Evaluation of driver drowsiness using respiration analysis by thermal imaging on a driving simulator

In this paper, a new non-intrusive driver drowsiness detection method is introduced based on respiration analysis using facial thermal imaging. Drowsiness is the cause of many driving accidents all over the world. Drivers’ respiration system undergoes significant changes from wakefulness to drowsiness and can be used to detect drowsiness. Current respiration measurement methods are intrusive and uncomfortable making respiration the least measured vital sign during driving. In this paper, a new method is presented based on facial thermal imaging to analyze drivers’ respiration signal non-intrusively. Thirty subjects are tested in a car simulator. They are fully awake at the beginning and experience drowsiness during the tests. The mean and the standard deviation of the respiration rate and the inspiration-to-expiration time ratio are extracted from the subjects’ respiration signal. To detect drowsiness, the Support Vector Machine (SVM) and the K-Nearest Neighbor (KNN) classifiers are used. The Observer Rating of Drowsiness method is used for scoring the drowsiness level and validating the proposed method. The performance and the results of both methods are presented and compared. The results indicate that drowsiness can be detected with the accuracy of 90%, sensitivity of 92%, specificity of 85%, and precision of 91%.

     

A Decision-Making Framework for Subcontractor Selection in Construction Projects

Subcontractor (SC) selection is a critical part of SC management, and a major challenge is the existence of multiple criteria that the project management team needs to evaluate in the selection process. To overcome this challenge, the Kano model is applied to classify the selection criteria into five categories including must-be, reverse, one-dimensional, attractive, and indifferent. Data were obtained via a questionnaire based on Kano model concepts to categorize the identified selection criteria. The obtained results show that the selection criteria can be categorized into three categories; must-be, one-dimensional, and attractive. According to this categorization, the weight of criteria is extracted by applying the Analytic Hierarchy Process. Then, a fuzzy multi-attribute decision framework is developed to select the best SC with two main components, screening by the must-be criteria category and selection based on the one-dimensional and attractive criteria categories. A case example of the framework application and the results of a questionnaire are presented and validate acceptance of the framework accuracy.     

Single image rain/snow removal using distortion type information

Multimedia Tools and Applications - Rainy or snowy weather conditions can severely impair the visual quality of images and videos. The rain streaks or snow particles that may vary in shape and size...     

Parameter estimation of bilinear systems based on an adaptive particle swarm optimization

Bilinear models can approximate a large class of nonlinear systems adequately and usually with considerable parsimony in the number of coefficients required. This paper presents the application of Particle Swarm Optimization (PSO) algorithm to solve both offline and online parameter estimation problem for bilinear systems. First, an Adaptive Particle Swarm Optimization (APSO) is proposed to increase the convergence speed and accuracy of the basic particle swarm optimization to save tremendous computation time. An illustrative example for the modeling of bilinear systems is provided to confirm the validity, as compared with the Genetic Algorithm (GA), Linearly Decreasing Inertia Weight PSO (LDW-PSO), Nonlinear Inertia Weight PSO (NDW-PSO) and Dynamic Inertia Weight PSO (DIW-PSO) in terms of parameter accuracy and convergence speed. Second, APSO is also improved to detect and determine varying parameters. In this case, a sentry particle is introduced to detect any changes in system parameters. Simulation results confirm that the proposed algorithm is a good promising particle swarm optimization algorithm for online parameter estimation.     

Hybrid extended Fourier series for optimal control of nonlinear algebraic dynamical systems

The paper introduces a new method for finding optimal control of algebraic dynamic systems. The structure of algebraic dynamical systems is nonlinear with quadratic and bilinear terms. A new hybrid extended Fourier series is introduced, and state and control variables of the system are expanded by this series. Moreover, properties of new series are presented, and integration and product operational matrices are obtained. Using operational matrices, optimal control of the systems is converted to a set of simultaneous nonlinear algebraic relations. An illustrative example is included to compare our results with those in the literature.     

Cellular uptake and cytotoxicity of silica nanotubes

"Template synthesized" silica nanotubes (SNTs) provide unique features such as end functionalization to control drug release, inner voids for loading biomolecules, and distinctive inner and outer surfaces that can be differentially functionalized for targeting and biocompatibility. Very limited information is available about their biological interactions. This work evaluates the influence of size and surface charge of SNTs on cellular toxicity and uptake. Results additionally indicate endocytosis to be one possible mechanism of internalization of SNTs.     

