Robust optimisation of sustainable food grain transportation with uncertain supply and intentional disruptions

The proliferating need for sustainability intervention in food grain transportation planning is anchoring the attention of researchers in the interests of stakeholders and environment at large. Uncertainty associated with food grain supply further intensifies the problem steering the need for designing robust, cost-efficient and sustainable models. In line with this, this paper aims to develop a robust and sustainable intermodal transportation model to facilitate single type of food grain commodity shipments while considering procurement uncertainty, greenhouse gas emissions, and intentional hub disruption. The problem is designed as a mixed integer non-linear robust optimisation model on a hub and spoke network for evaluating near optimal shipment quantity, route selection and hub location decisions. The robust optimisation approach considers minimisation of total relative regret associated with total cost subject to several real-time constraints. A version of Particle Swarm Optimisation with Differential Evolution is proposed to tackle the resulting NP-hard problem. The model is tested with two other state-of the art meta-heuristics for small, medium, and large datasets subject to different procurement scenarios inspired from real time food grain operations in Indian context. Finally, the solution is evaluated with respect to total cost, model and solution robustness for all instances.     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

Demonstration of a tool for automatic learning and re-use of knowledge in the activated sludge process.

Wastewater treatment plant operators encounter complex operational problems related to the activated sludge process and usually respond to these by applying their own intuition and by taking advantage of what they have learnt from past experiences of similar problems. However, previous process experiences are not easy to integrate in numerical control, and new tools must be developed to enable re-use of plant operating experience. The aim of this paper is to investigate the usefulness of a case-based reasoning (CBR) approach to apply learning and re-use of knowledge gained during past incidents to confront actual complex problems through the IWA/COST Benchmark protocol. A case study shows that the proposed CBR system achieves a significant improvement of the benchmark plant performance when facing a high-flow event disturbance.     

Analysis of enterococci using portable testing equipment for developing countries--variance of Azide NutriDisk medium under variable time and temperature.

This report compares the enterococci count on samples obtained with Azide NutriDisk (AND) (sterile, dehydrated culture medium) and Slanetz and Bartley (SB) medium when exposed to a variable in incubation time and temperature. Three experiments were performed to examine the recovery of enterococci on AND and SB media using membrane filtration with respect to: (a) incubation time; (b) incubation temperature; and (c) a combination of the two. Presumptive counts were observed at 37, 41, 46 and 47 degrees C and at 20, 24, 28 and 48 h. These were compared to AWWA standard method 9230 C (44 degrees C, 44 h). Samples were confirmed using Kanamycin Aesculin Azide (KAA) agar. Friedman's ANOVA and Students t-test analysis indicated higher enumeration of enterococci when grown on AND (p = 0.45) than SB (p = < 0.001) at all temperatures with a survival threshold at 47 degrees C. Significant results for AND medium were noted at 20 h (p = 0.021), 24 h (p = 0.278) and 28 h (p = 0.543). The study concluded that the accuracy of the AND medium at a greater time and temperature range provided flexibility in incubator technology making it an appropriate alternative to SB medium for monitoring drinking water using field testing kits in developing countries.     

Enhancing urban infrastructure investment planning practices for a changing climate.

Climate change raises many concerns for urban water management because of the effects on all aspects of the hydrological cycle. Urban water infrastructure has traditionally been designed using historical observations and assuming stationary climatic conditions. The capability of this infrastructure, whether for storm-water drainage, or water supply, may be over- or under-designed for future climatic conditions. In particular, changes in the frequency and intensity of extreme rainfall events will have the most acute effect on storm-water drainage systems. Therefore, it is necessary to take future climatic conditions into consideration in engineering designs in order to enhance water infrastructure investment planning practices in a long time horizon. This paper provides the initial results of a study that is examining ways to enhance urban infrastructure investment planning practices against changes in hydrologic regimes for a changing climate. Design storms and intensity-duration-frequency curves that are used in the engineering design of storm-water drainage systems are developed under future climatic conditions by empirically adjusting the general circulation model output, and using the Gumbel distribution and the Chicago method. Simulations are then performed on an existing storm-water drainage system from NE Calgary to investigate the resiliency of the system under climate change.     

Ecophysiology and niche differentiation of Nitrospira-like bacteria, the key nitrite oxidizers in wastewater treatment plants.

