Virtual reflected-light microscopy

Research on better methods to digitally represent microscopic specimens has increased over recent decades. Opaque specimens, such as microfossils and metallurgic specimens, are often viewed using reflected light microscopy. Existing 3D surface estimation techniques for reflected light microscopy do not model reflectance, restricting the representation to only one illumination condition and making them an imperfect recreation of the experience of using an actual microscope. This paper introduces a virtual reflected-light microscopy (VRLM) system that estimates both shape and reflectance from a set of specimen images. When coupled with anaglyph creation, the system can depict both depth information and illumination cues under any desired lighting configuration. Digital representations are compact and easily viewed in an online setting. A prototype used to construct VRLM representations is comprised only of a microscope, a digital camera, a motorized stage and software. Such a system automatically acquires VRLM representations of large batches of specimens. VRLM representations are then disseminated in an interactive online environment, which allows users to change the virtual light source direction and type. Experiments demonstrate high quality VRLM representations of 500 microfossils.     

Evaluating Social Navigation Visualization in Online Geographic Maps

Social navigation enables emergent collaboration between independent collaborators by exposing the behavior of each individual. This is a powerful idea for web-based visualization, where the work of one user can inform other users interacting with the same visualization. Results from a crowdsourced user study evaluating the value of such social navigation cues for a geographic map service are presented. Results show significantly improved performance for participants who interacted with the map when the visual footprints of previous users were visible.     

Introduction: In-Use,In-Situ: Extending Field Research Methods—Part 2

This study used protocol analyses and user drawings of their models of the system to investigate the “getting lost” problem in hypertext navigation. The “getting lost” problem is viewed as occurring when routine expectations of naive users, concerning appropriate linear sequences, are violated. Several ways in which users persistently attempt to work within a linear model, despite its inapplicability, are examined. The transition to more hierarchical user models is described.     

A combined UASB-MBR with shortcut nitrification-denitrification for energy reduction in wastewater reclamation

Shortcut nitrification has been successfully applied in a laboratory scale nitrification-denitrification process consisting of an up-flow anaerobic sludge blanket (UASB) and an aerobic membrane bioreactor (MBR) in treating synthetic and municipal wastewater to simultaneously remove organic carbon and nitrogen. For the treatment of synthetic wastewater, the combined system exhibited a high TOC removal of 98% with a steady ammonia removal efficiency of about 98% in the MBR and a total nitrogen (TN) removal efficiency of 90%. In treating municipal wastewater, due to its low COD concentration, removal efficiencies of TOC, ammonia and TN were 70%, 98% and 60%, respectively. The biogas production was around 76.4 L/m3 wastewater when treating synthetic wastewater. However, little biogas was produced when treating municipal wastewater which was the result of low organic carbon loading to the UASB. Energy analysis has demonstrated that this novel shortcut nitrification process could consume less energy than a conventional process and have the potential of bio-energy generation via biogas production thus helping to achieve a more favorable energy balance.     

Lot streaming for product assembly in job shop environment

Assembly job shop scheduling problem (AJSP) is an extension of classical job shop scheduling problem (JSP). AJSP starts with JSP and appends an assembly stage to the completed jobs. Lot streaming (LS) technique is a process of splitting jobs into smaller sub-jobs such that successive operations can be overlapped. This paper combines, for the first time, LS and AJSP, extending LS applicability to both machining and assembly. To solve this complex problem, an efficient algorithm is proposed using genetic algorithms and simple dispatching rules. Experimental results suggest that equal size LS outperforms varied size LS with respect to the objective function.     

Perceptual image preview

Image preview is a convenient way to browse large or multiple images on small displays. However, current signal-level image resampling algorithms may remove many features of interest in the preview image. In this paper, we propose perceptual image preview which retains more perceptual features such that users can inspect features of interest by viewing the preview image only and without zooming in. This technology has two components, structure enhancement and perceptual feature visualization. Structure enhancement enhances the image structure while suppressing subtle details using a gradient modulation method, thus making the succedent perceptual features more apparent. For perceptual feature visualization, features of interest detected in the picture is visualized on the structure enhanced preview image. We demonstrate with two examples of most commonly used image quality features, image blur and noise. The effectiveness of the proposed method is validated by experimental results.     

A decision support system for environmental effects monitoring

The Environmental Effects Monitoring (EEM) Statistical Assessment Tool (SAT) Decision Support System (DSS) has been developed to provide a user-friendly data analysis, display and decision support tool for Canada's federal environmental effects monitoring program for the pulp and paper and mining industries. The target users include industries, consultants, regional EEM coordinators, National EEM Office and scientists involved in EEM-related research. The tool allows the assessment of the effects of effluent from industrial or other sources on fish and benthic populations. Effect endpoints, which are used as indicators of potentially important effluent effects, are measured at effluent-exposed sites and are compared statistically to measures at reference sites, in order to determine if changes have occurred and the magnitude of the changes. The main driver of the EEM-SAT DSS is its rule-based expert system. The results are used in assessing the adequacy of existing regulations for protecting aquatic environments.     

Congestion-aware channel assignment for multi-channel wireless mesh networks

In this paper, we propose a distributed congestion-aware channel assignment (DCACA) algorithm for multi-channel wireless mesh networks (MC–WMNs). The frequency channels are assigned according to the congestion measures which indicate the congestion status at each link. Depending on the selected congestion measure (e.g., queueing delay, packet loss probability, and differential backlog), various design objectives can be achieved. Our proposed distributed algorithm is simple to implement as it only requires each node to perform a local search. Unlike most of the previous channel assignment schemes, our proposed algorithm assigns not only the non-overlapped (i.e., orthogonal) frequency channels, but also the partially-overlapped channels. In this regard, we introduce the channel overlapping and mutual interference matrices which model the frequency overlapping among different channels. Simulation results show that in the presence of elastic traffic (e.g., TCP Vegas or TCP Reno) sources, our proposed DCACA algorithm increases the aggregate throughput and also decreases the average packet round-trip compared with the previously proposed Load-Aware channel assignment algorithm. Furthermore, in a congested IEEE 802.11b network setting, compared with the use of three non-overlapped channels, the aggregate network throughput can further be increased by 25% and the average round-trip time can be reduced by more than one half when all the 11 partially-overlapped channels are used.     

Mixed-reality environment for frictional parameters identification in servo-pneumatic system

This paper outlines a method to identify the friction parameters for servo-pneumatic systems using a mixed-reality environment. To acquire system friction parameters accurately can be extremely difficult once the servo-system has been assembled because of its highly nonlinear nature, which causes a great difficulty in servo-pneumatic system modelling and control. In this research, a mixed-reality environment has been employed to determine the friction parameters effectively and efficiently through online identification. Traditionally, friction parameters identification can be performed manually or automatically using traditional optimization methods or modern ones such as neural networks. The advantages of the proposed method are the high accuracy in the estimated parameters, its simplicity and its speed. An experimental case study has been conducted and the results showed the accuracy and effectiveness of the proposed method.