Pilot treatment of olive pomace leachate by vertical-flow constructed wetland and electrochemical oxidation: An efficient hybrid process

A hybrid process comprising biological degradation in a vertical-flow constructed wetland (CW) and electrochemical oxidation over boron-doped diamond electrodes to decolorize, mineralize and detoxify a leachate from olive pomace processing (OPL) was investigated. Two alternative treatment schemes were compared: According to the first treatment scheme, OPL was treated by electrochemical oxidation followed by treatment in a constructed wetland pilot unit (CW-A). The second scheme comprised of treatment in a constructed wetland followed by electrochemical treatment (CW-B). The constructed wetlands units were planted with Phragmites australis (reeds) and were fed intermittently at organic loadings between 5 and 15 g COD m⁻² d⁻¹ and a residence time of 3 d. Electrochemical oxidation (EO) was performed for 360 min at 20 A.Treatment of OPL in the wetland at 15 g COD m⁻² d⁻¹ led to mean COD and color reduction of 86% and 77%, respectively; the wetland effluent with a COD of about 800 mg L⁻¹ was polished electrochemically for 360 min after which the overall COD and color removal of the combined process (i.e. CW-B/EO) was around 95%, while the final effluent was not toxic against the marine bacteria Vibrio fischeri.Electrochemical oxidation of the original OPL at COD values between 6250 and 14 100 mg L⁻¹ led to moderate COD and color reduction (i.e. less than 40%) through zero order kinetics. When this was coupled to constructed wetland post-treatment (i.e. EO/CW-A), the overall COD and color removal was 81% and 58%, respectively. The decreased efficiency may be assigned to the increased toxicity of the electrochemically treated effluent which was only partially removed in the natural treatment system.     

Dependent multiple cue integration for robust tracking

We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and position of the target. Robustness is achieved by the integration of appearance and geometric object features and by their estimation using Bayesian filters, such as Kalman or particle filters. In particular, each filter estimates the state of a specific object feature, conditionally dependent on another feature estimated by a distinct filter. This dependence provides improved target representations, permitting to segment it out from the background even in non-stationary sequences. Considering that the procedure of the Bayesian filters may be described by a "hypotheses generation--hypotheses correction" strategy, the major novelty of our methodology compared to previous approaches is that the mutual dependence between filters is considered during the feature observation, i.e, into the "hypotheses correction" stage,instead of considering it when generating the hypotheses. This proves to be much more effective in terms of accuracy and reliability. The proposed method is analytically justified and applied to develop a robust tracking system that adapts online and simultaneously the color space where the image points are represented, the color distributions, the contour of the object and its bounding box. Results with synthetic data and real video sequences demonstrate the robustness and versatility of our method.     

Transforming communicating X-machines into P systems

Tissue P systems (tPS) represent a class of P systems in which cells are arranged in a graph rather than a hierarchical structure. On the other hand, communicating X-machines (XMs) are state-based machines, extended with a memory structure and transition functions instead of simple inputs, which communicate via message passing. One could use communicating XMs to create models built out of components in a rather intuitive way. There are investigations showing how various classes of P systems can be modelled as communicating XMs. In this paper, we define a set of principles to transform communicating XMs into tPS. We describe the rules that govern such transformations, present an example to demonstrate the feasibility of this approach and discuss ways to extend it to more general models, such as population P systems, which involve dynamic structures.     

An exterior simplex type algorithm for the Minimum Cost Network Flow Problem

In this paper a new Network Exterior Point Simplex Algorithm (NEPSA) for the Minimum Cost Network Flow Problem (MCNFP) is analytically presented. NEPSA belongs to a special simplex type category and is a modification of the classical network simplex algorithm. The main idea of the algorithm is to compute two flows. One flow is basic but not always feasible and the other is feasible but not always basic. A complete proof of correctness for the proposed algorithm is also presented. Moreover, the computational behavior of NEPSA is shown by an empirical study carried out for randomly generated sparse instances created by the well-known GRIDGEN network problem generator.     

