Fuzzy real option analysis in patent related decision making and patent valuation

The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

Anxiety and depression in parents of a Brazilian non-clinical sample of attention-deficit/ hyperactivity disorder (ADHD) students

Higher prevalence rates of anxiety and depression have been reported in parents of children with attention-deficit/hyperactivity disorder (ADHD). The interaction between the burden of ADHD in offspring, a higher prevalence rate of this highly inherited disorder in parents, and comorbidities may explain this finding. Our objective was to investigate levels of ADHD, anxious and depressive symptomatology, and their relationship in parents of ADHD children from a non-clinical sample using a dimensional approach. The sample included 396 students enrolled in all eight grades of a public school who were screened for ADHD using the SNAP IV rating scale. Positive cases were confirmed through a semi-structured interview. Parents of all 26 ADHD students and 31 paired controls were enrolled. A sample of 36 parents of ADHD children (21 mothers, 15 fathers) and 30 parents of control children (18 mothers, 12 fathers) completed the Adult Self Report Scale, State-Trait Anxiety Inventory, and Beck Depression Inventory in order to investigate anxious and depressive symptomatology. Probands' mothers presented a higher level of ADHD symptomatology (with only inattention being a significant cluster). Again, mothers of ADHD children presented higher depressive and anxiety levels; however, these did not correlate with their own ADHD symptomatology. Only trait-anxiety levels were higher in ADHD mothers. Our findings suggest that: 1) anxious and depressive symptoms might be more prevalent in mothers of ADHD students; 2) anxious and depressive symptomatology might be independent of impairment associated with ADHD symptoms; 3) anxious and depressive symptoms are independent of the presence of ADHD.

Brain tissue segmentation using q-entropy in multiple sclerosis magnetic resonance images

The loss of brain volume has been used as a marker of tissue destruction and can be used as an index of the progression of neurodegenerative diseases, such as multiple sclerosis. In the present study, we tested a new method for tissue segmentation based on pixel intensity threshold using generalized Tsallis entropy to determine a statistical segmentation parameter for each single class of brain tissue. We compared the performance of this method using a range of different q parameters and found a different optimal q parameter for white matter, gray matter, and cerebrospinal fluid. Our results support the conclusion that the differences in structural correlations and scale invariant similarities present in each tissue class can be accessed by generalized Tsallis entropy, obtaining the intensity limits for these tissue class separations. In order to test this method, we used it for analysis of brain magnetic resonance images of 43 patients and 10 healthy controls matched for gender and age. The values found for the entropic q index were 0.2 for cerebrospinal fluid, 0.1 for white matter and 1.5 for gray matter. With this algorithm, we could detect an annual loss of 0.98% for the patients, in agreement with literature data. Thus, we can conclude that the entropy of Tsallis adds advantages to the process of automatic target segmentation of tissue classes, which had not been demonstrated previously.

Estimating the average length of hospitalization due to pneumonia: a fuzzy approach

Exposure to air pollutants is associated with hospitalizations due to pneumonia in children. We hypothesized the length of hospitalization due to pneumonia may be dependent on air pollutant concentrations. Therefore, we built a computational model using fuzzy logic tools to predict the mean time of hospitalization due to pneumonia in children living in São José dos Campos, SP, Brazil. The model was built with four inputs related to pollutant concentrations and effective temperature, and the output was related to the mean length of hospitalization. Each input had two membership functions and the output had four membership functions, generating 16 rules. The model was validated against real data, and a receiver operating characteristic (ROC) curve was constructed to evaluate model performance. The values predicted by the model were significantly correlated with real data. Sulfur dioxide and particulate matter significantly predicted the mean length of hospitalization in lags 0, 1, and 2. This model can contribute to the care provided to children with pneumonia.

