Corrigendum to “A model to control environmental performance of project execution process based on greenhouse gas emissions using earned value management” [Int. J. Proj. Manag. 36 (3) (April 2018) 397-413]

Abstract was revised as follows:In response to recent climate change, which is believed to be attributed to the release of greenhouse gas (GHG) emissions, many countries are placing CO₂ abatement programs such as carbon tax and cap-and-trade. Projects do have a significant share in GHGs and therefore their environmental performance, like their schedule and cost performance, should be monitored and controlled. Although many large projects would pass an environmental assessment in the project evaluation phase, the issue of environmental performance monitoring during the project execution phase has not been addressed in project management methodologies. The objective of this paper is to develop a model to estimate project GHG emissions, and to measure project GHG performance using the developed metrics, which can be used at any point in time over the life of a project. A comprehensive study is conducted to collect information on GHG emission factors of various project activity data (such as material use, energy and fuel consumption, transportation, etc.), and a user form interface is developed to calculate the total GHG of an activity. Also, a breakdown structure is proposed which supports managing all the project GHG accounts. The monitoring and control model is formulated based on the logic used in earned value management (EVM) methodology. The proposed model is then implemented to a work package of a real construction project. The results present the project initial GHG plan and show that the model is able to calculate project GHG variance by the reporting date and predict project final GHG based on a project GHG performance index. The method presented in this paper is general and can be applied to any type of projects in an organization that aims to reduce its carbon footprint. The same structure can be applied to monitor and control any other environmental impact associated with project execution process.     

Sparse representation based facial image compression via multiple dictionaries and separated ROI

Multimedia Tools and Applications - Constant increasing of visual information necessitates most efficient image compression schemes for saving storage space or reducing required transmission...     

Incorporation oftrans long-chain n−3 polyunsaturated fatty acids in rat brain structures and retina

During heat treatment, polyunsaturated fatty acids and specifically 18∶3n−3 can undergo geometrical isomerization. In rat tissues, 18∶3 Δ9c, 12c, 15t, one of thetrans isomers of linolenic acid, can be desaturated and elongated to givetrans isomers of eicosapentaenoic and docosahexaenoic acids. The present study was undertaken to determine whether such compounds are incorporated into brain structures that are rich in n−3 long-chain polyunsaturated fatty acids. Two fractions enriched intrans isomers of α-linolenic acid were prepared and fed to female adult rats during gestation and lactation. The pups were killed at weaning. Synaptosomes, brain microvessees and retina were shown to contain the highest levels (about 0.5% of total fatty acids) of thetrans isomer of docosahexaenoic acid (22∶6 Δ4c, 7c, 10c, 13c, 16c, 19t). This compound was also observed in myelin and sciatic nerve, but to a lesser extent (0.1% of total fatty acids). However, the ratios of 22∶6trans to 22∶6cis were similar in all the tissues studied. When the diet was deficient in α-linolenic acid, the incorporation oftrans isomers was apparently doubled. However, comparison of the ratios oftrans 18∶3n−3 tocis 18∶3n−3 in the diet revealed that thecis n−3 fatty acids were more easily desaturated and elongated to 22∶6n−3 than the correspondingtrans n−3 fatty acids. An increase in 22∶5n−6 was thus observed, as has previously been described in n−3 fatty acid deficiency. These results encourage further studies to determine whether or not incorporations of suchtrans isomers into tissues may have physiological implications. Presented in part at the 32nd International Conference on the Biochemistry of Lipids, 1991, Granada, Spain. Delta nomenclature (Δ) is used fortrans polyunsaturated fatty acids to specify the position and geometry of ethylenic bonds. Polyunsaturated fatty acids containingtrans double bonds are abbreviated giving the locations of thetrans double bonds only; e.g., 20∶5 Δ17t 20∶5 Δ5c,8c,11c,14c,17t; 22∶5 Δ19t, 22∶5 Δ7c,10c,13c,16c,19t; 22∶6 Δ19t 22∶6 Δ4c,7c,10c,13c,16c,19t.     

Condition Assessment of Buried Pipes Using Hierarchical Evidential Reasoning Model

Effective inspection and monitoring practices for the condition assessment of pipes ensure better decision(s) for repair or replacement before they fail. Pipe deterioration is a physical manifestation of the aging process in which many factors can contribute to structural failure. Various technologies/ techniques have been developed during the last few years to inspect/monitor piping systems, but how to intelligently interpret the collected data remains a challenge. In this paper, a new approach based on hierarchical evidential reasoning is proposed. This approach uses Dempster–Shafer (D-S) theory to make inferences for condition assessment of buried pipes. A hierarchical evidential reasoning model can help combine different distress indicators (bodies of evidence) at different hierarchical levels using D-S rule of combination. The proposed hierarchical evidential reasoning method is demonstrated with an example of condition assessment for a large diameter pipe. Information from multiple sources is fused to obtain a more reliable assessment of pipe deterioration.     

