Parallel, self-organizing, hierarchical neural networks. II

For pt.I see IEEE Trans. Neural Networks, vol.1, p.167-78 (1990). Parallel, self-organizing, hierarchical neural networks (PSHNNs) involve a number of stages with error detection at the end of each stage, i.e., rejection of error-causing vectors, which are then fed into the next stage after a nonlinear transformation. The stages operate in parallel during testing. Statistical properties and the mechanisms of vector rejection of the PSHNN are discussed in comparison to the maximum likelihood method and the backpropagation network. The PSHNN is highly fault tolerant and robust against errors in the weight values due to the adjustment of the error detection bounds to compensate errors in the weight values. These properties are exploited to develop architectures for programmable implementations in which the programmable parts are reduced to on-off or bipolar switching operations for bulk computations and attenuators for pointwise operations     

Tocopherol contents of some Turkish wine by-products

The aim of this study was to determine the tocopherol contents of wine by-products including grape seed, pomace (seed, skin and stem) and bagasse (skin and stem) by using two different extraction methods in order to evaluate the possibilities of them as natural non-polar antioxidants. Cold extraction appeared to give more tocopherol contents in seeds than hot extraction. But hot extraction was found more suitable for pomace and bagasse. α-Tocopherol was the most abundant tocopherol in the grape seed, pomace and bagasse. Although γ- and δ-tocopherols were found in the samples with low concentrations, β-tocopherol was not detected in the samples. Kalecik karası had the highest α and total tocopherol compared to the other cultivars. On the other hand, hot extracted bagasse in all cultivars gave the highest tocopherol contents. As a conclusion, wine by-products, a large scale wastes, can be evaluated both to get natural tocopherol source and to obtain economical gain.     

Diffractive-phase-element design that implements several optical functions

A scheme for the design of diffractive phase elements (DPE's) that integrates several optical functions is presented in a consistent sense based on the general theory of amplitude-phase retrieval and the Yang-Gu algorithm [Appl. Opt. 33, 209 (1994)]. We extend the original Yang-Gu algorithm to treat a system illuminated by a beam of incident light whose components are at different wavelengths, and a set of equations for determining the phase distribution of the DPE is derived. The profile of a surface-relief DPE can be designed with an iterative algorithm. Numerical simulations are carried out for the design of one-dimensional DPE's capable of both demultiplexing different wavelength components and focusing each partial wave at predetermined positions. The influence of the extension of sampling points in the DPE's from ideal geometric points to physical spots on design results is also investigated. The numerical simulation results show that the new algorithm can be used successfully to design the desired DPE's. It is therefore expected to be useful in the design of DPE's for micro-optical systems.     

Image‐Based Edge Bundles: Simplified Visualization of Large Graphs

We present a new approach aimed at understanding the structure of connections in edge‐bundling layouts. We combine the advantages of edge bundles with a bundle‐centric simplified visual representation of a graph's structure. For this, we first compute a hierarchical edge clustering of a given graph layout which groups similar edges together. Next, we render clusters at a user‐selected level of detail using a new image‐based technique that combines distance‐based splatting and shape skeletonization. The overall result displays a given graph as a small set of overlapping shaded edge bundles. Luminance, saturation, hue, and shading encode edge density, edge types, and edge similarity. Finally, we add brushing and a new type of semantic lens to help navigation where local structures overlap. We illustrate the proposed method on several real‐world graph datasets.     

Sink placement on a 3D terrain for border surveillance in wireless sensor networks

With their distributed nature and redundant operation capability, wireless sensor networks are very suitable for border surveillance scenarios that track intruders trying to breach to a safe side. In such scenarios, keeping the operation going on for as long as possible is the most important aspect of the network. We propose that by placing sink at a carefully selected coordinate will results in a longer living network. We also place restrictions on the candidate locations so that the sensing quality of the network is above a useful predetermined value and the sink is placed in a relatively safe location to avoid destruction. In order to find the suitable coordinates we propose a modified lifetime metric which takes quality and safety measures into account. We also propose a genetic algorithm which uses a discrete event simulator-in-the-loop over a three dimensional terrain to find locations for the sink that fits the given quality and safety restrictions. Using a three dimensional underlying terrain makes the proposed approach more realistic. The results obtained for various sensor network scenarios indicate that the proposed algorithm can find locations that increase the lifetime by also considering the sensing quality and safety.     

