Feature Extraction for Traffic Incident Detection Using Wavelet Transform and Linear Discriminant Analysis

To eliminate false alarms, an effective traffic incident detection algorithm must be able to extract incident-related features from the traffic patterns. A robust feature-extraction algorithm also helps reduce the dimension of the input space for a neural network model without any significant loss of related traffic information, resulting in a substantial reduction in the network size, the effect of random traffic fluctuations, the number of required training samples, and the computational resources required to train the neural network. This article presents an effective traffic feature-extraction model using discrete wavelet transform (DWT) and linear discriminant analysis (LDA). The DWT is first applied to raw traffic data, and the finest resolution coefficients representing the random fluctuations of traffic are discarded. Next, LDA is employed to the filtered signal for further feature extraction and reducing the dimensionality of the problem. The results of LDA are used as input to a neural network model for traffic incident detection.     

Integrated Genetic Algorithm for Optimization of Space Structures

Gradient‐based mathematical‐optimization algorithms usually seek a solution in the neighborhood of the starting point. If more than one local optimum exists, the solution will depend on the choice of the starting point, and the global optimum cannot be found. This paper presents the optimization of space structures by integrating a genetic algorithm with the penalty‐function method. Genetic algorithms are inspired by the basic mechanism of natural evolution, and are efficient for global‐searches. The technique employs the Darwinian survival‐of‐the‐fittest theory to yield the best or better characters among the old population, and performs a random information exchange to create superior offspring. Different types of crossover operations are used in this paper, and their relative merit is investigated. The integrated genetic algorithm has been implemented in C language and is applied to optimization of three space truss structures. In each case, an optimum solution was obtained after a limited number of iterations.     

Combination of Surface Charge and Size Controls the Cellular Uptake of Functionalized Graphene Sheets

A fundamental issue for biomedical applications of graphene is the correlation between its physicochemical properties and cellular uptake mechanism. However, such studies are challenging due to the intrinsic polydispersity of graphene. In this work, a series of water soluble graphene sheets with the same polymer coverage, density of functional groups, and fluorescence intensity but three different sizes and surface charges are produced. The effect of the latter two factors and their combination on the mechanism of cellular uptake and intracellular pathways of these defined nanosheets is investigated via confocal and Raman microscopies. While positively (? NH₃⁺) and negatively (? OSO₃^?) charged sheets show an energy dependent uptake, their neutral analogs do not show any significant uptake. The cellular uptake efficacy of positively charged graphene sheets is independent of the size and occurs both through phagocytosis and clathrin‐mediated endocytosis pathways. However, cellular uptake efficacy of graphene sheets with negative surface charge strongly depends on the size of the sheets. They cross the membrane mainly through phagocytosis and sulfate‐receptor‐mediated endocytosis. This study demonstrates that the impact of the size of graphene derivatives on their cellular uptake pathways highly depends on their surface charges and vice versa.     

Polypropylene reinforced with nanocrystalline cellulose: Coupling agent optimization

Five different grades of maleic anhydride polypropylene (MAPP) having different molecular weight and acid value (AV) were used as coupler in PP‐nanocrystalline cellulose (NCC) composites. The main objective was to study the effect of MAPP structure (Mw, AV) and filler/coupler (F/C) ratio on mechanical properties in order to find optimum mechanical properties in tension, flexion, and impact. Results showed that both Mw and AV have direct effect on mechanical properties and a balance between both must be achieved to get the best performance. However, regardless of MAPP structure, optimum improvement was obtained for F/C = 7.5/1. Shear rheological data showed that at high MAPP content, MAPP acts as lubricant. DSC and AFM analysis showed small reduction in the size of PP crystals in the presence of NCC. Rheological data under large amplitude oscillatory shear showed that the nanocomposites used here are under percolation. Using these analyses, possible reinforcement mechanisms were investigated. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42438.     

