The impact of cleaner processing on nutrient availability in the bleached kraft industry.

The pulp and paper industry has invested heavily over recent years in cleaner processing, to reduce losses and minimise its impact on the environment. Over the past fifteen years, a New Zealand integrated bleached kraft mill has undergone a comprehensive programme of upgrades to increase production, reduce water consumption and streamline its biological treatment process. Whilst the overall discharge of contaminants from the site decreased, the treatment system performance did not show a concurrent improvement as may have been expected. Reduced BOD removal, low dissolved oxygen levels, and poor solids settlability were symptomatic of phosphorus limitation in the aerated lagoon treatment system. The wastewater entering the system was found to be phosphorus limited at a BOD:P ratio of 100:0.2. Mono-ammonium-phosphate was supplemented, at approximately 30 kg P/d, to raise the phosphorus levels to a BOD:P ratio of 100:0.3. Treatment efficiencies improved very quickly after phosphorus dosage, with a 50% reduction in BOD and TSS discharge, a significant increase in dissolved oxygen levels, and improved BOD removal (85% to 93%). This case study demonstrates that whilst more closed operation can result in reduced discharge of organic loads, there may be negative impacts on the availability of nutrients for balanced biological growth.     

Comparison of the efficacy of oxidative processes and flocculation for the removal of colour from Eop effluent.

Up to 30% of the released colour arising from bleached kraft pulp and paper production comes from the alkaline extraction stage. This waste stream can therefore be readily targeted to remove colour at source in mills where improved colour management is required. The efficacy of five advanced oxidative treatment and physico-chemical technologies in removing colour from a typical Eop stage effluent was compared. The most effective oxidative treatment was peroxymonosulphate (79% colour removal in 15 minutes). Ozone and TAML treatments removed 74% and 58% of colour respectively within 30 minutes. In comparison, hydrogen peroxide alone was only able to remove 35% of the colour over 4 hours. Coagulation with polyaluminium chloride achieved 89% colour removal within 5 minutes. However, this treatment produced an undesirable sludge, and may cause toxicity in the treated wastewater. Overall, colour removal ability of the five technologies ranked from highest to lowest was polyaluminium chloride > peroxymonosulfate > ozone > TAML > hydrogen peroxide. Other factors, such as operating costs, feedstock modification and capital infrastructure, also need to be taken into account when selecting the most suitable colour management option.     

The effects of various post-mortem treatments on certain physical and sensory properties of three different bovine muscles

Sixty crossbred steers with chronological ages approximating 15 months, carcass weights approximating 270 kg and subcutaneous fat thickness measurements approximating 1·2 cm, were maintained for approximately 210 days on a constantly increasing concentrate ration (13 to 75%, according to NAS nutrient requirements for beef cattle; NAS, 1976). These animals were utilized to evaluate the effects of delayed chilling, hot-boning and electrical stimulation on certain physical, histological, biochemical and sensory properties of three different muscles (Semimembranosus, SM; Longissimus dorsi, LD; and Triceps brachii, TB). Results indicated that neither delayed chilling nor electrical stimulation produced consistent meaningful alterations in any of the physical, cooking or palatability attributes evaluated. However, early post-mortem excision of muscle (hot-boning) consistently produced toughening in all of the muscles evaluated. This was observed to a much greater degree in the TB than in either the SM or LD. Based upon sarcomere length determinations, such toughening could be attributed to cold shortening only in the TB. Electrical stimulation of excised muscle was ineffective in preventing or offsetting this toughening. The delayed chilling treatment imposed (2 h at 12·5°C) was ineffective in enhancing potential effects of electrical stimulation on tenderness.     

Vision Based Neuro-Fuzzy Controller for a Two Axes Gimbal System with Small UAV

This paper presents the development of a vision-based neuro-fuzzy controller for a two axes gimbal system mounted on a small Unmanned Aerial Vehicle (UAV). The controller uses vision-based object detection as input and generates pan and tilt motion and velocity commands for the gimbal in order to keep the interest object at the center of the image frame. A readial basis function based neuro-fuzzy system and a learning algorithm is developed for the controller to address the dynamic and non-linear characteristics of the gimbal movement. The controller uses two separate, but identical radial basis function networks, one for pan and one for tilt motion of the gimbal. Each system is initialized with a fixed number of neurons that act as rules basis for the fuzzy inference system. The membership functions and rule strengths are then adjusted with the feedback from the visual tracking system. The controller is trained off-line until a desired error level is achieved. Training is then continued on-line to allow the system to accommodate air speed changes. The algorithm learns from the error computed from the detected position of the object in image frame and generates position and velocity commands for the gimbal movement. Several tests including lab tests and actual flight tests of the UAV have been carried out to demonstrate the effectiveness of the controller. Test results show that the controller is able to converge effectively and generate accurate position and velocity commands to keep the object at the center of the image frame.     

