Uterine leiomyosarcoma (Ut-LMS) develops more often in myometrium of the uterine body than in the uterine cervix. The development of gynecologic tumors is often correlated with female hormone secretion; however, the development of Ut-LMS is not substantially correlated with hormonal conditions, and the risk factor(s) are not yet known. Importantly, a diagnostic-biomarker, which distinguishes ma...

Hepatocyte growth factor activator inhibitors (HAI-1 and HAI-2) are Kunitz-type serine protease inhibitors that have a broad inhibitory spectrum against serine proteases. This study examined the role of HAI-1 and HAI-2 in uterine leiomyosarcoma (LMS) patients, and in vitro. HAI-1 and HAI-2 was examined in uterine normal smooth muscle, leiomyoma and LMS specimens using immunohistochemistry. We i...

The channel estimation is one of important techniques to ensure reliable broadband signal transmission. Broadband channels are often modeled as a sparse channel. Comparing with traditional dense-assumption based linear channel estimation methods, e.g., least mean square/fourth (LMS/F) algorithm, exploiting sparse structure information can get extra performance gain. By introducing -norm penalty...

K. Martin M. A. Quigley S. Rogers This article describes how Aventis Pharmaceuticals, in partnership with IBM, is implementing a learning management system (LMS) globally both in the Research and Development organization and in clinical groups within the Commercial Operations organization. It also discusses how Aventis is applying an innovative change management approach that meets challenges t...

The chain of applying adaptivity to Learning Management Systems (LMS) is still deficient; there is a gap between authoring adaptive materials and delivering them in LMS. In this paper, we extend My Online Teacher (MOT), an adaptive authoring system, by adding compatibility with IMS Question & Test Interoperability (QTI) and IMS Content Packaging (CP). Thus, the authors can utilize the authored ...

Learning management systems (LMS) are very successful in e-education but provide only little adaptivity. Adapting courses to the needs of individual learners such as to their learning styles improves the learning progress of learners. However, a requirement for providing adaptivity is to know the needs of learners. In this paper, we describe an approach that enables LMS to identify the learning...

The least-mean-square (LMS) estimator is a nonlinear estimator with information dependencies spanning the entire set of data fed into it. The traditional analysis techniques used to model this estimator obscure these dependencies; to simplify the analysis they restrict the estimator to the finite set of data sufficient to span the length of its filter. Thus the finite Wiener filter is often con...

We consider a time varying wireless fading channel, equalized by an LMS linear equalizer in decision directed mode (DD-LMS-LE). We study how well this equalizer tracks the optimal Wiener equalizer. Initially we study a fixed channel. For a fixed channel, we obtain the existence of DD attractors near the Wiener filter at high SNRs using an ODE (Ordinary Differential Equation) approximating the D...

Language models (LMs) are an essential element in statistical approaches to natural language processing for tasks such as speech recognition and machine translation (MT). The advent of big data leads to the availability of massive amounts of data to build LMs, and in fact, for the most prominent languages, using current techniques and hardware, it is not feasible to train LMs with all the data ...

A principal component least mean square (PC-LMS) adaptive algorithm is described that has considerable benefits for large control systems used to implement feedforward control of single frequency disturbances. The algorithm is a transform domain version of the multichannel filtered-x LMS algorithm. The transformation corresponds to the principal components (PCs) of the transfer function matrix ...