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     

A comprehensive survey: artificial bee colony (ABC) algorithm and applications

Swarm intelligence (SI) is briefly defined as the collective behaviour of decentralized and self-organized swarms. The well known examples for these swarms are bird flocks, fish schools and the colony of social insects such as termites, ants and bees. In 1990s, especially two approaches based on ant colony and on fish schooling/bird flocking introduced have highly attracted the interest of researchers. Although the self-organization features are required by SI are strongly and clearly seen in honey bee colonies, unfortunately the researchers have recently started to be interested in the behaviour of these swarm systems to describe new intelligent approaches, especially from the beginning of 2000s. During a decade, several algorithms have been developed depending on different intelligent behaviours of honey bee swarms. Among those, artificial bee colony (ABC) is the one which has been most widely studied on and applied to solve the real world problems, so far. Day by day the number of researchers being interested in ABC algorithm increases rapidly. This work presents a comprehensive survey of the advances with ABC and its applications. It is hoped that this survey would be very beneficial for the researchers studying on SI, particularly ABC algorithm.     

Treatment of phenol formaldehyde production wastewater by electrooxidation-electrofenton successive processes

ABSTRACT

Treatments of phenol formaldehyde producing wastewater (PFPW) by electrooxidation (EO) and electro-Fenton (EF) successive processes were carried out in a batch electrolytic reactor using graphite (Gr) and stainless steel (Ss) electrodes. After the completion of the EO process, the wastewater was further treated with EF process. The influence of operating variables such as current density, operating time, initial pH_i and H₂O₂ concentration was evaluated for removals of phenol, TOC and COD in PFPW. Gr/Gr, Gr/Ss or Ss/Ss and Ss/Gr electrode pair were used as anode and cathode. The best removal efficiency in the EO process was obtained with Gr/Gr (93%) as compared to Gr/Ss (82%), Ss/Ss (63%) and Ss/Gr (55%). The removal efficiencies for the EO process using Gr-Gr electrode pair were obtained as 93% for phenol, 61% for COD and 44% for TOC at initial pH_i 7,5 g/L of NaCl, 50 mA/cm² and 5 h. In the EF process, the removal efficiencies at pH_i 3,5 mA/cm² and 30 mM H₂O₂ and 45 min were 100% for phenol, 76% for COD and 59% for TOC. This study provided that the successive processes are an effective method for the removal of phenolic compounds from the wastewater.     

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.