A case study on trace metals in surface sediments and dissolved inorganic nutrients in surface water of Olüdeniz Lagoon-Mediterranean, Turkey

Hydro-chemical parameters (salinity, temperature, pH, dissolved oxygen, nitrate, silicate and phosphate) in seawater and major trace metals (Al, Fe, Mn, Cr, V, Zn, Pb, Cu) in sediments were evaluated for the assessment of quality of seawater and sediments in very small lagoon in Mediterranean, Olüdeniz. Enrichment factors for metals in sediment were in the range of 1.62-8.09, comparable to crustal rock composition. For metals, comparison with literature data revealed relatively low metal concentrations for Olüdeniz sediments. Correlation analyses on the sediment metal data showed strong correlation in between Cr, Fe and Zn. Surface water salinity slightly decreases within the lagoon, indicating that limited fresh waters inflow to the lagoon. In October, the lagoon waters contained very low phosphate concentrations but measurable values of nitrate and silicate, yielding high NO(3)(-)/PO(4)(3-) ratios (90). Very low Chlorophyll-a (biomass indicator) concentrations measured in the lagoon suggest the phosphorus limitation of primary productivity.     

Effect of Steam Baking on Acrylamide Formation and Browning Kinetics of Cookies

Abstract: Effects of baking method and temperature on surface browning and acrylamide concentration of cookies were investigated. Cookies were baked in natural and forced convection and steam‐assisted hybrid ovens at 165, 180, and 195 °C and at different times. For all oven types, the acrlyamide concentration and surface color of cookies increased with increasing baking temperature. Significant correlation was observed between acrylamide formation and browning index, BI, which was calculated from Hunter L, a, and b color values, and it showed that the BI may be considered as a reliable indicator of acrylamide concentration in cookies. Acrylamide formation and browning index in cookies were considered as the first‐order reaction kinetics and the reaction rate constants, k, were in the range of 0.023 to 0.077 (min^?1) and 0.019 to 0.063 (min^?1), respectively. The effect of baking temperature on surface color and acrylamide concentration followed the Arrhenius type of equation, with activation energies for acrylamide concentration as 6.87 to 27.84 kJ/mol; for BI value as 19.54 to 35.36 kJ/mol, for all oven types. Steam‐assisted baking resulted in lower acrylamide concentration at 165 °C baking temperature and lower surface color for all temperatures. Steam‐assisted baking is recommended as a healthy way of cooking providing the reduction of harmful compounds such as acrylamide for bakery goods, at a minimal level, while keeping the physical quality. Practical Application: The kinetics of acrylamide formation and browning of cookies will possibly allow definition of optimum baking temperatures and times at convectional and steam‐assisted baking ovens. The kinetic model can be used by developing baking programs that can automatically control especially a new home‐scale steam‐assisted hybrid oven producing healthy products, for the use of domestic consumers.     

A real time traffic simulator utilizing an adaptive fuzzy inference mechanism by tuning fuzzy parameters

Traffic lights are installed at intersections mostly for traffic management. Traffic signals turn on during the amount of time determined. Intelligent traffic management systems emerge as a need to handle the dynamicity of traffic. These systems are first implemented on simulators in order to mimic the real life situations before realization.     

Stability limit of human-in-the-loop model reference adaptive control architectures

Model reference adaptive control (MRAC) offers mathematical and design tools to effectively cope with many challenges of real-world control problems such as exogenous disturbances, system uncertainties and degraded modes of operations. On the other hand, when faced with human-in-the-loop settings, these controllers can lead to unstable system trajectories in certain applications. To establish an understanding of stability limitations of MRAC architectures in the presence of humans, here a mathematical framework is developed whereby an MRAC is designed in conjunction with a class of linear human models including human reaction delays. This framework is then used to reveal, through stability analysis tools, the stability limit of the MRAC–human closed-loop system and the range of model parameters respecting this limit. An illustrative numerical example of an adaptive flight control application with a Neal–Smith pilot model is presented to demonstrate the effectiveness of developed approaches.     

Taguchi Method–GONNS integration: Complete procedure covering from experimental design to complex optimization

Determination of the optimal operating conditions from the experimental data without fitting any analytical or empirical models is very convenient for manufacturing applications. In this paper, integration of Taguchi Method and Genetically Optimized Neural Networks (GONNS) is proposed. The proposed procedure covers all the steps from experimental design to complex optimization. The feasibility of the approach was evaluated by estimating the optimal cutting conditions for the milling of Ti6Al4V titanium alloy with PVD coated inserts. The test conditions were determined by the Taguchi Method. The optimal cutting condition and influences of the cutting speed, feed rate and cutting depth on the surface roughness were analyzed with the same method. GONNS estimated that the optimal cutting conditions were very close to the Taguchi Method when the same criterion was used. GONNS was also capable to minimize or maximize one of the output parameters while the others were kept within the desired range. Study demonstrated that Taguchi Method and GONNS complement each other for creation of a robust procedure for determination of the test conditions, analysis of the quality of the collected data, estimation of the influence of each parameter on the output(s) and estimation of optimal conditions with complex optimization objective functions.     

