468 research outputs found

    Calibrating and Evaluating Dynamic Rule-Based Transit-Signal-Priority Control Systems in Urban Traffic Networks

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    Setting the traffic controller parameters to perform effectively in real-time is a challenging task, and it entails setting several parameters to best suit some predicted traffic conditions. This study presents the framework and method that entail the application of the Response Surface Methodology (RSM) to calibrate the parameters of any control system incorporating advanced traffic management strategies (e.g., the complex integrated traffic control system developed by Ahmed and Hawas). The integrated system is a rule-based heuristic controller that reacts to specific triggering conditions, such as identification of priority transit vehicle, downstream signal congestion, and incidents by penalizing the predefined objective function with a set of parameters corresponding to these conditions. The integrated system provides real time control of actuated signalized intersections with different phase arrangements (split, protected and dual). The premise of the RSM is its ability to handle either single or multiple objective functions; some of which may be contradicting to each other. For instance, maximizing transit trips in a typical transit priority system may affect the overall network travel time. The challenging task is to satisfy the requirements of transit and non-transit vehicles simultaneously. The RSM calibrates the parameters of the integrated system by selecting the values that can produce optimal measures of effectiveness. The control system was calibrated using extensive simulation-based analyses under high and very high traffic demand scenario for the split, protected, and dual control types. A simulation-based approach that entailed the use of the popular TSIS software with code scripts representing the logic of the integrated control system was used. The simulation environment was utilized to generate the data needed to carry on the RSM analysis and calibrate the models. The RSM was used to identify the optimal parameter settings for each control type and traffic demand level. It was also used to determine the most influential parameters on the objective function(s) and to develop models of the significant parameters as well as their interactions on the overall network performance measures. RSM uses the so-called composite desirability value as well as the simultaneous multi-objective desirabilities (e.g., the desirability of maximizing the transit vehicles throughput and minimizing the average vehicular travel time) estimates of the responses to identify the best parameters. This study also demonstrated how to develop “mathematical” models for rough estimation of the performance measures vis-à-vis the various parameter values, including how to validate the optimal settings. The calibrated models are proven to be significant. The optimal parameters of each control type and demand level were also checked for robustness, and whether a universal set of relative parameter values can be used for each control type. For the high traffic demand level, the optimal set of parameters is more robust than those of the very high traffic demand. Besides, the dual actuated controller optimal setting under the very high traffic demand scenario is more robust (than other control types settings) and shows the best performance

    Sustainable Approaches for Highway Runoff Management During Construction and Operation

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    Paper V and paper VI have not been published yet.Environmentally friendly approaches for highway runoff management during construction and operation are considered in this project. First, the state of the art in runoff management in terms of characterization, treatment, and modeling approaches were surveyed, and knowledge gaps were identified. Then, the characterization and treatment of tunneling wastewater (by natural and chemical coagulants) was investigated. In the next stage, the vulnerability of water quality to road construction activities was investigated by analyzing field monitoring data. In addition, two different approaches, involving information theory and gamma test theory, were suggested to optimize the water quality monitoring network during road construction. Lastly, the application of satellite data (i.e., Sentinel-2 Multi-Spectral Imager satellite imagery products) for water quality monitoring was examined. Based on the results, it can be shown that site-specific parameters (e.g., climate, traffic load) cause spatiotemporal variation in the characterization of highway runoff and performance of best management practices (BMP) to protect water quality. There is a knowledge gap regarding the characterization of highway runoff under different climatic scenarios, as well as the continuous monitoring and assessment of roadside water bodies. Analysis of the field monitoring data indicates that blasting, area cleaning, and construction of water management measures have the highest impact on surface water quality during road construction. Additionally, the application of information theory and gamma test theory indicate that the primary monitoring network assessed here is not optimally designed. The number and spatial distribution of monitoring stations could be modified and reduced, as the construction activities vary over time. Additionally, the suggested remote sensing techniques applied in this project are able to estimate water quality parameters (i.e., turbidity and chlorophyll-a) in roadside water bodies with a reliability consistent with field observations, reflecting the spatiotemporal effects of road construction and operations on water quality. Finally, an efficient two-step treatment strategy (15 min sedimentation followed by chemical coagulation and 45 min sedimentation) is suggested for the treatment of tunneling wastewater. The optimum coagulant dosages in the jar test exhibit high treatment efficiency (92-99%) for both turbidity and suspended solids (SS), especially for particle removal in the range of 10-100 μm, which is hard to remove by sedimentation ponds and may pose serious threats to the aquatic ecosystem. It is hoped the knowledge generated by this project will help decision-makers with management strategies and support UN Sustainable Development Goals (SDGs). The proposed approaches directly contribute to managing highway runoff and achieving SDG 6 (clean water and sanitation) and especially target 6.3 (water quality).publishedVersio