Enthalpy-entropy compensation based on isotherms of mango

Moisture equilibrium data of mango pulp were determined using the static gravimetric method. Adsorption and desorption isotherms were obtained in the range of 30-70 ºC, to water activities (a w) from 0.02 to 0.97. The application of the GAB model to the experimental results, using direct nonlinear regression analysis, provided agreement between experimental and calculated values. The net isosteric heat of sorption was estimated from equilibrium sorption data, using the Clausius-Clapeyron equation. Isosteric heats of sorption were found to increase with increasing temperature and could be well adjusted by an exponential relationship. The enthalpy-entropy compensation theory was applied to sorption isotherms and plots of deltaH versus deltaS provided the isokinetic temperatures, indicating an enthalpy controlled sorption process.

Modelling Energy Consumption of a Switch using Fuzzy-Rule Classifier

The energy consumption of IT equipments is becoming an issue of increasing importance. In particular, network equipments such as routers and switches are major contributors to the energy consumption of internet. Therefore it is important to understand how the relationship between input parameters such as bandwidth, number of active ports, traffic-load, hibernation-mode and their impact on energy consumption of a switch. In this paper, the energy consumption of a switch is analyzed in extensive experiments. A fuzzy rule-based model of energy consumption of a switch is proposed based on the result of experiments. The model can be used to predict the energy saving when deploying new switches by controlling the parameters to achieve desired energy consumption and subsequent performance. Furthermore, the model can also be used for further researches on energy saving techniques such as energy-efficient routing protocol, dynamic link shutdown, etc.

Microbial profile of a kefir sample preparations: grains in natura and lyophilized and fermented suspension

Probiotics are supplementary foods developed by microbial strains that improve animal health beyond basic nutrition. Probiotics are consumed orally, regardless of being considered as normal inhabitants of the intestines, able to survive in enzimatic and biliary secretions. Kefir is a probiotic originated from the old continent, fermented by several bacteria and yeasts, encapsulated in a polyssacharide matrix, and resembles jelly grains. Kefir is also presented as its sourish product both in sugary or milky suspensions containing vitamins, aminoacids, peptides, carbohydrates, ethanol, and volatile compounds. Kefir is known to have a diverse microbial content depending on the country and fermentative substrates, which cause distinct probiotic effects. In this sense, the purpose of this work was to isolate, identify, and quantify the microbial content of a native sugary kefir sample (fermented suspension and lyophilized natural grains). Serial dilutions were plated on Rogosa agar (AR) and De Man, Rogosa and Sharpe (MRS), for Lactobacillus; Brain Heart Infusion (BHI), for total bacteria; Sabouraud-Dextrose-Agar (SDA), for yeasts and filamentous fungi; Thioglycolate Agar (TA), for Streptococcus, Acetobacteria and Leuconostoc; and Coconut Water Agar (CWA), and CWA supplemented with yeast extract (CWAY), for various genera. Genera and species for all strains were identified through biochemical reactions and specific API systems. The microbial profile of kefir was different from other sources of grains despite the presence of similar microorganisms and others which have not been reported yet. The data obtained with the CWA and CWAE media suggest that both substrates are alternative and salutary media for culture of kefir strains.

Study of the enthalpy-entropy mechanism from water sorption of orange seeds (C. sinensis cv. Brazilian) for the use of agro-industrial residues as a possible source of vegetable oil production

Orange seeds are a promising agroindustry-waste which can be implemented in the extraction and production of vegetable oil. The relationship between moisture content and water activity provides useful information for the processing and storage of this waste item. The aim of this study was to determine the mechanism of water sorption enthalpy-entropy of orange seeds (C. sinensis cv. Brazilians) according to the moisture content. Therefore, desorption isotherms were determined at five different temperature (30, 40, 50, 60, and 70 ºC) under a wide range of moisture content (0.005-0.057 kg kg-1 d.b.) and water activity (0.02-0.756). Theoretical and empirical models were used for modeling the desorption isotherms. An analytical solution of the Clausius-Clapeyron equation was proposed to compute the isosteric heat of sorption, the differential entropy, and Gibbs free energy using the Oswin model when the effect of temperature on the hygroscopic equilibrium was considered.