Video background modeling: recent approaches,issues and our proposed techniques

Effective and efficient background subtraction is important to a number of computer vision tasks. We introduce several new techniques to address key challenges for background modeling using a Gaussian mixture model (GMM) for moving objects detection in a video acquired by a static camera. The novel features of our proposed model are that it automatically learns dynamics of a scene and adapts its parameters accordingly, suppresses ghosts in the foreground mask using a SURF features matching algorithm, and introduces a new spatio-temporal filter to further refine the foreground detection results. Detection of abrupt illumination changes in the scene is dealt with by a model shifting-based scheme to reuse already learned models and spatio-temporal history of foreground blobs is used to detect and handle paused objects. The proposed model is rigorously tested and compared with several previous models and has shown significant performance improvements.     

Tensile modulus modeling of carbon‐filled nylon 6,6 and polycarbonate‐based resins

Electrically and thermally conductive resins can be produced by adding conductive fillers to insulating polymers. Mechanical properties, such as tensile modulus, are also important. This research focused on performing compounding runs followed by injection molding and tensile testing of carbon‐filled nylon 6,6 and polycarbonate‐based resins. The three carbon fillers investigated included an electrically conductive carbon black, synthetic graphite particles, and a milled pitch–based carbon fiber. For each polymer, resins were produced and tested that contained varying amounts of these single‐carbon fillers. In addition, combinations of fillers were investigated by conducting a full 2³ factorial design and a complete replicate in each polymer. These tensile modulus experimental results were then compared to results predicted by several different models. For the composites containing only one filler type, the Nielsen model with the modified Ψ term provided the best prediction of the actual experimental values. For the composites containing more than one filler type, a new parameter, which includes the vibrated bulk density (VBD) of the fillers, was incorporated into the Nielsen model with the modified Ψ term. This model with the new VBD parameter provided the best estimate of experimental tensile modulus for composites containing multiple‐filler types. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 90: 1716–1728, 2003     

Runout effects in milling: Surface finish, surface location error, and stability

This paper investigates the effect of milling cutter teeth runout on surface topography, surface location error, and stability in end milling. Runout remains an important issue in machining because commercially-available cutter bodies often exhibit significant variation in the teeth/insert radial locations; therefore, the chip load on the individual cutting teeth varies periodically. This varying chip load influences the machining process and can lead to premature failure of the cutting edges. The effect of runout on cutting force and surface finish for proportional and non-proportional tooth spacing is isolated here by completing experiments on a precision milling machine with 0.1 μm positioning repeatability and 0.02 μm spindle error motion. Experimental tests are completed with different amounts of radial runout and the results are compared with a comprehensive time-domain simulation. After verification, the simulation is used to explore the relationships between runout, surface finish, stability, and surface location error. A new instability that occurs when harmonics of the runout frequency coincide with the dominant system natural frequency is identified.     

Estimating storm discharge and water quality data uncertainty: A software tool for monitoring and modeling applications

Uncertainty estimates corresponding to measured hydrologic and water quality data can contribute to improved monitoring design, decision-making, model application, and regulatory formulation. With these benefits in mind, the Data Uncertainty Estimation Tool for Hydrology and Water Quality (DUET-H/WQ) was developed from an existing uncertainty estimation framework for small watershed discharge, sediment, and N and P data. Both the software and its framework-basis utilize the root mean square error propagation methodology to provide uncertainty estimates instead of more rigorous approaches requiring detailed statistical information, which is rarely available. DUET-H/WQ lists published uncertainty information for data collection procedures to assist the user in assigning appropriate data-specific uncertainty estimates and then calculates the uncertainty for individual discharge, concentration, and load values. Results of DUET-H/WQ application in several studies indicated that substantial uncertainty can be contributed by each procedural category (discharge measurement, sample collection, sample preservation/storage, laboratory analysis, and data processing and management). For storm loads, the uncertainty was typically least for discharge (±7–23%), greater for sediment (±16–27%) and dissolved N and P (±14–31%) loads, and greater yet for total N and P (±18–36%). When these uncertainty estimates for individual values were aggregated within study periods (i.e. total discharge, average concentration, and total load), uncertainties followed the same pattern (Q < TSS < dissolved N and P < total N and P). This rigorous demonstration of uncertainty in discharge and water quality data illustrates the importance of uncertainty analysis and the need for appropriate tools. It is our hope that DUET-H/WQ contributes to making uncertainty estimation a routine data collection and reporting procedure and thus enhances environmental monitoring, modeling, and decision-making. Hydrologic and water quality data are too important for scientists to continue to ignore the inherent uncertainty.     

Picbreeder: a case study in collaborative evolutionary exploration of design space

For domains in which fitness is subjective or difficult to express formally, interactive evolutionary computation (IEC) is a natural choice. It is possible that a collaborative process combining feedback from multiple users can improve the quality and quantity of generated artifacts. Picbreeder, a large-scale online experiment in collaborative interactive evolution (CIE), explores this potential. Picbreeder is an online community in which users can evolve and share images, and most importantly, continue evolving others' images. Through this process of branching from other images, and through continually increasing image complexity made possible by the underlying neuroevolution of augmenting topologies (NEAT) algorithm, evolved images proliferate unlike in any other current IEC system. This paper discusses not only the strengths of the Picbreeder approach, but its challenges and shortcomings as well, in the hope that lessons learned will inform the design of future CIE systems.