Multi-level attention model for tracking and segmentation of objects under complex occlusion

A multi-level attention framework for tracking and segmentation of humans and objects under complex occlusions is investigated, featuring an effective probabilistic appearance-based technique for pixel reclassification during object grouping and splitting. A novel ’spatial-depth affinity metric’ is introduced in the conventional likelihood function, utilising information of both spatial locations of pixels and dynamic depth ordering of the component objects in grouping. Depth ordering estimation is achieved through a combination of top-down and bottom-up approach. Experiments on some realworld difficult scenarios of low quality and highly compressed videos demonstrate the very promising results achieved.     

Knowledge-based control and case-based diagnosis based upon empirical knowledge and fuzzy logic for the SBR plant.

Because biological wastewater treatment plants (WWTPs) involve a long time-delay and various disturbances, in general, skilled operators manually control the plant based on empirical knowledge. And operators usually diagnose the plant using similar cases experienced in the past. For the effective management of the plant, system automation has to be accomplished based upon operating recipes. This paper introduces automatic control and diagnosis based upon the operator's knowledge. Fuzzy logic was employed to design this knowledge-based controller because fuzzy logic can convert the linguistic information to rules. The controller can manage the influent and external carbon in considering the loading rate. The input of the controller is not the loading rate but the dissolved oxygen (DO) lag-time, which has a strong relation to the loading rate. This approach can replace an expensive sensor, which measures the loading rate and ammonia concentration in the reactor, with a cheaper DO sensor. The proposed controller can assure optimal operation and prevent the over-feeding problem. Case-based diagnosis was achieved by the analysis of profile patterns collected from the past. A new test profile was diagnosed by comparing it with template patterns containing normal and abnormal cases. The proposed control and diagnostic system will guarantee the effective and stable operation of WWTPs.     

Photocatalytic oxidation of low concentration 2,4-D solution with new TiO2 fiber catalyst in a continuous flow reactor.

Environmental pollution by low concentrations of 2,4-Dichlorophenoxyacetic acid (2,4-D) is a concern these days due to ever increasingly stringent regulations. Photocatalysis with immobilized TiO2 fiber is a promising oxidation method. Laboratory experiments on photocatalytic degradation of 0.045 mmol l(-1) 2,4-D with the world's first high-strength TiO2 fiber catalyst were carried out in a continuous flow reactor in which the degradations were, in general, similar to those with high 2,4-D concentrations investigated elsewhere. Degradation and mineralization of 2,4-D were significantly enhanced with no initial pH adjustments. The rate constants for total organic carbon (TOC) without pH adjustment were about two-fold bigger than the pH adjustment cases. CO2 gas measurement and carbon mass-balance were carried out for the first time, where about 34% organic carbon converted into CO2 gas during four-hour oxidation. 2,4-Dichlorophenol (2,4-DCP), phenol, benzyl alcohol and two unknowns (RT = 2.65 and 3.78 min.) were detected as aromatic intermediates while Phenol was the new aromatic in HPLC analysis. Dechlorination efficiencies were high (> 70%) in all the cases, and more than 90% efficiencies were observed in chloride mass balance. Bigger flow rates and solution temperature fixed at 20 degrees C without pH adjustment greatly enhanced 2,4-D mineralization. These results can be an important basis in applying the treatment method for dioxin-contaminated water and wastewater.     

Electrical Properties of GeO2–NiO Materials Containing Ni2GeO4

The GeO₂–NiO system is studied in the stability range of Ni₂GeO₄ by temperature-dependent resistivity measurements, in combination with x-ray diffraction, differential thermal analysis, and thermogravimetry. The resistivity of the starting mixtures and heat-treated samples is measured in the composition range 55–90 mol % NiO. The effect of air humidity on the resistivity of the samples is examined.     

A multigrid accelerated hybrid unstructured mesh method for 3D compressible turbulent flow

 A cell vertex finite volume method for the solution of steady compressible turbulent flow problems on unstructured hybrid meshes of tetrahedra, prisms, pyramids and hexahedra is described. These hybrid meshes are constructed by firstly discretising the computational domain using tetrahedral elements and then by merging certain tetrahedra. A one equation turbulence model is employed and the solution of the steady flow equations is obtained by explicit relaxation. The solution process is accelerated by the addition of a multigrid method, in which the coarse meshes are generated by agglomeration, and by parallelisation. The approach is shown to be effective for the simulation of a number of 3D flows of current practical interest. Sponsored by The Research Council of Norway, project number 125676/410 Dedicated to the memory of Prof. Mike Crisfield, a respected colleague     

Catalytic aminolysis of epoxide by alumina prepared from amine-protected Al precursor

The catalytic activities of alumina prepared from an Al alkoxide-amine adduct monomer for the reaction of cyclopentene oxide with piperidine was determined after various pretreatments, including calcination and exposure to moisture. They were compared with the activity of alumina prepared by the conventional hydrolysis method. It was found that the as-prepared sample from the alkoxide-amine monomer preparation was five times more active than a conventional preparation, suggesting that it has a higher density of surface Lewis acid sites. However, its activity was much more severely suppressed by exposure to moisture.     

Sequential testing of sorted and transformed data as an efficient way to implement long GLRTs

It is often required to detect a long weak signal in Gaussian noise, and frequently, the exact form of that signal is parameterized but not known. A bank of matched filters provides an appropriate detector. However, in some practical applications, there are very many matched filters, and most are quite long. The consequent computational needs may render the classical bank-of-filters approach infeasibly expensive. One example, and our original motivation, is the detection of chirp gravitational waves by an Earth-based interferometer. In this paper, we provide a computational approach to this problem via sequential testing. Since the sequential tests to be used are not for constant signals, we develop the theory in terms of average sample number (ASN) for this case. Specifically, we propose two easily calculable expressions for the ASN: one a bound and the other an approximation. The sequential approach does yield moderate computational savings, but we find that by preprocessing the data using short/medium fast Fourier transforms (FFTs) and an appropriate sorting of these FFT outputs such that the most informative samples are entered to a sequential test first, quite high numerical efficiency can be realized. The idea is simple but appears to be quite successful: Examples are presented in which the computational load is reduced by several orders of magnitude. The FFT is an example of an energy-agglomerating transform, but of course, there are many others. The point here is that the transform need not match the sought signal exactly in the sense that all energy becomes confined to a single sample; it is enough that the energy becomes concentrated, and the more concentrated the better.     

Nonlinearity analysis and optimization of HBTs for optical mixer designs

Two types of photo heterojunction bipolar transistor (HBT) to directly down-convert optical signals to electronic signals have been reported in the literature: a conventional photo-HBT in which light penetrates through the area of the base-collector junction and an HBT where light shines through the base-collector edge for higher conversion efficiency. Although the performance in relation to bias conditions has been published, the detailed analyses for identifying the parameters and bias conditions that provide optimum direct down-conversion have not been examined. This paper provides a full explanation of the operation of the down-conversion for both HBT configurations based on low-frequency analyses. Such information is useful for both understanding the nonlinear mechanisms involved and designing for maximum efficiency. In addition, a new circuit has been developed from the basic HBT down-conversion circuit that provides improved performance.     

Radiometric sensor for temperature control of food processing

This paper describes a novel planar antenna sensor created for the purpose of noninvasive temperature measurements using microwave radiometry. In order to improve radiometric measurements in industrial applications, a new generation of sensors is introduced, composed of a metallic sheet. Simulations based upon the method of moments is used both to design and to determine their electromagnetic performances. This paper also describes a radiometric device using these sensors to measure and control the temperature of food products during deep freezing processes. The results and discussions are presented.