Polysulfone based amphiphilic graft copolymers by click chemistry as bioinert membranes

A series of well-defined amphiphilic graft copolymers with hydrophobic polysulfone (PSU) as backbones and hydrophilic poly(ethylene glycol) (PEG) as side chains were synthesized and characterized. For this purpose, PSUs were converted to azido-functionalized polymers by successive chloromethylation and azidation processes to give clickable PSUs. Then, the ω-hydroxyl function of the commercially available PEG-OH was converted into propargyl functionality by simple esterification process. Ultimately, the alkyne functionalized PEO was successfully grafted onto the PSUs by click chemistry. The final polymers and intermediates at various stages were characterized by ¹H NMR, FT-IR, and GPC techniques. The bioinert character of PEG grafted PSU was confirmed by static protein adsorption and prokaryotic and eukaryotic cell adhesion studies, and compared to that of unmodified PSU.     

Multivariate microaggregation by iterative optimization

Microaggregation is a well-known perturbative approach to publish personal or financial records while preserving the privacy of data subjects. Microaggregation is also a mechanism to realize the k-anonymity model for Privacy Preserving Data Publishing (PPDP). Microaggregation consists of two successive phases: partitioning the underlying records into small clusters with at least k records and aggregating the clustered records by a special kind of cluster statistic as a replacement. Optimal multivariate microaggregation has been shown to be NP-hard. Several heuristic approaches have been proposed in the literature. This paper presents an iterative optimization method based on the optimal solution of the microaggregation problem (IMHM). The method builds the groups based on constrained clustering and linear programming relaxation and fine-tunes the results within an integrated iterative approach. Experimental results on both synthetic and real-world data sets show that IMHM introduces less information loss for a given privacy parameter, and can be adopted for different real world applications.     

CONSCOM: An OO Construction Scheduling and Change Management System

In a companion paper, an object-oriented (OO) information model was presented for construction scheduling, cost optimization, and change order management (CONSCOM), based on the creation of a domain-specific development framework. The framework architecture is developed using generic software design elements, called patterns, which provide effective low-level solutions for creating, organizing, and maintaining objects. The OO model has been implemented in a prototype software system for management of construction projects, called CONSCOM, using the Microsoft Foundation Class library in Visual C++. CONSCOM is particularly suitable for highway construction change order management. It can be used by the owner as an intelligent decision support system in schedule reviews, progress monitoring, and cost-time trade-off analysis for change order approval. The OO information model for construction scheduling cost management can be integrated into a concurrent engineering model for the architecture, engineering, and construction industry.     

Neural Networks in Civil Engineering: 1989–2000

The first journal article on neural network application in civil/structural engineering was published by in this journal in 1989. This article reviews neural network articles published in archival research journals since then. The emphasis of the review is on the two fields of structural engineering and construction engineering and management. Neural networks articles published in other civil engineering areas are also reviewed, including environmental and water resources engineering, traffic engineering, highway engineering, and geotechnical engineering. The great majority of civil engineering applications of neural networks are based on the simple backpropagation algorithm. Applications of other recent, more powerful and efficient neural networks models are also reviewed. Recent works on integration of neural networks with other computing paradigms such as genetic algorithm, fuzzy logic, and wavelet to enhance the performance of neural network models are presented.     

Linear‐dendritic copolymers as nanocatalysts

Functionalized poly(ethylene glycol) (PEG) containing four chloride end functional groups (PEG‐Cl₄) was synthesized through reaction between cyanuric chloride and PEG‐(OH)₂. Chloride end functional groups of PEG‐Cl₄ were able to initiate the ring opening polymerization of 2‐ethyl‐2‐oxazoline and star copolymers containing a PEG core, and poly(2‐ethyl‐2‐oxazoline) (POX) arms were obtained. Polymerization was quenched using diethanolamine, and star copolymers containing hydroxyl end functional groups (PEG‐POX‐OH) were obtained. ε‐Caprolactone was then polymerized using the hydroxyl end functional groups of star copolymers and amphiphilic linear‐dendritic copolymers containing PEG and POX, and poly(caprolactone) (PCL) blocks were synthesized. Linear‐dendritic copolymers were able to load the organic and inorganic guest molecules. Application of host‐guest systems such as nanocatalyst for Heck chemical reaction was also investigated. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009