Developing Oregon’s renewable energy portfolio using fuzzy goal programming model

Renewable energy continues to be a hot topic in the United States affecting security and sustainability. A model to create renewable energy portfolio is established using guidelines drawn by Oregon’s Renewable Portfolio Standard (RPS) legislation with the objective of responding to a 25% of the state electricity demand by renewable resources in 2025. The fuzzy goal programming model is adaptable to accommodate changes in energy costs and future advances in technology maturity. It can also take into consideration the preferences of policy-makers and stakeholders. This model can help to reveal the costs and benefits of complex decisions regarding renewable energy.     

Patent value analysis using support vector machines

Receiving patents or licenses is an inevitable act of research in order to protect new ideas leading innovation. Request for patents has increased exponentially in order to legalize the intellectual property. Measuring economical value of each patent has been widely studied in the literature. Majority of the research in this field is focused on the patent driver prospect handled for the patent offices. There are a variety of criteria affecting decisions on each patent right; and predicting the possibility of grant may help the researchers to take some precautions. Objective of this study is to propose a robust model to determine if the appeal has a chance of approval. A case study is run on the patents that are accepted and rejected in home appliance industry to construct an intelligent classification model. The support vector machine, Back-Propagation Network and Bayes classification methods are compared on the proposed model. The proposed model in this study will help the decision makers to predict whether the patent appeal will be accepted. The study is unique with the approach that helps the candidate patent owners.     

Clean energy investment scenarios using the Bayesian network

Clean energy investment decisions are getting more difficult to make due to public reactions. In order to support the policies in the field, analysis of the positive conditions is needed. This research aims to construct the positive scenarios for nuclear energy and renewable energy investments in the state of Oregon, USA. The Bayesian network technique will be used to create the scenarios. Oregon has a wide range of renewable energies; hence, investment is becoming more complex. Criteria affecting the decisions are taken from the literature, but were reviewed with energy authorities in Oregon in order to define the interactions.     

A Novel Approach to Limit Chemical Deterioration of Gilthead Sea Bream (Sparus aurata) Fillets: Coating with Electrospun Nanofibers as Characterized by Molecular,Thermal, and Microstructural Properties

Coating of sea bream fillets with thymol loaded chitosan based electrospun nanofibers (TLCN) and chitosan based nanafibers (CN) has been presented a novel approach to delay chemical deterioration. We assessed CN and TLCN with respect of scanting of total volatile basic nitrogen (TVBN), trimethylamine (TMA), thiobarbituric acid (TBA) deterioration during cold storage condition. Electrospinning process was applied to obtain TLCN and CN. Both of nanofibers obtained from biopolymer and bioactive material were cylindrical, smooth, beadless. Thermal, molecular, zeta potential (ZP), and surface properties of the groups were investigated, revealing that CN indicated molecular interactions with thymol in nanofibers, reduce in physical properties of these structures, thermal decomposition (an alteration in mass of CN and TLCN at temperatures below 190 °C, corresponding to 20.53% and 19.97%, respectively) and also dispersion stabilities (ζ potential) of CN and TLCN were determined 33.68 ± 3.35 and 21.85 ± 1.96 mV, respectively. TVBN and TMA stability analyses demonstrated that CN and TLCN were both effective in delaying chemical deterioration of fish fillets, furthermore TLCN was more effective against chemical deterioration. TBA analyses results of fish fillets indicated that CN and TLCN delayed rancidity in fish meat as compared to control group samples. The presented study results suggested that coating of the sea bream fillets with CN and TLCN would be a promising approach to delay the chemical deterioration of fish fillets.     

Development of future energy scenarios with intelligent algorithms: Case of hydro in Turkey

Energy production is considered as one of the key indicators for economic development. It is vital to improve the renewable energy production for global sustainability, while leveraging the national resources. This study is contributing to the demonstration of using genetic algorithms (GA) in the development of future energy scenarios as well as to the strategic energy studies in Turkey. The forecasting model developed in this study uses forward feeding back-propagation (BP) method improved by GA. The proposed model is applied in the Turkish case. The test errors are shown to emphasize the positive difference between the proposed model and the classical BP model. The results highlight that there is strong evidence indicating that the government should reconsider their current energy strategies.     

Zeta potential study of natural‐ and acid‐activated sepiolites in electrolyte solutions

Detailed characterisation of natural sepiolite from the Eskisehir region of Turkey was performed using X‐ray diffraction, X‐ray fluorescence, field emission scanning electron microscopy, specific surface area (BET method), Fourier transform infrared spectra, derivative thermogravimetry (DTG) and differential thermal analysis. Electrokinetic properties of natural‐ and acid‐activated sepiolites were investigated as a function of the concentration of various electrolytes, such as NaCl, KCl, LiCl, CaCl₂, MgCl₂, NaNO₃, Na₂CO₃, FeCl₃ and Al(NO₃)₃. While mono and divalent cations and anions did not change the surface charge of natural‐ and acid‐activated sepiolite, trivalent cations changed the surface charge from negative to positive. Acid‐activated sepiolite samples shifted towards the positive region in nearly all electrolyte solutions when compared with the natural sepiolite. © 2011 Canadian Society for Chemical Engineering     

Quantification of soybean oil adulteration in extra virgin olive oil using portable raman spectroscopy

Extra virgin olive oil is produced through either a cold press procedure or a centrifugation with no thermal and chemical treatments and it is considered as the best quality oil under the category of olive oils. The superior properties of olive oil due to its rich in phenolic and antioxidant content and its contribution to prevent several health problems has increased the demand for olive oil over the years. Consequently, it is nowadays sold at remarkably higher price than regular vegetable oils in the market. Unfortunately, extra virgin olive oil (EVOO) has been adulterated with other cheap oils due to potential high commercial profit. Even though, there are methods available to detect the adulteration in EVOO (such as chromatographic methods and PCR), alternative simpler and faster methods are being studied. In this study, performance of portable Raman spectroscopy to quantify soybean oil (SO) adulteration [up to 25?% (w/w)] in EVOO has been evaluated. Partial Least Square Regression (PLSR) calibration models were developed and both internally (using cross-validation, leave-one-out approach) and externally (using an independent sample set) validated. The model gave standard error of prediction (SEP) of 1.34?% (w/w) SO in EVOO and correlation coefficient of prediction (rPred) of 0.99. Additionally, the residual predictive deviation (RPD) value calculated for the model was found to be 5.71, indicating that the model was considered as “good” and could be used for routine analysis and quality control applications.     

Renovating the excitation circuit of a conventional welding converter

This paper presents two different new excitation current supplies based on power electronics for an existing conventional welding converter. The proposed circuits are simulated using Lab-VIEW 1200 AI and a PC based system. In the expressions for winding currents the dynamic inductances are used to take into account the saturation in the core of the winding. The experimental circuits are implemented and tested. The percentage peak-to-peak ripple currents are calculated for both simulation and experimental results and for both circuit configurations. The results are summarized in two tables for comparison.