Estimating microalgae Synechococcus nidulans daily biomass concentration using neuro-fuzzy network

In this study, a neuro-fuzzy estimator was developed for the estimation of biomass concentration of the microalgae Synechococcus nidulans from initial batch concentrations, aiming to predict daily productivity. Nine replica experiments were performed. The growth was monitored daily through the culture medium optic density and kept constant up to the end of the exponential phase. The network training followed a full 3³ factorial design, in which the factors were the number of days in the entry vector (3,5 and 7 days), number of clusters (10, 30 and 50 clusters) and internal weight softening parameter (Sigma) (0.30, 0.45 and 0.60). These factors were confronted with the sum of the quadratic error in the validations. The validations had 24 (A) and 18 (B) days of culture growth. The validations demonstrated that in long-term experiments (Validation A) the use of a few clusters and high Sigma is necessary. However, in short-term experiments (Validation B), Sigma did not influence the result. The optimum point occurred within 3 days in the entry vector, 10 clusters and 0.60 Sigma and the mean determination coefficient was 0.95. The neuro-fuzzy estimator proved a credible alternative to predict the microalgae growth.

Influence of distillation time and sample mass on sulfur dioxide analysis in passion fruit juice through Monier-Williams method

AbstractThis study aimed to evaluate the effect of the distillation time and the sample mass on the total SO2 content in integral passion fruit juice (Passiflora sp). For the SO2 analysis, a modified version of the Monier-Williams method was used. In this experiment, the distillation time and the sample mass were reduced to half of the values proposed in the original method. The analyses were performed in triplicate for each distilling time x sample mass binomial, making a total of 12 tests, which were performed on the same day. The significance of the effects of the different distillation times and sample mass were evaluated by applying one-factor analysis of variance (ANOVA). For a 95% confidence limit, it was found that the proposed amendments to the distillation time, sample mass, and the interaction between distilling time x sample mass were not significant (p > 0.05) in determining the SO2 content in passion fruit juice. In view of the results that were obtained it was concluded that for integral passion fruit juice it was possible to reduce the distillation time and the sample mass in determining the SO2 content by the Monier-Williams method without affecting the result.

How Is Credit Risk Estimated? Discussion and Evidence based on Cross-Industry Sample Utilizing the KMV Model

The purpose of this thesis is to focus on credit risk estimation. Different credit risk estimation methods and characteristics of credit risk are discussed. The study is twofold, including an interview of a credit risk specialist and a quantitative section. Quantitative section applies the KMV model to estimate credit risk of 12 sample companies from three different industries: automobile, banking and financial sector and technology. Timeframe of the estimation is one year. On the basis of the KMV model and the interview, implications for analysis of credit risk are discussed. The KMV model yields consistent results with the existing credit ratings. However, banking and financial sector requires calibration of the model due to high leverage of the industry. Credit risk is considerably driven by leverage, value and volatility of assets. Credit risk models produce useful information on credit worthiness of a business. Yet, quantitative models often require qualitative support in the decision-making situation.

Sample preparation and heavy metal determination by atomic spectrometry /

Microwave digestions of mercury in Standards Reference Material (SRM) coal samples with nitric acid and hydrogen peroxide in quartz vessels were compared with Teflon® vessel digestion by using flow injection cold vapor atomic absorption spectrometry. Teflon® vessels gave poor reproducibiUty and tended to deliver high values, while the digestion results from quartz vessel show good agreement with certificate values and better standard deviations. Trace level elements (Ag, Ba, Cd, Cr, Co, Cu, Fe, Mg, Mn, Mo, Pb, Sn, Ti, V and Zn) in used oil and residual oil samples were determined by inductively coupled plasma-optical emission spectrometry. Different microwave digestion programs were developed for each sample and most of the results are in good agreement with certified values. The disagreement with values for Ag was due to the precipitation of Ag in sample; while Sn, V and Zn values had good recoveries from the spike test, which suggests that these certified values might need to be reconsidered. Gold, silver, copper, cadmium, cobalt, nickel and zinc were determined by continuous hydride generation inductively coupled plasma-optical emission spectrometry. The performance of two sample introduction systems: MSIS™ and gas-liquid separator were compared. Under the respective optimum conditions, MSIS^"^ showed better sensitivity and lower detection limits for Ag, Cd, Cu, Co and similar values for Au, Ni and Zn to those for the gas-liquid separator.