Nitrite-oxidizing bacteria of the genus Nitrospira are key nitrifiers in wastewater treatment plants. Pure cultures of these organisms are unavailable, but cultivation-independent molecular methods make it possible to detect Nitrospira-like bacteria in environmental samples and to investigate their ecophysiology. Comprehensive screening of natural and engineered habitats and of public databases for 16S rRNA sequences of Nitrospira-like bacteria revealed a surprisingly high biodiversity in the genus Nitrospira, which comprises at least four phylogenetic sublineages. All Nitrospira-like bacteria detected in wastewater treatment plants belonged to the sublineages I and II. Subsequently, the population dynamics of different Nitrospira-like bacteria were monitored, by quantitative fluorescence in situ hybridization with rRNA-targeted probes, confocal laser scanning microscopy and digital image analysis, during incubation of nitrifying activated sludge in media containing different nitrite concentrations. These experiments showed that Nitrospira-like bacteria, which were affiliated with the phylogenetic sublineages I or II of the genus Nitrospira, responded differently to nitrite concentration shifts. Previously unknown properties of Nitrospira-like bacteria were discovered in the course of an environmental genomics project. Implications of the obtained results for fundamental understanding of the microbial ecology of nitrite oxidizers as well as for future improvement of nutrient removal in wastewater treatment plants are discussed.     

Analysis of phosphorus removal and anaerobic selector performance in a full-scale activated sludge process in Singapore.

This paper analyses the performance of the anaerobic selector (A/O process) in a full-scale activated sludge process receiving mostly industrial sewage discharge (> 60%) in Singapore. In addition to the sludge settleability, enhanced biological phosphorus removal (EBPR) was studied. The sludge volume index (SVI) reduced from 200 to 80 ml g(-1) and foaming was suppressed significantly, indicating the effectiveness of the anaerobic selector in improving sludge settleability. The phosphorus removal efficiency was 66%, and 7.5 mg HAc-COD was consumed per mg PO4(3-) -P removed. In the anaerobic compartment, 31% of the SCOD and 73% of the acetic acid in the settled sewage were removed with PO4(3-) -P release of 14.1 mg PO4(3-)-P l(-1). The linear correlation between PO4(3-) -P release in the anaerobic compartment and PO4(3-) -P uptake in the aerobic compartment indicates that there is about 0.8 mg PO4(3-) -P release in the anaerobic compartment per mg PO34(3-) -P uptake in the aerobic compartment. The fates of volatile fatty acids (VFAs) and its short chain acids (SCAs) in the process were studied and discussed.     

Using decision analysis to determine optimal experimental design for monitoring sewer exfiltration with tracers.

The tracer methods developed to assess exfiltration from sewers in the European project APUSS (assessment of the performance of sewer systems) have a high degree of freedom with regard to the choice of tracer and the dosing strategy. These can lead to very different degrees of uncertainty in the measured exfiltration ratio. In this study, we demonstrate how to select an optimal experimental design using decision analysis, which accounts for this uncertainty and its associated costs. Although the results are site-specific, we can conclude generally that, when NaCl is used as the tracer, the accuracy of the exfiltration estimate is most sensitive to the amount of tracer used and the starting time of the experiment.     

Tracking influent inorganic suspended solids through wastewater treatment plants.

From an experimental and theoretical investigation of the continuity of influent inorganic suspended solids (ISS) along the links connecting the primary settling tank (PST), fully aerobic or N removal activated sludge (AS) and anaerobic and aerobic sludge digestion unit operations, it was found that the influent wastewater (fixed) ISS concentration is conserved through primary sludge anaerobic digestion, activated sludge and aerobic digestion unit operations. However, the measured ISS flux at different stages through a series of wastewater treatment plant (WWTP) unit operations is not equal to the influent ISS flux, because the ordinary heterotrophic organisms (OHO) biomass contributes to the ISS flux by differing amounts depending on the active fraction of the VSS solids at that stage.     

One-dimensional GIS-based model compared with a two-dimensional model in urban floods simulation.

A GIS-based one-dimensional flood simulation model is presented and applied to the centre of the city of N?mes (Gard, France), for mapping flow depths or velocities in the streets network. The geometry of the one-dimensional elements is derived from the Digital Elevation Model (DEM). The flow is routed from one element to the next using the kinematic wave approximation. At the crossroads, the flows in the downstream branches are computed using a conceptual scheme. This scheme was previously designed to fit Y-shaped pipes junctions, and has been modified here to fit X-shaped crossroads. The results were compared with the results of a two-dimensional hydrodynamic model based on the full shallow water equations. The comparison shows that good agreements can be found in the steepest streets of the study zone, but differences may be important in the other streets. Some reasons that can explain the differences between the two models are given and some research possibilities are proposed.