Network-wide Emissions Estimation Using the Macroscopic Fundamental Diagram

This report presents a review of the studies incorporating the Macroscopic Fundamental Diagram (MFD) dynamics for emissions estimation using various microscopic estimation frameworks. These studies show the potential of applicability of the MFD-basedtools for emissions estimation. However, the accuracy of existing models in estimating the emissions of large-scale urban networks is questionable due to their inability in capturing the variations in traffic conditions across such networks. As a solution to this problem, we have proposed to develop a multi-reservoir emissions estimation framework by partitioning large-scale networks into smaller regions with homogeneous traffic conditions and low-scatter MFDs like the multi-reservoir Dynamic TrafficAssignment (DTA) models, which can result in more accurate network-wide emissions estimation. The key component of this framework is finding a method to accurately estimate the emissions using aggregated network representation and its corresponding variables. A numerical experiment on an arbitrary network shows that the estimation efficiency can increase significantly by implementing aggregated network representation, albeit the results will be less accurate the more aggregated the representation becomes. The possible reasons and considerations for future applications have been discussed, which would lead to developing calibrated aggregated-level methods, which can estimate the emissions efficiently and accurately. After calibrating the MFD-based emissions estimation method to acceptable levels of accuracy and efficiency, traffic control strategies can be proposed to optimize the energy consumption and emissions of CO, CO2, NOx, PM2.5, CH4, VOC, etc. The proposed control strategies can include perimeter control strategies in the boundaries of the regions, ramp-metering strategies at the connections to the freeways and signal timing strategies, which is known to influence the shape of the MFD. View the NCST Project Webpag

Information extraction of cybersecurity concepts: An LSTM approach

Extracting cybersecurity entities and the relationships between them from online textual resources such as articles, bulletins, and blogs and converting these resources into more structured and formal representations has important applications in cybersecurity research and is valuable for professional practitioners. Previous works to accomplish this task were mainly based on utilizing feature-based models. Feature-based models are time-consuming and need labor-intensive feature engineering to describe the properties of entities, domain knowledge, entity context, and linguistic characteristics. Therefore, to alleviate the need for feature engineering, we propose the usage of neural network models, specifically the long short-term memory (LSTM) models to accomplish the tasks of Named Entity Recognition (NER) and Relation Extraction (RE).We evaluated the proposed models on two tasks. The first task is performing NER and evaluating the results against the state-of-the-art Conditional Random Fields (CRFs) method. The second task is performing RE using three LSTM models and comparing their results to assess which model is more suitable for the domain of cybersecurity. The proposed models achieved competitive performance with less feature-engineering work. We demonstrate that exploiting neural network models in cybersecurity text mining is effective and practical. - 2019 by the authors.This publication was made possible by the support of Qatar University and DISP laboratory (Lumi?re University Lyon 2, France).Scopu

Macroscopic urban dynamics: Analytical and numerical comparisons of existing models

In this paper we compare a single reservoir model and a trip-based model under piecewise linear MFD and a piecewise constant demand. These assumptions allow to establish the exact solution of the accumulation-based model, and continuous approximations of the trip-based model at any order using Taylor series

A comprehensive approach to analyze discrepancies between land surface models and in-situ measurements: a case study over the US and Illinois with SECHIBA forced by NLDAS

The purpose of this study is to test the ability of the Land Surface Model SECHIBA to simulate water budget and particularly soil moisture at two different scales: regional and local. The model is forced by NLDAS data set at 1/8th degree resolution over the 1997–1999 period. SECHIBA gives satisfying results in terms of evapotranspiration and runoff over the US compared with four other land surface models, all forced by NLDAS data set for a common time period. The simulated soil moisture is compared to in-situ data from the Global Soil Moisture Database across Illinois by computing a soil wetness index. A comprehensive approach is performed to test the ability of SECHIBA to simulate soil moisture with a gradual change of the vegetation parameters closely related to the experimental conditions. With default values of vegetation parameters, the model overestimates soil moisture, particularly during summer. Sensitivity tests of the model to the change of vegetation parameters show that the roots extraction parameter has the largest impact on soil moisture, other parameters such as LAI, height or soil resistance having a minor impact. Moreover, a new evapotranspiration computation including bare soil evaporation under vegetation has been introduced into the model. The results point out an improvement of the soil moisture simulation when this effect is taken into account. Finally, soil moisture sensitivity to precipitation variation is addressed and it is shown that soil moisture observations can be rather different, depending on the method of measuring field capacity. When the observed field capacity is deducted from the observed volumetric water profiles, simulated soil wetness index is closer to the observations

Yersiniosis outbreak in rainbow trout at fish farm in Oromia Regional State, Ethiopia

This study presents the results of an investigation conducted on an outbreak of Yersiniosis (Enteric red mouth disease) caused by Yersinia ruckeri at a rainbow trout farm situated at Adaba, Oromia Regional State, Ethiopia. Seven diseased rainbow trout fish having average weight 80 - 100 grams and aged 9 months, were brought to the National Animal Health Diagnostic and Investigation Center (NAHDIC) for further examination and laboratory testing. The young sick fish showed clinical signs of darkening of the skin, loss of appetite and gasping at the surface of the water before death. The fish were sacrificed and examined thoroughly  externally for the presence of visible lesions. Scrapings were collected from the skin especially from areas around the fins and observed under the  stereomicroscope and also under the low power objective of the compound microscope. Bacteriological tests were carried out on samples from the kidney, liver and spleen. It was concluded that the fish were affected by Yersinia ruckeri based on colony morphology during growth on Tryptose Soy Agar (yellow colonies, gram negative and rodshaped) and distinctive biochemical characteristics. Y. ruckeri is identified from sick fish for the first time in Ethiopia. The protozoan parasites Trichodina species were also recovered in large colonies from the skin scrapings and histopathological sections of the gills. The pathological lesions recorded  included high degree anaemia of oral and branchial mucosa, congested gills, kidney and spleen and pale liver, congestion, extensive necrosis in the kidney and spleen, and infiltration with inflammatory cells. Antibiogram test conducted on the bacteria showed that the Y. ruckeri strain were susceptible to Oxytetracycline, Furazolidone, Trimethoprim and Streptomycin. This study showed the importance of stress induced by higher temperature and poor water quality associated with infestations by Trichodina species as predisposing factors to bacterial diseases in intensive fish farming practices. Key words: bacterial culture, histopathology, rainbow trout, Yersinia ruckeri, Trichodina specie

Kinematics and morphology of ionized gas in Hickson Compact Group 18

We present new observations of $H\alpha$ emission in the Hickson Compact Group 18 (HCG 18) obtained with a scanning Fabry-Perot interferometer. The velocity field does not show motions of individual group members but, instead, a complex common velocity field for the whole group. The gas distribution is very asymmetric with clumps of maximum intensity coinciding with the optically brightest knots. Comparing $H\alpha$ and HI data we conclude that HCG 18 is not a compact group but instead a large irregular galaxy with several clumps of star formation.Comment: Accepted for publication in Astronomical Journal (13p 6 figures