Serum iron as an indicator of acute inflammation in cattle

The aim of this study was to assess the value of serum iron concentration in the diagnosis of acute inflammation in cattle. The diagnostic value of this approach was compared with that of various other hematological tests, including commonly used techniques that measure the levels of various other acute-phase proteins. The study population comprised 10 cows with acute traumatic reticuloperitonitis (RPT group) and 10 cows with acute mastitis (mastitis group) admitted to the Veterinary Teaching Hospital at Firat University (Elazi?, Turkey). Ten cows from local barns, kept and fed under same conditions as the diseased animals, were used as controls. After the clinical examination, blood samples were collected for biochemical, hematological, and acute-phase protein (haptoglobin, serum amyloid A, α-1 acid glycoprotein, and fibrinogen) analyses. The mean levels of serum iron in the RPT, mastitis, and control groups were 6.00, 7.82, and 26.78 µmol/L, respectively. Serum iron level was significantly reduced in the RPT and mastitis groups. The results of this study indicate that serum iron analysis, preferably in combination with other markers of inflammation, may be a useful diagnostic tool for acute inflammation in cattle. Because serum iron measurement is individually available and easily applicable, it may be used for clinical cases as well as the determination of herd health.     

Multi-sink load balanced forwarding with a multi-criteria fuzzy sink selection for video sensor networks

Congestion is a challenging problem in wireless sensor networks, which exacerbates with the high volume of data traffic imposed by video applications such as video surveillance and target tracking. Deployment of multiple sinks is a candidate solution for congestion and is also promising in terms of reliability and energy-efficiency. In order to gain the maximum benefit from multiple sinks, it is essential to distribute the load among them evenly. In this paper, we propose a cross layer geographic forwarding scheme MLBRF (Multi-Sink Load Balanced Reliable Forwarding) which aims to provide reliable and energy efficient video delivery in a multi-sinked sensor network for target tracking. In order to provide load balancing among the sinks, MLBRF proposes a sink selection mechanism based on fuzzy logic for the frame forwarding which evaluates the traffic density in the direction of each sink by combining two dynamic criteria which are the number of contenders and the buffer occupancy levels in the neighborhood with the static distance criterion. The performance of the fuzzy sink selection mechanism is compared using simulation with various sink selection mechanisms. The results show that MLBRF gains the maximum benefit from deploying multiple sinks in terms of reliability, latency and energy efficiency by using the proposed fuzzy sink selection mechanism.     

WCOT: A utility based lifetime metric for wireless sensor networks

Network lifetime is a novel performance metric which is derived in need to evaluate the networks that are composed of nodes with non-replenishable energy sources. Wireless Sensor Networks (WSNs) are the primary examples of such networks, in which elongating the network lifetime is the main concern. Optimal WSN design is highly dependent on the application scenario context. Correct quantification of the application specific network lifetime is a must to further optimize the design or to comparatively evaluate the proposed schemes – e.g. a legacy layered design vs. a cross-layer implementation. However, in practice, we observe that the focus is given on proposing sophisticated schemes to increase the energy efficiency, whereas only rudimentary lifetime metrics are employed to evaluate the outcome of this effort which compromises the correctness of the results. To realistically and correctly quantify the lifetime, we propose a utility based lifetime measurement framework called Weighted Cumulative Operational Time (WCOT). WCOT lets users incorporate the application dependence into the lifetime metric through its utility based interface. WCOT performs a weighted summation of time where utility values are the weights. With this mechanism, a more representative lifetime metric which maps the complete network behavior into a numeric value is obtained. This is in contrast with metrics which focus solely on certain milestones of the network functionality to quantify the lifetime which include the first node death, the last node death.