The physics of e-commerce supply chains

The Internet is rapidly improving our ability to support information flows across global supply chains. However, the business impact of these IT investments depends not just on the information flows supported by such systems, but also on other non-information related characteristics of the supply chain. It is the complex interplay among these characteristics that results in business performance, or lack thereof. In order to better understand the business impact of IT investments in the supply chain, we are motivated to examine the ‘physics’ of supply chain structures. By physics, we mean the performance patterns inherent in its informational and physical characteristics. Using the systems dynamics methodology, we model basic information and physical characteristics of supply chains and examine their impact on some common measures of performance. Experiments with the models suggest that, in addition to information delays, physical delays also have a major impact on the stability of supply chains, as well as on operating cost. Moreover, the tradeoff between chain stability and responsiveness appears to be nonlinear, suggesting that a small compromise in responsiveness may yield larger gains in stability. Multi-tier chains appear to be less ‘stiff’ in responding to demand fluctuations, implying that their information systems must be specifically designed to overcome this structural tendency. These results have managerial implications in terms of designing the information and physical structure of a supply chain as well as for its operation.     

Apparent solubility of drugs in partially crystalline systems

Using several griseofulvin samples, representing different solid-state structures, the solubility behavior of drugs in both one-state (totally ordered, semiordered or disordered) and two-state systems was studied. Special attention was directed towards the surface structure of the particles. The partially crystalline samples were obtained by milling the raw material (crystalline standard) or storing the quenched sample (amorphous standard). The solid-state structure of the materials was studied using x-ray diffraction (XRD), differential scanning calorimetry (DSC), isothermal microcalorimetry (IMC), and scanning electron microscopy (SEM). The saturation concentration of the materials was studied in suspensions containing different dispersion concentrations of drug after centrifugation and filtration, using spectrophotometry. In all cases these dispersion concentrations exceeded the solubility of the drug. The solubilities were plotted vs. dispersion concentrations for each sample. Several solubility plateaus were found. The lowest and highest solubility plateaus corresponded to the solubilities of crystalline and amorphous standards. These plateaus were reached at 8 and 44 µg/mL for crystalline and amorphous griseofulvin standards, respectively. An intermediate plateau served as an indication of the existence of a totally semiordered structure. This was reached at 19 µg/mL for griseofulvin. Any deviation from these plateaus was suggested to be indicative of the existence of heterogeneity on the surface structure, which in most cases could be described as a two state system. In such cases, the apparent solubility was a function of dispersion concentration, until at very high dispersion concentrations (4000-20,000 µg/mL) the saturation concentration of the totally disordered (44 µg/mL) or semiordered (19 µg/mL) one-state phase was reached. No reduction in these values was observed during storage for 50 days. It is thus concluded that, in partially crystalline systems, the saturation concentration is an interfacial phenomenon, which depends on the amount, reactivity, and solid-state structure of the exposed solid surfaces in equilibrium with the solution. A simplified solubility model is proposed to qualitatively describe the relationship between established apparent solubilities (saturation concentrations) and different combinations of solid-state structures.     

Sampling properties of the spectrum and coherency of sequences of action potentials

The spectrum and coherency are useful quantities for characterizing the temporal correlations and functional relations within and between point processes. This article begins with a review of these quantities, their interpretation, and how they may be estimated. A discussion of how to assess the statistical significance of features in these measures is included. In addition, new work is presented that builds on the framework established in the review section. This work investigates how the estimates and their error bars are modified by finite sample sizes. Finite sample corrections are derived based on a doubly stochastic inhomogeneous Poisson process model in which the rate functions are drawn from a low-variance gaussian process. It is found that in contrast to continuous processes, the variance of the estimators cannot be reduced by smoothing beyond a scale set by the number of point events in the interval. Alternatively, the degrees of freedom of the estimators can be thought of as bounded from above by the expected number of point events in the interval. Further new work describing and illustrating a method for detecting the presence of a line in a point process spectrum is also presented, corresponding to the detection of a periodic modulation of the underlying rate. This work demonstrates that a known statistical test, applicable to continuous processes, applies with little modification to point process spectra and is of utility in studying a point process driven by a continuous stimulus. Although the material discussed is of general applicability to point processes, attention will be confined to sequences of neuronal action potentials (spike trains), the motivation for this work.     

Multiple statistical models for soft decision in noisy speech enhancement

Most speech enhancement algorithms are based on the assumption that speech and noise are both Gaussian in the discrete cosine transform (DCT) domain. For further enhancement of noisy speech in the DCT domain, we consider multiple statistical distributions (i.e., Gaussian, Laplacian and Gamma) as a set of candidates to model the noise and speech. We first use the goodness-of-fit (GOF) test in order to measure how far the assumed model deviate from the actual distribution for each DCT component of noisy speech. Our evaluations illustrate that the best candidate is assigned to each frequency bin depending on the Signal-to-Noise-Ratio (SNR) and the Power Spectral Flatness Measure (PSFM). In particular, since the PSFM exhibits a strong relation with the best statistical fit we employ a simple recursive estimation of the PSFM in the model selection. The proposed speech enhancement algorithm employs a soft estimate of the speech absence probability (SAP) separately for each frequency bin according to the selected distribution. Both objective and subjective tests are performed for the evaluation of the proposed algorithms on a large speech database, for various SNR values and types of background noise. Our evaluations show that the proposed soft decision scheme based on multiple statistical modeling or the PSFM provides further speech quality enhancement compared with recent methods through a number of subjective and objective tests.     