A convex optimization approach to signal reconstruction over switching networks

In this paper we consider signal reconstruction over communication network channels that can be modeled as input switching systems. Such systems can be associated with a variety of applications including control and estimation over networks. In particular, we formulate the signal reconstruction problem as a prototypical model matching problem where the various mappings involved belong to a class of input switching systems. The design interest is placed on minimizing the worst case or stochastic average performance of this model matching system over all possible switchings with an H₂ norm as the performance criterion. This minimization is performed over all stable receivers R in the class of input switching systems. For the particular setup at hand, and in the case of matched switching, two convergent sequences to the optimal solution from above and below respectively are formulated in terms of quadratic programs. An approximate solution with any a priori given precision is possible by finite truncation. Also, it is shown that in the cases of arbitrary, partially matched or unmatched switching, the optimal receiver R need not depend on the switching sequence and that it can be obtained as a linear time-invariant solution to an associated H₂ norm optimization.     

A survey of techniques for remote access to home networks and resources

Consumer Electronics devices are becoming network enabled, and along with smart phones and personal computers, they are all interconnected in home networks with broadband Internet connectivity. This sets the opportunity of making the home network, its devices and content accessible from the Internet, allowing the home owners to remotely access their connected home any time, any place, using any device. This paper provides a holistic overview of the “Remote Acces” topic, presenting all the problems and issues that make it challenging in different contexts, and most importantly analyzing six techniques and methods for enabling the remote access scenarios. It is a guide created by the combination of scientific research, extensive industrial experiences and first hand participation in relevant standardization activities.     

Economics of Dynamic Pricing in a Reputation Brokered Agent Mediated Marketplace

We present a framework to study the microeconomic effects in a reputation brokered Agent mediated Knowledge Marketplace, when we introduce dynamic pricing algorithms. We study the market with computer simulations of multiagent interactions. In this marketplace, the seller reputations are updated in a collaborative fashion based on the performance of the user in the delegated tasks. To the best of our knowledge this is the first agent mediated marketplace where the agents use dynamic pricing based on dynamically updated reputations. The framework can be used to investigate the different equilibria reached, based on the level of intelligence of the selling agents, the level of price-importance elasticity of the buying agents, and the level of unemployment in the marketplace. Preliminary experiments addressing these issues are presented.     

Synergy between Object Recognition and Image Segmentation Using the Expectation-Maximization Algorithm

In this work, we formulate the interaction between image segmentation and object recognition in the framework of the Expectation-Maximization (EM) algorithm. We consider segmentation as the assignment of image observations to object hypotheses and phrase it as the E-step, while the M-step amounts to fitting the object models to the observations. These two tasks are performed iteratively, thereby simultaneously segmenting an image and reconstructing it in terms of objects. We model objects using Active Appearance Models (AAMs) as they capture both shape and appearance variation. During the E-step, the fidelity of the AAM predictions to the image is used to decide about assigning observations to the object. For this, we propose two top-down segmentation algorithms. The first starts with an oversegmentation of the image and then softly assigns image segments to objects, as in the common setting of EM. The second uses curve evolution to minimize a criterion derived from the variational interpretation of EM and introduces AAMs as shape priors. For the M-step, we derive AAM fitting equations that accommodate segmentation information, thereby allowing for the automated treatment of occlusions. Apart from top-down segmentation results, we provide systematic experiments on object detection that validate the merits of our joint segmentation and recognition approach.     

The IA-64 Itanium processor cartridge

The Itanium processor cartridge is a packaging optimization for electrical and thermal performance in a server environment. The 3-in. x 5-in. cartridge contains the Itanium CPU, up to 4 megabytes of level-3 (L3) cache, an innovative power delivery scheme, and an integrated vapor chamber thermal spreading lid for removing power. Cartridges and a chip set can be ganged electrically by means of a glueless bidirectional, multidrop system bus. Power is delivered through a custom connection with separate voltages for the 0.18-micron CPU and 0.25-micron custom cache devices. An I²C serial connection provides access to system management features such as temperature monitoring and cartridge identification information