New Traversability Indices and Traversability Grid for Integrated Sensor/Map‐Based Navigation

This paper presents new measures of terrain traversability at short range and long range of a mobile robot; namely, local and global traversability indices. The sensor‐based local traversability index is related by a set of linguistic rules to large obstacles and surface softness within a short range of the robot measured by on‐board sensors. The map‐based global traversability index is obtained from the terrain topographic map, and is based on major surface features such as hills and lakes within a long range of the robot. These traversability indices complement the mid‐range sensor‐based regional traversability index introduced earlier. Each traversability index is represented by four fuzzy sets with the linguistic labels {POOR, LOW, MODERATE, HIGH}, corresponding to surfaces that are unsafe, moderately‐unsafe, moderately‐safe, and safe for traversal, respectively. The global terrain analysis also leads to the new concepts of traversability map and traversability grid for representation of terrain quality based on the global map information. The traversability indices are used in two sensor‐based traverse‐local and traverse‐regional behaviors and one map‐based traverse‐global behavior. These behaviors are integrated with a map‐based seek‐goal behavior to ensure that the mobile robot reaches its goal safely while avoiding both sensed and mapped terrain hazards. This provides a unified system in which the two independent sources of terrain quality information, i.e., prior maps and on‐board sensors, are integrated together for reactive robot navigation. The paper is concluded by a graphical simulation study. © 2003 Wiley Periodicals, Inc.     

Evidential reasoning using extended fuzzy Dempster–Shafer theory for handling various facets of information deficiency

This work investigates the problem of combining deficient evidence for the purpose of quality assessment. The main focus of the work is modeling vagueness, ambiguity, and local nonspecificity in information within a unified approach. We introduce an extended fuzzy Dempster–Shafer scheme based on the simultaneous use of fuzzy interval‐grade and interval‐valued belief degree (IGIB). The latter facilitates modeling of uncertainties in terms of local ignorance associated with expert knowledge, whereas the former allows for handling the lack of information on belief degree assignments. Also, generalized fuzzy sets can be readily transformed into the proposed fuzzy IGIB structure. The reasoning for quality assessment is performed by solving nonlinear optimization problems on fuzzy Dempster–Shafer paradigm for the fuzzy IGIB structure. The application of the proposed inference method is investigated by designing a reasoning scheme for water quality monitoring and validated through the experimental data available for different sampling points in a water distribution network. © 2011 Wiley Periodicals, Inc.     

Robust adaptive backstepping tracking control of stochastic nonlinear systems with unknown input saturation: A command filter approach

This paper studies the problem of adaptive observer‐based radial basis function neural network tracking control for a class of strict‐feedback stochastic nonlinear systems comprising an unknown input saturation, uncertainties, and unknown disturbances. To handle the issue of a non‐smooth saturation input signal, a smooth function is chosen to approximate the saturation function and the state observer is used to estimate unmeasured states. By the so‐called command filter method in the controller design procedure, the implementation complexity is reduced in the proposed backstepping method. Moreover, a radial basis function neural network is deployed to reconstruct the unknown nonlinear functions. In addition, the gains of all radial basis function neural networks are updated through one updating law leading to a minimal learning parameter which is independent of the number of neural nodes and the order of the system. Comparing with the existing results, the proposed approach can stabilize a constrained stochastic system more effectively and with less computational burden. Finally, a practical example shows the performance of the proposed controller design.     

An integrated robust probing motion planning and control scheme: A tube-based MPC approach

‘This paper introduces the integration of a probing scheme into a robust MPC-based robot motion planning and control algorithm. The proposed solution tackles the output-feedback tube-based MPC problem using the partially-closed loop strategy to incorporate future measurements in a computationally efficient manner. This combination will provide not only a robust controller but also avoids overly conservative planning which is a drawback of the original implementation of the output-feedback tube-based MPC. The proposed solution is composed of two controllers: (i) a nominal MPC controller with probing feature to plan a globally convergent trajectory in conjunction with active localization, and (ii) an ancillary MPC controller to stabilize the robot motion around the planned trajectory. The performance and real-time implementation of the proposed planning and control algorithms have been verified through both extensive numerical simulations and experiments with a mobile robot.