Improving the estimation of project overheads in construction companies in Hong Kong

Project overheads cover the site cost of administrating a project as a whole, rather than a particular work section. Estimation of these items is one of the routine tasks of all parties including the contractors and project owners. Nevertheless, our understanding of this subject mainly lies on the theoretical level due to the limited empirical study in the past. More importantly, estimation of project overheads demands a lot of expertise but still exhibits a high risk of inaccuracy. Therefore, the aims of this research study are to explore the estimation and expenses of project overheads in practice and to devise an efficient model for project overheads estimation. [Continues.

A branching fuzzy-logic classifier for building optimization

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005.Includes bibliographical references (p. 109-110).We present an input-output model that learns to emulate a complex building simulation of high dimensionality. Many multi-dimensional systems are dominated by the behavior of a small number of inputs over a limited range of input variation. Some also exhibit a tendency to respond relatively strongly to certain inputs over small ranges, and to other inputs over very large ranges of input variation. A branching linear discriminant can be used to isolate regions of local linearity in the input space, while also capturing the effects of scale. The quality of the classification may be improved by using a fuzzy preference relation to classify input configurations that are not well handled by the linear discriminant.by Matthew A. Lehar.Ph.D

Єдина Європа: Погляд у майбутнє

Викладено результати наукових досліджень щодо сучасних проблем глобалізації та інтеграційних процесів, участі в них українських та польських підприємств, вирішення екологічних та соціально-економічних питань, пов’язаних з інтеграційними процесами, підвищенням конкуренції та інтенсифікацією виробництва. Видання буде корисним для наукових співробітників, фахівців-практиків, які займаються проблемами європейського розвитку, викладачів, аспірантів, студентів вищих навчальних закладів, урядових і неурядових аналітичних організацій, інституцій ЄС

Dynamic Modeling, Sensor Placement Design, and Fault Diagnosis of Nuclear Desalination Systems

Fault diagnosis of sensors, devices, and equipment is an important topic in the nuclear industry for effective and continuous operation of nuclear power plants. All the fault diagnostic approaches depend critically on the sensors that measure important process variables. Whenever a process encounters a fault, the effect of the fault is propagated to some or all the process variables. The ability of the sensor network to detect and isolate failure modes and anomalous conditions is crucial for the effectiveness of a fault detection and isolation (FDI) system. However, the emphasis of most fault diagnostic approaches found in the literature is primarily on the procedures for performing FDI using a given set of sensors. Little attention has been given to actual sensor allocation for achieving the efficient FDI performance. This dissertation presents a graph-based approach that serves as a solution for the optimization of sensor placement to ensure the observability of faults, as well as the fault resolution to a maximum possible extent. This would potentially facilitate an automated sensor allocation procedure. Principal component analysis (PCA), a multivariate data-driven technique, is used to capture the relationships in the data, and to fit a hyper-plane to the data. The fault directions for different fault scenarios are obtained from the prediction errors, and fault isolation is then accomplished using new projections on these fault directions. The effectiveness of the use of an optimal sensor set versus a reduced set for fault detection and isolation is demonstrated using this technique. Among a variety of desalination technologies, the multi-stage flash (MSF) processes contribute substantially to the desalinating capacity in the world. In this dissertation, both steady-state and dynamic simulation models of a MSF desalination plant are developed. The dynamic MSF model is coupled with a previously developed International Reactor Innovative and Secure (IRIS) model in the SIMULINK environment. The developed sensor placement design and fault diagnostic methods are illustrated with application to the coupled nuclear desalination system. The results demonstrate the effectiveness of the newly developed integrated approach to performance monitoring and fault diagnosis with optimized sensor placement for large industrial systems

Wind Power Forecasting : State-Of-The-Art 2009.

Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and uncertainty in wind power and to more efficiently operate power systems with large wind power penetrations. Moreover, in a market environment, the wind power contribution to the generation portofolio becomes important in determining the daily and hourly prices, as variations in the estimated wind power will influence the clearing prices for both energy and operating reserves. With the increasing penetration of wind power, WPF is quickly becoming an important topic for the electric power industry. System operators (SOs), generating companies (GENCOs), and regulators all support efforts to develop better, more reliable and accurate forecasting models. Wind farm owners and operators also benefit from better wind power prediction to support competitive participation in electricity markets against more stable and dispatchable energy sources. In general, WPF can be used for a number of purposes, such as: generation and transmission maintenance planning, determination of operating reserve requirements, unit commitment, economic dispatch, energy storage optimization (e.g., pumped hydro storage), and energy trading. The objective of this report is to review and analyze state-of-the-art WPF models and their application to power systems operations. We first give a detailed description of the methodologies underlying state-of-the-art WPF models. We then look at how WPF can be integrated into power system operations, with specific focus on the unit commitment problem

On the Combination of Game-Theoretic Learning and Multi Model Adaptive Filters

This paper casts coordination of a team of robots within the framework of game theoretic learning algorithms. In particular a novel variant of fictitious play is proposed, by considering multi-model adaptive filters as a method to estimate other players’ strategies. The proposed algorithm can be used as a coordination mechanism between players when they should take decisions under uncertainty. Each player chooses an action after taking into account the actions of the other players and also the uncertainty. Uncertainty can occur either in terms of noisy observations or various types of other players. In addition, in contrast to other game-theoretic and heuristic algorithms for distributed optimisation, it is not necessary to find the optimal parameters a priori. Various parameter values can be used initially as inputs to different models. Therefore, the resulting decisions will be aggregate results of all the parameter values. Simulations are used to test the performance of the proposed methodology against other game-theoretic learning algorithms.</p

Improving the sustainability of coal SC in both developed and developing countries by incorporating extended exergy accounting and different carbon reduction policies

In the age of Industry 4.0 and global warming, it is inevitable for decision-makers to change the way they view the coal supply chain (SC). In nature, energy is the currency, and nature is the source of energy for humankind. Coal is one of the most important sources of energy which provides much-needed electricity, as well as steel and cement production. This manuscript-based PhD thesis examines the coal SC network as well as the four carbon reduction strategies and plans to develop a comprehensive model for sustainable design. Thus, the Extended Exergy Accounting (EEA) method is incorporated into a coal SC under economic order quantity (EOQ) and economic production quantity (EPQs) in an uncertain environment. Using a real case study in coal SC in Iran, four carbon reduction policies such as carbon tax (Chapter 5), carbon trade (Chapter 6), carbon cap (Chapter 7), and carbon offset (Chapter 8) are examined. Additionally, all carbon policies are compared for sustainable performance of coal SCs in some developed and developing countries (the USA, China, India, Germany, Canada, Australia, etc.) with the world's most significant coal consumption. The objective function of the four optimization models under each carbon policy is to minimize the total exergy (in Joules as opposed to Dollars/Euros) of the coal SC in each country. The models have been solved using three recent metaheuristic algorithms, including Ant lion optimizer (ALO), Lion optimization algorithm (LOA), and Whale optimization algorithm (WOA), as well as three popular ones, such as Genetic algorithm (GA), Ant colony optimization (ACO), and Simulated annealing (SA), are suggested to determine a near-optimal solution to an exergy fuzzy nonlinear integer-programming (EFNIP). Moreover, the proposed metaheuristic algorithms are validated by using an exact method (by GAMS software) in small-size test problems. Finally, through a sensitivity analysis, this dissertation compares the effects of applying different percentages of exergy parameters (capital, labor, and environmental remediation) to coal SC models in each country. Using this approach, we can determine the best carbon reduction policy and exergy percentage that leads to the most sustainable performance (the lowest total exergy per Joule). The findings of this study may enhance the related research of sustainability assessment of SC as well as assist coal enterprises in making logical and measurable decisions

Social work with airports passengers

Social work at the airport is in to offer to passengers social services. The main methodological position is that people are under stress, which characterized by a particular set of characteristics in appearance and behavior. In such circumstances passenger attracts in his actions some attention. Only person whom he trusts can help him with the documents or psychologically

World Multidisciplinary Civil Engineering- Architecture- Urban Planning symposium

We would like to express our sincere gratitude to all 900+ submissions by 600+ participants of WMCAUS 2018 from 60+ different countries all over the world for their interests and contributions in WMCAUS 2018. We wish you enjoy the World Multidisciplinary Civil Engineering-Architecture-Urban Planning Symposium – WMCAUS 2018 and have a pleasant stay in the city of romance Prague. We hope to see you again during next event WMCAUS 2019 which will be held in Prague (Czech Republic) approximately in the similar period