Rock Salt Ni/Co Oxides with Unusual Nanoscale‐Stabilized Composition as Water Splitting Electrocatalysts

The influence of nanoscale on the formation of metastable phases is an important aspect of nanostructuring that can lead to the discovery of unusual material compositions. Here, the synthesis, structural characterization, and electrochemical performance of Ni/Co mixed oxide nanocrystals in the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is reported and the influence of nanoscaling on their composition and solubility range is investigated. Using a solvothermal synthesis in tert ‐butanol ultrasmall crystalline and highly dispersible Ni _x Co_{1? x} O nanoparticles with rock salt type structure are obtained. The mixed oxides feature non‐equilibrium phases with unusual miscibility in the whole composition range, which is attributed to a stabilizing effect of the nanoscale combined with kinetic control of particle formation. Substitutional incorporation of Co and Ni atoms into the rock salt lattice has a remarkable effect on the formal potentials of NiO oxidation that shift continuously to lower values with increasing Co content. This can be related to a monotonic reduction of the work function of (001) and (111)‐oriented surfaces with an increase in Co content, as obtained from density functional theory (DFT+U) calculations. Furthermore, the electrocatalytic performance of the Ni _x Co_{1? x} O nanoparticles in water splitting changes significantly. OER activity continuously increases with increasing Ni contents, while HER activity shows an opposite trend, increasing for higher Co contents. The high electrocatalytic activity and tunable performance of the nonequilibrium Ni _x Co_{1? x} O nanoparticles in HER and OER demonstrate great potential in the design of electrocatalysts for overall water splitting.     

Synthesis and Characterization of New Cobalt(II)–Pyrazine Coordination Polymer as Precursor for Preparation of Co(II) Oxide Nanoparticles: Surprising Coordination,DFT Calculation and Spectroscopic Studies

The new 2-D cobalt(II) coordination polymer with pyrazine was synthesized surprisingly from reaction of CoCl₂ and tetrapyrido[3,2-a:2′,3′-c:3″,2″-h:2?,3?-j]phenazine (tpphz) in methanol as medium and characterized by means of Fourier transform infrared spectroscopy (FT-IR), UV–Vis spectroscopy and X-ray single crystal analysis. The results showed that coordination polymer consist of cobalt(II) chain with pyrazine-bridged which crystallizes in orthorhombic unit cell (a?=?10.1307, b?=?10.1310, c?=?10.6838 Å) and space group Pban. Density functional theory (DFT) calculations were also done to figure out the electronic structure of the compound from theoretical aspect. The electronic spectrum of coordination polymer was investigated and the DFT/TDDFT procedures were employed to assign the absorption bands. The thermal decomposition of the title compound resulted in formation of cobalt(II) oxide nanoparticles with average size of 50 nm.     

Theranostic nanoparticles based on magnetic nanoparticles: design,preparation, characterization,and evaluation as novel anticancer drug carrier and MRI contrast agent

In this work, we reported the synthesis of curcumin (CUR)-loaded hydrophilic and hydrophobic natural amino acids (AAs)-modified iron oxide magnetic nanoparticles (IONPs). Two types of AAs, l-lysine (Lys) and l-phenylalanine (PhA), were selected to study their effects on loading capacity, release profile of CUR, biocompatibility, and anticancer activity. CUR-loaded AAs-modified IONPs (F@AAs@CUR NPs) were characterized by X-ray diffraction (XRD), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), vibrating sample magnetometer (VSM), and transmission electron microscopy (TEM) techniques. Next, the various kinetic equations were fitted to the release data of CUR from F@Lys@CUR NPs and F@PhA@CUR NPs. Additionally, hemolysis test and MTT assays on HFF-2 and HEK-293 cell lines were performed for determination of biocompatibility of AAs-coated IONPs. Finally, the anticancer activity of F@AAs@CUR NPs examined on MCF-7 breast cancer cell line. The results indicate that these nanocarriers are nontoxic and biocompatible and also F@AAs@CUR NPs are suitable carriers for delivery of curcumin and even other hydrophobic drugs. Also, the MRI training established the effectiveness of IONPs as contrast agent for the revealing of tumor as evidenced from the phantom images as well as higher T₂ relaxivity.