Organic Nanoparticles: Preparation,Self‐Assembly,and Properties

The strong tendency of organic nanoparticles to rapidly self‐assemble into highly aligned superlattices at room temperature when solution‐cast from dispersions or spray‐coated directly onto various substrates is described. The nanoparticle dispersions are stable for years. The novel precipitation process used is believed to result in molecular distances and alignments in the nanoparticles that are not normally possible. Functional organic light‐emitting diodes (OLEDs)—which have the same host–dopant emissive‐material composition—with process‐tunable electroluminescence have been built with these nanoparticles, indicating the presence of novel nanostructures. For example, only changing the conditions of the precipitation process changes the OLED emission from green light to yellow.     

Practical OSPF traffic engineering

Open Shortest Path First (OSPF) traffic engineering (TE) is intended to bring long-awaited traffic management capabilities into IP networks, which still rely on today's prevailing routing protocols: OSPF or IS-IS. In OSPF, traffic is forwarded along, and split equally between, equal cost shortest paths. In this letter, we formulate the basic requirements placed on a practical TE architecture built on top of OSPF and present a theoretical framework meeting these requirements of practicality. The main contribution of our work comes from the recognition that coupled with an instance of the maximum throughput problem there exists a related inverse shortest-path problem yielding optimal OSPF link weights.     

Relevance of coupling effects on DRA array design

A finite-difference time-domain (FDTD) approach is proposed in order to obtain suitable criteria for the design of a four-element dielectric resonator antenna (DRA) array. The numerical analysis is focused on the study of the electromagnetic coupling phenomena arising between DRA fed by a microstrip-slot transition. Scattering parameters behavior and radiation patterns are determined by taking advantage of the geometrical symmetry of the structure, analyzing only one half or one quarter of the entire domain through two or four separate FDTD runs.     

PNNI-based control plane for automatically switched optical networks

Much effort has been spent on the definition of control plane protocols for automatically switched optical networks (ASON). Most of the proposals brought into the standardization for an International Telecommunications Union-Telecommunication Sector, Internet Engineering Task Force, and Optical Internetworking Forum are based on Internet protocol concepts. One such proposal is the generalized multi-protocol label switching (GMPLS), an extension of the MPLS traffic engineering control plane model that includes nonpacket switched technologies (time, wavelength, and fiber switching). Recently, the potential use of private network-network interface (PNNI) in ASONs has been discussed as an alternative proposal by the standardization bodies. The goal of this paper is to appropriately adapt asynchronous transfer mode into an optical PNNI (O-PNNI) protocol that can be used as the control plane of ASONs. The paper also provides a critical viewpoint on the potential usage of either O-PNNI or GMPLS control plane and analyzes the pros and cons of each. The methodology adopted toward devising O-PNNI hinges on reviewing PNNI along with ASON recommendations in order to determine the set of PNNI features that require adaptation. Having identified these features we engineer and present appropriate solutions relating to routing, signaling and addressing aspects.     

A fuzzy logic based-method for prognostic decision making in breast and prostate cancers

Accurate and reliable decision making in oncological prognosis can help in the planning of suitable surgery and therapy, and generally, improve patient management through the different stages of the disease. In recent years, several prognostic markers have been used as indicators of disease progression in oncology. However, the rapid increase in the discovery of novel prognostic markers resulting from the development in medical technology, has dictated the need for developing reliable methods for extracting clinically significant markers where complex and nonlinear interactions between these markers naturally exist. The aim of this paper is to investigate the fuzzy k-nearest neighbor (FK-NN) classifier as a fuzzy logic method that provides a certainty degree for prognostic decision and assessment of the markers, and to compare it with: 1) logistic regression as a statistical method and 2) multilayer feedforward backpropagation neural networks an artificial neural-network tool, the latter two techniques having been widely used for oncological prognosis. In order to achieve this aim, breast and prostate cancer data sets are considered as benchmarks for this analysis. The overall results obtained indicate that the FK-NN-based method yields the highest predictive accuracy, and that it has produced a more reliable prognostic marker model than both the statistical and artificial neural-network-based methods.     

Protecting local access telecommunications networks: Toward a minimum-cost solution

The problem of designing fibre-optic networks for local-access telecommunications generates (at least) three non-trivial subproblems. In the first of these subproblems one must determine how many fibre-optic cables (fibres) are required at either end of a street. In the next subproblem a minimum-cost network must be designed to support the fibres. The network must also provide distinct paths from either end of the street to the central exchange(s). Finally, the fibre-optic cables must be placed in protective covers. These covers are available in a number of different sizes, allowing some flexibility when covering each section of the network. In this paper we describe a dynamic programming (DP) formulation for finding a minimum-cost (protective) covering for the network (the third of the subproblems). This problem is a generalised set covering problem with side constraints and is further complicated by the introduction of fixed and variable welding costs. The DP formulation selects covers along each arc (in the network), but cannot exactly model the fixed costs and so does not guarantee optimality. We also describe an integer programming (IP) formulation for assessing the quality of the DP solutions. The cost of the networks constructed by the IP model is less than those designed using the DP model, but the saving is not significant for the problems examined (less than 0.1%). This indicates that the DP model will generally give very good solutions. Furthermore, as the problem dimensions grow, DP gives significantly better solution times than IP.     

From Poldhu to the Italian station of Coltano: Marconi and the first years of transcontinental wireless

This paper presents the evolution of low-frequency, high-power transcontinental transmission, starting from the first successful transatlantic link from Poldhu up to the Italian transcontinental station of Coltano. The trend toward higher and higher transmitting power, and the dead end into which wireless was heading if it were not for research in the higher frequency ranges, are pointed out.     

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.     

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.