Gesture Recognition: A Survey

Gesture recognition pertains to recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head, and/or body. It is of utmost importance in designing an intelligent and efficient human-computer interface. The applications of gesture recognition are manifold, ranging from sign language through medical rehabilitation to virtual reality. In this paper, we provide a survey on gesture recognition with particular emphasis on hand gestures and facial expressions. Applications involving hidden Markov models, particle filtering and condensation, finite-state machines, optical flow, skin color, and connectionist models are discussed in detail. Existing challenges and future research possibilities are also highlighted     

Tools for Performance Analysis and Design of Space–Time Block Codes

Space-time block codes (STBCs) have attracted recent interest due to their ability to take advantage of both space and time diversity to reliably transmit data over a wireless fading channel. In many cases, their design is based on asymptotically tight performance criteria, such as the worst-case pairwise error probability (PEP) or the union bound. However, these quantities fail to give an accurate performance picture, especially at low signal-to-noise ratio, because the classical union bound is known to be loose in this case. This paper develops tighter performance criteria for STBCs which yield considerably better bounds. First, the union bound is developed as the average of the exact PEPs. By noting that some of the terms in the bound are redundant, a second bound is obtained by expurgation. Since this still yields a loose bound, a tighter bound, denoted as the progressive union bound (PUB), is obtained. Because the PUB cannot be computed in closed form, in its most general case, and to avoid computing a high-dimensional numerical integration, its saddlepoint approximation is developed. In addition to the significant improvement of the PUB analysis over other bounding methods, it is also shown that codes designed to optimize the PUB can perform better than those obtained by the looser criteria     

Quantized UWB Transmitted Reference Systems

Digital implementation of ultra-wideband receivers requires analog-to-digital conversion (ADC) at an extremely high speed, thereby limiting the available bit resolution. Herein, the effect of low bit resolution quantization on the performance of UWB transmitted reference receivers is investigated. It is verified that the gain of the automatic-gain-control (AGC) has a significant effect on the achievable performance. Because of the considerable performance loss of conventional transmitted reference receivers in the presence of a low resolution ADC a new family of receiver structures optimized and tailored to quantized observations is presented. In particular, the generalized- likelihood ratio test (GLRT) based on the quantized samples is derived and shown to provide modest performance gains relative to the infinite resolution GLRT rule employed on the quantized received signal suggesting that conventional receiver structures can also be employed in the presence of a low resolution ADC. Results reveal that four bits of resolution in combination with an optimal choice for the AGC gain are sufficient to closely approach the performance of an infinite resolution receiver.     

The design of low noise digital filters with controlled dynamic range

A novel digital filter structure, that allows proper positioning of the zeros of the noise transfer functions to reduce the output roundoff noise, is introduced. Relations between zero locations, roundoff noise and dynamic range are derived and are then utilized in an heuristic optimization method for synthesizing a low noise scaled digital filter structure. Illustrative examples supporting the proposed approach are included.     

Sketch‐to‐Design: Context‐Based Part Assembly

Designing 3D objects from scratch is difficult, especially when the user intent is fuzzy and lacks a clear target form. We facilitate design by providing reference and inspiration from existing model contexts. We rethink model design as navigating through different possible combinations of part assemblies based on a large collection of pre‐segmented 3D models. We propose an interactive sketch‐to‐design system, where the user sketches prominent features of parts to combine. The sketched strokes are analysed individually, and more importantly, in context with the other parts to generate relevant shape suggestions via adesign galleryinterface. As a modelling session progresses and more parts get selected, contextual cues become increasingly dominant, and the model quickly converges to a final form. As a key enabler, we use pre‐learned part‐based contextual information to allow the user to quickly explore different combinations of parts. Our experiments demonstrate the effectiveness of our approach for efficiently designing new variations from existing shape collections.     

Constraint-aware interior layout exploration for pre-cast concrete-based buildings

Creating desirable layouts of building interiors is a complex task as designers have to manually adhere to various local and global considerations arising from competing practical and design considerations. In this work, we present an interactive design tool to create desirable floorplans by computationally conforming to such design constraints. Specifically, we support three types of constraints: (i) functional constraints such as number of rooms, connectivity among the rooms, target room areas, etc., (ii) design considerations such as user modifications and preferences, and (iii) fabrication constraints such as cost and convenience of manufacturing. Based on user specifications, our system automatically generates multiple floor layouts with associated 3D geometry that all satisfy the design specifications and constraints, thus exposing only the desirable family of interior layouts to the user. In this work, we focus on pre-cast concrete-based constructions, which lead to interesting discrete and continuous optimization possibilities. We test our framework on a range of complex real-world specifications and demonstrate the control and expressiveness of the exposed design space relieving the users of the task of manually adhering to non-local functional and fabrication constraints.