Flow pattern measurement in a full scale silo containing iron ore

The flow pattern in a silo is important because it affects both the recovery of solids and the pressures on the silo wall during discharge. Wherever mass flow is not achieved, the boundary of the flow channel has significant implications for both the functional and structural design of the silo. Many techniques have been used for the study of flow patterns in model silos, but most cannot be used at full scale, and very few quality measurements at full scale have ever been made. This paper outlines a full scale experimental study in which the patterns of solids flow and the flow channel boundaries are reliably quantified.The full scale silo was specially designed, constructed and instrumented to exhibit funnel flow and to make observations of the solids flow pattern and the silo wall pressures. It had three outlets: one concentric, one fully eccentric and one in between. Three materials were used: iron ore pellets, slag fines and crushed basalt. This paper describes experiments involving iron ore pellets. The silo was seeded with radio frequency tags whose residence times were measured by detecting them on exit during discharge. The residence time data were studied to deduce the discharge flow pattern. This paper presents the results of three different flow pattern interpretation techniques: the best of them (mass-time relationships) is shown to give a very clear identification of the solids flow pattern and the flow channel boundary.     

Kinetics of hydrogen peroxide bleaching of ALCELL® derived pulp

In this study, a kinetic model of the final bleaching stage with hydrogen peroxide in a totally chlorine free (TCF) bleaching sequence for ALCELL® processed pulp was developed. The model was based on the rate of chromophore destruction characterized by the decrease in the light absorption coefficient of bleached pulp at 457 nm, C_K. Based on the fact that the chromophore destruction proceeds rapidly in an initial phase followed by a much slower reaction during which a “floor-level” chromophore concentration is approached asymptotically, we propose that the hydrogen peroxide stage of the ALCELL® derived pulp in the studied TCF sequence consists of two distinct phases. The initial phase is a very fast reaction. The rate equation of the second phase was determined as: which is valid in a pH range of 10.5 to 11.5 and a temperature range of 60 to 92.5°C.     

Rigid Polyurethane Foam Production from Palm Oil-Based Epoxidized Diethanolamides

A new type of rigid polyurethane foam was produced by incorporating oxazolidone heterocyclic rings on to polyurethane backbones. Epoxidized diethanolamides were synthesized by reacting palm oil blends of epoxidized palm olein and refined bleached deodorized palm kernel olein with diethanolamine to produce rigid polyurethane foams. Epoxides, retained in the diethanolamides, reacted with isocyanate during foam production in the presence of AlCl₃–THF complex catalyst to form oxazolidone linkages in the polyurethane network. The carbonyl stretch of oxazolidone was identified at 1,750 cm⁻¹ through Fourier Transform Infra Red analysis. Chemical modifications of the polyurethane network also improved the thermal and mechanical properties of the foams. In addition, isocyanate index 1.4 was determined to be the most suitable in the production of foams from this newly synthesized epoxidized diethanolamides.     

Faceless identification based on temporal strips

This paper first presents a novel approach for modelling facial features, Local Directional Texture (LDT), which exploits the unique directional information in image textures for the problem of face recognition. A variant of LDT with privacy-preserving temporal strips (TS) is then considered to achieve faceless recognition with a higher degree of privacy while maintaining high accuracy. The TS uses two strips of pixel blocks from the temporal planes, XT and YT, for face recognition. By removing the reliance on spatial context (i.e., XY plane) for this task, the proposed method withholds facial appearance information from public view, where only one-dimensional temporal information that varies across time are extracted for recognition. Thus, privacy is assured, yet without impeding the facial recognition task which is vital for many security applications such as street surveillance and perimeter access control. To validate the reliability of the proposed method, experiments were carried out using the Honda/UCSD, CK+, CAS(ME)² and CASME II databases. The proposed method achieved a recognition rate of 98.26% in the standard video-based face recognition database, Honda/UCSD. It also offers a 81.92% reduction in the dimension length required for storing the extracted features, in contrast to the conventional LBP-TOP.

     

Evaluation of Reorientation Techniques and Distractors for Walking in Large Virtual Environments

Vir tual Environments (VEs) that use a real-walking locomotion interface have typically been restricted in size to the area of the tracked lab space. Techniques proposed to lift this size constraint, enabling real walking in VEs that are larger than the tracked lab space, all require reorientation techniques (ROTs) in the worst-case situation—when a user is close to walking out of the tracked space. We propose a new ROT using visual and audial distractors—objects in the VE that the user focuses on while the VE rotates—and compare our method to current ROTs through three user studies. ROTs using distractors were preferred and ranked more natural by users. Our findings also suggest that improving visual realism and adding sound increased a user's feeling of presence. Users were also less aware of the rotating VE when ROTs with distractors were used.     

Avatar mobility in user-created networked virtual worlds: measurements, analysis, and implications

We collected mobility traces of avatars spanning multiple regions in Second Life, a popular user-created virtual world. We analyzed the traces to characterize the dynamics of the avatars’ mobility and behavior, both temporally and spatially. We discuss the implications of our findings on the design of peer-to-peer architecture, interest management, mobility modeling of avatars, server load balancing and zone partitioning, caching, and prefetching for user-created virtual worlds.     

Nanomembrane‐Based,Thermal‐Transport Biosensor for Living Cells

Knowledge of materials' thermal‐transport properties, conductivity and diffusivity, is crucial for several applications within areas of biology, material science and engineering. Specifically, a microsized, flexible, biologically integrated thermal transport sensor is beneficial to a plethora of applications, ranging across plants physiological ecology and thermal imaging and treatment of cancerous cells, to thermal dissipation in flexible semiconductors and thermoelectrics. Living cells pose extra challenges, due to their small volumes and irregular curvilinear shapes. Here a novel approach of simultaneously measuring thermal conductivity and diffusivity of different materials and its applicability to single cells is demonstrated. This technique is based on increasing phonon‐boundary‐scattering rate in nanomembranes, having extremely low flexural rigidities, to induce a considerable spectral dependence of the bandgap‐emission over excitation‐laser intensity. It is demonstrated that once in contact with organic or inorganic materials, the nanomembranes' emission spectrally shift based on the material's thermal diffusivity and conductivity. This NM‐based technique is further applied to differentiate between different types and subtypes of cancer cells, based on their thermal‐transport properties. It is anticipated that this novel technique to enable an efficient single‐cell thermal targeting, allow better modeling of cellular thermal distribution and enable novel diagnostic techniques based on variations of single‐cell thermal‐transport properties.     

An effective 3-in-1 keyword search method over heterogeneous data sources

Conventional keyword search engines are restricted to a given data model and cannot easily adapt to unstructured, semi-structured or structured data. In this paper, we propose an efficient and adaptive keyword search method, called EASE, for indexing and querying large collections of heterogeneous data. To achieve high efficiency in processing keyword queries, we first model unstructured, semi-structured and structured data as graphs, and then summarize the graphs and construct graph indices instead of using traditional inverted indices. We propose an extended inverted index to facilitate keyword-based search, and present a novel ranking mechanism for enhancing search effectiveness. We have conducted an extensive experimental study using real datasets, and the results show that EASE achieves both high search efficiency and high accuracy, and outperforms the existing approaches significantly.