A new command governor architecture for transient response shaping

In this paper, we develop a control framework for stabilization and command following of nonlinear uncertain dynamical systems. The proposed methodology consists of a new command governor architecture and an adaptive controller. The command governor is a dynamical system that adjusts the trajectory of a given command to follow an ideal reference system capturing a desired closed‐loop dynamical system behavior in transient time. Specifically, we show that the controlled nonlinear uncertain dynamical system can approach the ideal reference system by choosing the design parameter of the command governor. In addition, an adaptive element is used to asymptotically assure that the error between the controlled nonlinear uncertain dynamical system and the ideal reference system is reduced in long term. Therefore, the proposed methodology not only has closed‐loop transient and steady‐state performance guarantees but can also shape the transient response by adjusting the trajectory of the given command with the command governor. We highlight that there exists a trade‐off between the adaptive controller's learning rate and the command governor's design parameter. This key feature of our framework allows rapid suppression of system uncertainties without resorting to a high learning rate in the adaptive controller. Furthermore, we discuss the robustness properties of the proposed approach with respect to high‐frequency dynamical system content such as measurement noise and ∕ or unmodeled dynamics. A numerical example is provided to demonstrate the efficacy of the proposed architecture. Copyright © 2012 John Wiley & Sons, Ltd.     

The expressive power of temporal relational query languages

The authors consider the representation of temporal data based on tuple and attribute timestamping. They identify the requirements in modeling temporal data and elaborate on their implications in the expressive power of temporal query languages. They introduce a temporal relational data model where N1NF relations and attribute timestamping are used and one level of nesting is allowed. For this model, a nested relational tuple calculus (NTC) is defined. They follow a comparative approach in evaluating the expressive power of temporal query languages, using NTC as a metric and comparing it with the existing temporal query languages. They prove that NTC subsumes the expressive power of these query languages. They also demonstrate how various temporal relational models can be obtained from the temporal relations by NTC and give equivalent NTC expressions for their languages. Furthermore, they show the equivalence of intervals and temporal elements (sets) as timestamps in their model     

Genetic tool monitor (GTM) for micro-end-milling operations

Almost all existing tool condition monitoring methods require either the critical parameters of models which are experimentally found or the self-learning algorithms that are trained with existing data. Genetic Tool Monitor (GTM) is proposed to identify the problems by using an analytical model for micro-end-milling operations and genetic algorithm. The current version of the GTM is capable to monitor the micro-end-milling operations without any previous experience and is able to estimate symmetrical wear and local damages at the cutting edges of a tool. Genetic algorithms (GA) are found as a promising health monitoring tool if an expression exists and the necessary computational time is allowable in that particular application. GTM generates meaningful information about the ongoing operation and allows the establishment of rules based on the operators' experience.     

Crystallization kinetics and affecting parameters on polycaprolactone composites with inorganic and organic additives

The isothermal crystallization and mechanical behavior of biodegradable polycaprolactone (PCL) composites with organic (oleic acid and glycerol monooleate) and inorganic (zinc oxide, organoclay, and hydroxy apatite) additives used alone or simultaneously were investigated. The effect of all additives on the degree of crystallinity percentage (DOC%), isothermal crystallization kinetics parameters, and mechanical test results of PCL composites was studied. The PCL composite films were prepared by solvent casting by using dichloromethane as the solvent. The films were characterized by X‐ray diffraction, differential scanning calorimetry (DSC), and tensile tests. DSC of the first melting and X‐ray diffraction DOC% results (for composites by solvent casting) are compatible. The values by DSC of the second melting (for composites by extrusion method) are lower. Organoclay gives the highest crystallinity among the other inorganic additives used. Small amounts of inorganic additives act as a nucleating agent and increase the crystallinity; the higher amounts decrease. The organic additives act as the plasticizer. When used alone, it lowers the crystallinity, but when used with inorganic additives, it improves the dispersion of inorganic particles in the polymer matrix. The isothermal crystallization kinetics parameters by Avrami analysis showed that crystallization was controlled by nucleation and the crystals had spherical structure. The nucleation type changed between thermal and athermal nucleation. The Pukanzky model interaction parameter B indicated that the organic additives improved the dispersion of inorganic particles in the polymer matrix. Statistically significant, eight correlations (F > 6) were obtained for the crystallinity, crystallization parameters, Young's modulus, and tensile strength as a function of concentration of additives. J. VINYL ADDIT. TECHNOL., 21:174–182, 2015. © 2014 Society of Plastics Engineers