    Bioprocess Monitoring and Control

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    Process monitoring and control are fundamental to all processes; this holds especially for bioprocesses, due to their complex nature. Usually, bioprocesses deal with living cells, which have their own regulatory systems. It helps to adjust the cell to its environmental condition. This must not be the optimal condition that the cell needs to produce whatever is desired. Therefore, a close monitoring of the cell and its environment is essential to provide optimal conditions for production. Without measurement, no information of the current process state is obtained. In this book, methods and techniques are provided for the monitoring and control of bioprocesses. From new developments for sensors, the application of spectroscopy and modelling approaches, the estimation and observer implementation for ethanol production and the development and scale-up of various bioprocesses and their closed loop control information are presented. The processes discussed here are very diverse. The major applications are cultivation processes, where microorganisms were grown, but also an incubation process of bird’s eggs, as well as an indoor climate control for humans, will be discussed. Altogether, in 12 chapters, nine original research papers and three reviews are presented

    Sustainable Agriculture and Advances of Remote Sensing (Volume 2)

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    Agriculture, as the main source of alimentation and the most important economic activity globally, is being affected by the impacts of climate change. To maintain and increase our global food system production, to reduce biodiversity loss and preserve our natural ecosystem, new practices and technologies are required. This book focuses on the latest advances in remote sensing technology and agricultural engineering leading to the sustainable agriculture practices. Earth observation data, in situ and proxy-remote sensing data are the main source of information for monitoring and analyzing agriculture activities. Particular attention is given to earth observation satellites and the Internet of Things for data collection, to multispectral and hyperspectral data analysis using machine learning and deep learning, to WebGIS and the Internet of Things for sharing and publication of the results, among others