The micromorphology of Paleoseismic soft sediment deformation structures in glacial deposits from three sample sites in Scotland /

The nature of this research is to investigate paleoseismic deformation of glacial soft sediments from three sampling sites throughout the Scottish Highlands; Arrat's Mills, Meikleour and Glen Roy. The paleoseismic evidence investigated in this research will provide a basis for applying criteria to soft sediment deformation structures, and the trigger mechanisms that create these structures. Micromorphology is the tool used in this to investigate paleoseismic deformation structures in thin section. Thin section analysis, (micromorphology) of glacial sediments from the three sampling sites is used to determine microscale evidence of past earthquakes that can be correlated to modem-day events and possibly lead to a better understanding of the impact of earthquakes throughout a range of sediment types. The significance of the three sampling locations is their proximity to two major active fault zones that cross Scotland. The fault zones are the Highland Boundary Fault and the Great Glen Fault, these two major faults that parallel each other and divide the country in half Sims (1975) used a set of seven criteria that identified soft sediment deformation structures created by a magnitude six earthquake in Cahfomia. Using criteria set forth by Sims (1975), the paleoseismic evidence can be correlated to the magnitude of the deformation structures found in the glacial sediments. This research determined that the microstructures at Arrat's Mill, Meikleour and Glen Roy are consistent with a seismically induced origin. It has also been demonstrated that, even without the presence of macrostructures, the use of micromorphology techniques in detecting such activity within sediments is of immense value.

Effects of sample solvent composition and injection volume on chromatographic peak profiles of methyl w- benzimidazolecarbamate and 3-butyl1-2,4-dioxo[1,2-a]-s- triazinobenzimidazole in RP-HPLC

The effects of sample solvent composition and the injection volume, on the chromatographic peak profiles of two carbamate derivatives, methyl 2-benzimidazolecarbamate (MBC) and 3-butyl-2,4-dioxo[1,2-a]-s-triazinobenzimidazole (STB), were studied using reverse phase high performance liquid chromatograph. The study examined the effects of acetonitrile percentage in the sample solvent from 5 to 50%, effects of methanol percentage from 5 to 50%, effects of pH increase from 4.42 to 9.10, and effect of increasing buffer concentration from ° to 0.12M. The effects were studied at constant and increasing injection mass and at four injection volumes of 10, 50, 100 and 200 uL. The study demonstrated that the amount and the type of the organic solvents, the pH, and the buffer strength of the sample solution can have a pronounced effect on the peak heights, peak widths, and retention times of compounds analysed. MBC, which is capable of intramolecular hydrogen bonding and has no tendency to ionize, showed a predictable increase .in band broadening and a decrease in retention times at higher eluting strengths of the sample solvent. STB, which has a tendency to ionize or to strongly interact with the sample solvent, was influenced in various ways by the changes in ths sample solvent composition. The sample solvent effects became more pronounced as the injection volume increased and as the percentage of organic solvent in the sample solution became greater. The peak height increases for STB at increasing buffer concentrations became much more pronounced at higher analyte concentrations. It was shown that the widely accepted procedure of dissolving samples in the mobile phase does not yield the most efficient chromatograms. For that reason samples should be dissolved in the solutions with higher aqueous content than that of the mobile phase whenever possible. The results strongly recommend that all the samples and standards, regardless whether the standards are external or internal, be analysed at a constant sample composition and a constant injection volume.