of the crystalline Si microtubes will promote further experimental studies on their physical properties and smart applications.     

Influence of device engineering on the analog and RF performances of SOI MOSFETs

This work presents a systematic comparative study of the influence of various process options on the analog and RF properties of fully depleted (FD) silicon-on-insulator (SOI), partially depleted (PD) SOI, and bulk MOSFET's with gate lengths down to 0.08 /spl mu/m. We introduce the transconductance-over-drain current ratio and Early voltage as key figures of merits for the analog MOS performance and the gain and the transition and maximum frequencies for RF performances and link them to device engineering. Specifically, we investigate the effects of HALO implantation in FD, PD, and bulk devices, of film thickness in FD, of substrate doping in SOI, and of nonstandard channel engineering (i.e., asymmetric Graded-channel MOSFETs and gate-body contacted DTMOS).     

High-gain hybrid amplifier consisting of cascaded fluoride-based TDFA and silica-based EDFA in 1458-1540 nm wavelength region

A hybrid optical fibre amplifier is described that consists of a fluoride-based thulium-doped fibre amplifier and a silica-based erbium-doped fibre amplifier connected in a cascade. The amplifier has a gain of more than 25 dB and a noise figure of less than 9 dB over a wide wavelength region of 1458-1540 nm.