    Securing Cloud Storage by Transparent Biometric Cryptography

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    With the capability of storing huge volumes of data over the Internet, cloud storage has become a popular and desirable service for individuals and enterprises. The security issues, nevertheless, have been the intense debate within the cloud community. Significant attacks can be taken place, the most common being guessing the (poor) passwords. Given weaknesses with verification credentials, malicious attacks have happened across a variety of well-known storage services (i.e. Dropbox and Google Drive) – resulting in loss the privacy and confidentiality of files. Whilst today's use of third-party cryptographic applications can independently encrypt data, it arguably places a significant burden upon the user in terms of manually ciphering/deciphering each file and administering numerous keys in addition to the login password. The field of biometric cryptography applies biometric modalities within cryptography to produce robust bio-crypto keys without having to remember them. There are, nonetheless, still specific flaws associated with the security of the established bio-crypto key and its usability. Users currently should present their biometric modalities intrusively each time a file needs to be encrypted/decrypted – thus leading to cumbersomeness and inconvenience while throughout usage. Transparent biometrics seeks to eliminate the explicit interaction for verification and thereby remove the user inconvenience. However, the application of transparent biometric within bio-cryptography can increase the variability of the biometric sample leading to further challenges on reproducing the bio-crypto key. An innovative bio-cryptographic approach is developed to non-intrusively encrypt/decrypt data by a bio-crypto key established from transparent biometrics on the fly without storing it somewhere using a backpropagation neural network. This approach seeks to handle the shortcomings of the password login, and concurrently removes the usability issues of the third-party cryptographic applications – thus enabling a more secure and usable user-oriented level of encryption to reinforce the security controls within cloud-based storage. The challenge represents the ability of the innovative bio-cryptographic approach to generate a reproducible bio-crypto key by selective transparent biometric modalities including fingerprint, face and keystrokes which are inherently noisier than their traditional counterparts. Accordingly, sets of experiments using functional and practical datasets reflecting a transparent and unconstrained sample collection are conducted to determine the reliability of creating a non-intrusive and repeatable bio-crypto key of a 256-bit length. With numerous samples being acquired in a non-intrusive fashion, the system would be spontaneously able to capture 6 samples within minute window of time. There is a possibility then to trade-off the false rejection against the false acceptance to tackle the high error, as long as the correct key can be generated via at least one successful sample. As such, the experiments demonstrate that a correct key can be generated to the genuine user once a minute and the average FAR was 0.9%, 0.06%, and 0.06% for fingerprint, face, and keystrokes respectively. For further reinforcing the effectiveness of the key generation approach, other sets of experiments are also implemented to determine what impact the multibiometric approach would have upon the performance at the feature phase versus the matching phase. Holistically, the multibiometric key generation approach demonstrates the superiority in generating the bio-crypto key of a 256-bit in comparison with the single biometric approach. In particular, the feature-level fusion outperforms the matching-level fusion at producing the valid correct key with limited illegitimacy attempts in compromising it – 0.02% FAR rate overall. Accordingly, the thesis proposes an innovative bio-cryptosystem architecture by which cloud-independent encryption is provided to protect the users' personal data in a more reliable and usable fashion using non-intrusive multimodal biometrics.Higher Committee of Education Development in Iraq (HCED

    Social Ecography : International trade, network analysis, and an Emmanuelian conceptualization of ecological unequal exchange

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    This thesis demonstrates how network analysis, ecological economics and the world-system perspective can be combined into an ecographic framework that can yield new insights into the underlying structure of the world-economy as well as its surrounding world-ecology. In particular, the thesis focuses on the structural theory of ecological unequal exchange, a theory suggesting a relationship between positionality within the world-system and unequal exchange of biophysical resources. Using formal tools from social network analysis, the theory is tested on empirical trade data for two commodity types – primary agricultural goods and fuel commodities – for the period 1995-1999. As the selected commodities can be seen as adequate representations of the third Ricardian production factor, i.e. natural resources, ecological unequal exchange as conceptualized in this thesis is more in line with the original Emmanuelian factor-cost theory than previous approaches. Here, similar to Emmanuel’s formulation, it is a theory about factor cost differentials. Whereas the theory mostly holds true in the case of fuel commodities, the analysis of primary agricultural commodities actually points to an inverse relationship between structural positionality and ecological unequal exchange. This could point to a fundamental difference between these two types of commodities, for instance as reflected in an observed ecological Leontief paradox, which underlines the need for more detailed, and less typological, treatments of ecological unequal exchange

    Ejector refrigeration: A comprehensive review

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    The increasing need for thermal comfort has led to a rapid increase in the use of cooling systems and, consequently, electricity demand for air-conditioning systems in buildings. Heat-driven ejector refrigeration systems appear to be a promising alternative to the traditional compressor-based refrigeration technologies for energy consumption reduction. This paper presents a comprehensive literature review on ejector refrigeration systems and working fluids. It deeply analyzes ejector technology and behavior, refrigerant properties and their influence over ejector performance and all of the ejector refrigeration technologies, with a focus on past, present and future trends. The review is structured in four parts. In the first part, ejector technology is described. In the second part, a detailed description of the refrigerant properties and their influence over ejector performance is presented. In the third part, a review focused on the main jet refrigeration cycles is proposed, and the ejector refrigeration systems are reported and categorized. Finally, an overview over all ejector technologies, the relationship among the working fluids and the ejector performance, with a focus on past, present and future trends, is presented. (C) 2015 Elsevier Ltd. All rights reserved
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