The treatment of sulfate-rich wastewater using an anaerobic sequencing batch biofilm pilot-scale reactor

This paper presents the results from 92 cycles of an anaerobic sequencing batch biofilm reactor containing biomass immobilized on inert support (mineral coal) applied for the treatment of an industrial wastewater containing high sulfate concentration. The pilot-scale reactor, with a total volume of 1.2 m³, was operated at sulfate loading rates ranging from 0.15 to 1.90 kgSO₄²⁻/cycle (48 h — cycle) corresponding to sulfate concentrations of 0.25 to 3.0 gSO₄²⁻ l^− 1. Domestic sewage and ethanol were utilized as electron donors for sulfate reduction. Influent sulfate concentrations were increased in order to evaluate the minimum COD/sulfate ratio at which high reactor performance could be maintained. The mean sulfate removal efficiency remained between the range of 88 to 92% at several sulfate concentrations. Temporal profiles along the 48 h cycles were carried out under stable operation at sulfate concentrations of 1.0, 2.0 and 3.0 gSO₄²⁻ l^− 1. Sulfate removal reached 99% for cycle times of 15, 25, and 30 h, and the effluents sulfate concentrations were lower than 8 mgSO₄²⁻ l^− 1. The results demonstrate the potential applicability of the anaerobic configuration for the biological treatment of sulfate-rich wastewaters.     

Experimental evaluation of loss perception in continuous media

Perception of multimedia quality, specified by quality-of-service (QoS) metrics, can be used by system designers to optimize customer satisfaction within resource bounds enforced by general-purpose computing platforms. Media losses, rate variations and transient synchronization losses have been suspected to affect human perception of multimedia quality. This paper presents metrics to measure such defects, and results of a series of user experiments that justify such speculations. Results of the study provide bounds on losses, rate variations and transient synchronization losses as a function of user satisfaction, in the form of Likert values. It is shown how these results can be used by algorithm designers of underlying multimedia systems.     

Deep interactive encoding with capsule networks for image classification

With new architectures providing astonishing performance on many vision tasks, the interest in Convolutional Neural Networks (CNNs) has grown exponentially in the recent past. Such architectures, however, are not problem-free. For instance, one of the many issues is that they require a huge amount of labeled data and are not able to encode pose and deformation information. Capsule Networks (CapsNets) have been recently proposed as a solution to the issues related to CNNs. CapsNet achieved interesting results in images recognition by addressing pose and deformation encoding challenges. Despite their success, CapsNets are still an under-investigated architecture with respect to the more classical CNNs. Following the ideas of CapsNet, we propose to introduce Residual Capsule Network (ResNetCaps) and Dense Capsule Network (DenseNetCaps) to tackle the image recognition problem. With these two architectures, we expand the encoding phase of CapsNet by adding residual convolutional and densely connected convolutional blocks. In addition to this, we investigate the application of feature interaction methods between capsules to promote their cooperation while dealing with complex data. Experiments on four benchmark datasets demonstrate that the proposed approach performs better than existing solutions.

     

Homography vs similarity transformation in aerial mosaicking: which is the best at different altitudes?

Multimedia Tools and Applications - Aerial image mosaicking of an area of interest is the process of combining multiple images, of an area with overlapping regions, into a single comprehensive...     

Electrodeposition of PbS multilayers on Ag(111) by ECALE

Lead sulfide (PbS) thin films were grown on a single crystal Ag(111) substrate by Electrochemical Atomic Layer Epitaxy (ECALE) method, i.e., by alternated underpotential deposition (UPD) of lead and sulfur. The electrochemical analysis includes the investigation of the underpotential deposition processes of both Pb and S, and the characterization of deposits obtained with different deposition cycles to confirm the attainment of the right stoichiometric ratio between Pb and S. The morphological analysis has been performed by Atomic Force Microscopy (AFM) for deposits formed with 50 and 75 deposition cycles and at different times of exposition to the atmosphere.     

Distributed architectures and logical-task decomposition inmultimedia surveillance systems

In the past few years, the development of complex surveillance systems has captured the interest of both the research and industrial worlds. Strong and challenging requirements of modern society are involved in this problem, which aims to increase safety and security in several application domains such as transport, tourism, home and bank security, military applications, etc. At the same time, fast improvements in microelectronics, telecommunications, and computer science make it necessary to consider new perspectives in this field. The main objective of this paper is to investigate, discuss, and evaluate the impact of distributed processing and new communication techniques on multimedia surveillance systems, which represent the so-called third-generation surveillance systems (3 GSSs). In particular, aspects related to the distribution of intelligence among multiple-processing and wide-bandwidth resources are discussed in detail. It is shown how distribution of intelligence can be obtained by a hierarchical architecture that partitions, in a dynamic way, the main logical processing tasks (i.e., representation, recognition, and communication) performed in a 3 GSS physical architecture made up of intelligent cameras, hubs, and central control rooms. The advantages of this solution are pointed out in terms of 1) increased flexibility and reconfigurability and 2) optimal allocation of available processing and bandwidth resources. Finally, a case study is analyzed that allows one to gain a deeper insight into a distributed surveillance system     

Modal method in deep metal-dielectric gratings: the decisive role of hidden modes

The modal method is well adapted for the modeling of deep-groove, high-contrast gratings of short period, possibly involving metal parts. Yet problems remain in the case of the TM polarization in the presence of metal parts in the corrugations: whereas most of the diffraction features are explained by the interplay of an astonishingly small number of true propagating and low-order evanescent modes, the exact solution of the diffraction problem requires the contribution of two types of evanescent modes that are usually overlooked. We investigate the nature and the role of these modes and show that metal gratings can be treated exactly by the modal method.     

Outdoor Scene Classification by a Neural Tree-Based Approach

This paper describes a Neural Tree (NT) based system for outdoor scene classification. A new NT classifier with backtracking capabilities is employed at different levels of the system architecture. First, it is used to obtain a rough interpretation of the scene by classifying each image pixel into multiple classes of static background objects, e.g. road, sky, vegetation, or into one generic class representing moving objects, e.g. vehicles, pedestrians. Then it is applied to obtain a more accurate scene interpretation by classifying all detected mobile objects into multiple classes, e.g. cars, lorries, buses, and also estimating their pose. Experiments have been performed on a large set of optical and infrared images. System performances are tested on both clean and noisy data, and comparative studies with other classifiers (i.e. a multi-layer perceptron, a binary decision tree, a standard NT and a bank of neural networks) and with other scene classification methods are carried out. Receiveed: 29 May 1998?,Received in revised form: 13 November 1998?Accepted: 15 December 1998     

Active video-based surveillance system: the low-level image and video processing techniques needed for implementation

The importance of video surveillance techniques has considerably increased since the latest terrorist incidents. Safety and security have become critical in many public areas, and there is a specific need to enable human operators to remotely monitor the activity across large environments. For these reasons, multicamera systems are needed to provide surveillance coverage across a wide area, ensuring object visibility over a large range of depths. In the development of advanced visual-based surveillance systems, a number of key issues critical to its successful operation must be addressed. This article describes the low-level image and video processing techniques needed to implement a modern surveillance system. In particular, the change detection methods for both fixed and mobile cameras (pan and tilt) are introduced and the registration methods for multicamera systems with overlapping and nonoverlapping views are discussed.